Chapter 10: Climate services and using climate information

Chapter description

This chapter describes the role of climate services in helping various readers use the information in this report and other sources for adaptation planning, risk assessment, design, and emergency management in a changing climate, and outlines some common considerations for finding, choosing, and using information on future climate.

Plain language summary

The assessment of changes in Canada’s physical climate set out in this report was developed by teams of authors who have in-depth subject matter expertise. This chapter bridges the gap between the physical climate science and the subsequent practical application of climate data and information on regional and local scales. It is distinct from other chapters in this report because, rather than giving a formal assessment as the others do, this chapter provides a starting point for understanding how best to use currently available climate information.

One of the key roles of climate service providers is to tailor climate data and information to meet users’ specific needs by region, sector, or profession. Climate service providers therefore engage with users to understand their needs, provide guidance on using climate data and information, and co-produce information with them when warranted. The mandates and focus of climate service providers vary widely. For example, some provide adaptation services or carry out applied regional climate research. While there are many climate service providers established around the world, there are no formal standards or governing bodies for providing climate information.

Requirements and incentives to make use of climate projections are becoming more common. These requirements and incentives are driven by multiple levels of government, and professional associations and organizations in charge of standards and codes. As a result, many professionals who have never made use of climate projections are now required to do so (or soon will be). While there is a wide range of users and ways in which they apply climate projections, certain common considerations are important across the field of climate services. These considerations include ensuring the relevance of information to specific user needs, considering the area of interest and resolution of the information required, considering the timescale over which the climate indicators of interest change, describing emissions scenarios and identifying the relevant time horizons, exploring ranges of change (uncertainty), and understanding differences arising from the use of different baseline periods.

Climate service providers have a role to play in supporting adaptation to climate change, including facilitating the assessment of climate risks. To do so, they often organize climate information by hazard category as a way of connecting users to relevant climate variables and available climate projections. In this chapter, we present a set of 12 hazard categories relevant to Canada. For each, we draw from information available in other chapters of this report relevant to the hazards in the category.

10.1: Introduction

Chapters 2 to 9 of this report assess the state of knowledge of key aspects of past and future changes in physical climate in Canada (see Chapter 1, section 1.3.2, for what’s in and out of scope in this report). In many places, those chapters build on global-scale and regional-scale information from the Intergovernmental Panel on Climate Change (IPCC) reports (IPCC, 2021b, 2022b). However, as noted in one of the two IPCC reports cited, the information is generally not on the national, local, or sectoral scale needed for adapting to a changing climate:

“Some climate adaptation planning already uses climate information as provided by the IPCC. However, depending on the decision context, this information may be too coarse, too broad or too disciplinary to directly inform decision-making at the scale where adaptation measures are taken (Howarth & Painter, 2016; Nissan et al., 2019). Thus, while the IPCC’s role is clearly perceived as that of a reference – an authoritative starting point – there is a need for complementary information to translate the assessments at the national, local or sectoral level (Howarth & Painter, 2016; Kjellström et al., 2016; van den Hurk et al., 2018; Vaughan et al., 2018).”
– Excerpt from Chapter 12: Climate Change Information for Regional Impact and for Risk Assessment, in Climate Change 2021: The Physical Science Basis (Ranasinghe et al., 2021)

Our objective in this chapter is to help readers move from knowledge to application, to help them use this report in their own context, to describe where to find more specific information, and to know what to expect when using tailored climate information. We start by describing the role of climate service providers (see Table 10.1 for definitions of climate services). This role has emerged to bridge the gap between larger-scale knowledge assessments and the localized and specific information that users need.

Responding to climate change involves both mitigation and adaptation. Mitigation focuses on reducing greenhouse gas emissions to limit the severity of impacts associated with global warming. Adaptation is aimed at increasing resilience to the amount of climate change that has already occurred, and to future changes that cannot be avoided. Both mitigation and adaptation take place simultaneously as climate continues to change, and are often related. For example, as the climate changes, many efforts to reduce emissions will need to explicitly take future climate into account to be effective. Future climate risks can be reduced by undertaking both mitigation and adaptation (IPCC, 2018).

Climate change will affect every location in Canada differently. Therefore, readers using this report for the purpose of adapting to climate change need to apply the information in it to their own specific context. For example, in some cases, they need to assess small differences in local characteristics that strongly influence how the impacts of climate change will play out (sections 10.3.1 and 10.3.2). The impacts of climate change also need to be assessed differently for each profession and economic sector.

In a stable climate, decision-makers could prepare for the expected weather and climate conditions by using only historical data (for locations where sufficient observations existed). However, in a changing climate, adaptation requires a shift from relying solely on past-climate information to incorporating climate projections. Explicitly considering future-climate information in a wide range of decision-making and planning activities, such as risk assessment, design, and emergency management, is essential (O’Kane et al., 2024). However, determining exactly how professional, sectoral, and local contexts affect the interpretation of data and information is not always straightforward. While climate projections are a powerful tool, there are challenges associated with their wide-scale and immediate adoption. These challenges include the range of possible outcomes indicated by climate projections, their evolving methods, the possibility that climate projections may not be available for all hazards of interest, and the reality that most professionals have little experience using them. When there are difficulties obtaining projections or no clear guidance on their use, it can result in either decision paralysis or reverting to using historical data alone. Therefore, the role of climate service providers has emerged to facilitate this complex and nuanced process.

To help readers use this report in conjunction with localized and tailored climate information, we have divided this chapter into three main sections. In the first, we provide an overview of what climate services are and the roles they play (section 10.2). Next, we outline common considerations when using climate projections (section 10.3). Then, we present a synthesis of 12 categories of climate hazards (section 10.4). These 12 climate hazard categories are as follows:

1. Extreme heat and heatwaves
2. Extreme cold, loss of cold, and seasonally frozen ground
3. Extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods
4. Extratropical storms and hurricanes
5. Thunderstorms
6. Non-pluvial (rain-on-snow, snowmelt, and ice jam) floods
7. Droughts
8. Wildfires
9. Permafrost warming and thaw-driven landscape changes, and terrestrial ice loss
10. Sea-level change, storm surge, and coastal flooding
11. Marine hazards (ocean circulation, ocean temperature, marine heatwaves, ocean salinity, ocean stratification, ocean acidification, and deoxygenation)
12. Strong winds

This list draws on the contents of some of the other chapters of this report and examples of how various indicators have been or could be used to inform decisions for a given hazard. Finally, in section 10.5, we provide a high-level summary of the main messages addressed by this chapter.

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

10.2: Climate services

10.2.1: Defining climate services

Generally speaking, climate service providers produce information to assist decision-making (WMO, 2011) about climate risk management and adaptation planning (Hewitt & Lowe, 2018). However, to provide climate services, they do more than simply produce data. They also put considerable effort into ensuring the information and data they produce are useful, usable, and used (Máñez Costa et al., 2022; Vaughan et al., 2018).

Climate services typically differ from meteorological forecasting services in that climate services provide information on the future climate regionally and over long time horizons. Meteorological forecasts, in contrast, focus on near-term weather conditions at specific locations. However, in some instances, both types of services are available from a single organization, and some providers’ mandates include seasonal and decadal predictions.

The field of climate services has been rapidly evolving (Lourenço et al., 2016; O’Kane et al., 2024) and is ultimately regional or local in nature. For these reasons, there is no single definition of what climate services are (see Table 10.1 for examples of definitions). The range of services offered by climate service providers vary in terms of the products they provide, the services they deliver, the audiences they serve, and their level of engagement to tailor their products. For instance, some providers are involved in the development of raw data and scientific studies, applying this expertise to summaries, statistical analyses, and other tailored information products and expert advice (WMO, 2011). Providers can also be actively involved in co-developing tailored data products with users for risk assessment and adaptation purposes, including convening transdisciplinary work involving experts in climate modelling, impacts, and adaptation (Findlater et al., 2021; Hewitt et al., 2012). See section 10.3.2 for examples that illustrate how providers engage with users in the co-development or co-production of tailored services.

Table 10.1: Three definitions of climate services

Adapted from: Brasseur and Gallardo (2016).

Climate service providers can play different roles along the adaptation planning cycle illustrated in Figure 10.2. The first step, early engagement and planning, often requires guidance, resources, and training. The second step, understanding how the climate is changing, involves using robust historical- and projected-climate information tailored to a specific context (region, sector, users, etc.). The third step, identifying impacts of climate change, involves further tailoring information to a specific context and related hazards to enable risk assessment and adaptation in subsequent steps.

 Figure take-away: Climate services have a role to play in each step of the climate adaptation planning cycle, though some providers focus more on some steps than others.

Figure 10.2: An illustration of the iterative nature of the adaptation cycle and key steps in the cycle. Climate services can play a role at each step. Adapted from: Figure 2 in Canada’s National Adaptation Strategy (ECCC, 2023).

Despite differences in audiences served by different providers (Vaughan & Dessai, 2014), a core set of audiences tends to include policy analysts and decision-makers, professional and industry associations, and individual users in specific sectors and professions. These users include engineers, planners, farmers, agrologists, ecologists, and consultants. While some climate service providers explicitly seek to inform the public, the media, and the education system (BC Climate Action Secretariat, 2025), doing so is not a priority for others. Finally, some climate service providers work more directly with researchers in the fields of climate science and impacts.

Climate services have important attributes in common that make them valuable as a solid source of information for decision-makers: first, their credibility, which is their perceived authoritativeness or the believability of their technical prowess; second, their legitimacy, or the perceived fairness of produced data and information; and third, their saliency, or the perceived relevance of the information they provide (Cash et al., 2003). Climate services rely, for instance, on assessment reports such as this one to help ensure that guidance is up to date and credible. This report has expert authorship, has been extensively peer-reviewed, and uses consistent uncertainty language, set out in Chapter 1, section 1.4.3. The role of climate services is essentially to make use of credible information in a way that is relevant to potential users.

Box 10.1: Climate service providers in Canada

The landscape of climate service providers in Canada is evolving, with more people needing access to climate services than ever. Climate services have been delivered on a user-driven basis in various forms in some parts of the country for over two decades. This has been carried out by regional climate service providers, as well as non-profits, academic institutions, and consulting firms.

In 2018, the Canadian Centre for Climate Services was established by the Government of Canada as part of Environment and Climate Change Canada. As the national climate service provider, the Centre plays a role in coordinating climate services across the country and in advancing Canada’s National Adaptation Strategy (Chapter 1, Box 1.1) (ECCC, 2023). Increasing demand for climate services is reflected in the 36% increase in requests received by the Centre’s Support Desk, growing from about 500 cases per year in 2019–2021 to over 700 cases per year in 2022–2024.

Creating a comprehensive list of climate service providers is not feasible, as such a list may quickly become outdated, be too long to be useful, or rely on arbitrary distinctions to define which organizations are considered climate service providers. This challenge reflects the fact that a wide range of organizations do work or have worked in this field. As a starting point for readers of this report, Box 10.1 Table 1 provides a list of five regional climate service providers (at the time of publication) that directly help the national climate service provider deliver on its mandate, including the ClimateData.ca portal.

Note that no regional climate service provider dedicated to northern Canada is listed in Box 10.1 Table 1. For northern Canada, a collaborative approach to delivering climate services is in place with multiple partners, including Indigenous organizations, regional climate service providers, and Crown-Indigenous Relations and Northern Affairs Canada.

Climate services continue to be offered by many organizations that are not on this list (see, for example, Case Story 10.1). The climate services landscape is still emergent, so it is helpful to take stock of the providers that may be available.

Box 10.1 Table 1: List of five regional climate service providers that partner with the national provider to deliver climate services to different regions across Canada (at the time of publication)

As noted in Box 10.1, there is increasing demand for climate services, including from professionals who have never used climate projections data before. This is due in part to increasingly common requirements to explicitly consider future climate. The following are some examples, at the time of publication, of such initiatives:

• The modernization of national codes through periodic updates to the National Building Code of Canada, the Canadian Highway Bridge Design Code, the Canadian Electrical Code, the National Fire Code, and the National Energy Code for Buildings (Canadian Commission on Building and Fire Codes, 2022a, 2022c, 2022b; Canadian Standards Association, 2019, 2024a).
• Provincial-level building codes and procurement. For example, in 2015, British Columbia’s Ministry of Transportation and Infrastructure (called the Ministry of Transportation and Transit at the time of publication) introduced a requirement to consider climate change in all new designs (BC Ministry of Transportation and Infrastructure, 2015, 2019).
• Infrastructure funding programs prompting applicants to consider climate projections.
• The adoption of national and regional adaptation strategies and plans.
• nsurance companies including climate change in risk models to inform decisions regarding policy coverage and climate-related damages.
• he federal Office of the Superintendent of Financial Institutions’ release of Guideline B-15 on Climate Risk Management (OSFI, 2023), which establishes the Office’s expectation that federally regulated financial institutions consider information on future climate in managing climate-related risks.

10.2.2: Understanding user needs, tailoring, and co-production

Bridging the gap from producing useful information to producing information that is also usable and used does not come without challenges. While mandates vary, what is essential to all climate service providers is the recognition that delivering credible, tailored information that meets user needs requires a concerted effort (Hewitt et al., 2012; Huard et al., 2014). In other words, delivering tailored information means ensuring a deep understanding of the products, services, and guidance that climate service users need. However, achieving such an understanding cannot be obtained solely through a survey of needs; it requires meaningful engagement with users, including in some cases direct collaboration or co-production. Furthermore, climate services increasingly combine different types of knowledge, from scientific to narrative storytelling, to better engage target groups of decision-makers (Moezzi et al., 2017).

Just as users have different needs, those needs are not static. Climate service providers invest ongoing resources in understanding users’ needs to ensure that their products and services not only remain grounded in those needs but also continue to evolve in response to evolving needs. Climate service providers have a responsibility to provide authoritative and defensible information and data while ensuring that users understand the information provided and how it can be used in their decision-making process. This is particularly important as new data are continually made available.

Several factors are key to delivering successful, multidisciplinary, cross-sector climate services. According to an early vision for climate services by the United States National Research Council (National Research Council et al., 2001), successful climate service providers are organizations that (1) are user-centred, (2) are supported by active research, (3) provide information, including climate projections, on a variety of space and timescales, (4) steward their knowledge base, and (5) engage in active and well-defined collaborations with government, business, organized civil society, and academia. Common themes in recent assessments of climate services tend to highlight the importance of deeply understanding user needs, building capacity to bridge the gap between climate science and user expertise, and displaying a willingness to co-produce information where warranted (Lucas, 2025).

To learn more about the emergence of climate services, the history, their assessment, and the challenges that come with providing such services, see Chapter 12 of the Working Group I contribution to the IPCC’s Sixth Assessment Report (AR6) (Ranasinghe et al., 2021).

Case Story 10.1: Climate change, food security, and Tŝilhqot’in wild food harvesting

The Tŝilhqot’in National Government is the governing body that represents the Tŝilhqot’in Nation and the six Tŝilhqot’in communities, Xeni Gwet'in, Yuneŝit'in, Tl'esqox, Tl'etinqox, Tŝideldel and ɁEsdilagh. The Tŝilhqot’in are the “People of the River” and their territory extends from the Coast Mountains in central British Columbia to the Fraser River.

Recommended citation:

Tŝilhqot’in National Government (2026). Climate change, food security, and Tŝilhqot’in wild food harvesting [Case story 10.1]. In Canada’s Changing Climate Report 2026. (pp. xx–xx). Government of Canada.

