Chapter 6: Changes in the cryosphere

Chapter description

This chapter describes past conditions and future climate change in Canada for snow on land, sea ice, lake and river ice, glaciers, seasonally frozen ground, and permafrost, collectively referred to as the cryosphere.

Chapter key messages

Plain language summary^{Footnote 1}

In this chapter, we describe and assess past and future changes in six important components of the Canadian cryosphere: snow, sea ice, freshwater ice on lakes and rivers, glaciers, seasonally frozen ground, and permafrost. Among these six components of the cryosphere, we see similar, interconnected changes in both what has been observed in the past and what we expect for the future. It is not surprising that these changes share similarities, since these components are all shaped by frozen water in the physical climate system, all of which is responding to human-caused climate change. The changes occurring in the cryosphere will not only affect the physical climate system but also have implications for Canada’s ecosystems, infrastructure, and water resources, and for the health, well-being, and everyday lives of Canadians and people living in Canada.

Our assessment in this chapter reveals that over the past four to five decades, the portion of Canadian land and sea covered by snow and ice has decreased and the upper ground layer has been frozen for less of the year. Glaciers in Canada have thinned and retreated, while permafrost has warmed and lost ice. These changes in the Canadian cryosphere are consistent with changes observed in other cold regions globally.

The past changes in the individual components of the cryosphere summarized below are largely a response to rising global average temperatures driven by human-caused emissions of greenhouse gases. Beyond the overall warming trend, there is also some regional and seasonal variation due to natural variability in surface temperature, precipitation, and large-scale weather patterns. However, in the coming decades, further increases in global average temperature are expected to intensify the climate-driven changes in the cryosphere under all future emissions scenarios.

Across the Northern Hemisphere, seasonal snow has decreased in its overall coverage, duration, and amount over the past four decades. This is also true for Canada as a whole, but there are regional deviations from those overall trends. For example, some parts of central Canada have experienced larger peak snowpack amounts and more days with snow cover. These increases are expected to be temporary, as climate models project fewer days of snow cover across the entire country with continued warming. Peak annual snowpack amounts are also projected to decrease across most of Canada with further warming, except for the eastern and central Canadian Arctic, where models project modest increases. In mountainous regions across the country, peak annual snowpack amounts are projected to decrease with continued warming while the fraction of snowpack that melts during winter is projected to increase, leading to changes in the timing and reductions in the predictability of water resources.

Sea ice cover across the Canadian Arctic has measurably declined in both summer and winter over the past five decades. As these declines have occurred, the multi-year sea ice that once dominated the Canadian Arctic has been replaced in many places by thinner seasonal sea ice that melts away during summer and must form again during winter. Landfast ice, a type of sea ice that forms close to the shoreline, has also declined. This type of sea ice is vital for wildlife habitat and is important for the harvest cycle of northern communities. With further rises in global average temperature, the sea ice–free period is projected to lengthen further in waters across the Canadian Arctic and Hudson Bay region, increasing by about one month for each additional degree of warming. Even though the ice-free period will lengthen across the Canadian Arctic, the shipping season through the Northwest Passage is not expected to lengthen by the same amount because of the continued flow of multi-year ice into the region from farther north.

The annual duration of ice cover on Canadian lakes has shortened for Canada as a whole over the past four decades. There have also been increases in the number of mid-winter break-up events on Canadian rivers. Such events have the potential to cause flooding and other river-related damage. In the future, the annual number of days with ice cover on Canadian lakes and rivers is expected to decline by at least 1 to 2 weeks for each 1°C rise in global average temperature. For parts of southern Canada and for most coastal regions even larger declines up to 4 weeks for each 1°C rise in global average temperature are expected. It is uncertain how the severity of river ice break-up events or ice jam–related flooding will change across Canada in the future because such events are very complex to model and need to account for many river-specific characteristics.

Glaciers across Canada have thinned and lost mass, and there is evidence that the rate of loss has accelerated in recent decades. The loss of glacier mass is projected to continue throughout the rest of the 21st century under all emissions scenarios, but losses will be larger with increased warming, and much of the glacier melt will contribute to global sea level rise. Glaciers in Canada would require hundreds of years to regrow even if the climate cooled, which makes these declines in mass effectively irreversible as well as their implications for freshwater availability in western and Arctic Canada. The continued loss of glacier ice is also expected to lead to an increase in hazardous events such as floods and landslides that can be initiated by melt of or sudden collapse of glacier ice.

For Canada as a whole, there has been a decline in the number of days each year when the upper ground layer is frozen. Further declines are expected to continue until at least mid-century. Whether these declines will stabilize or continue after mid-century depends on the total amount of greenhouse gases that humans emit globally over the coming decades.

Permafrost has warmed since the 1980s and lost some of its ice, according to ground temperature monitoring and changes in active-layer thickness. Additional evidence of thaw also comes from tracking landscape changes caused by melting of ground ice. With future climate warming, both permafrost warming and thaw-driven landscape changes will continue.

6.1: Introduction

The cryosphere is an umbrella term for the parts of the Earth’s surface where water is frozen. The cryosphere includes snow, sea ice, ice on lakes or rivers, glaciers, ice caps, ice sheets, seasonally frozen ground, and permafrost. The components of the cryosphere have effects both locally where they exist and, in many cases, globally given how they interact with the climate and with ecological systems, and how they are used by humans both as natural resources and in connection with livelihoods.

Since water can freeze only when temperatures are below 0°C, the components of the cryosphere are most abundant closer to the Earth’s poles (the Arctic and Antarctic) and at higher elevations (high mountain and plateau regions). Their occurrence, coverage, and amount can vary with the seasons. Given its northern location, Canada is one of the few countries with especially extensive coverage of all the components of the cryosphere (Figure 6.2). This gives Canada an important role in the stewardship of these resources, and responsibility to help to preserve them. Increasingly, the government of Canada seeks to collaborate on stewardship with the First Nations, Inuit, and Métis who make their homes across the same land and ocean, and whose ways of life are interwoven with snow, ice, and frozen ground.

Figure take-away: A visual snapshot of the contents of this chapter and of important cross-chapter linkages.

Figure title: Visual guide to the content of Chapter 6 and key cross-chapter linkages (no period at the end)

Figure 6.1: Visual guide to Chapter 6 content and cross-chapter linkages.

Figure take-away: Canada is one of the few countries with especially extensive coverage of all components of the cryosphere.

Figure title: Components of the cryosphere across Canada and surrounding regions

Figure 6.2: Map with colours showing coverage of various components of the cryosphere across Canada and surrounding regions. Cyan shading shows the minimum and maximum annual extent of sea ice over the last 25 years and the approximate location of the Last Ice Area, the region of the Arctic where perennial sea ice is expected to survive the longest. Purple shading shows the areas of continuous and discontinuous permafrost, regions partially to completely underlain by ground that is always frozen. Blue shading shows the typical number of days in a year that the ground surface is frozen. The number of days that the ground surface freezes can easily exceed 90, but for clarity, only three contours are shown. Lakes and rivers in the blue and purple regions will also freeze, but the timing and duration may differ from freezing of the ground surface. The maximum extent of snow cover in a typical year is shown by the white region. Glaciers, ice caps, and the Greenland ice sheet are shown in black.

The cryosphere acts as an important regulator of the Earth’s climate. For example, snow and sea ice cover are key components of the surface albedo feedback, since decreases in surface brightness from snow and ice melt lead to additional warming. Through this albedo feedback, past decreases in snow and ice cover have been a key driver of Arctic amplification (Chapter 4, section 4.2). This feedback helps explain why Canada and other northern countries are warming faster than the global average. Further feedbacks come from the cryosphere’s influence on clouds, the water and carbon cycles, heat and moisture exchange between the surface and the atmosphere, and atmospheric and oceanic circulation.

The cryosphere also serves important ecosystem functions, as many organisms have adapted to living in or on frozen ground, snow, and ice. These adaptations exist across the entire food web, from distinctive microbial and fungal communities to seals and polar bears, which rely on sea ice for breeding, feeding, and mobility. Ice cover influences the algal growing season, water temperature, and oxygen levels, and it allows wildlife to cross bodies of water and reach shorelines. Many landscapes are influenced by the cryosphere, and when it changes, existing hazards may intensify, or new ones may form. For example, declining sea ice and thawing permafrost contribute to high rates of coastal erosion, and retrogressive thaw slumps (a type of landslide triggered by melting permafrost) threaten roads and transform downstream aquatic ecosystems when they occur near bodies of water.

Canada’s economy has developed to rely on components of the cryosphere as natural resources. During the cold season, snow and glaciers store freshwater, which is then released upon melt during the spring and summer. This freshwater melt is an essential component of municipal, industrial, and agricultural water supply across the country. Across parts of northern Canada, the presence and thickness of sea ice determine the mode of travel or transportation used, for example, by snowmobile or other vehicles on top of the sea ice, or by boat or ship through open water. Winter roads, which make it possible to resupply remote regions with essential goods, require snow for construction and lake ice that is thick enough for safe travel over water (Box 6.4). Both ocean and land routes are used by people to transport goods or to travel for a range of activities, from resource extraction to recreation. Permafrost was used historically as waste containment at sites across northern Canada. However, climate change is altering the stability of permafrost soils and rock, and many of these waste containment sites are now at risk of releasing their hazardous contents.

The cryosphere is also important to the traditional ways of life of many First Nations, Inuit, and Métis communities. For example, snow can be used as a predictor of animal behaviour, and both glaciers and permanent snow regions form micro-habitats, which can house cultural keystone species (McDowell et al., 2023). Snow and lake ice make it easier to travel across land, while safe and dependable access to sea ice ensures that these communities can continue to hunt and harvest Arctic wildlife during winter (Inuit Circumpolar Council Canada, 2008). In many northern communities, permafrost provides a stable base for infrastructure, so permafrost thaw has implications for community buildings and housing, in addition to further impacting travel and wildlife harvesting (Firelight Research Inc, 2022). For the Inuit across the coastal north, the cryosphere is fundamental: the Arctic’s cold temperatures and ice are essential to their transportation, safety, health, and education (Climate Atlas of Canada, 2022). As climate change alters these once dependable elements, First Nations, Inuit, and Métis across the country are disproportionately affected. For example, Paul Emingak offers an Inuk’s observations of climate change and its consequences for the northern community of Iqaluktuuttiaq, also known as Cambridge Bay (Case Story 6.1). Case stories and other information referenced throughout this chapter (case stories 6.1, 6.2, 6.3, Box 6.4) not only highlight the challenges that First Nations, Inuit, and Métis living in Canada are facing, but also try to make clear some of the ways in which their communities are adapting in response to these challenges.

This chapter also provides information from a Western science perspective on observations of and expectations for changes in the cryosphere both globally and in Canada. Information on these changes is provided by component of the cryosphere, namely, terrestrial snow (section 6.2), sea ice (section 6.3), lake and river ice (section 6.4), glaciers (section 6.5), seasonally frozen ground (section 6.6), and permafrost (section 6.7). This chapter also touches on a range of cryospheric hazards, from flooding to landscape instabilities, such as mudslides driven by glacier melt and ground collapse driven by permafrost thaw. Generally, these hazards are expected to worsen with climate change. Additional information on framing cryospheric changes as climate hazards is provided in Chapter 10, section 10.4.

6.2: Terrestrial snow

Key message 6.1: Snow cover duration has shortened in Canada as a whole over the past four decades (high confidence^{Footnote 2}). Snow cover duration has shortened in northern Canada, southern Ontario, and parts of eastern Canada by one to four weeks, while snow cover duration has lengthened across central Canada by one to four weeks (medium confidence). This regional variability is also reflected in changes in peak snowpack amounts over the past four decades (high confidence).

Key message 6.2: Snow cover duration is projected to shorten across all of Canada and peak snowpack amounts are projected to decrease across most of Canada with increasing climate warming (very high confidence). Unlike the rest of Canada, the western and central parts of northern Canada are projected to experience larger peak snowpack amounts due to increased snowfall despite a shorter projected snow season (medium confidence).

Key message 6.3: Past amounts and changes in snowpack are more uncertain for mountainous regions than elsewhere (high confidence). In a warmer climate, mountainous regions in Canada are expected to have less snowpack accumulation and experience more mid-winter melt events, changing the timing and reducing the predictability of Canadian water resources (high confidence).

Snow interacts with its environment and the Earth system in two important ways. First, snow is a key component of the surface albedo feedback: when present on the ground, snow reflects large amounts of sunlight back into the atmosphere, but when snow cover is reduced, more light is absorbed by the ground and turned into heat, causing increased warming. This feedback mechanism contributes to Arctic amplification (Chapter 4, section 4.2) and is part of the reason why Canada is warming at a faster rate than the global average. Understanding how the surface albedo feedback will amplify warming requires knowledge of where and when snow cover on the Earth’s surface is changing. Such changes can be examined using the following two indicators:

1. snow cover extent (the total area covered by snow across a particular region)
2. snow cover duration (the length of time that a given location is covered by snow)

A second important role of snow is in seasonal storage of freshwater. Understanding changes in the amount and timing of freshwater due to climate change requires knowledge of changes in the amount of snow on the ground. Such changes can be examined using the following two indicators:

1. the mass of snow across a particular region
2. snow water equivalent (the amount of snow at a given location, represented as the snowpack’s equivalent height in liquid water)

Note that while snow depth also provides a measure of snow quantity, it does not account for the density of the snowpack, which can vary substantially from one place to another and over the snow season. Therefore, the same snow depth could contain very different amounts of stored water. A high-density snowpack can contribute 3 to 10 times as much water into the water cycle as a low-density snowpack of the same height.

Beyond these two key roles, snow interacts with other cryospheric and Earth system components. Snowpack insulates the surface below it from the atmosphere above it, affecting heat exchange between the two layers. When snowpack is present on the surface of ice (whether sea ice, lake ice, or river ice), this insulation process affects the rate of ice growth and melt (sections 6.3 and 6.4). For snowpack on land, the same process affects soil temperature and permafrost processes (sections 6.6 and 6.7). Snow also requires substantial energy to melt, which delays energy input into the surface layers underneath during spring (slowing the seasonal transition between winter and summer). Along with temperature conditions, the amount of snowfall determines annual glacier mass balance (section 6.5). Changes in the amount of snowpack and the timing of its melt affect all downstream components of the water cycle: surface runoff, soil moisture, and groundwater recharge, as well as the strength and timing of waterflow in streams and rivers (Chapter 5). Snow also influences numerous biological and ecological interactions, which, although important, will not be covered thoroughly in this report (for example, H. G. Jones et al., 2011; Meredith et al., 2019).

The focus of this section is terrestrial snow, defined as all snow that accumulates and remains over land either on or near the ground. This definition includes the snowpack on the land surface and snow suspended in vegetation (such as on the leaves and branches of trees and shrubs), which wind may dislodge to the surface or which, upon melting or sublimating, will re-enter the water cycle. It excludes snow over the ocean surface, which either melts in open water or forms snowpack over sea ice (which can affect sea ice growth and melt, although there are very limited observations of this, as discussed in section 6.3.4). The influence of snow over lake and river ice and of snow over glaciers are discussed separately in sections 6.4 and 6.5, respectively. Finally, the following sections contain a separate assessment of past and future changes to snow in mountainous regions. The distinction between mountainous and non-mountainous regions is made because more snow accumulates in mountainous regions, and this seasonal accumulation forms an important part of Canada’s freshwater resources. Despite the importance of snow accumulation, there are differing levels of confidence in its changes across non-mountainous and mountainous regions, which stem from both reduced observational coverage and lower ability to simulate snow in such regions.

6.2.1: Past changes

Across the Northern Hemisphere, both the extent and mass of snow in each month between September and June significantly decreased from 1981 to the near present, according to a study by Mudryk et al. (2020). The trends considered in that study and those presented below integrate information from multiple sources, including surface observations, multiple types of satellite observations, and datasets of simulated snow based on historical weather conditions (see Box 6.1 for a description of different sources of information on snow cover and amount of snow). The use of multiple datasets to establish past trends in snow cover extent and mass (Gottlieb and Mankin, 2024; Mudryk et al., 2017; Räisänen, 2023; Thackeray et al., 2016) is a shift from the use of single snow cover datasets typical of studies from a decade or more ago. This shift represents a way of dealing with large uncertainties in historical snow estimates, since when independent datasets agree in their values, combining information from them improves confidence in the resulting trends. For example, past declines in hemispheric snow cover extent during the early part of the snow season (September–December) had previously been debated for more than a decade (Box 6.2) related to the long-standing reliance on a single source for estimating past snow cover extent trends. The consideration of multiple datasets demonstrated that anomalous behavior was a characteristic limited to that single data source, and that the remaining estimates were in better agreement with one another and with expectations of past change in a warming climate.

Compared to the consistently strong declines in snow cover extent and snow mass in the Northern Hemisphere, changes in the presence and amount of snow across Canada over the past four decades vary more (Figure 6.3). These trends are based on multiple sources analogous to the analysis by. Mudryk et al. (2020) but updated to include the most current generation of available datasets shown to have good agreement with ground observations and one another (Mudryk et al., 2025). Snow cover duration shortened from 1979 to 2023 in broad regions of the country, especially across northern Canada (including northern Quebec), southern Ontario, and parts of eastern Canada. However, snow cover duration lengthened in parts of central Canada, especially across the Prairies and eastern British Columbia. Snow cover duration for Canada as a whole was approximately 0.8 days shorter per decade over the period from 1979 to 2023 (Figure 6.4). Changes in peak snowpack amount (measured by snow water equivalent) vary across the country when tracked over the same period (Figure 6.3). These regional signals in both snow cover duration and snow water equivalent are corroborated by other studies based on site-specific observations (R. D. Brown, Smith, et al., 2021), satellite sensors augmented by machine-learning (Notarnicola, 2022), and changes in snowmelt timing and snow water equivalent from passive-microwave observations (Anttila et al., 2018; Pulliainen et al., 2020).

Figure take-away: Past changes in snow cover duration and peak snowpack amount differ by location across Canada.

Figure title: Changes in snow cover duration and peak snowpack amount in Canada from 1979 to 2023

Figure 6.3: Maps with colours showing changes in snow cover duration (left) and peak snowpack amount (right, measured by snow water equivalent [SWE]) across Canada from 1979 to 2023. Dots represent statistical significance at the 5% level (there is ≤ a 5% chance of concluding that an effect or trend exists when it does not). Data source: updated from Mudryk et al. (2020) using SWE from MERRA2 (Global Modeling and Assimilation Office, 2015); ERA5-Land (Muñoz Sabater, 2019); SnowCCIv3.1 (Luojus et al., 2024); Crocus-ERA5 (Decharme et al., 2024) and snow cover extent records from NOAA (Robinson et al., 2012) and Rutgers (Robinson and Estilow, 2021).

Figure take-away: The number of days with snow cover decreased for Canada as a whole from 1979 to 2023.

Figure title: Changes in snow cover duration for Canada as a whole from 1979 to 2023

Figure 6.4: Annual deviation in the number of days with snow cover in Canada as a whole from 1979 to 2023. Blue bars indicate years that had more days with snow cover than the average, while red bars indicate years that had fewer days with snow cover than the average. The black dashed line depicts the overall trend. Data source: as in Figure 6.3.

6.2.2: Causes of past changes

Air temperature and precipitation are the main influences on where and when snow is present and how much snow there is (Mudryk et al., 2017; Räisänen, 2023; Sospedra-Alfonso and Merryfield, 2017). With climate change, near-surface air temperature has already risen (Chapter 2, section 2.4), and it is virtually certain to rise further (Chapter 3, section 3.4). Likewise, precipitation is already increasing in some regions (Chapter 2, section 2.5), and further increases are expected over most of Canada (Chapter 3, section 3.5). The effects of higher temperatures and more precipitation can counteract each other, especially with regard to snow accumulation. Where and when temperatures remain below zero, more precipitation will mean more snowfall, increasing snow accumulation, and therefore higher peak snowpack amounts. Where and when temperatures rise above zero, more precipitation will reduce peak snowpack amounts by reducing the proportion of annual precipitation that occurs as snowfall (meaning more precipitation will occur as rain), and by directly melting snowpack.

Changes in precipitation and temperature can be caused by more than climate change. Internal climate variability (Chapter 3, section 3.3.3) results in fluctuations of precipitation and temperature. These fluctuations can temporarily outweigh the expected climate signals and thus mask their effects (for an example demonstrating the influence of internal variability on snow water equivalent trends, see Siler et al., 2019). This masking effect from internal climate variability is larger over smaller regions and shorter time periods, so the clearest signals of human-caused climate change come from hemispheric or global studies over long periods.

The influence of internal climate variability also means that attributing past changes in the coverage or amount of snow to human-caused carbon emissions is easier (results will have higher statistical confidence) on larger scales and with longer records. On the hemispheric scale, human-caused greenhouse gas emissions were shown to be the primary cause of declines in both spring snow cover extent and peak annual snow mass in the Northern Hemisphere (Gottlieb and Mankin, 2024; Najafi et al., 2016; Paik and Min, 2020). The success of these studies in attributing past changes in snow cover extent and mass to human influence is consistent with the long-established attribution of global temperature rise to human-caused carbon emissions and the strong response of snow presence and snowpack amount to temperature. Although temperature and precipitation are the key drivers of snow cover and snowpack change and variability, especially on the hemispheric scale, other factors can be more important locally (Thackeray et al., 2019). These factors include the type and density of vegetation, which can trap snow (Bokhorst et al., 2016) and alter the surface albedo (Loranty et al., 2014), the presence of impurities in the snow such as dust and black carbon that absorb light thereby affecting melt rates (Gleason et al., 2019; Skiles et al., 2018), and wind-driven processes that affect the pattern of snow accumulation (Mott et al., 2018).

6.2.3: Future changes

Multiple generations of climate models have projected decreases in snow cover extent and snow mass in the Northern Hemisphere over the 21st century under all emissions scenarios (Diffenbaugh et al., 2013; Mudryk et al., 2020; Räisänen, 2008; Thackeray et al., 2016; Zhu et al., 2021). Scientists assess the reliability of these models’ projections in part by how closely their simulations of past conditions match observations (see Chapter 3, section 3.3 for a discussion). On average, the most recent generation of climate models (Phase 6 of the Coupled Model Intercomparison Project, CMIP6) better represent the climatology of past snow cover extent compared to the previous generation (Phase 5 of the Coupled Model Intercomparison Project, CMIP5), which typically simulated lower values (Mudryk et al., 2020). Scientists also have higher confidence in the ability of climate models to simulate trends in past snow cover extent during fall. This higher confidence is not because of changes in the simulated trends but because those simulated trends were compared to a broader selection of past trend estimates. This comparison revealed that the simulated trends were consistent with all but one historical source of data that had previously been relied upon to evaluate the simulations (Box 6.2) (Mudryk et al., 2020). Despite these improvements in simulated snow cover extent, the recent models still simulate too broad a range of values for snow albedo feedback (Thackeray et al., 2021). The models also simulate too much total snow mass across the Northern Hemisphere (Mudryk et al., 2020), because they simulate too much snowfall (Kouki et al., 2022).

Because snow cover duration and snow mass are both influenced by temperature, how snow will change both in the near term (2021 to 2040) and for the remainder of the 21st century will depend primarily on future levels of global warming over those periods. For the Northern Hemisphere as a whole, each 1°C rise in global average temperature will result in proportionally less snow cover (Mudryk et al., 2020). Regionally, the projected losses in snow cover are greater across mid-latitudes of the Northern Hemisphere as compared with Arctic or mountainous regions (Mudryk et al., 2017). For peak snowpack amount (or the snow mass across a region), precipitation will also play a role, but for much of Canada, temperature is a more important influence (Sospedra-Alfonso and Merryfield, 2017). For Canada, snow cover duration is projected to shorten across the entire country in proportion to the rise in global average temperature (Figure 6.5). The ensemble of climate models projects that most parts of the country will lose one to two weeks of seasonal snow cover for each 1°C rise in global average temperature. Parts of Ontario, Quebec, and eastern Canada are projected to lose more than two weeks, and coastal British Columbia is projected to lose more than three weeks for each 1°C rise in global average temperature. Compared to changes in snow cover duration, projected changes in peak snowpack amount vary more across the country in both strength and sign. There is greater regional variability because local changes in the amount of snow depend on the interplay between increasing precipitation and rising surface air temperature. For all the Canadian provinces except the northern part of Quebec, models consistently project relative decreases in peak snowpack amounts, with the largest decreases in the most southern and coastal regions (Figure 6.5). However, across some northern parts of Canada, a combination of more winter precipitation and winter temperatures that remain below freezing (even with climate warming) are expected to lead to overall increases in peak snowpack, despite an overall shorter snow season. While the models show less agreement across northern Canada compared to southern Canada, they all project increased peak snowpack for some portion of the North. Their disagreement stems from differences in where each model projects the dividing line between decreases and increases in peak snowpack amounts in Canada. This inter-model spread in the range of projections may result from how each model represents different physical processes that affect snowfall (McCrystall et al., 2021; Zhong et al., 2022) and represents a source of uncertainty in the projections.

Figure take-away: Snow cover duration is projected to shorten across Canada, whereas peak snowpack amount is projected to decrease for most of Canada but increase for northernmost regions.

Figure title: Future changes in snow cover duration and peak snowpack amount across Canada per global warming level

Figure 6.5: Maps with colours showing projected changes in snow cover duration (left) and peak snowpack amount (right, as measured by snow water equivalent) across Canada for each 1°C increase in global warming level. Colours show the ensemble median change. Dots shows where 90% of the models agree on whether the change is positive or negative. The warming levels are calculated relative to the average for 1850 to 1900. Data source: snow cover fraction and snow water equivalent output from 15 CMIP6 models.

6.2.4: Past and future changes in mountainous regions

Mountainous regions represent a key Canadian water resource because they act as natural reservoirs. During winter, these high elevation regions build up snow. Then, during spring and summer, the accumulated snowpack melts and provides important contributions to the water levels of many rivers and lakes across the country (Chapter 5). As important as this resource is, past and future changes in snowpack are more uncertain for mountainous regions than elsewhere (see below and section 6.2.5).  

