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Vulnerability Assessment of Dust Storms in the United States under a Changing Climate Scenario
Citation:
Garcia, V., K. Stevens, Chris Nolte, T. Spero, AND J. Crooks. Vulnerability Assessment of Dust Storms in the United States under a Changing Climate Scenario. 2015 CMAS Conference, Chapel Hill, NC, October 07, 2015.
Impact/Purpose:
The National Exposure Research Laboratory (NERL) Atmospheric Modeling and Analysis Division (AMAD) conducts research in support of EPA mission to protect human health and the environment. AMAD research program is engaged in developing and evaluating predictive atmospheric models on all spatial and temporal scales for forecasting the air quality and for assessing changes in air quality and air pollutant exposures, as affected by changes in ecosystem management and regulatory decisions. AMAD is responsible for providing a sound scientific and technical basis for regulatory policies based on air quality models to improve ambient air quality. The models developed by AMAD are being used by EPA, NOAA, and the air pollution community in understanding and forecasting not only the magnitude of the air pollution problem, but also in developing emission control policies and regulations for air quality improvements.
Description:
Severe weather events, such as flooding, drought, forest fires, and dust storms can have a serious impact on human health. Dust storm events are not well predicted in the United States, however they are expected to become more frequent as global climate warms through the 21st century. Understanding what causes dust storms will facilitate the prediction of vulnerability to dust storm events within the context of a changing climate. In turn, this will inform adaptation and mitigation strategies to help protect human health, and prevent crop and property damage. Using data on dust storms in the United States from 1992 to 2010 collected by the U.S. National Weather Service, and output from the Weather Research and Forecasting Model containing meteorological variables for the affected portion of the country, we will predict vulnerability to dust storms under future climate scenarios. More specifically, a logit regression model will be used to investigate the association between these meteorological variables and the presence or absence of a dust storm event.ﾠ The regression model will be applied to generate probability maps of dust storm events in the United States under a changing climate scenario. A comparison will also be performed of the dust product simulated by the Community Multiscale Air Quality (CMAQ) model. The results of this project will be extended to determine the effects of dust storms on population health.
