To investigate the impact of climate-driven disasters on communities and whether they’re receiving the assistance they need, we compiled data from federal agencies to assess 1) how many climate-fueled disasters a county had experienced, 2) how much disaster preparedness funding they had received through the Federal Emergency Management Agency and 3) what each county looked like demographically.
Our county-by-county data included disaster information from several sources:
- Federal disaster declaration data by county was our primary data source for the number of disasters a county experienced. We included only major disaster declarations for wildfires, hurricanes and floods. Climate scientists told us that, though climate change is likely impacting tornadoes, mudslides and some other types of disasters, it is certainly worsening hurricanes, floods and wildfires.
Disaster declarations do not cover every event a community has experienced. They help distinguish between minor and major incidents, but research shows that presidential disaster declarations can be politically influenced.
- Because experts told us that it was particularly difficult to receive a major disaster declaration for wildfires, we included the “risk to potential structures” values from the Forest Service’s Wildfire Risk to Communities database.
- Because sea-level rise and coastal flooding do not yet trigger disaster declarations, we used the FEMA National Risk Index’s “coastal flooding, annualized frequency” value, which estimates the number of times a county is likely to experience a coastal flood over the course of a year.
About this series
The federal government knows that millions of Americans will need to move to avoid the most punishing impacts of climate change, but the country offers little organized assistance for such relocation. When communities ask the government for help, they face steep barriers — a particular problem for communities of color.
To find communities that were interested in relocating, some experts told us to consider places hit by multiple disasters over a 30-year period — the typical home-mortgage term. Others told us that communities hit multiple times over the past five years were more likely to be interested in relocating now. We reviewed data over both time spans.
We ultimately defined hard-hit counties as those that had three or more federally declared major wildfire, hurricane or flooding disasters in the last five calendar years (from 2017 to 2021), because we’re primarily interested in places that are currently facing intensifying disasters. Because the FEMA spending data was provided by fiscal year, we also looked at the demographics of counties that were hard hit over the five fiscal years ending in 2020.
FEMA has moved more people out of flood zones through its buyouts than any other federal agency, acquiring some 50,000 properties since the Hazard Mitigation Assistance programs began funding buyouts in 1989.
To measure that spending, we used FEMA’s Hazard Mitigation Assistance projects data. We calculated the total spent in each county and the per-person tally.
FEMA noted a limitation to its dataset: In some cases, projects were carried out in multiple counties. The FEMA staffer who manages this dataset said there were relatively few such projects and the primary county listed is a good estimate for the amount spent in each county.
Side note: FEMA’s data included a grant of $518 million in Greene County, New York, which the county had no record of receiving. We suppressed that grant from the total amount for Greene, leaving the county with 17 other grants totaling about $4.6 million over the three-decade period.
We also obtained a dataset through a Freedom of Information Act request of completed FEMA buyouts by address from the start of the Hazard Mitigation Assistance programs in 1989 through 2017. The data contained some inconsistencies, such as misspelled place names. After correcting those issues, we totaled buyouts by county. This information is searchable in the dataset embedded in our story.
To assess communities’ ability to relocate, we added several demographic measures to our data:
- Variables from the Centers for Disease Control and Prevention’s Social Vulnerability Index that experts told us were relevant to our research. Those included the poverty rate, the percentage of people in a county without a high school diploma and percentage of nonwhite residents.
- Race and ethnicity variables from the 5-year 2019 American Community Survey.
How we used this data
The data helped us identify communities for field reporting, focusing on those that were hard hit by disasters, had received little assistance through FEMA’s programs and appeared, based on demographic and socioeconomic data, less likely to be able to relocate without government assistance.
This led us to focus on certain communities in Louisiana and the Carolinas pummeled by hurricanes, counties in California hard hit by wildfires and communities in the Midwest repeatedly hit by river flooding.
We also analyzed the demographic data alongside the disaster and spending data to determine whether federal aid was disproportionately benefiting certain types of communities.
For that finding, we compared FEMA hazard mitigation spending over the five fiscal years ending in fall 2020, the most recent time frame with robust data, to disaster declarations over that same period.
We also analyzed FEMA spending over the entire period for which any hazard mitigation project data is available (1989 through 2021). The findings were similar for both time spans.
Additionally, we worked with Carolynne Hultquist, a disaster researcher at Columbia University, to perform a regression analysis across various states. This assessed the relationship between climate disasters over a 30-year timeframe to the demographic makeup of the counties within those states. This allowed us to say, for example, that in Virginia, counties with a greater share of Black residents were much more likely to have experienced a higher number of hurricanes or floods over the past 30 years.
How we did it
Months spent data reporting
Number of datasets used
To perform this analysis, reporters interviewed experts, including federal officials and scholars, to find the datasets that would shed light on climate relocation. The team spent 12 months identifying, compiling and analyzing the data.
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