A long-running U.S. database that tracks the financial toll of extreme weather events has found new life outside the federal government. The Billion-Dollar Weather and Climate Disasters Database, which was retired by the Trump administration in May, has been relaunched independently and already shows a record-breaking start to 2025.
According to the database’s latest update, the first six months of 2025 have been the most expensive on record, with $101.4 billion in damages from disasters that each exceeded the billion-dollar threshold.
The project, now managed by Climate Central, a nonprofit organization that focuses on climate research and communication, continues to use the same methodology developed under the National Oceanic and Atmospheric Administration (NOAA). Its data helps inform insurers, policymakers, researchers, and citizens about the rising costs of severe weather.
The Economist Behind the Data
The database’s revival is being overseen by Adam Smith, the economist who originally managed it during his time at NOAA. After taking early retirement, Smith joined Climate Central to continue the project, ensuring that decades of consistent and comparable data remain available to the public.
In the first half of 2025 alone, Smith identified 14 separate billion-dollar disasters across the country. These included the Los Angeles wildfires in January and a tornado outbreak that swept through the central United States in March. With several months still remaining in the year — including the most active part of hurricane season — additional events are expected to join the list.
Without the database, researchers say, the public would lose an essential way to monitor how much extreme weather costs the nation each year — a concern given the rising frequency of such events.
Costs Driven by Growth and Climate Change
The data shows that both climate change and population growth are fueling the increase in economic losses. Warmer temperatures are intensifying storms, floods, and fires, while expanding development continues to put more homes and infrastructure in high-risk areas.
According to Smith’s findings, the frequency of billion-dollar disasters has doubled over the last decade. Between 1980 and 2024, the U.S. averaged about nine billion-dollar disasters a year. Over the past five years, that number has jumped to 24 per year, peaking at a record 28 events in 2023.
This year’s figures already suggest a similar pattern, with climate-related destruction spreading across multiple regions — and rising repair costs following close behind.
Wildfires Lead 2025’s Record Damages
So far, 2025 has been dominated by wildfires and severe storms, with no major hurricanes yet making U.S. landfall. The most destructive event to date, the Los Angeles wildfires, caused an estimated $61.2 billion in damage, making them the most expensive wildfires in American history.
Entire communities in Southern California were devastated, forcing large-scale evacuations and leaving thousands displaced. The fires’ unprecedented scale was fueled by prolonged drought, record heat, and dense development along the wildland-urban interface — a clear sign of how both human activity and environmental conditions are converging to heighten disaster risks.
Public Demand Restores a Critical Dataset
When NOAA’s version of the Billion-Dollar Disasters Database was discontinued, it ended more than four decades of government-led recordkeeping. The decision was part of a broader effort to cut climate data programs across federal agencies, but it quickly drew backlash from scientists, insurers, and lawmakers who relied on the dataset for decision-making.
In response, Climate Central stepped in to rebuild and host the database, hiring Smith to ensure consistency. The new version picks up directly from where NOAA’s list ended in 2024 and uses the same methodology — combining insurance records, federal data, and economic modeling to measure losses.
Experts note that maintaining continuity is critical for understanding how disasters evolve over time and how climate trends affect economic vulnerability.
