With funding from EPA, ClimateSight quantified the mental health risks of climate change in the U.S. We projected that suicides could increase by up to 1,660 additional cases annually. Building a better understanding of climate change and its impact on mental health can help identify ways to address both crises.
Climate risk modeling
Current climate challenges and the role of climate risk modeling
As climate change intensifies worldwide, governments and organizations must brace for severe—and increasingly devastating—risks predicted to disrupt socioeconomic systems across the globe. While historic records of past extreme weather were once reliable predictors of future extreme weather, climate change now changes the game. To meet resilience goals, discover actionable approaches, and make the case for mitigation, organizations should rely on climate risk modeling—a necessity in predicting future climate scenarios.
Climate risk modeling is the process of using the latest climate science and data to project changes in future extreme weather—including heat, droughts, flooding, and storms—and the potential impacts of that weather.
Considering the Biden Administration’s goal of achieving net-zero greenhouse gas (GHG) emissions by 2050, climate action is a top priority for mitigating the severe physical and economic damages that result from climate change. Fewer greenhouse gas (GHG) emissions result in less extreme weather, ultimately reducing the harm caused to people and communities across the globe.
The risks are expansive and powerful, including direct impacts on agriculture and food systems, energy resources and demand, transportation and infrastructure, financial and banking sectors, natural habitats, livability, and displacement.
But across all industries, preparing for and mitigating against future damage requires precise climate risk modeling. Climate risk modeling provides agencies and organizations with the opportunity to make informed cases for forward-looking action, achieve resilience goals, and reveal potential actions.
Climate risk modeling uses large datasets to identify key scenarios and create actionable insights, including:
- Targeting national expenditure and regional program development
- Assessing vulnerability to inform long-term energy infrastructure and resilience planning
- Projecting crop yield, growing-season changes, and adaptation for long-term agricultural planning
- Screening potential investments for risks and opportunities
In addition to mitigation, climate risk models deliver the data necessary to create short- and long-term solution plans that reinforce and enhance industry and consumer confidence.
Climate risk modeling is only as good as the platforms used to crunch the data. Models tell you how the climate and extreme weather are projected to change, but additional analyses are needed to understand what risks or impacts those projections pose to a client. This is important, because it allows a platform such as ClimateSight to apply sectoral expertise to help understand and address climate risks.
Climate risk models and types
Climate risk models take a variety of forms, each synthesizing the complexity of surrounding variable data to provide clear, visual, and actionable data. With proven science-based processes, each model type serves a particular purpose—but all provide organizations with a visualization of scenarios that inform future risk assumptions and resiliency decisions based on industry needs and infrastructure.
Numerical weather model (NWM)
The most familiar weather model, NWMs use weather model data to forecast different types of weather, including precipitation, temperature, barometric pressure, and other meteorological elements. NWMs can be customized to create visual representations depending on specific meteorological needs.
Global climate model (GCM)
GCMs improve long-term understanding and prediction of the major climate system components—atmosphere, land surface, ocean, and climate behavior. They provide a global view of climate but can be customized at a specific regional level with granular detail. GCMs predict the long-term climate behavior that directly leads to disruptions, like the impact of emissions on extreme heat and precipitation.
Short for catastrophe modeling, this model estimates losses and simulates potential financial catastrophes using computer-assisted calculations. Insurance companies often use CAT models to evaluate and manage devastating risks from natural disasters like hurricanes, earthquakes, floods, and wildfires.
Climate risk model
The climate risk model blends a version of the GCM model and the CAT model to provide a robust view of climate risk scenarios. Importantly, climate risk models also include a financial component to help companies determine future climate risk planning from multiple angles, including socio-economic.
Real examples of climate risk modeling applications
Number of additional suicides with 3°C warming
Building community resilience to extreme heat
Extreme temperatures threaten lives and livelihoods. In Pennsylvania, ClimateSight mapped the number of days that temperatures will rise above 90°F by 2050 and identified potential climate risks to human health where vulnerable populations are most exposed to extreme heat. Our analysis and insights inform adaptation and resilience planning across the state.
Identifying heat-related threats to electrical infrastructure
ClimateSight projected daily maximum temperatures at midcentury around Portland, Oregon to determine heat-related risks that increasingly threaten electrical infrastructure. We identified a range of future climate conditions to account for multiple greenhouse gas emission scenarios. Equipped with these projections, utilities can invest in resilience efforts to prevent and limit heat-related power outages.
Projecting precipitation around transportation infrastructure
Fueled by climate change, flooding and heavy precipitation damage roads and other transportation infrastructure. ClimateSight projected and mapped heavy precipitation at midcentury to state roadways around Portland, Oregon. Our analysis helps planners build with resilience against increasing flood risks.
Benefits of climate modeling
Climate modeling allows organizations to translate their resilience goals into actionable plans and programs. Achieving goals starts with capturing the right data in order to visualize a long-term plan. Climate models prepare your agency or company to prepare for “what if” scenarios, with data informed by science. Maintaining infrastructure against catastrophic changes requires long-term planning, and climate risk modeling provides agencies and companies with the data and tools to execute on short- and long-term planning.