Patterns of snow distribution across mountainous regions can be particularly complex and vary over much smaller scales than typically seen outside mountainous regions (Baba et al., 2019; Blöschl, 1999). This complexity is due to the number of processes that can affect snowpack in mountainous regions. For example, snow accumulation and melt can be altered by elevation (higher elevations are colder), terrain steepness, exposure to sun or shade, sky conditions (cloudiness), presence or absence of vegetation that can trap snow, and local wind and precipitation patterns (Clark et al., 2011). As the snow season progresses, the effects of wind and avalanching will redistribute snow, resulting in seasonally evolving patterns of deep versus shallow snowpack that affect the timing and duration of melt during spring (DeBeer & Pomeroy, 2009; Marsh et al., 2024). These individual processes can act independently, but they can also chain together in complex ways (Marsh et al., 2024; Mott et al., 2018; Vionnet et al., 2021). Although climate change does not affect physical mountain characteristics such as steepness or exposure to sun and shade, it can alter many of the other components such as local wind conditions, the height and distribution of vegetation, precipitation amounts, and the elevation at which precipitation falls as snow. How climate-driven changes in these individual processes will combine to affect the pattern and evolution of seasonal snowpack is still an open question, and one which limits how precisely scientists can estimate changes in the timing and magnitude of spring and summer water availability (see also Chapter 5).

Overall, there are more limited types and quantities of data available for mountainous regions, which makes it difficult to characterize past changes in snowpack compared to non-mountainous regions (section 6.2.5). In place of direct snowpack measurements, past changes in amounts of snow can sometimes be inferred from past changes in temperature or precipitation, which are more broadly available for mountainous regions. In some cases, they can also be inferred from streamflow changes in rivers that are supplied by mountain snowmelt, albeit with additional uncertainty.

The estimated changes in past snow cover and snowpack from a range of sources (direct snowpack measurements, satellite data, and reanalysis) generally show shorter snow cover duration and lower snowpack amounts across North American mountain ranges (Figure 6.3) (R. D. Brown, Smith, et al., 2021; Kunkel et al., 2016; Mote et al., 2018; Notarnicola, 2022; Räisänen, 2023). An exception is the Canadian Rockies, which instead show increasing snow cover and peak snowpack over the past four to five decades. The overall decreases in the remaining regions are consistent with the strong influence of air temperature on snow and a projected shift toward a greater proportion of precipitation falling in the form of rain (Mankin & Diffenbaugh, 2015). Additional evidence for an increase in the proportion of precipitation occurring as rain can be found in mountainous regions outside of North America where trends in decreasing snow accumulation are stronger and more statistically significant during transitional seasons and below transitional altitudes (Bozzoli et al., 2024; Hock et al., 2019). In North America, there is also evidence for earlier timing of peak snow water equivalent and earlier snowmelt with corresponding changes in streamflow across the continental United States and parts of Canada  (Clow, 2010; Dudley et al., 2017; Elias et al., 2021; Whitfield et al., 2021). Although snow measurements over most Canadian mountains are limited, we know that annual average air temperature rose across all Canadian mountain ranges from 1950 to 2020, particularly during winter across the maritime ranges of westernmost British Columbia and the interior ranges of northern British Columbia and southern Yukon (see Table 5.1 in McDowell et al., 2023). 

In a warmer climate, peak snowpack amounts are projected to decrease for most North American locations (Shrestha et al., 2021), and snow losses are projected to depend greatly on elevation, location, and season (Mortezapour et al., 2022; Rasouli et al., 2022; Sobie & Murdock, 2022; Sospedra-Alfonso et al., 2015). The largest relative losses are expected during the shoulder seasons and below 2000 m, with projected decreases of 40 to 60% by the end of the century under a very high emissions scenario (RCP8.5) (Mortezapour et al., 2022). Although less snow will be lost at higher elevations, the frequency of mid-winter snowmelt events is expected to increase in such regions because of more frequent mid-winter warm spells (Scaff et al., 2024) and rain-on-snow events (Musselman et al., 2018). These changes will alter the timing and rate of seasonal snowmelt (Musselman et al., 2017), with follow-on implications for the timing and predictability of water resources (see also Chapter 5) (Dibike et al., 2018; Dibike, Shrestha, et al., 2021; Wieder et al., 2022). Increased occurrence of rainfall on mountain snow during spring is also expected to increase the chance of large floods for parts of Canada (Chapter 5, section 5.7) (Brandt et al., 2022; Cho et al., 2021; Jiang et al., 2020; Vionnet et al., 2020).

6.2.5: Knowledge gaps

1) Estimates of past snow mass are more uncertain than those of past snow cover extent.
Site-specific measurements of snowpack amount (including depth of snow, snow density, and snow water equivalent) are under-sampled in both time and space, which limits how well the observations track total snow mass over large regions. Although snow water equivalent can also be estimated from passive-microwave data collected by satellite, these estimates are sensitive to snowpack structure, and their accuracy can be affected by the presence of wet snow or ice layers as well as interference from the presence of trees and large plants (Sandells et al., 2022). Snow water equivalent estimates are also limited in resolution compared to estimates of snow presence available from visible-light sensors. These limitations lead to higher uncertainty in satellite-based observations of snowpack amounts and increased reliance on simulated datasets (for example, reanalysis data) to estimate past changes. Despite these limitations, recent work has both narrowed the spread and better assessed the accuracy of different methods of estimating snow mass (Mortimer et al., 2024; Mudryk et al., 2025; Pulliainen et al., 2020) across non-mountainous regions in the Northern Hemisphere.

2) Estimates of past and future changes in snow are more uncertain for mountainous regions than elsewhere.
Site-specific observations in the mountains are sparse in space and time compared to elsewhere (DeBeer et al., 2021; Vionnet et al., 2021). Observations from high-elevation mountainous regions are particularly sparse because of the difficulty and risk associated with site access and poor instrument reliability under harsh conditions. As a result, high elevation sites are under-sampled compared to what is needed for effective model validation (DeBeer et al., 2021; Fang et al., 2019). The limitations of passive-microwave sensors discussed in the first knowledge gap result in such poor accuracy that measurements of snow mass are rarely even attempted in mountainous regions (Bormann et al., 2018). The coarse resolution of other types of gridded data that are typically available (reanalysis data or snow models) also limits how precisely changes in snowpack amount can be assessed or linked to elevation and elevation-dependent temperature changes (see Box 2.1 in Hock et al., 2019 for an assessment of potential feedbacks between warming and elevation in mountain regions). Overall, uncertainty about past snow mass is estimated to be two to three times greater for mountainous regions than non-mountainous regions (see Figure 2 from Mudryk et al., 2025; Wrzesien et al., 2018).

Projected changes are also more uncertain for mountainous regions than elsewhere. To model snow in mountainous regions, complex chains of processes that can often be neglected elsewhere, must be considered (section 6.2.4). In addition, model resolution is a source of uncertainty because it affects the simulated estimates of both past and future amounts of snow. For past changes in snow, reanalysis data with finer resolution or models that simulate many layers of snow better match available observations of mountain snow (Marsh et al., 2024; Mudryk et al., 2025; Tesemma et al., 2024). For future changes in snowpack, resolution can affect the amount of projected snowpack loss. For example, as spatial resolution becomes finer, higher-elevation locations (which experience less snow loss) are better represented, which lessens the total snowpack loss compared to coarser resolution models (McCrary et al., 2022). Finer temporal resolution can affect how transitional processes are represented (for example, the amount of melt during rain-on-snow events). This uncertainty about past and future mountain snowpack compounds the uncertainty in projections of water supply (Chapter 5).

3) There is a limited number of studies that project changes in mountain snow across Canada.
Many regional studies project changes in mountain snowpack for the European Alps, the Andes in South America, or the Pacific Coast and Rocky Mountain ranges of the western United States. However, a comparatively small number of regional studies make such projections for Canada. Additional warming is expected to reduce peak mountain snowpack and increase the fraction of snowmelt that happens during winter. This will change the timing and predictability of Canadian water resources (Dierauer et al., 2019), but regionally specific impacts are poorly quantified. Most studies to date focus on very high emissions scenarios (SSP5-8.5 from CMIP6 studies or RCP8.5 from CMIP5 studies), whereas the intermediate emissions scenario (for example, SSP2-4.5) would be more consistent with existing global emissions policy, and the low emissions scenario (for example, SSP1-2.6) would be more consistent with Paris Agreement targets (see Chapter 3, section 3.3 for more details on emissions scenarios).

4) Uncertainty about the regional and global magnitude of snow albedo feedbacks and short-lived climate forcers is still a major source of uncertainty in projections of regional warming and snow loss.
While the average global snow cover extent estimated by climate models is in good agreement with observations, snow cover extent from individual models can vary widely (the spread in the simulated value among all models is large) (Mudryk et al., 2020). Along with biases in vegetation characteristics, spread in the estimates of snow cover extent simulated by models contributes to spread in the strength of surface albedo feedback simulated by the models (Thackeray et al., 2021) and continues to be a source of uncertainty in climate model projections. For example, regional model simulations indicate that the strength of simulated snow albedo feedback can substantially increase localized amounts of warming in mountainous regions (Letcher & Minder, 2015; Walton et al., 2017). Likewise, the influence of light-absorbing particles such as dust, black carbon, and microbes on past changes to snow is still poorly quantified in many regions. This influence provides another source of uncertainty in projections of regional snow loss (Skiles et al., 2018).

6.2.6: Confidence terms in key messages: summary of evidence

Key message 6.1: Snow cover duration has shortened in Canada as a whole over the past four decades (high confidence). Snow cover duration has shortened in northern Canada, southern Ontario, and parts of eastern Canada by one to four weeks, while snow cover duration has lengthened across central Canada by one to four weeks (medium confidence). This regional variability is also reflected in changes in peak snowpack amounts over the past four decades (high confidence).

Key message 6.2: Snow cover duration is projected to shorten across all of Canada and peak snowpack amounts are projected to decrease across most of Canada with increasing climate warming (very high confidence). Unlike the rest of Canada, the western and central parts of northern Canada are projected to experience larger peak snowpack amounts due to increased snowfall despite a shorter projected snow season (medium confidence).

Key message 6.3: Past amounts and changes in snowpack are more uncertain for mountainous regions than elsewhere (high confidence). In a warmer climate, mountainous regions in Canada are expected to have less snowpack accumulation and experience more mid-winter melt events, changing the timing and reducing the predictability of Canadian water resources (high confidence).

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because most attribution studies have been done for changes in snow cover for the Northern Hemisphere as a whole. Despite the lack of formal attribution studies specific to Canada, we assess that human-caused climate change is certain to be influencing snow cover in Canada (section 6.2.2).

With respect to Key Message 6.1, the assessed changes (both snow cover duration and peak snowpack amounts) are based on a diverse range of individual sources that generally agree with one another and that are in line with modelled expectations of climate change for the Northern Hemisphere as a whole. Where observed departures from these hemispheric expectations exist across Canada (such as increases in snow cover duration observed across central Canada), they are consistent with a range of other ground measurements and independent satellite analyses conducted over similar periods. Because there is overall agreement from multiple sources apart from a traceable set of inputs that differ for established reasons (Box 6.2), we have high confidence in the past changes for snow cover duration in Canada as a whole and the existence of regional variability in peak snowpack amounts. Our medium confidence in changes to snow cover duration for certain regions in Canada reflects the increased specificity of changes with location and magnitude.

With respect to Key Message 6.2, the assessment of very high confidence in future snow cover duration and peak snowpack amounts arises from the robust agreement among multiple generations of climate models in the declines in snow cover extent, snow cover duration, and peak annual snow water equivalent consistent with those shown in Figure 6.5 and with a good physical understanding of the factors driving the changes. For the regions projected to experience increased peak snowpack, while there is still a good understanding of the factors that drive the increases in peak annual snowpack across these regions, there is less model consensus on where the boundary between decreases and increases in peak annual snowpack occurs. For this reason, we have medium confidence in the locations where peak snowpack amounts will increase.

With respect to Key Message 6.3, uncertainty about past mountain snowpack amounts is due to many factors: the limited number of site-specific observations, the poor accuracy of existing passive-microwave sensors in mountainous regions, resolution constraints on simulated data, and a limited understanding of, or limited ability to represent in models, the additional processes important to accurately model snow distribution over such regions (section 6.2.4). Because each of these factors leads to uncertainty, we have high confidence in the uncertainty about the past amount and distribution of mountain snowpack. The same factors also lead to some uncertainty about the past changes in mountain snowpack, especially compared to non-mountainous regions. However, in the case of past changes in snowpack amounts, they can also be inferred from temperature measurements, precipitation measurements, and streamflow measurements based on an understanding of the processes that relate these variables to accumulated snowpack. This understanding of processes also means that there is much less uncertainty about the expected direction (if not the magnitude) of future snowpack change in a warming climate. The strong influence of temperature on direct melt and on the proportion of precipitation that falls as rain leads to our high confidence that there will be less overall snowpack accumulation across mountainous regions. Likewise, our understanding of how water availability depends on the timing of snowmelt and extrapolation from past changes in the continental United States (which is more closely monitored than mountainous regions in Canada) leads to our high confidence in how less snowpack accumulation leads to changes in the timing of water resources and their lower predictability.

6.3: Sea ice

Key message 6.4: Sea ice cover has declined in Canadian waters over the past four to five decades (very high confidence). Regions once covered by thick, multi-year sea ice are now covered by thinner seasonal sea ice that melts every summer (very high confidence). Landfast ice cover, which provides habitat for wildlife and is important for transportation, hunting, and the culture of northern communities, has also declined across the Canadian Arctic and Hudson Bay region (high confidence).

Key message 6.5: The transport of sea ice from the central Arctic Ocean into Canadian Arctic waters has increased over the past two and a half decades (high confidence). This increased transport of sea ice out of the central Arctic Ocean depletes its reserves of thick, multi-year sea ice, while the corresponding flow of multi-year ice into southern Canadian Arctic waters, such as the Northwest Passage, creates hazardous conditions for shipping.

Key message 6.6: The sea ice–free period is projected to lengthen further across Canadian Arctic and Hudson Bay waters with increasing climate warming (very high confidence). In regions with seasonal sea ice cover, the number of ice-free days is projected to increase by approximately one month for each degree of global warming, with smaller increases in the Labrador Sea and larger increases in the Beaufort Sea (medium confidence). The transport of multi-year ice into the Northwest Passage is projected to continue beyond mid-century thereby continuing to limit the shipping season (medium confidence).

Climate-driven changes to sea ice affect local ecosystems throughout the Arctic and influence northern residents through impacts on travelling, hunting, and fishing, with implications for people’s lives, livelihoods, cultural practices, and economic activities (Ford et al., 2019; Fuentes et al., 2020; Galappaththi et al., 2019; Lannuzel et al., 2020). The loss of sea ice also leads to higher ocean waves because wind can then blow over water for longer distances (known as increased fetch), which in turn increases coastal erosion, with often devastating impacts for local residents (Chapter 7) (Casas‐Prat & Wang, 2020). Satellite observational data show dramatic decreases in Arctic sea ice extent^{Footnote 3} over the past 40+ years (Comiso et al., 2017; Parkinson & DiGirolamo, 2021; Stroeve & Notz, 2018). The extreme low record of Arctic sea ice extent seen in 2012 would not have occurred without human-caused climate change (Kirchmeier-Young et al., 2017). These recent decreases in Arctic sea ice extent are also remarkable in comparison to changes in the past 150 years based on historical reconstructions (Walsh et al., 2017) and even more so to changes over the past 1000+ years based on paleoclimatic observations (Kinnard et al., 2011).

Average ice thickness for the entire Arctic Ocean decreased by 2 m, or approximately 66%, over the 60 years from 1958 to 2018 (Kwok, 2018). The thick multi-year ice that once dominated the Arctic and was capable of surviving a full summer melt season has been largely replaced by thinner seasonal ice that melts completely during summer (Comiso, 2012; Maslanik et al., 2011; Tschudi et al., 2020). This transition from multi-year ice to seasonal ice did not occur gradually. Instead most of the change is associated with two-step changes (Babb et al., 2023). The first occurred in 1988 to 1989 when a winter atmospheric circulation anomaly (a strongly positive Arctic Oscillation pattern, Thompson & Wallace, 1998) exported a considerable amount of multi-year ice out of the Arctic Ocean through the Fram Strait (Rigor & Wallace, 2004). The second occurred from 2006 to 2008 when multi-year ice export through the Fram and Nares straits (Kwok et al., 2010; Nghiem et al., 2007) combined with albedo-enhanced melt (Perovich et al., 2007) to further reduce multi-year ice reserves in the Arctic Ocean. The combined loss from these step changes has left the remaining Arctic sea ice more vulnerable to further loss, since seasonal ice drifts faster and is more susceptible to melt (Perovich & Polashenski, 2012; Rampal et al., 2011; Stroeve et al., 2012; Tandon et al., 2018; F. Zhang et al., 2023). Over the past several decades, even the thickest and more melt-resilient multi-year ice, which lies north of the Canadian Arctic Archipelago and Greenland (also known as the Last Ice Area), has begun to show signs of decline (G. W. K. Moore et al., 2019; G. W. K. Moore, Howell, & Brady, 2021).

In Arctic-wide regions where sea ice is already seasonal, state-of-the-art climate models project a lengthening of the ice-free season by roughly one month for each 1°C rise in global average temperature (Barnhart et al., 2016; Crawford et al., 2021). They also project that the central Arctic Ocean will transition from being consistently covered by multi-year ice to having mostly seasonal sea ice cover that melts during the late summer if emissions continue. September, the month with the lowest sea ice extent in a year, is projected to see sea ice extent drop consistently below 1 million km² with as little as 1.8°C of global warming, which may occur by the mid-21st century (Jahn et al., 2024; Notz & SIMIP Community, 2020; Sigmond et al., 2018). With continued warming, climate models project that the remaining sea ice will become more mobile in winter (Ward & Tandon, 2024). They also show that past trends toward thinner Arctic sea ice in winter will continue (Y. J. Lee et al., 2023; Notz & SIMIP Community, 2020), and that the snowpack that develops on top of that sea ice will become thinner (Webster et al., 2021).

The lengthening of the ice-free season is particularly relevant to northern communities across the Canadian Arctic (Case Story 6.2), resource extraction companies in the region, and the Arctic shipping industry (Box 6.3). Specifically, the Northwest Passage runs through the Canadian Arctic and connects the Atlantic and Pacific oceans over a shorter distance than the Northern Sea Route, which runs along the northern coast of Eurasia. The Canadian Arctic has already experienced a considerable increase in shipping activity since the 1990s (Dawson et al., 2018; Pizzolato et al., 2014) associated with sea ice decreases and longer melt seasons (Howell & Brady, 2019; Howell et al., 2009). Interest in practical use of the Northwest Passage continues to grow as climate models project the sea ice cover along the passage will continue to decline (Mudryk et al., 2021; L. C. Smith & Stephenson, 2013). This interest is amplified by the political uncertainty of using the Northern Sea Route along the Russian Arctic coast (X. Li & Lynch, 2023; Vylegzhanin et al., 2020). 

Although past and future Arctic-wide changes in sea ice are dramatic overall, regional variability is considerable (Laliberté et al., 2016; Onarheim et al., 2018). Canadian sea ice regions include portions of the open Arctic Ocean, where sea ice can circulate freely (the western Arctic–Beaufort Sea region), as well as the narrow waterways of the Canadian Arctic Archipelago, where ice is landfast for most of the year. Along the more temperate east coast and in Hudson Bay, the ice melts completely each spring and reappears in the fall.

6.3.1: Past changes

6.3.1.1: Sea ice area

Generally speaking, sea ice area is the total area in a given part of the ocean covered by ice. The Canadian Ice Service has produced digital ice charts since 1968, representing a 50+-year record of total sea ice area (ice of any type or thickness), multi-year ice area (which includes only ice classified as multi-year), and landfast ice area (which includes only ice classified as landfast) in Canadian waters. Ice charts are created by experts who assess the presence and type of sea ice in Canadian waters based on a variety of datasets and information. These datasets can include satellite images (for example, RADARSAT, a Canadian imaging radar, has been the primary imagery source since 1995), surface observations, airborne and ship reports, and operational model results (Tivy et al., 2011). The ice chart record is almost 10 years longer and has been shown to provide more accurate estimates of sea ice area in Canadian waters than those from passive-microwave satellite data (Agnew and Howell, 2003), even though with ice charts some uncertainty stems from human interpretation (Cheng et al., 2020). We use this record to examine changes over three regions in Canadian waters, defined throughout section 6.3.1.1 as the Canadian Arctic domain, the Hudson Bay domain, and the Canadian East Coast domain (Figure 6.6). The Canadian Arctic contains almost all the multi-year sea ice present in Canadian waters and has the longest annual duration of ice cover. Annual duration of ice cover is shorter in the Hudson Bay region, while along the Canadian east coast there is ice cover only during winter and it is ice-free for the rest of the year. Given these characteristics, winter sea ice area is a better indicator of sea ice change over the Canadian East Coast domain, while summer sea ice area is a better indicator of sea ice change over the Canadian Arctic and Hudson Bay domains.

Figure take-away: Changes in sea ice area, thickness, and transport have been calculated using defined regions and locations of Canada.

Figure title: Regions and locations of Canada used to calculate changes in sea ice area, thickness, and transport

Figure 6.6: Illustration of three sea ice regions in Canadian waters, along with subregions. The three regions are defined as the Canadian Arctic domain (blue), the Hudson Bay domain (orange), and the Canadian East Coast domain (green). Smaller subregions in these domains are separated with black lines and labelled. Trends in sea ice area are calculated for the three domains and their subregions. Yellow circles illustrate locations with long-term ice thickness measurements. Red dots illustrate locations where the transport of sea ice into Canadian waters is calculated.

Total sea ice area has experienced significant decreases in every subregion of Canadian waters since 1968 (Figure 6.7), with the largest decreases occurring during summer in the Hudson Strait (14.2% per decade). The trends reflect the average change because year-to-year differences in sea ice area are high (Figure 6.8) due to the combination of internal climate variability (natural variation in the atmosphere and oceans) and external climate forcing (especially greenhouse gas emissions). This high internal climate variability can mask long-term trends on scales of a decade or two. For example, the trend in Arctic-wide sea ice extent has been relatively flat since 2007, but this does not mean the effects of climate change forcing on sea ice have stopped (England et al., 2025; Stern, 2025).

Figure take-away: Sea ice area of all types has declined across Canadian waters.

Figure title: Past trends in sea ice area for various regions and ice types

Figure 6.7: Past trends in total sea ice area (SIA), multi-year ice area, and landfast ice area for subregions in Canadian waters. Principal colours (blue, orange, green) distinguish three main regions (domains) with ice type distinguished by shade. See Figure 6.6 for domain and subregion outlines. Trends in total sea ice area and multi-year ice area are over the period from 1968 to 2023; trends in landfast ice area are over the period from 1984 to 2023. All changes presented are significant at the 5% level (meaning there is ≤ a 5% chance of concluding that an effect or trend exists when it does not). Data source: Canadian Ice Service Ice Archive (2021).

Across the Canadian Arctic, multi-year ice has also declined significantly (Figure 6.7). The largest declines have occurred in the Foxe Basin and Baffin Inlets subregion of the Canadian Arctic (17.5% per decade), where virtually no multi-year ice has existed since 1994 (not shown). Loss of multi-year ice in the Beaufort Sea is also high (8.4% per decade) and representative of changes in the Arctic-wide pattern of sea ice circulation. Historically, the Beaufort Sea served as a conduit for the transport of multi-year ice from the central Arctic Ocean to the eastern Arctic Ocean, thereby distributing multi-year ice over a wider region. Data available from 1981 until 2005 establishes that more than 90% of multi-year ice that historically transited through the Beaufort Sea would survive the melt season (Maslanik et al., 2011). A comparison of recent (2017 to 2021) and more historical (1997 to 2001) data clearly shows that the Beaufort Sea has become a significant area of multi-year ice loss, and very little ice in the Beaufort Sea now survives the melt season to reach the eastern Arctic Ocean (Babb et al., 2022). In fact, the Beaufort Sea became virtually ice-free near the end of the melt seasons in both 2012 and 2016 (Babb et al., 2016, 2019). Recent multi-year ice losses mean that the Beaufort Sea now accounts for 26% of Arctic-wide multi-year ice area loss from melt, despite covering only 14% of the Arctic Ocean (Regan et al., 2023).

The rate of loss of total sea ice area and multi-year ice area is weaker for several subregions within the Canadian Arctic Archipelago (for example, the Queen Elizabeth Islands and Northwest Passage Waterways) than for other parts of the Canadian Arctic because of the multi-year ice replenishment processes that occur there. Multi-year ice from the Arctic Ocean is continuously forced up against the northern coastline of the Queen Elizabeth Islands by the predominantly anti‐cyclonic (clockwise) Beaufort Gyre, from where it then flows into the Canadian Arctic Archipelago during the melt season (Howell et al., 2013; Kwok, 2006). Within this archipelago, multi-year ice is also generated from seasonal first-year ice that survives the summer melt season (Alt et al., 2006; Howell et al., 2009; Melling, 2002). While multi-year ice replenishment in the Canadian Arctic Archipelago continues to occur up to the present (established from data available for the period from 1968 to 2020), since 2007 the amount of first-year ice aging has dropped by 47%, and the amount of multi-year ice that is transported into the Canadian Arctic Archipelago has dropped by 22%, compared to the period from 1968 to 2006. Together, these changes have led to a notable drop in multi-year ice area across the entire Canadian Arctic Archipelago since 2007 (Howell, Babb, Landy, and Brady, 2023).

Landfast sea ice is defined as “sea ice which remains fast along the coast, where it is attached to the shore, to an ice wall, to an ice front, or over shoals, or between grounded icebergs” (Armstrong, 1972). Landfast ice is important to northern communities in the Canadian Arctic for transportation, hunting, and culture, as well as to wildlife there for habitat (Cooley et al., 2020; Laidler et al., 2010). Typical values for landfast ice from 1991 to 2002 were included for the first time in the most recent ice-related climatology published by the Canadian Ice Service (2021). This data for landfast ice was quality-controlled by the Canadian Ice Service and enabled calculations of summer trends in percent per decade for the period from 1984 to 2023 (Figure 6.7). Landfast ice area has decreased significantly in all subregions of the Canadian Arctic and Hudson Bay domains, ranging from 5.7% per decade in the Queen Elizabeth Islands to 20.8% per decade along the north Labrador coast. This is consistent with an earlier breakup and later freeze-up of landfast ice in the Canadian Arctic (Galley et al., 2012; Lam et al., 2023).