The Tŝilhqot’in National Government (TNG) undertook a project from 2021 to 2022 aimed at better understanding and developing strategies for responding to the effects of climate change on traditional food security and, by extension, Tŝilhqot’in health and wellness. The goal was to begin to understand how climate change might affect important traditional foods. The project was funded by the First Nations Health Authority’s Indigenous Climate Health Action Program to support the Tŝilhqot’in Nation’s planning initiatives. The Tŝilhqot’in Nation has six member communities (ʔEsdilagh, Tl’esqox, Tl’etinqox, Tŝideldel, Yuneŝitin and Xeni Gwet’in) and the Nation’s Territory is in central British Columbia. Access to traditional foods is an important aspect of promoting healthy deni (people), and this requires healthy nen (lands, resources, territory). Understanding nenqay detelɁaŝ (how the land, water and resources change and impact the Nation’s cultural security) and managing for cumulative effects are important aspects of adaptation planning. The project team engaged with the Tŝilhqot’in communities to identify concerns, conduct risk assessments, map out projected changes in the territory, develop climate change education material, and establish strategies for ongoing work.

Focused on the communities’ priority food security concerns, TNG collaborated with ESSA Technologies Ltd. to assess Tŝilhqot’in Territory, review research and analyze scientific data (including climate data from ClimateNA) (Centre for Forest Conservation Genetics, 2025b; Mahony et al., 2022; Wang et al., 2016) to better understand environmental changes. To inform environmental management and natural-resource planning, a first phase of work analyzed changes to future annual and seasonal climate variables that were projected by comparing observations (1981–2020) to mid-century (2061–2080) projections. Temperature changes were projected for mean annual temperature and maximum summer temperature. Precipitation changes were projected for autumn and winter precipitation. Changes in moisture deficits were projected for spring and summer, and annually. Variables were projected for both intermediate (SSP2-4.5) and very high (SSP5-8.5) emissions scenarios.

Biogeoclimatic Ecosystem Classification (BEC) is a rigorous, hierarchical classification system used to describe vegetation of mature ecosystems in British Columbia (B.C. Ministry of Forests, 1991). In the second phase of work, Dr. Tongli Wang, Associate Professor in the Department of Forest and Conservation Sciences at the University of British Columbia, shared data for projected changes in BEC zones to inform TNG’s high-level planning (see Wang et al., 2012 for original BEC zone mapping).^{Footnote 1} Using the BEC projection datasets, ESSA Technologies conducted change detection mapping to identify areas where large changes in BEC zones were projected, and areas where BEC zones were not expected to change. Case Story 10.1 Figure 1 shows the degrees of ecosystem change across Tŝilhqot’in Territory from the present to the end of the century.

Case Story 10.1 Figure 1: Map showing the degree of ecosystem change (high to low, in grey shading) in the Biogeoclimatic Ecosystem Classification (BEC) zones projected under an intermediate emissions scenario (SSP2-4.5) for the period from 2011 to 2100 in Tŝilhqot’in Nation Territory.

The changing distribution patterns of ecosystems highlight two notable areas to support resource management and long-term food security: climate refugia and climate impact. Areas of climate refugia are ecosystems where change is least expected, which would continue to support the existing conditions for suitable habitat. Ecosystem protection and monitoring of species populations, genetic diversity, and potential stressors can increase these ecosystems’ resilience to changes in areas of climate refugia. Areas of climate impact are ecosystems where change is expected to be greatest. Ecosystem restoration efforts and informed management of existing populations would be important in areas of climate impact.

Digging deeper, the team modelled (Phillips et al., 2025) distributions of six culturally important plant species that are gathered for food and medicine and have values for wildlife and wildlife habitat. Species that were modelled, included dɨg (saskatoon, Amelanchier alnifolia), súnt’iny (mountain potato, Claytonia lanceolate), bedzɨsh yedeyan (Labrador tea, Rhododendron groenlandicum), ledi (trapper’s tea, Rhododendron columbianum), nuŵɨsh (soopolallie, Shepherdia canadensis), and melguns (chokecherry, Prunus virginiana). Current habitat suitability was modelled, and changes in habitat suitability were projected based on the intermediate emissions scenario (SSP2-4.5). Case Story 10.1 figures 2, 3, and 4 show the model outputs for habitat suitability for Labrador tea.

Case Story 10.1 Figure 2: Map showing the past habitat suitability (high to low, in grey shading) for Labrador tea estimated for the period from 1991 to 2020 in Tŝilhqot’in Nation Territory.

Case Story 10.1 Figure 3: Map showing the habitat suitability (high to low, in grey shading) projected for Labrador tea by mid-century (2041–2070) under an intermediate emissions scenario (SSP2-4.5) in Tŝilhqot’in Nation Territory.

Case Story 10.1 Figure 4: Map showing the habitat suitability (high to low, in grey shading) projected for Labrador tea by the end of the century (2071–2100) under an intermediate emissions scenario (SSP2-4.5) in Tŝilhqot’in Nation Territory.

In parallel to this work, TNG’s forester, wildlife biologist, and agrologist mentored graduate students from the University of British Columbia’s Sustainability Scholars Program to conduct literature reviews to compile information to support discussions around caring for wildlife, plants and soils. TNG teams continue to engage with Tsilhqot’in members (including youth, elders, and knowledge holders) and the public, and coordinate efforts with external governments, and universities to advance approaches for sustainable resources management. Through respectful collaboration and the weaving together of Indigenous Knowledge and scientific approaches, TNG has established a starting point for food security planning in a changing climate.

10.2.3: Climate services standards

Currently no standardization or certification applies to the provision of climate data, information, or guidance. However, recently there has been a move internationally towards voluntary adoption of climate services standards (Climate Sense, 2022), the guiding principles of which are agility, collaboration, flexibility, integration, learning, traceability, and transparency. An emerging aspect of this work is defining ethics for climate service providers regarding the responsibility they share when delivering information that will be used to assess risks (Biella et al., 2024; Dee et al., 2024).

Climate service providers who interface with decision-makers, typically provide detailed guidance on how data are or are not intended to be used. For example, climate service providers encourage the use of a range of climate model projections wherever possible and help users understand sources of uncertainty associated with these projections (such as the emissions scenario, climate model, downscaling method, and internal climate variability) and their changing relative importance over different time horizons (Box 10.2; Chapter 3, section 3.3). See section 10.3 for additional considerations on the use of climate information.

10.2.4: Climate data standards and platforms in Canada

Accessibility and reproducibility of scientific data and results are major concerns in all scientific disciplines (Baker, 2016). Most Canadian climate service providers adopt principles assuring the quality of data products disseminated in support of adaptation, given the high monetary and human costs associated with climate change (Sawyer et al., 2020). These principles, which were also adopted in IPCC AR6 (Iturbide et al., 2022), are grouped together under the acronym FAIR, which stands for Findable, Accessible, Interoperable, and Reusable. In accordance with these principles, most Canadian climate service providers supply details about the data they provide, such as data provenance, suitability, and completeness; associated uncertainty; and methodologies used, for example, to calculate specific indicators, to downscale to finer spatial resolution, or to correct biases that may be present in climate model simulations compared to observations.

To enable the adoption of FAIR principles, Canada’s national and regional climate service providers collaborate with each other, with researchers, and with advanced users on the Power Analytics and Visualization of Climate Science (PAVICS) platform. Developed and maintained by Ouranos and numerous collaborators, PAVICS is a virtual laboratory of climate data, metadata, and analysis tools for climate service providers and advanced users. The platform is used to analyze observations, climate projections, and reanalyses while ensuring quality control over the data provided and related metadata without the need to download them in bulk locally. Created in 2018, PAVICS is now used to prepare a large portion of the data disseminated by several major Canadian climate data portals and is accessible to the public.

The GeoMet platform, provided by the Meteorological Service of Canada, also operates according to the FAIR principles and enables public access to weather, climate, and water datasets under the Open Government License through interoperable web services and application programming interfaces.

Box 10.2: Providing guidance helps users avoid data overload and decision paralysis

Climate service providers improve the availability and usability of climate data for adaptation decision-making. This can result in a wealth of data related to physical climate risks. However, climate data can be so abundant and technical as to impede use of the data in decision-making. A common misconception about the use of scientific information in decision-making is the belief that it flows directly from scientists to end users (Feldman & Ingram, 2009). In fact, data tend to be presented and organized in a way that seems logical to subject matter experts in the climate domain, but that can be unintuitive to practitioners who need to incorporate information on future climate into their work. This gap between climate science and decision-making has been called the “valley of death” (Swart et al., 2021). Good guidance can help users navigate the wealth of climate data and information available, including how to interpret information about uncertainty and confidence.

For climate projections, the range of possible future climates can be explicitly linked to factors such as emissions scenarios, internal climate variability, and differences in climate models (section 10.3.5). To avoid decision paralysis, it is important to clearly communicate these types of details and the level of scientific confidence in the information provided. Without clear guidance on the importance of considering a range of projected changes, users may use a single (often median or average) value (Wallisch & Karlovich, 2019) and potentially default to using observations alone if unsure how to proceed.

Information about scientific confidence and how it may be related to but distinct from uncertainty is also necessary. Datasets and reports may include levels of confidence. For example, the knowledge assessment chapters of this report (chapters 2 to 9) use standardized confidence language, with carefully defined meanings, and this language follows IPCC AR5 and AR6, as described in Chapter 1, section 1.4.3. In addition to using clearly defined confidence language, it is equally important to guide users in interpreting what confidence levels mean in practice when using climate projections. Without such guidance it is easy to assume that low confidence is a reason to disregard information, whereas the intent is to use the information with caution and caveats in mind.

Finally, an important part of providing guidance is to help users understand when standards, practices, and heuristics developed for a static climate may need to be reviewed, updated, and in some cases reconstructed to be suitable for use in a changing climate. The scope of this challenge for users could lead to decision paralysis without sufficient guidance.

10.3: Common considerations for using climate projections

When it comes to characterizing future climate in a warming world, incorporating climate projections is essential, as historical data alone are insufficient (see section 10.2.3 for a discussion of the emergence of standards and ethics related to providing climate projections). A common way to obtain climate data is from publicly accessible climate portals. To meet specific local needs and provincial and territorial government requirements, many climate service providers have created their own climate data products and portals (Box 10.1 Table 1). One example of a national portal, ClimateData.ca, is the result of a collaboration among multiple partners. This portal in turn makes use of national platforms, such as PAVICS and GeoMet, where researchers and advanced users can carry out analysis and collaborate on code development (section 10.2.4).

Choosing which projections to use can be challenging, as different sources may appear to provide different information. While data from different providers and portals may reflect slight methodological differences, Lavoie, Caron, et al. (2024) showed that, across four Canadian portals, differences are typically minor and unlikely to influence decision-making in practical applications. The preference for and expectation of a single objectively correct value for climate data is one that is better suited to a static climate than a changing one.

In some cases, online data portals may not provide information on a user’s desired indicator, in a desired format, or at a desired level of regional aggregation. In these cases, climate service providers may be a source of custom analyses of climate projections. The availability of reliable data on future climate depends on the ability of climate models to simulate complex variables and phenomena. In cases where this limits the availability of authoritative projections, user needs may be met by qualitative guidance based on literature reviews.

Regardless of where users look for information best suited to their specific needs, they will be confronted with a series of choices. To help them find relevant information and make the best choices, some key considerations are described in the box and sections that follow.

Box 10.3: Enhancing climate data usability through the co-development of tailored climate data visualizations

Reviewed by Cambium Indigenous Professional Services and the Cree Nation Government.

Climate services aim to provide climate information for adaptation planning that is useful, usable, and used to support increased resilience to climate change (section 10.2.1). In pursuit of this goal, climate service providers often collaborate with partners and users to develop new techniques for contextualizing changes in climate. This collaboration also seeks to reduce data overload and decision paralysis associated with climate data.

The iterative process of working together on the development of new tools and methods, resulting in collaborative products, allows users to express what is important for their project, and for the data experts to provide information that suits these needs without creating data overload. The Canadian Centre for Climate Services participated in a project led by Cambium Indigenous Professional Services to co-develop community climate data profiles with four First Nation, Inuit, and Métis partners. This collaboration resulted in a flexible template and guidance that improved the usability of climate data by contextualizing it alongside lived experience. 

The incorporation of generational framing, showing the data alongside a representative lifespan, helped community members better relate to and position themselves in the evolution of the climate. This generational framing, showing an individual aging from child to senior, visualizes and communicates the long-term impacts of climate change by better aligning with Indigenous worldviews and ways of knowing. Similar concepts have independently been used elsewhere, such as in the IPCC’s AR6 Synthesis Report (IPCC, 2023) and by other organizations in Canada working to communicate climate information.

Subsequent collaboration and co-development of climate data between the Cree Nation Government, Cambium Indigenous Professional Services and the Canadian Centre for Climate Services endeavoured to effectively communicate climate data at a workshop on Climate Change Adaptation and Environmental Emergency Preparedness in Chisasibi, Quebec. The co-development of material for this workshop resulted in multi-generational graphics such as Box 10.3 Figure 1, which was presented to the Cree Nation of Chisasibi. This visual reduces data overload for Community members because it is more intuitive than conventional technical graphs.

Box 10.3 Figure 1: Multi-generational thermometer graphic illustrating how different generations will experience temperature increases on the hottest day of the year due to climate change. Source: adapted with permission from the Cree Nation Government.

Expanding on the inclusion of a single generation, Box 10.3 Figure 1 uses three generations to further contextualize the change in climate from 1950 to the end of the century. This approach depicts the three generations of today (seniors, adults, and youth) centred on 2025. Today’s seniors, born in the 1960s, experienced the past climate during their childhood. Today’s adults, born in the 1990s, will experience the changes projected for the middle of the century. Today’s youth, born in the 2020s, will experience even more changes projected for the end of the century.

To position the generations alongside data, a climate index is presented above the timeline. Proportionally filled thermometers were chosen to display the average hottest days in Chisasibi, based on downscaled CMIP6 climate models (Lavoie, Bourgault, et al., 2024). The black line and the numerical value display the 50th percentile of the model ensemble for the chosen emissions scenario. The shaded pink region is representative of the uncertainty window between the 10th and 90th percentiles.

A single emissions scenario is presented in this graphic, to more effectively communicate relevant information and reduce information overload. More scenarios were provided in accompanying documentation for users that wanted additional technical information. The choice of scenario (see also section 10.3.4) was made in conjunction with the Cree Nation Government to ensure consistency with provincial regulations that lay out which scenario should be used in adaptation-planning decisions.

Finally, the graphic is concluded with a plain language statement, summarizing the change in the climate that the generations of today will experience in their lifetime. This approach uses climate services’ best practices, such as focusing on the change value and making the information more accessible and understandable to the audience using it.

To learn more about the Climate Change Adaptation and Environmental Emergency Preparedness workshop in Chisasibi, please visit the Map of Adaptation Actions.

10.3.1: Considering spatial domain, resolution, downscaling, and bias-correction

“Spatial domain” refers to an area of interest, or a region over which statistics of climate projections are calculated. A spatial domain can be a point location or a custom area or region, such as a watershed. Specific local climate characteristics, such as those typical of coastal zones or areas with complex topography, will not be discernable in averages calculated over larger regions that encompass variations in these characteristics. However, it is often at such specific locations within larger areas that risk analyses are needed. For this reason, the refinement of regions of interest in collaboration with users is an important consideration.