Climate modeling also includes adaptation benefits and co-benefits. Adaptation benefits incorporate reversibility and robustness of solutions to support flexible resilience strategies. Co-benefits factor in important features like safety, customer financial benefits, reputational benefits, equity, and infrastructure upgrades—pieces often intertwined. For example, identifying climate risks and addressing them through adaptation can both increase an organization’s operations while also upgrading infrastructure in underserved communities.
When earning stakeholder buy-in, capturing the full range of such benefits can help build mutual support for a resilience strategy.
Physical and transition risks
Climate risk analysis often requires encompassing two broad categories of risk: physical risks and transition risks. Both provide meaningful data for benchmarking and developing climate action strategies.
Acute physical risks result from natural, climatic events like floods or wildfires. While important to measure—and increasing in frequency due to climate change—it’s also necessary to model the trajectory of longer-term physical risks like rising sea temperatures. By factoring in both types of physical risks, the climate risk model can provide a more comprehensive view of future projections.
Transition risks take into account large-scale transformation of systems, policies, and economies directly tied to large-scale decarbonization efforts. Transition risks shine a light on changing behaviors and business models based on such transformations. Transition risks are important to account for across industries, and can provide opportunity for analysis of climate strategy investments.
Read our case studies
Use cases for climate risk modeling
In conjunction with deep expertise, climate risk modeling uses cutting-edge technology to help agencies and organizations use their resources more efficiently, reduce costs, accelerate mission accomplishments, make better decisions in the face of uncertainty, and create actionable plans to meet resiliency goals.
Climate risk modeling is a key component of the following client studies:
For many in the Pacific Northwest, the extreme temperatures at the end of June 2021 were miserable at best and deadly at worst. In this analysis, we discuss what made this heatwave so deadly and what we can expect in the future.
Warming temperatures play a role in negatively impacting mental health with an increased risk of suicide. Climate risk analytics create projections that help tackle both crises, including the development of effective mental health interventions.
Utilities increasingly face high-impact challenges from spikes in energy consumption and service disruptions. By changing how it plans and designs its energy delivery systems to be more resilient against intensifying climate events, Con Edison takes a forward-looking approach to planning and response.
The United States is experiencing the impacts of climate change in every region, from fires in the west to hurricane-related flooding in the east. ICF supports the U.S. Global Change Research Program in producing the 5th National Climate Assessment report identifying climate risks to humans and natural systems in the United States, now and in the future.
How to achieve climate risk maturity
No two organizations experience the same maturity path. The people and culture of an organization determine its digital transformation journey. Our climate experts evaluate people, organizations, and technologies to help enterprises deliver on their promises to users through digital transformation.
Best practices for achieving risk maturity
1. Tap into data-backed climate analysis.
Uncertainty shouldn’t be a barrier to action. Serious climate action begins with data and methods—brought to life through analytical rigor, state-of-the-science approaches, and technical integrity. Climate experts must execute hundreds of action planning projects and manage flagship resilience plans for federal, state, and local agencies, utilities, and private companies. Implementing the National Climate Assessment, it’s imperative to bring a data-backed approach to climate impact assessment and risk analysis, mitigation technologies, adaptation analysis, and decarbonization’s economic, equity, and health benefits.
2. Collaborate with integrated teams of experts.
Technical training and assistance (TTA) are, above all else, a partnership. Rely on robust industry knowledge to create targeted assessments and solutions, prepare and execute climate action plans, and promote sustainable urban development at the sub-national level with regions, provinces, and cities. A holistic approach to understanding climate risks and actions—combined with scientific expertise—refines future climate hazards into realistic vulnerability risks and assessments, helping to cultivate a realistic path to maturity.
3. Secure stakeholder buy-in throughout the process.
Raising awareness through stakeholder outreach is essential to achieving climate goals Any successful climate action plan, however large or localized, requires continuous outreach and engagement throughout the planning process. Outreach can include everything from workshops to information awareness campaigns.
How accurate is climate risk modeling?Climate risk modeling is reliable and accurate. Constantly evolving with the latest science and technology, modeling incorporates the millions of human and computer-assisted weather observation networks around the world recording data constantly—variable and fluctuating data from the air, land, and ocean, such as temperatures, wind patterns, and ocean currents. The more data points fed into a model, including comparative historical data, the more accurate its output. While there is always some level of uncertainty with predictions and forecasts, climate models of the 21st century are based on well-founded physical principles of physics and earth system processes.
What else can climate models measure?Climate models simulate and visualize changes on Earth over time. Models allow us to test hypotheses and draw conclusions on past and future climate systems, from natural to human influences that impact our atmosphere, weather, and climate events. A climate risk model’s predictions and results can help alleviate the harmful effects of climate change—like severe storms and droughts, extreme temperatures, rising sea levels, and melting glaciers—that directly harm people and animals and destroy the places we live. Climate risk models can also help us prioritize environmental issues based on scientific evidence.
How actionable should a climate model analysis be?Climate models should provide data with the intent of providing actionable analysis. By contextualizing reliable data, climate risk models provide information that serves as the basis for functioning action items. With this data, organizations can act at the juncture of climate modeling information and end-user actions. The translation of climate information into real-life action requires the credibility and reliability of the data, as well as its ability to convey information in a clear, salient manner.