Chapter 4: Large-scale atmosphere-ocean processes affecting climate

Chapter description

This chapter assesses changes in processes and phenomena in the atmosphere and ocean that influence regional changes in Canadian climate, including Arctic amplification, atmosphere-ocean circulation patterns, and the large-scale conditions that lead to thunderstorms.

Chapter key messages

Plain language summary^{Footnote 1}

In this chapter, we assess changes in processes and phenomena that influence regional changes in Canadian climate and are relevant to changes in surface temperature and precipitation (discussed in chapters 2 and 3) and in other variables (discussed in chapters 5 to 9). We distinguish between climate-related changes due to processes associated with changes in radiation and heat fluxes (thermodynamic processes) and those due to processes associated with the circulation of air in the atmosphere and water in the ocean (dynamical processes).

Thermodynamic processes are the main drivers of a phenomenon referred to as Arctic amplification, that is, the Arctic region’s faster increase in surface temperature compared to the global average surface temperature. This phenomenon largely explains why Canada has warmed at a faster rate than the global average, and why northern Canada has warmed at a faster rate than southern Canada, as reported in Chapter 2. Arctic amplification will continue to dominate global and Canadian warming patterns in the future. Thermodynamic processes are also associated with other projected changes. For example, the greater availability of water vapour in the atmosphere associated with global warming leads to an increase in the intensity and frequency of atmospheric rivers—long, narrow, corridors of strong horizontal water vapour transport in the atmosphere. Thermodynamic processes also contribute to the projected increase in environmental conditions that favour the development of thunderstorms, particularly across central and eastern Canada. In addition, we expect an increase in average and maximum rain rates associated with Atlantic hurricanes and in the proportion of Atlantic hurricanes that become very strong. However, since only a small number of Atlantic hurricanes affect Canada, uncertainty exists about how these changes will impact eastern Canada.

Changes in dynamical processes, such as in the large-scale circulation of air in the atmosphere, are important for understanding and predicting climate change in Canada at a regional level but are more uncertain than changes in thermodynamic processes. This uncertainty is due to the large impact of internal climate variability on dynamical processes and to the disagreement among models about many aspects of the projected changes. Changes in the large-scale atmospheric circulation are the result of large-scale variations in temperature. For example, Arctic amplification leads to a smaller difference in the near-surface temperature between the tropics and the Arctic. This generally contributes to a shift toward the equator in the location of the jet streams, strong bands of wind that flow from west to east throughout the lowest 15 km of the atmosphere (Figure 4.6). On the other hand, increased warming in the tropics’ upper troposphere, around 10 to 15 km above the Earth’s surface, tends to lead to a larger difference in the upper-level temperature between the tropics and the poles and contributes to a strengthening of the jet streams and their shift toward the poles. Climate models suggest that in most cases, the increased warming in the tropics will dominate, causing jet streams, extratropical storms, and atmospheric rivers to migrate toward the poles under climate change. An increase in the north-south meandering of the jet streams, making them wavier, and in the strength or frequency of atmospheric blocks (very slowly moving high pressure systems), could lead to more intense and more frequent climate extremes. However, there is no robust evidence that the waviness of the jet streams and strength or frequency of blocks have changed in the past or will do so in the future.

The El Niño–Southern Oscillation is a mode of variability characterized by fluctuations every two to seven years in sea surface temperatures and air pressure in the tropical Pacific Ocean. This mode of variability is also associated with large year-to-year fluctuations in Canadian climate. Currently limited mainly to western Canada, these fluctuations are projected to extend to central and eastern Canada in response to additional climate warming. However, these projections are uncertain due to systematic climate model biases in the tropical Pacific.

Future warming over eastern and northern Canada may be slightly reduced by a projected weakening of the Atlantic Meridional Overturning Circulation, the primary large-scale ocean current affecting Canadian climate, but the magnitude of this cooling influence is uncertain. A substantially larger cooling influence over eastern and northern Canada associated with a possible shutdown of this ocean current in this century cannot be ruled out.

4.1: Introduction

Chapters 2 and 3 provide detailed assessments of past and future average changes in temperature, precipitation, and surface winds, and a general overview of past and future changes in specific aspects of Canada’s climate based on the detailed assessments of those changes in chapters 4 to 9. This chapter is the first of those more technical chapters and describes and assesses changes in large-scale atmosphere and ocean processes that affect most other aspects of climate change in Canada discussed in other chapters. It assesses processes and phenomena that occur in the atmosphere and ocean on scales of more than 100 km, and that shape patterns of change in Canadian climate (figures 4.1, 4.3, Box 4.1). These large-scale processes explain why Canada is warming at a faster rate than the global average. They also contribute to spatial variations in temperature and precipitation changes in Canada, and to the other aspects of climate change in Canada described in chapters 5 to 9. For a more general overview of global processes that are responsible for global climate change, see chapters 2 and 3 of the first edition of Canada’s Changing Climate Report (CCCR2019). An overview of the spatial and temporal scales of the processes assessed in this chapter is in Figure 4.1.

Figure take-away: Atmosphere-ocean processes and phenomena that influence climate change in Canada occur on a wide range of time and space scales

Figure title: Atmosphere-ocean processes relevant to climate change in Canada and assessed in this chapter

Regional variations in climate and climate change in Canada are partly governed by thermodynamic processes. Thermodynamic processes are those linked to changes in radiation and heat fluxes and have a direct connection to climate and climate change through their impacts on temperature and humidity. These processes often include feedbacks, where a particular change in the climate system drives a change in another aspect of the climate system that amplifies or weakens the original change. Feedbacks lead to a phenomenon known as Arctic amplification, that is, the Arctic region’s faster increase in surface temperature compared to the global average. This phenomenon largely explains why Canada is warming at a faster rate than the global average (see also FAQ 4.1), and why northern Canada is warming at a faster rate than southern Canada. Arctic amplification is assessed in section 4.2.

Regional variations in Canadian climate and climate change in Canada are also shaped by dynamical processes. These processes are responsible for the large-scale circulation of air and water. There is generally more uncertainty about human-induced changes in dynamical processes compared to thermodynamic processes (Shepherd, 2014). This is because changes in the large-scale circulation are usually the result of multiple, often competing processes. In addition, changes in the large-scale circulation often depend on changes in the spatial variations (or gradients) of large-scale thermodynamic conditions (such as those associated with Arctic amplification). The large-scale atmospheric circulation shapes regional variations in Canadian temperature and precipitation. For example, since the winds over mid-latitudes blow most often from west to east, relatively temperate and humid ocean air is transported to Canada’s west coast, making this region’s climate more temperate and humid than other parts of Canada. Also, the coldest days of the year are typically experienced when cold Arctic air is transported south by winds that blow from north to south. Changes in the strength and direction of winds will therefore lead to regional changes in surface temperature and precipitation.

A complicating factor in understanding past trends in the large-scale circulation is the fact that trends over periods shorter than a few decades are often dominated by internal climate variability, that is, fluctuations in the climate that are not caused by external climate forcings (Chapter 3, section 3.3.3). Since it is often not clear which part of the observed changes is due to external climate forcings (such as increasing greenhouse gases in the atmosphere due to human activity) and which part is due to internal climate variability, determining the cause of past trends can be challenging. Internal climate variability in Canada manifests itself on essentially all timescales and is the result of complex interactions in the climate system. It is often associated with “modes of internal variability,” meaning elements of the climate system that generally alternate between one set of patterns (or phase) and another (such as the El Niño–Southern Oscillation). These modes are often the result of feedbacks that lead to organized, large-scale fluctuations on timescales of weeks to decades. While this chapter focuses on trends in climate averaged over longer periods (typically 30 years), we also consider how modes of internal climate variability can be influenced by external climate forcing (such as greenhouse gas emissions due to human activity). Separating changes that are externally forced from those that are due to internal climate variability is particularly challenging when external climate forcing results in patterns of average change that resemble one of the phases of a mode of internal climate variability. Atmospheric modes of variability (such as the North Atlantic Oscillation) are discussed in section 4.3, and coupled atmosphere-ocean modes (including the El Niño–Southern Oscillation) are discussed in section 4.8.

Large internal climate variability also introduces uncertainty about projections of the atmospheric circulation and associated regional changes in temperature and precipitation. The projected near-term changes in low-level west-to-east wind, surface temperature, and precipitation simulated by version 5 of the Canadian Earth System Model are shown in Figure 4.2. An ensemble of 50 simulations was run with identical external climate forcings but with small perturbations through which different “realizations” of internal climate variability were generated (Chapter 3, section 3.3.3). The first column shows the average of the 50 simulations, in which the effect of internal climate variability is averaged out and hence represents the projected change caused by external climate forcings. Differences in responses between these simulations are unrelated to external climate forcings and are therefore the result of internal climate variability. The impact of this internal climate variability is illustrated by the second and third columns, which show projections in two simulations with opposing changes in wind. The simulation with a projected increase in wind over the Pacific Ocean (realization #13) features more transport of relatively warm and humid ocean air into western Canada, resulting in more warming and precipitation over western Canada than the simulation with a projected decrease in wind over the Pacific Ocean (realization #35). As internal climate variability cannot be predicted more than a few years in advance and these are projections for the near term relative to the pre-industrial period (approximated in this report as 1850 to 1900), both simulations are equally plausible. The large difference in regional climate responses between these two simulations highlights the large degree of uncertainty about regional climate change caused by internal climate variability, especially with regard to changes in precipitation.

Figure take-away: Internal climate variability has a large influence on the projections of the atmospheric circulation and associated temperature and precipitation patterns.

Figure title: Wind, surface temperature, and precipitation projections in a large ensemble of climate model simulations

An additional common challenge in assessing changes in large-scale phenomena is the fact that there is some subjectivity in how these phenomena are defined. For example, as discussed in section 4.4, there are several complementary definitions of atmospheric blocks commonly used in the scientific literature. Observed and projected trends can be sensitive to the definition, which introduces additional uncertainty. This also applies to atmospheric rivers, discussed in section 4.5.

The outline of this chapter is as follows. In section 4.2, we assess changes in Arctic amplification and their implications for Canadian temperatures. In sections 4.3 to 4.6, we assess changes in the horizontal large-scale atmospheric circulation that impact Canada’s average climate and climate extremes. Section 4.3 focuses on jet streams, storm tracks, and atmospheric modes of variability, such as the North Atlantic Oscillation. Section 4.4 focuses on changes in extratropical storms, extratropical high-pressure systems, and atmospheric blocks that affect Canada. Section 4.5 assesses changes in atmospheric rivers, while section 4.6 assesses changes in North Atlantic hurricanes. Changes in the vertical atmospheric circulation, and in particular changes in the large-scale environmental conditions that favour the development of thunderstorms over Canada, are assessed in section 4.7. Finally, sections 4.8 and 4.9 assess large-scale processes that involve the ocean. Changes in atmosphere-ocean coupled climate processes that impact the amplitude of year-to-year and decade-to-decade variability in Canadian climate, such as El Niño and La Niña, are assessed in section 4.8. Changes in the ocean circulation and its impact on Canadian climate are assessed in section 4.9.

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 4 and key cross-chapter linkages

4.2: Arctic amplification

Key message 4.1: The Arctic (the region north of the Arctic circle) has warmed at more than three times the rate of the global average over the past five decades (high confidence^{Footnote 2} ). Most of this increased warming, known as Arctic amplification, is caused by human influence (high confidence) and involves local climate processes and feedbacks, including sea ice loss. It largely explains why Canada has warmed nearly twice as fast as the global average and the Canadian Arctic three times as fast for the period 1970-2023 (high confidence).

Key message 4.2: Arctic amplification, and the greater rate of warming in Canada’s Arctic compared to the rest of Canada, will continue over the 21st century (very high confidence). In the coming decades, the Canadian Arctic is projected to warm at more than twice the rate of the global average (medium confidence).

4.2.1: Effects on Canadian weather and climate

As described in Chapter 2, in FAQ 4.1, and previously in CCCR2019, Canada and, to a greater extent, northern Canada are warming faster than the global average. This is largely related to a phenomenon known as Arctic amplification, the Arctic region’s faster increase in surface temperature compared to that of most other regions of the world (Holland & Bitz, 2003; Previdi et al., 2021; Serreze & Barry, 2011; Taylor et al., 2022). The rapid warming of the Arctic is having profound impacts on sensitive Arctic ecosystems and on First Nations, Inuit, and Métis livelihoods and ways of life (Hancock et al., 2022; Moon et al., 2024).

The Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report (AR6) Working Group I (WGI) (IPCC AR6 WGI) determined (see section 7.4.4.1.3 in Forster et al., 2021) that there is high confidence that Arctic amplification “is a robust feature of the long-term response to greenhouse gas forcing.” Arctic amplification is quantified using the Arctic amplification factor, meaning the ratio of Arctic average surface temperature change to global average surface temperature change. Thus, a value greater than 1 indicates that the Arctic has warmed at a greater rate than the global average.

Arctic amplification is primarily driven by local climate feedbacks that act to amplify the warming from increasing atmospheric greenhouse gas concentrations. For example, Arctic warming leads to increased snow and sea ice melt, decreasing the amount of solar radiation that is reflected, which then further increases Arctic warming. These positive (amplifying) feedbacks are typically referred to as the snow and sea ice albedo feedbacks (see Box 4.2 for more information about the processes and feedbacks contributing to Arctic amplification). Arctic amplification affects the entire Arctic and thus impacts temperatures in northern Canada. Arctic amplification contributes to greater warming in Canada compared to the global average and greater observed warming in northern Canada compared to southern Canada, as well as to the seasonal patterns of warming in Canada, with a peak in late fall and early winter (Box 4.2, FAQ 4.1; Chapter 2, section 2.4.1). These spatial and seasonal patterns show up in the observed increase in surface temperature across the country (Chapter 2, section 2.4.1) and the observed decrease in the intensity and frequency of extreme cold spells, particularly in northern Canada (Chapter 8, section 8.2.1), and are related to a decline in snow cover and sea ice (Chapter 6, sections 6.2.2 and 6.3.2). Arctic amplification does not substantially change either the north-south meandering of the jet stream or storm tracks (section 4.3, Box 4.4).

4.2.2: Past changes and their causes

Surface temperature measurements in the Arctic consist of land-based weather station measurements of surface air temperature and sea surface temperature measurements from buoys and ships. However, because of the perennial ice cover across much of the Arctic Ocean, measurements in the central Arctic are limited. Global gridded observational data products (see Figure 4.4 and FAQ 4.1 Figure 1 for examples and Chapter 2, section 2.3.3, for a detailed description) therefore employ interpolation techniques (estimations of unknown data based on known data) to fill in the gaps in data-sparse regions like the Arctic contributing to uncertainty about Arctic surface temperature trends  (see section 2.3.1.1.3 in Gulev et al., 2021; Lenssen, 2022). When in-situ (on-location) data, satellite data, or reanalysis data (explained below) are used to assess these interpolated data products, interpolation is found to improve estimates of global and Arctic averaged temperature change compared to the alternative of estimates that ignore regions with little or no data (Cowtan & Way, 2014; Lenssen et al., 2019; Simmons et al., 2017). Although gridded observational data products have improved, there has been a recent reduction in in-situ data gathering in the Arctic due to both the decline in the number of weather stations across Canada’s North (Voosen, 2023) and the exclusion of Russia from internationally coordinated Arctic monitoring programs since 2022 (López-Blanco et al., 2024; Witze, 2022). This reduction may introduce a bias in regional estimates of Arctic surface temperature. Reanalysis data products provide a complementary but not independent alternative to gridded observational data products (Chapter 2, section 2.3.3). Reanalysis data products are numerical representations of the recent past global climate and are produced by combining a collection of in-situ and satellite observations of the atmosphere, land surface, and ocean with state-of-the-art weather forecast models. They provide temporal and spatial consistency and completeness. In the remainder of section 4.2.2, both gridded observational data products and reanalysis data will be assessed.

Figure take-away: Arctic warming and Arctic amplification have become stronger in recent decades.