Global climate models (GCMs) simulate the fundamental equations of motion and transfer of heat, momentum, and other physical quantities around the globe. To do so, these numerical models simulate characteristics of and interactions between many physical, chemical, and biological systems that interact with the climate system. Computational limitations on performing these calculations for the entire globe mean that most GCMs model relatively coarse scales, typically in grids greater than 100 km x 100 km. This scale is suitable for syntheses of large regions, as contained in other sections of this report. Adaptation in practice, however, is inherently subregional or local, and a key activity of climate services is enhancing the spatial resolution of information available to users.

Fortunately, it is possible to produce higher resolution projections through a process called downscaling. Downscaling methods fall into two main categories. The first category, dynamical downscaling, uses GCM simulations to drive regional climate models (RCMs) over a limited area (Giorgi, 2019). The second category uses statistical downscaling methods that involve combining GCM projections with higher-resolution historical spatial information (Maraun & Widmann, 2018). Climate models contain systematic biases (Chapter 3, Box 3.3) that must be corrected before they can be used to calculate climate indicators or serve as inputs to subsequent modelling. Statistical downscaling methods typically include a bias correction step, although bias correction can also be carried out as a final post-processing step, and in some cases with further increases in resolution (Sobie & Murdock, 2017).

It is important for climate service providers to understand and explain the advantages and disadvantages of different downscaling and bias adjustment methods, as well as the additional uncertainty associated with them. Some of the main benefits and limitations of these approaches are shown in Table 10.2. Note that as computational resources and downscaling methods improve, the resolutions of available projections may increase relative to the resolutions reflected in this table at the time of publication.

Table 10.2: Comparison of typical resolutions, output, and main limitations of global climate models, dynamical downscaling from regional climate models, statistical downscaling, and high-resolution bias correction

Downscaling and bias correction can better represent topographic features, which is particularly important for some variables, especially indicators that count the number of events above fixed thresholds and extreme events. For these reasons, it is important to consider the different strengths and weaknesses of methods as described in Table 10.2 to match data type to intended use. However, as noted in the Ouranos Guidebook on Climate Scenarios (Charron, 2016), there is a common belief that finer resolution data are always more useful or accurate. This can lead to a preference for RCM or statistically downscaled data over GCM outputs. However, higher resolution does not guarantee better performance for all variables or more useful information for decision-makers. Accuracy and resolution (precision) are not the same. The goal is to improve accuracy. Higher resolution can, however, make results more relatable, which can assist local adaptation planning (Charron, 2016).

Simulating extreme events on local scales remains a considerable challenge because many localized extremes are controlled by physical processes that are unresolved or only partially resolved in climate models designed for large-area simulations (Chapter 8, Plain language summary). Spatial resolution is inherently connected to extremes because the values produced by a model correspond to average conditions within each grid cell, whereas observed extremes at stations or where humans live take place at specific points. Model resolution can limit the direct representation of topography and other local phenomena that may contribute to extremes. Also, for the most intense extremes, it is possible that they do not arise in the chosen simulations by random chance, since these events are, by definition, very rare.

Finally, it should also be noted that most observational data series are relatively short, and therefore not an adequate statistical representation of the past climate. This can affect statistical downscaling and bias correction, as these observations are used to adjust climate projections.

10.3.2: Choosing relevant climate information

While access is improving, any search for information on future climate must begin by identifying what is required, and for what purpose. For example, is the goal to raise awareness among decision-makers, conduct a risk assessment, or implement adaptation measures? Are specific variables, indicators, hazards, data formats, or regions necessary, or could compromises be made to accommodate use of information that is more readily available?

As described in section 10.4, users tend to know what hazard they are interested in, but not necessarily which specific climate indicators would be most relevant to use. Climate service providers play a role in helping users choose and in some cases define new indicators. For example, Ogden et al. (2005) defined a climate indicator relevant to blacklegged tick survival that relied on the number of annual cumulative degree days above 0°C. They then validated the indicator through various field studies (Gabriele-Rivet et al., 2015; Leighton et al., 2012; Ripoche et al., 2022). The indicator is now a reference for mapping the future prevalence of blacklegged ticks in a changing Canadian climate, as documented by Ripoche et al. (2023) and described in a ClimateData.ca case study. It is not always possible to define and validate new indicators this way, but scientific literature, guidance (e.g., Cannon et al., 2020), local knowledge, analysis of meteorological data, and professional judgement are all sources for selecting, in collaboration with users, which climate indicators to use. 

Tailoring through the use of different tools to summarize and visualize climate data

One example of an effective tool to communicate projected change is spatial climate analogues. Spatial analogues are locations that are currently experiencing climate conditions similar to those projected in the future for a specified location. They can serve as a starting point for proposing adaptation measures. For example, instead of expressing projected changes for a city using numbers (e.g., changes in the number of hot days, warm nights, and cooling degree days), a list is provided of cities where these numbers are the present-day climate normals. In this way, abstract values of changes are translated into contemporary cases. Users can look to management practices at the analogous locations to gain insights into how to prepare for and adapt to the expected changes in the chosen climate indicators. For example, for the three indicators listed in brackets above, the projected average climate of Yellowknife from 2041 to 2070 under an intermediate emissions scenario (SSP2-4.5) is analogous to the recent past climate in Nanaimo (see the spatial analogues application on ClimateData.ca).

Tailoring global climate model projections to improve local relevance through downscaling

User needs can make the development of downscaling methods (section 10.3.1) a priority. For example, freezing rain can have a major impact on infrastructure, vegetation, and road and air transport. Improvements in the spatial and temporal resolution of RCMs have enabled a more realistic representation of the key processes leading to freezing rain events, which form over short periods of time and can vary over small distances. Moreover, because current GCMs do not directly simulate different types of precipitation (snow, rain, freezing rain, and ice pellets), diagnostic methods were developed to be able to distinguish between them within RCMs. Users need this type of information, and efforts over the last decade have been dedicated to the development and use of data on freezing rain from RCMs (Cannon et al., 2020; McCray et al., 2022; Ouranos, 2024; St-Pierre et al., 2019).

Tailoring data to the local context and co-producing the interpretation of results

Climate services have an important role to play in working with users to ensure that local context is considered in the interpretation of climate projections (see also Case Story 10.2). An example of the influence of local context can be seen by comparing regional climate impact assessment reports that were co-produced by a regional climate service provider (Pacific Climate Impacts Consortium) collaborating with each of three regional districts adjacent to each other: Metro Vancouver, Capital Regional District (Greater Victoria), and Cowichan Valley Regional District (Cowichan Valley Regional District, 2017; Metro Vancouver et al., 2016; PCIC, 2024).

Despite containing similar projected warming and changes to precipitation across the larger area, the three reports each had different interpretations of results. For example, the impacts of climate change on water supply in each region differ because of differences in watershed characteristics. Different interpretations also arose in other aspects, such as tourism, emergency preparedness, and seasonal energy demand, because the regional districts each had a different demography and governance structure. For Metro Vancouver, the work was internally driven and led by the water and sanitation department, which took on the role of engaging with other relevant departments. For the smaller Capital Regional District, the process was internal but fully cross-departmental and involved member municipal governments. In the case of the more rural Cowichan Valley Regional District, the project was community-driven and featured an advisory board that included Indigenous, regional, municipal, and community leaders.

In the case of Metro Vancouver, another illustration of the importance of co-production with users to ensure the relevance of results to their context comes from subsequent collaborations with climate service providers on specific sectors to meet their needs. For example, a full assessment of regional climate impacts was developed for the regional health authority that focused on human health impacts and buildings (Aubie Vines et al., 2018; Vancouver Coastal Health & Fraser Health, 2022), and custom-tailored indicators of precipitation extremes were developed for the agricultural sector (Li et al., 2018).

Case Story 10.2: Ecosystem services and shifting seasonal rounds: a Gitxsan perspective

This case story was written by Janna Wale, a Gitxsan climate researcher. Janna Wale is Gitxsan from the Gitanmaax First Nation and, on her mother's side, is Cree-Métis and mixed-European. She currently resides in Snuneymuxw Territory on what is now known as Vancouver Island B.C.

Recommended citation:

Wale, J. (2026). Ecosystem services and shifting seasonal rounds: a Gitxsan perspective [Case story 10.2]. In Canada’s Changing Climate Report 2026. (pp. xx–xx). Government of Canada. 

Indigenous communities hold deep relationships with their Lands and territories. These relationships include an understanding of seasonal change patterns that tie together social and ecological contexts. The Gitxsan calendar recognizes 13 moons (months) and 4 seasons. Each moon is named for natural events occurring during that moon and related Gitxsan activities. However, climate change is causing shifts to traditional seasonal rounds (Case Story 10.2 Figure 1).

Case Story 10.2 Figure 1: The traditional and present-day distorted Gitxsan seasonal cycle. a) Traditional Gitxsan seasonal cycle inclusive of seasonal activities. b) Present-day distorted Gitxsan seasonal cycle resulting from shifting climate and other factors. Adapted from: a) Main Johnson (1997); b) Wale and Parrott (2024).

As climate change causes shifts to traditional seasonal rounds, so too do the ecosystem services that sustain both human and ecological well-being. Ecosystem services such as nutrient cycling, biodiversity support, and carbon storage depend on timing. The freeze and thaw cycles, flowering periods, and animal migrations all shape how ecosystems function and support life. The disruptions to seasonal cues have already impacted the availability of traditional foods and medicines, and with that, cultural continuity and community health. These disruptions diminish the services ecosystems can provide, from carbon sequestration to wildfire resistance.

In Gitxsan territories, long-relied-upon indicators such as salmon runs, berry ripening, and moose migration have become less predictable. Community members have observed that “it’s almost like the plants are confused.” These disrupted patterns affect not only food security but also the ecological processes that underpin cultural practices, relationships, and responsibilities. When harvest seasons become inconsistent, so too does access to key ecosystem services such as food provisioning, habitat health, and water quality.

This is where Indigenous governance and climate services intersect. Tailored information, rooted in collaboration, ensures that climate knowledge is not only technically accurate, but meaningful and usable. In Gitxsan territory, relational governance frameworks already exist. The practice of monitoring and adapting to seasonal change is not new; it’s embedded in our seasonal round, within our cultures, and how we steward the Land.

Finally, action is an important piece of building resiliency, but we believe that acting on the assessment ought to be up to each community, as determined by their values, culture, and goals, in accordance with their own sovereignty and nationhood. It is at this stage that forward-looking climate projections may be used in partnership with Indigenous ways of knowing and being, to help communities protect and enhance ecosystem services in a time of uncertainty. By listening carefully and through observation, ceremony, data, and story, we can protect the ecosystem services that sustain us for generations to come.

10.3.3: Considering the timing of events and timescales of indicators

As mentioned in section 10.4.2, the timing of when hazards occur during the year can be very important. The timescale over which climate variables and indicators are defined also matters. For example, a forester interested in which tree species would be suitable for a given location in the future may be primarily interested in indicators derived from monthly or even seasonal data. A maple syrup producer might want to know the change in start and end dates of the frost season derived from daily data. A user installing a rainwater collection system that has a maximum capacity may need information about precipitation accumulations over durations shorter than a day (for example, at 15-minute, hourly, or 6-hourly intervals), as discussed in section 10.4.6 in relation to extreme precipitation and rainfall-related flood hazards. Similarly, an engineer modelling the energy use of a building designed for a future climate will need hourly temperature information. As is the case with spatial downscaling (section 10.3.1), numerical methods can, in some cases, be used to derive data that is more or less temporally resolved than climate model outputs (Gaur & Lacasse, 2022; Wells et al., 2020).

10.3.4: Evaluating emissions scenarios and identifying time horizons

When using climate projections, multiple emissions scenarios are normally considered to ensure that a range of possible impacts are assessed under different conditions that could occur in the future (see also Chapter 3, section 3.3.1). Depending on the given application, identifying the future time horizons over which changes must be assessed is key. Consideration can be given to factors such as the lifespan of infrastructure, the adaptability of a system, the type of measure to be implemented, and the availability of projections (see, for example, Case Story 10.3).

The time horizon of interest can help to inform the selection of emissions scenarios. If a project lifespan does not extend past 2040, then the emissions scenario may be of minimal consequence because the climate-related changes projected by that time are similar across scenarios (Chapter 3, section 3.2.1). If the project lifespan is long, the selection could be much more consequential, since climate projections diverge considerably between emissions pathways toward the end of the century.

Some applications also need to consider climate change beyond 2100. This is the case for land-use planning activities, such as forestry and ecosystem conservation, and infrastructure adaptation, such as maintenance or restoration of mining sites and coastal protection from storm surge. However, most climate simulations in the Coupled Model Intercomparison Project Phase 6 (CMIP6) archive stop at the end of the century, making it impossible to use them for robust regional-scale projections beyond 2100 (Easterling et al., 2024). Some Canadian climate service providers are working to develop post-2100 climate projections that will eventually be available on Canadian data portals, for example, Ouranos’ post-2100 mining sector project profile.

More information on different sources of uncertainty in climate projections and how these changes play out over different timescales is available in Chapter 3, section 3.3.3, and an example of how climate services describe emissions scenarios is available in a ClimateData.ca Learning Zone article about selecting emissions scenarios when using projections of future climate. Global warming levels are emerging as another way (complementary to emissions scenarios) to consider a range of future climate conditions. See Chapter 3, Box 3.1 for more information on assessing changes in climate at different global warming levels.

10.3.5: Exploring ranges of change (uncertainty)

Three major sources of uncertainty are present in climate projections: internal climate variability, model uncertainty, and emissions scenario uncertainty. These three sources of uncertainty are the topic of Chapter 3, section 3.3. Climate service providers also give guidance to users to ensure that the implications of each is well understood, such as the ClimateData.ca Learning Zone article on uncertainty.

Emissions scenario uncertainty can be treated separately from the other two sources when ensembles of climate projections driven by different scenarios are available. Currently, projections are generally presented by emissions scenario, or for individual global warming levels.

Internal climate variability refers to the natural fluctuations in the climate that occur without any change in natural climate forcing (such as volcanic eruptions) or in anthropogenic forcing (such as increases in greenhouse gas concentrations due to human activity). To ensure adequate representation of internal climate variability, climate service providers recommend that users consider an ensemble of climate projections, ideally from multiple models. In this way, the uncertainty from both internal climate variability and model uncertainty can be represented by percentiles that span most of the ensemble of projections. In certain cases, there may be reasons to use a subset of the available ensemble. For example, it can be computationally expensive to consider every available model when subsequent hydrological, ecological, or other modelling is carried out. In such cases, climate service providers will help users choose an appropriate number of models, while avoiding common pitfalls, such as placing too much weight on a model’s agreement with observations, which may have more to do with coincidental similarities in natural climate variability than with model skill (Mahony et al., 2022).

10.3.6: Differences in baseline periods

Throughout this report, there are differences in the baseline periods used to compare projected changes in climate, and in the periods over which past trends are calculated. For example, Chapter 2 uses 1961 to 1990 for observed changes in temperature and precipitation, Chapter 3 uses 1850 to 1900 (the pre-industrial period approximated in this report) for projected changes in temperature and precipitation, and Chapter 8 uses 1971 to 2000 and 1986 to 2016 for projected changes in some extremes. A single standardized baseline is not feasible. Choice of baseline reflects a mix of conventions, convenience, availability of data, and practical constraints (such as observation station density in Canada peaking during the period from 1971 to 2000). Without adjusting for differences in baselines, readers may interpret results as contradictory when they are in fact consistent.

