CA - RESEARCH: How climate risk data can help communities become more resilient - Insights from San Diego

The average annual damages from weather- and climate-related disasters jumped from $18 billion in the 1980s to $81 billion in the 2010s, and the 2020s are easily on pace to shatter that record.

Governments at all levels have a responsibility to help communities adapt to increasing climate risks. Local governments are on the front lines, as they regulate and incentivize the location of new housing and commercial development, develop and operate transportation and water infrastructure, and oversee emergency preparedness and response. The rapidly growing field of climate analytics can help local governments adopt a more proactive approach by identifying risks, developing climate action plans, and implementing strategies that limit the harms of both chronic and acute climate stresses, from intense storms to wildfires to extreme heat.

The goal of this project is to illustrate how local governments can use geographically granular climate risk data to map local hazards and plan community-based adaptation strategies, while highlighting some of the challenges in working with this data. We also discuss areas where regional, state, and federal agencies can support their local colleagues in these efforts. This analysis is intended to be useful for local governments—including elected officials and career staff—as well as utilities, regional planning agencies, private sector firms, and civic organizations engaged with built environment planning.

To illustrate the potential uses and challenges of geographically granular climate risk information, we analyze data created by First Street Foundation that measures heat, wildfire, and flood risk. Focusing on the city of San Diego, we create risk maps at several levels of geography—city, neighborhood, and parcel—to illustrate how risk varies across geography, over time, and by climate risk category. These metrics primarily capture physical risk; when possible, we look at overlaps with social and economic characteristics that affect community vulnerability. Case studies of three neighborhoods with particularly high risks show the usefulness—and some cautions—of parcel-level analysis.

Briefly, our key findings are:

• Geographically granular climate risk data provides new insights that can inform adaptation strategies—but is quite complicated to work with, creating a steep learning curve. Local governments that want to undertake this type of analysis will need to invest in developing staff capacity with appropriate technical skills and subject matter expertise to analyze and interpret the data.
• Heat is the most widespread risk in San Diego, and is strongly correlated with geography. Heat risk rises moving inland from the coast. The frequency of extreme heat will increase substantially over the next 30 years across most neighborhoods. Low-income neighborhoods do not have a higher average heat risk, but will need more support in implementing adaptive strategies.
• About half of San Diego neighborhoods face wildfire risk. While the general patterns do not change over the next 30 years, the intensity of wildfire risk in areas currently affected will increase.
• Flood risk is both spatially concentrated and diffuse. About 1% of parcels citywide have estimated flood risk. These parcels are dispersed widely across the city—many neighborhoods have one or two parcels with high risk. A small handful of neighborhoods have concentrated clusters of high-risk parcels; these are likely targets for intervention.

While the spatial patterns we find are specific to San Diego, some of the insights from the analysis apply more broadly to local and regional public agencies across the country. Generalizable recommendations include:

• Regional or state governments should take the lead in acquiring and managing geographically granular climate risk data. Climate hazards cross political borders, with both extreme and chronic events likely to impact multiple jurisdictions at the same time. Many cities and counties do not have the technical expertise, staff bandwidth, or fiscal resources to conduct their own analysis. Because of the high upfront costs for learning how to use this data, there are clear economies of scale in sharing knowledge across multiple localities.
• Local governments should integrate findings from climate risk analysis into their resilience and adaptation plans. Having better information on the types of risk that affect different neighborhoods will allow local governments to prioritize limited public resources and undertake adaptive strategies with the greatest social benefits. Overlaying physical risks with other types of information—including social and economic characteristics or the condition of buildings and other infrastructure—will enable leaders to better target capital investments.
• Public officials and civic leaders should develop better ways to communicate local climate risks to general audiences. To build public trust and buy-in to adaptation investments, community members should understand both underlying risks and how specific risk reduction strategies can help. Enhancing the public’s understanding demands overcoming the complexities and abstractions within climate risk data and its underlying concepts. The task is made even more difficult when considering sensitive issues around the uncertainty of weather predictions, fraying trust in public institutions, rising insurance costs, and unequal abilities to pay for adaptation.

Climate stresses on our homes, neighborhoods, and budgets will only grow in the coming decades. Public officials should act now to incorporate climate adaptation throughout their decisionmaking, investment, and communication processes.