Figure title: Past surface temperature trends and local amplification for the Arctic and sub-Arctic regions

Since the mid-20th century, the Arctic has been warming at a faster rate than the global average (Figure 4.4). Given this updated analysis and previous studies, there is high confidence that annual average surface temperature in the Arctic as a whole has warmed at more than three times the rate of the global average since the 1970s (Figure 4.4d) (Chylek et al., 2022; Douville, 2023; Lenssen, 2022; Rantanen et al., 2022). This is equivalent to an Arctic amplification factor of more than 3. Arctic amplification peaks in late fall and reaches a low in summer (Box 4.1) (Previdi et al., 2021; Rantanen et al., 2022; Taylor et al., 2022), and the region with the greatest amplification corresponds to the region with the greatest sea ice loss (Previdi et al., 2021). Arctic amplification has contributed to past warming rates of close to two times in Canada and three times in the Canadian Arctic compared to the global average (FAQ 4.1). Studies estimate that Arctic amplification only became discernable during the late 20th century (England et al., 2021). Before then, Arctic warming from anthropogenic (human-caused) greenhouse gas emissions was masked by large internal climate variability and the cooling effect of anthropogenic aerosols, that is, particulates in the air created by human activities such as burning fossil fuels (X. Chen & Dai, 2024; Douville, 2023; England et al., 2021; Holland & Landrum, 2021; Najafi et al., 2015; Previdi et al., 2023; Y.-T. Wu et al., 2024).

There is high confidence that most of the observed Arctic amplification is due to human activities. Three independent studies calculated the human-caused part of Arctic amplification by removing from the observations for 1979 to 2022 the part of Arctic amplification that is due to internal climate variability. They found that human activity is responsible for 75% of the observed Arctic amplification. The Arctic amplification factor associated with human activity is close to the corresponding value in the multi-model average (Douville, 2023; Sweeney et al., 2023; W. Zhou et al., 2024).

4.2.3: Future changes

Arctic amplification will continue to be a dominant pattern of climate change over the 21st century (very high confidence) (Davy & Griewank, 2023; Douville, 2023; see Section 7.4.4.1.3 in Forster et al., 2021; Ono et al., 2022; Y. Wu et al., 2023). This is consistent with projected warming for Canada, where Arctic amplification will continue to contribute to greater warming in northern Canada compared to southern Canada (Chapter 3). There is medium confidence in the projected magnitude of Arctic amplification, however, with Arctic warming by the end of the century ranging from 1.5 to 3.5 times the global average across climate models (Hay et al., 2024; Linke et al., 2023; Ono et al., 2022). Because Arctic amplification reflects the warming of the Arctic relative to the global average (the ratio of Arctic warming to global warming), it is relatively insensitive to the emissions scenario (Hay et al., 2024). The large range in projected Arctic amplification primarily results from internal climate variability and differences in the representation of climate feedbacks between models, which can affect the projected rate of both global and Arctic warming (Z. Cai et al., 2021; Y. Wu et al., 2023).

While Arctic amplification will continue over the 21st century, climate models project a shift in the timing of peak Arctic amplification from late fall to early winter as the sea ice minimum occurs later in the fall, particularly for high emissions scenarios (medium confidence). The projected time frame for this shift from fall to winter is uncertain, reflecting both model differences and internal climate variability (Davy & Griewank, 2023; Douville, 2023; Hahn et al., 2022; Holland & Landrum, 2021; Liang, Polvani, & Mitevski, 2022; Taylor et al., 2022; Y. Wu et al., 2023).

In addition to a projected shift in the seasonal timing of Arctic amplification, some studies suggest that the annual average strength of Arctic amplification peaks and then declines with additional warming. As the climate warms, there is less snow and sea ice available to melt. This reduces the amplifying snow and sea ice albedo feedbacks. As a result, subsequent warming will be less amplified in the Arctic, which contributes to a decline in the magnitude of the Arctic amplification factor (see Box 4.1 for more information on climate feedbacks) (Dai et al., 2019; Davy & Griewank, 2023; Douville, 2023; Holland & Landrum, 2021). A decline in Arctic amplification may also result from a decrease in poleward heat transport by the Atlantic Meridional Overturning Circulation (section 4.9) (W. Liu et al., 2020). There is substantial uncertainty about the projected year and strength of a peak-and-decline due to the large amount of variability across models (Davy & Griewank, 2023; Douville, 2023). Additional uncertainty about a projected peak-and-decline is due to a sensitivity to the reference period: a peak-and-decline of Arctic amplification is projected when using mid-to-late 20th-century reference periods, but not when using a pre-industrial reference period (Hay et al., 2024). Overall, confidence in a projected peak-and-decline in Arctic amplification is low. It is important to note that a future decline in the magnitude of Arctic amplification would not indicate that the Arctic is no longer warming, but that the rate of Arctic warming relative to global warming is declining.

Projected trends for the Canadian Arctic are similar to what is described above for the entire Arctic. CMIP6 models project that the Canadian Arctic amplification factor will stabilize around an annual average value of slightly more than 2 (medium confidence; Figure 4.5a). This is consistent with what is observed, given the large role of internal climate variability in the observational record (section 4.2.2). Models also project a shift in seasonal timing of Arctic amplification in the Canadian Arctic (Figure 4.5b), which is most pronounced in high (SSP3-7.0) and very high (SSP5-8.5) emissions scenarios for the Canadian Arctic.

Figure take-away: Arctic amplification in Canada stabilizes in the near term and the seasonal timing shifts from late fall to early winter by late-century.

Figure title: Projected evolution of Arctic amplification in Canada with warming

4.2.4: Confidence terms in key messages: summary of evidence

Key message 4.1: The Arctic (the region north of the Arctic circle) has warmed at more than three times the rate of the global average over the past five decades (high confidence). Most of this increased warming, known as Arctic amplification, is caused by human influence (high confidence) and involves local climate processes and feedbacks, including sea ice loss. It largely explains why Canada has warmed nearly twice as fast as the global average and the Canadian Arctic three times as fast for the period 1970-2023 (high confidence).

Key message 4.2: Arctic amplification, and the greater rate of warming in Canada’s Arctic compared to the rest of Canada, will continue over the 21st century (very high confidence). In the coming decades, the Canadian Arctic is projected to warm at more than twice the rate of the global average (medium confidence).

In summary, we have high confidence that the Arctic has warmed more than three times faster than the global average, and that this is contributing to the nearly two times greater observed warming in Canada and three times greater observed warming in the Canadian Arctic in recent decades. Moreover, we have high confidence that most of the recent Arctic amplification is attributable to human-caused climate change. This assessment is supported by evidence from multiple studies and analyses based on various observational and reanalysis data products, historical climate model simulations, and theoretical understanding of Arctic amplification, and is consistent with the IPCC AR6 WGI assessment.

We have very high confidence that Arctic amplification will continue over the 21st century and will continue to contribute to greater warming in the Canadian Arctic compared to southern Canada. This assessment is based on multiple studies and analyses using CMIP6 climate model projections and is consistent with the IPCC AR6 WGI assessment. Our medium confidence in the future strength of Canadian Arctic amplification, with an annual average value of slightly more than 2, is due to large internal climate variability, and climate model uncertainty about the relative contributions of the numerous climate feedbacks that cause Arctic amplification.

4.3: Jet streams, storm tracks, and atmospheric modes of variability

Key message 4.3: Changes in recent decades in the jet streams and storm tracks that affect Canada are small and seen only in limited seasons and regions. There is low confidence in any human influence on these past changes. An overall poleward shift in the jet streams and storm tracks is projected by the end of the 21st century, but the changes are small and depend on the region and season (low confidence).

4.3.1: Effects on Canadian weather and climate

Jet streams are strong bands of wind that flow from west to east throughout the lowest 15 km of the atmosphere that are driven by temperature differences between high and low latitudes, and the Earth’s rotation (Figure 4.6). In the Northern Hemisphere, the strongest jet streams occur over the Pacific and Atlantic oceans. Jet streams are closely linked with extratropical storms (section 4.4), which travel from west to east and tend to occur just to the north of the jet stream in regions referred to as storm track regions. The position and strength of the jet streams vary naturally on all timescales from days to multiple decades. Changes in the position and strength of the jet streams are closely connected to modes of variability, like the North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) (see Box 2.5 of CCCR2019). A positive phase of the AO is defined by lower than average pressure over the Arctic and higher than average pressure in the mid-latitudes, and is linked with a stronger, more poleward jet stream. The NAO is the regional manifestation of the AO over the Atlantic, and its positive phase is associated with a stronger and more northward jet stream over the North Atlantic (Figure 4.7). The negative phases of the AO and NAO have opposite changes in pressure and the jet stream relative to the positive phases.

Variability in the jet streams can have a large influence on weather and climate variability in Canada, but the exact influence can vary by region and season. For example, a stronger jet stream in the North Pacific during winter causes warmer and wetter weather on the west coast. A stronger North Pacific jet stream is also associated with a strengthening of the storm tracks. This means stronger or more frequent extratropical storms or both affecting the west coast. Shifts in the position of the Pacific jet stream and associated storm tracks strongly influence the amount and location of precipitation on the west coast. A stronger and more poleward Atlantic jet stream (associated with the positive phase of the NAO) during winter brings colder temperatures and less precipitation on the east coast of Canada (Figure 4.7). During summer, extratropical storms bring cooler ocean air over land. As a result, weaker than normal storm tracks (weaker or fewer storms or both) tend to lead to warmer temperatures and extreme heat (Coumou et al., 2015). Because the jet stream separates colder air to the north from warmer air to the south (Figure 4.6), large meanders or waves in the jet stream are linked to extreme temperatures (Screen & Simmonds, 2014). For example, extreme events such as the Pacific Northwest heatwave of June 2021 (Neal et al., 2022) and the extreme cold across central and eastern Canada during the winter of December 2013 to February 2014 (Watson et al., 2016) were associated with large meanders in the jet stream.

Figure take-away: The position and strength of the jet streams affect regional weather and climate.

Figure title: Illustration of the jet stream, and associated temperature anomalies

Unlike changes directly associated with temperature, it is not clear from physical reasoning how jet streams, storms tracks, and modes of variability might change in a warming climate. This uncertainty is due to the opposing influences of various processes that all have uncertain magnitudes (T. Shaw et al., 2016). For example, strong warming in the Arctic due to Arctic amplification decreases the north-south temperature gradients in the lower troposphere of the Northern Hemisphere (section 4.2). This decrease in the lower troposphere opposes the increase in the north-south temperature gradient in the upper troposphere (around 10 to 15 km above the Earth’s surface) associated with increased warming in the tropics (see also Box 4.4) (Barnes & Polvani, 2015). Other processes, such as changes in clouds (Ceppi & Hartmann, 2015) and the strength of the circulation in the stratosphere (15 to 50 km above the Earth’s surface) (Karpechko et al., 2022), will also likely play a role in determining how jet streams may change in a warming climate.

Figure take-away: Each North Atlantic Oscillation phase is associated with a different winter climate pattern in Canada.

Figure title: The effects of the North Atlantic Oscillation on winter climate in Canada

4.3.2: Past changes and their causes

Past changes in the position and strength of jet streams are generally small relative to internal climate variability, are regionally complex, and can depend on the time period considered (Blackport & Fyfe, 2022; Manney & Hegglin, 2018; Simmons, 2022). The IPCC AR6 assesses that the jet streams “have likely been shifting poleward in both hemispheres since the 1980s with marked seasonality in trends (medium confidence)” (see section 2.3.1.4.3 in Gulev et al., 2021). In the Northern Hemisphere, the poleward shift is most evident over the Pacific Ocean during winter, where the trends since 1980 do not depend on the choice of dataset or how the position of the jet stream is defined (Keel et al., 2024).

One way to determine changes in the jet streams is by looking at changes in the west-to-east low-level winds (at about 3 km above the Earth’s surface). The poleward shift in the Pacific jet stream is indicated by stronger low-level west-to-east winds north of the average position of the jet stream and weaker low-level west-to-east winds south of the average position of the jet stream (Figure 4.8). The Pacific jet stream has generally shifted toward the North Pole in other seasons too, but the trends are weak and not statistically significant (Keel et al., 2024). Over the Atlantic Ocean, since 1980, the jet stream has strengthened in winter and spring, shifted toward the pole in fall, and shifted toward the equator in summer (Figure 4.8). The past trends can depend strongly on the start year they are calculated from. For example, when the trends are calculated starting from the mid-20th century instead of 1980, the trend toward a stronger winter North Atlantic jet stream is larger (Blackport & Fyfe, 2022) and the poleward shift in the winter Pacific jet stream is substantially weaker (Patterson & O’Reilly, 2025).

Attributing past trends to specific causes is challenging because of small signal-to-noise ratios in most regions and seasons. In addition, climate models perform poorly in reproducing past trends and variability (Blackport & Fyfe, 2022; Bracegirdle et al., 2018; Patterson & O’Reilly, 2025), making it difficult to understand the causes of the changes. Overall, confidence in attributing jet stream trends to human influence is low.

Figure take-away: The past trends in the strength and position of the Northern Hemisphere jet streams are generally weak and depend on the region and season.

Figure title: Past trends in low-level west-to-east wind speeds across Canada and surrounding oceans

Changes in storm tracks are consistent with changes in jet streams. In winter, the Pacific storm track has strengthened (which is associated with stronger or more frequent extratropical storms or both) and shifted poleward (E. K. M. Chang & Yau, 2016). The Atlantic storm track has strengthened with little change in position since the mid-20th century, but over the shorter period since 1980 the strengthening has been small and not statistically significant (E. K. M. Chang & Yau, 2016). The causes of these changes are difficult to assess because of the small signal-to-noise ratios and lack of studies directly comparing historical model simulations and observations. However, the strengthening of the North Atlantic storm track and the poleward shift in the Pacific storm track are consistent with projections, but the strengthening of the Pacific storm track is not seen in projections (section 4.3.3). In summer, storm tracks have weakened (which is associated with weaker or fewer extratropical storms or both) over the Northern Hemisphere (Coumou et al., 2015), and this weakening is more pronounced over North America (E. K. M. Chang et al., 2016). The weakened summer storm tracks are also seen in historical climate model simulations (E. K. M. Chang et al., 2016; Chemke & Coumou, 2024; Kang et al., 2023) and can be attributed to human-caused forcing (medium confidence) (Chemke & Coumou, 2024; Kang et al., 2024). However, the mechanisms are not well understood (Kang et al., 2023).

Past trends in the NAO and AO are dominated by a large amount of variability over many decades, making it difficult to identify robust changes. Since the mid-20th century, there has been a trend toward the positive phase of the NAO and AO during winter (Blackport & Fyfe, 2022; Eyring et al., 2021a). The upward trend is primarily a result of a strong increase that occurred from the 1960s to the 1990s. This increase was followed by a reversal of the trend toward the negative phase of the NAO and AO from the 1990s until the early 2010s, and a period of a positive NAO and AO in the last decade. This has resulted in very weak trends since 1980, as also reflected in the weak trends in the winter Atlantic jet stream shown in Figure 4.8a. The observed upward trend in the winter NAO and AO since the middle of the 20th century is outside of the range of trends in model simulations, which indicate only a very weak upward trend on average (Blackport & Fyfe, 2022; Eyring et al., 2021b). The discrepancy between models and observations makes it challenging to understand and attribute the trends. There is evidence that the NAO showed a strong downward trend during summers from the 1990s until the early 2010s (Hanna et al., 2015). However, this trend has not continued, and the longer-term trends remain small relative to internal climate variability (Hanna et al., 2022).

Some studies have suggested that Arctic amplification (section 4.2, boxes 4.3, 4.4) has caused jet streams to become “wavier” over recent decades, meaning they have larger meanders (Cohen et al., 2020; Francis & Vavrus, 2012). However, the metrics used to measure jet stream waviness have been shown to be flawed, and better metrics show a lack of statistically significant trends (Barnes, 2013; Screen & Simmonds, 2013). Updated trends and metrics show little change in jet stream waviness since 1979 relative to internal climate variability over both the Northern Hemisphere and Canada (Blackport & Screen, 2020), despite substantial Arctic amplification.