For example, in Chapter 2, Figure 2.7 identifies 2010, 2023, and 2006 as the warmest years on record, at 3.05°C, 2.84°C, and 2.46°C, respectively, above the 1961–1990 baseline average temperature. A reader may want to express these temperatures relative to a different baseline to compare them to more recent climate conditions or to values from other sources with a different baseline. To enable the “translation” of temperatures to different baselines, we have created Table 10.3, which provides the observed differences in annual temperature across Canada between several periods. Using this table, we can compare the rows for 1961–1990 and 1991–2020. For Canada, the average temperature difference between the two baseline periods is 1.0°C. The warmest year (2010) was thus 3.05°C minus 1.0°C, or approximately 2.05°C above the more recent 1991–2020 baseline. Note that the ranking of warmest years remains unchanged.

The use of projections in climate services and adaptation often implicitly assumes that we are presently prepared for a particular past climate. However, depending on the specific use of projections, including the sector and jurisdiction, different past baseline periods may better represent the “current practice” on which to base projected changes. Shifting baseline periods forward over time when new data are available can result in the magnitude of the adaptation challenge being underestimated because of what is effectively a moving target. This is because the baseline, once considered “normal,” keeps changing as time goes on. Table 10.3 can be used to understand the magnitude of this effect over time. Note that some sequential periods can have less warming than preceding ones due to the influence of natural variability. Regions such as Quebec and northern Canada are warmer under their most recent baseline, 2015–2024, compared to 1971–2000 by a larger margin than other regions.

Table 10.3: Common baseline periods and differences in annual average temperature^{Footnote 2} compared to the 1971–2000 baseline for the main regions used in the report

See Chapter 2, Figure 2.2 for definitions of the regions. Note that throughout this report Canada’s North refers to the region defined by the political boundaries of the three territories, whereas Canada’s South refers to all other regions combined.

Note that while Table 10.3 gives a sense of how big the effect of using different baselines can be, these are large regions. Locations within these regions may differ considerably. Seasonal differences may also be more pronounced. Readers are encouraged to use the table as a starting point. For information on smaller regions, site locations, seasons, and other variables, it is important to seek out data to determine the magnitude of the effect of different baselines.

In Chapter 2, Box 2.4 Table 1 highlights the proportion of warming from the pre-industrial baseline period (1850–1900) that is driven by anthropogenic climate forcing. Disagreement on warming between historical periods in Box 2.4 Table 1 and Table 10.3 is expected because Table 1 provides the anthropogenically forced response, whereas Table 10.3 also includes the effects of natural climate variability that occurred between those periods in the region. In other words, Box 2.4 Table 1 is useful for understanding how regions have responded to anthropogenic climate forcing, whereas Table 10.3 is useful for comparing climate projections for the same region that have different baselines. Unfortunately, because of insufficient global observations for the period 1850–1900, this baseline is not available in Table 10.3 We can infer from the estimates in Box 2.4 Table 1 that warming would be around 2°C less if this projection was expressed relative to the most recent decade (2015–2024) because that is the amount of warming due to anthropogenic forcing between those two periods. Chapter 3 reports that by the late-century (2081–2100), Canada’s average temperature is projected to be 5°C warmer relative to the model-simulated 1850–1900 baseline (according to the intermediate emissions scenario of SSP2-4.5).

10.4: A hazard-based approach to navigating climate data

Canada’s climate has changed over the past century (see the synthesis in Chapter 2, section 2.2), and the impacts, losses, and damages associated with climate change are being felt across Canada and, in particular, in some critical sectors of the economy and sensitive ecosystems (Lulham et al., 2023). The costs of damages due to the impacts of climate change are increasing in Canada in numerous economic sectors, notably infrastructure and health (Clark et al., 2021, 2022; Ness et al., 2021; Sawyer et al., 2020). As a result, there is an increasing sense of urgency to better anticipate and prepare for the impacts of a changing climate, including both risks and opportunities. In Canada, the use of climate projections is progressing from a recommendation to a requirement.

Planning and preparing for climate risks is occurring at multiple decision-making levels. Canada’s National Adaptation Strategy (ECCC, 2023) outlines goals and targets to increase resilience across five interconnected systems, which can be summed up as follows: reducing the impacts of climate-related disasters, improving health and well-being, protecting and restoring nature and biodiversity, building and maintaining resilient infrastructure, and supporting the economy and workers (see also Chapter 1, Box 1.1). Formal adaptation strategies have been, and continue to be, developed by a range of governments and organizations.

At the heart of adaptation planning is understanding current and future risks due to a changing climate. The impacts of climate change pose different risks to different economic sectors and populations. To assess physical climate risks, it is often helpful to characterize them by climate hazard.

10.4.1: Understanding climate risks

The body of literature on risk is extensive and far reaching. International standards related to risk management, such as International Organization for Standardization 31000 (ISO, 2018), have been in place for many decades. The same is true for guidebooks and frameworks.

Climate risks describe the potential for adverse consequences from climate change. Conceptually, risks are typically broken down into three components (Figure 10.3). First, to characterize how climate risks will evolve, it is necessary to understand climate hazards and how the changing climate will affect them. Second, risks occur if, and only if, assets or systems are both exposed to hazards and vulnerable to those hazards.

Figure take-away: Climate risks are generated by the interactions between climate hazards, and the vulnerability and exposure of natural and human systems to these hazards.

Figure 10.3: Conceptual framework for understanding climate risks. Risks from climate-related impacts are due to the interaction of climate-related hazards (including hazardous events and trends) with the vulnerability and exposure of human and natural systems. Changes in both the climate system (left) and socio-economic processes, including adaptation and mitigation (right), are drivers of hazards, exposure, and vulnerability. While risk is typically defined in such a way as to include negative impacts only, opportunities may also arise from climate change. Note that there are several variants of this graphic, including more recent ones. This version best fits the concepts here. To learn more about regional climate risk assessment in general, see Chapter 12 of the Working Group I contribution to the Intergovernmental Panel on Climate Change’s (IPCC’s) Sixth Assessment Report (Ranasinghe et al., 2021), and for infrastructure risk assessments in Canada, see the PIEVC meta-analysis and case studies (MacMillan et al., 2024b, 2024a). Source: Figure SPM.1 of the Working Group II Summary for Policymakers of the IPCC’s Fifth Assessment Report (IPCC, 2014).

The term “hazards” is used in many contexts. With regard to climate, it can refer to the information about current and future climate conditions that have the potential to drive adverse climate-related impacts, as reflected in Figure 10.3. The United Nations Office for Disaster Risk Reduction defines a hazard as “a process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation” (UNDRR, 2016). Common to both definitions is the concept of a hazard as something with the potential to cause negative consequences.

Case Story 10.3: Mâmawi Nistam: Resilience Through Seasons, a climate risk and vulnerability report by the Otipemisiwak Métis Government, of the Métis Nation within Alberta

Written by Jennifer Pylypiw and Ali Greenslade, on behalf of the Environment and Climate Change Department of the Otipemisiwak Métis Government, part of the Métis Nation within Alberta. Jennifer is Métis-Settler on her mother’s side and Ukrainian on her father’s side. She is proud to carry the teachings from all her ancestors with her as she works to centre Indigenous ways of being and knowing in all climate conversations. Ali is Jenn’s right hand, a settler with mixed European ancestry who grew up in Alberta, is educated in climate action leadership and continuously strives to be an ally and friend of the Métis Nation.

Recommended citation:

Pylypiw, J. and Greenslade, A. (2026). Mâmawi Nistam: Resilience Through Seasons, a climate risk and vulnerability report by the Otipemisiwak Métis Government, of the Métis Nation within Alberta [Case Story 10.3]. In Canada’s Changing Climate Report 2026. (pp. xx–xx). Government of Canada. 

As we find ourselves living through a climate crisis, there has never been a time more relevant than now to try and make sense of the climate risks we face and determine actions (sometimes called climate change adaptation) we can take to ensure a good way of living.

Usually, climate change adaptation planning begins by completing a climate change risk assessment. However, these assessments typically focus solely on impacts to the built environment, centring an understanding of climate change hazards on what the impact will be on infrastructure such as bridges, buildings, roads, and power lines. This is a limited way of thinking and ignores the fact that infrastructure does not exist without the humans and animals that utilize it.

As we began adaptation planning for our Nation, we asked ourselves, what if we think about the humans inside the buildings? What if we think about the animals migrating under the power lines and the fish in the river beneath the bridge? Because what is the value of a building if we have no people to occupy it? What is the value of a bridge if there are no birds and fish dancing below?

We completed a climate risk assessment in a different way to better understand how to reduce risk and build resilience of our inter-connected kin, the over 72,000 Métis people across Alberta and the land they belong to. Our report is titled Mâmawi Nistam (Otipemisiwak Métis Government & The Resilience Institute, 2025), which translates to “together first.” The name gifted to these learnings pays homage to the Métis people, who are descendants of First Nations grandmothers and European grandfathers, whose ancestors walk with us today.

The main intention of this assessment was to do things differently. We did this by bringing together Métis Knowledge and experience with western climate data, therefore centring these connections between humans and nature within the assessment.

We gathered information and stories from Métis people in various ways, ultimately incorporating over 3600 Métis voices in our report through primary engagement and a desktop review process.

We listened to Elders.

We worked with Climalogik Inc. to generate projections of climate hazards meaningful to our people and lands in Alberta (such as flooding, wildfires, and drought) over the short, medium, and long term, for two different emissions scenarios (RCP4.5 and RCP8.5). We came together and ate bannock and talked about community gardens, about how to respectfully harvest medicines, and dreamt of putting good fire back on the land and bringing the bison home.

By coming together in a good way, we build trust among ourselves and our community. We shared climate projections and climate change information in a safe space where questions could be asked, and fears could be shared (Case Story 10.3 Figure 1). Those who gathered with us believed the climate change information we presented because they believe in their connection with their Nation.

We layered stories onto the projections, allowing the projected future and hazards to exist not only as a risk to infrastructure, but also to a way of being. We gathered the voices of Elders, youth, Kokums, harvesters, two-spirit people, and our ancestors, and brought voices to the plants and animals, the non-human kin, and the land, in our rubrics and in our hearts. We focused on the legacy of resilience of the Métis and how doing things better to address climate impacts can also help people reconnect with the land and with each other in a good way.

Youth shared that they have hopes outside of being climate leaders of tomorrow. We need to step up today, so they have less weight to carry.

We chose to come together and no longer be left out of risk assessments and studies. When we are together, our voices are stronger. The only way we can build real climate resilience is by prioritizing our understanding of how climate change risks will impact the connections between all things, human and non-human, built and natural environments.

Gratitude to the Elders who grounded our journey, to the Métis Citizens who are steadfast in their dreams of a better future for their children, to our partners at The Resilience Institute who brought this project vision to life, and to the Indigenous Climate Leadership team at Crown-Indigenous Relations and Northern Affairs Canada, who empowered us to do this project in our way.

Case Story 10.3 Figure 1: This figure shares an example of the Métis Nation within Alberta and The Resilience Institute’s approach to categorizing climate risks and impacts under Fire, one of the four classical elements: Fire, Water, Air, and Land. Similar figures for Water, Air, and Land are shared in Mâmawi Nistam. These elements are woven with the Métis infinity symbol, which represents the coming together of two ancestral lines (Indigenous and European) and symbolizes both the immortality of the Métis Nation and the four seasons, to visually highlight climate impacts in a meaningful way. Source: Otipemisiwak Métis Government and The Resilience Institute (2025).

10.4.2: Understanding climate hazards

The term “hazards” is used in many contexts. With regard to climate, it can refer to the information about current and future climate conditions that have the potential to drive adverse climate-related impacts, as reflected in Figure 10.3. The United Nations Office for Disaster Risk Reduction defines a hazard as “a process, phenomenon or human activity that may cause loss of life, injury or other health impacts, property damage, social and economic disruption or environmental degradation” (UNDRR, 2016). Common to both definitions is the concept of a hazard as something with the potential to cause negative consequences.

An emerging practice among climate service providers is to use hazards to categorize climate data in a way that connects to users’ concerns. While some climate variables and indicators will be directly relevant to certain hazards, others may not fully represent a hazard of concern but will still serve as reasonable indicators for analysis. In the latter cases, multiple indicators may be needed to get a more complete picture of changes to the hazard. Previously, climate data was generally presented by climate variables alone.

The Global Climate Observing System and the World Meteorological Organization have identified essential climate variables that characterize the Earth’s climate, such as surface temperature and precipitation (GCOS, 2025). With essential climate variables as the starting point for categorization, several indicators can be derived from them. For example, the surface temperature category includes indicators such as the first fall frost, number of days above 30°C, and coldest night. The Interactive Climate Atlas, the Copernicus Interactive Climate Atlas present climate indicators derived from essential climate variables. The IPCC refers to these indicators as climatic impact-drivers and defines them as “physical climate system conditions (e.g., means, events, extremes) that affect an element of society or ecosystems” (Ranasinghe et al., 2021). This variable-centric approach can be difficult to navigate for users who are not interested in all indicators. Categorizing climate data in this way also pre-supposes that users have a certain amount of knowledge about both the climate and the climate drivers of a given hazard.

International organizations have initiated efforts to translate climate data into more useful information by more clearly linking hazards to impacts through a sector-based lens (Tebaldi et al., 2023). While decision-makers concerned about hazards and risks related to climate change are often aware that climate data is available, they may not know how to find and use specific climate variables for different purposes. A hazard-based approach aims to address this gap so that communities and practitioners can best access and use climate data. Organizing climate data by hazard better matches how climate information is considered in areas such as disaster risk reduction and emergency management, as exemplified by the United Nations Disaster Risk Reduction and International Science Council Hazard Information Profiles (UNDRR & ISC, 2025). It can also help frame climate information in ways that better resonate with a wider audience, including decision-makers. Work in Canada is starting to incorporate a more hazard-centric approach, including through the development of hazard and impact maps. For example, in the Health of Canadians in a Changing Climate report, Chapter 3: Natural Hazards takes a sector-based and hazard-based approach to climate data in assessing risks (Gosselin et al., 2022), and in the National Issues Report, Chapter 7: Sector Impacts and Adaptation takes a sectoral-impact approach to climate data (Lemmen et al., 2021). Public Safety Canada’s National Risk Profile also makes use of a broader hazard-based approach while including some information on future climate (Public Safety Canada, 2023).

As noted in Chapter 8, climate change affects hazards and extremes in important ways that can change their frequency, intensity, duration, and timing. In the descriptions of projected changes in the sections on hazards that follow, we generally describe changes occurring to one or more of these four dimensions of change of hazards:

• Frequency, which refers to the number of events over a given period of time. Changes in frequency occur when events happen more or less often, or when the probability, recurrence interval, return period,^{Footnote 3} or wait time of events changes.
• Intensity, which refers to the magnitude of events. Changes in intensity occur when events are marked by higher highs or lower lows, or when the return level or severity of events changes.
• Duration, which refers to how long events last. Changes in duration occur when events or seasons last for a longer or shorter amount of time.
• Timing, which refers to when events happen. Changes in timing occur when events start or end at a different time of year than they used to.

It is also important to note that hazards not only occur as single events, but as compound events, which should also be considered (Zscheischler et al., 2018). Compound events are extreme events that happen simultaneously or in a sequence, as well as cumulatively over time (Chapter 8, section 8.7), which are thus far not well represented in risk assessments.