Sea ice area in the Canadian East Coast domain has also declined during winter (Figure 6.7). The rate of decline between 1969 and 2023, determined from the Canadian Ice Service ice charts for the domain as a whole, is 8.7% per decade (Figure 6.8), but the rate varies by subregion. For example, the rate of decline for the Gulf of Saint Lawrence (9.3% per decade) is weaker than that for eastern Newfoundland waters (11.9% per decade), while the rate of decline for the southern Labrador Sea is weaker than either of those, at 5.7% per decade (Figure 6.7). There is also dramatic year-to-year variability in sea ice in this domain (Figure 6.8), driven largely by air temperature and winds (Deser and Teng, 2008; Galbraith et al., 2024; Peterson et al., 2015).

Figure take-away: Year-to-year fluctuations in sea ice area and an overall decline have been observed in all three sea ice regions assessed.

Figure title: Year-to-year fluctuations in total sea ice area for three sea ice regions

Figure 6.8: Year-to-year fluctuations in sea ice area shown by red circles for three main regions (domains) in Canadian waters. The domains are shown in Figure 6.6. Sea ice area is based on summer data for the Canadian Arctic and Hudson Bay domains and winter data for the Canadian East Coast domain. Dashed black lines show the average trends. Data source: Canadian Ice Service Ice Archive (2021).

6.3.1.2: Sea ice thickness

Satellite altimetry estimates of Arctic sea ice thickness come from sensors that measure the height at the top of the sea ice relative to the ocean surface (Kacimi and Kwok, 2022; Kwok, 2018; Landy et al., 2022; Tilling et al., 2015). The main satellites that are equipped with altimeters are the European Space Agency’s CryoSat-2 and NASA’s Ice, Cloud, and land Elevation satellites (ICESat-1 and ICESat-2). These satellites can be readily used to estimate ice thickness in areas of the Canadian Arctic, such as Hudson Bay (Babb et al., 2021; Kirillov et al., 2020; Landy et al., 2017), Baffin Bay (Glissenaar et al., 2023; Landy et al., 2017), and the Beaufort Sea (Babb et al., 2019, 2020). Over the period from 1996 to 2020, the satellite observations indicated that sea ice thinned at an average rate of 8.2 cm per decade across the Canadian Arctic, not including Hudson Bay (Glissenaar et al., 2023). Negative trends in average ice thickness were also observed across Hudson Bay and Baffin Bay when data were available from 2003 to 2009, but they were not statistically significant (Landy et al., 2017).

Manual landfast ice thickness measurements have been made regularly at many coastal stations throughout the Canadian Arctic since about 1950 (R. D. Brown and Cote, 1992). These data are quality-controlled and archived at the Canadian Ice Service. While most station measurements ended in the 1990s, Alert, Eureka, Resolute, and Cambridge Bay are still active (Figure 6.6) and now span over 60 years, representing one of the longest records of Arctic ice thickness available. Investigating the annual maximum thickness over long time periods provides important information to help understand variability and change.

Significant decreases in annual maximum landfast ice thickness (Figure 6.9) have occurred over the past 60 years at Cambridge Bay (4.5 cm thinner per decade), Eureka (4.4 cm thinner per decade), and Alert (5 cm thinner per decade). The trend at Resolute, while not significant, was also decreasing over the period from 1950 to 2023. Overall, the trends at these four long-term measurement sites indicate that maximum ice thickness is being reached earlier in the year (Howell et al., 2016). Compared to other published long-term records, the trends in landfast ice thickness for Canada are in line with negative trends reported for the Siberian coast (3.3 cm thinner per decade) (Polyakov et al., 2010) but are smaller than those in the Barents Sea (11 cm thinner per decade) (Gerland et al., 2008). Extrapolating the observed trends indicates that over the last 60+ years, the landfast ice in the Canadian Arctic has thinned by approximately 22 to 34 cm.

Figure take-away: Maximum landfast ice thickness has decreased at measurement sites in the Canadian Arctic over the past 60 years.

Figure title: Annual maximum ice thickness at four measurement locations in the Canadian Arctic

Figure 6.9: Time series of annual maximum landfast ice thickness (cm/dec) in the Canadian Arctic at Eureka, Alert, Resolute, and Cambridge Bay from 1958 to 2023. See Figure 6.6 for site locations. Data source: Canadian Ice Service Ice Archive (2021).

Inuit communities across the Canadian Arctic also monitor landfast sea ice thickness as part of community-based monitoring programs. For example, the SmartICE program empowers these communities to combine traditional knowledge with satellite mapping and remote-sensor technology to determine how local ice conditions are evolving seasonally (Case Story 6.2). Other Inuit-led programs have helped to extend pre-existing but discontinued records of landfast ice thickness. For example, the Nunatsiavut government has been monitoring snow and ice thickness at two community ice stations near Nain since 2009. These more recent measurements can be combined with the Canadian Ice Service record from 1961 to 1984 at nearby Hopedale to produce a longer-term record (Figure 6.10). Because these communities have a similar maximum landfast ice thickness in any given year (Nunatsiavut Research Centre, personal communication), the combined record suggests that maximum ice thickness in the region has decreased by more than 30 cm over the past 70 years.

Figure take-away: Community monitoring has extended records of landfast ice thickness to form indicators of long-term change.

Figure title: Annual maximum ice thickness measurements during two different periods at locations near Nain and Hopedale, Labrador

Figure 6.10: Time series of seasonal maximum ice thickness (in cm/dec) in Labrador. The red data points were taken at Hopedale from 1961 to 1984 and are included in the Canadian Ice Service Ice Archive (2021); the blue data points were taken at Nain from 2009 to 2023 and were collected through community-based monitoring. Data source: Nunatsiavut Sea Ice Monitoring Program, provided by Nunatsiavut Government.

The Last Ice Area is located to the north of Greenland and the northern Canadian Arctic Archipelago (Figure 6.2). Sea ice formed elsewhere in the Arctic Ocean converges on this area and piles up against the northern sides of these islands. This area therefore contains the oldest and thickest multi-year ice in the Arctic. The multi-year ice in the Last Ice Area is predicted to last longer than in other regions of the Arctic, providing a refuge for ice-dependent species (R. Newton et al., 2021). Despite the continued presence of multi-year ice in this region, even the Last Ice Area has begun to show signs of change. Ice volume in this region is declining at twice the rate of the Arctic Ocean as a whole (G. W. K. Moore et al., 2019). Furthermore, polynyas (areas of open water in the sea ice) were observed for the first time in the eastern part of the Last Ice Area in the spring of 2018 (Ludwig et al., 2019; G. W. K. Moore et al., 2019) and in the western part of the Last Ice Area in May 2020 (G. W. K. Moore, Howell, and Brady, 2021). Finally, the lowest sea ice concentrations observed to date occurred across the eastern part of the area during the summer of 2020 (Schweiger et al., 2021). These recent events in the Last Ice Area suggest that the multi-year ice in this region may be less resilient in a warmer Arctic, and such events could therefore become more common in the future.

6.3.1.3: Sea ice transport through the Canadian Arctic

The transport of sea ice between regions (ice area flux) is a key aspect of the Arctic marine system. Specifically, sea ice is transported from the Arctic Ocean into the Canadian Arctic Archipelago, and through the Fram and Davis straits into the North Atlantic Ocean, where it melts and delivers freshwater to the global ocean (Kwok, 2004, 2009). The primary passageways for sea ice to be transported from the Arctic Ocean to the Canadian Arctic are the Amundsen Gulf, M’Clure Strait, Queen Elizabeth Islands, and Nares Strait. The Queen Elizabeth Islands and Nares Strait are particularly important, as ice to the north of these regions is the oldest and thickest in the Arctic (Landy et al., 2022; Maslanik et al., 2011; Ryan and Münchow, 2017; Tschudi et al., 2020). Ice transport through these passageways is limited by ice arches that form across the straits during winter and prevent ice transport. However, recent studies show that the ice arches in the Nares Strait and those that enclose the Queen Elizabeth Islands have deteriorated over the past 20 years or more, leading to a corresponding increase in the amount of sea ice transported from the Arctic Ocean into the Canadian Arctic (Howell and Brady, 2019; G. W. K. Moore, Howell, Brady, et al., 2021; Vincent, 2019). The amount of transported sea ice increased by 1029 km²/yr for the Queen Elizabeth Islands and 6062 km²/yr for the Nares Strait from 1997 to 2023 (Figure 6.11). The time series of sea ice area flux for the Nares Strait is more striking, with large values in recent years. These large values are related to anomalous ice arch behaviour. In particular, they are associated with an early arch collapse in May 2017 (G. W. K. Moore and McNeil, 2018) and with the total lack of arch formation in 2019 (G. W. K. Moore, Howell, Brady, et al., 2021).

Figure take-away: The amount of sea ice transported from the central Arctic Ocean through the Canadian Arctic has increased over the past two decades.

Figure title: Changes in transport of sea ice (ice area flux) into the Canadian Arctic through two different entrances

Figure 6.11: Time series of the annual transport of sea ice (ice area flux) through the Queen Elizabeth Islands and Nares Strait from 1998 to 2023. Averages are calculated using data from September to August for the Nares Strait and from May to November for the Queen Elizabeth Islands (since very little ice transport occurs between December and April). Data source: Queen Elizabeth Islands data updated from Howell, Babb, Landy, Moore, et al. (2023); Howell and Brady (2019); G. W. K. Moore, Howell, Brady, et al. (2021). Nares Strait updated from Kwok et al. (2010).

Increases in the amount of ice transported from the Arctic Ocean through these passageways will have multiple consequences. The increased transport can affect the Atlantic Meridional Overturning Circulation (Chapter 4, section 4.9) by providing more freshwater to the North Atlantic (Aagaard and Carmack, 1989; Carmack et al., 2015; Gregory et al., 2005). It also creates hazardous conditions for ships transiting through the Northwest Passage (Box 6.3) (Fol et al., 2025; Haas and Howell, 2015; Howell, Babb, Landy, and Brady, 2023; Melling, 2002). Ice transported southward through the Nares Strait has reached as far as the east coast of Newfoundland, causing hazardous ice conditions there as well (Barber et al., 2018). Finally, increases in the amount of ice exported from the central Arctic Ocean reduces the remaining reservoir of the oldest and thickest ice in the Arctic (located in the Last Ice Area, to the north of the Canadian Arctic Archipelago and Greenland).

6.3.2: Causes of past change

Past declines in Arctic sea ice area, thickness, and volume have resulted from a combination of long-term, human-caused global warming and natural variations in the atmosphere and ocean such as internal climate variability. For example, the accelerated decline of sea ice concentration from August to October in the East Siberian, Chukchi, and Beaufort seas in the early 21st century can be attributed in part to an anomalous atmospheric circulation pattern that favours the transport of heat and moisture into the Arctic from the North Pacific Ocean (J. Liu et al., 2021; S. Zhang et al., 2020). On longer timescales, internal variability of sea surface temperature in the Pacific Ocean (Baxter et al., 2019; X.-Y. Yang et al., 2020) and Atlantic Ocean (Castruccio et al., 2019) can influence Arctic sea ice trends over multiple decades, often through the influence of ocean variability on atmospheric energy transport to the Arctic (He et al., 2024; Topál et al., 2020). For example, if the North Atlantic Ocean is warmer than normal in winter, winds blowing from the Atlantic to the Arctic are warmer and wetter than normal, making the Arctic warmer and cloudier and slowing sea ice growth (He et al., 2024). After accounting for these factors, modelling studies have calculated that long-term global warming is responsible for about 50 to 60% of the decline since 1979 in Arctic sea ice extent or area (for example, Ding et al., 2019; Kay et al., 2011; Notz and Marotzke, 2012; Notz and Stroeve, 2016; Stroeve et al., 2007). On seasonal timescales, the rate of Arctic sea ice growth or loss is also dependent on atmospheric circulation patterns (Serreze, Stroeve, et al., 2016), atmospheric heat and moisture transport (Kapsch et al., 2016; G. W. K. Moore, 2016; Mortin et al., 2016), ocean heat transport (Serreze, Crawford, et al., 2016; Woodgate et al., 2010), and the sea ice albedo feedback (Perovich et al., 2007; Perovich and Polashenski, 2012; Stroeve et al., 2014). For example, when highly reflective snow-covered sea ice is replaced by open water, the darker water surface absorbs a greater fraction of the sunlight that reaches it, and the more sunlight is absorbed, the faster snow and sea ice melt, accelerating the transition to open water. This feedback matters most when sea ice and sunlight are both present, for example, during late spring and early summer when daylight hours become very long in the Arctic but before the previous winter’s ice has fully melted.

6.3.3: Future changes

The main tools used for projecting future changes in Arctic sea ice are dynamical climate models with coupled atmosphere, ocean, and sea ice components. “Dynamical” models use physical equations to simulate how mass and energy move through the Earth’s climate system. A sea ice model simulates both thermodynamics (freezing and melting of sea ice) and dynamics (such as the growth of ridges when two ice floes crush together, or the movement of sea ice into new areas). In a fully coupled model, any change in the sea ice being simulated will go on to impact the other parts of the model (for example, the formation of sea ice will inhibit the transfer of energy from a warm ocean to a colder atmosphere), but any change in those other parts of model will also affect the sea ice (for example, a change in ocean currents or wind will change how the sea ice moves, and a change in air temperature will change how quickly sea ice grows or melts). The information provided on future changes in sea ice are either results as reported in published literature or in the case of figures 6.13 and 6.14, based on our own analysis of CMIP6 output for regions specific to Canada. For the latter, the methods and results are consistent with other published literature describing Arctic-wide changes as justified in the text by citations to specific studies. Where italicized likelihood statements are provided, they are based on the Intergovernmental Panel on Climate Change (IPCC) guidelines for calibrated language.

In broad terms, projections from CMIP6 agree with previous CMIP phases: Arctic-wide sea ice extent will continue to contract in all months, and more Arctic waters will transition from perennially ice-covered to seasonally ice-free (Årthun et al., 2021; Crawford et al., 2021). Projections from CMIP6 models show that with continued warming, the remaining sea ice will become more mobile in winter (Ward and Tandon, 2024), that past trends toward thinner Arctic sea ice in winter will continue (Y. J. Lee et al., 2023; Notz and SIMIP Community, 2020), and that the snowpack that develops on top of that sea ice will also become thinner (Webster et al., 2021). How fast these changes will occur depends strongly on how fast the world warms (Crawford et al., 2021; Notz and SIMIP Community, 2020; Zhao et al., 2024). Additionally, although CMIP6 models show some improvements in their ability to replicate past sea ice properties compared to earlier models, biases still exist (Crawford et al., 2023; Notz and SIMIP Community, 2020; Shen et al., 2021). Therefore, our estimates of future seasonal sea ice in various regions and along shipping routes in the Canadian Arctic include a delta-shift bias correction for the models (Stroeve et al., 2024). The bias correction used is the observed duration of sea ice–free conditions based on satellite measurements over the period from 1979 to 2013 (Figure 6.12), and the results shown in figures 6.13 and 6.14 are corrected on this basis.

6.3.3.1: Seasonal sea ice

For areas with seasonal sea ice, the length of the ice-free season increases by a consistent amount with each 1°C of global warming in climate model projections and in historical observations (Crawford et al., 2021). This relationship can be used to determine the level of global warming that would lengthen the ice-free period beyond a particular value. For example, western Hudson Bay was typically ice-free for about 120 to 150 days per year during the period from 1979 to 2013 (Figure 6.12). The climate model output shown in Figure 6.13 has been bias-corrected so that the average sea ice–free period simulated between 1979 and 2013 matches the average observed value over the same time period. After this bias correction is applied, the models can be used to determine future sea ice conditions. They project 180 ice-free days per year across most of the region (Figure 6.13c) at global warming levels of 1.0 to 1.5°C relative to the pre-industrial period (approximated in this report as 1850 to 1900), and 240 ice-free days per year across the region (Figure 6.13d) at global warming levels of 3.0 to 3.5°C relative to the pre-industrial period (Figure 6.13d). The range of 1.0 to 1.5°C is close to the current amount of warming (Chapter 2, Box 2.4 Table 1). The range of 3.0 to 3.5°C is higher than the best estimate of projected warming by the end of the 21st century under an intermediate emissions scenario (SSP2-4.5) but very likely to occur under a high (SSP3-7.0) or very high (SSP5-8.5) emissions scenario (assessed in Chapter 3; see Table 3.1). Looking at another region, many of the channels in the Canadian Arctic Archipelago would very likely require 2.0 to 4.5°C of warming to be ice-free 120 days per year. Greater uncertainty in the models for this region makes it harder to project ice-free days and leads to the broader range of projected warming for the specified duration of sea ice–free conditions.

Table 6.1: Future additional ice-free days per degree Celsius of global warming for the Arctic as a whole and Canadian subregions

The best estimate is from the median of an ensemble of CMIP6 models, and the very likely range spans the 5th to 95th percentiles of that ensemble.

Figure take-away: The duration of ice-free conditions in the Canadian Arctic varies by location.

Figure title: Average duration of ice-free conditions across Canadian waters from 1979 to 2013

Figure 6.12: Map showing the ice-free period in the Canadian Arctic from 1979 to 2013, calculated from satellite measurements. Colours show the average duration of ice-free conditions (sea ice concentration continuously below 15%) in the Canadian Arctic from 1979 to 2013. During this period, global warming was roughly 0.7°C above the pre-industrial (1850 to 1900) average. Data source: average of three sea ice concentration records, NASA Team (Comiso, 2023), Bootstrap (DiGirolamo et al., 2022), and OSI SAF (2025).

Figure take-away: The ice-free period will lengthen across Canadian waters with each increment of global warming, but changes will occur more slowly in the Canadian Arctic than in the Hudson Bay region or along the Canadian east coast.

Figure title: Global warming levels at which different ice-free season lengths are reached across Canadian waters

Figure 6.13: Maps with colours showing the global warming levels at which the ice-free period is projected to exceed a) 120 days (4 months), b) 150 days (5 months), c) 180 days (6 months), or d) 240 days (8 months). Maps based on conditions in the median CMIP6 model after applying a bias correction. White indicates insufficient data. Global warming level is relative to the pre-industrial (1850 to 1900) baseline. Data Source: temperature and sea ice concentration output from 17 CMIP6 models.

On average, CMIP6 models project that the ice-free period will increase at a rate of 31 days per 1°C of global warming in seasonally ice-free Arctic waters (Table 6.1) (Crawford et al., 2021). Projected rates are close to the pan-Arctic average for Hudson Bay, Baffin Bay, and the Canadian Arctic Archipelago but are faster for the Beaufort Sea and slower for the Labrador Sea (a projected rate for the Labrador Sea is not provided in Table 6.1 since, as the region approaches ice-free conditions, the rate of change is slower and slower). In prior studies, changes in the ice-free period were typically reported as changes per year or changes per decade instead of changes per degree of global warming. Based on CMIP5 models, these calculations indicate increases in the ice-free period of 5 to 30 days per decade for various regions of the Arctic (Lebrun et al., 2019; M. Wang et al., 2018). These numbers can be roughly equated to a corresponding increase of 10 to 45 days per degree Celsius of global warming, which is consistent with projections from CMIP6 for most regions (Table 6.1). The Beaufort Sea, the Canadian Arctic Archipelago, Hudson Bay and Baffin Bay will all maintain winter sea ice cover even with 4 or 5°C of warming (Årthun et al., 2021; Crawford et al., 2021). The Labrador Sea may become consistently ice-free year-round with as little as 3.9°C of global warming, or it may require as much as 6°C. The Gulf of Saint Lawrence is projected to become consistently ice-free year-round at even lower levels of warming (the very likely range projected by the models is 1.8 to 3.4°C ) (Crawford et al., 2021). We did not include the Gulf of Saint Lawrence’s increase in number of ice-free days in Table 6.1 because of the complete loss of sea ice projected for the region and the fact that the calculations require sea ice to be present seasonally for global warming levels from 1 to 5°C.

For individual communities, changes in sea ice far from the coasts are less relevant than those for local landfast ice. Projections from CMIP5 models using the very high emissions scenario (RCP8.5) indicate that the spring landfast ice season across Canadian waters will be 5 to 44 days shorter by 2100 (Cooley et al., 2020). However, those same projections also show that an extensive landfast ice cover should remain for at least five months of the year through to the end of the 21st century (Laliberté et al., 2018).

6.3.3.2: The central Arctic Ocean

The timing of the central Arctic Ocean’s transition to being seasonally ice-free has been a topic of research for several decades (Jahn et al., 2024). Predicting this timing is complicated by several factors, namely, (i) whether sea ice area or extent is used, (ii) the threshold below which sea ice area or extent has to drop for the Arctic to be qualified as “ice-free,” (iii) whether the first year of ice-free conditions or the year when seasonally ice-free conditions become the new normal is used, (iv) internal variability in the climate system, (v) model uncertainty, and (vi) uncertainty about human activities (especially future greenhouse gas emissions). Recent studies typically use average monthly September sea ice extent or area below 1 million km² as the definition for “seasonally ice-free,” but some studies focus on projecting the first occurrence of an ice-free September (for example, DeRepentigny et al., 2020; Y.-H. Kim et al., 2023; Notz and SIMIP Community, 2020), while others focus on when Septembers will become consistently ice-free (Wei et al., 2020; Zhao et al., 2022), and still others combine these approaches (Bonan et al., 2021; Jahn et al., 2024; Sigmond et al., 2018; Topál and Ding, 2023).

Using a subset of high-performing CMIP6 models, the first ice-free September is projected to occur between 1.3°C and 2.9°C of global warming (Notz and SIMIP Community, 2020). Based on multiple studies using multiple methods, the projected threshold for when Septembers become consistently ice-free ranges from 1.8 to 2.8°C (Jahn et al., 2024), which other studies show will occur between 2035 and 2075 (Bonan et al., 2021; Wei et al., 2020; Zhao et al., 2022). These projections assume either an intermediate (SSP2-4.5), high (SSP3-7.0), or very high (SSP5-8.5) emissions scenario.

Another way to frame these projections is to consider the likelihood that an ice-free September in the central Arctic Ocean would occur in any given year or at any given global warming level. At a global warming level of 1.5°C (the best estimate of the near-term global warming level for the period from 2021 to 2040, see Chapter 3, Table 3.1), the chance of an ice-free September in any given year is low (roughly 5%) (Jahn, 2018; Jahn et al., 2024; Sigmond et al., 2018). However, because there is a 5% chance each year, we assess it is about as likely as not that we will experience at least one ice-free September between 2021 and 2040 (Bonan et al., 2021; Jahn et al., 2024; Zhao et al., 2022). Also note that at higher global warming levels, the chance of an ice-free September in any given year is also higher. By a global warming level of 1.8°C (the best estimate of the future global warming level for the period from 2081 to 2100 under net zero emissions, see Chapter 3, Table 3.1), we assess that ice-free Septembers are likely to be occasional, unexceptional occurrences happening about once every 3 to 7 years (Jahn, 2018; Jahn et al., 2024; Sigmond et al., 2018). In contrast, the intermediate emissions scenario (SSP2-4.5) is projected to result in a global warming level of 2.7°C for the period from 2081 to 2100. At that level, we assess that most Septembers are likely to be ice-free, and by 3.0°C, effectively every September is projected to be ice-free (Jahn et al., 2024; Sigmond et al., 2018).

Over the past five decades, thick multi-year ice has been gradually replaced by thinner seasonal ice across the Arctic (section 6.3.1) (see also Babb et al., 2023; Kwok, 2018), and the past trends in sea ice thickness have been strongly negative (section 6.3.1) (see also Crawford et al., 2025; Kwok, 2018; Sumata et al., 2023). Fall (October–December) measurements from submarines and satellites indicate that average ice thickness in the central Arctic Ocean has been cut nearly in half, from around 3.0 m in the 1970s and 1980s to around 1.5 m in the 2010s and 2020s. Although dramatic historically, Arctic sea ice thinning is projected to be much slower in the future, especially in September, simply because there is so little multi-year sea ice left to thin (Wei et al., 2020). Projections of Arctic-wide September sea ice thickness therefore show no significant trends, except under the very high emissions scenario (SSP5-8.5), when warming is strong enough to limit winter growth so much that lingering seasonal sea ice in September drops from near 1 m thick in the 2020s to around 50 cm thick in the essentially ice-free Septembers of the 2080s and beyond (Wei et al., 2020). The future impacts of global warming on Arctic sea ice will therefore be more apparent in the form of a loss of area and a transition to being fully seasonal sea ice (Årthun et al., 2021; Jahn et al., 2024; Sigmond et al., 2018).

6.3.3.3: Sea ice and shipping routes

Future increases in the length of the ice-free season coupled with thinning of winter sea ice will increase the accessibility of Arctic shipping routes. Especially for ice-strengthened (“Polar Class”) vessels, projecting sea ice thickness is of paramount importance for projecting navigability (Pizzolato et al., 2016; L. C. Smith and Stephenson, 2013). More specifically, a combination of ship class and sea ice thickness is used to quantify the risk in a region or along a route, which in turn determines whether the region or route is navigable for the ship class in question (Copland et al., 2021; Howell and Yackel, 2004; Mudryk et al., 2021; L. C. Smith and Stephenson, 2013). An additional variable is how much risk is deemed tolerable by ship owners and insurers; the higher the risk tolerance, the longer the navigable period will be (Mudryk et al., 2021).

The Arctic Bridge Route, which connects the port of Churchill, Manitoba, on Hudson Bay, to the Atlantic Ocean and Europe, is typically limited by sea ice conditions in the Hudson Strait or Hudson Bay (Figure 6.14e). At 1°C of global warming (reached roughly during the 2010s), the Arctic Bridge Route was fully ice-free on average 110 days (ranging from 99 to 123 days) from late July to early November (Figure 6.14b). According to projections from an ensemble of 17 bias-corrected CMIP6 models, the average is projected to increase to 141 days (ranging from 128 to 158 days) with 2°C of warming, and to 221 days (ranging from 187 to 265 days) with 4°C of warming, from about June 1st to early January. Other estimates using the Community Earth System Model and applying no bias correction estimated about 250 days at 4°C of warming (Mudryk et al., 2021). For Polar Class 7 vessels, which are moderately ice-strengthened, the Arctic Bridge is already navigable about 164 days (very likely range of 144 to 186 days) at 1°C of warming when tolerating only nominal risk along the route (Figure 6.14). The navigable period is projected to increase to 209 days (ranging from 186 to 248 days) with 2°C of warming, and to 286 days (ranging from 263 to 327 days) with 4°C of warming. A progressive increase in the navigable period with continued warming is common to all models. However, uncertainty about the timing of opening and closing is greater for higher warming levels.