4.3.3: Future changes

Climate models project that changes in the jet streams due to additional global warming will be small relative to internal climate variability, and will vary by season and region (C. Li et al., 2018; Oudar et al., 2020; Simpson et al., 2014). The IPCC AR6 WGI reported overall low confidence in projected regional changes in the Northern Hemisphere’s low-level west-to-east winds, particularly for the North Atlantic region in winter (Lee et al., 2021). Although there is a general tendency for a small poleward shift in both the Atlantic and Pacific jet streams, the magnitude of the shift is uncertain across individual models and seasons (Barnes & Polvani, 2013).

On average, climate models project a poleward shift in the jet streams and low-level west-to-east winds during spring and fall by the end of the 21st century under very high (RCP8.5) (Simpson et al., 2014) and intermediate (SSP2-4.5) emissions scenarios (Figure 4.9b,d). The projected shift shows better model agreement and is most pronounced during fall (Figure 4.9d). In summer, the Atlantic jet stream is projected to shift toward the North Pole while the Pacific jet stream is projected to weaken. In winter, the projected changes are more complex and uncertain. While the winter Pacific jet stream is projected to shift toward the North Pole, its eastern flank over the west coast of North America is projected to shift toward the equator, but with less model agreement (Figure 4.9a). The winter Atlantic jet stream appears to show only small changes with little model agreement (Figure 4.9a). However, these small apparent changes are a consequence of a robust poleward shift in early winter and an equatorward shift in later winter (García-Burgos et al., 2024).

Figure take-away: The jet streams are generally projected to shift toward the North Pole with additional climate warming, but this varies by season and region.

Figure title: Projected changes in low-level west-to-east winds

The uncertainty and large model spread in the response is in part due to the competing effects of upper and lower tropospheric temperature gradients (Oudar et al., 2020). In addition to model uncertainty, internal climate variability in the jet stream is expected to dominate over the forced response in near-term projections (Barnes & Polvani, 2015) and in projections at 1.5°C and 2.0°C warming (C. Li et al., 2018). Note that, except for fall, the projected trends in the jet stream over North America (Figure 4.9) appear different from the observed trends (Figure 4.8). These differences could be due to either model error or internal climate variability that has overwhelmed any forced trends. These discrepancies between observed trends and model projections contribute to the low confidence in both the projected responses and the attribution of the observed trend during these seasons.

Projected winter storm track changes are uncertain but show a small poleward shift, weakening over the Pacific and strengthening over the Atlantic by the end of the 21st century under intermediate (RCP4.5, SSP2-4.5) and very high (RCP8.5) emissions scenarios (Harvey et al., 2014, 2020). There is strong agreement across climate models that the summer storm tracks will weaken (have fewer or less intense storms or both) over North America and the mid-latitudes by the end of the 21st century under intermediate (RCP4.5, SSP2-4.5) and very high (RCP8.5, SSP5-8.5) emissions scenarios (E. K. M. Chang et al., 2016; Coumou et al., 2015; Harvey et al., 2020). However, there are disagreements on the amount that they weaken (Coumou et al., 2015), and the mechanism is not well understood (Kang et al., 2023).

Climate models generally project that the NAO and AO will shift toward their positive phases relative to the current climate, in all seasons except summer. The shift during winter is robust across most models under very high emissions scenarios (RCP8.5, SSP5-8.5) by the end of the 21st century, but there is strong disagreement across models in the magnitude that the NAO and AO will shift (Lee et al., 2021; McKenna & Maycock, 2021). In the near term (under all emissions scenarios) and for the end of the century under very low (SSP1-1.9) to intermediate (SSP2-4.5) emissions scenarios, the projected changes in the NAO and AO are relatively small compared to the magnitude of internal climate variability, and there is considerable spread across models (Lee et al., 2021). Models project little change in the AO during summer under all scenarios (Lee et al., 2021).

On average, climate models project little change in jet stream waviness, but with some spread across models and some dependence on season. A small decrease in jet stream waviness in the mid-troposphere over North America is projected for most seasons under high (SSP3-7.0) and very high (RCP8.5) emissions scenario by the end of the 21st century (Barnes & Polvani, 2015; Cattiaux et al., 2016; Nie et al., 2023; Yamamoto & Martineau, 2024). The projected decrease in waviness is more pronounced during summer and shows strong model agreement. In near-term projections, the changes in waviness are small compared to internal climate variability and model spread in all seasons (Barnes & Polvani, 2015). Overall, confidence in how jet stream waviness will change as the climate warms is low.

The low confidence in climate model projections of jet streams, storm tracks, and atmospheric modes of variability is due to weaknesses in models’ abilities to simulate observed changes and variability. This is particularly the case over the North Atlantic during winter where models appear to underestimate predictable signals in the NAO and the jet stream on seasonal timescales (Scaife & Smith, 2018), and underestimate variability on multidecadal timescales (Bracegirdle et al., 2018). The observed changes in the winter North Atlantic jet stream’s strength and NAO since the middle of the 20th century are also outside the ranges simulated by models, even after accounting for internal climate variability (Blackport & Fyfe, 2022). The reasons for these discrepancies between models and observations are not known, which means that their implications for the projections are uncertain.

4.3.4: Confidence terms in key messages: summary of evidence

Key message 4.3: Changes in recent decades in the jet streams and storm tracks that affect Canada are small and seen only in limited seasons and regions. There is low confidence in any human influence on these past changes. An overall poleward shift in the jet streams and storm tracks is projected by the end of the 21st century, but the changes are small and depend on the region and season (low confidence).

In short, we have low confidence in any human influence on changes in the jet streams, storm tracks, and atmospheric modes of variability that affect Canada. This assessment is based on the small magnitude of the trends compared to the large internal climate variability in most seasons and regions. In addition, climate models have difficulty capturing the past changes, making it challenging to understand the causes of those changes. The jet streams and storm tracks across Canada and the oceans around Canada are projected to shift poleward in a warming climate in some regions and seasons, but we have low confidence in such projections. This is because of disagreement across individual models, known model weaknesses, and a lack of understanding of the underlying physical mechanisms.

4.4: Extratropical storms and atmospheric blocks

Key message 4.4: Changes in recent decades in the frequency and intensity of extratropical storms and of atmospheric blocks are uncertain. There is low confidence in any human influence on these past changes. A poleward shift in extratropical storms and a decrease in the frequency of summer extratropical storms are projected over Canada (low confidence). Atmospheric blocks are projected to occur less frequently over Canada, but there are large regional variations (low confidence).

4.4.1: Effects on Canadian weather and climate

Extratropical cyclones are low-pressure weather systems occurring outside of the tropics. These are referred to as extratropical storms in this chapter. Their weather counterparts are extratropical anticyclones, which are referred to as extratropical high-pressure systems in this chapter. These extratropical storms and high-pressure systems are the dominant large-scale weather systems travelling across Canada. These weather systems typically travel from west to east with the jet stream. Strong extratropical high-pressure systems that persist over one region for several days or more are referred to as atmospheric blocks. The impacts of extratropical storms and atmospheric blocks on people, places, and nature depend on their intensity, their frequency, and their persistence or the speed at which they travel. Particularly strong extratropical storms and atmospheric blocks can bring extreme weather to Canada (Grotjahn et al., 2016; Yu et al., 2022). Atmospheric blocks, which result in strong distortions in the jet stream, are associated with both summer hot extremes (Figure 4.10) and winter cold extremes (Pfahl & Wernli, 2012). As an example, the June 2021 Pacific Northwest heatwave was associated with a particularly strong atmospheric block (White et al., 2023), creating atmospheric conditions that are sometimes referred to as a heat dome (Box 8.2).

Figure take-away: Atmospheric blocks can lead to surface heatwaves through multiple processes.

Figure title: Atmospheric blocks and heatwaves

Strong extratropical storms can bring extreme precipitation and winds, as well as storm surges along the coasts (X. Zhang et al., 2023). These strong storms include explosive cyclones, also known as “bomb” cyclones, which intensify very rapidly, with a pressure drop of greater than 24 hectopascals (hPa, equivalent to millibars) within 24 hours (Sanders & Gyakum, 1980). Less frequent summer extratropical storms could lead to more persistent warm periods in summer (Coumou et al., 2015; Pfleiderer et al., 2019). Extratropical storms are more likely to form in certain locations and travel along certain pathways, creating storm track regions. Changes in extratropical storms can therefore result in changes in storm tracks, which are assessed in section 4.3. In this section, we assess changes from the individual storm perspective, including the frequency, strength, and movement of extratropical storms. Changes in extreme winds and rainfall associated with potential changes in extratropical storms are assessed in Chapter 8, section 8.4.3.

4.4.2: Past changes and their causes

Changes in extratropical storm frequency or intensity are studied using event-based tracking algorithms that detect, count, and track extratropical storms (e.g., Hoskins & Hodges, 2002). Methods to identify high-pressure systems are similar and often focus only on atmospheric blocks. The locations and movement of extratropical storms and high-pressure systems are strongly influenced by the jet streams and associated storm tracks. Changes in the frequency and intensity of extratropical storms and high-pressure systems can also be influenced by changes in temperature gradients and the extent of Arctic sea ice (Hay et al., 2023; T. Shaw et al., 2016) and changes in atmospheric moisture (Mathews et al., 2024). There is substantial uncertainty about, and low signal-to-noise ratios for, observed changes in extratropical storms, high-pressure systems, and atmospheric blocks (Gulev et al., 2021). Contributing to the uncertainty are low signal-to-noise ratios for observed changes in the jet streams and storm tracks (section 4.3), as well as the many complex and sometimes opposing mechanisms for potential changes in extratropical storms and high-pressure systems (T. Shaw et al., 2016; Steinfeld et al., 2022; Woollings et al., 2018). In addition, different tracking methods and different observational datasets can lead to differing trends for both extratropical storms (Neu et al., 2013; Walker et al., 2020) and high-pressure systems (Barnes et al., 2014; Woollings et al., 2018).

There is low confidence in observed trends for the frequency and strength of atmospheric blocks, even on a hemispheric scale, as trends vary widely depending on the reanalysis dataset, detection algorithm, and time period used (Barnes et al., 2014; Davini et al., 2012; Efe & Lupo, 2022; Lupo et al., 2019; Rohrer et al., 2019; Woollings et al., 2018). Trends in winter atmospheric-block frequency and intensity over Canada since the mid-20th century are weak (Davini et al., 2012; Woollings et al., 2018). Some evidence points to more frequent summer atmospheric blocks over eastern Canada since the mid-20th century (Woollings et al., 2018), but this increase is dependent on the blocking detection algorithm used (Pepler et al., 2019; Woollings et al., 2018). On longer timescales (since the early 20th century), the lack of agreement in trends between datasets gives low confidence in observed changes over Canada (Rohrer et al., 2019).

Observed changes in extratropical storm frequency vary by season and region, and also depend on the dataset and metric used to detect extratropical storms, resulting in low confidence in observed trends for Canada more broadly. There is some evidence for a past increase in Arctic storms over eastern Canada, although the trends vary with the time period (Neu et al., 2013; X. Zhang et al., 2023), season, and dataset used (Zahn et al., 2018). This potential past increase in Arctic storms is also consistent with an observed increase in atmospheric rivers (P. Zhang et al., 2023), although increases in atmospheric humidity, expected in a warming climate, can also explain the increase in atmospheric rivers (section 4.5). There is some evidence for an increase in strong extratropical storms during winter across southern Canada, and over the eastern Pacific and western Atlantic close to Canada (E. K. M. Chang & Yau, 2016; Douville et al., 2021). Across the Northern Hemisphere more broadly, studies find small increases in winter storm frequency (E. K. M. Chang & Yau, 2016; X. L. Wang et al., 2016), although even on a hemispheric scale this finding varies depending on the dataset used, leading to low confidence in these changes. These observed trends are also sensitive to the time period being analyzed, contributing to low confidence in attributing them to human activities (Rohrer et al., 2019; X. L. Wang et al., 2016). There is some evidence for a downward trend in the frequency of strong summer extratropical storms over the Northern Hemisphere, and particularly over eastern Canada and the western Atlantic (E. K. M. Chang et al., 2016). However, disagreement between reanalysis datasets and methodologies leads to low confidence in these trends (X. L. Wang et al., 2016). The observed decreases in summer extratropical storm frequency are consistent with decreases in the summer storm track strength over the Northern Hemisphere more broadly (section 4.3) (Chemke & Coumou, 2024). Recently, methods have been developed to quantitatively attribute strong extratropical storms to human-caused climate change, and there is some evidence that an increasing frequency of strong extratropical storms in Europe is due to human activities (Ginesta et al., 2023), but studies specifically for Canada are lacking.

4.4.3: Future changes

Overall, across the Northern Hemisphere, climate models project a decrease in the frequency of atmospheric blocks (Davini & D’Andrea, 2020; Lohmann et al., 2024; Matsueda & Endo, 2017; Woollings et al., 2018), including over parts of Canada. However, regional changes depend on the metric used to identify the atmospheric blocks, and fewer than two thirds of the CMIP5 models agree on the sign of the change over much of Canada (Figure 4.11). Both CMIP5 (Davini & D’Andrea, 2020) and CMIP6 models (Davini & D’Andrea, 2020; Lohmann et al., 2024) provide some evidence for a future small decrease in summer blocking over eastern Canada, although this is not consistent across all models and metrics (Gao et al., 2025). There is substantial disagreement in projected trends for winter between different models and metrics across Canada (Figure 4.11) (Gao et al., 2025; Jeong et al., 2023; Lohmann et al., 2024; Woollings et al., 2018). The lack of a complete theoretical explanation of how atmospheric blocks should respond to climate change (Hassanzadeh et al., 2014; Nabizadeh et al., 2019; Steinfeld et al., 2022; Woollings et al., 2018), combined with uncertainty about observed trends and climate model biases in the representation of atmospheric blocks (Davini & D’Andrea, 2016, 2020) leads to low confidence in projected changes over Canada.

Figure take-away: Projections of atmospheric-block frequency are very sensitive to the method used to identify atmospheric blocks and are inconsistent between different models, particularly for specific regions such as Canada.

Figure title: Projected changes in the frequency of atmospheric blocks in CMIP5 models for three different blocking metrics

The projected poleward shift of the winter storm tracks in the North Pacific (section 4.3) is expected to lead to a poleward shift in the locations of winter extratropical storms (Lee et al., 2021), including explosive “bomb” cyclones (Seiler & Zwiers, 2016). This poleward shift will, in general, lead to an increase in the frequency of extratropical storms at higher latitudes, and a decrease at lower latitudes. In addition, there is some evidence that individual extratropical storms may travel further poleward under warming (Tamarin & Kaspi, 2017). Projected changes in the frequency of winter extratropical storms are small, particularly over Canada and the oceans around Canada (E. K.-M. Chang, 2018; Priestley & Catto, 2022a), with even the sign of the changes for specific regions dependent on the model or study methods or both (E. K.-M. Chang, 2018; Lee et al., 2021; Priestley & Catto, 2022b; Yettella & Kay, 2017; Zappa et al., 2013). Projected changes in the intensity of extratropical storms are also small (Seneviratne et al., 2012). For the summer season, climate models project a decrease in extratropical storm frequency for Canada and the oceans around Canada (E. K. M. Chang et al., 2016; Priestley & Catto, 2022a), consistent with the Northern Hemisphere average. This includes a weak response to Arctic sea ice loss (Kang et al., 2023). This projected decrease in frequency is also consistent with a projected weakening of the summer storm tracks (E. K. M. Chang et al., 2016; Harvey et al., 2020; Kang et al., 2023). There is also some evidence for a projected weakening of strong summer extratropical storms (Priestley & Catto, 2022a). Climate models have biases in the simulation of extratropical storms (Priestley et al., 2023), and disagree on many projections, particularly for specific regions, leading to low confidence in projections for Canada.