10.4.3: Guide to the climate hazard sections

In the sections that follow, we aim to summarize information that can be found throughout this report to help readers find relevant information by climate hazard of interest. We focus on 12 climate hazard categories and related climate indicators. These are intended as a starting point to explore the information in this report but are not meant to be exhaustive or prescriptive.

Each of the next sections deals with a separate hazard category and includes details on the following:

• Related hazards, which refer to other sections of this report (the 2026 edition of Canada’s Changing Climate Report, or CCCR2026) that contain information on hazards that may be connected.
• CCCR2026 sections and key messages, which reproduce key messages, including calibrated uncertainty language^{Footnote 4} from other chapters in this report where the hazards are discussed. With a focus on projected changes, the most relevant key messages are placed at the top of the list, while others are listed in ascending section order. In some cases, excerpts from key messages have been reproduced. The full versions can be found in their respective sections and a list of all Key Messages is available in an Annex to the Report Summary.
• Relevant key words, which consist of a variety of terms used to refer to hazards informally across different professions and sectors, as well as closely related or relevant terms that can be helpful to users interested in delving into a given hazard.
• Direction of projected change and example indicators, describes changes to one or more of the dimensions of change listed in section 10.4.2. In most cases, the projected changes and respective climate indicators are assessed in this report, and the relevant sections are noted in square brackets.
• Additional details on how to consider information for this hazard, which includes a discussion of miscellaneous topics, such as how climate projections for indicators related to the hazard have been used for adaptation, as well as context, caveats, or limitations relevant to the interpretation of data related to the hazard. Examples of sectors, industries, or communities affected by each hazard are meant to be illustrative rather than comprehensive.

For readers looking for information on other commonly sought topics that are relevant to multiple chapters, such as methodologies for climate assessment, climate variables, or cross-cutting themes addressed in this report, it may be helpful to refer to the visual guides to cross-chapter linkages at the beginning of each chapter, and to the summary table on where to find information on major cross-cutting themes in the Chapter 1, Annex: Index of cross-cutting topics in the report.

Climate modelling and information are dynamic because research continually updates our understanding of climate systems, and computing capabilities continually improve. The following sections on hazard categories are thus a snapshot of the climate data and information contained in this report and available at the time of publication.

It is important to keep in mind that climate hazards are influenced by various underlying mechanisms and drivers. Different components of climate hazards may be affected by climate change in complex ways, and the causes of observed changes are discussed throughout the chapters of this report. Some climate-related hazards interact with factors not related to climate. For example, permafrost conditions are dependent on geophysical characteristics, and wildfires are influenced by both fire weather and other factors related to fuel and ignition (Chapter 9, section 9.5.2.7 and Case Story 9.1). Additionally, as noted in Chapter 4, section 4.7.1, changes in severe weather indicators that describe conditions favouring the occurrence of severe weather events do not necessarily imply changes in those severe weather events, and the ability of those indicators to describe severe weather conditions can vary regionally and seasonally.

10.4.4: Extreme heat and heatwaves

Related hazards

• Droughts (4.10); and wildfires (10. 4.11).
• See Chapter 4: Large-scale atmosphere-ocean processes affecting climate for potential influences on extreme heat and heatwaves.

CCCR2026 sections and key messages

• 8.2: Temperature extremes
  • Key message 8.2 excerpt: Increases in the intensity and frequency of hot extremes […] are projected for all regions of Canada, with changes becoming larger as global mean temperature increases (very high confidence).
• 8.7.4: Human-perceived heat stress
  • Key message 8.14: The intensity and frequency of human-perceived heat stress—which results from the combined effects of high temperatures and humidity—have increased in Canada as a whole (high confidence). Human-perceived heat stress is projected to increase in Canada, driven mainly by increases in air temperature (high confidence).
• 2.2: Synthesis of past changes
  • Key message 2.1: Canada is warming in all regions and seasons. Canada warmed by 2.0°C during the 1948–2023 period (very likely 0.9–3.1°C), with northern regions experiencing warming of 2.6°C (very likely 1.4–4.1°C) and generally more warming occurring in winter than in summer.
  • Key message 2.4 excerpt: The observed occurrence in summer of longer growing seasons, increased building cooling requirements, and higher hot temperature extremes are all consistent with a warming climate […]. Fire seasons have become longer (high confidence), and the area burned in wildfires has increased (medium confidence).
• 3.4: Temperature
  • Key message 3.6 excerpt: Average surface air temperature is projected to increase across Canada in all seasons (very high confidence).
  • Key message 3.7: Under a current-policies scenario, annual average temperature is projected to increase by 5.0°C (3.8–6.6°C) relative to 1850–1900 by 2081–2100 (high confidence), with larger increases in northern Canada in winter that could exceed 10°C in some regions (medium confidence). Under a no-policies scenario, average warming for Canada is projected to reach 6.9°C (5.2–8.9°C) by the same period (high confidence). Under a net-zero scenario, annual average temperature for Canada is projected to stabilize after 2050, reaching 3.5°C (2.3–4.8°C) above 1850–1900 levels in 2081–2100 (high confidence).

Relevant key words

Extreme temperatures, extreme warm temperatures, extreme heat, hot extremes, heatwaves, heat waves, tropical nights, humidex, heat stress, hottest day, heat dome

Table 10.4: Projected directional changes and example indicators for extreme heat and heatwaves

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Extreme heat is already impacting and will continue to impact sectors such as agriculture, ecosystems, and human health in Canada (Lulham et al., 2023). Many indicators are available for describing how extreme heat events will change in frequency, intensity, duration, and timing. Threshold-based indicators are useful to consider because they translate climate variables such as maximum temperature into values that are more concrete to decision-makers. For example, indicators like hot days, defined as the number of days where maximum temperatures reach above 30°C, may be more helpful to some users than maximum temperature. Hot days can provide information that relates more directly to the need for cooling solutions, particularly in locations with few hot days in the past. Thresholds can be used to quantify if and how frequently critical levels will be crossed in the future. This helps planners understand if a once-rare event will become common enough to warrant infrastructure changes. In areas where hot days were previously rare, such as communities in coastal and northern Canada, even a modest increase in hot days could have major impacts, given limited past exposure, little previous experience in managing extreme heat events, and an overall lower resilience to extreme heat.

Projections of extreme heat are used in the public health and human health sectors. For example, hospitals need to be designed to maintain cooling for optimal health. In a future climate where extreme heat is more common, the cooling infrastructure of hospitals will need to be able to withstand higher loads, and it is possible heatwaves will put stress on the health care system if there are spikes in cases of heat-related illness during these extreme heat events (Aubie Vines et al., 2018; Canadian Standards Association, 2024b; Vancouver Coastal Health & Fraser Health, 2022).

10.4.5: Extreme cold, loss of cold, and seasonally frozen ground

Related hazards

• Permafrost warming and thaw-driven landscape changes, and terrestrial ice loss (10.4.12).
• See Chapter 4: Large-scale atmosphere-ocean processes affecting climate for potential influences on extreme cold, loss of cold, and seasonally frozen ground.

CCCR2026 sections and key messages

• 8.2: Temperature extremes
  • Key message 8.2 excerpt: […] decreases in the intensity and frequency of cold extremes are projected for all regions of Canada, with changes becoming larger as global mean temperature increases (very high confidence).
• 2.2: Synthesis of past changes
  • Key message 2.1: Canada is warming in all regions and seasons. Canada warmed by 2.0°C during the 1948–2023 period (very likely 0.9–3.1°C), with northern regions experiencing warming of 2.6°C (very likely 1.4–4.1°C) and generally more warming occurring in winter than in summer.
  • Key message 2.4 excerpt: […] consistent with a warming climate […] is the occurrence in winter of reduced building heating requirements and less severe cold temperature extremes. […] The warming climate has also led to substantial changes in the water cycle and cryosphere (very high confidence), as indicated by increased annual precipitation and intensified precipitation extremes, snow cover and glacier mass reductions, earlier spring streamflow in rivers, decreasing lake and river ice, and thawing permafrost.
• 3.4: Temperature
  • Key message 3.6 excerpt: Average surface air temperature is projected to increase across Canada in all seasons (very high confidence).
  • Key message 3.7: Under a current-policies scenario, annual average temperature is projected to increase by 5.0°C (3.8–6.6°C) relative to 1850–1900 by 2081–2100 (high confidence), with larger increases in northern Canada in winter that could exceed 10°C in some regions (medium confidence). Under a no-policies scenario, average warming for Canada is projected to reach 6.9°C (5.2–8.9°C) by the same period (high confidence). Under a net-zero scenario, annual average temperature for Canada is projected to stabilize after 2050, reaching 3.5°C (2.3–4.8°C) above 1850–1900 levels in 2081–2100 (high confidence).
• 6.6: Seasonally frozen ground
  • Key message 6.12: The annual number of days with seasonally frozen ground, and the maximum annual depth of seasonally frozen ground outside permafrost areas, are expected to decrease across Canada until mid-century before stabilizing under a low emissions scenario (high confidence). In contrast, these indicators of seasonally frozen ground are expected to continue declining until the end of century and beyond under emissions scenarios with higher levels of carbon emissions and increasing global temperatures (high confidence).
• 4.1: Arctic amplification
  • 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).

Relevant key words

• Cold extremes, extreme cold spells, cold spells, cold wave, cold event, loss of cold, winter mean temperatures, winter average temperatures, winter minimum temperatures, winter warming, mid-winter warm spells
• Seasonally frozen ground (SFG), frozen soil

Table 10.5: Projected directional changes and example indicators for extreme cold, loss of cold, and seasonally frozen ground

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

The drivers of extreme cold include factors such as the polar vortex, jet streams, and Arctic warming (Chapter 4, Box 4.3 and Box 4.4). A decrease in extreme cold is often considered an opportunity, since many sectors may benefit from shorter and milder winters. However, in some cases it can be a hazard. In sectors such as forestry, a lack of extreme cold can result in increased forest pests and disease infestations. A prominent example is that warmer winter conditions since the 1990s led to a mountain pine beetle epidemic, which destroyed over 18 million hectares of forest in British Columbia (F. Warren et al., 2021). The beetle’s range is expected to keep expanding into Canada’s northern and eastern pine forests as temperatures continue to warm (F. Warren et al., 2021). Changing patterns of forest tent caterpillar outbreaks in Canada have also been recorded throughout boreal forests in Canada, affecting forest health and management (Cooke & Roland, 2018). In the past, deep-winter cold spells have limited the outbreaks of these and other pests because winter temperatures are a key factor affecting egg survival and influencing population dynamics in northern climates (Cooke & Roland, 2003). Understanding how the indicators related to this hazard will evolve can therefore help forest managers plan tree planting and seed transfer programs (McKenney et al., 2009; O’Neill et al., 2017; Thomson et al., 2010).

Changing environments in northern Canada are already impacting and will continue to impact Indigenous communities and traditional activities in numerous ways (see, for example, Case Stories 6.1 and 8.1). For example, people in Inuit Nunangat (Inuit homelands) have a close relationship with and reliance on the land for sustenance, livelihoods, and culture (Case Story 2.1) (Reed et al., 2024). Inuit-led interview-based research found that connection to these elements is central to Inuit mental and physical health and well-being, and to traditional activities such as hunting and fishing (Middleton et al., 2020). As one Elder from an Inuit community in Nunatsiavut shared, “we’re winter people … we’re people of the snow; we want the snow, we want the ice.” The authors also note that in the past, winter was the season of greatest mobility, when sea ice formation and snow cover made it possible for people to access land farther from the communities. However, as extreme cold temperatures rise and winters warm, the community faces changes that affect traditional activities, such as more variability in the safe travel season, changes in access to country food, and changes in food storage options (Hancock et al., 2022). These changes also affect community well-being (Reed et al., 2024). Climate services can help communities adapt to and prepare for these current and future changes by translating climate data, such as icing season or first fall frost, into more actionable and relatable indicators, such as safe snowmobiling or hunting season indicators. 

10.4.6: Extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods

Related hazards

• Non-pluvial (rain-on-snow, snowmelt, and ice jam) floods (4.9); extratropical storms and hurricanes (10.4.7); thunderstorms (10.4.8); and sea-level change, storm surge, and coastal flooding (10.4.13).
• See Chapter 4: Large-scale atmosphere-ocean processes affecting climate for potential influences on extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods.

CCCR2026 sections and key messages

• 8.3: Precipitation extremes
  • 8.3.1: One-day and five-day total precipitation extremes
    • Key message 8.4: Increases in the frequency and intensity of one-day and five-day precipitation extremes are projected for all regions of Canada (high confidence), with changes becoming larger as global average temperature increases (high confidence).
  • 8.3.2: Short-duration rainfall extremes
    • Key message 8.6: The intensity and frequency of short-duration rainfall extremes in Canada are projected to increase in the future (high confidence), with the increases becoming larger as global average temperature increases (high confidence). The projected rate of intensification of short-duration rainfall extremes for Canada as a whole is consistent with the rate of increase in atmospheric moisture along with average warming in Canada (medium confidence).
  • 8.3.3: One-day snowfall extremes
    • Key message 8.7 excerpt: Under future warming, these heavy snowfall amounts are projected to increase across much of northern and eastern Canada (medium confidence). In southwestern Canada, heavy one-day snowfall amounts have decreased since the mid-20th century (medium confidence), while no clear pattern has been observed in southeastern Canada. There is low confidence in the magnitude and direction of future changes in extreme snowfall events for southern Canada.
  • 8.3.4: Freezing rain extremes
    • Key message 8.8 excerpt: The frequency of extreme freezing rain is projected to increase in most regions of Canada (low confidence), while some decreases or no significant changes are projected in parts of southern Ontario, the Atlantic provinces, and coastal regions of Hudson Bay (low confidence).
  • 8.3.5: Hail
    • Key message 8.9 excerpt: Projections indicate a potential increase in the frequency of severe hail across parts of western Canada (very low confidence), but this assessment is based on limited evidence and involves substantial modelling challenges.
  • 2.2: Synthesis of past changes
    • Key message 2.4 excerpt: The warming climate has also led to substantial changes in the water cycle and cryosphere (very high confidence), as indicated by increased annual precipitation and intensified precipitation extremes, snow cover and glacier mass reductions, earlier spring streamflow in rivers, decreasing lake and river ice, and thawing permafrost.
  • 2.5: Past precipitation changes
    • Key message 2.9: Annual total precipitation has increased in Canada since 1949, with larger percentage increases in northern Canada (very high confidence). Annual total precipitation has increased much faster in Canada than for the global land area as a whole over a similar period (very high confidence).
    • Key message 2.12: The annual snowfall amount and annual number of days with snowfall are estimated to have decreased at most stations in Canada’s South but increased at most stations in Canada’s North (medium confidence). Both the proportion of precipitation days with snow and the proportion of precipitation amount falling as snow have decreased across most of Canada (medium confidence).
  • 3.5: Precipitation
    • Key message 3.8 excerpt: Winter and annual average precipitation are expected to increase everywhere in Canada, especially in northern Canada and around Hudson Bay (high confidence). Summer average precipitation is expected to increase in northern Canada (medium confidence) and decrease in parts of southern Canada (low confidence).
    • Key message 3.9: Annual snowfall is projected to increase in northern Canada, but it is projected to decrease in southernmost Canada, particularly in coastal regions (medium confidence). This pattern reflects an increase in precipitation everywhere in Canada but warming causing less of it to fall as snow in southernmost regions. Under current-policies and no-policies scenarios, freezing rain is projected to become more frequent over much of Canada, but less frequent over Atlantic Canada and southern Ontario (medium confidence), driven by changes in the simultaneous occurrence of freezing conditions at the surface and warmer air aloft.
  • 5.2: Atmospheric component of the water cycle
    • Key message 5.1: The atmospheric component of Canada’s water cycle has been altered and will continue to be altered by human influence (medium confidence). Total annual precipitation and heavy precipitation events have increased and are projected to continue to increase (high confidence). Warm-season evaporation has increased and is projected to continue to increase across much of Canada, including over open water because of longer ice-free periods (low confidence). The 0°C air temperature isotherm (constant temperature line) is projected to move farther north and to higher elevations across Canada (medium confidence), which is expected to result in changes in the proportion of rainfall versus snowfall.
  • 5.7: Floods
    • Key message 5.10: Projected increases in extreme precipitation are expected to lead to more frequent and intense flash flooding across Canada (high confidence). Warmer temperatures are expected to lead to the earlier occurrence of snowmelt, rain-on-snow events, and ice jam breakups, resulting in earlier streamflow-related spring floods (medium confidence). However, their future frequency remains uncertain because of the interactions among rising temperatures, reduced snow cover, and the complex dynamics of ice jam–related and snowmelt-related floods. 