While the Arctic Bridge Route is already open for much of the year with 1°C of global warming, the Northwest Passage is not projected to be reliably ice-free each year until over 1.5°C of global warming (Figure 6.14a,b). Viscount-Melville Sound acts as a choke point for shipping (see also Box 6.3) (Cook et al., 2024; Haas and Howell, 2015; Howell, Babb, Landy, and Brady, 2023; Howell et al., 2009), and southern branches of the Northwest Passage (such as the M’Clure Strait and Amundsen Gulf) are more often open than the northern route (straight through the Parry Channel). It is difficult to assess how long this route is expected to be open each year because models show more uncertainty for the Northwest Passage than for the Arctic Bridge (hence the larger error bars in Figure 6.14). This uncertainty arises both because these channels are conduits for the export of thicker ice from the Central Arctic Ocean (Box 6.3) (Fol et al., 2025; Howell, Babb, Landy, and Brady, 2023; Melling, 2002) and because some models lack the spatial resolution to properly simulate the numerous narrow channels of the Canadian Arctic Archipelago, especially the connectivity of the Parry Channel to the central Arctic Ocean between the Queen Elizabeth Islands (Crawford et al., 2023).

The results shown in Figure 6.14 include a bias correction to account for the under-estimation of sea ice in many climate models (Crawford et al., 2023; Notz and SIMIP Community, 2020; Shen et al., 2021). This is important to note because studies using model subsets or bias correction to estimate changes in the Northwest Passage tend to yield more modest navigable periods than other studies (J. Chen et al., 2022; Min et al., 2022; Mudryk et al., 2021; Wei et al., 2020). Overall, any projection for the Northwest Passage is highly uncertain because of known biases in the models (including their coarse spatial grids and biases in sea ice thicknesses), high sensitivity to different methodological choices for addressing biases, and high variability between models. However, all studies agree that the Northwest Passage will become open for longer periods with continued warming. Taking the literature as a whole, we assess the passage will likely be reliably open for moderately ice-strengthened vessels for multiple months each year with at least 2°C of warming (medium confidence).

Figure take-away: The length of the navigable season along the Northwest Passage and Arctic Bridge shipping routes will increase with continued warming.

Figure title: Future length of time per year that Canadian shipping routes will be navigable by global warming level and ship type

Figure 6.14: Plots of the duration of navigable conditions during the year in seasonally ice-covered waters for a) and c) the Northwest Passage routes, and b) and d) the Arctic Bridge routes. Red and blue squares indicate the median day of opening and closing; the 10th and 90th percentiles are indicated by whiskers (darker grey). In a) and b), a route is considered navigable on a given day if either branch of the shipping route, shown in the map in e), has sea ice concentration below 15%, making it “ice free” and navigable for any vessel. In c) and d), a route is considered navigable where sea ice thickness is less than 95 cm, for which Polar Class 7 vessels have a risk value of 0 based on the Polar Operational Limit Assessment Risk Index System. Global warming level is relative to the pre-industrial (1850 to 1900) baseline. Data source: temperature, sea ice concentration, and sea ice thickness output from 17 bias-corrected CMIP6 model simulations.

6.3.4: Knowledge gaps

1) There are great uncertainties about past sea ice thickness.
As mentioned in section 6.3.1.2, temporal and spatial observations of sea ice thickness in the Canadian Arctic Archipelago are sparsely available. Manual observations of ice thickness have been systematically collected by the Canadian Ice Service at several Arctic stations and communities since the 1950s (R. D. Brown & Cote, 1992; Howell et al., 2016), but their spatial coverage is limited and the record ends once the ice is no longer landfast during spring. More recently, instruments equipped with upward-looking sonar that can take sea ice thickness measurements have been sporadically installed on the ocean floor throughout the Canadian Arctic Archipelago and provide year-round records of ice thickness (Babb et al., 2021; Kirillov et al., 2020; Melling, 2022), but there is no continuous long-term record. Drill hole measurements from the 1970s are available for the northern Canadian Arctic Archipelago (Melling, 2002), with a few airborne ice thickness surveys in the western Canadian Arctic Archipelago (Haas & Howell, 2015) and ice-based surveys in the eastern Canadian Arctic Archipelago (Melling et al., 2015), but these also do not provide long-term records. Improved coordination and consistency in observing ice thickness in the Canadian Arctic Archipelago (including by better coordination with other knowledge systems) would improve understanding of the ice pack, and continuing efforts to overcome the limitations of satellite altimetry over landfast ice are of particular interest. 

Sea ice thickness estimates from satellite altimetry are poorly constrained due to uncertainties about the thickness of snow on sea ice. Observations of snow on sea ice are not available with spatial and temporal consistency across the Canadian Arctic. In-situ observations are limited to coastal-based measurements collected at the same times as ice thickness measurements.

2) Model uncertainties still exist because of a variety of factors.

Four knowledge gaps related to projections of sea ice are highlighted here: 1) coarse spatial resolution, 2) biases toward too little sea ice (and excessively long seasonal ice-free periods) in many Canadian waters, 3) poor representation of the thickest sea ice along the northern edge of the Canadian Arctic Archipelago, and 4) uncertainty about a growing diversity of methods used to try to reduce model uncertainty. 

The first issue (coarse spatial resolution) is especially limiting for projections in the Canadian Arctic Archipelago, where most climate models have difficulty resolving local-scale sea ice dynamics in the narrow and intricate channels. Coarse resolution also prevents these climate models from distinguishing coastal landfast ice in many regions. Arctic-average and Arctic-integrated model projections are often analyzed (for example, Long et al., 2021; Notz & SIMIP Community, 2020; Shen et al., 2021), but more regional analysis of model projections (Årthun et al., 2021; A. Smith et al., 2020) is required to assess impacts. 

The second issue is that models included in CMIP6 do not always accurately reproduce observed sea ice seasonality as measured by satellites in the southern Beaufort Sea, in Hudson Bay, and on Canada’s east coast, where simulated sea ice breakup is too early, freeze-up is too late, and the ice-free period is 30 to 45 days too long on average compared to observations (Crawford et al., 2023). Similar biases were present in CMIP5 models (Kushner et al., 2018; Laliberté et al., 2016). Why this happens is an active area of research. Variation in the sea ice averages and trends among climate models may arise from different equations and parameters to describe sea ice (Keen et al., 2021; J.-G. Lee & Ham, 2023; Tandon et al., 2018). They may also arise from differences in equations and parameters that describe atmospheric processes (Crawford et al., 2023; Luo et al., 2021; Topál & Ding, 2023; Topál et al., 2020), oceanic processes (Y. J. Lee et al., 2023; Watts et al., 2021), radiative transfer (Topál et al., 2020), or even biomass burning (DeRepentigny et al., 2022). Regardless of its origin, the notable presence of bias in models of the Canadian Arctic’s sea ice (especially its average state) must be accounted for when making projections. Recently, sources of bias have been isolated and addressed for a few specific models (such as sea ice albedo in CESM2; Kay et al., 2022), but other sources of bias remain unresolved. Possible sources of bias include formulations and parameterizations of the sea ice model components (Keen et al., 2021; J.-G. Lee & Ham, 2023; Tandon et al., 2018), and biases in the atmospheric, oceanic, and biogeochemical components of climate models that can influence the sea ice (for example, Crawford et al., 2023; Y.-H. Kim et al., 2023; Ward & Tandon, 2024). This wide array of possible sources of bias limits progress on reducing the errors of ensemble-mean estimates. 

A third issue is that many models struggle to reproduce the thickest sea ice regime along the northern edge of the Canadian Arctic Archipelago (Henke et al., 2023), and the vast majority of CMIP6 models produce thinner sea ice than historical estimates from the Pan-Arctic Ice Ocean Modeling and Assimilation System for both the central Arctic Ocean and Hudson Bay (Crawford et al., 2023). Reducing bias and uncertainty in long-term simulations of sea ice thickness is more difficult than sea ice concentration because of existing uncertainties of observational datasets, most of which are available for limited years (Y. J. Lee et al., 2023; Watts et al., 2021). Correlations of the spatial patterns of sea ice thickness are low (0.18–0.46) between CMIP6 and ICESat-1 (2003–2008), but higher (0.47–0.64) between CMIP6 and CryoSat-2 (2011–2014) (Watts et al., 2021). The great uncertainty about past sea ice thickness (discussed above) is also limiting, which demonstrates the potential for other knowledge systems to help evaluate climate model output.

Finally, the fourth issue is that, as the number of climate models has grown, sea ice scientists have tried increasingly to narrow the model uncertainty range in projections. This is a change from the previous standard of using a “model democracy,” where each model receives equal weight to produce a multi-model mean. The process of narrowing uncertainty typically involves comparing simulations of past conditions to some observational (or quasi-observational) record and then either (i) selecting a subset of models, (ii) assigning different model weights in a multi-model mean, or (iii) applying some constraint or bias-correction to each model before calculating a multi-model mean. A variety of parameters can be used to determine which models are “better” or “worse” at matching observations. These parameters include how well the model represents past sea ice states, how well it represents past sea ice trends, and how sensitive the model is to forcing variables such as global surface air temperature or cumulative greenhouse gas emissions.  Additionally, even if accurate simulation of sea ice is what is most desired, a model might be evaluated based on some related variable like the regional temperature or atmospheric circulation. Because of the diversity of options for reducing uncertainty, the ironic result is that this exercise introduces a new source of uncertainty. For example, depending on the method used to narrow uncertainty, the very likely range for the first year in which the Arctic is ice-free in September under the low emissions scenario (SSP1-2.6) may be as early as 2010 and as late as never (Bonan et al., 2021; Jahn et al., 2024), but taking the simple model democracy from Notz and the Sea-Ice Model Intercomparison Project Community (2020) yields a very likely range between 2010 and 2085.

6.3.5: Confidence terms in key messages: summary of evidence

Key message 6.4: Sea ice cover has declined in Canadian waters over the past four to five decades (very high confidence). Regions once covered by thick, multi-year sea ice are now covered by thinner seasonal sea ice that melts every summer (very high confidence). Landfast ice cover, which provides habitat for wildlife and is important for transportation, hunting, and the culture of northern communities, has also declined across the Canadian Arctic and Hudson Bay region (high confidence).

Key message 6.5: The transport of sea ice from the central Arctic Ocean into Canadian Arctic waters has increased over the past two and a half decades (high confidence). This increased transport of sea ice out of the central Arctic Ocean depletes its reserves of thick, multi-year sea ice, while the corresponding flow of multi-year ice into southern Canadian Arctic waters, such as the Northwest Passage, creates hazardous conditions for shipping.

Key message 6.6: The sea ice–free period is projected to lengthen further across Canadian Arctic and Hudson Bay waters with increasing climate warming (very high confidence). In regions with seasonal sea ice cover, the number of ice-free days is projected to increase by approximately one month for each degree of global warming, with smaller increases in the Labrador Sea and larger increases in the Beaufort Sea (medium confidence). The transport of multi-year ice into the Northwest Passage is projected to continue beyond mid-century thereby continuing to limit the shipping season (medium confidence).

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because most attribution studies have been done for changes in sea ice for the Arctic region as a whole. Despite the lack of formal attribution studies specific to Canada, we assess that human-caused climate change is certain to be influencing sea ice in Canadian waters (section 6.3.2).

With respect to Key Message 6.4, our very high confidence in past declines in sea ice cover is based on an established dataset with trends reported in this chapter for total sea ice area and multi-year ice area that are consistent with previous trend assessments (Mudryk et al., 2018; Tivy et al., 2011) and with numerous studies based on passive-microwave observations (Comiso et al., 2017; Parkinson & DiGirolamo, 2021; Stroeve et al., 2012; Stroeve & Notz, 2018). Note that while the key message uses the general term of Canadian waters, we only considered sea ice across the Canadian Arctic, Hudson Bay region, and Canadian east coast (Figure 6.6). We have high rather than very high confidence in reported changes in landfast ice because although they are based on a quality-controlled dataset, it has been compared with fewer other sources of information (Howell et al., 2016).

With respect to Key Message 6.5, we have high confidence in the increased transport because the results are consistent with multiple studies that have demonstrated reduced efficiency in the ice arches that control the exchange of sea ice between the Arctic Ocean and Canadian Arctic (Howell & Brady, 2019; Kwok et al., 2010; G. W. K. Moore, Howell, Brady, et al., 2021; G. W. K. Moore & McNeil, 2018; Vincent, 2019). The statement of fact describes the consequences of sea ice transport caused by the general circulation of sea ice over the entire Arctic Ocean and known shipping hazards associated with travel through regions where multi-year ice is present.

With respect to Key Message 6.6, our very high confidence in the projected length of the sea ice–free period arises from robust agreement among multiple generations of climate models in the declines of sea ice cover consistent with those shown in Figure 6.13 and with good physical understanding of the factors driving the changes. Additionally, although observational sea ice trends are stronger than simulated trends in the Canadian Arctic, the difference in magnitude cannot be distinguished from the effects of internal climate variability (Crawford et al., 2021; England et al., 2025). The value of approximately one month comes from two studies of the seasonal ice-free period using CMIP6 models (Crawford et al., 2021, 2023), which is similar to values from CMIP5 studies (Lebrun et al., 2019; M. Wang et al., 2018) once differences in reporting methods are taken into account. Precise values are provided in Table 6.1. Therefore, we have very high confidence that the sea ice–free season is lengthening, but medium confidence in the size of the trend and how it varies among different regions. Numerous studies have examined the transition from perennial to seasonal sea ice cover in the Arctic Ocean using CMIP6 models, and although estimates of the exact timing vary, a consistent result is that the central Arctic Ocean transitions to seasonal sea ice before the northern part of the Canadian Arctic Archipelago (the Queen Elizabeth Islands) and the Lincoln Sea (Fol et al., 2025; Jahn et al., 2024; G. W. K. Moore et al., 2019). Although, we have high confidence that thicker multi-year ice will continue to collect in the Northwest Passage after the Central Arctic Ocean transitions to being seasonally ice-free, large uncertainties about the timing of that transition combined with uncertainties about the Northwest Passage itself result in our only medium confidence that it will be beyond mid-century before multi-year ice is no longer common in the passage. Our assessment that the presence of multi-year ice in the Northwest Passage will continue to limit shipping is based on an assumption that there will be no new developments in the capabilities of ships to respond to the presence of multi-year ice.

6.4: Lake and river ice

Key message 6.7: Lake ice duration has shortened in Canada as a whole over the past four decades (high confidence). Lake ice duration has shortened in northern Canada, British Columbia, southern Ontario, and parts of Atlantic Canada by one to four weeks, while lake ice duration has lengthened across central Canada by up to two weeks (medium confidence). The timing of river ice breakup during spring has changed in response to temperature, and the number of mid-winter breakups is increasing in Canada (medium confidence).

Key message 6.8: Lake ice duration is projected to shorten across Canada as climate warming increases, leading to corresponding decreases in maximum ice thickness (very high confidence). River ice duration and thickness are also expected to decrease generally with increasing climate warming (high confidence), but there is low confidence that such changes will be consistently accurate for individual rivers.

Canada has an abundance of freshwater with the densest and most expansive coverage of lakes in the world and a network of rivers traversing the breadth of the country (Figure 6.15) (Messager et al., 2021). Freshwater lake and river ice is a major component of the cryosphere and affects biological, physical, chemical, and hydrological processes (Burrell et al., 2023; Hampton et al., 2017). Lake and river ice make a wide range of winter recreation activities possible, with cultural and economic benefits for local communities (Knoll et al., 2019; Sharma et al., 2023). In northern regions, they form crucial travel and transportation links, improving community access (Stephenson et al., 2011), access to traditional food (Ford et al., 2008), and resupply (for example, see Box 6.4 on Canada’s network of winter roads that rely on lakes and rivers freezing over). River ice can have major socio-economic impacts through constraints on transportation and navigation, interference with water supply facilities and hydropower generation, and ice-related flooding (Huokuna et al., 2022; Rokaya et al., 2018a). Costs from ice jam–related flooding alone is estimated to cause US$300 million or approximately Can$400 million of damage in 2017 dollars annually across North America (French, 2018; Rokaya et al., 2018b). Biologically, ice governs under-ice ecosystem processes when atmospheric contact with water is almost entirely inhibited (Powers et al., 2017; Thellman et al., 2021). Limited light and unique biogeochemical environments (Powers et al., 2022) impact everything from fish persistence (Block et al., 2020) to oxygen availability (Obertegger, 2022).

Figure take-away: Canada has some of the most expansive freshwater coverage in the world.

Figure title: River networks and lake fraction across Canada with photo of small lakes northeast of Lake Winnipeg

Figure 6.15: Maps and a photo of Canada’s expansive freshwater coverage. River network across Canada (middle) where line thickness indicates typical river discharge (thin line, 10–100 m³/s; medium line, 100–1000 m³/s; thick line, > 1000 m³/s). Lake cover across Canada (top) where shading indicates the fraction of a 10-km x 10-km region that is covered by lakes, with a red square highlighting the region in the photo (bottom), which illustrates many small lakes not evident at the scale of the map. Data source: lake and river data from HydroLAKES and HydroRIVERS (Seamless hydrographic data for global and regional applications); photo is an image taken by the NASA MODIS sensor.

The extent and thickness of freshwater ice are indicators of climate change (Adrian et al., 2009; Magnuson et al., 2000). A warming climate alters the timing of ice formation and melt on rivers and lakes, shortens ice cover duration, and reduces ice thickness, especially the maximum thickness attained toward the end of the winter. In addition to altered ice timing and reduced ice thickness, warmer winter temperatures and altered precipitation patterns can affect the quality of the ice that forms on rivers and lakes (Dibike et al., 2011). Lower-quality ice is less dense and has a reduced capacity to bear weight, with implications for safety (Culpepper, Jakobsson, et al., 2024; Woolway et al., 2022). Lower-quality ice is also less transparent and therefore decreases the amount of light that penetrates through to the water below, which has ecological consequences (Weyhenmeyer et al., 2022a). In rivers, climate change can also alter how often ice jams form and their severity (Box 6.5), with implications for the chances of flooding (Rokaya et al., 2018b). Because flow in rivers is much faster than the relatively slow circulation of water that occurs in lakes, different processes must be considered for river ice compared to lake ice. For this reason, river ice and lake ice are discussed separately in the following sections.

6.4.1: Past changes

6.4.1.1: Lake ice timing, duration, and thickness

Studies of lake ice phenology can be difficult to interpret because the number of available records depends heavily on the time period analyzed. For lakes with long-term records (75 to 100 years), ice cover duration has shortened by about 6 to 17 days per century or about 0.6 to 1.7 days per decade (A. M. W. Newton and Mullan, 2021; Sharma, Richardson, et al., 2021). However, these long-term records are biased toward two locations, northern Europe (primarily Sweden and Finland) and the Great Lakes region of North America. Over shorter periods, data is more broadly available, and studies have reported trends in ice cover duration with losses as large as 6 to 11 days per decade based on analysis periods of 25 to 30 years. While shorter analysis periods can intrinsically yield stronger trends, by examining progressive segments of the record, studies have shown that the rate of ice loss has increased over the course of the 20th century and into the 21st century (A. M. W. Newton and Mullan, 2021; Sharma, Richardson, et al., 2021). In these and similar studies, changes in the timing of ice melt (for example, towards earlier breakup) have usually been stronger and easier to detect than changes in the timing of ice formation (for example, towards later freeze-up), consistent with simulated ice formation and melt in models (Benson et al., 2012).

There are far fewer measurements of lake ice thickness than lake ice duration, and attempts to examine the measurements available have found no systematic trends (Imrit et al., 2022). Even for lake ice timing, the number of field measurements has decreased in recent decades after peaking during the period from 1960 to 1995 (Murfitt and Duguay, 2021). In place of the decreasing number of field measurements, studies have examined the potential for a range of satellite-borne sensors to provide information on lake ice timing and thickness, including sensors capable of observing visible wavelengths, microwave wavelengths (both passive and active sensors), and satellite altimeters (Dauginis and Brown, 2021; Du et al., 2017; Kang et al., 2014; Kheyrollah Pour et al., 2017; X. Li et al., 2023). While such measurements are accurate, especially in the case of ice timing, the high-resolution information needed to observe small lakes has generally been available for too short a period to assess climate-driven trends (see Knowledge Gaps in section 6.4.4). An exception is visible satellite records using Landsat, which can extend back to 1985, but which cannot provide information in polar regions during winter. Analysis of this satellite information indicates the formation of ice cover on lakes in the temperate zone of the Northern Hemisphere decreased by about 50% during January to March from 1985 to 2020 (X. Wang et al., 2021).

Given the sparse field measurements and relatively short period covered by satellite records, an alternative is to simulate the timing of lake ice formation and melt with a model driven by past temperatures and other relevant meteorological conditions. Of particular importance for lakes in Canada is that snow must be accounted for to obtain accurate ice thickness values, since it insulates the ice below and can contribute to the formation of white ice (Kheyrollah Pour et al., 2012). The Canadian Lake Model (Duguay et al., 2003) takes snow into account and has been validated against both field measurements and remote-sensing data and shown to accurately simulate the timing of ice formation, melt, and thickness (L. C. Brown and Duguay, 2011a; Duguay et al., 2003; Ménard et al., 2002). Here, we provided past changes in lake ice duration from this model driven by historical estimates of near-surface air temperature, snow depth, and other meteorological conditions from ERA5-Land (Figure 6.16).

Figure take-away: Over the past four decades, lake ice duration has shortened across much of Canada but lengthened over parts of central Canada and southern Quebec.

Figure title: Past changes in lake ice duration in Canada

Figure 6.16: Map with colours showing change in duration of lake ice cover across Canada from 1979 to 2021. Data source: output from the Canadian Lake Ice Model driven by historical estimates of near-surface air temperature, snow depth, and other meteorological conditions from ERA5-Land.

Changes in lake ice duration from 1979 to 2021 range from losses of three to four weeks across parts of British Columbia (an average rate of about six days per decade), one to three weeks across much of northern Canada, southern Ontario, and parts of Atlantic Canada (about three days per decade), and increases of up to two weeks across some regions of central Canada (Figure 6.16). This pattern of losses in both northern Canada and maritime regions of the country but increases over central Canada is consistent with hemispheric studies (Grant et al., 2021) and roughly consistent with changes in snow cover duration (section 6.2). Past changes in lake ice cover duration for Canada as a whole from the Canadian Lake Ice Model (weighted for where lakes are more numerous) amount to a decrease of approximately 1.5 days per decade (Figure 6.17), which is on the upper end of long-term observation-based estimates but smaller than recent hemispheric averages (Sharma, Richardson, et al., 2021).

Figure take-away: The number of days with lake ice cover decreased for Canada as a whole from 1979 to 2021.

Figure title: Change in lake ice duration for Canada as a whole from 1979 to 2021

Figure 6.17: Annual deviation in the number of days with lake ice cover in Canada as a whole from 1979 to 2021. Blue bars indicate years that had more days with lake ice cover than the average, while pink bars indicate years with fewer days of lake ice cover than the average. The black dashed line depicts the overall trend. Data source: output from the Canadian Lake Ice Model driven by historical estimates of temperature, snowfall accumulation, and other meteorological conditions from ERA5-Land.

6.4.1.2: River ice timing, duration, and severity

Studies using data from Canadian hydrometric stations (stations that collect data on water resources) indicate both earlier and later timing of river ice breakup across Canada, depending on the location, over the period from 1970 to 2016 (Figure 6.18). Although the station trends vary markedly with location, the majority of stations show trends towards earlier breakup (Y. Chen and She, 2020), and the year-to-year variation in break-up date is strongly correlated with year-to-year variability in spring temperature (Y. Chen and She, 2020; Dibike, Hartmann, et al., 2021; A. M. W. Newton and Mullan, 2021; von de Wall et al., 2010). Spatial patterns for river ice freeze-up (not shown) are generally more complex than for river ice breakup (Lacroix et al., 2005; Thellman et al., 2021).

River ice severity describes the processes associated with major ice jams that cause flooding or have other socio-economic and ecological effects, whether negative or positive (see Box 6.5 on river ice jams and Chapter 5, section 5.7 on floods). Ice jams can form during both freeze-up and breakup. Breakup jamming is typically more severe because the flow of many rivers in Canada peaks during spring and is lower during fall. For regulated rivers, which have their flow rates managed, this may not be the case. The peak instantaneous water level that occurs during the breakup event is commonly used as an indicator of breakup severity. Data from numerous Canadian rivers revealed both decreasing and increasing water level trends (in centimetres per decade) over different time periods, extending as far back as the early 20th century (Beltaos, 2004; Curi et al., 2021; Dibike, Hartmann, et al., 2021; Poulin et al., 2021; Turcotte et al., 2019). The magnitude of breakup discharge is a weak indication of flooding potential when used without additional evidence. For any given discharge, peak water levels during breakup can vary widely, depending on whether a sizeable ice jam forms nearby. For many northern rivers, a single spring breakup event is the norm. Occasionally, a few days of mild weather accompanied by significant rainfall may raise discharge and water level enough to trigger breakup of the ice cover, sometimes more than once during a single winter. These are called mid-winter breakups (Beltaos, 2002; Janowicz, 2010; Turcotte et al., 2020). For this assessment, “winter” refers to the period between the initial formation and final breakup of the ice cover and may extend beyond the calendar limits of the winter season. Mid-winter breakup can be more severe than a spring event (for example, the winter 2018 flood in Grand River, Ontario) (Curi et al., 2019), since jams formed mid-winter will freeze in place upon resumption of cold weather and can prime more persistent jams during the next breakup event. Across Canada, mid-winter breakups have occurred with increasing frequency (Figure 6.1.9) (De Coste et al., 2022).

Figure take-away: River ice breakup trends across Canada show regional variation in timing from earlier to later.

Figure Title: Changes in timing of river ice breakup across Canada from 1970 to 2016

Figure 6.18: Map with colours showing changes in timing of river ice breakup across Canada from 1970 to 2016. Circles indicate site location and colours reflect the sign and magnitude of the change. Data source: Y. Chen and She (2020).