4.4.4: Confidence terms in key messages: summary of evidence

Key message 4.4: Changes in recent decades in the frequency and intensity of extratropical storms and of atmospheric blocks are uncertain. There is low confidence in any human influence on these past changes. A poleward shift in extratropical storms and a decrease in the frequency of summer extratropical storms are projected over Canada (low confidence). Atmospheric blocks are projected to occur less frequently over Canada, but there are large regional variations (low confidence).

The uncertainty about the observed changes of extratropical storm and atmospheric-block frequency and intensity over Canada is due to the sensitivity of observed trends to detection method and reanalysis dataset. Since the observed changes are small compared to internal climate variability, we have low confidence in attributing them to human influence. We have low confidence in projections that extratropical storms over Canada will shift poleward and become less frequent during summer, because of disagreement between individual models, known weaknesses in models’ abilities to simulate observed storms, including their changes and variability, and incomplete theoretical understanding. While models generally project a small decrease in the frequency of atmospheric blocks, there are large regional variations and a low level of model agreement, which results in low confidence in projections for Canada.

4.5: Atmospheric rivers

Key message 4.5: The frequency and intensity of atmospheric rivers have increased for Canada as a whole in recent decades (medium confidence). However, there is very low confidence in the magnitude of these increases due to the limited number of studies and the sensitivity of results to how atmospheric rivers are defined and detected. There is insufficient evidence to attribute long-term trends for Canada as a whole to human influence. However, human influence has increased the likelihood of extreme atmospheric-river events in southern British Columbia (low confidence). 

Key message 4.6: The frequency and intensity of atmospheric rivers over Canada will increase in the future in high emissions scenarios (high confidence) and intermediate emissions scenarios (medium confidence). However, the magnitude of these increases is uncertain.

4.5.1: Effects on Canadian weather and climate

Atmospheric rivers have emerged as an important research topic in recent decades, in part because they lead to weather and climate extremes when they make landfall (Guan et al., 2023; Newell et al., 1992; Ralph et al., 2004, 2017; Zhu & Newell, 1994, 1998). Atmospheric rivers are defined as corridors of strong water vapour transport that are thousands of kilometres long, up to a thousand kilometres wide, and transient, typically lasting one to three days. They are often associated with a low-level jet stream, typically around 1500 m above the surface, ahead of the cold front of an extratropical storm (AMS, 2024; Guan et al., 2023). Most atmospheric rivers are associated with an extratropical storm, and they therefore more frequently occur in regions where there are more frequent extratropical storms (Guo et al., 2020). The water vapour in atmospheric rivers can come from tropical or extratropical moisture sources, or some of both. It has been estimated that atmospheric rivers are responsible for more than 90% of poleward moisture transport across the mid-latitudes despite only occurring over around 10% of the Earth’s surface in these latitudes at any given time (Guan & Waliser, 2024; Zhu & Newell, 1998).

Atmospheric rivers can be observed directly with remote sensing (e.g., satellite measurements of water vapour) or during intensive field campaigns (e.g., using weather measurement devices called “dropsondes,” designed to be dropped from aircraft and to collect data as they fall to the Earth) (Ralph et al., 2004). However, observations have been limited in both their spatial and temporal coverage. Therefore, atmospheric rivers are typically detected using methods designed to identify their shape and structure in atmospheric reanalysis datasets or climate model outputs (Ralph, Wilson, et al., 2019; Shields et al., 2018). The resulting algorithm and reanalysis uncertainty is an important contributor to overall uncertainty when quantifying past and future change and the consequences of atmospheric rivers.

The major consequence of landfalling atmospheric rivers is persistent heavy precipitation, which can lead to extreme flooding, landslides, and avalanches. Some atmospheric rivers may cause damaging winds or dangerous Föhn wind events (relatively warm and dry downslope winds in the lee of mountain ranges) (Mo, 2024), or contribute to heatwaves (Bozkurt et al., 2018; Mattingly et al., 2023; Mo et al., 2022; Waliser & Guan, 2017). However, atmospheric rivers can also be beneficial by providing critical water supply for ecosystems and people (Ralph, Rutz, et al., 2019).

Figure take-away: Atmospheric rivers mostly affect the east and west coasts of Canada but can extend inland and be seasonally important in the north.

Figure title: Frequency of atmospheric rivers in Canada

The presence and impacts of atmospheric rivers vary widely across Canada. In reanalyses for the period 1940 to 2023, atmospheric rivers are found to have occurred on average approximately 35 to 45 days per year (Figure 4.12a) (Mo, 2024) along both the west and east coasts of Canada. While most prevalent closest to the coasts, atmospheric rivers can extend inland. For example, atmospheric rivers have occurred, on average, between 20 and 35 days per year in Ontario and the Prairies, and 15 to 20 days per year in northern Canada. Atmospheric rivers are seasonally important in the Arctic, occurring 10 to 14 days per summer (Figure 4.12d), but less often in other seasons. The detection algorithm used in the analysis identifies atmospheric rivers on the basis of moisture transport thresholds. If an atmospheric river moving inland loses significant moisture, for example, as precipitation falls, to the point that it no longer meets the detection criteria, then it will fail to be classified as an atmospheric river. This pattern aligns with the physical nature of atmospheric rivers, which often weaken as they move away from their moisture sources.

Historically, atmospheric rivers affecting western Canada have received the most attention, in part because they interact with the region’s mountain ranges. Warm, moist marine airflow can be effectively blocked by the Pacific Coast and Rocky Mountain ranges in British Columbia, leading to prolonged and sometimes heavy rain falling on some windward mountain slopes. Intense atmospheric rivers contributed to the 2010 floods in the Bella Coola Valley, the massive snowstorm in mid-February 2015 in the Terrace-Kitimat Valley, and the catastrophic floods in southwestern British Columbia in mid-November 2021 (Gillett et al., 2022; Richards-Thomas et al., 2024). Based on a six-hourly atmospheric-river catalogue for the period 1948 to 2016, Gershunov et al. (2017) found that British Columbia and southeastern Alaska are hit by 30 to 40 landfalling atmospheric rivers each year on average, most of which occur during the fall and winter (Figure 4.12b–e). Atmospheric rivers contribute about 13% of total annual precipitation across these regions (Sharma & Déry, 2020a), with higher contributions (up to 33%) along the coast, including important contributions to streamflow (Sharma & Déry, 2020b). The higher coastal contributions are consistent with Gershunov et al. (2017), who found that about 30 to 40% of the annual precipitation in southwestern British Columbia can be attributed to landfalling atmospheric rivers.

Atmospheric rivers are also large contributors to annual precipitation along the east coast (Figure 4.13a) and are responsible for significant precipitation events in the Mackenzie River Basin (Gyakum, 2000; Smirnov & Moore, 1999, 2001). They also cause high-impact weather events in other parts of Canada, especially atmospheric rivers originating in the Gulf of Mexico and the Atlantic Ocean (Lin et al., 2019; Low et al., 2022; Mo & Lin, 2019; Mo, 2024; Newell & Zhu, 1994). A large proportion of moderate precipitation (Figure 4.13b) and wind extremes (Figure 4.13c) are associated with atmospheric rivers. Furthermore, in British Columbia, Quebec and southern Ontario, upwards of 70% of joint wind and precipitation extremes are associated with atmospheric rivers (Figure 4.13d). Note that Chapter 8 provides assessments of precipitation and wind extremes, including compound wind and rainfall events, which are relevant for infrastructure design.

Figure take-away: Atmospheric rivers contribute substantially to total precipitation, precipitation extremes, wind extremes, and compound precipitation and wind extremes in Canada.

Figure title: Contribution of atmospheric rivers to precipitation and wind extremes in Canada

4.5.2: Past changes and their causes

A water vapour corridor is considered an atmospheric river when its moisture transport reaches a certain strength. Its strength depends on the amount of water vapour in the atmosphere and on the direction and strength of winds that move this moisture from place to place. Changes in each of these factors will contribute to changes in atmospheric-river characteristics (Payne et al., 2020). According to the laws of thermodynamics (Box 8.3), human-caused climate change is expected to lead to increases in the amount of atmospheric moisture. For every degree-Celsius rise in temperature, air can hold around 6 to 7% more water vapour. Therefore, a warmer atmosphere can support more intense atmospheric rivers. Similar reasoning supports our understanding that precipitation driven by atmospheric rivers will intensify with warming (Payne et al., 2020). As noted in previous sections, however, there is generally less confidence in changes in winds, which are driven by atmospheric dynamics and the large-scale circulation.

The IPCC AR6 WGI concluded that it is likely there has been an increase in atmospheric-river activity in the eastern North Pacific since the mid-20th century, but it had low confidence in the exact magnitude of this trend, which has not been formally attributed to human-caused climate change. Still, the increase is in line with expected and observed rises in atmospheric moisture linked to human-caused global warming (Douville et al., 2021). A recent synthesis of multiple atmospheric-river detection algorithms and reanalyses (1980–2023) shows Canada-wide increases in atmospheric-river moisture and a global expansion of atmospheric-river area (Henny & Kim, 2025). Over western North America, observational and historical climate-modelling studies report increases in the occurrence of atmospheric rivers and of precipitation and streamflow associated with atmospheric rivers (Curry et al., 2019; Gershunov et al., 2017; Sharma & Déry, 2020c), with larger increases since the late 20th century (Sharma & Déry, 2020c). Trends estimated from multiple detection algorithms and reanalyses show robust increases in the frequency of atmospheric rivers over Atlantic Canada and the northern Pacific coast, accompanied by an intensification of moisture transport in the strongest atmospheric rivers (Henny & Kim, 2025). These results are consistent with up-to-date trends that show increases in the annual occurrence of atmospheric rivers and the intensity of the most extreme atmospheric rivers over North America since the middle of the 20th century (Figure 4.14).

Figure take-away: Atmospheric-river activity has increased over Canada since the mid-20th century.

Figure title: Past trends in annual occurrence of atmospheric rivers and in moisture transport during the strongest atmospheric river of the year

Recent observational and modelling analyses have focused on regions outside of western North America, with findings that support those shown in figures 4.13 and 4.14. Dong et al. (2024) found upward trends in winter atmospheric-river frequency over eastern North America, including eastern Canada, in multiple reanalyses and high-resolution (∼50-km horizontal resolution) atmospheric model simulations. They attribute the upward trend in part to recent changes in the Pacific–North American teleconnection pattern (section 4.8), which also explain much of the interannual variability in the occurrence of atmospheric rivers. Studies focused on the Arctic have similarly emphasized the importance of year-to-year variability in modulating observed upward atmospheric-river trends. For example, Ma et al. (2024) found that regional differences in the expression of the Pacific Decadal Oscillation and the Atlantic Multidecadal Oscillation (section 4.8) are responsible for around a quarter of the variability in near-future spatially averaged Arctic atmospheric-river trends in climate model simulations. Studies that have split the observed increases in Arctic atmospheric rivers into thermodynamic and dynamical contributions have found that the thermodynamic contribution dominates (Ma et al., 2024; C. Zhang et al., 2023; P. Zhang et al., 2023). Overall, while upward trends in atmospheric rivers are found consistently for different regions of Canada across modern reanalyses, different detection algorithms describe their climatological characteristics—frequency, seasonality, and magnitude—in different ways (Collow et al., 2022), which can affect the magnitude of reported trends.

As concluded by the IPCC AR6 WGI (Douville et al., 2021), it has not been possible to assess the influence of human-caused climate change on long-term observed trends in atmospheric rivers or individual extreme atmospheric-river events, given the lack of formal attribution studies. (Note that Section 8.1.1 of the IPCC AR6 WGI report discusses the distinction between attribution of long-term trends in climate extremes and attribution for specific extreme events.) With some exceptions, this is still the case. One way to understand the causes of observed changes in atmospheric rivers is to use single-forcing climate model experiments, which evaluate the climate system’s response to individual classes of forcing agents, such as greenhouse gases or aerosols. Experiments of this type have found that the opposing effect of weakening influences from aerosols and strengthening influences from greenhouse gases led to modest historical change in atmospheric rivers over the west and east coasts of North America from 1920 to 2005 (Baek & Lora, 2021)Baek and Lora (2021). However, atmospheric rivers and precipitation driven by atmospheric rivers intensify rapidly in simulations for subsequent decades as the greenhouse gas signal starts to dominate. An event attribution study of the mid-November 2021 floods driven by atmospheric rivers over southwestern British Columbia found that human-caused climate change made the frequency of atmospheric-river events with similar storm-total moisture transport at least 60% more likely, made similar two-day precipitation 45% more likely, and made similar flooding 120 to 330% more likely (Gillett et al., 2022).

4.5.3: Future changes

Two main drivers of future changes in atmospheric rivers and atmospheric-river impacts over Canada can be attributed to human-caused climate change (Radić et al., 2015; Shields et al., 2023; S. Wang et al., 2023). The first, which affects atmospheric rivers globally, is the thermodynamically driven increase in moisture transport associated with the increase in water vapour that arises from the warming of the lower atmosphere. This increase in water vapour due to warming is also the primary driver of increases in precipitation and precipitation extremes associated with atmospheric rivers (Radić et al., 2015; Shields et al., 2023; S. Wang et al., 2023). The second is dynamically driven change, including the poleward shift in atmospheric rivers associated with a poleward shift in the mid-latitude storm tracks (section 4.3).

To illustrate these two main drivers, Figure 4.15 summarizes results from a recent model intercomparison project focused on assessing projected changes in atmospheric rivers in CMIP5 and CMIP6 climate models under very high emissions scenarios (RCP8.5, SSP5-8.5) (O’Brien et al., 2022). Simulated changes are broadly consistent with recent observed trends, indicating steady increases in the frequency of atmospheric rivers in the 21st century (Figure 4.15b) that are primarily driven by increases in atmospheric water vapour (Figure 4.15d). The dynamical component of change, which is attributed to the poleward shift in mid-latitude storm tracks (sections 4.3 and 4.4), reinforces this upward trend in the north and weakens it in the south (Figure 4.15e). Differences in how atmospheric rivers are defined and detected contributed as much to uncertainty as differences in climate models.

Figure take-away: Atmospheric rivers in Canada are projected to increase in frequency, mostly because of increases in atmospheric moisture.

Figure title: Projections of atmospheric-river occurrence and moisture transport

Evidence from studies based on different multi-model ensembles, across different generations of climate models (Gao et al., 2015; Hagos et al., 2016; Kolbe et al., 2023; Nellikkattil et al., 2023; Tan et al., 2020; M. D. Warner et al., 2015; P. Zhang et al., 2021; Zhao, 2020), show similar results. These results lead to high confidence that under high (SSP3-7.0) to very high (RCP8.5, SSP5-8.5) emissions scenarios, atmospheric rivers over Canada will increase in intensity and frequency, mainly because warming results in more moisture being transported (the thermodynamic driver). While studies with intermediate emissions scenarios are lacking, the same thermodynamic mechanism applies. Therefore, there is medium confidence that these results can be extrapolated to intermediate emissions scenarios, although the magnitude of changes will be smaller with less warming. The thermodynamic influence will also drive the intensification of atmospheric-river precipitation (Shields et al., 2023; S. Wang et al., 2023). However, the impact of changes in atmospheric circulation on changes in moisture transport, while smaller, adds to uncertainty about the overall magnitude of change. Uncertainty about the overall magnitude of change also arises from internal climate variability (Tseng et al., 2021), structural model uncertainty, and, as noted above for observed changes and by O’Brien et al. (2022), differences in how atmospheric rivers are defined and detected.

4.5.4: Confidence terms in key messages: summary of evidence

Key message 4.5: The frequency and intensity of atmospheric rivers have increased for Canada as a whole in recent decades (medium confidence). However, there is very low confidence in the magnitude of these increases due to the limited number of studies and the sensitivity of results to how atmospheric rivers are defined and detected. There is insufficient evidence to attribute long-term trends for Canada as a whole to human influence. However, human influence has increased the likelihood of extreme atmospheric-river events in southern British Columbia (low confidence). 