Relevant key words

• Extreme precipitation, heavy precipitation, intense precipitation, short-duration rainfall extremes, Intensity-Duration-Frequency (IDF), persistent precipitation, extreme rainfall events, hailstorm, hail, snow, snowfall, 0°C air temperature isotherm, constant temperature line, precipitation-triggered landslides
• Rainfall-dominated flood, rainfall induced, pluvial flood, urban flooding, flash flood

Table 10.6: Projected directional changes and example indicators for extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

The influence of climate change on the water cycle is already impacting Canadian food, energy and natural resource sectors, communities, and the natural environment (Carlson et al., 2021). This is reflected in the large number of related hazards. For heavy precipitation or fluvial flooding in particular, Intensity Duration Frequency (IDF) curves are widely used by practitioners. They are useful, for example, in stormwater management, urban planning, and flood risk assessment. IDF curves have typically been updated periodically as new observations have become available. In 2019, Environment and Climate Change Canada released guidance that encouraged users to apply a temperature-scaling methodology (Chapter 8, Box 8.3) to IDF curves to develop future shifted IDF curves that take climate change into account. This has become a standard practice (Canadian Standards Association, 2025; Martel et al., 2021), with municipalities and other organizations incorporating this methodology into their work, such as Yang et al. (2024). Using these future shifted IDF curves, Yang et al. (2024) noted that peak flow rate and flooding duration are both projected to increase and that current stormwater systems could be overloaded in the future. The ClimateData.ca Learning Zone  describes the use of IDF data in the context of a changing climate.

10.4.7: Extratropical storms and hurricanes

Related hazards

Extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods (10.4.6); thunderstorms (10.4.8); non-pluvial (rain-on-snow, snowmelt, and ice jam) floods (10.4.9); sea-level change, storm surge, and coastal flooding (10.4.13); and strong winds (10.4.15).

CCCR2026 sections and key messages

• 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).
• 4.6: North Atlantic hurricanes
  • 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.  
• 4.3: 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).
• 8.4: Wind extremes
  • Key message 8.10: There isinsufficient evidence to assess historical changes in extreme winds in Canada due to limited station coverage and representativeness, significant uncertainties in reanalysis products, and the paucity of studies examining trends in wind extremes. There is very low confidence in the direction and magnitude of future changes in extreme winds due to the limited number of studies and the substantial uncertainty related to model projections of wind-related phenomena.

• 8.7: Compound events
  • 8.7.2: Compound coastal flooding
    • Key message 8.12: Compound coastal flooding arises from jointly occurring climate conditions, such as heavy rain during episodes of extreme water levels. Such co-occurring drivers have increased in frequency and intensity in some parts of Canada, with evidence primarily from Atlantic locations (low confidence), and are projected to become more frequent and intense at locations along the Atlantic, Pacific and Western Arctic coastlines (medium confidence). These projected increases are mostly due to rising sea levels and increases in the frequency and intensity of extreme precipitation events (medium confidence).
  • 8.7.3: Compound wind and rainfall
    • Key message 8.13: There is insufficient evidence to assess historical changes in compound wind and rainfall events in Canada, due to limited studies focusing on observed trends. Compound extreme wind and rainfall events are projected to increase (medium confidence), driven mainly by the greater frequency of future extreme rainfall, but with very low confidence in the regional pattern and magnitude of changes.

Relevant key words

• Atmospheric blocks, extratropical cyclones (ETC), anticyclones, extratropical anticyclones, extratropical storms, blocking anticyclones, strong cyclones, explosive cyclones, bomb cyclones, post-tropical storms, post-tropical cyclones, post-tropical transitions, extratropical transitions
• North Atlantic hurricanes, hurricane tracks, tropical storms, Atlantic tropical storms, tropical cyclones, landfall, post-tropical storms, post-tropical cyclones, post-tropical transitions, extratropical transitions

Table 10.7: Projected directional changes and example indicators for extratropical storms and hurricanes

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Extratropical cyclones and hurricanes can stimulate displacement and migration, impact energy supply and distribution, and impair transportation networks (F. J. Warren & Lulham, 2021). They also impact ecosystems. For example, forest management practices in Nova Scotia consider the return frequency of numerous hazards, including cyclones and hurricanes. Like many regions in Canada, Nova Scotia is restoring its forests through the implementation of ecological forestry, a management practice where natural disturbance patterns are emulated to sustain natural forest structures, biodiversity, and functional processes (McLean et al., 2021). Climate change will alter disturbance regimes in the future (Taylor et al., 2020).

The impacts of cyclones and anticyclones are affected by their strength, propagation speed, and frequency, and particularly strong cyclones and anticyclones can bring extreme weather to Canada (Barlow et al., 2019; Grotjahn et al., 2016; Yu et al., 2022). In addition, rising sea surface temperatures and more evaporation at higher latitudes are expected to influence the track, size, and frequency of tropical cyclones (Knutson et al., 2020).

In Chapter 4, section 4.6.3 assesses tropical-cyclone and Atlantic hurricane frequency. While projections for the North Atlantic basin are uncertain, an increase is projected in the intensity of tropical cyclones and Atlantic hurricanes around the world. An increase in the proportion of Category 4 and 5 tropical cyclones and hurricanes is projected, with an accompanying increase in precipitation rates (medium confidence) and in wind speeds (low confidence).

10.4.8: Thunderstorms

Related hazards

Extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods (10.4.6); extratropical storms and hurricanes (10.4.7); non-pluvial (rain-on-snow, snowmelt, and ice jam) floods (10.4.9); and strong winds (10.4.15).

CCCR2026 sections and key messages

• 4.7: Large-scale environmental conditions favouring thunderstorms
  • 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.
• 8.4: Wind extremes
  • Key message 8.10: There isinsufficient evidence to assess historical changes in extreme winds in Canada due to limited station coverage and representativeness, significant uncertainties in reanalysis products, and the paucity of studies examining trends in wind extremes. There is very low confidence in the direction and magnitude of future changes in extreme winds due to the limited number of studies and the substantial uncertainty related to model projections of wind-related phenomena.

Relevant key words

Convective storms, convective storm environments, large-scale convective storms, large-scale environmental conditions favouring thunderstorms, convective available potential energy (CAPE), tornadoes, tornados, storms, storm winds, downbursts, microbursts, derechos

Table 10.8: Projected directional changes and example indicators for thunderstorms

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Thunderstorms, or convective storms, are complex atmospheric events often associated with additional climate-related hazards, such as lightning strikes, wind damage, tornadoes, hail, and flash flooding (NAV CANADA, n.d.). While there is great interest in these hazards and their impacts, little direct information is, as of yet, available from climate models (Chapter 4, sections 4.4 and 4.6). It is, however, possible to make use of information on conditions that favour their development and on proxies to assess their evolution over time. As noted in Chapter 4, section 4.7.1, severe weather proxies (indicators) are not the same as severe weather events. The correlation of these proxies to severe weather can vary regionally and seasonally (Tippett et al., 2019). In other words, changes in these proxies will not necessarily translate into changes in severe weather events (Chapter 4). However, these indicators make it possible to examine changes in the occurrence of large-scale conditions that favour the development of convective storms and severe weather. In this way, these indicators may be useful for examining future changes in severe-weather risk based on climate projections. Most climate models do not have adequate horizontal or vertical resolution to directly model weather systems on scales of tens to hundreds of kilometres, so more direct metrics are not possible.

The Regional Perspectives Report (Douglas & Pearson, 2022), published as part of the Canada in a Changing Climate: National Assessment Process, includes a case story on an adaptation strategy undertaken by Metrolinx. Metrolinx is a public transportation authority for the Greater Toronto Area. This case story highlights how engineers have incorporated climate indicators in their work, from designing more climate-resilient train tracks to adapting their operations for convective storms and other changes in the climate. Various aspects of this Metrolinx case study are also highlighted on ClimateData.ca in a written case study and as a podcast.

10.4.9: Non-pluvial (rain-on-snow, snowmelt, and ice jam) floods

Related hazards

• Extreme precipitation (heavy precipitation, freezing rain, hail, and extreme snowfall) and pluvial (rainfall-related) floods (4.6); extratropical storms and hurricanes (10.4.7); thunderstorms (10.4.8); and sea-level change, storm surge, and coastal flooding (10.3.13).
• See Chapter 6: Changes in the cryosphere for potential influences on non-pluvial (rain-on-snow, snowmelt, and ice jam) floods.

CCCR2026 sections and key messages

• 5.7: Floods
  • Key message 5.10: Projected increases in extreme precipitation are expected to lead to more frequent and intense flash flooding across Canada (high confidence). Warmer temperatures are expected to lead to the earlier occurrence of snowmelt, rain-on-snow events, and ice jam breakups, resulting in earlier streamflow-related spring floods (medium confidence). However, their future frequency remains uncertain because of the interactions among rising temperatures, reduced snow cover, and the complex dynamics of ice jam–related and snowmelt-related floods. 
• 2.5: Past precipitation changes
  • Key message 2.9: Annual total precipitation has increased in Canada since 1949, with larger percentage increases in northern Canada (very high confidence). Annual total precipitation has increased much faster in Canada than for the global land area as a whole over a similar period (very high confidence).
  • Key message 2.12: The annual snowfall amount and annual number of days with snowfall are estimated to have decreased at most stations in Canada’s South but increased at most stations in Canada’s North (medium confidence). Both the proportion of precipitation days with snow and the proportion of precipitation amount falling as snow have decreased across most of Canada (medium confidence).
• 3.5: Precipitation
  • Key message 3.8 excerpt: Winter and annual average precipitation are expected to increase everywhere in Canada, especially in northern Canada and around Hudson Bay (high confidence). Summer average precipitation is expected to increase in northern Canada (medium confidence) and decrease in parts of southern Canada (low confidence).
  • Key message 3.9 excerpt: Annual snowfall is projected to increase in northern Canada, but it is projected to decrease in southernmost Canada, particularly in coastal regions (medium confidence). This pattern reflects an increase in precipitation everywhere in Canada but warming causing less of it to fall as snow in southernmost regions.
• 5.2: Atmospheric component of the water cycle
  • Key message 5.1: The atmospheric component of Canada’s water cycle has been altered and will continue to be altered by human influence (medium confidence). Total annual precipitation and heavy precipitation events have increased and are projected to continue to increase (high confidence). Warm-season evaporation has increased and is projected to continue to increase across much of Canada, including over open water because of longer ice-free periods (low confidence). The 0°C air temperature isotherm (constant temperature line) is projected to move farther north and to higher elevations across Canada (medium confidence), which is expected to result in changes in the proportion of rainfall versus snowfall.
• 5.3: Streamflow magnitude and timing
  • Key message 5.2: The greatest changes in streamflow magnitude across Canada have occurred and are projected to continue to occur on a seasonal basis. During the last 50 to 70 years, streamflow amounts have increased in winter and spring, and in some areas have decreased during summer (high confidence). Winter increases are projected to continue across the entire country, while summer decreases are projected across western Canada (high confidence).
  • Key message 5.3: Annual streamflow amounts have increased in regions of northern Canada dominated by permafrost and will continue to do so (high confidence). No long-term historical or projected changes in annual streamflow are evident across the rest of the country (high confidence).
  • Key message 5.4: The timing of spring peak streamflow has shifted across Canada to earlier in the season because of the earlier onset of spring freshets. This shift has resulted in changes from more snowmelt-dominated streamflow regimes to rainfall-dominated regimes. These changes are projected to continue (high confidence).
• 6.5: Glaciers
  • Key message 6.10: Canada’s glaciers are projected to continue losing mass under every future emissions scenario (very high confidence). […] The number and severity of glacier-related hazards, such as flooding and landslides, are expected to increase, particularly in western Canada (medium confidence).

Relevant key words

• Hydrological extremes, hydrometeorological extremes
• Floods, inundation, water surpluses, mixed flooding
  • Rain-on-snow (ROS) flood, rain-on-snow events, rain-on-ice flooding
  • Snowmelt flood, spring freshet, snowmelt-related flooding, snowmelt-dominated flood, nival flood, extreme snow-melting events, extreme ice-melting events
  • Ice jam flood, ice jam breakup, ice breakups, thermal breakups, ice movement, river ice, freeze-up, breakup, spring flood
  • Streamflow flood, fluvial flood, riverine flood, streamflow events, high-flow events, streamflow regime
  • Glacial flood, glacier-dominated flood

Table 10.9: Projected directional changes and example indicators for non-pluvial (rain-on-snow, snowmelt, and ice jam) floods

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Floods are Canada’s most commonly reported natural disaster, as tracked by the Canadian Disaster Database, which contains information on significant disaster events from 1900-2022 (Public Safety Canada, 2025). Floods can occur at any time of year, near and far from bodies of water, and can be triggered by several different mechanisms (Public Safety Canada, 2023). The major categories of floods explored in these hazard sections are spring freshet (snowmelt), pluvial (heavy precipitation; section 10.4.6), ice jam, rain-on snow, and coastal flooding due to storm surges and sea-level rise (section 10.4.13).

The numerous chapter links in this section and section 10.4.6 (extreme precipitation) demonstrate that flooding is a cross-cutting hazard. This is because flooding is a complex hazard that has many causes, some of which are driven by interactions between different aspects of climate. This hazard is also complex due to interactions with non-climate factors, such as topography, surface conditions, and the implementation of adaptation measures. It is an important hazard to understand and adapt to because of the seriousness of the consequences. Understanding flood risks also generally requires using climate model projections to drive further hydrological modelling to understand changes in streamflow, and potentially hydraulic modelling as well to understand vulnerability to floods on a fine spatial scale (Natural Resources Canada, 2023).

Transportation infrastructure in British Columbia over the 21st century has made use of climate indicators to assess increases in flood risks. A key concern for transportation infrastructure in this region is landslides. In Sobie (2020), the author combined a landslide model with downscaled precipitation projections and past geohazard data to generate detailed simulations of landslide hazards in British Columbia over the 21st century. In 2010, British Columbia’s Ministry of Transportation and Infrastructure conducted a Climate Change Engineering Vulnerability Assessment of the Coquihalla Highway (BC Ministry of Transportation and Infrastructure, 2010), which found that “the Coquihalla Highway is generally resilient to climate change with the exception of drainage infrastructure response to Pineapple Express [atmospheric river] events.” This risk assessment led to the requirement (BC Ministry of Transportation and Infrastructure, 2015, 2019) that climate change be considered in all new projects and in rehabilitation and maintenance. In November 2021, an atmospheric river made landfall in southwestern British Columbia, bringing intense precipitation to the region, including the stretch of highway that had undergone a climate risk assessment about 15 years earlier. Gillett et al. (2022) found that human-induced climate change contributed substantially to the chance of such an atmospheric-river event, and that the probability of such events will increase in the future. The explicit use of climate projections in all transportation construction for almost a decade is intended to reduce the impact of these events on transportation infrastructure. After the damage to the Coquihalla Highway in 2021, the Ministry is now focusing on ensuring that retrofits are also resilient to a changing climate. 