Figure take-away: The number of mid-winter breakups in Canada has increased since 1955

Figure title: Number of mid-winter breakups in Canada from 1955 to 2015

Figure 6.19: Number of mid-winter breakups identified in the Canadian River Ice Database from 1955 to 2015, including trendline. The trend is statistically significant at the 5% level (meaning there is ≤ a 5% chance of concluding that an effect or trend exists when it does not). Data source: De Coste et al. (2022).

6.4.1.3: River ice thickness

The thickness of river ice in winter is a key consideration in the safety of river crossings when winter roads are built in northern Canada for transportation. Additionally, the maximum thickness reached by the ice cover before a breakup event is one of the factors that control ice jam formation. For example, thin ice is less likely to block the large chunks of mobilized ice and rubble that can lead to ice jams. On the other hand, extremely thick ice is more likely to disintegrate in place rather than be mobilized by rising flow and produce enough ice rubble to contribute to other jams. Trends toward thinner ice cover in rivers have been reported in studies for the Northern Hemisphere, including at two Canadian sites (Beltaos and Prowse, 2009; Burrell et al., 2023). Rates of thinning over periods of at least 30 years typically amounted to a few millimetres per year. However, recent trends on six different rivers in Yukon indicate rates of late-winter ice thinning of 8 to 18 mm/yr over periods of 13 to 23 years, which is consistent with declines in overall winter coldness as measured by accumulated freezing-degree-days (Turcotte et al., 2019). Concerns over deteriorating environmental conditions in the Peace–Athabasca Delta, including reduced ice thickness and quality, led to the implementation of community-based monitoring programs operated by the Mikisew Cree First Nation since 2008 and the Athabasca Chipewyan First Nation since 2010. Among other environmental variables, ice thickness and quality are tracked at select sites throughout each winter (Maclean et al., 2021). A data-based regional ice growth model has been developed, enabling calculation of maximum seasonal ice thickness going back to the winter of 1920 to 1921. The model indicated a loss of 8 cm over the subsequent 100 years (Maclean et al., 2021), while the rate of thinning appears to have been higher during the past approximately 50 years.

6.4.2: Causes of past changes

Ice in a body of water such as a lake or river will be affected by two general types of factors: the local climate conditions; and secondary characteristics related to the body of water itself, such as its size, shape, and speed of flow. The local climate conditions are typically related to where a lake or part of a river is located. For example, how far north (latitude), how far inland, and at what elevation a body of water is located will determine the range of seasonal air temperatures, the amount of snowpack, the typical cloud cover (which affects incoming and outgoing radiation), and whether there are important climate teleconnections that influence the region’s weather (Beltaos and Prowse, 2009; L. C. Brown and Duguay, 2010; Prowse et al., 2007; Turcotte et al., 2012). Among these climate conditions, air temperature is the main variable affecting freshwater ice cover and thickness, as ice can form only when air temperatures remain consistently below 0°C (L. C. Brown and Duguay, 2010; Dibike, Hartmann, et al., 2021; Palecki and Barry, 1986; Warne et al., 2020).

For individual lakes, local air temperature conditions can fluctuate from year to year, and these temperature fluctuations exert the largest control on year-to-year variations in the timing of ice formation and melt, and in total ice duration (Imrit and Sharma, 2021). These regional fluctuations in temperature are typically driven by internal climate variability (Chapter 3, section 3.3.3), which means that lake ice timing trends will also be at least partially driven by internal climate variability, especially over shorter time periods. However, even for individual lakes, long-term trends in ice cover timing are detectable (Imrit and Sharma, 2021), and when examining the average response of lakes across the Northern Hemisphere, the long-term warming signal becomes the dominate control on lake ice timing (Benson et al., 2012). The strength of the response to temperature is why for the Northern Hemisphere as a whole, the loss of freshwater ice (whether indicated by shorter ice cover duration or reduced ice thickness) has been attributed to human-caused warming driven by greenhouse gas emissions (Grant et al., 2021). Local snow conditions also exert influence on lake ice conditions (L. C. Brown and Duguay, 2010; Duguay et al., 2003; Jensen et al., 2007). For example, snow acts as an insulator, so during winter a layer of snow on ice will slow the rate at which ice continues to form below the snow, while during spring the ice on lakes covered by a deeper snowpack will take longer to melt than the ice on lakes covered by a shallower snowpack. However, snow can also contribute to the overall ice thickness when a portion of the snowpack mixes with water and freezes to form white ice (L. C. Brown and Duguay, 2010), which is weaker and allows less light to penetrate through the ice to the water below. Beyond climate-related factors, lake-specific characteristics such as surface area and depth can also alter the timing of ice and its growth rate (Basu et al., 2024; Nõges and Nõges, 2014; Rafat et al., 2023) because these characteristics affect wind fetch, water circulation, and temperature, as well as heat storage. These effects are more prominent in larger lakes (Rouse et al., 2008).

For rivers, climactic variables beyond temperature, such as snow, rain, solar radiation, and cloud cover, can directly affect river ice phenology and thickness (Beltaos and Prowse, 2009; Turcotte et al., 2012), but the flowing nature of rivers adds complex hydrodynamics that are often important. These hydrodynamics are controlled by river-specific characteristics, such as channel size and slope, shape, orientation, and discharge hydrograph, which is a graph showing how the river discharge changes over time during a specified interval, such as a year, month, etc. (Turcotte and Morse, 2013). Some of these factors themselves depend on climate, adding complexity to projected river ice changes under different climate conditions. For example, a high level of autumn discharge tends to delay ice cover formation; a high level of spring discharge tends to advance breakup and increase the severity of ensuing ice jams; and a high level of mid-winter discharge resulting from a brief thaw and rainfall can cause mid-winter breakup and jamming (Beltaos and Prowse, 2009; Gebre and Alfredsen, 2011; Turcotte et al., 2020). The elevation of the body of water into which a river may drain (such as another river, a lake, or an ocean) can also influence ice processes a considerable distance from the mouth of the river. It is beyond the scope of this report to detail the physical mechanisms that control river ice regimes and their numerous climate-related linkages. Such information can be found in recent reviews, each containing an extensive bibliography (Beltaos, 2021; Beltaos and Prowse, 2009; Thellman et al., 2021). The fact that both geomorphology and flow underpin ice formation in rivers makes it extremely difficult to predict how river ice will change in a warming climate in general terms on a large scale.

6.4.3: Future changes

6.4.3.1: Lake ice timing and duration

Because lake ice is strongly controlled by air temperature, how lake ice duration and thickness change over the near term (2021 to 2040) and through the rest of the 21st century will depend primarily on future levels of global warming. Current state-of-the-art lake ice models project lake ice duration for the Northern Hemisphere to shorten on average by 9 to 10 days for every 1°C rise in global average temperature (Grant et al., 2021; Huang et al., 2022). In response to warming temperatures, ice is projected to form later and melt earlier, but changes in ice breakup are projected to be larger (Grant et al., 2021). For lakes located in southern Ontario and Quebec or some locations along the west coast of British Columbia, sufficient warming under a very high emissions scenario (RCP8.5) could lead to complete loss of ice cover by the end of the 21st century (Sharma, Blagrave, et al., 2021).

Otherwise, most lakes in Canada are not expected to lose ice cover entirely this century but are expected to have shortened lake ice duration comparable to or greater than the Northern Hemisphere average. This assessment is based on updated projections provided here from the Canadian Lake Model (Duguay et al., 2003) driven by future estimates of temperature, snow depth, and other meteorological conditions from two CMIP6 models (Figure 6.20). The projections indicate that lake ice duration in Canada is expected to shorten by at least 10 days for every 1°C rise in global average temperature and across much of the country by 14 to 21 days for every 1°C rise in global average temperature. These projections are in line with other model studies that report changes of 15 to 50 days across the country over a period of time with an approximately 2°C rise in global average temperature (L. C. Brown and Duguay, 2011b; Dibike et al., 2011).

Figure take-away: Lake and river ice duration is projected to shorten across Canada with rising global average temperature.

Figure title: Future changes in lake and river ice duration across Canada per degree Celsius of global warming

Figure 6.20: Maps with colours showing projected changes in lake (left) and river (right) ice duration across Canada for each 1°C rise in global average temperature. Data source: for lake ice, Canadian Lake Ice Model simulations of lake ice forced by projections of surface temperature, snow depth, and other meteorological conditions from two CMIP6 models (lake ice projections); for river ice, temperature output from an ensemble of CMIP6 models (see details in text).

6.4.3.2: Lake ice thickness

With rising global average temperatures, annual maximum ice thickness is also projected to decline for the Northern Hemisphere as a whole and across Canada. Projected losses for the Northern Hemisphere as a whole by the end of the 21st century are 18 cm under a low emissions scenario (RCP 2.6), 26 cm under a high emissions scenario (RCP6.0) and 35 cm under a very high emissions scenario (RCP8.5) (X. Li et al., 2022). Because warming is projected to be higher in the Canadian Arctic, losses of annual maximum ice thickness will be greater there (Huang et al., 2022; X. Li et al., 2022). Canadian lake ice is crucial for transportation and travel in many Canadian communities (see Box 6.4 on winter roads), and the decreases in lake ice thickness projected with continued warming could interfere with such transportation routes (Woolway et al., 2022).

6.4.3.3: River ice timing, duration, and severity

It has been difficult to account for the influence of river discharge on projections of river ice timing, duration, and severity, because the hydrological models that attempt to represent those relationships do not accurately reproduce historically observed discharge. Therefore, many authors have adopted approaches that focus on air temperature alone or air temperature plus total winter and summer precipitation. As an example, previous studies have projected changes in the timing of when temperatures drop below 0°C in the fall and the corresponding timing of when they return above 0°C in the spring (Prowse and Bonsal, 2004, using a previous generation of CMIP models). These studies find that the onset of below-freezing temperatures in the fall will be delayed, while above-freezing temperatures in the spring will come earlier, leading to shorter durations of below-freezing temperatures. Such changes can be used as a proxy for changes in river ice duration, since ice requires air temperatures below freezing to form and thicken. Here, we provided updated projections based on this method using the most recent generation of CMIP6 models (Figure 6.20). The model projections indicate that across Canada, river ice duration will be shorter by between 10 to 21 days for each 1°C rise in global average temperature. This is reasonably consistent with hemispheric projections for the end of the century under a very high emissions scenario (SSP5-8.5) (X. Yang et al., 2020). Projections for specific Canadian rivers also exist but are based on previous generations of CMIP models (Andrishak and Hicks, 2008; Beltaos et al., 2006). For example, for a Peace River site near the Peace–Athabasca Delta, river ice duration was projected to be four weeks shorter by the end of the century under a very high emissions scenario (SSP5-8.5) (Beltaos et al., 2006), which is consistent with Figure 6.20 and with hemispheric projections (X. Yang et al., 2020). However, there is limited confidence that these projections of shorter ice duration can be generalized and accurately applied to specific rivers, because they do not account for climate-related factors beyond air temperature, nor do they account for the influence of water flow or how these additional factors will, themselves, be altered by climate change.

Quantitative calculations of ice jam severity involve great uncertainty (Beltaos, 2021). As a result, model projections of ice jam severity can vary depending on location and even on methodology for bias correction of hydrological models (Beltaos et al., 2006; Lamontagne et al., 2021; Mahabir et al., 2007; Rokaya et al., 2018b, 2020). In qualitative terms, mid-winter breakups are expected to become more frequent and occur increasingly farther north, which is expected to result in more frequent ice jams. However, changes in ice jam severity will depend on changes in the size of the prevailing river flows, since these determine flooding potential. In coastal rivers, rising sea level (Chapter 7, section 7.4) may cause favourable conditions for ice jam formation to move much farther upstream (Beltaos and Prowse, 2001). The same mechanism may also operate where a river discharges into a lake or another river if local or regional conditions raise respective levels. Because the climate is warming faster in northern Canada than in southern Canada (Chapter 4, section 4.2), the thermal gradient encountered by north-flowing rivers will decrease in the future. Other factors being equal, this outcome will tend to shorten ice cover duration and reduce the frequency of the most severe ice jams (AMAP, 2021a; Thellman et al., 2021). The chance of ice-related flooding for riverside communities and infrastructure will differ on a case-by-case basis and will depend on recent local trends in relevant variables (Burrell et al., 2024). Local-scale variation has implications for the ongoing national flood hazard assessment program [accessed Dec. 20, 2024].

6.4.3.4: River ice thickness

The simplest approach to projecting changes in river ice thickness in a changed climate is to relate ice thickness to seasonally accumulated freezing-degree days (Stefan, 1891). This approach has been used to project changes for specific rivers with comparable results for both CMIP5 and CMIP3 models (Beltaos et al., 2006; Lamichhane et al., 2022). In both studies, authors found declining annual maximum river ice thickness consistent with continued warming and shorter ice cover duration. In addition, the influence of snow cover (Ashton, 2011) has been modelled across the Northern Hemisphere (Park et al., 2016) and for specific rivers (Beltaos et al., 2006). To account for the effects of additional factors, such as cloud cover (Imrit et al., 2022), numerical models developed for lake ice growth may be helpful.

6.4.4: Knowledge gaps

1) There is a lack of current and past freshwater ice observations across Canada.

For rivers, there are historically fewer ice phenology records (for example, freeze-up or breakup timing records) than for lakes (Beltaos and Prowse, 2009; Thellman et al., 2021). A global river ice database was made available only in the last few years (X. Yang et al., 2019). Moreover, this database is limited to ice occurrence on rivers more than 90 m across, essentially limiting data to only the largest rivers on Earth. A Canadian River Ice Database also exists (de Rham et al., 2020) but has not been updated since the end of 2015. While there are historically more ice phenology records for lakes than for rivers, they have been declining since the 1990s (Murfitt and Duguay, 2021), when many of the lake ice records stopped in the Global Lake and River Ice Phenology Database and the Canadian Ice Database (Benson et al., 2000; Lenormand et al., 2002). Observations of variables not related to phenology, such as ice thickness or ice quality, are very sparse (Murfitt and Duguay, 2021). While obtaining field observations is logistically challenging, lake ice occurrence and thickness are considered essential climate variables crucial to characterizing the Earth’s climate (WMO, 2021). They are also critical for validating model simulations, especially satellite measurements, because, while model simulations of historical periods can be validated with past data, new satellites require contemporaneous ground measurements to validate.

2) There are challenges in using remote-sensing observations.
Satellite measurements from both optical and microwave sensors can be used to determine the presence of ice cover and have been available since the 1970s, but trade-offs in spatial and temporal resolution have limited their use. From early satellites, observations of a particular location could be available frequently, but at a relatively coarse spatial resolution, limiting analysis to very large lakes (Cai et al., 2022), or at a high resolution, but less frequently (particularly for northern locations), meaning that the timing of ice formation and melt is not very precisely captured (Murfitt and Duguay, 2021). Since the 2000s, newer satellites have had improved combinations of spatial and temporal resolution. While studies have examined the shorter-term patterns and trends in such observations (Dauginis and Brown, 2021; Šmejkalová et al., 2016), the records are only one to two decades in length, which makes detecting signals of climate change difficult. Going forward, satellites like the Canadian RADARSAT Constellation Mission (with data available since late 2019) will provide even more frequent, high-resolution observations. These observations, combined with new data analysis techniques (for example, Engram et al., 2018; Murfitt and Duguay, 2020), are expected to provide a growing collection of ice cover timing data in the future.

Compared to those providing observations of ice timing, fewer satellites can provide the information required to measure ice thickness from space. Until recently, accurate measurements were possible only for shallow tundra lakes (Engram et al., 2018; Surdu et al., 2014) or very large lakes (Kang et al., 2014). While new methodologies have emerged using active microwave wavelengths (Antonova et al., 2016; Gunn et al., 2018; Murfitt and Duguay, 2020) or altimetry data (Beckers et al., 2017; Mangilli et al., 2022; Ye et al., 2024) to estimate lake ice thickness, ground validation data for such methods are very limited.

3) Projections of ice cover across Canada do not account for local-scale characteristics and simplify many physical processes.

Projections of lake ice across Canada have typically simulated generalized lakes rather than the real-life variety of lakes that exist across the country. For example, the range of lakes across the country would typically be modelled as each having a single constant depth, with no accounting for differences in surface area or circulation. These simplifications reflect both a lack of available data for many lakes in the country, as well as practical limits of computational resources. Likewise, projections of river ice conditions exist only for a handful of specific rivers in Canada, and many have not been updated using the most recent CMIP model output. In the case of rivers, hydrological models that can best model changes in water flow are generally not able to account for the presence of ice. This deficiency limits scientific understanding of how river flow and ice interact, particularly dynamic processes such as the onset of breakup, the transport and fate of mobilized segments of the winter ice cover, the formation and release of ice jams, and their erosion and sediment transport potential.

6.4.5: Confidence terms in key messages: summary of evidence

Key message 6.7: Lake ice duration has shortened in Canada as a whole over the past four decades (high confidence). Lake ice duration has shortened in northern Canada, British Columbia, southern Ontario, and parts of Atlantic Canada by one to four weeks, while lake ice duration has lengthened across central Canada by up to two weeks (medium confidence). The timing of river ice breakup during spring has changed in response to temperature, and the number of mid-winter breakups is increasing in Canada (medium confidence).

Key message 6.8: Lake ice duration is projected to shorten across Canada as climate warming increases, leading to corresponding decreases in maximum ice thickness (very high confidence). River ice duration and thickness are also expected to decrease generally with increasing climate warming (high confidence), but there is low confidence that such changes will be consistently accurate for individual rivers.

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because most attribution studies have been done for changes in lake ice duration for the Northern Hemisphere as a whole. Despite the lack of formal attribution studies specific to Canada, we assess that human-caused climate change is certain to be influencing lake and river ice in Canada (section 6.2.2).

With respect to Key Message 6.7, our high confidence in past changes in lake ice duration in Canada as a whole is based on historical simulations of a well-tested model that has been shown to generally agree with trends from site-specific observations. Additional confidence is provided by the strong relationship between lake ice duration and air temperature determined from process studies, as well as the pattern correlation evident in this report among trends in snow cover duration, lake ice duration, and number of days of seasonally frozen ground, all variables known to respond strongly to air temperature changes. Our medium confidence in changes in lake ice duration for certain regions across Canada reflects the increased specificity of changes with location and magnitude. We have medium confidence in the relationship between river ice breakup timing and air temperature since it is based on multiple independent studies that have been analyzed over various time periods. While this relationship is well established seasonally, it does not result in river ice duration trends that correlate with existing spring temperature trends across the country, possibly because of the influence of river-specific characteristics, as discussed (section 6.4.2). We have medium confidence in the changes in mid-winter break-ups because, although it is based on a single source, the data and analysis are strongly in agreement with theoretical expectations.

With respect to Key Message 6.8, we have very high confidence in the future changes in lake ice duration since they are based on projections from a well-tested model that has been shown to generally agree with trends from site-specific observations. We have very high confidence in the corresponding changes in lake ice thickness based on process and modelling studies linking shortened lake ice duration to reduced annual maximum ice thickness. The general expectations for changes in river ice duration and thickness are based on the strong relationship between ice cover timing and air temperature determined from process studies or analysis of proxy variables from multiple generations of climate model projections (the duration of freezing temperatures is one such variable, as presented in Figure 6.20). This leads to our high confidence in the generalized changes expected, but we have low confidence that these generalized changes accurately reflect future changes for specific rivers in Canada because the generalized projections do not account for climate-related factors beyond air temperature, nor do they account for the influence of water flow.

6.5: Glaciers

Key message 6.9: All glaciers in western Canada and the Canadian Arctic have thinned and lost mass over the past two and a half decades, as shown by satellite measurements with comprehensive spatial coverage (very high confidence). Longer-term field measurements on a small number of reference glaciers show that glaciers in Canada have been losing mass since at least the 1960s, and that the rate of loss has accelerated in recent decades (high confidence). In western Canada, declines in glacier contributions to summer streamflow have been observed in several watersheds (high confidence), marking an irreversible decrease in a critical source of freshwater for these regions.

Key message 6.10: Canada’s glaciers are projected to continue losing mass under every future emissions scenario (very high confidence). In western Canada, more than 55% of glacier ice is predicted to disappear by 2100, even if global warming is limited to 2°C (high confidence). The number and severity of glacier-related hazards, such as flooding and landslides, are expected to increase, particularly in western Canada (medium confidence). Melt water from glaciers and ice caps in the Canadian Arctic will continue to be among the largest glacier sources of global sea-level rise up to and beyond 2100 (very high confidence).

Glaciers form as snow accumulates and is compacted over centuries to millennia. Glaciers gain mass primarily through the accumulation of snowfall and lose mass (ablation) primarily through snow and ice melt and iceberg calving. Excluding the Antarctic and Greenland ice sheets, Canada’s glaciers comprise approximately 20% of the Earth’s glacier ice volume (see Figure 6.21 for maps of the glaciers in the Canadian Arctic Archipelago and western Canada). Canada’s glaciers in the Canadian Arctic Archipelago cover approximately 146,000 km², divided into two regions, defined as Arctic Canada North, spanning roughly 105,000 km², and Arctic Canada South, spanning roughly 41,000 km². Glaciers in western Canada cover approximately 39,500 km², including glaciers along the Alaskan coast that are located on the Canadian side of the border with the United States. There is also approximately 24 km² of glaciers in northern Labrador (not shown in Figure 6.21). Climate change is increasing glacier thinning and melt nearly everywhere around the globe, driven by decadal rises in temperature and shifts to more rainfall and less snowfall (Hugonnet et al., 2021). Paleo-climate records interpreted from deep ice cores show that recent summer warmth across the Canadian Arctic, a key driver of glacier melt in the region, has been unprecedented in the last several thousand years (Fisher et al., 2012).

Figure take-away: Glacier mass loss and sea-level rise have been calculated using defined regions and locations in Canada.

Figure title: Regions and locations in Canada used to calculate changes in glacier mass and sea-level rise

Figure 6.21: Maps with colours showing glaciers across Canada split into four regions. These regions are defined as Arctic Canada North (dark green), Arctic Canada South (light green), western Canada (light brown), and Alaska (dark brown), which includes glaciers in northern British Columbia and Yukon along the border between Canada and Alaska. Labelled hexagons mark the locations of seven reference glaciers where long-term field measurements are available.

The loss of glacier ice has important implications both locally and globally. In Canada, meltwater from glaciers is a source of freshwater for lakes, rivers, and groundwater (Bonsal et al., 2020; Castellazzi et al., 2019). Historically, these contributions have augmented summer streamflow, thus increasing water availability after snowmelt is finished and providing late summer cooling vital for rivers’ aquatic ecosystems. While accelerating glacier melt may temporarily increase these summer contributions, in the long term they are expected to dwindle (Huss and Hock, 2018). Declining summer water availability would have implications for drinking, agricultural, and industrial water use, as well as for ecosystem functioning (see also Chapter 5, Case Story 5.1) (Bonsal et al., 2020; J. W. Moore et al., 2023).

As an increased amount of meltwater from glaciers and ice caps makes its way to the ocean, it also contributes to sea-level rise. Canada’s Arctic glaciers and ice caps are among the greatest contributors to sea-level rise globally (Hugonnet et al., 2021; Wouters et al., 2019), with detectable contributions since the early 1990s (Box et al., 2018).

Finally, the retreat of glaciers has impacts on marine primary productivity. Glaciers that terminate in the ocean transfer nutrients from the land into the ocean (Hopwood et al., 2020). By creating upwelling from glacier meltwater discharged at depth (Bhatia et al., 2021), ocean-terminating glaciers also act to bring deep, nutrient-rich waters to the surface. As glaciers retreat, they can transition from ocean-terminating to land-terminating (Cook et al., 2019; Kochtitzky and Copland, 2022). Such changes are expected to negatively affect marine primary productivity by reducing the nutrient upwelling enabled by glacier meltwater discharge at depth (P. L. Williams et al., 2021). Combined with ongoing thinning of Arctic sea ice (section 6.3), retreat of marine-terminating glaciers is likely to pose increased challenges for sourcing traditional marine food that supports the Inuit population of this region (Bhatia et al., 2021).

As glaciers and ice caps gain or lose mass over long time scales, they slowly deform and flow, adjusting to their changing weight under the force of gravity (Zekollari et al., 2022). This adjustment time varies with the size and shape of the glacier or ice cap (Bahr et al., 1998; Zekollari et al., 2020) but is generally decades to centuries (Jóhannesson et al., 1989; Roe et al., 2017), meaning that none of the glaciers or ice caps in the world have yet fully adjusted to past warming. A consequence of this slow adjustment is that even if global temperatures stabilize, there will still be additional glacier retreat and mass loss committed from warming that occurred prior to stabilization (Christian et al., 2018; Marzeion et al., 2018). This committed but as yet unrealized mass loss will continue contributing to sea-level rise and altering freshwater availability for decades to centuries after global temperature stabilizes (Zekollari et al., 2025).

6.5.1: Past changes

Integrated research and monitoring has reduced uncertainties in understanding changes to Canada’s glaciers, which is necessary for preparing for the impacts of these changes on Canadian ecosystems and communities. Collectively, field-based, remote-sensing, and modelling investigations of glacier change in Canada offer strongly corroborated evidence that rates of glacier mass loss have remained the same or increased over the past several decades (Box et al., 2018; Hugonnet et al., 2021; Noël et al., 2018; WGMS, 2025; Zemp et al., 2019). Field measurements of glacier surface mass balance (Box 6.6) have been collected at Canada’s seven official reference glaciers (Figure 6.21) since the early 1960s and are reported in metres of water equivalent (m w.e.) per year (Cogley, 2010). While year-to-year variability exists, the cumulative finding of these records, which can be considered as vertical metres of water loss, indicate glacier-wide losses of 10 to 20 m w.e. in the Canadian Arctic and 45 to 60 m w.e. in western Canada (Figure 6.22). These measurements also show evidence of accelerated changes in both the Canadian Arctic and western Canada. The rates of glacier thinning at the four monitoring sites in the Canadian Arctic rose four-fold for the period from 2000 to 2022, relative to the forty-year monitoring period prior to 2000 (Burgess and Danielson, 2022; Gardner and Sharp, 2007). Similarly, the rates of glacier thinning at the three monitoring sites in western Canada rose three-fold since the 1970s (WGMS, 2025). In both regions, these strong trends in negative mass balance are highly correlated with summer warmth, making glacier mass balance a valuable climate indicator and one of the World Meteorological Organization’s Global Climate Observing System’s essential climate variables (Bojinski et al., 2014). Since the 1970s, increased warming augmented by extreme heat events, such as in 2021, has accelerated the melting of glaciers in western Canada (for example, Anderson and Radić, 2023; Demuth et al., 2008).