Key message 4.6: The frequency and intensity of atmospheric rivers over Canada will increase in the future in high emissions scenarios (high confidence) and intermediate emissions scenarios (medium confidence). However, the magnitude of these increases is uncertain.

Our medium confidence that the frequency and intensity of atmospheric rivers have increased over Canada since the mid-20th century is supported by evidence from multiple studies based on different reanalyses and using different methods of detecting atmospheric rivers. In addition, these reanalyses may be subject to inhomogeneity due to changes in the contributions of observational data sources over time. These trends are broadly consistent with historical climate model simulations, including single-forcing attribution experiments, as well as with our physical understanding of how atmospheric moisture increases with warming. However, we have very low confidence in the magnitude of trends and their attribution to human-caused climate change because of the lack of formal detection and attribution studies, the role played by internal climate variability, and the varying results depending on what atmospheric-river detection algorithm a study uses. There is insufficient evidence to attribute long-term trends for Canada as a whole to human influence as there are no studies that have addressed this. There is some evidence that human influence has increased the likelihood of extreme atmospheric-river events in southern British Columbia, but we have low confidence in this because the evidence is based on the attribution of only one recent atmospheric-river event.

Our high confidence in future increases in the frequency and intensity of atmospheric rivers over Canada under high (SSP3-7.0) and very high (RCP8.5, SSP5-8.5) emissions scenarios is supported by robust results from projections based on CMIP5 and CMIP6 simulations and using different climate models and atmospheric-river detection algorithms. These increases will be driven primarily by the increase in atmospheric water vapour associated with projected warming, which further supports our high confidence in projections of an intensification of heavy precipitation associated with atmospheric rivers. This is also consistent with our physical understanding. These changes (with a smaller magnitude) are also expected for intermediate emissions scenarios, but given the fact that there are no specific studies using intermediate emissions scenarios, we have only medium confidence in such projections. Our low confidence in the magnitude of changes stems from uncertainty about the influence of circulation changes. While of smaller magnitude, these changes are expected to play a role in modulating regional changes over Canada. Further uncertainty can be attributed to the internal climate variability, emissions scenario, climate model, and choice of atmospheric-river detection algorithm.

4.6: North Atlantic hurricanes

Key message 4.7: The strength and associated precipitation rates of North Atlantic hurricanes have increased (medium confidence). However, since only a small proportion of Atlantic hurricanes affect Canada, there is low confidence in the degree to which these changes have affected eastern Canada.

Key message 4.8: The average precipitation rates, maximum precipitation rates, and peak wind speeds associated with North Atlantic hurricanes, as well as the proportion of hurricanes in the North Atlantic that reach categories 4 and 5, are projected to increase (high confidence). However, regarding the small number of hurricanes affecting Canada, there is medium confidence in increasing precipitation rates and low confidence in increasing wind speeds. Changes in frequency of hurricanes affecting Canada are uncertain.  

4.6.1: Effects on Canadian weather and climate

Atlantic hurricanes are a subset of a weather phenomenon referred to as tropical cyclones. Tropical cyclones are low-pressure weather systems that, in contrast to the extratropical storms discussed in section 4.4, initiate over tropical oceans. The high sea surface temperatures in these tropical regions provide abundant energy for these cyclones to grow. Therefore, tropical cyclones can often grow to be much stronger, due to their lower pressure and thus faster winds, than extratropical storms. Although they are stronger, they are typically smaller in diameter. If a tropical cyclone has low enough pressure and fast enough winds to become sufficiently strong and evolves in the region around North America, it is called a hurricane. Hurricanes are categorized by strength, based on their pressure and wind speeds from 1 to 5, with 1 being the weakest that a cyclone can be while still being classified as a hurricane. Hurricanes typically form in the late summer and fall, and tend to move toward the northwest in the tropics, recurving toward the northeast if they travel north of 20 to 30°N (Knapp et al., 2010). As hurricanes move away from the warm tropical oceans, they weaken relatively quickly. The warm Gulf Stream temperatures along the east coast of North America can slow this weakening, allowing Atlantic hurricanes to occasionally reach Canada, in contrast to the cooler waters off the west coast, which prevent Pacific hurricanes from reaching the west coast of Canada. North Atlantic hurricanes can reach Canada either as tropical cyclones or as “post-tropical cyclones” (Milrad et al., 2009). A recent example of such a system is Hurricane Fiona, which made landfall over Nova Scotia as a post-tropical cyclone in 2022, impacting the entire Atlantic region. Other notable cyclones that made landfall over Canada in recent years as tropical or post-tropical cyclones include Hurricane Beryl (2024), Hurricane Dorian (2019), hurricanes Earl and Igor (2010), Hurricane Kyle (2008), and Hurricane Juan (2003). Given their intense winds and the related storm surge, hurricanes do not have to make landfall (defined as when the centre of the hurricane moves over land) to have damaging impacts in Canada.

Many, although not all, tropical and post-tropical cyclones weaken to below hurricane strength before they reach Canada. In fact, analysis of historical hurricane track datasets (IBTrACS, HURDAT2, NOAA Hurricane Research Division) (Knapp et al., 2010) shows that while Canada receives the remnants of tropical cyclones on average once or twice a year, it only suffers a direct hit by a tropical cyclone once every two years and a direct hit by a Category 1 or 2 hurricane once every three to four years. No major hurricane (Category 3, 4, or 5) has made landfall over Canada since reliable record-keeping began. When hurricanes do reach Canada, they bring strong winds and flooding due to both coastal storm surges and heavy precipitation. The Maritime provinces and the eastern part of Quebec are the regions most affected by tropical and post-tropical cyclones, although they have also affected southern Quebec (e.g., Hurricane Debby, in 2024) and even occasionally southern Ontario (e.g., Hurricane Hazel, in 1954).

4.6.2: Past changes and their causes

Detecting changes in tropical cyclones and attributing changes to human-caused climate change has been challenging. This is mainly because tropical cyclones occur relatively infrequently, and because it has been difficult to obtain precise and consistent data on tropical cyclones’ characteristics for climate research. Measurement systems have changed over time and have not always had comprehensive spatial coverage, particularly before the advent of Earth-observing satellites in 1979 (Kossin et al., 2013; Landsea et al., 2006). Globally, an increase in tropical-cyclone strength has been detected (Elsner, 2020; Emanuel, 2020; Kossin et al., 2020). This increase is consistent with the expected impact of human-caused warming based on theoretical considerations (Sobel et al., 2016) and high-resolution models (P. Chang et al., 2020; Knutson et al., 2020). While this increase in tropical-cyclone strength is also detectable at the basin level over the North Atlantic, no studies have investigated whether there is also an increase in hurricanes making landfall in Canada. A recent study reported an increase in tropical cyclone–related precipitation rates both at the global level and in the North Atlantic basin (Tu et al., 2021). Increasing precipitation rates have also been found for major Atlantic hurricanes making landfall in the continental United States (Touma et al., 2019). An increase in tropical cyclone–related precipitation is consistent with both our theoretical understanding of tropical cyclones and tropical cyclone-modelling studies. However, no studies have investigated whether an increase in precipitation is detectable in Canadian landfalling hurricanes. Some evidence suggests a shift toward an earlier start to the hurricane season in the North Atlantic region, which affects hurricanes making landfall in the United States in particular (Truchelut et al., 2022). There is also some evidence for a decrease in the dissipation rate of hurricanes after landfall for hurricanes forming in the North Atlantic (L. Li & Chakraborty, 2020), which, all else being equal, would allow hurricanes to reach further inland. These changes were primarily attributed to increasing sea surface temperatures. However, the small number of studies leads to low confidence in attributing changes in hurricane season’s start, or dissipation after landfall, to human-caused climate change, and it remains unclear whether there is a similar pattern for hurricanes that affect Canada. Estimates of North Atlantic hurricane size based on satellite or reanalysis data show no trends over the past several decades (Knaff et al., 2014; Schenkel et al., 2017; K. Zhang & Chan, 2023). An event attribution study of post-tropical cyclone Fiona (2022) found that human-caused climate change made the extreme wind speeds experienced over parts of Atlantic Canada during Fiona more than twice as likely when compared to the 1950–1979 climate (Malinina et al., 2025).

4.6.3: Future changes

The general consensus from theory and climate modelling is that, globally, the strongest tropical cyclones(in terms of low surface pressure and related wind speed) will get stronger in the future, and we should therefore expect an increase in the proportion of all tropical cyclones that reach very intense strength (Category 4 or 5) (Bhatia et al., 2018; P. Chang et al., 2020; Knutson et al., 2020; Patricola & Wehner, 2018; Roberts et al., 2020). At a global warming level of 2°C, the global strength of tropical cyclones is projected to increase by 5%, associated with a 13% increase in the proportion of all tropical cyclones that reach at least Category 4 (Knutson et al., 2020) These changes are projected to be accompanied by an approximately 15% increase in the precipitation rate of tropical cyclones, thus further increasing the chance of inland flooding. This projection agrees with the approximately 7% increase in atmospheric moisture per degree of warming required by physical theory (the Clausius-Clapeyron relationship). However, high-resolution climate modelling suggests that the precipitation rate near the inner core of the storms follows a “super Clausius-Clapeyron” scaling, with an increase in precipitation rates of 13 to 17% per degree of warming (M. Liu et al., 2019). While the confidence in these global changes is high, it is lower when extrapolating the changes to Canada because of other possible influences on regional scales and the small number of studies specifically on projections of hurricanes that affect Canada.

Projections of tropical-cyclone frequencies are not as robust as those associated with tropical-cyclone strength and tropical-cyclone precipitation because of the incomplete understanding of what determines the number of tropical cyclones, and the greater disagreement between models on projections of changes in frequency. For example, projections of tropical-cyclone frequencies for the North Atlantic basin are uncertain because the projected change in the annual number of tropical cyclones across different models and studies varies from minus 35% to plus 30% for a global warming level of 2°C, with a median value of minus 15% (Knutson et al., 2020). Confidence in such projections is further reduced by uncertainty about how the tropical equatorial Pacific, in particular the El Niño–Southern Oscillation (section 4.8), will respond to human-caused climate change, since changes in the tropical Pacific can influence the formation of Atlantic hurricanes (Sobel et al., 2023). Other changes in the characteristics of North Atlantic tropical cyclones, such as their size and amount of poleward propagation, could also lead to changes in tropical cyclones affecting Canada, but projections of such changes are currently uncertain (S. I. Seneviratne et al., 2021, Section 11.7.1). Tropical cyclones that do reach Canada may be influenced by changes in mid-latitude circulation, such as variations in the jet stream, which can affect extratropical transitions of hurricanes into post-tropical cyclones (Evans et al., 2017). Projected changes in the number of extra-tropical transitions remain uncertain, however, as most available evidence comes from single-model studies. Some of these studies suggest increases (A. J. Baker et al., 2022), while others indicate decreases (Cheung & Chu, 2023; M. Liu et al., 2017), and these changes are generally not statistically significant. Excluding any changes in Atlantic hurricanes themselves, increasing sea level due to human-caused climate change is projected to result in a larger influence of Atlantic hurricanes on extreme sea level events impacting coastal regions of Canada (Chapter 7, section 7.6) (Cheung & Chu, 2023)

4.6.4: Confidence terms in key messages: summary of evidence

Key message 4.7: The strength and associated precipitation rates of North Atlantic hurricanes have increased (medium confidence). However, since only a small proportion of Atlantic hurricanes affect Canada, there is low confidence in the degree to which these changes have affected eastern Canada.

Key message 4.8: The average precipitation rates, maximum precipitation rates, and peak wind speeds associated with North Atlantic hurricanes, as well as the proportion of hurricanes in the North Atlantic that reach categories 4 and 5, are projected to increase (high confidence). However, regarding the small number of hurricanes affecting Canada, there is medium confidence in increasing precipitation rates and low confidence in increasing wind speeds. Changes in frequency of hurricanes affecting Canada are uncertain.  

Our low confidence in past trends of hurricanes affecting Canada is due to the challenges of the changing observational system over the past decades, the relatively small number of events affecting Canada, and the lack of studies examining events affecting Canada specifically. We have medium confidence in increases in the strength and precipitation rates of North Atlantic hurricanes because some evidence exists for such increases and they are consistent with theoretical expected changes and changes on a global level.

We have high confidence that the strongest Atlantic hurricanes and their corresponding precipitation rates and peak wind speeds will intensify in the future. This is based on consistent evidence from theoretical understanding, observed changes, and model projections .

Regarding hurricanes affecting Canada, our medium confidence in projected increases in precipitation rates is due to the strong and well-understood effects of climate warming on tropical cyclone–related precipitation. We have low confidence in projected increases in wind speeds of hurricanes affecting Canada due to other possible influences on wind speeds on regional scales. Our lower confidence for both precipitation and wind speeds for Canada, relative to Atlantic hurricanes more broadly, is due to strong regional internal climate variability and the small number of studies specifically on projections of hurricanes that affect Canada.

Projected changes in the frequency of Atlantic hurricanes are uncertain due to a lack of established theory, multiple mechanisms through which changes could occur, a lack of understanding about the processes of possible changes, no clear observational signal, and disagreements between model projections. This leads to uncertainty about projected changes in the frequency of Atlantic hurricanes that affect Canada.

4.7: Large-scale environmental conditions favouring thunderstorms

Key message 4.9: There is low confidence that large-scale environmental conditions favouring thunderstorms in Canada have changed over the past several decades. This is due to a lack of regional studies for Canada, the weak, conflicting trends across different environmental-condition indicators and data products, and large internal climate variability.

Key message 4.10: Large-scale environmental conditions favouring thunderstorms are projected to become more prevalent across central and eastern Canada in spring, summer, and fall (high confidence). However, there is low confidence that thunderstorms and other severe weather events will increase, because an increase in favourable environmental conditions does not always lead to more thunderstorms.

4.7.1: Effects on Canadian weather and climate

Convective storms, which we refer to as thunderstorms for simplicity, are weather systems ranging from 2 to 200 km in scale that are associated with heavy rainfall caused by convection, the process by which warm and moist air rises, cools rapidly and produces rain through condensation. When thunderstorms are severe, they can also be associated with hail, strong winds, lightning, and tornadoes. Direct measurements of many of these phenomena can be limited, globally and in parts of Canada, and it is well-documented that storm reports are biased toward more densely populated regions, where there is a greater likelihood that a storm will be observed (Cheng et al., 2013; Etkin, 2018; Sills & Joe, 2019). For these reasons, it is sometimes difficult to establish reliable estimates of long-term trends in the occurrence of thunderstorms. In addition, global climate models lack sufficient granularity to simulate individual thunderstorms explicitly, making future thunderstorm occurrence uncertain. An alternative, indirect approach to estimating the occurrence of thunderstorms is to identify thunderstorm environments, consisting of key atmospheric conditions that favour the development of these storms (Brooks et al., 2003; R. H. Johns et al., 1993). The spatial distribution, severity, and frequency of such thunderstorm environments can be identified using atmospheric properties. Unlike thunderstorms themselves, which have relatively small spatial scales, thunderstorm environments tend to exhibit large-scale patterns of about 100 to 1000 km. It is important to note that conditions favourable to the development of thunderstorms do not always lead to their actual development, which is determined by processes that act on smaller scales than most climate models can simulate. Therefore, favourable conditions are indicators of thunderstorm environments but are not perfect predictors of actual thunderstorms. Furthermore, the correspondence between the indicators and actual thunderstorms varies depending on the region, season, or observational and reanalysis data product used, and may change as the climate warms (Gopalakrishnan et al., 2025; Hoogewind et al., 2017; Raupach et al., 2021; Tippett et al., 2019). In addition, changes in these indicators will not necessarily translate into changes in severe weather occurrences (Chapter 8, sections 8.3 and 8.4). However, there is value in assessing the changes in these indicators because they allow us to examine past changes consistently over time and give us some indication of how thunderstorms might change in the future using climate model output. This section assesses observed changes in and projections of thunderstorm environments, while Chapter 8 assesses observed changes in thunderstorm and severe weather events themselves.