10.4.10: Droughts

Related hazards

• Extreme heat and heatwaves (4.4); and wildfires (10.4.11).
• See Chapter 4, section 4.8: El Niño-Southern Oscillation and other atmosphere-ocean coupled modes of variability for potential influences on droughts; and Chapter 5, section 5.5: Groundwater and how it may be affected by changes to droughts.

CCCR2026 sections and key messages

• 5.6: Droughts
  • Key message 5.8: Meteorological and agricultural droughts are projected to be longer and more frequent and intense across central and southern Canada during summer, and to be more prominent with higher amounts of global warming and at the end of the century (high confidence). Summer hydrological droughts are also projected to be longer and more frequent and intense in many regions of southern Canada, mainly because of increased evaporation and lower runoff from mountainous regions (low confidence). Historically, periodic droughts have occurred across much of Canada, but no long-term changes in their frequency are detectable (high confidence).
• 5.9: Synthesis of water cycle changes
  • Key message 5.11: There has been a shift in the timing of many water cycle–related processes to earlier in the spring (high confidence). The shifts include earlier occurrences of snowmelt, spring freshet, groundwater aquifer recharge, and freshwater ice-free dates. These changes are projected to continue (high confidence) with possible consequences for future freshwater security.
  • Key message 5.12: Canada’s water cycle has been altered and will continue to be altered by climate warming (medium confidence). This involves more precipitation, changes in the proportion of rainfall versus snowfall, increases in warm-season evaporation, and a greater potential for flash flooding and summer drought. These changes are expected to directly impact the availability of surface and subsurface freshwater across Canada. 
• 6.2: Terrestrial snow
  • Key message 6.2: Snow cover duration is projected to shorten across all of Canada and peak snowpack amounts are projected to decrease across most of Canada with increasing climate warming (very high confidence). Unlike the rest of Canada, the western and central parts of northern Canada are projected to experience larger peak snowpack amounts due to increased snowfall despite a shorter projected snow season (medium confidence).
  • Key message 6.3: Past amounts and changes in snowpack are more uncertain for mountainous regions than elsewhere (high confidence). In a warmer climate, mountainous regions in Canada are expected to have less snowpack accumulation and experience more mid-winter melt events, changing the timing and reducing the predictability of Canadian water resources (high confidence).

Relevant key words

Surface water shortage, moisture deficits, water scarcity, water shortages, surface drying, dry spell, meteorological/agricultural/hydrological/ecological drought, flash drought, snow drought, Standardized Precipitation Index (SPI), potential evapotranspiration (PET), Palmer Drought Severity Index (PDSI), Standardized Precipitation Evapotranspiration Index (SPEI), standardized runoff indices (SRI), standardized streamflow index (SSI), standardized groundwater index, 1-in-10-year drought events, snow water equivalent deficit, soil moisture deficit index (SMDI), Climate Moisture Index (CMI), Temperature Humidity Index

Table 10.10: Projected directional changes and example indicators for droughts

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Drought is important for water management and agriculture, where increased drought could limit opportunities associated with climate change, such as changing crop suitability and a longer growing season (Chapter 5) (Lemmen et al., 2021). In most parts of the country, projected climate-related increases in drought potential are driven mainly by warming and associated increases in evaporation (Chapter 5, section 5.3). The landscape of available climate projections for localized drought conditions in Canada has improved in recent decades. At the start of the century, users had to make inferences about drought based on the known climate drivers of drought and separate climate variables, such as total precipitation and maximum temperatures at the resolution of GCMs of the time, around 2° to 6° (or 120 km x 200 km to 360 km x 600 km) (Barrow et al., 2004).

Since then, various drought indicators have become available (Chapter 5, section 5.6.1). For example, in 2018, the Standardized Precipitation Evapotranspiration Index was calculated using CMIP5. These projections were based on precipitation and potential evapotranspiration, which was calculated based on temperature (Tam et al., 2019). In 2023, when this index was updated with CMIP6 (Tam et al., 2023), a more complex calculation method for potential evapotranspiration was used, based on wind speed, humidity, radiation, and air temperature. This version also makes use of higher resolution observations for bias correction where possible and provides more complete coverage of Canada. Overall, the evolution in the availability of drought-related climate data highlights the need for iteration in planning and water resource management so that new climate data can be incorporated into decision-making when available. Other drought indicators, such as composite indicators, are an active area of research, and novel methods are still under development, such as research from Soltani et al. (2024) that uses deep learning to investigate future drought zones in Canada.

10.4.11: Wildfires

Related hazards

Extreme heat and heatwaves (10.4.4); and droughts (10.4.10).

CCCR2026 sections and key messages

• 8.7.1: Fire weather and wildfires
  • Key message 8.11: The fire season has lengthened in most parts of Canada (high confidence) and is projected to continue to lengthen as the global average temperature increases (high confidence). Fire weather—characterized by hot, dry, and windy conditions conducive to wildfires—has increased in Alberta and British Columbia (medium confidence), with some indications of increases in other regions (very low confidence). The frequency and intensity of extreme fire weather conditions are projected to increase in most regions of Canada with increases in global average temperature (high confidence).
• 9.5: The carbon cycle in Canada
  • Key message 9.10 excerpt: […] extreme events like the 2023 fire season can cause the land to become a temporary source of carbon (low confidence). In the future, both carbon uptake from increased vegetation growth (medium confidence) and carbon emissions from permafrost thaw, wildfires, and other disturbances (high confidence) are expected to increase.
  • Key message 9.11: The annual forest area burned by fires in Canada has increased since the early 1980s (medium confidence). The area burned is projected to increase further as the climate continues to warm (high confidence).

Relevant key words

Fire, wildfire, wildland fires, fire weather, area burned, burn, burnable mass, sources of ignition, fuel moisture, fire behaviour, fire danger rating systems, Canada’s Fire Weather Index (FWI) system, fire season, Initial Spread Index (ISI), the Build-up Index (BUI), extreme fire weather

Table 10.11: Projected directional changes and example indicators for wildfires

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

The impacts of wildfires in Canada are far-reaching because wildfires and the associated smoke can result in, for example, evacuations, damage to personal property and public infrastructure, air quality issues, health impacts, and reduced visibility (Public Safety Canada, 2023; F. J. Warren & Lulham, 2021). Wildfire activity has increased in Canada in recent decades, and recent extreme wildfire seasons can be directly linked to human-caused climate change (Chapter 8, section 8.7.1, Box 8.1). The climate component of wildfire danger is related to hot, dry, and windy “fire weather” conditions. However, wildfire activity is also heavily influenced by factors not related to climate, such as flammable vegetation and debris (fuel), and natural and human-caused ignitions (Chapter 8, section 8.7.1; Chapter 9, section 9.5.1.7).

As described in Chapter 8, Canadian forest fire professionals widely and routinely use the Canadian Forest Fire Danger Rating System (CFFDRS) to plan for and estimate wildfire danger by assessing the potential for wildfire ignition, spread, and intensity (Stocks et al., 1989). This system includes several indicators that make up the Fire Weather Index (FWI) (Van Wagner, 1987). Future FWI projections and a web-based application were developed with extensive user input at multiple stages (Van Vliet et al., 2024) to reduce decision overload and enhance the appropriate integration of fire weather information into long-term decision-making. Even with such tailored indices, it is important to carefully describe the limitations of use and what additional information may be needed to understand future wildfire risks.

For example, the CFFDRS considers the three main factors that typically influence wildfire activity: (1) hot, dry, windy climate conditions, which increase fire ignition and spread, (2) fuel, such as vegetation and debris, which are needed for fires to ignite and grow, and (3) sources of ignition, which can be natural, such as lightning, or human-caused, such as sparks from a campfire (Stocks et al., 1989). The CFFDRS also considers other important wildfire controls, such as topography (landscape features). While the FWI projections, such as the Extreme Build-Up Index noted in Chapter 8, section 8.7.1, can inform users about weather-related aspects of potential fire danger, they do not provide information on the other factors of the CFFDRS: fuel availability, topography, and ignition sources. Consideration of these non-climate factors is important for gaining a better understanding of local fire danger risk.

Additionally, wildfire-related impacts to human health from wildfire smoke, requires other modelling tools in addition to FWI indices. The development of modelling tools and indices that consider future climate in addition to data and projections for the other components of risks from wildfire is an active area of work. In the meantime, users seeking information on additional aspects of the potential for fire weather can consider localized assessments, vegetation maps, and monitoring programs, or information specific to ignition.

10.4.12: Permafrost warming and thaw-driven landscape changes, and terrestrial ice loss

Related hazards

• Extreme cold, loss of cold, and seasonally frozen ground (4.5).
• See Chapter 5, sections 3: Streamflow magnitude and timing, 5.4: Surface water levels – lakes and wetlands and 5.5: Groundwater, for potential influences on permafrost warming and thaw-driven landscape changes.

CCCR2026 sections and key messages

• 6.7: Permafrost
  • Key message 6.14: Permafrost warming and thaw-driven landscape changes are expected to continue with increased climate warming (very high confidence). Even if the climate stabilizes, some thawing will continue at depth (very high confidence). However, there is low confidence regarding the magnitude and timing of these changes because of the influence of local ground characteristics.
• 6.5: Glaciers
  • Key message 6.10: Canada’s glaciers are projected to continue losing mass under every future emissions scenario (very high confidence). In western Canada, more than 70% of glacier ice (by volume) is predicted to disappear by 2100, even if warming is limited to 1.5°C (high confidence). The number and severity of glacier-related hazards, such as flooding and landslides, are expected to increase, particularly in western Canada (medium confidence). Melt water from glaciers and ice caps in the Canadian Arctic will continue to be among the largest glacier sources of global sea-level rise up to and beyond 2100 (very high confidence).

Relevant key words

Continuous permafrost, discontinuous permafrost, sporadic permafrost, isolated permafrost, permafrost temperature, permafrost thaw, permafrost thermal state, ground temperatures, thaw depth, active layer, active layer thickness (ALT), thaw-driven landscape change, permafrost degradation or aggradation, thaw subsidence, ground settlement, ground ice, ice-wedge networks and ponds, permafrost thaw lakes, thermokarsts terrain and landforms, pond formation, lake expansion or drainage, slope failures such as thaw slumps, landslide, geoscience hazard, glacier

Table 10.12: Projected directional changes and example indicators for permafrost warming and thaw-driven landscape changes

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Permafrost warming and permafrost-induced landscape change are of concern because permafrost underlays a large portion of Canada (Chapter 6, Figure 6.30). In the past, permafrost stayed frozen, making transportation, infrastructure stability, and traditional land uses more reliable in northern regions (Firelight Research Inc, 2022; Hancock et al., 2022). However, warming permafrost and associated landscape changes are resulting in impacts such as land subsidence and the formation of thermokarsts (lakes) (Lewkowicz & Way, 2019). It can also impact other hazards that include a climate component, such as eroding coastlines and landslides (GRID-Arendal, 2020). Understanding current permafrost conditions and how they may evolve in response to a changing climate is essential for assessing the impacts of climate change and developing adaptation strategies in northern Canada (see the detailed assessment of changes in permafrost in Chapter 6, section 6.7) (Firelight Research Inc, 2022; GRID-Arendal, 2020; Hancock et al., 2022; Lewkowicz & Way, 2019). Due to permafrost being a geoscience hazard, non-climate information is important to use in conjunction with climate information. As noted in Chapter 6, section 6.7, while climate projections clearly show that in general permafrost will continue to warm and thaw across northern Canada, there are limitations with permafrost-related projections, particularly on the local scale.

Permafrost temperature conditions are complex and depend on several climate-related factors, such as air temperature (including Arctic amplification), precipitation patterns, and snow cover. Climate service providers can help users by summarizing the current state of knowledge and by highlighting connections with other changing hazards, such as wildfires (section 10.4.11), which can affect permafrost through changes in surface conditions. Many non-climate factors are location-specific and will impact how climate change affects permafrost, and these must also be considered. These factors include soil properties, subsurface materials, overlying organic matter and vegetation, ground ice, and physiographic factors, such as topography, shade, surface albedo, hydrological properties, and surface geology. All the factors taken together affect the physical response of the landscape to thaw (Chapter 6, section 6.7). There are limitations associated with the data and approaches used to model permafrost due to inadequate representations of the complex interactions of these factors (Chapter 6, section 6.7.3).

Given the limitations in the monitoring networks and models used, including inadequate representation of important factors and processes influencing permafrost, the magnitude and timing of warming and thawing (especially regionally) are less certain, despite very high confidence in the direction of change (warmer, more thaw).

10.4.13: Sea-level change, storm surge, and coastal flooding

Related hazards

Extratropical storms and hurricanes (10.4.7); non-pluvial (rain-on-snow, snowmelt, and ice jam) floods (10.4.9); and marine hazards (ocean circulation, ocean temperature, marine heatwaves, ocean salinity, ocean stratification, ocean acidification, and deoxygenation) (10.4.14).

CCCR2026 sections and key messages

• 2.2: Synthesis of past changes
  • Key message 2.5 excerpt: The effects of the warming climate are also clearly seen in Canada’s ocean areas, through increases in ocean water temperature, more frequent marine heatwaves, freshening of near-surface ocean waters, and decreasing sea ice cover, which has resulted in increasing ocean wave heights in the Arctic (high confidence). Some of Canada’s coastal areas are also experiencing the effects of sea-level rise (very high confidence) and more frequent extreme sea-level events (high confidence), which can contribute to coastal flooding.
• 7.4: Global and relative mean sea level
  • Key message 7.7: Global mean sea level is projected to rise by many tens of centimetres in the 21st century under a low emissions scenario and is unlikely to be more than a metre under a very high emissions scenario (medium confidence). Relative sea levels in different parts of Canada are, however, projected to rise or fall depending on local vertical land motion as well as the amount of global sea-level rise. Owing to land subsidence, parts of Atlantic Canada and the western Arctic are projected to experience increases in relative sea-level that are larger than the change in the global mean sea level during the coming century (high confidence).
• 7.5: Waves and storm surge
  • Key message 7.9: The projected lengthening of the Arctic ice-free season will cause increases in mean and extreme wave heights (high confidence) and storm surges (medium confidence). In areas of Atlantic Canada not affected by sea ice, mean wave heights are projected to decrease (medium confidence), while weak changes are projected in the northeast Pacific (low confidence). Projections of extreme wave heights in areas without sea ice provide limited evidence of increases in Atlantic Canada (low confidence).
• 7.6: Extreme sea level
  • Key message 7.11: Extreme sea-level events are projected to occur more often and to become larger because of future increases in relative sea-level rise in many parts of Canada (high confidence). The projected decline of sea ice along Canada’s Arctic and Atlantic coasts will result in increased waves and storm surges, which will exacerbate extreme sea-level events (high confidence).
• 6.3: Sea-ice
  • Key message 6.6: The sea ice–free period is projected to lengthen further across Canadian Arctic and Hudson Bay waters with increasing climate warming (very high confidence). In regions with seasonal sea ice cover, the number of ice-free days is projected to increase by approximately one month for each degree of global warming, with smaller increases in the Labrador Sea and larger increases in the Beaufort Sea (medium confidence). The transport of multi-year ice into the Northwest Passage is projected to continue beyond mid-century thereby continuing to limit the shipping season (medium confidence).
• 6.5: Glaciers
  • Key message 6.10: Canada’s glaciers are projected to continue losing mass under every future emissions scenario (very high confidence). In western Canada, more than 70% of glacier ice (by volume) is predicted to disappear by 2100, even if warming is limited to 1.5°C (high confidence). The number and severity of glacier-related hazards, such as flooding and landslides, are expected to increase, particularly in western Canada (medium confidence). Melt water from glaciers and ice caps in the Canadian Arctic will continue to be among the largest glacier sources of global sea-level rise up to and beyond 2100 (very high confidence).
• 8.7.2: Compound coastal flooding
  • Key message 8.12: Compound coastal flooding arises from jointly occurring climate conditions, such as heavy rain during episodes of extreme water levels. Such co-occurring drivers have increased in frequency and intensity in some parts of Canada, with evidence primarily from Atlantic locations (low confidence), and are projected to become more frequent and intense at locations along the Atlantic, Pacific and Western Arctic coastlines (medium confidence). These projected increases are mostly due to rising sea levels and increases in the frequency and intensity of extreme precipitation events (medium confidence).

