Evaluating the Impact of Land Surface Properties on Simulated Dust Emissions and Air Quality in the Southwest United States

In the Southwestern United States (SW US), dust concentrations peak during the spring due to strong surface winds and dry soil moisture, which can lead to degraded air quality and harmful effects on public health. Thus, it is important to realistically forecast dust emissions and transport processes in order to provide accurate air quality alerts to the public. Previous studies have highlighted a moist bias in soil moisture from the Global Forecast System (GFS) over the SW US, which can influence too weak of dust emissions within regional chemistry modeling systems such as the Weather Research and Forecasting with Chemistry (WRF-Chem) model. This study examines how more realistic soil and vegetation information impacts simulated dust emissions within WRF-Chem over the SW US for several well-observed cases: 27 April 2014, 23 March 2017, 31 March 2017, and 17 April 2018. Our control (CTRL) simulations utilize Global Forecast System (GFS) reanalysis data for initial and lateral meteorological conditions. For our experimental (EXP) runs, we update the GFS soil moisture and green vegetation fraction (GVF) fields with the NASA Land Information System (LIS) product. The 3-km NASA LIS product is developed from data assimilation of precipitation and soil moisture from satellites, rain gauges, and radar estimates at 3-km resolution. A suite of satellite and ground-based data sets were utilized for our validation effort including the ground-based data from the Aerosol Robotic Network (AERONET), AOD from both the Moderate Resolution Imaging Spectroradiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR), and particulate matter (PM) concentrations from EPA Air Quality System (AQS) and Interagency Monitoring of Protected Visual Environments (IMPROVE). Overall, we found that the EXP runs outperformed the CTRL as drier soil conditions within the EXP permitted stronger dust emissions, and consequently, degraded air quality conditions across the region.