Figure take-away: Glaciers in both western Canada and the Canadian Arctic have been losing mass since the 1960s, and there is evidence of accelerated thinning in recent decades.

Figure title: Cumulative glacier mass loss from long-term field measurements of mass balance in western Canada and the Canadian Arctic since the 1960s

Figure 6.22: Cumulative mass loss calculated from mass balance measurements on seven glaciers with long-term records (since the 1960s) in both western Canada (left) and the Canadian Arctic (right). Mass loss is reported as thickness change in metres of water equivalent (m w.e.). Data source: Burgess and Danielson (2022); Thomson et al. (2017); WGMS (2025).

Broad-scale glacier change can also be determined from satellite sensor measurements that complement field observations to provide insight into glacier dynamics, thickness change, regional mass loss, and contributions to global sea-level rise. Satellite-based measurements of elevation change in metres per year^{Footnote 5} indicate that from 2000 to 2019, glaciers across western Canada had a more than four-fold increase in thinning rates, which ranged from 0.13 m/yr to 1.19 m/yr over the study period (Figure 6.23) (Hugonnet et al., 2021), making these glaciers some of the fastest thinning globally. The most severe losses are observed in the Coast Mountains and south-central Rockies (Schiefer et al., 2007), where field measurements confirm glacier ice has thinned 40 to 60 m since the mid-1960s (Figure 6.22) (WGMS, 2025). British Columbia and Alberta have lost approximately 30%, or 9130 km² of their glacier coverage since 1984 (Bevington and Menounos, 2022), and like glacier thinning rates, observed rates of glacier retreat have also increased markedly in recent years. Relative to rates for the period from 1984 to 2010, debris-free glaciers across mainland British Columbia and Alberta have retreated 7 times faster during the more recent period from 2011 to 2020, and debris-free glaciers on Vancouver Island have retreated up to 32 times faster during the same period (Bevington and Menounos, 2022). Calculations based on satellite measurements across the Canadian Arctic indicate that for the period from 2000 to 2019, mass loss from glaciers in the Arctic Canada North region (32 ± 3 Gt/yr) and the Arctic Canada South region (23 ± 2 Gt/yr) were comparable; however, rates of glacier thinning were more than two times higher across the southern region than the northern one for the same period (about 0.75 m/yr versus 0.33 m/yr, illustrated on Figure 6.23) (Hugonnet et al., 2021). Collectively, glaciers in the Canadian Arctic are estimated to have lost an average mass of 53 gigatons per year from 2000 to 2023, largely driven by rising summer temperatures (The Glacier Mass Balance Intercomparison Exercise (GlaMBIE) Team, 2024). This amount of ice loss equates to an approximately 2.7-mm rise in sea level, or 20% of the total contribution from all Arctic ice caps and glaciers excluding the Greenland ice sheet over this 23-year period.

Figure take-away: Glaciers in western Canada and the Canadian Arctic have thinned and lost mass over the past two and a half decades.

Figure title: Satellite-based measurements of rates of glacier thinning in western Canada and the Canadian Arctic from 2000 to 2019

Figure 6.23: Maps of western Canada (left) and the Canadian Arctic (right) overlaid with rates of glacier thinning from 2000 to 2019. Circle colours show the average rate of change in glacier elevation (m/yr) over the period; circle size is proportional to area of glacier coverage. Changes in thinning rates from individual glaciers are grouped together and spatially gridded; circle locations are at the middle of the grid cells, and their size and thinning rates represent the aggregated glacier change from glaciers within that grid cell. Data source: Hugonnet et al. (2021).

Area change and retreat of glaciers can also be demonstrated using satellite imagery and photographic evidence (see an example in Figure 6.24). Calculations show that the area of the Melville Ice Cap in 2023 is nearly half of its 1960 value and that its speed of shrinkage has doubled since 1999. Increased fragmentation of glacier complexes and the expansion of lakes at or near the glacier margin accompany these findings, in some cases threatening surrounding infrastructure and landscape stability, and increasing the risk of glacier lake outburst floods (Clague and O’Connor, 2021; Geertsema et al., 2022; Hik et al., 2022; Shugar et al., 2020).

Figure take-away: Mass loss from glaciers and ice caps can be inferred from images that indicate retreat, fragmentation, and decreases in area.

Figure title: Examples of glacier retreat detectable from photos and satellite images

Figure 6.24: Photos showing retreat of the terminus Peyto Glacier in Banff National Park by approximately 1 km between 2003 (top right) and 2024 (bottom right). Photo credits: Mike Demuth (2003) and Mark Ednie (2024). Satellite image (left) shows the Melville Ice Cap, Northwest Territories, from 2023 with past outlines superimposed from 1999 (red) and 1960 (black). Ongoing fragmentation (separate regions marked by an “F”) and newly exposed interior bedrock (empty sections of the central ice cap region marked by the “B”) are clear indications of rapid disintegration of this low-lying plateau ice cap (at 514–740 m above sea level) in Canada’s western Arctic. Photo Source: Sentinel-2, true color image acquired on July 18, 2023.

Glacier melt and its variability impact the downstream river environment, including discharge levels, water chemistry, and water temperatures. The impact of glacier change on meltwater runoff varies depending on the percent coverage of glacier ice in each catchment and the distribution of ice with elevation (R. D. Moore, 1992). While additional glacier melt initially increases streamflow as the total area of glacier ice declines, glacier melt contributions eventually start to decline as well, indicating that “peak water” has passed (Huss and Hock, 2018). Irreversible decreases in streamflow from glacier-fed rivers and streams have been detected across several major western watersheds, with projections of further declines through to the end of the century (Chesnokova et al., 2020; Huss and Hock, 2018; Marshall et al., 2011; R. D. Moore et al., 2020; Stahl and Moore, 2006). Likewise, across the Canadian Arctic, recent studies have documented changes in the area of small (< 5000 km²) glaciers and ice caps and find they have reduced by 60 to 100% since 1960 (Burgess and Danielson, 2022; Papasodoro et al., 2015; Serreze et al., 2017). Such ongoing depletion of small, stagnant ice masses across the high Arctic desert landscape threatens local summer water supplies that support flora and fauna, as well as water availability for some communities at high northern latitudes (Chapter 5, Case Story 5.1). For places and periods of time that maintain increasing rates of glacier melt, these can translate into increasing contributions to sea-level rise from runoff that flows to the oceans. For example, glacier melt from the Canadian Arctic was responsible for an approximately 3.2-mm rise in the global sea level from 1971 to 2017, which was about 14% of the total melt contributions from all Arctic land ice, including Greenland (Box et al., 2018).

6.5.2: Causes of past changes

Glaciers and ice caps in Canada gain mass by snow accumulation and lose mass mainly by surface melt and runoff, with some loss also occurring through melting at the base, and through iceberg calving where glaciers terminate in oceans or lakes. Among these processes, surface melt is currently the largest control on the annual mass balance of glaciers and ice caps across Canada, and the amount of surface melt depends primarily on the strength and duration of summer warmth (Koerner, 2005; R. D. Moore and Demuth, 2001). Because Canada’s glaciers are situated in Arctic and alpine environments, where surface air temperatures have been rising two to four times faster than the global average (Chapter 4, section 4.2) (Pepin et al., 2015; Serreze et al., 2009), glacier mass loss through surface melt is expected to increase throughout the 21st century.

In western Canada, studies have shown that the year-to-year changes in glacier mass are dominated primarily by summer melt (correlation of 0.9), with winter snow accumulation having a smaller but still detectable influence (correlation of 0.6) (Marshall et al., 2011; WGMS, 2025). Because western Canada’s weather is strongly influenced by Pacific Ocean temperatures, there are also effects related to long-term atmospheric circulation patterns in that region. For example, a shift to the “warm phase” of the Pacific Decadal Oscillation in the mid-1970s is associated with a sharp rise in the rate of mass loss from western Canada’s glaciers (Demuth et al., 2008), as well as a persistent decline in winter snowfall accumulation in the Coast Mountains (Menounos et al., 2019).

In the Canadian Arctic, the net mass balance of glaciers is controlled almost entirely by variability in summer melt (explaining about 98% of year-to-year changes), while the effect of snow accumulation variability on mass balance is considered negligible (Koerner, 2005). Since the early 2000s, surface melting has accounted for approximately 90% of glacier mass loss in the Canadian Arctic, with the remaining losses occurring from iceberg calving (van Wychen et al., 2015; Wouters et al., 2019; Wychen et al., 2020), which contribute 6 to 8% of total regional losses. More than half of those losses come from the Trinity and Wykeham glacier complex, which drains the Agassiz Icefield on Ellesmere Island, Nunavut (Wychen et al., 2020). Glacier retreat associated with calving accounted for approximately 560 km² of glacier area loss in the region between 2000 and 2020 (Kochtitzky and Copland, 2022), and rising air temperatures rather than rising ocean temperatures are primarily responsible for losses from marine-terminating glaciers (Cook et al., 2019). Similar to how glaciers in western Canada are influenced by atmospheric circulation patterns driven by the Pacific Ocean, changes to glaciers in the Canadian Arctic are also linked to regional atmospheric circulation patterns. Accelerated thinning of the four Canadian Arctic reference glaciers after 1986 has been associated with the circumpolar vortex shifting eastward (from the western to eastern hemisphere), which resulted in warmer summer temperatures in the Archipelago (Gardner and Sharp, 2007). Likewise, strong warming across the Canadian Arctic since the mid-2000s has been linked to an increase in northward movement of warm air from the northwest Atlantic, where sea surface temperatures have been higher than normal (Chapter 7, section 7.2.1) (Sharp et al., 2011). These studies provide examples demonstrating that consideration of how climate change will alter large-scale pressure systems and patterns of atmospheric circulation is critical to accurately predicting future changes in mass balance of Arctic glaciers and ice caps (see Chapter 4, sections 4.3 and 4.8, for further discussion of how large-scale atmospheric circulation processes can affect Canada’s climate) (Gardner and Sharp, 2007; Sasgen et al., 2024).

Finally, glacier surface albedo (surface reflectivity) has a large influence on glacier melt rates, and declines in glacier surface albedo have been observed in both western Canada (Williamson and Menounos, 2021) and the Canadian Arctic (Mortimer and Sharp, 2018; Williamson et al., 2020). Declines in albedo, perceived as surface darkening, increase the amount of solar radiation absorbed in the snow or ice surface, in turn leading to increased melt and, often, further darkening through a series of feedback mechanisms (Naegeli and Huss, 2017; Skiles and Painter, 2019). Arctic and alpine warming trends have resulted in an earlier loss of snow cover (section 6.2), shifts toward more frequent rainfall rather than snowfall (Chapter 2, section 2.5.1.2), warming snowpacks leading to larger snow grain size, and the loss of firn.^{Footnote 6} Deposits of light-absorbing particles, such as soot and ash from wildfire activity, as well as the growth of algae across ice and snow, can further increase melt and trigger feedbacks that lead to further declines in albedo (Aubry-Wake et al., 2022; Engstrom et al., 2022).

Beyond Canada, satellite and in-situ observations of changes in glacier area and mass indicate that for the world as a whole, mountain glaciers have receded significantly in recent decades (Medwedeff and Roe, 2017; Zemp et al., 2019). Human-caused climate change has been shown to be the primary driver of global glacier retreat and mass loss (Roe et al., 2021), as global glacier retreat and melt is driven primarily by observed temperature trends (Marzeion et al., 2014; Roe et al., 2017).

6.5.3: Future changes

In this section, projected changes in Canada’s glaciers are based primarily on Rounce et al. (2023), who derived policy-relevant global glacier changes for the period from 2015 to 2100. These projections incorporate observational datasets of glacier change to both calibrate their models and make detailed adjustments needed to properly calculate sea-level rise. These adjustments account for the approximately 15% of the world’s glacier ice that is below sea level and that therefore does not contribute to sea-level rise. In the paragraphs below, the numbers indicate percent mass loss relative to 2015 values and are provided as a range covering the 95% confidence interval calculated from the model ensemble (that is, there is a 95% chance that the true value falls within this range).

The analysis by Rounce et al. (2023) indicates that by 2100, total glacier mass in western Canada will decline by 76 ± 21% under a low emissions scenarios (RCP2.6), by 94 ± 19% under an intermediate emissions scenario (RCP4.5), and by 99 ± 6% under a very high emissions scenario (RCP8.5) relative to the 2015 mass. The highest rates of glacier shrinkage in this region will occur along the eastern slopes of the Canadian Rockies. As a result of this loss in glacier mass, contributions of glacier meltwater to river headwaters are also projected to decrease by 80 to 90% by the end of the century (Marshall et al., 2011). The large icefields of coastal British Columbia are more resilient to century-scale warming (Clarke et al., 2015), but by 2100 they are still projected to lose 50 to 70% of their 2005 mass. These projections exclude Saint Elias glaciers located in the Yukon (~10,000 km²) (Barrand and Sharp, 2010), but they are assessed collectively as “Alaskan” glaciers in Rounce et al. (2023). Coastal glaciers of northern British Columbia are projected to yield increasing meltwater discharge beyond 2100 under emissions scenarios from low (RCP2.6) to very high (RCP8.5) (Clarke et al., 2015). Despite these localized increases, total meltwater discharge from all glacierized regions in western Canada combined is expected to decrease steadily after 2040 (Rounce et al., 2023) as most glaciers thin and retreat to higher elevation terrain (Bevington and Menounos, 2022).

The vast majority of Canada’s glacier ice is located in the Canadian Arctic, and glacier melt in this region will have important consequences for global sea-level rise. Projections by Rounce et al. (2023) indicate that by 2100, mass loss from glaciers and ice caps in Arctic Canada North (Figure 6.21) will be 16 ± 8% under a low emissions scenario (RCP2.6), 18 ± 8% under an intermediate emissions scenario (RCP4.5), and 24 ± 13% under a very high emissions scenario (RCP8.5), relative to their 2015 values. While these losses represent a much smaller percent of Arctic Canada North’s ice mass than what is projected for western Canada, melt from this region will contribute much more to global sea-level rise. This is because of the large volume of glacier ice in this region, much of which is located above the climate equilibrium line altitude, that is, the spatially averaged elevation that separates the accumulation zone from the ablation zone (Burgess and Danielson, 2022). Ice mass above this altitude (approximately 1500 m for the Arctic Canada North region on average) provides an ongoing supply of glacier ice to lower elevations where the majority of the melt occurs. As a result, rates of mass loss from Arctic Canada North and corresponding contributions to sea-level rise are projected to hold steady or even increase throughout the 21st century (Figure 6.25). While Arctic Canada South has less ice volume than Arctic Canada North (roughly three quarters of all Arctic glacier ice is in the northern region), the more southern region will lose a larger percentage of its ice mass so that the contributions to sea-level rise from the two Arctic regions are comparable (Rounce et al., 2023). For the southern region, projections indicate that by 2100, glacier and ice cap mass loss will be 41 ± 26% under a low emissions scenario (RCP2.6), 42 ± 26% under an intermediate emissions scenario (RCP4.5), and 63 ± 24% under a very high emissions scenario (RCP8.5), relative to their 2015 values. By the end of the 21st century, combined glacier melt from all of the Canadian Arctic (north and south) is projected to be contributing 0.19 to 0.47 mm/yr to increases in global mean sea level. This range of projected rates assumes a 2 to 3°C rise in global average temperature above the pre-industrial (1850 to 1900) average, which aligns with results reported by Working Group I in the IPCC’s Sixth Assessment Report for the intermediate RCP emissions scenario (Fox-Kemper et al., 2021). These projected rates of glacier melt are expected to make the region the largest contributor to global sea-level rise on Earth outside of the continental ice sheets of Antarctica and Greenland.

Figure take-away: Contributions to global sea-level rise from glaciers in the northern Canadian Arctic will continue to increase through to 2100.

Figure title: Sea-level rise projected from annual glacier melt in the northern Canadian Arctic

Figure 6.25: Annual contributions to sea-level rise from combined glacier melt across the Arctic Canada North region in millimetres of sea-level equivalent per year. Contributions to sea-level rise vary with global warming level. Colours distinguish annual contributions to sea-level rise under four different warming scenarios that result in respective global average temperature increases by 2100 of 1.5°C (blue), 2°C (yellow), 3°C (orange), and 4°C (red), relative to the pre-industrial period (1850 to 1900). Shading depicts the 95% confidence interval for annual contributions to sea-level rise under temperature rises of 1.5°C (blue shading) and 4°C (red shading). Adapted from: Rounce et al. (2023).

In western Canada, the potential for glacier-related hazards is expected to increase in response to recent and future trends in extreme glacier thinning. Glacier melt can release trapped sediment and rock, initiating landslides in the process. As glaciers warm and melt, large sections of ice can weaken and collapse (Hock and Truffer, 2024). Increases in the volume of many pro-glacial lakes (Shugar et al., 2020), combined with the loss of natural ice dams, may also increase the potential for glacier lake outburst floods in this region (Clague and Evans, 2000). While the precise timing of glacier-related landslides, debris flows, and glacier lake outburst floods are difficult to predict directly (Huggel et al., 2012), there are identifiable increases in the past frequency of glacier-related hazards following warming events. One such example is the identified increase in glacier-related hazards that occurred during the warmer period that followed the Little Ice Age (approximately from 1450 to 1850) (Harrison et al., 2018). Even if glacier-related hazards do not increase in frequency, a higher risk to public safety and infrastructure may result as development and tourism encroach further into remote areas (Geertsema et al., 2022; Taylor et al., 2023).

6.5.4: Knowledge gaps

1) The extent to which feedbacks will alter glacier melt across Canada is uncertain.

Recent studies show evidence of declines in glacier surface albedo feedback in parts of western Canada (Williamson and Menounos, 2021) and the Canadian Arctic (Mortimer and Sharp, 2018; Williamson et al., 2020), resulting in surface darkening and an increase in absorbed solar radiation that can augment snow and ice melt. However, no nation-wide assessment of glacier surface albedo change has been conducted, and the spatial variability and temporal trajectory of glacier albedo (and subsequent effect on melt) remain unknown.

While the causes of glacier surface albedo change related to warming are relatively well understood, they are not always incorporated into predictive models of glacier change due to the inherent complexity of feedback processes (Curry et al., 1995). Also, significant uncertainty remains about how glaciers will be impacted by future wildfire activity, which can increase melt through deposits of dark, albedo-reducing impurities or decrease melt as wildfire smoke blocks some sunlight.

Glacier fragmentation is known to accelerate the loss of glacier ice through increased terrain irradiance (longwave radiation) and heat advection to the glacier surface (Bevington and Menounos, 2022). Fragmentation can occur in various ways, including hydro-fracture from marine-terminating glaciers, dry-calving from land-terminating glaciers, excessive melt across low-lying ice caps, and glacier thinning from below and subsequent collapse. Sparse information on where and when fragmentation will occur introduces uncertainty as to the current and future melt rates across all glacierized regions of Canada (Jiskoot and Mueller, 2012).

The degree to which past and continuing reductions in cold content of glacier ice will increase future melt is also uncertain. Warming glacier ice at depth (10 to 20 m) preconditions the ice to allow for more intense melt during the following melt season (Zdanowicz et al., 2012). A sparsity of subsurface temperature measurements from Canada’s glaciers (Bezeau et al., 2013; Blatter, 1987; Paterson and Clarke, 1978) leaves uncertainty about how glaciers across Canada will respond to the climate warming scenarios projected.

2) The impacts of tidewater glacier retreat on marine ecosystems are poorly understood.

The Canadian Arctic Archipelago supports more than 350 marine-terminating glaciers that drain approximately 45% of this region’s total glacierized area (Cook et al., 2019; van Wychen et al., 2015). Along with large proportions of the melt water generated across the glacier or ice cap basins, these tidewater glaciers release approximately 3 km³ of ice mass loss per year into the oceans. Meltwater and glacier ice released at a tidewater glacier feed marine micro-organisms through the contribution of nutrients and organic carbon from the land and through upwelling induced by rising submarine discharge plumes (Bhatia et al., 2021) that bring nutrients from the ocean floor toward higher levels in the water column where photosynthesis occurs (Hopwood et al., 2020). Inuit Knowledge indicates that waters near marine-terminating glaciers are rich in wildlife that support the local Inuit in the Canadian Arctic Archipelago (personal communication, J. Qaapik, Grise Fiord Rangers). Research to date indicates that Canada’s tidewater glaciers are rapidly transitioning from marine to land-terminating glaciers (Cook et al., 2019). This transition is expected to have negative impacts on the nutrients available near these termini, potentially threatening the ocean ecosystems they support. As glacier-ocean interactions in the Canadian Arctic have been studied for only a small fraction of Canada’s tidewater glaciers (Apollonio, 1973; Bhatia et al., 2021; P. L. Williams et al., 2021), more broad-scale studies of marine-terminating glacier retreat are required to fully understand the impacts on marine ecosystems and the local Inuit they support.

6.5.5: Confidence terms in key messages: summary of evidence

Key message 6.9: All glaciers in western Canada and the Canadian Arctic have thinned and lost mass over the past two and a half decades, as shown by satellite measurements with comprehensive spatial coverage (very high confidence). Longer-term field measurements on a small number of reference glaciers show that glaciers in Canada have been losing mass since at least the 1960s, and that the rate of loss has accelerated in recent decades (high confidence). In western Canada, declines in glacier contributions to summer streamflow have been observed in several watersheds (high confidence), marking an irreversible decrease in a critical source of freshwater for these regions.

Key message 6.10: Canada’s glaciers are projected to continue losing mass under every future emissions scenario (very high confidence). In western Canada, more than 55% of glacier ice is predicted to disappear by 2100, even if global warming is limited to 2°C (high confidence). The number and severity of glacier-related hazards, such as flooding and landslides, are expected to increase, particularly in western Canada (medium confidence). Melt water from glaciers and ice caps in the Canadian Arctic will continue to be among the largest glacier sources of global sea-level rise up to and beyond 2100 (very high confidence).

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because most attribution studies have examined changes in glacier mass and area for the world as a whole. However, because of the dominant role of air temperature in controlling glacier retreat and mass loss, we assess that human-caused climate change is certain to be influencing glacier melt in Canada (section 6.5.2).

With respect to Key Message 6.9, our very high confidence that glaciers across Canada have lost mass over the past 25 years is based on numerous independent studies applying distinct methodologies that corroborate one another’s findings. Satellite-derived measurements of glacier mass changes (using gravimetric methods) and volume changes (using surface elevation changes) are consistent with rates of mass loss from field-based measurements of Canada’s reference glaciers over the past 25 years, and agree with expectations from process-based studies correlating observed negative annual mass balance with observed summer warmth. Over the 25-year period of available observations, the satellite measurements provide comprehensive spatial coverage across all glacierized regions of Canada.  Our high confidence in the accelerating rate of mass loss is based on field-measurements, but because these measurements are available only on a limited number of glaciers, we have high rather than very high confidence that mass loss is accelerating for glaciers across all of Canada. Our high confidence that summer stream flow has started to decline for specific watersheds is based on multiple studies that have compared direct observations of streamflow to changes projected by models.

With respect to Key Message 6.10, multiple generations of climate models stemming from several independent research teams support very high confidence that glaciers in western Canada and the Canadian Arctic will lose mass continuously through to 2100. The most recent generation of CMIP6 models has demonstrated that this will occur even if increases in global average temperature are limited to 1.5°C above the pre-industrial (1850–1900) average. Warming scenarios based on current policy predict global temperatures to rise 2.3 to 3.5°C above pre-industrial levels (IPCC, 2023: Climate Change 2023). Under this scenario, the linkages between temperature and glacier change strongly support continuous, and in some cases accelerated world-wide glacier mass loss beyond 2100. Multiple studies independently using different methodologies and different reference time periods have projected that glaciers in western Canada will experience significant declines in volume through to 2100. However, only one study has specifically focused exclusively on western Canadian glaciers. Therefore, we have high rather than very high confidence in this statement. The statement regarding glacier-related hazards is based on a range of studies that examine diverse aspects of how glaciers and the surrounding landforms are expected to evolve as glaciers continue to melt. While scientists are able to analyze glacier-related hazards during past warm periods as analogues to the current climate, we have medium confidence in the increasing number and severity because there are no direct model projections of future changes to glacier-related hazards. Sea-level rise has also been robustly projected by multiple generations of climate models. Our very high confidence in the magnitude of contributions from glaciers in the Canadian Arctic is based not only on agreement among model projections but also on a theoretical understanding of how enhanced warming at high northern latitudes and the large quantity of high-elevation ice present in the Canadian Arctic will result in increasing glacier melt from this region.

6.6: Seasonally frozen ground

Key message 6.11: The annual number of days with seasonally frozen ground has decreased in Canada over the past four decades (high confidence). At locations without underlying permafrost, decreases in the depth of seasonal freezing are expected to have occurred, while at most locations with underlying permafrost, increases in the depth of seasonal thawing are expected to have occurred (medium confidence), but the limited number of observations prevent direct assessment of such changes.

Key message 6.12: The annual number of days with seasonally frozen ground, and the maximum annual depth of seasonally frozen ground outside permafrost areas, are expected to decrease across Canada until mid-century before stabilizing under a low emissions scenario (high confidence). In contrast, these indicators of seasonally frozen ground are expected to continue declining until the end of century and beyond under emissions scenarios with higher levels of carbon emissions and increasing global temperatures (high confidence).

“Seasonally frozen ground” refers to a ground layer that freezes in winter and completely thaws in summer. It consists of the seasonally freezing and thawing ground layers in both non-permafrost and permafrost regions. Where permafrost exists, the seasonally frozen ground is above the permafrost and is referred to as the active layer. Nearly all of Canada’s land is subject to seasonal freezing and thawing. Frozen ground is often identified using thermal conditions, where the ground is considered frozen when its temperature falls below 0°C. Seasonally frozen ground can be characterized by the ground surface state (frozen or unfrozen), which can be used to calculate the annual number of days with frozen ground. Seasonally frozen ground can also be characterized by the maximum annual depth of ground that freezes and then thaws over the course of a year.