One of the key atmospheric properties used as an indicator of thunderstorm environments is convective available potential energy, which is a measure of the instability of the atmosphere, that is, the capacity of the atmosphere to generate upward motion. Stronger convective available potential energy increases the amount of energy available for convection, which is essential for the development of thunderstorms. On the other hand, stronger convective inhibition (a measure of the energy that needs to be overcome for convection to occur) can prevent or delay the onset of convection. However, when combined with stronger convective available potential energy, convective inhibition can potentially increase the intensity of convection and associated precipitation (J. Chen et al., 2020; Del Genio et al., 2007; Diffenbaugh, N.S. et al., 2013; Rasmussen et al., 2017). Lower tropospheric vertical wind shear (the change in wind speed or direction that comes with a change in altitude) and storm relative helicity (a measure of the potential for cyclonic updrafts) are indicators of squall line or supercell development, with stronger shear and helicity leading to conditions that favour the development of more severe and longer-lived severe thunderstorms and tornadoes (Trapp, 2018). Thunderstorm environments are most often identified by combining several of these atmospheric properties together into what are called severe weather proxies (Lepore et al., 2021; Seeley & Romps, 2015). These atmospheric properties and severe weather proxies serve as indicators of the potential for severe weather, and their measurement and interpretation are crucial for forecasting such events (R. H. Johns & Doswell, 1992).

Atmospheric conditions that favour the development of thunderstorms, including tornadoes and hailstorms, are more prevalent in central and eastern Canada and in the Rocky Mountain region than in other parts of Canada (Figure 4.16a,c) (Brooks et al., 2003; Cheng et al., 2013; Etkin, 2018; Prein & Holland, 2018; Sills & Joe, 2019; Taszarek, Allen, Marchio, et al., 2021). Seasonally, thunderstorm environments in Canada are most prevalent in summer, followed by fall (Taszarek, Allen, Marchio, et al., 2021).

Figure take-away: Past trends in the frequency of conditions favourable to the occurrence of thunderstorms are weak across Canada.

Figure title: Past frequency and trends in the frequency of thunderstorm and severe thunderstorm environments in Canada

4.7.2: Past changes and their causes

Due to the limited number of regional studies that examine trends in thunderstorm environments in Canada, there is low confidence that thunderstorm environments in Canada have changed over the past several decades. This low confidence is also due to small and conflicting trends across different atmospheric properties, severe weather proxies, and data products.

Many studies examining past trends in thunderstorm environments focus on the continental United States (Koch et al., 2021; Taszarek, Allen, Brooks, et al., 2021). While some information can often be gleaned from these studies for the southernmost regions of Canada, it is not possible to extrapolate to the rest of Canada. Moreover, different studies use different proxies and different data products, making it challenging to compare and assess past changes (J. Chen & Dai, 2023; F. Li et al., 2020; Pilguj et al., 2022; Tang et al., 2019; Taszarek, Allen, Marchio, et al., 2021).

With respect to conflicting trends, observed trends for convective available potential energy in Canada display differing trends in in-situ observational data and reanalysis data in some regions of Canada (J. Chen & Dai, 2023; F. Li et al., 2020; Pilguj et al., 2022; Taszarek, Allen, Marchio, et al., 2021). Furthermore, relatively weak and spatially heterogeneous trends have been observed in thunderstorm environments in Canada for 1979 to 2019 (Taszarek, Allen, Marchio, et al., 2021), while upward trends in hailstorm environments have been observed for southeastern Canada (A. W. Johnson & Sugden, 2014; Tang et al., 2019). Finally, observations indicate lightning has increased in western and northern Canada and decreased in central and eastern Canada in recent decades (Burrows et al., 2025; Kochtubajda & Burrows, 2020), but these results do not align with trends in thunderstorm environment frequency (Figure 4.16b,d).

The inconsistency across severe weather proxies may be due in part to opposing changes in the properties of thunderstorm environments. Theory suggests that as the climate warms, the atmosphere will become more unstable over land areas, meaning that convective available potential energy will increase. On the other hand, convective inhibition will also increase and vertical wind shear in the lower troposphere will likely decrease (Seeley & Romps, 2015; Singh & O’Gorman, 2013; Trapp et al., 2007). These opposing changes, in addition to large internal climate variability, make it challenging to detect trends in thunderstorm environments for the recent past (Franke et al., 2024).

In this section, the assessment has been limited to past changes in thunderstorm environments. For details on changes in the storms themselves and associated short-duration precipitation, hail, and strong winds, see Chapter 8, sections 8.3 and 8.4, respectively.

4.7.3: Future changes

Climate model projections show an overall increase in the prevalence of environmental conditions that favour thunderstorm development in Canada (Diffenbaugh, N.S. et al., 2013; Gensini et al., 2014; Glazer et al., 2021; Lepore et al., 2021; Rasmussen et al., 2017; Raupach et al., 2021). Models project an increase in Canada of such favourable environmental conditions ranging from 40 to 53% per degree Celsius of global warming (Figure 4.17). The prevalence of thunderstorm environments is projected to increase across southcentral and eastern Canada in all seasons, with spring showing the largest percentage increases (Lepore et al., 2021). Thunderstorm environments are projected to extend further north in central and eastern Canada and into the Northwest Territories and Nunavut in summer, despite greater opposition between increases in convective available potential energy and decreases in vertical wind shear in the lower troposphere in this region (Lepore et al., 2021; Paquin et al., 2014). The winter season is not shown because there are too few occurrences of thunderstorm environments during the past several decades to robustly assess relative future changes.

The increase in conditions favourable to the development of thunderstorms is mainly due to thermodynamic processes: a strong increase in convective available potential energy (high confidence) as the climate warms that is not fully opposed by increasing convective inhibition (J. Chen et al., 2020; Diffenbaugh, N.S. et al., 2013; Lepore et al., 2021; Seeley & Romps, 2015; Singh & O’Gorman, 2013). An increase in moisture in the lower atmosphere due to climate change is an important factor driving increases in convective available potential energy, while a decrease in relative humidity in the lower atmosphere over land contributes to greater convective inhibition (Byrne & O’Gorman, 2016; J. Chen et al., 2020; Diffenbaugh, N.S. et al., 2013; Rasmussen et al., 2017). Regional climate model projections with sufficient granularity to simulate convection show that the combination of stronger convective available potential energy and stronger convective inhibition has the potential to suppress mild and weak storms but to generate more extreme storms with more intense rainfall (Dai et al., 2017; Prein et al., 2017; Rasmussen et al., 2017). Dynamical processes that affect storm organization and severity, vertical wind shear, and helicity show relatively weak decreases (Diffenbaugh, N.S. et al., 2013; Lepore et al., 2021; Seeley & Romps, 2015).

Figure take-away: The frequency of the environmental conditions favourable to the occurrence of thunderstorms in Canada increases with increasing global warming levels.

Figure title: Percentage increases in the frequency of thunderstorm environments in Canada as a function of global warming level

Overall, climate model projections show increasingly favourable environmental conditions for thunderstorm development. However, the IPCC AR6 WGI concluded (Seneviratne et al., 2021, Section 11.7.3.5) that there is generally low confidence in projections of changes in thunderstorms based on thunderstorm environments because the relationship between simulated thunderstorm environments in models and the occurrence of observed thunderstorms requires improved validation and may change as the climate changes. Moreover, recent analysis indicates that model biases in key atmospheric properties, such as convective available potential energy, can lead to uncertainty in estimates of the prevalence of thunderstorm environments in models, contributing to the low confidence assessment (Gopalakrishnan et al., 2025).

4.7.4: Confidence terms in key messages: summary of evidence

Key message 4.9: There is low confidence that large-scale environmental conditions favouring thunderstorms in Canada have changed over the past several decades. This is due to a lack of regional studies for Canada, the weak, conflicting trends across different environmental-condition indicators and data products, and large internal climate variability.

Key message 4.10: Large-scale environmental conditions favouring thunderstorms are projected to become more prevalent across central and eastern Canada in spring, summer, and fall (high confidence). However, there is low confidence that thunderstorms and other severe weather events will increase, because an increase in favourable environmental conditions does not always lead to more thunderstorms.

In summary, we have low confidence in observed changes in the prevalence of thunderstorm environments in Canada. This assessment is based on a lack of regional studies for Canada; large atmospheric internal climate variability; and weak and conflicting trends across different data products, severe-weather proxies and individual properties that contribute to the prevalence of thunderstorm environments. We have high confidence in an increase in convective available potential energy as the climate warms, resulting in an increase in the prevalence of favourable thunderstorm environments across central and eastern Canada in spring, summer, and fall. This assessment is based on theoretical understanding of how convective available potential energy will change as the climate warms. It is also based on multiple studies using global climate model projections with regional climate model projections that have sufficient granularity to simulate thunderstorms. However, in line with the assessment by the IPCC AR6 WGI, we have low confidence that increases in the frequency of these environments will translate into increases in thunderstorms themselves. This assessment is based on uncertainties in the accuracy and stationarity of severe weather proxies used to identify thunderstorm environments, climate model biases in the simulation of key properties that contribute to thunderstorm environments, and the fact that global climate models do not have sufficient granularity to simulate thunderstorms.

4.8: El Niño–Southern Oscillation and other atmosphere-ocean coupled modes of variability

Key message 4.11: The El Niño–Southern Oscillation (ENSO) is the dominant source of year-to-year climate variability in western Canada. Year-to-year climate fluctuations associated with ENSO have been larger since 1950 than in the previous century (medium confidence). However, there is low confidence that this change is due to human-caused climate change because internal climate variability is large.

Key message 4.12: The El Niño–Southern Oscillation (ENSO) will remain the dominant source of climate variability in western Canada in the 21st century (high confidence), but there is low confidence in projected changes in year-to-year climate fluctuations associated with ENSO. While climate models consistently show that by the end of the century, the effect of ENSO on winter climate fluctuations will extend into central and eastern Canada, there is low confidence in these projections due to systematic climate model biases.

4.8.1: Effects on Canadian weather and climate

Atmosphere-ocean coupled modes of climate variability are oscillations or fluctuations that involve the interaction or coupling between sea surface temperatures and the atmosphere, leading to local and remote large-scale atmospheric circulation anomalies that can influence climate and weather across large distances. The remote atmospheric circulation anomalies are often termed “teleconnections” and can directly affect surface temperature and precipitation in Canada. The dominant atmosphere-ocean coupled modes of climate variability affecting Canada are the El Niño–Southern Oscillation (ENSO) (Philander, 1990), the Pacific Decadal Oscillation (PDO) (Mantua et al., 1997), and the Atlantic Multidecadal Oscillation (AMO) (Kerr, 2000). Brief definitions of these modes can be found in Box 4.1.  

ENSO is the dominant mode of year-to-year climate variability in western Canada and originates from coupled atmosphere-ocean interactions in the tropical Pacific (Philander, 1990). It is characterized by fluctuations in sea surface temperature with warmer than average (El Niño) and colder than average (La Niña) sea surface temperatures in the central to eastern equatorial Pacific occurring every two to seven years. The ENSO amplitude (or strength) is the magnitude of these fluctuations. It is typically quantified by the anomaly (the difference relative to average conditions) of the sea surface temperature in a rectangular region of the central tropical Pacific, such as the Niño 3.4 region, within 5^oN to 5^oS and 120^oW to 170^oW. Larger positive (warmer than average) or negative (cooler than average) sea surface temperature anomalies in the central tropical Pacific indicate stronger El Niño or La Niña events, respectively. ENSO is associated with anomalies in tropical atmospheric deep-convection and heating, leading to the formation of atmospheric teleconnections affecting climate on a global scale (e.g., Timmermann et al., 2018; Trenberth et al., 1998; Yeh et al., 2018). ENSO influences temperature and precipitation in Canada mainly through an atmospheric teleconnection that resembles the Pacific–North American teleconnection pattern (PNA), (Wallace & Gutzler, 1981). The effects of this teleconnection are most pronounced in the winter season (Ropelewski & Halpert, 1986). Climate anomalies associated with the warm (positive) phase of ENSO (El Niño) are shown in Figure 4.18. During El Niño events, a positive PNA-like pattern is typically observed. This pattern moves warm southern air northward into western and central Canada, resulting in warmer winter air temperatures and drier conditions across much of southern Canada. When this happens, warmer than average temperatures are most prominent in western and central parts of southern Canada, while drier than average weather is most prominent in southwestern Canada (Figure 4.18, top panels). Generally, opposite patterns are observed during La Niña events, although some asymmetries exist (e.g., Burgers & Stephenson, 1999; Eyring et al., 2021a; Hayashi et al., 2020). The strength of the temperature and precipitation anomalies are influenced by ENSO amplitude. ENSO has little impact on summer temperature and precipitation variations in Canada.

ENSO events are divided into two types, eastern and central Pacific, whose names indicate the location of the largest sea surface temperature anomaly during the event (Ashok et al., 2007; Capotondi et al., 2015). Different types of events tend to produce distinct large-scale teleconnections and remote climate effects (e.g., Ratnam et al., 2014; Taschetto et al., 2020). The effects on Canadian temperature and precipitation are slightly weaker for central Pacific ENSO compared to eastern Pacific ENSO events, as the teleconnected circulation responses are slightly weaker and shifted westward (Yu et al., 2015).

The PDO is the result of a combination of physical processes across the tropics and extratropics, including remote tropical forcing—primarily from ENSO—and local North Pacific atmosphere-ocean interactions (e.g., Newman et al., 2016; Schneider & Cornuelle, 2005). The spatial pattern of the PDO resembles that of ENSO, but the amplitude of the sea surface temperature anomalies associated with the PDO is larger in the mid-latitudes (Figure 4.18, middle left panel). The largest distinction between the PDO and ENSO is their timescales: ENSO is primarily a phenomenon that varies irregularly over periods of a few years, while the PDO varies irregularly over timescales ranging from years to decades. The PDO also influences Canadian climate through PNA-like teleconnections. However, the centre of action of the PDO-associated atmospheric circulation anomalies is further west and north than those associated with ENSO. As a result, a positive PDO phase usually brings warmer than average temperatures to western and northern Canada and drier than average conditions to southwestern Canada (Figure 4.18, middle panels).

Figure take-away: Atmosphere-ocean coupled modes of climate variability (El Niño–Southern Oscillation, Pacific Decadal Oscillation, and Atlantic Multidecadal Oscillation) influence the prevailing winter climate conditions in Canada.

Figure title: Winter climate anomalies associated with positive phases of the El Niño–Southern, Pacific Decadal, and Atlantic Multidecadal oscillations from 1951 to 2022

The AMO is a pattern of interdecadal (every ten years or so) to multidecadal (every few decades) variability characterized by North Atlantic sea surface temperature fluctuations (Kerr, 2000), with a characteristic timescale of 60 to 80 years. It features sea surface temperature anomalies across most of the North Atlantic, with stronger anomalies in the subpolar region and weaker anomalies in the tropics (Figure 4.18, lower left). The AMO is the result of slowly varying ocean processes, whereas the atmospheric North Atlantic Oscillation (described in section 4.3) varies on shorter, interannual (every few years) and even shorter timescales. However, the AMO affects climate in eastern Canada primarily through teleconnections that are like the North Atlantic Oscillation, except that they are shifted westward. During the positive phase of the AMO, a negative North Atlantic Oscillation–like pattern is typically observed, which corresponds to weaker than average west-to-east winds. Relative to average conditions, there is more transport of relatively warm ocean air into eastern Canada, causing warmer than average temperatures in the eastern parts of the country. The impact of the AMO on Canadian precipitation is generally weak (Figure 4.18, lower panels).

