Billion-Dollar Weather and Climate Disasters: Time Series

The graphic below helps to visualize how the different types of identified U.S. Billion-dollar disaster events have changed over time. Caution should be used in interpreting any trends based on this graphic for a variety of reasons. For example, inflation has affected our ability to compare costs over time. To reflect this, the graphic also shows events with less than $1 billion in damage at the time of the event, but after adjusting for Consumer Price Index (inflation), now exceed $1 billion in damages.

In 2017, there were 16 weather and climate disaster events with losses exceeding $1 billion each across the United States. More notable than the high frequency of these events is the cumulative cost, which exceeds $300 billion in 2017a new U.S. annual record. The cumulative damage of these 16 U.S. events during 2017 is $306.2 billion, which shatters the previous U.S. annual record cost of $214.8 billion (CPI-adjusted), established in 2005 due to the impacts of Hurricanes Dennis, Katrina, Rita and Wilma.

Milestones to Improve Data Analysis

In May 2012, NOAA's National Centers for Environmental Information -- then known as National Climatic Data Center (NCDC) -- hosted a workshop including academic, federal, and private sector experts to discuss best practices in evaluating disaster costs.

A research article "U.S. Billion-dollar Weather and Climate Disasters: Data Sources, Trends, Accuracy and Biases" (Smith and Katz, 2013) regarding the loss data we use, our methods and any potential bias was published in 2013. This research article found the net effect of all biases appears to be an underestimation of average loss. In particular, it is shown that the factor approach can result in an underestimation of average loss of roughly 10–15%. This bias was corrected during a reanalysis of the loss data to reflect new loss totals.

It is also known that the uncertainty of loss estimates differ by disaster event type reflecting the quality and completeness of the data sources used in our loss estimation. In 2017, seven of the sixteen billion-dollar events (i.e., the 2 inland flooding events, drought, freeze and hurricanes Harvey, Irma and Maria) have higher potential uncertainty values around the loss estimates due to less coverage of insured assets and data latency. The remaining nine events (i.e., the 8 severe storm events and wildfire) have lower potential uncertainty surrounding their estimate due to more complete insurance coverage and data availability. Our newest research defines the cost uncertainty using confidence intervals as discussed in the peer-reviewed article "Quantifying Uncertainty and Variable Sensitivity within the U.S. Billion-dollar Weather and Climate Disaster Cost Estimates" (Smith and Matthews, 2015). This research is a next step to enhance the value and usability of estimated disaster costs given data limitations and inherent complexities.

The most recent analysis offers new graphing options to better visualize event costs over time. These options include: 1) annual U.S. disaster costs for billion-dollar events including 95% confidence interval estimates of cost uncertainty and 2) the 5-year cost mean. The 95% confidence interval (CI) probability is a representation of the uncertainty associated with the disaster cost estimates. Monte Carlo simulations were used to produce the upper and lower bounds (Smith and Matthews, 2015).

For more information, please see: Calculating the Cost of Weather and Climate Disasters.

Citing this information:

NOAA National Centers for Environmental Information (NCEI) U.S. Billion-Dollar Weather and Climate Disasters (2018).