Relevant key words

• Sea-level rise, relative sea level (RSL), global mean sea level (GMSL), coastal flooding, extreme coastal water-level (ECWL) events, extreme sea level (ESL), extreme still-water level (ESWL), extreme total water level (ETWL), high-end sea level, coastal erosion, erosion, saltwater intrusion, land motion, vertical land motion, subsidence, uplift, Antarctic ice sheet instability, sea-level high end
• Swells, tide gauge, tide, astronomical tide, waves, wave height, significant wave height (Hs), mean wave period, mean wave direction, sea-level pressure (SLP), extreme winds

Table 10.13: Projected directional changes and example indicators for sea-level change, storm surge, and coastal flooding

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Sea-level change, storm surge, and coastal flooding are interconnected hazards that can damage natural habitats, affect property, impact infrastructure, and disrupt communities (F. J. Warren & Lulham, 2021). Global mean sea-level rise is an important indicator of climate change, one that is driven primarily by thermal expansion of warming seawater and ice loss from glaciers and ice sheets (Chapter 7, section 7.4). However, at any given location, relative (or local) sea-level change is most relevant because it includes vertical land motion. In Canada, some locations will experience an increase in relative sea level where land is subsiding, whereas other locations will experience a decrease in relative sea level where land uplift is larger than the rate of global sea-level change (Chapter 7, section 7.4).

The effect of a rise in sea level will initially be experienced through an increase in the frequency and magnitude of extreme water levels. Higher mean sea levels lead to water levels being higher during standard high astronomical tides (Chapter 7, section 7.6, Figure 7.28). Additionally, changes in storm surge will further increase coastal flooding (see section 10.4.9 and 10.4.6 for other flood mechanisms) and coastal erosion. While storm surges are affected by the underlying mean sea-level change, they are also impacted by changes in climate variability, large-scale atmospheric processes, and wave height due to the decline of sea ice (Chapter 7, section 7.5.2.1).

In an adaptation context, the high-end global sea-level projection, extreme sea level, or enhanced scenarios described in Chapter 7 are important to consider. Although the projections in Chapter 7, sections 7.4 and 7.6, go to 2100, there is a long-term committed change to sea-level change beyond the end of the century because the thermal expansion of ocean water and the melting of glaciers and ice sheets in response to past greenhouse gas emissions is a very slow process. The projected changes in global sea level are similar for all future scenarios until the middle of the 21st century, which reduces the need to select a specific scenario for planning. For long-term decisions that may be influenced by these changes in sea level, the precautionary principle would suggest using projections from the very high emissions scenario (SSP5-8.5) (Fox-Kemper et al., 2021) (Chapter 7, section 7.4.2). In the case of low tolerance to risk and for projects with time frames extending past 2100, it is prudent to consider the high-impact, low-probability storyline scenario, which includes an adjusted rise in global sea level that reflects a potential contribution from catastrophic loss of the Antarctic ice sheet (Chapter 7, Box 7.2).

The Canadian Extreme Water Level Adaptation Tool (CAN-EWLAT) is an adaptation planning tool that combines projections of rises in sea level with information about local harbours on Canada’s coastlines over the coming century and offers advice on how much higher to build coastal infrastructure to accommodate the projected rise. The tool, developed for Fisheries and Oceans Canada Small Craft Harbour locations, is also useful for planners dealing with infrastructure along Canada’s ocean coastlines.

10.4.14: Marine hazards (ocean circulation, ocean temperature, marine heatwaves, ocean salinity, ocean stratification, ocean acidification, and deoxygenation)

Related hazards

Sea-level change, storm surge, and coastal flooding (10.4.13).

CCCR2026 sections and key messages

• 2.2: Synthesis of past changes
  • Key message 2.5 excerpt: The effects of the warming climate are also clearly seen in Canada’s ocean areas, through increases in ocean water temperature, more frequent marine heatwaves, freshening of near-surface ocean waters, and decreasing sea ice cover, which has resulted in increasing ocean wave heights in the Arctic (high confidence). […] The oceans around Canada have also absorbed anthropogenic carbon dioxide from the atmosphere, which has resulted in ocean acidification in the ocean’s near-surface layers (very high confidence).
• 4.9: Ocean circulation
  • 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.
• 7.2: Ocean temperatures
  • Key message 7.2: Continued warming is projected for the oceans around Canada, with the magnitude increasing with higher greenhouse gas emissions (high confidence). The increase in annual average sea surface temperatures is expected to be greater in the waters next to Atlantic Canada and British Columbia than in the Arctic (medium confidence). During the summer period, sea surface temperatures are expected to increase the most in the Beaufort Sea and Hudson Bay, in part due to the decline of seasonal sea ice cover there (medium confidence).
  • Key message 7.3: More frequent and intense marine heatwaves have been observed in the Pacific and Atlantic oceans around Canada since the 1980s and are expected to continue to increase in all oceans, including the Arctic, because of human-caused climate change (high confidence).
• 7.3: Ocean salinity and stratification
  • Key message 7.4: The surface waters of the oceans around Canada are characterized by relatively low salinity and have become even fresher since the 1950s (high confidence). The increasing freshwater input to these oceans results from warming-driven increases in precipitation and runoff from land, which includes glacier and ice sheet meltwater (high confidence). Ocean freshening is projected to continue throughout the 21st century; however, the limited number of emissions scenarios studied and the variability among model projections have resulted in low confidence for the Arctic and medium confidence for the Atlantic and Pacific.
  • Key message 7.5: Increased stratification, or layering of the upper ocean according to water density, in the northeast Pacific and southern Atlantic Canada regions has resulted from warming and freshening of the sea surface (high confidence). Increased stratification reduces the vertical mixing of nutrients and other chemical compounds in the upper ocean, which is an important process in the marine ecosystem.
• 7.7: Ocean chemistry
  • Key message 7.14: Over the rest of the 21st century, the oceans around Canada are projected to continue to absorb anthropogenic carbon dioxide, to increase in acidity (very high confidence), and to lose oxygen in the subsurface (medium confidence). The level of projected acidification in the latter half of this century will strongly depend on the level of future carbon dioxide emissions (very high confidence).
• 9.5: The carbon cycle in Canada
  • Key message 9.12: On average, Canada’s oceans (inside the Exclusive Economic Zone) take up carbon dioxide (CO₂) (medium confidence), although some nearshore areas emit CO₂ (low confidence). Overall, Canada’s oceans will continue to take up CO₂, as long as atmospheric CO₂ concentrations continue to increase (medium confidence).

Relevant key words

• Ocean circulation, Atlantic Meridional Overturning Circulation (AMOC), AMOC strength, AMOC shut down, ocean circulation currents, ocean current systems, heat transport, North Atlantic warming hole
• Ocean warming, sea surface temperatures (SST), ocean heat content (OHC), subsurface temperature, bathymetry, marine heatwaves, marine cold spells
• Ocean salinity, saltiness of the sea, freshening, freshwater runoff, high salinity, saline, practical salinity units (PSU), seawater salinity, sea surface salinity (SSS), water density, ocean circulation, vertical density stratification, vertical mixing, vertical transport, pycnocline
• Ocean chemistry, ocean acidification, pH, ocean deoxygenation, dissolved oxygen, hypoxia, surface absorption of carbon dioxide, total ocean carbon levels, carbon content, eutrophication

Table 10.14: Projected directional changes and example indicators for marine hazards (ocean circulation, ocean temperature, marine heatwaves, ocean salinity, ocean stratification, ocean acidification, and deoxygenation)

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

As the ocean absorbs excess heat and carbon dioxide, its surface warms and increases in acidity. That warming, together with surface ocean freshening, is increasing stratification, reducing communication between the surface and deeper ocean layers, and reducing the transport of oxygen and anthropogenic carbon to deeper waters (Venegas et al., 2023). These marine changes are likely to impact ecosystems by favouring some organisms over others, causing shifts in typical ranges and depths, and reorganization of food webs. Fisheries and aquaculture management professionals make particular use of projections for acidification and hypoxia in planning adaptation of best practices and mitigation efforts at individual shellfish hatcheries (Doney et al., 2020).

Ocean data are becoming more accessible through the recently established Canadian Integrated Ocean Observing System but, compared to atmospheric data, remain less accessible. Ocean data also differ in availability and number of indicators that are pre-calculated and made readily accessible through online portals.

While GCMs include (coarse resolution) ocean variables, regional ocean models are also available for limited areas (generally along and adjacent to coastlines). Regional ocean models may include components that simulate circulation and stratification, biogeochemistry, and some aspects of ecosystem modelling. Statistical downscaling of ocean data to make the data more locally relevant is a relatively new research topic. Machine learning algorithms are increasingly being used to fill the gaps (spatial and temporal) between sparse ocean measurements.

10.4.15: Strong winds

Related hazards

Extratropical storms and hurricanes (10.4.7) and thunderstorms (10.4.8).

CCCR2026 sections and key messages

• 8.4: Wind extremes
  • Key message 8.10: There isinsufficient evidence to assess historical changes in extreme winds in Canada due to limited station coverage and representativeness, significant uncertainties in reanalysis products, and the paucity of studies examining trends in wind extremes. There is very low confidence in the direction and magnitude of future changes in extreme winds due to the limited number of studies and substantial model uncertainty related to projections of wind-related phenomena.

• 8.7.3: Compound wind and rainfall
  • Key message 8.13: There is insufficient evidence to assess historical changes in compound wind and rainfall events in Canada, due to limited studies focusing on observed trends. Compound extreme wind and rainfall events are projected to increase (medium confidence), driven mainly by the greater frequency of future extreme rainfall, but with very low confidence in the regional pattern and magnitude of changes.
• 2.6: Past wind speed changes
  • Key message 2.13 excerpt: Annual and seasonal average surface wind speeds decreased during the 1953–2023 period across a large part of southern Canada stretching from the southern Prairies to central Quebec (medium confidence). In contrast, average wind speeds increased in British Columbia in spring and summer (low confidence). There is low confidence overall in assessments of the magnitude of annual average wind speed changes due to inconsistency between observational data products.
• 3.6: Average near-surface wind
  • Key message 3.10: Average near-surface wind speed and wind power potential are projected to decrease for Canada (low confidence). Wind speed projections for Canada are highly uncertain due to low model agreement.
• 4.3: Jet streams, storm tracks, and atmospheric modes of variability
  • Key message 4.3 excerpt: Changes in recent decades in the jet streams and storm tracks that affect Canada are small and seen only in limited seasons and regions. […] 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).
• 4.6: North Atlantic hurricanes
  • 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.  

Relevant key words

• Extreme winds, wind extremes, surface winds, near-surface winds, damaging winds, föhn wind events, chinook winds, extreme storms, wind speed, wind shear
• Cyclone-related wind extremes, cyclones, tornadoes, downbursts, derechos, microbursts

Table 10.15: Projected directional changes and example indicators for strong winds

Note that the direction of projected change is general and averaged across Canada. For further details on indicators and projected changes, readers should consult the specific sections of this report on which these summaries are based (as indicated in square brackets).

Additional details on how to consider information for this hazard

Winds and strong winds are important to decision-making in sectors such as renewable energy, infrastructure development, and disaster preparedness (F. J. Warren & Lulham, 2021). However, few studies have estimated trends in extreme winds in Canada, as assessed in Chapter 8, section 8.4.1. Research is also limited on the mechanisms and causes of observed and projected changes to wind in Canada. Another complexity for understanding changes to wind is that extreme wind speeds often occur in association with extreme storms, such as extratropical cyclones, hurricanes, blizzards, and tornadoes (Chapter 8, section 8.4). Current global models are spatially coarse and do not resolve the small-scale processes that lead to extreme wind speeds. Wind speeds are also highly affected by local topography and landcover characteristics, which (currently) are not directly captured in coarse-resolution climate models. Wind projections from different models often have large differences in wind speed and direction, and inconsistent projections across seasons and regions, which can result in seemingly small or unimportant ensemble average changes. While use of modelled wind projections presents challenges, this does not mean that past wind data alone can be relied on as an indicator of future wind conditions. Careful interpretation of what is known about potential changes in wind, including uncertainty, is important to consider. For example, Climate Change and Strong Winds summarizes the state of knowledge about projected changes to wind in Canada in a way that may be useful for adaptation planning and decision-making.

10.5 Concluding statements

The statements below summarize at a high level the contents of sections 10.2 to 10.4.

10.5.1: Climate services

Climate services have emerged to make climate science more actionable in an adaptation context. In a warming climate, using climate projections will better inform risk assessment, design, and other decision-making, policy, and planning activities. Instead of relying solely on observations that reflect past climate conditions, using climate projections will enhance resilience.

Climate services aim to provide data and information to users in a form that is useful, usable, and used. Tailoring information to meet the needs of users is at the heart of climate services and ensures the relevance of the information to users. To be credible, climate service providers require subject matter expertise. Although not yet widely adopted or standardized, best practices regarding the delivery of climate services are emerging.

10.5.2: Finding and using tailored climate projections

Climate data are available from many sources, including through self-serve online portals developed by climate service providers. Portals typically include and are supported by different levels of guidance, outreach, and training to facilitate their use. Many climate service providers also develop and disseminate climate data and information tailored to relevant indicators and widely used formats.

Using climate projections requires careful consideration of uncertainties and challenges that arise in adapting to a changing climate. An important role of climate services is to help users navigate these issues by iteratively co-developing guidance and best practices. For example, use of climate projections requires thinking through implications of spatial and temporal coverage and resolution of climate data, availability of different emissions scenarios, implications of ranges of change and uncertainty, and selection of different baseline periods.

10.5.3: Hazards

A key component of risk assessment and adaptation planning is using hazard information tailored to regional or local scales.

Climate hazards and related indicators are typically affected by climate change in ways that can change the frequency, intensity, duration, and timing of events.

FAQs

As the emerging field of climate services continues to evolve (as described in section 10.2), frequently asked questions change. For this reason, instead of a static list of short FAQs, this chapter includes many links to external resources and a section (10.3) where common considerations in using climate projections are described in more detail.

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