Due to its relatively long timescales, ENSO can be predicted months to years in advance, which helps predict climate patterns across Canada on seasonal to annual timescales (see also Chapter 3, section 3.4.1). The PDO can be predicted with moderate skill, while the AMO is somewhat predictable on decadal to multidecadal timescales and is important for understanding long-term climate variability across eastern Canada (Chapter 3, section 3.4.1). It is important to note, however, that the specific effects of ENSO, PDO, and AMO may vary from event to event, and that teleconnections can interact with each other.

4.8.2: Past changes and their causes  

Observations reveal strong multidecadal variations in both the amplitude and frequency of ENSO events throughout the 20th century (e.g., Gulev et al., 2021; Hope et al., 2017; J. Li et al., 2013; Torrence & Compo, 1998). The amplitude of ENSO has been high in recent decades but was relatively low in the mid-20th century (Gulev et al., 2021). Increased ENSO amplitude has the potential to increase associated year-to-year variations in temperature and precipitation in Canada. However, because of short observational datasets and large internal climate variability, such changes in year-to-year variability have not been identified. On the longer timescales, the IPCC AR6 WGI (Gulev et al., 2021) found that there is medium confidence that both ENSO amplitude and the frequency of high-magnitude events since 1950 are higher than they were over the previous century. Observations also show an increase in the number of central Pacific ENSO events in last 20 to 30 years (Capotondi et al., 2015; McPhaden et al., 2011; Timmermann et al., 2018).

There is no clear evidence that the observed changes in ENSO amplitude and event type can be attributed to human-caused climate change (Eyring et al., 2021a; L’Heureux et al., 2013). Climate model simulations do not show strong trends in ENSO amplitude over the past decades and show large internal climate variability, suggesting that observed trends are the result of internal climate variability and are unrelated to human-caused climate change (e.g., Hope et al., 2017; N. Maher et al., 2018; Stevenson et al., 2019). By contrast, there is some evidence that natural and human-caused climate forcings have contributed to variability resembling the PDO and AMO. For example, climate model simulations suggest that the PDO is affected by large volcanic eruptions and changes in incoming solar radiation, both of which are natural climate forcings (e.g., T. Wang et al., 2012). Modelling experiments also suggest that past changes in aerosols from human activity have influenced the phase of the PDO (Boo et al., 2015; Dittus et al., 2021; Klavans et al., 2025), although there is a large degree of uncertainty about such an influence due to large internal climate variability (Oudar et al., 2018). Human-caused greenhouse gases (Bellomo et al., 2018; Mann & Emanuel, 2006; Murphy et al., 2017), human-caused aerosols (Booth et al., 2012; Qin et al., 2020), and volcanoes (Mann et al., 2021) have all been linked to changes in the phase of the AMO. However, no consistent trends in the PDO and AMO have occurred over the historical period (high confidence).

4.8.3: Future changes

The IPCC AR6 WGI report assessed there is high confidence that ENSO will remain the primary mode of climate variability in the 21st century (Lee et al., 2021). The report also found that there is no robust model consensus on changes in ENSO amplitude and ENSO type frequency during the 21st century with warming, even under very high emissions scenarios (SSP5-8.5, RCP8.5) (Bellenger et al., 2014; W. Cai et al., 2018, 2022; Freund et al., 2020; Lee et al., 2021; Wengel et al., 2021). However, it also found that climate models project a significant increase in the strength of precipitation variations associated with ENSO over the 21st century under all emissions scenarios, with larger increases for higher emissions scenarios (Lee et al., 2021; Power et al., 2013; Yun et al., 2021). ENSO-related precipitation variations are also projected to shift and extend eastward under global warming (Huang & Xie, 2015; Power et al., 2013; Yan et al., 2020). These changes modulate teleconnections, resulting in changes in the effects of ENSO on remote temperature and precipitation variations (Beverley et al., 2021; Brown et al., 2020; Taschetto et al., 2020; Y. Wang et al., 2022). On average, CMIP6 models project that Canadian temperature and precipitation variations associated with ENSO will expand eastward (Figure 4.19). These changes are associated with climate models projecting greater warming in the eastern compared to the central tropical Pacific, which reduces the sea surface temperature difference across this region and causes the teleconnections to shift eastward. However, confidence in these climate model projections is limited due to systematic model biases in the simulations of the tropical Pacific. Observations show a persistent cooling of the eastern equatorial Pacific in recent decades, while climate models show a persistent warming (Bayr et al., 2019; Coats & Karnauskas, 2017; N. C. Johnson et al., 2019; L’Heureux et al., 2013; Sandeep et al., 2014; Seager et al., 2019; Sohn et al., 2013). This difference between observations and climate models could suggest that the climate models’ equatorial Pacific sea surface temperature response to global warming is incorrect, and that projections of associated ENSO teleconnections have limited credibility (C. Michel et al., 2020). As the climate warms, ENSO-driven extreme weather events in Canada, such as droughts, floods, and storms, may become more intense and frequent (e.g., Basu et al., 2020; Del Rio Amador et al., 2023; Sun et al., 2023). These changes could result in more severe impacts on ecosystems and communities.

Figure take-away: The influence of the El Niño–Southern Oscillation on Canadian winter climate variability is expanding eastward as the climate warms.

Figure title: Winter climate anomalies associated with the El Niño–Southern Oscillation in the pre-industrial period and late twenty-first century in Canada

The amplitude of the PDO and associated decade-to-decade variations in temperatures and precipitation are projected to become smaller under global warming (Geng et al., 2019; Lee et al., 2021; L. Zhang & Delworth, 2016). Uncertainties about this weakening arise from uncertainties about the future evolution of the mechanisms that determine the PDO and about how future changes in the average state of the Pacific Ocean will interact with sea surface temperature variability on interannual and decadal timescales (Fedorov et al., 2020). Therefore, there is low confidence in the assessed projected weakening of the PDO. In addition, there is low confidence in the AMO response to climate forcing in the future. Because the AMO operates on multidecadal timescales, the length of climate model projections (which typically end in 2100) may not be sufficient to confidently attribute any changes in the AMO to climate forcings (Lee et al., 2021). Nonetheless, PDO and AMO fluctuations in the coming decades may affect regional climate, including in Canada, compounding or offsetting some of the effects of global warming.

4.8.4: Confidence terms in key messages: summary of evidence

Key message 4.11: The El Niño–Southern Oscillation (ENSO) is the dominant source of year-to-year climate variability in western Canada. Year-to-year climate fluctuations associated with ENSO have been larger since 1950 than in the previous century (medium confidence). However, there is low confidence that this change is due to human-caused climate change because internal climate variability is large.

Key message 4.12: The El Niño–Southern Oscillation (ENSO) will remain the dominant source of climate variability in western Canada in the 21st century (high confidence), but there is low confidence in projected changes in year-to-year climate fluctuations associated with ENSO. While climate models consistently show that by the end of the century, the effect of ENSO on winter climate fluctuations will extend into central and eastern Canada, there is low confidence in these projections due to systematic climate model biases.

We have medium confidence that ENSO amplitude has increased since 1950. This assessment is based on multiple observational and paleoclimate data products. We have low confidence that observed changes in ENSO amplitude and patterns are due to human-caused climate change. This is because climate models show large internal climate variability and a lack of significant trends in ENSO characteristics in recent decades.

We have high confidence that no consistent trends in the PDO and AMO have occurred over the historical period. This assessment is based on multiple observational and paleoclimate data products.

Our high confidence that ENSO will remain the dominant mode of climate variability in the 21st century is due to the strong consensus across all models. We have low confidence that the effect of ENSO on winter climate variability will extend into central and eastern Canada. This is because while climate models consistently project these changes, confidence is limited by persistent model biases. There is some evidence that natural and human-caused external climate forcings have contributed to observed PDO- and AMO-like variability. However, we have low confidence in projections of the PDO and AMO because of complex internal climate variability and inconsistent model representations of these patterns.

4.9: Ocean circulation

Key message 4.13: The primary large-scale ocean current system affecting climate in Canada is the Atlantic Meridional Overturning Circulation (AMOC). A weaker than normal AMOC is associated with cooler and drier than normal winters over eastern Canada. There is high confidence that a temporary weakening of the AMOC between 2007 and 2015 led to a period of cooler North Atlantic Ocean surface temperatures and low confidence that this AMOC weakening can be attributed to human influence.

Key message 4.14: There is high confidence that the Atlantic Meridional Overturning Circulation (AMOC) will gradually weaken over the remainder of the 21st century due to human influence, and that this will slightly reduce the warming of eastern and northern Canada. However, the possibility that the AMOC could shut down, leading to a more pronounced regional cooling influence, cannot be ruled out. There is medium confidence that the AMOC will not shut down in the 21st century.

4.9.1: Effects on Canadian weather and climate

Ocean circulation is driven mainly by winds pushing on the ocean surface, and by flows of heat and freshwater into or out of the ocean that affect the density of seawater. For example, warming by sunlight and freshening due to rainfall tend to make seawater less dense, whereas evaporation enhanced by surface winds tends to make seawater cooler, saltier, and denser. The resulting ocean circulation currents move heat around the globe and play an essential role in shaping the Earth’s climate. Especially important is the oceans’ role in moving heat from tropical regions, where heating by the sun is strongest, toward the Earth’s polar regions. The atmosphere plays a major role in this movement of heat as well. Without this continual movement of heat, temperatures would be even hotter near the equator and colder near the poles.

The Atlantic Meridional Overturning Circulation (AMOC) is vitally important for Northern Hemisphere climate because it transports sinking cold sub-Arctic waters southward and warmer surface waters northward, bringing vast amounts of heat to the North Atlantic. The strength of the AMOC largely determines how much heat it carries, so changes in its strength can strongly affect climate in the North Atlantic. For example, a weaker AMOC exerts a cooling influence that is most pronounced in winter and extends westward from the ocean into eastern Canada. A weaker AMOC also tends to reduce precipitation regionally, resulting in fewer wet winter days in eastern Canada (Bellomo et al., 2023). Variations in the AMOC occur naturally and are a major cause of the Atlantic Multidecadal Oscillation (R. Zhang et al., 2019), whose influence on Canada’s climate is described in section 4.8. Although other ocean current systems vary and may change in a warming climate, none has as large an impact on Canadian weather and climate as the AMOC.

4.9.2: Past changes and their causes

Direct ocean current measurements are too few to provide a clear picture of changes in large-scale currents and associated transports of heat. As a result, such information comes mainly from less direct methods. For example, ocean current velocity can be inferred through its physical relationships with more thoroughly observed ocean properties, such as seawater density and sea level (McCarthy et al., 2020). A notable application of this approach is an array of moored instruments (devices anchored in place to measure ocean properties in one location for an extended period), typically referred to as the RAPID array, which has provided continuous measurements of the strength of the AMOC at a latitude of 26.5°N since 2004 (Kanzow et al., 2008; Srokosz & Bryden, 2015). Additional instrument arrays deployed more recently enable a more complete view of AMOC changes over a shorter period (Lozier, 2023).

Measurements from the RAPID array indicate that the AMOC was relatively strong from 2004 to 2007, became weaker from 2007 to 2015, and regained strength afterward until at least 2020 (Figure 4.20a). These changes were likely caused by the combined influences of changes in winds and the density of seawater (Buckley & Marshall, 2016). During the period when the AMOC was relatively weak, it transported less heat into the North Atlantic than when it was relatively strong (Figure 4.20b) (W. E. Johns et al., 2023). This caused upper ocean temperatures in the subpolar North Atlantic to cool by up to 0.2°C/yr (Figure 4.20c) (Bryden et al., 2020; Jackson et al., 2022), leading to successive years of relatively cold sea surface temperatures in that region. In some years, these cold sea surface temperatures extended to the Newfoundland and Labrador coast (Colbourne et al., 2016). By contrast, upper ocean temperatures in the Gulf of Maine and Scotian Shelf warmed dramatically during the weaker AMOC period (Figure 4.20c). Evidence from observations and model simulations points to the contrasting tendencies in these two regions as being a signature of AMOC variability (R. Zhang et al., 2019). A further tendency that appears to be connected with the weakening of the AMOC is a pronounced drop in oxygen concentrations in Scotian and adjacent shelf waters (Claret et al., 2018), which, along with temperature changes, may affect marine ecosystems in this region (Brennan et al., 2016).

Figure take-away: Recent variations in the Atlantic Meridional Overturning Circulation affect the North Atlantic Ocean.

Figure title: Past variations in the strength of the Atlantic Meridional Overturning Circulation and associated heat transport, and a spatial map of the North Atlantic upper ocean temperature trend from 2007 to 2015

The AMOC’s influences on climate before 2004, when high-quality measurements of AMOC strength and heat transport became available, must be studied using other lines of evidence about which we have less confidence. These lines of evidence include analyses of climate and ocean models, ocean reanalysis datasets (data from ocean models combined with observational data), and observed properties that have a statistical connection with the AMOC, such as sea surface temperature (Jackson et al., 2022). A key observation is that sea surface temperatures in the subpolar North Atlantic have cooled from the late 19th century until the present, even as the rest of the world has warmed. This phenomenon, known as the North Atlantic warming hole, is also present in climate models’ historical simulations. One potential explanation is that this regional cooling trend could be linked to a human-caused weakening of the AMOC (K.-Y. Li & Liu, 2025). Such a weakening has been inferred from patterns of sea surface temperature change and other indirect lines of evidence (Caesar et al., 2018, 2021; Rahmstorf et al., 2015). However, climate scientists have debated whether the evidence for these inferred changes is robust (Kilbourne et al., 2022; S. L. L. Michel et al., 2025; Terhaar et al., 2025; Worthington et al., 2021) and whether the changes are caused by internal climate variability rather than human activity (Latif et al., 2022). In addition, CMIP6 historical climate simulations show no clear long-term decrease in the AMOC (blue curve and shading in Figure 4.21a) (Fox-Kemper et al., 2021; Jackson et al., 2022). Instead, these simulations show AMOC strength gradually increasing on average from 1850 until the late 20th century. This strengthening in the CMIP6 models is caused by the simulated influences of human-caused aerosols on clouds, although observational evidence suggests that CMIP6 models may overestimate this influence (Menary et al., 2020). While these simulations show AMOC strength decreasing on average from the late 20th century until the present due to the increasing atmospheric greenhouse gas concentrations, these changes are relatively small and gradual compared to the observed shorter-term variations (black curve in Figure 4.21a), which evidently are dominated by internal climate variability (Eyring et al., 2021a, Section 3.5.4.1).

Overall, there is high confidence that between 2004 and the present, the AMOC weakened and then partially recovered, and low confidence that these changes were forced by human factors. In addition, there is low confidence that AMOC strength has been influenced by human activity since the late 19th century. This is not inconsistent with the existence of the North Atlantic warming hole because other processes that may have contributed to its formation have been identified. These processes include increased poleward heat transport out of the subpolar North Atlantic region, with some contribution from increased low-level clouds (Keil et al., 2020), and increased cooling of the ocean surface caused by changes in winds (Fan et al., 2023; He et al., 2022; Hu & Fedorov, 2020; L. Li et al., 2022).

Figure take-away: Past and future changes in the Atlantic Meridional Overturning Circulation have implications for climate in Canada.

Figure title: Time series of observed and simulated past and future Atlantic Meridional Overturning Circulation strength, and the effect of its future weakening on annual average Canadian temperatures

4.9.3: Future changes

Although it is uncertain whether human-caused warming has resulted in an AMOC weakening between the late 19th and early 21st centuries, there is high confidence in climate model projections of a weakening AMOC over the remainder of the 21st century in response to greenhouse gas emissions from human activity (red curve and shading in Figure 4.21a) (Jackson et al., 2022). This weakening is projected under all CMIP6 emissions scenarios, ranging from very low to very high emissions (Fox-Kemper et al., 2021; Weijer et al., 2020). The magnitude of the weakening does not heavily depend on the emissions scenario (e.g., Bonan et al., 2025). However, there is low confidence in how much weakening will occur by 2100, due mainly to differences between models in simulating projected responses of the AMOC, although ways to reduce this uncertainty have been explored (Bonan et al., 2025). A major cause of the simulated weakening is increased input of heat and freshwater into the subpolar North Atlantic (e.g., Madan et al., 2024). This increase in heat and freshwater reduces the density of surface waters and inhibits the sinking motions that help drive the AMOC. Climate model experiments indicate that melting of Arctic sea ice (W. Liu et al., 2019), which is fresher than seawater, and meltwater from the Greenland ice sheet (Bakker et al., 2016) will contribute to this process.