The seasonal freezing and thawing of ground impacts hydrology, greenhouse gas emissions, and infrastructure. The ground state (frozen or unfrozen) determines the permeability of the ground to water, impacting infiltration, percolation, evapotranspiration, ground water recharge, and runoff. Seasonally frozen ground affects hydrological processes at 75% of 162 sites studied across the Northern Hemisphere (Ala-Aho et al., 2021). Seasonally frozen ground can affect greenhouse gas emissions from soil in two ways. First, the freeze-thaw cycle reduces the stability of the soil structure, resulting in the release of existing pockets of dissolved organic carbon. Second, the cycle alters the number and composition of soil micro-organisms, which in turn affects soil respiration rates (how much carbon dioxide soil micro-organisms release over a given period) (Y. Liu et al., 2024). Carbon dioxide emissions through soil respiration are generally lower for frozen soils than unfrozen soils; however, emissions can be present even when the ground is frozen (Natali et al., 2019) if it contains unfrozen soil moisture (Arndt et al., 2023; Mavrovic et al., 2023). Emissions of other greenhouse gases, such as methane and nitrogen dioxide, are also affected by the ground state (Mavrovic et al., 2025; Wagner-Riddle et al., 2017). Frozen ground governs the length of the growing season, and the sequestration of carbon dioxide by plants through photosynthesis, by limiting water availability in spring (El-Amine et al., 2022; Richardson et al., 2013). Freezing and thawing also impact infrastructure, especially roads, because winter freezing and spring thaw can make roadbeds unevenly deformed, leading to road degradation and safety issues (Kestler et al., 2011).

Monitoring seasonally frozen ground under snow and vegetation remains a challenge. In Canada, there are few locations with long-term ground temperature measurements (Shiklomanov, 2012). Instead, datasets on freezing and thawing derived from passive-microwave satellite observations are typically used, since they cover the entire Northern Hemisphere and extend back to 1979 (Y. Kim et al., 2021). These datasets provide only coarse-scale (25-km resolution) estimates on whether the soil surface is frozen or not (Y. Kim et al., 2011; Rowlandson et al., 2018). However, when the ground is snow-covered, the thaw signal mainly comes from liquid water in the snowpack (A. Roy et al., 2015), so the thaw timing may not reflect that of the ground surface itself. Near-surface air temperature provides a third source of information that can be used as a substitute for direct information on frozen ground (Leduc & Logan, 2025), since it acts as a driver of freezing and thawing in the ground (Beltrami & Kellman, 2003; Frauenfeld & Zhang, 2011). Therefore, in this report, we use projected changes in the number of frost days (days where the near-surface air temperature is below 0°C) as a way to estimate changes in the future state of frozen ground.

6.6.1: Past changes

Analysis of seasonally frozen ground from remotely sensed passive-microwave data (Y. Kim et al., 2021) covering 1979 to 2021 reveals an average decrease of 1.7 days per decade (95% confidence interval: a decrease of 3.1 to 0.2 days per decade) in the annual number of days with frozen ground for Canada as a whole (Figure 6.26). Across the country there are regional variations in the magnitude of change, with a stronger decrease of 1.9 days per decade (95% confidence interval: a decrease of 3.5 to 0.3 days per decade) in tundra regions and even small increases observed at some locations (Figure 6.27). Overall, these findings are in line with a global-scale analysis that found the number of days of seasonally frozen ground had decreased across the Northern Hemisphere at an average rate of 1.3 days per decade from 1979 to 2017 (T. Li et al., 2021), although the rate is lower in North America than in Eurasia. Analysis based on weather station datasets for Canada also found that the annual number of days with seasonally frozen ground decreased over a 38-year period (1966–2004) in response to rising average winter air temperatures (Henry, 2008).

Figure take-away: The number of days with seasonally frozen ground decreased for Canada as a whole from 1979 to 2021.

Figure title: Change in annual number of days with seasonally frozen ground in Canada from 1979 to 2021

Figure 6.26: Bar chart where each bar represents the deviation in a given year from the average number of days with seasonally frozen ground for the period from 1979 to 2021. Blue bars indicate years with more days than the average, while red bars indicate years with fewer days than the average. The trend line (black) depicts the overall trend. Data source: Y. Kim et al. (2021).

Figure take-away: The annual number of days with seasonally frozen ground decreased in most regions of Canada from 1979 to 2021.

Figure title: Regional changes in annual number of days with seasonally frozen ground across Canada from 1979 to 2021

Figure 6.27: Map with colours showing changes in the annual number of days with seasonally frozen ground across Canada from 1979 to 2021. Regions with more than 20% water (lakes or ocean) or complex topography are more uncertain and have been masked out (shaded in grey). Data source: Y. Kim et al. (2021).

While there is a limited number of observations of shallow ground temperatures in Canada, analysis of those available indicate warming trends (Chouinard and Mareschal, 2007; Pickler et al., 2016). In addition, studies show a strong link globally between maximum annual depth of seasonally frozen ground and air temperature even in snow-covered regions (Soong et al., 2020). The strong link suggests that the maximum annual depth of seasonally frozen ground will decrease in Canada with rising air temperatures. At many permafrost locations, however, the maximum annual depth of seasonally frozen ground (the active layer, see section 6.7.1.2) will first increase as the top of the permafrost degrades in response to rising air temperatures. More extensive ground temperature data are available for regions outside of Canada. Analysis of data from 423 stations in Eurasia revealed a significant decrease in annual depth of seasonally frozen ground of 4.5 cm per decade for 1930 to 2000 (Frauenfeld and Zhang, 2011). However, most of the decrease was reported for the relatively short period of 1970 to 1990 and may simply reflect internal climate variability. Global models that simulate past ground conditions indicate that the maximum annual depth of seasonally frozen ground decreased by 13.9 to 19.1% over the Northern Hemisphere from 1981 to 2010 (C. Chen et al., 2024), with stronger decreases in high-latitude regions.

6.6.2: Causes of past changes

Robust theory and widely adopted methods identify air temperature as the first order control for the depth of ground freezing and thawing (Andersland and Ladanyi, 2003; P. J. Williams and Smith, 1989), with snow cover playing a lesser, but still significant role. Air temperature is commonly used as a diagnostic variable for frozen ground, since it is readily available and often reflects the way conditions are changing at the interface between soil and atmosphere (Leduc and Logan, 2025; T. Zhang, 2005). In general, snow cover tends to warm the underlying ground over a typical annual cycle and to decrease the occurrence and depth of frozen ground. Studies have shown that air temperature is the main contributor to fewer days of seasonally frozen ground in northern Canada, while changes in the amount of snowpack are more important in the southern Canadian Prairie region (T. Li et al., 2021).

6.6.3: Future changes

In this report, in place of simulated changes in the number of days with frozen ground, we use projected changes in the number of frost days (days where the near-surface air temperature falls below 0°C) as a proxy for the future changes in seasonally frozen ground. The number of frost days was calculated directly from CMIP6 model output, and the results, which are presented in figures 6.28 and 6.29, are consistent with studies over eastern North America based on bias-corrected CMIP6 output (Leduc and Logan, 2025). By late-century (2081 to 2100), CMIP6 global climate models project a decrease in the annual number of frost days relative to 1991 to 2020 for Canada as a whole ranging from a loss of 15 days on average in the low emissions scenario (SSP1-2.6), a loss of 30 days in the intermediate emissions scenario (SSP2-4.5) and a loss of 45 days on average in the high emissions scenario (SSP3-7.0) (Figure 6.28). Projected changes also show regional differences in Canada. For the intermediate emissions scenario (SSP2-4.5), the losses range from about 25 to 35 days in the Northwest Territories, northern Yukon, and the Prairies, 25 to 44 days in eastern Canada, and over 50 days near the coast in British Columbia. There are also large differences in the seasonal distribution of these changes (Figure 6.29). For most of Canada, the projected changes are more pronounced in the transition seasons when the average air temperature is around 0°C. Consequently, in southern Canada, the changes mostly occur in April to May and October to November. In northern Canada, the largest decrease in the number of frost days occurs from June to September, when air temperature is already often around 0°C in today’s climate. These results are in line with a study that examined maximum annual depth of frozen ground on a global scale and projected a decrease of 11 to 42% from 2015 to 2099 relative to the period from 1981 to 2010 (C. Chen et al., 2024). These analyses are based on near-surface air temperature and neglect the potential impact that future changes in snow and vegetation characteristics can have on seasonally frozen ground.

Figure take-away: The annual number of frost days is expected to decrease across Canada in the late century (2081 to 2100), with greater losses associated with higher emissions scenarios.

Figure title: Changes in the annual number of frost days across Canada in the late century (2081 to 2100)

Figure 6.28: Top panels: Maps with colours showing projected changes in the annual number of frost days across Canada for the late century (2081 to 2100), relative to the average for the period from 1991 to 2020. Three emissions scenarios are compared: low emissions (SSP1-2.6), intermediate emissions (SSP2-4.5), and high emissions (SSP3-7.0). Lower panel: The chart shows the simulated changes in average annual frost days in Canada from 1951 to 2100 relative to the average for the period from 1991 to 2020. Data source: monthly frost days calculated from CMIP6 model output for the Copernicus Interactive Climate Atlas, available from Copernicus Climate Change Service, Climate Data Store (2024).

Figure take-away: The monthly number of frost days is expected to decrease across Canada in the late century (2081 to 2100), with large seasonal and regional differences.

Figure title: Changes in the monthly number of frost days across Canada in the late century (2081 to 2100)

Figure 6.29: Projected decreases in the monthly number of frost days in Canada for the late century (2081 to 2100), relative to the average for the period from 1991 to 2020, using an intermediate emissions scenario (SSP2-4.5). Data source: as in Figure 6.28.

6.6.4: Knowledge gaps

1) There is a lack of direct ground temperature measurements, and systematic uncertainty exists in remote-sensing data.

The lack of ground temperature measurements in Canada limits our ability to study seasonally frozen ground with direct observations, increasing our reliance on the use of remotely sensed passive-microwave datasets. However, these datasets measure conditions in the uppermost ground layer only and provide no information on changes in the depth of frozen ground. The amount of information we can obtain from models is also limited. Models that simulate ground temperature under snowpack have not been extensively evaluated in Canada (Melton et al., 2019), which limits our confidence in such simulations. Future efforts require a better understanding of the way in which changing air temperature and changing snow cover combine to alter soil temperature and freezing in Canada.

2) There are uncertainties due to local variation in ground characteristics.

In seasonally frozen ground, temperature heterogeneity can be high because of the spatial variability of soil, vegetation, soil wetness, and snow characteristics (Domine et al., 2022; Khani et al., 2023). Wet soil can greatly delay complete freezing, from several days in tundra regions (Davesne et al., 2022) to several weeks in boreal forests (Prince et al., 2019). Hence, modelling and remote-sensing analysis at coarse spatial resolution (1 to 100 km) does not capture the relevant spatial complexity of seasonally frozen ground processes and the implications for hydrological and ecological processes.

6.6.5: Confidence terms in key messages: summary of evidence

Key message 6.11: The annual number of days with seasonally frozen ground has decreased in Canada over the past four decades (high confidence). At locations without underlying permafrost, decreases in the depth of seasonal freezing are expected to have occurred, while at most locations with underlying permafrost, increases in the depth of seasonal thawing are expected to have occurred (medium confidence), but the limited number of observations prevent direct assessment of such changes.

Key message 6.12: The annual number of days with seasonally frozen ground, and the maximum annual depth of seasonally frozen ground outside permafrost areas, are expected to decrease across Canada until mid-century before stabilizing under a low emissions scenario (high confidence). In contrast, these indicators of seasonally frozen ground are expected to continue declining until the end of century and beyond under emissions scenarios with higher levels of carbon emissions and increasing global temperatures (high confidence). 

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because no direct attribution studies are available. However, because of the dominant role of air temperature in controlling the number of days with frozen ground and the depth to which it freezes and thaws seasonally (section 6.6.2), we assess that human-caused climate change is certain to be influencing seasonally frozen ground in Canada (section 6.6.2).

With respect to Key Message 6.11, trends from passive-microwave remote-sensing data show significant decreases across most of the country that are consistent with similar analyses conducted on a global scale. While there is some uncertainty regarding freeze and thaw cycles determined from remote-sensing data, it is constrained enough to have high confidence in the observed decrease in annual number of days with seasonally frozen ground in Canada. Theory and process studies indicate a strong correlation between increasing air temperatures and the maximum annual depths of seasonally frozen ground. Therefore, despite the limited number of monitoring sites, observed increases in near-surface air temperature provide sufficient evidence to assess with medium confidence that the maximum annual depth of seasonally frozen ground has also changed in Canada.

With respect to Key Message 6.12, CMIP6 global climate models driven by different emissions scenarios provide projections of the annual number of frost days (days where the near-surface air temperature is below 0°C). We have very high confidence in the changes in frost days (section 6.6.3) because of robust agreement among multiple generations of climate models in how near-surface air temperature responds to associated changes in global emissions of carbon and other greenhouse gases. There is also a high level of agreement among multiple process studies that near-surface air temperature controls when freezing in the ground occurs, and can therefore serve as a reliable proxy for changes in frozen ground. However, because the changes in frost days are not directly equivalent to changes in ground state, and because they do not account for secondary effects related to changes in snow, soil moisture, and vegetation, we have high rather than very high confidence in the ground state changes themselves.

6.7: Permafrost

Key message 6.13: Permafrost at monitored locations in northern Canada has warmed and thawed since the 1980s (very high confidence). Landscapes in the parts of northern Canada with ice-rich terrain have changed in response to climate-driven permafrost thaw (very high confidence).

Key message 6.14: Permafrost warming and thaw-driven landscape changes are expected to continue with increased climate warming (very high confidence). Even if the climate stabilizes, some thawing will continue at depth (very high confidence). However, there is low confidence regarding the magnitude and timing of these changes because of the influence of local ground characteristics.

Permafrost is defined as ground (soil or rock) that remains at a temperature of 0°C or lower for at least two consecutive years (Lewkowicz et al., 2025). Most permafrost has existed for much longer than that, from centuries to many millennia. Permafrost exists underneath about 40% of Canada’s exposed land area (land not covered by glaciers or large lakes) (Natural Resources Canada, 2022) and affects ecosystems, people, and climate in many ways. Some permafrost also exists beneath shallow ocean water off Canadian coasts (Normandeau et al., 2024; Overduin et al., 2023). The terrestrial distribution of permafrost is patchy and sporadic in the southern part of the permafrost region and becomes more continuous farther north (Figure 6.30). Climate change is a main driver of permafrost thaw, but the magnitude, rates, and nature of changes reflect local conditions such that the environmental and societal implications of thawing vary considerably across the landscape (Kokelj et al., 2023). Therefore, knowing how permafrost conditions vary across the country and how they evolve is critical.

Permafrost temperature and its change depend on several factors, including climate (especially air temperature and snow cover), soil properties, overlying organic matter, vegetation, and the amount of ice contained in the ground (S. L. Smith et al., 2022). Depending on ground ice content, soil, topography, and hydrological conditions, a variety of distinct “thermokarst” landforms (typical landforms resulting from the thaw of ice-rich permafrost) can develop when permafrost thaws (Kokelj & Jorgenson, 2013). Possible landscape changes due to thaw include ground settlement, pond formation, lake expansion or drainage, and slope failures such as thaw slumps. These changes, in contrast to permafrost temperature, are often easily visible and can have distinct and direct consequences for ecosystems and human environments, such as infrastructure and traditional land use (for example, Case Story 6.3) (Kokelj et al., 2023). In this assessment, we use progressive changes in the area, state, and distribution of thaw-driven landforms as a new and intuitive indicator of permafrost thaw.

Permafrost thaw influences how water flows at and below the ground surface (Chapter 5, sections 5.3, 5.4, 5.5) (Spence et al., 2020). Thaw-induced landscape instability can affect terrestrial and aquatic ecosystems by moving sediment, dissolved materials, and organic materials to bodies of water (Chin et al., 2016; Shakil et al., 2020) and by releasing contaminants previously stored in permafrost, such as mercury and other heavy metals (AMAP, 2021b; Rutkowski et al., 2021; Schuster et al., 2018). Thawing permafrost therefore acutely impacts northern communities and traditional lifestyles, with effects on infrastructure, land access, and food security (Hancock et al., 2022; Hausner et al., 2021).

The global permafrost region is estimated to store around 1100 to 2000 Gt of carbon (Hugelius et al., 2014; Lindgren et al., 2018). When permafrost thaws, some of this carbon can be released into the atmosphere as carbon dioxide or methane, which, as greenhouse gases, contribute to additional warming and even more thaw (Chapter 9, section 9.5).

This section assesses how permafrost has warmed and thawed over the last several decades and discusses controlling factors. Compared to the information on many other variables discussed in this report, information on permafrost conditions is available for fewer locations, for relatively short periods of time, and with less reliance on model output. The key indicators used for this assessment are derived from both site-specific measurements and the interpretation of remotely sensed imagery (satellite and airborne). We also discuss expected future changes in permafrost environments, including the limitations of the approaches used.

Figure take-away: Ground temperature measurements indicate permafrost is warming in northern Canada.

Figure title: Permafrost warming rates at sites in northern Canada

Figure 6.30: Map showing permafrost warming rates based on ground temperature records in different regions of northern Canada. Circle colour distinguishes trends (based on linear regression) at sites where data are available only since the year 2000 (red) and sites with longer records (orange). Circle sizes are proportional to the rate of change. Where rates of warming are low (for example, in Wapusk or Yellowknife), there can still be strong permafrost thaw because the melting of ice in the ground consumes energy. Adapted from: S. L. Smith, Duchesne, et al. (2024). Data source: see Supplementary Table S6.1.

6.7.1: Past changes

Permafrost temperature and active-layer thickness (ALT) records from monitoring sites across Canada provide site-specific indicators of permafrost change. Since these records are available only at a limited number of locations, we also assess the distribution and changes to thermokarst landforms as a complementary suite of indicators of changes in ice-rich permafrost terrain over broader areas (Kokelj et al., 2023).

6.7.1.1: Permafrost temperature

Ground temperatures reflect changes in climate, including air temperature and snow cover, and in local ground conditions. Near the surface, the ground temperature fluctuates in response to daily and seasonal variations. These fluctuations become less pronounced with depth and are usually negligible below around 10 to 20 m. Temperature measurements at this depth are typically used as the indicator of the long-term variation in permafrost temperature. They are acquired using temperature sensors installed in boreholes.

Permafrost temperature monitoring in northern Canada consists of over 100 instrumented boreholes forming regional networks operated by the Geological Survey of Canada, territorial governments, and academic researchers. Some monitoring sites have been in operation for over three decades, but most have been operating less than 20 years, with many established during the International Polar Year, from 2007 to 2009 (for example, S. L. Smith et al., 2010). The monitoring network covers a range of permafrost and climate conditions, from the warmer permafrost of the discontinuous zone to the colder permafrost of the high Arctic. The monitored sites also reflect a range of vegetation, geology, and terrain conditions.

Updated time series of ground temperatures from sites across northern Canada show that permafrost is generally warming, with short-term variations overlying the longer-term trend (figures 6.30 and 6.31). Overall, the observed trends agree with those previously reported (Derksen et al., 2019; Gulev et al., 2021; S. L. Smith et al., 2019) and indicate that permafrost continues to warm across northern Canada. Record-high ground temperatures have occurred since 2017 at most sites, including 17 of the 18 sites shown in Figure 6.31.

Temperatures in warmer permafrost (> -2°C) in northwestern Canada, including the southern Yukon and Mackenzie Valley (figures 6.30 and 6.31a), have increased less than in colder permafrost, particularly at sites with ice-rich sediments. This is because energy is used to melt ground ice when thawing occurs, resulting in little change in ground temperature. For sites with longer records (for example, Norman Wells and Wrigley), permafrost has generally warmed by about 0.1°C per decadesince the 1980s. Shorter records, available for sites such as those elsewhere in the central and southern Mackenzie Valley, Yellowknife, southern Yukon, and Labrador, indicate similar or lower rates of warming (figures 6.30 and 6.31a) (Duchesne et al., 2020; L.-P. Roy et al., 2024; Y. Wang et al., 2024).

For sites with colder permafrost, including those in the northern part of the Mackenzie Valley and the eastern and high Arctic, the rate of permafrost warming has been higher (Figure 6.31), ranging from about 0.4 to 0.7°C per decade(for example, Duchesne et al., 2024; S. L. Smith, Duchesne, et al., 2024). Permafrost temperatures have risen even faster at eastern Arctic sites, such as Resolute and Clyde River. Data collected between the mid-1990s and 2023 (Allard et al., 2024) for colder permafrost or bedrock sites in northern Quebec show warming at similar rates (0.2 to 0.7°C per decade) to those in the Baffin region. Since 2019, permafrost cooling has been observed at some sites in the northern Mackenzie region (for example, Big Lake, Niglintak, and Norris Creek in Figure 6.31a), which reflects lower air temperatures and less snow in the region. However, permafrost temperatures were steady or rose after 2022, reflecting higher air temperature in 2023.

Figure take-away: Permafrost is warming at most sites in the western and eastern Canadian Arctic.

Figure title: Changes in permafrost temperature at sites in the western and eastern Canadian Arctic

Figure 6.31: Permafrost temperature at selected sites in the a) western and b) eastern Canadian Arctic. Temperatures are measured at the depth indicated in parentheses. Data source: see Supplementary Table S6.1.

6.7.1.2: Active-layer thickness

The active layer, defined as soil and rock above permafrost that freezes and thaws annually, responds more to shorter-term variations in climate than to ground temperatures at depth. The base of the active layer is normally defined by the maximum annual depth of thaw (where the temperature exceeds 0°C). Increases in ALT are commonly used as an indicator of permafrost degradation. Information on ALT trends has been available since the early 1990s from a network of thaw tubes in the Mackenzie Valley (Box 6.7). There is considerable variation over time in the ALT records (O’Neill, Smith, Burn, Duchesne, et al., 2023; S. L. Smith et al., 2022), with higher values corresponding to years with the highest air temperatures (for example, 1998, 2006, 2012, and 2023) and lower values to colder years (for example, 1996 and 2000). Overall, trends of ALT in the Mackenzie Valley, while not statistically significant, showed an increase of about 1 cm per decade from 1991 to 2023 and of about 5 cm per decade since 2005 (S. L. Smith, Duchesne, et al., 2024). However, there is a considerable range in the magnitude of trends in the region, with some sites showing very little change over time (O’Neill, Smith, Burn, Duchesne, et al., 2023; S. L. Smith et al., 2022). A comparison of ALT measurements from 2017 to 2018 with observations from a 1962 survey along the Mackenzie Highway between Keg River, Alberta, and Hay River, Northwest Territories, found increased ALT at many sites, but little change at others over the 55-year period (Holloway and Lewkowicz, 2020).

Information on ALT changes has also been acquired from shallow temperature measurements in the Baffin region. Data collected at six sites from 2008 to 2020 indicate that ALT has increased at some sites while decreasing at others (trends of -7.5 to +2.5 cm per decade) (Duchesne et al., 2024). However, ALT has varied widely over time at these sites, mainly in ice-poor material or bedrock.

Changes in ALT have been negligible at sites underlain by ice-rich sediments. Instrumentation in the Mackenzie Valley that records maximum seasonal thaw penetration relative to a fixed reference (the ground surface elevation at the start of the record) makes it possible to determine the minimum ground surface elevation each year (Box 6.7). Records indicate that for ice-rich material, permafrost degradation, indicated by surface settlement, has occurred where thaw progressed deeper into the ground. Under such conditions, there is a smaller increase in ALT due to the accompanying settlement of the ground surface (O’Neill, Smith, Burn, Duchesne, et al., 2023; S. L. Smith, Duchesne, et al., 2024). For the sites in the Mackenzie Valley, significant loss of near-surface permafrost (median rate of 8 cm per decade) and subsidence (median rate of 4 cm per decade) occurred at over 70% of the sites, with records spanning the 1990s to the 2010s (O’Neill, Smith, Burn, Duchesne, et al., 2023).

In eastern Canada, observations from four peatland sites in Labrador indicate deeper thawing accompanied by surface subsidence from 2014 to 2023 (Y. Wang et al., 2024). A 50% decrease in height of palsas, peat plateaus or mounds, or elevated areas of frozen peat from 1968 to 2021 was also found (Beer et al., 2024).

6.7.1.3: Landscape change

Climate-driven thaw of ice-rich permafrost causes the terrain to subside (O’Neill, Smith, Burn, Duchesne, et al., 2023) and thermokarst landforms to develop (Kokelj and Jorgenson, 2013). The nature of these landforms varies with ground ice type and local terrain characteristics, such as soil type and thickness, depth of the top of underlying bedrock, and waterflow through the region (Figure 6.32) (Kokelj et al., 2023). Mapping the distribution of thermokarst landforms and tracking their changes using field-based or remotely sensed observations provides comprehensive information on the effects of permafrost thaw on a landscape and can indicate likely trajectories of future changes (Kokelj et al., 2023). Past climate-driven changes in common thermokarst landforms and their distributions are summarized below.

Retrogressive thaw slumps are a type of landslide caused by the thaw of ice-rich permafrost (Figure 6.32a1) (Kokelj et al., 2021). These chronic slope failures occur in greatest abundance and size in glacial sediments of northwestern Canada, where permafrost has preserved thick layers of relict ground ice (Kokelj, Lantz, et al., 2017). Recent studies show that thaw slumps increased significantly in association with particularly warm summers (Lewkowicz and Way, 2019; Ward Jones et al., 2019). For example, on Banks Island in the western Canadian Arctic, a 60-fold increase in the number of retrogressive thaw slumps was observed between 1984 and 2015 (Lewkowicz and Way, 2019). Once thaw slumps have started, warmer summer temperatures and extreme summer rain accelerate downslope removal of materials, perpetuating slump growth and mass wasting, causing slumps to grow extremely large (Figure 6.32a3) (Kokelj et al., 2015). These processes can thaw millions of cubic metres of permafrost at specific locations over only a few decades (Kokelj et al., 2021). In the western Canadian Arctic, where retrogressive thaw slumps are numerous in glacial deposits near the last glacial margins, they have increased in number, area, and volume up to 100-fold since the mid-1980s (Kokelj et al., 2021; Lewkowicz, 2024). In one intensely impacted 800-km² catchment, the average surface lowering in the watershed area attributed to thaw slump growth increased from 0.1 mm/yr from 1986 to 2002 to about 0.8 mm/yr from 2002 to 2018. At individual thaw slumps, more than half of the lowering can be attributed to ground ice melt, and the rest is from the flow of debris from slopes into valley bottoms and lakes, which is profoundly altering lake sediment loads, water quality, and the structure and function of aquatic ecosystems across the western Canadian Arctic, with impacts on Indigenous fisheries (Chin et al., 2016; Kokelj et al., 2021; Shakil et al., 2020; Ziegler et al., 2024, 2025).

