Climate change is here, and its consequences are being felt from natural disasters continuing to increase in frequency and severity. That includes extreme wildfires in the western U.S. and Canada, devastating floods in Europe, and Hurricane Ida, which resulted in one of the highest individual insured losses on record. Natural disasters are combining to challenge businesses to make the right decisions to build risk resilience.1
In 2021 alone, global economic losses solely from weather disasters totaled $343 billion – 27 percent higher than the 21st Century average, and the seventh costliest year on record after adjusting for inflation.2
The changing climate continues to significantly impact the placement of natural catastrophe risks, and environmental risks pose the greatest damage to the global economy. As the world continues to warm, catastrophic events will continue to increase in frequency and intensity in ways that are impossible to predict using conventional risk assessment techniques. Using data and predictive analytics, organizations can measure and analyze their current state and benchmark against industry norms, projecting financial impact and protecting both tangible and intangible assets.
That includes making use of climate modeling to help manage the climate transition and help build risk resilience and reduce any surprises that can adversely impact a business. Probabilistic models help companies make strategic and risk management decisions under complex and changing environmental conditions.
Four Climate Model Types Serve Different Purposes
Climate models are based on well-documented physics-based processes to simulate the transfer of energy and materials through the climate system. There are currently four primary model types in use and, depending on the model, they provide the risk manager with a view of various perils and scenarios that could occur in the future to build risk assumptions down to the location level. Risk managers can work with a broker experienced with climate models to help make critical risk resiliency decisions, including future investments in a company’s own infrastructure, locations and people.
Here’s a deeper dive into each, from shorter-term weather forecasting to longer-term climate model types that look at the bigger picture of how our planet’s conditions will change 10 years to even 100 years from now.
Numerical Weather Model.
This is perhaps the most familiar form of weather model data as it is used to forecast weather, including temperature, precipitation, and other meteorological elements by media weather professionals.3
Global Climate Model (GCM).
This is a complex mathematical look at the major climate components – atmosphere, land, oceans and sea ice – that predict what the atmosphere, oceans and climate behavior will do over a long term.4 For example, GCM is able to look at various scenarios and see increases in carbon dioxide emissions and how that will lead to further disruptions in the jet stream and weather. It provides a global view of climate but can also go down to a more regional level.
With the rise in catastrophic events and losses over the past 25 years, CAT modeling has taken on an increased level of importance. CAT modeling was developed in the 1980s and enhanced since. It is used primarily by insurers and reinsurers to evaluate and manage catastrophe risk from many different types of catastrophes, ranging from hurricanes and floods to earthquakes and wildfires. Models are created by teams of cross-disciplinary professionals, who work together to create software, data and algorithms to help simulate the potential financial impact that catastrophes can bring in specified circumstances.
Climate Risk Model.
Climate risk models are a blend of the Global Climate Model output and the CAT Model, which includes a financial engine with the global climate model. While climate risk models come with a high level of uncertainty, through the use of different scenarios and pathways they are helpful to companies planning for future climate risk and how climate change may be evolving, including rising sea levels, which is expected to lead to stronger storms and changes in flood risk.
Making Use of Climate Models
Global climate models are typically utilized at the academic level, but insurers, reinsurers, brokers and, ultimately, businesses are more frequently seeking ways to convert some of their modeling results into strategic decision-making. Insurers and reinsurers are increasingly using near-term output from the models to help quantify climate risk in their portfolios and make adjustments that will help enable better pricing decisions on pricing, investments and exposure management now and over the long term. As mentioned earlier, a broker experienced in climate change modeling can help businesses interpret the results of these complex models and, based on their risk profile, work to determine a the right risk management program that builds resiliency for clients.
The Future of Climate Modeling
Scientists tend to agree that the world’s climate is changing largely due to human activity and that the average global temperature and sea levels will continue to rise.5 They also agree that this evolving climate behavior will continue to cause weather patterns to act more unusually than in the past.6 The use of climate modeling is global in nature and, as a result, has had an open culture of global collaboration. The primary example is the Coupled Model Intercomparison Project (CMIP), which since 1996 has combined the world’s climate models and scenarios every 6-7 years into a set of simulations. The result is a repository of global data that serves as the underlying basis for the Intergovernmental Panel on Climate Change (IPCC). CMIP 6 is an update of the repository, and has been released this year, along with the main findings from the Sixth Assessment Report of the IPCC.
Further, as computer power continues to grow stronger, climate modeling will continue to become more refined, more site-specific and provide users with more confidence in how impacts will be felt.