Climate model projections consistently show a relative lack of warming of surface air temperature across a subpolar North Atlantic region (Figure 4.21b) (Fox-Kemper et al., 2021; W. Liu et al., 2020) similar to that of the observed North Atlantic warming hole (Keil et al., 2020). In contrast to the uncertain contribution of AMOC weakening to the long-term past cooling in this region, AMOC weakening is a primary cause of this projected lack of warming (Menary & Wood, 2018). Climate model experiments have explored the extent to which the projected AMOC weakening may reduce the amount of warming in different regions. For example, one experiment compared a very high emissions scenario (SSP5-8.5) simulation, with strong AMOC weakening, to one in which AMOC strength was artificially held steady (W. Liu et al., 2020). The experiment found that AMOC weakening reduced warming across the subpolar North Atlantic and Labrador Sea from 1961 to 1980 and from 2061 to 2080 by up to 3°C (Figure 4.21c). Warming across eastern and northern Canada was similarly reduced by about 1°C because of the projected weakening of the AMOC. However, this cooling effect only partially offsets the projected warming of over 3°C across Canada under this scenario in this climate model (Figure 4.21b). In this example, the AMOC weakened by about 25% over the interval considered, but in other simulations the AMOC weakens more or less depending on the model and scenario (Lee et al., 2021). Therefore, while the results in Figure 4.21 b) and c) illustrate the probable effects of AMOC weakening on surface warming, the magnitude and timing of these effects is uncertain (Fox-Kemper et al., 2021).

Additional climate model experiments have explored what will happen to the AMOC if global warming is limited to 1.5°C or 2.0°C. In these experiments, the AMOC continues to decline for a few years after global temperatures stabilize, but then gradually recovers to nearly pre-warming levels after about 150 years (Lee et al., 2021; Sigmond et al., 2020). Because a stronger AMOC carries more heat to the North Atlantic, this region warms during the period of AMOC recovery despite global temperatures having stabilized. The future North Atlantic warming hole caused by the previous weakening of the AMOC (Figure 4.21b) is effectively “filled in.” A similar sequence of events occurs if global temperatures rise to 3.0°C above pre-industrial levels before stabilizing.

A further possibility that has been explored is whether the projected changes in the subpolar North Atlantic, especially increased inputs of freshwater, could cause the AMOC to abruptly shut down (Weijer et al., 2019). This is motivated by studies of climate and ocean circulation in the last Ice Age, showing that the AMOC abruptly weakened or shut down numerous times between about 80,000 and 11,700 years ago (Lynch-Stieglitz, 2017). Those episodes are believed to have been caused by sudden large inputs of buoyant freshwater from ice sheet melt or discharge, shutting off the sinking of dense subpolar North Atlantic surface waters that helps drive the AMOC. Their effects on climate included rapid cooling of the Northern Hemisphere, especially in the North Atlantic region. This has prompted climate model experiments that artificially impose an unrealistically large freshening of the North Atlantic to induce an AMOC shutdown (Jackson et al., 2023). Such experiments indicate that the cooling effect of an AMOC shutdown would far exceed that of the projected AMOC weakening illustrated in Figure 4.21 c) (Jackson et al., 2023; W. Liu et al., 2017; Weijer et al., 2019).

Whether the AMOC could actually shut down during the 21st century or beyond is a separate question. Climate model projections do not simulate a 21st century AMOC shutdown even under very high emissions scenarios (Fox-Kemper et al., 2021). However, they do not represent some processes that may increase meltwater release from the Greenland ice sheet, such as accelerated flow of ice into the ocean. Nonetheless, estimates of future Greenland meltwater release from a detailed ice sheet model, while tending to weaken the AMOC, are still insufficient to trigger a 21st century shutdown (Golledge et al., 2019). Some scientists have argued that the AMOC in climate models is unrealistically stable because of systematic model errors, and that simulated AMOC shutdown can occur when these errors are corrected (W. Liu et al., 2017). Additional studies have cited modelling and observational evidence to assert that an AMOC shutdown could be much more likely than standard climate simulations indicate (Ditlevsen & Ditlevsen, 2023; van Westen et al., 2024). However, further work is needed before a scientific consensus can be reached on this question, and currently there is medium confidence that the AMOC will not shut down in the 21st century (J. A. Baker et al., 2025; Fox-Kemper et al., 2021).

Changes in ocean current systems besides the AMOC are less likely to directly impact climate in Canada. There is, however, evidence from climate model experiments that warming-induced changes in wind-driven ocean circulation act as a positive feedback that modestly amplifies the rate of warming, including over central and eastern Canada (McMonigal et al., 2023).

4.9.4: Confidence terms in key messages: summary of evidence

Key message 4.13: The primary large-scale ocean current system affecting climate in Canada is the Atlantic Meridional Overturning Circulation (AMOC). A weaker than normal AMOC is associated with cooler and drier than normal winters over eastern Canada. There is high confidence that a temporary weakening of the AMOC between 2007 and 2015 led to a period of cooler North Atlantic Ocean surface temperatures and low confidence that this AMOC weakening can be attributed to human influence.

Key message 4.14: There is high confidence that the Atlantic Meridional Overturning Circulation (AMOC) will gradually weaken over the remainder of the 21st century due to human influence, and that this will slightly reduce the warming of eastern and northern Canada. However, the possibility that the AMOC could shut down, leading to a more pronounced regional cooling influence, cannot be ruled out. There is medium confidence that the AMOC will not shut down in the 21st century.

We have high confidence that a temporary weakening of the AMOC led to a cooling of North Atlantic Ocean surface temperatures from 2007 to 2015. This assessment is based on the availability of reliable AMOC observations since 2004 and the consistency between the observed AMOC heat transport changes and North Atlantic Ocean temperature trends. However, because of large internal climate variability and the short observational period, we have low confidence that these changes were anthropogenically forced.

We have high confidence that subpolar North Atlantic surface temperatures have cooled since the late 19th century, based on high consistency between different reanalysis datasets. However, we have low confidence that this was caused by an anthropogenically forced weakening of the AMOC, because historical simulations with climate models do not consistently show a long-term decline in the AMOC.

Owing to high consistency among climate model projections and across scenarios, we have high confidence that the AMOC will weaken over the 21st century due to human influence, and that this will reduce the rate of warming in the subpolar North Atlantic and nearby regions, including eastern and northern Canada. While the projected magnitude of AMOC reductions is not very sensitive to emissions scenario, we have low confidence in the magnitude of the AMOC reductions and corresponding consequences for regional climate, due to a large model spread.

While climate models do not project a shutdown of the AMOC in the 21st century, there is only medium confidence in these projections. This is because the AMOC in climate models may be more stable than in reality, as the models do not represent all the processes that affect the AMOC. Therefore, a shutdown of the AMOC in the 21st century cannot be ruled out.

4.10: Synthesis of changes in atmosphere-ocean processes and phenomena

Key message 4.15: Changes that are due to thermodynamic processes are generally robust and well understood.

Key message 4.16: Regional variations in Canadian climate depend strongly on changes in dynamical processes, which are uncertain and less well understood.

Key message 4.17: There is generally more confidence in future human-caused changes than in the attribution of past changes to human-caused climate change.

Compared to CCCR2019, this chapter has been added to assess large-scale atmosphere-ocean processes and phenomena that are relevant to past and future regional variations in Canadian climate. The assessment of these processes and phenomena strengthens the basis of our understanding of other aspects of climate change in Canada assessed in other chapters. This synthesis provides a high-level overview of our main conclusions on large-scale atmosphere-ocean processes and phenomena.

Key Message 4.15 states that changes that are due to thermodynamic processes are generally robust and well understood. This is because changes in thermodynamic processes are directly caused by changes in the radiative balance as a result of human-caused increases in greenhouse gas concentrations. At high latitudes, such changes are amplified through local climate processes, leading to a phenomenon referred to as Arctic amplification. This phenomenon largely explains why northern Canada warms faster than other parts of Canada. Human-caused global warming also results in an increased availability of moisture in the atmosphere, which acts to amplify precipitation across Canada, including that associated with atmospheric rivers and North Atlantic hurricanes. There is evidence that thunderstorm activity across Canada will increase as well, but such changes are less certain because of limitations in the climate models that underpin these projections.

Key Message 4.16 states that regional variations in Canadian climate depend strongly on changes in dynamical processes, which are uncertain and less well understood. Changes in the atmospheric circulation, such as the strength and position of the jet stream, extratropical storms, and atmospheric blocks, are critical to understanding regional patterns of climate change in Canada but are less certain than changes associated with thermodynamic processes. This is because of:

1. the large role of internal climate variability, which is inherently unpredictable beyond a few years
2. the fact that changes in atmospheric circulation are generally driven by gradients (or spatial differences) in temperature changes
   1. Note: Under climate change, different processes lead to opposing changes in large-scale temperature gradients, resulting in relatively small net changes in the atmospheric circulation.
3. limitations of climate models
   1. Note: A notable example is that while climate models consistently project that year-to-year climate variability associated with the El Niño–Southern Oscillation will increase across Canada, there is a large degree of uncertainty due to systematic climate model biases in the tropical Pacific, the key region of the El Niño–Southern Oscillation.  

Key Message 4.17 states that there is generally more confidence in future human-caused changes than in the attribution of past changes to human-caused climate change. This statement is true for several processes assessed in this chapter, including atmospheric rivers, rain rates associated with North Atlantic hurricanes affecting Canada, large-scale environmental conditions favouring thunderstorms, and changes in the Atlantic Meridional Overturning Circulation. This is because:

1. past climate changes are often heavily influenced by internal climate variability, making it challenging to determine if such changes are due to human-caused climate change;
2. past climate changes are relatively small compared to future climate changes, at least in intermediate (SSP2-4.5) to high (SSP3-7.0) emissions scenarios; and
3. many observational datasets are relatively short.

4.11: Knowledge gaps

Much of the uncertainty in projections of regional variations in Canadian climate is due to internal climate variability, which is inherently unpredictable beyond a few years, and hence cannot be reduced. However, the following knowledge gaps can be narrowed with future efforts.

Understanding mechanisms responsible for changes in the atmospheric circulation and their representation in climate models

While changes in the atmospheric circulation are thought to be driven by changes in large-scale spatial differences in temperature changes, the underlying mechanisms are poorly understood. For example, a theoretical framework on how atmospheric blocks respond to global warming is lacking. Progress can be made by conducting systematic studies using idealized experiments with a hierarchy of models of different complexity (P. Maher et al., 2019) and by leveraging other existing and emerging tools (T. A. Shaw et al., 2024).

There is also uncertainty about how well these processes are captured in current climate models. While climate models tend to project a poleward shift of the jet streams in response to climate change, some studies have questioned the reliability of such projections. In particular, it has been suggested that climate models systematically underestimate the response to Arctic climate change (Screen et al., 2022; Smith et al., 2022), and that after correction of this underestimation, there would be a net projected equatorward shift, not the poleward shift of the uncorrected projections (Screen et al., 2022). However, new evidence suggests that climate models do not systematically underestimate the jet stream response to Arctic climate change (Sigmond & Sun, 2025), highlighting the need for further studies. In addition, climate models are not able to simulate the amplitude of past changes in the North Pacific jet stream (Patterson & O’Reilly, 2025) and North Atlantic jet stream (Blackport & Fyfe, 2022), which calls into question the reliability of projections. Resolving these model-observation discrepancies should therefore be a high research priority.

Attributing past long-term trends in atmospheric-river activity

While observations show that the frequency and intensity of atmospheric rivers have increased over Canada in recent decades, there are currently no studies that have tried to attribute such changes to human activity. There is evidence that recent extreme atmospheric-river events have been made more likely by climate change, but attribution studies on the long-term trends are currently lacking.

More studies focused on the impacts of North Atlantic hurricanes in Canada

While it is well established that the intensity of North Atlantic hurricanes will increase in the future as a result of human-caused climate change, studies on hurricanes that affect Canada are sparse. Given the potentially large impacts these changes have on extreme rain and wind events in eastern Canada, studies focused on Canada would improve understanding of this topic.  

Reducing tropical Pacific climate model biases to increase confidence in the impacts of the El Niño–Southern Oscillation (ENSO) on Canada

Climate models consistently show that future human-caused climate change will act to extend ENSO-related year-to-year climate variability into eastern Canada. While such a high level of model agreement typically leads to confident projections, there is a concern that there is a common bias in climate models that may lead to incorrect projections. Specifically, there is persistent cooling of the eastern equatorial Pacific in observations over recent decades, which cannot be reproduced by current climate models. Resolving this discrepancy through climate model improvements would lead to a better understanding and to more confident projections of the impact of ENSO on Canadian climate variability.  

Representation of the Atlantic Meridional Overturning Circulation (AMOC) in climate models

Climate models consistently project that the AMOC will weaken in response to human-caused climate warming. However, there is much uncertainty about the magnitude of this weakening, with some studies arguing that the AMOC could even shut down during the 21st century. While current climate models do not project such a shutdown, these claims are based on the fact that climate models do not properly represent the impacts of the melting of the Greenland Ice Sheet, and some evidence that suggests that the AMOC in climate models is unrealistically stable because of other systematic model errors. Resolving these issues will increase confidence in projections of winter climate in eastern Canada.

FAQs

FAQ 4.1: Why is Canada warming faster than the world as a whole?

The Earth’s climate is heating up because of increasing greenhouse gas emissions from human activity, primarily the burning of fossil fuels (Chapter 1, section 1.1). The response of global surface temperature to increasing greenhouse gas emissions is not spatially uniform. Greater warming of the surface over land than over oceans is observed because the oceans’ greater heat capacity slows down warming over oceans relative to warming over land. Greater warming in the Arctic than for the world as a whole is also observed because climate feedbacks amplify warming in this region, a phenomenon known as Arctic amplification. Both of these factors contribute to the fact that Canada, and the Canadian Arctic in particular, is warming at a faster rate than the global average.

Figure take-away: Canada has warmed at nearly twice the rate of the global average, and Canada’s Arctic has warmed at three times the rate of the global average since 1970.

Figure title: Surface temperature trends for Canada, the Canadian Arctic, and the global average

FAQ 4.1 Figure 1 shows that Canada’s rate of surface warming has been close to two times the global rate for the period 1970-2023. This is partly because Canada is mostly land and also because of the phenomenon of Arctic amplification. Given the smaller heat capacity of land, land areas warm more quickly than ocean areas. This is evident in the figure, which shows that for 1970-2023 the global land area has warmed about 50% faster than the combined global surface temperature, which combines surface air temperature over land and sea surface temperatures. Furthermore, Canada’s location at mid-to-high latitudes means that warming in Canada is amplified by local climate feedbacks. In the Canadian Arctic, Arctic amplification contributes to an even greater rate of warming, about three times the global rate for the period 1970-2023 (learn more about Arctic amplification in section 4.2 and Box 4.2). Note that the warming rates shown in FAQ 4.1 Figure 1 are based on the average of four gridded global surface temperature data products. These products are used for consistency across the global and Canadian regions. In Chapter 2, data products specific to Canada (see gridded station data in section 2.3.4.1 for details) are used to assess past surface temperature change in Canada and show similar warming rates (section 2.4.1). Source: Chapter 4, section 4.2.

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Supplementary Material

Figure take-away: The positive NAO phase is associated with a stronger jet stream and colder and drier conditions over eastern Canada.

Figure title: The winter wind, temperature, and precipitation patterns associated with the positive phase of the North Atlantic Oscillation