Figure take-away: Thermokarst landforms indicate thawing permafrost across the Canadian Arctic.

Figure title: Examples of thermokarst landscapes

Figure 6.32: Thermokarst landforms indicate thawing landscapes in the Canadian Arctic. a1) to a3) Retrogressive thaw slumps on the Peel Plateau, Northwest Territories; slump area increased from a1) 1970 to a2) 2021. b1) to b3) Upland terrain with tundra polygons on Banks Island, Northwest Territories (Inuvialuit Settlement Region); increases in connected pond networks and small lakes from b1) 1961 to b2) 2019 indicate progressive thaw of permafrost across the region. c1) to c3) Permafrost peat plateaus in Labrador, outlined in black; permafrost thaw has converted much of the original peat plateau area since c1) 1948 into collapse scar bogs and fens, leaving a fraction of the original peat plateau in c2) 2023. Photo credit: for a1), b1), and c1), National Air Photo Library, roll #A21538 photo #180, roll #A17379 photo #044, and roll #LAB16(N) photo #0212; for a2), a3), and b3), Government of Northwest Territories; for b2), Maxar, 2019; for c2) and c3), Northern Environmental Geoscience Library at Queen’s University.

Tundra polygons are the surface expression of underlying ice wedge networks, which are ubiquitous throughout the tundra of the Canadian Arctic (Figure 6.32b1) (Kokelj et al., 2023). Such polygonal terrain reflects climate-sensitive permafrost because an increase in ALT can cause wedge ice to melt and the overlying troughs to expand and deepen as the ground subsides. Stratigraphic evidence from monitoring sites in Nunavik, northern Quebec, indicates that between 1989 and 2018, an increase in ALT caused the thawing of ice wedge tops across several study sites (Gagnon and Allard, 2020). Detailed monitoring of hillslope ice wedges in the Mackenzie Delta region of the western Arctic has shown thaw of slope, and an increase in hilltop wedges, resulting in subsidence in troughs of 1.8 to 3.2 cm/yr from 2007 to 2018 (Burn et al., 2021). Warm summers also influence top-down thawing of ice wedges in cold permafrost settings, such as Banks Island, in the western Canadian Arctic (Farquharson et al., 2019). This finding complements Landsat trend analysis showing an increasing wetness of tundra uplands caused by the top-down thawing of ice wedge networks (Fraser et al., 2018). The notable increase in ponds above the thawing ice wedges that began in the late 1990s was associated with several unusually warm summers, and the cause is demonstrated by a time series of high-resolution imagery showing the 10-fold increases in the number and size of ice wedge ponds (Fraser et al., 2018). Data aggregation indicates that about 17% (over 12,000 km²) of terrain on Banks Island is affected by increases in upland ice wedge ponding interpreted from Landsat imagery, indicating change on the landscape scale. A growing body of remote-sensing observations confirms that upland ice wedge thaw and pond expansion occur at sites across the western Canadian Arctic (Abolt et al., 2024).

Permafrost peatlands are a dominant component of the vast wetlands in discontinuous permafrost zones of the Taiga and Hudson plains (Vitt et al., 1994) and are locally important across all permafrost regions in Canada (Y. Wang, Way, Beer, et al., 2023). Thermokarst following permafrost thaw in palsas or peat plateaus forms bogs and fens because of thaw consolidation of the previously frozen peat and underlying mineral substrate, which both contain high volumes of ground ice. These wetland landform combinations (Figure 6.32c1) are a dominant land cover type in 370,000 km² of the southern Taiga Plains in the Northwest Territories, reflecting warm, thin, and patchy permafrost. The proportion of permafrost peatland coverage decreases from the northern to southern margin of discontinuous permafrost, with bog or fen area comprising up to 70% of the wetland areas of the southern Northwest Territories (C. Gibson et al., 2021). Field studies indicate that gradual increases in ALT from 1990 to 2015 are outpaced by area losses of peat plateaus and palsas (Mamet et al., 2017), indicating the importance of increases in water movement in accelerating the degradation of patchy, organic-rich permafrost (Devoie et al., 2021). Although cyclical patterns of permafrost thaw and formation characterize the evolution of permafrost peatlands, almost all recent studies point toward net degradation of permafrost peatland area (Beer et al., 2024; Mamet et al., 2017; Y. Wang, Way, and Beer, 2023). In coastal Labrador, this degradation, from as early as 1948, has resulted in a mean decline of permafrost extent of 0.8 to 1.5% per year (Y. Wang, Way, and Beer, 2023). Greater rates of peatland loss associated with water flow (Pironkova, 2017) are further compounded by the effects of fire (C. M. Gibson et al., 2018).

6.7.2: Causes of past changes

Robust theory and widely adopted methods identify air temperature as the first order control for permafrost temperature, thaw penetration, and near-surface permafrost area (Andersland and Ladanyi, 2003; Gruber, 2012; P. J. Williams and Smith, 1989), with snow cover and ground characteristics playing a lesser, but still significant role. Long-term trends in permafrost temperature (Figure 6.31) are generally consistent with those for air temperature (Box et al., 2021; S. L. Smith et al., 2022; S. L. Smith, Duchesne, et al., 2024). However, some of the warming may also be linked to changes in snow cover (Biskaborn et al., 2019). Shorter-term variations in ground temperature also occur. For example, lower ground temperatures since 2019 at Big Lake and Norris Creek reflect a period of lower air temperature and shallow snow cover (Figure 6.31a) (S. L. Smith, Duchesne, et al., 2024; S. L. Smith, Romanovsky, et al., 2024). Similarly, warm or cold years are reflected in ALT and thaw penetration records (O’Neill, Smith, Burn, Duchesne, et al., 2023). The magnitude of the observed change in ground temperature will additionally depend on ground properties, such as moisture and ice content. For the Northern Hemisphere, the decline in near-surface permafrost area (Guo et al., 2020) and the observed increase in permafrost temperature in 15 boreholes (Gudmundsson et al., 2022) have been attributed to anthropogenic climate change.

For some aspects of permafrost change, the seasonal timing of temperature changes is important. Thaw slump and ice wedge pond indicators show that the cold, ice-rich permafrost of the western Canadian Arctic is very sensitive to rising summer air temperatures. Large increases in the number of retrogressive thaw slumps over terrain hosting relict ground ice across the western and high Canadian Arctic regions are linked to exceptionally warm summers (Lewkowicz, 2024; Lewkowicz and Way, 2019; Ward Jones et al., 2019). The rapid enlargement and persistence of these failures can be related to warmer air temperature and increased precipitation (Kokelj et al., 2015). Warmer air temperature increases the rate of thawing at the ice-rich headwall, the part of a thaw slump that retreats as thaw continues, and increased precipitation promotes evacuation of material from the exposed area, allowing further enlargement of the slump (Kokelj et al., 2015). Widespread increases in ice wedge degradation and ponding on Banks Island and in Nunavik has been attributed to increases in ALT associated with unusually warm summers and longer-term warming over the past three decades (Farquharson et al., 2019; Fraser et al., 2018; Gagnon and Allard, 2020). Similarly, regional warming along with peatland greening has resulted in degradation and fragmentation of palsas and peat plateaus in coastal Labrador (Beer et al., 2024; Y. Wang, Way, and Beer, 2023).

Changes in the amount and timing of snowpack influence the response of ground temperature to warmer air temperature (Jan and Painter, 2020). Since the insulating effect of snow reduces winter heat loss from the ground, the ground beneath a thicker snow cover will be warmer than where snow cover is thinner, with effects compounded in wet areas (Kokelj, Palmer, et al., 2017; S. L. Smith et al., 2022; Y. Zhang et al., 2018).

Vegetation can strongly influence permafrost conditions by altering snow accumulation patterns. The expansion of shrubs in tundra regions results in deeper snow and potentially higher permafrost temperatures compared to tundra with shorter vegetation or where shrubs have been removed (R. D. Brown, Marsh, et al., 2021; Cameron et al., 2024; Kropp et al., 2020; Pelletier et al., 2019; Wilcox et al., 2019). Some simulation studies suggest that the overall warming effect resulting from snow buildup associated with the growth of taller vegetation will outweigh the effect of increased shading from that vegetation in summer (Way and Lapalme, 2021).

Wildfire accompanies climate warming and drier conditions, resulting in major disturbances to permafrost, particularly in boreal regions. Burning of vegetation, and the surface organic layer in particular, results in warmer ground temperature and greater permafrost degradation, an effect proportional to burn severity (Holloway et al., 2020; S. L. Smith et al., 2015; Y. Wang et al., 2021). Observational evidence indicates that wildfire has been an important driver of permafrost degradation in the Northwest Territories (Daly et al., 2022; C. M. Gibson et al., 2018; Young et al., 2022). In the boreal peatlands, for example, wildfire over the last three decades has been a major cause of 700 to 3700 km² (95% confidence interval) of thermokarst bog development (C. M. Gibson et al., 2018). The legacy of fires contributes to short-term increases in landslides caused by active-layer detachment and in retrogressive thaw slumps, and to a more gradual warming at depth that is linked to large deep-seated landslides (Young et al., 2022).

The interaction between landscape change and ground temperature can further compound the effects of climate warming. Subsidence associated with the thawing of ice-rich permafrost increases shallow ground warming and thawing deeper into the ground (O’Neill, Smith, Burn, Duchesne, et al., 2023; Y. Wang et al., 2024). Pond formation that can accompany subsidence promotes further ground warming and permafrost degradation, leading to thermokarst expansion of the ponds (O’Neill et al., 2020; Quinton et al., 2019). Evidence also exists of permafrost aggradation driven by local hydrology changes, including lake and pond drainage and conversion of wetlands to forest and associated effects on microclimate (B. M. Jones et al., 2022; Lantz et al., 2022; Sniderhan et al., 2023). Observations from the western Canadian Arctic show that in thaw slumps, the removal of the vegetation mat, saturation of thawed material, and snow accumulation in the depression that forms can all cause ground temperatures to rise, compounding the effects of climate warming and promoting further instability (Kokelj et al., 2009; Krautblatter et al., 2024). Analysis of ground temperatures and modelling shows that ground temperature on disturbed slopes surrounding lakes rises, which promotes thaw under shorelines, leading to further slumping (Kokelj et al., 2009). Similarly, thawing and collapse at frozen peat plateau margins and pond expansion are compounded by heat advection with water, promoting warming and lateral thawing, accelerating the shrinkage of peat plateaus (Devoie et al., 2021; Dyke and Sladen, 2022; Quinton et al., 2019).

6.7.3: Future changes

Projections of permafrost change for the Northern Hemisphere summarized in Chapter 3 of the IPCC’s Special Report on the Ocean and Cryosphere in a Changing Climate (Meredith et al., 2019) indicate that for global warming levels of 1.5°C and 2°C above pre-industrial (1850 to 1900) levels, permafrost area will eventually shrink by 30% and 40%, respectively (Chadburn et al., 2017). By 2100, thaw depth is projected to exceed 3 m in more than 25% of the Northern Hemisphere’s current permafrost region under a low emissions scenario (RCP2.6) and in more than 70% of the region under a very high emissions scenario (RCP8.5) (Meredith et al., 2019). Decreases in the Northern Hemisphere’s permafrost volume of 3,000 to 5,300 km³ are projected for each degree Celsius increase in global average temperature (Burke et al., 2020; Fox-Kemper et al., 2021). However, this projected volume change does not take into account thaw below a depth of 2 m and may therefore be an underestimate. Although these projections are for the Northern Hemisphere, comparable changes in permafrost conditions can be expected for northern Canada over the next century.

In Canada, the Canadian Land-Surface Scheme model is used to predict permafrost conditions on a national scale. Predictions using this model suggest that under a very high emissions scenario (RCP8.5), ALT will increase by 0.5 to 3 m in northern Canada in the near term (2021 to 2040) relative to the period from 1991 to 2010, while permafrost temperature at a depth of 5 m will increase by 0.5 to 3°C (Teufel and Sushama, 2022). These changes will be accompanied by a loss of soil strength affecting its ability to bear weight with implications for northern infrastructure (for example, Faki et al., 2022).

Regional climate models using intermediate (RCP4.5) and very high (RCP8.5) emissions scenarios and more recent estimates of ground ice distribution mapping (Fatolahzadeh Gheysari and Maghoul, 2024; O’Neill et al., 2019) have indicated an increasing risk of ground instability due to ground warming in northern Canadian transportation corridors over the 21st century. In southeast Labrador, numerical one-dimensional (vertical) temperature modelling at site-specific peatland locations examined the vulnerability of isolated patches of thin permafrost (< 10 m thick) under a range of emissions scenarios from low to very high (RCP2.6, RCP4.5, RCP8.5) (Y. Wang and Way, 2025; Way et al., 2018). These studies indicate that in coastal Labrador, permafrost may persist at some sites beyond 2100 under low emissions scenarios, but complete degradation of permafrost is projected by 2100 under intermediate to very high emissions scenarios, occurring by mid-century at more southerly sites or where permafrost is thinner. Increases in shrub growth accompanied by greater snow depth will increase thaw and advance the timing of permafrost loss in this region (Y. Wang and Way, 2025).

Modelling studies project the loss of permafrost extent and volume in Canada over the next century, but there are limitations associated with the approaches used because of inadequate representations of complex interactions among climate, vegetation, ground material properties, and landscape processes (S. L. Smith et al., 2022). Effects not currently accounted for include accurate representation of ground material properties, excess ice content, ground subsidence, and interactions between ground temperature and landscape change (for example, O’Neill et al., 2020). Improved regional projections and infrastructure vulnerability simulations require digital maps of ground ice information that are substantially more detailed than those commonly used for modeling on national and circumpolar scales (O’Neill et al., 2024). Better information on snow cover is also required because of the considerable spatial variability of snow cover on regional and local scales (R. D. Brown, Marsh, et al., 2021; Kokelj, Palmer, et al., 2017; Morse et al., 2012; S. L. Smith et al., 2022). Vegetation changes are expected to accompany climate warming with effects on snow cover and permafrost, but these interactions are usually not integrated into simulations of future conditions (Kropp et al., 2020; Y. Wang and Way, 2025; Way and Lapalme, 2021; Wilcox et al., 2019).

6.7.4: Knowledge gaps

A more complete characterization of permafrost landscapes is required to focus monitoring and enable landscape-scale prediction.

The spatial distribution of permafrost landforms provides critical insight into the fundamental properties and emergent behaviour of thawing landscapes (Kokelj et al., 2026). Monitoring ground temperatures, ALT, and subsidence can track site-specific indicators of changes in permafrost due to climate change (O’Neill, Smith, Burn, Duchesne, et al., 2023; S. L. Smith, Duchesne, et al., 2024; S. L. Smith et al., 2022). However, the heterogeneity of atmosphere, terrain, and ground ice conditions produces a wide range of thaw-driven landscape changes that make it difficult to upscale site-specific monitoring results (Figure 6.32) (Chiasson and Allard, 2022; O’Neill et al., 2024; S. L. Smith et al., 2022; Subedi et al., 2020; Way et al., 2021). Permafrost landforms reflect variations in subsurface properties, and tracking their change through time indicates the rates, magnitudes, and consequences of permafrost thaw (Figure 6.32). Landform mapping over broad regions depicts variation in terrain, subsurface conditions, and thaw-driven consequences, providing critical context for assessing gaps in permafrost monitoring networks, extrapolating site-specific trends, and inferring the ecosystem consequences of permafrost thaw (Kokelj et al., 2023).

A better understanding of the mechanisms and feedbacks that control permafrost responses to a changing climate is required to improve simulations of future change.

A better understanding of the complex interactions between changing climate, warming permafrost, and permafrost terrain responses is required to improve simulations and support planning and decision-making needs (Burn et al., 2025; Government of the Northwest Territories, 2019). Permafrost monitoring and ancillary data collection focused on the Mackenzie Valley corridor provide Canada’s most detailed legacy information on permafrost conditions (for example, S. L. Smith, Duchesne, et al., 2024). Coordinating similar data from across the country using coherent permafrost monitoring networks, open data management systems, and timely and transparent reporting could improve our understanding of permafrost processes and our ability to predict and project future changes (N. Brown et al., 2024; Northwest Territories Geological Survey, 2021). The key elements of a permafrost monitoring network include standards for data collection, stewardship, and reporting; a commitment to Indigenous partnerships and capacity building; coordination of sentinel sites across key landscape types; and innovation to integrate remote-sensing and field-based observational methods. Ensuring ease of access to publicly funded datasets will allow for successfully incorporating science and evidence-based information into policies, binding agreements, and strategies made at the territorial, national, and international levels (Government of the Northwest Territories, 2025).

An improved understanding of how permafrost thaw will affect built environments can inform adaptation-related decisions made by those living and working in northern Canada.

Permafrost monitoring and climate change reporting traditionally focus on the natural environment (S. L. Smith, Duchesne, et al., 2024). However, permafrost-related information is also critical for guiding design, mitigation, and adaptation planning for transportation, resource development, and community infrastructure (Allard et al., 2023). Integrating site investigation and follow-up monitoring into planning phases of infrastructure projects provides an opportunity collect larger amounts of information on the changing state of permafrost (Ensom et al., 2020; Grozic and Zhang, 2018). Given the multiple stressors on northern environments, permafrost monitoring focused on the combined effects of climate change, human activity, and other environmental disturbances is essential for informing land management, infrastructure, and adaptation planning.

A vision that supports an integrated approach and collaboration can help Canada address its permafrost knowledge needs and emerge as an international leader.

Advancing permafrost knowledge in the public interest requires a territorial and national vision that fosters coordination and collaboration among diverse knowledge generators and users (Gruber et al., 2023; Northwest Territories Geological Survey, 2021). While locally driven and project-specific monitoring remains critical to address land use and adaptation planning issues, the understanding of regional to national-scale conditions requires a distributed network that can combine resources and strategies for data stewardship, analysis, synthesis, and sharing. Strategies to enable pan-territorial coordination and knowledge-sharing are required to foster collaboration and co-development of permafrost knowledge in Canada and to support scientific syntheses, policy development, and international reporting requirements.

6.7.5: Confidence terms in key messages: summary of evidence

Key message 6.13: Permafrost at monitored locations in northern Canada has warmed and thawed since the 1980s (very high confidence). Landscapes in the parts of northern Canada with ice-rich terrain have changed in response to climate-driven permafrost thaw (very high confidence).

Key message 6.14: Permafrost warming and thaw-driven landscape changes are expected to continue with increased climate warming (very high confidence). Even if the climate stabilizes, some thawing will continue at depth (very high confidence). However, there is low confidence regarding the magnitude and timing of these changes because of the influence of local ground characteristics.

A note on attribution of changes in Canada: The key messages do not include a statement on attribution of observed changes in Canada because the few attribution studies available have been done for permafrost changes over the Northern Hemisphere as a whole. However, because of the dominant role of air temperature in controlling permafrost temperature, thaw penetration, and near-surface permafrost area (section 6.7.2), we assess that human-caused climate change is certain to be influencing the warming and thawing of permafrost in Canada.

With respect to Key Message 6.13, multiple lines of evidence from field-based observations and interpretation of remote-sensing imagery provide consistent evidence for permafrost warming and thaw across northern Canada. Analysis of in-situ measurements acquired from monitoring sites clearly indicates a rise in ground temperature since the 1980s. Observations of thaw at monitoring sites and the growing evidence of landscape change (thermokarst development) from both field-based and remotely sensed observations provide evidence that permafrost thaw and loss of permafrost volume are occurring. These results agree with those from monitoring sites throughout the northern circumpolar region. There is also a strong physical understanding of the way in which changes in climate related factors, including air temperature, snow cover, and wildfire, are driving permafrost change. Given the strong agreement among multiple high-quality lines of evidence, we have very high confidence that permafrost has warmed and thawed at places throughout northern Canada and is resulting in changes to its landscape.

With respect to Key Message 6.14, projections clearly show that permafrost will continue to warm and thaw across northern Canada as atmospheric warming continues, which agrees with the conclusions of assessments for the Northern Hemisphere. The robust understanding of key processes involved in permafrost change and the strong agreement among multiple studies give us very high confidence in continued warming and thawing of permafrost, and its delayed response at depth. However, given the limitations in the monitoring networks and models used, including the inadequate representation of important factors and processes influencing permafrost response to a changing climate (such as ground material properties, excess ice content, ground subsidence, and snow and vegetation cover), we have low confidence in the magnitude and timing of warming, thaw, and landscape change, especially on regional and local scales.

6.8: Synthesis

Key message 6.15: Coherent changes across many components of the cryosphere are evident both globally and across Canada.

Key message 6.16: The evidence for formal attribution of changes in the cryosphere to human influence, and for correlations between cryospheric and temperature signals, has strengthened. Because air temperature exerts the dominant control on many components of the cryosphere, human-caused climate change is certain to be influencing widespread changes in the cryosphere in Canada.

Key message 6.17: Changes in all components of the cryosphere are projected to worsen or intensify with additional global warming, but limiting the increases in global average temperature will limit these changes.

This section provides a high-level description of how the knowledge on the cryosphere included in this chapter and the corresponding chapter of the first edition of Canada’s Changing Climate Report (CCCR2019) (Derksen et al., 2019) compare.

Key Message 6.15 is a synthesis of the findings in this chapter and in CCCR2019 (Derksen et al., 2019) that demonstrate coherent changes across many components of the cryosphere both globally and in Canada. The number of days with snow cover, lake ice cover, and seasonally frozen ground have all decreased for Canada as a whole, along with a coherent pattern of regional increases in snow cover and lake ice cover across the prairie provinces and parts of central Ontario and Quebec. The oceans in the Canadian Arctic and Hudson Bay region have shown strong declines in all types of sea ice during summer, while off the coast of eastern Canada, decreases in sea ice cover have been observed even during winter. We have also seen increasing rates of mass loss from glaciers in both western Canada and the Canadian Arctic and wide-spread evidence of permafrost warming and thaw.

The evidence base to support Key Message 6.15 has strengthened since CCCR2019, as there has been increased quantification of changes in the mass or volume of components of the cryosphere. For many of the components analyzed in this chapter, changes in coverage or duration have historically been the easiest to detect. However, since the publication of CCCR2019, quantification of changes in the mass or volume of many components of the cryosphere has also increased. Multiple sources of snow water equivalent data indicate snow mass loss through most of the year, while measures of lake and river ice thickness indicate thinning, and rates of glacier thinning in western Canada are among the fastest in all monitored glacier regions on the planet. Likewise, estimates of sea ice thickness show thinning ice during winter and spring consistent with measurements of thinning landfast ice near coastal Arctic stations. These estimates of thinning ice have been used to quantify sea ice volume loss over the last decade. Also, while still difficult to precisely quantify, lost volume of frozen ground is evident from observations of the decreasing depth (thinning) of seasonally frozen ground and observations of warming and thawing permafrost.

Not only are changes across the cryosphere coherent, but also, compared to CCCR2019, this report provides evidence that the cryosphere in Canada is being increasingly altered beyond its range of historical conditions, particularly across the Canadian Arctic. The evidence includes unprecedented sea ice changes, such as recent formation of polynyas in the Last Ice Area, indicative of weakening ice, and the deterioration of ice arches in the Canadian Arctic Archipelago, linked to increased sea ice transport through the Canadian Arctic. Inland, mid-winter break-ups of river ice cover are increasingly common, and in parts of northern Canada with ice-rich terrain, there is evidence of increasing landscape change in response to climate-driven permafrost thaw. Wildfire has also become acknowledged as an important disturbance event across northern Canada, with the potential to intensify permafrost thaw and landscape change (sections 6.5 and 6.7 and Chapter 9, section 9.5).

While statements attributing changes in specific components of the cryosphere in Canada to human influence were not included in the other sections’ key messages, Key Message 6.16 indicates that there has been improved evidence for making such attribution statements when considering changes for the circumpolar Arctic and Northern Hemisphere. As reported in the sections on causes of past changes, observed decreases in Northern Hemisphere snow cover extent, snow mass, lake ice cover, and near-surface permafrost area, as well as decreases in Arctic-wide sea ice extent and permafrost temperature changes at select sites, have all been attributed to human-caused climate change. Human-caused climate change has also been shown to be the primary driver of global glacier retreat and mass loss. These statements depend on the existence of long-term relationships between specific cryospheric variables and temperature signals driven by atmospheric carbon dioxide concentration. However, for many components there is also improved evidence linking the year-to-year variability in each component to the year-to-year variability in air temperature. Examples referenced in this chapter include variability in snow cover extent, sea ice, lake ice, and glacial mass balance, as well as active-layer thickness, and thaw penetration over permafrost.

Key Message 6.17 is a synthesis of future changes in Canada’s cryosphere. Changes in all components of the cryosphere are expected to intensify with additional global warming, but limiting increases in global average temperature will limit these changes. For many components of the cryosphere, projections now provide more detailed information on how changes in ice or snow will scale with the level of global warming, that is, they indicate a specific change in the area or volume of ice or snow expected for each 1°C rise in global average temperature. By calculating projected changes in this way, the changes can be directly linked to global temperature policy thresholds rather than specific emissions scenarios. All of the calculations made in this way in this report are for the components of the cryosphere that respond relatively quickly to changes in global average temperature (snow, sea ice, lake and river ice, and near-surface ground). Because those components adjust quickly, any future reductions in global average temperature would result in tempered changes for those components. Glacier mass loss and permafrost warming and thaw at depth are important exceptions to the above statement. For these components of the cryosphere, there are delays of years to centuries between the initial changes in climate (for example, a rise in temperature) and the complete adjustment of these components to that change. Therefore, the level of past warming will contribute to future glacier melt and permafrost thaw for some time beyond the stabilization of global average temperature.

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Supplementary materials

Supplementary Table S6.1: Permafrost temperature data sources used in figures 6.30 and 6.31.

Column 1 contains each region shown in Figure 6.30, where individual site records are averaged. Column 2 contains the number of site records available and the years in which the sites were established. Sites established before 2000 are listed separately from sites established after 2000. Individual site records are available from the year each site was established until 2021 to 2024, depending on site location. Column 3 contains data source reference(s).

References for supplementary table S6.1

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