1A.1 Interannual Variability of the Satellite-Observed and WRF-Modeled Soil Moisture in Connection with Dust Events

Monday, 8 January 2018: 8:45 AM
Room 9 C (ACC) (Austin, Texas)
Min Huang, George Mason Univ., Fairfax, VA; and G. R. Carmichael

Dust aerosols affect human life, ecosystems, and the climate. It is important to extend the historical dust records, to better understand their temporal changes, and to use such information to help improve the daily dust forecasting skill as well as the projection of future dust activity under the changing climate. In this study, we develop dust records from the Moderate Resolution Imaging Spectroradiometer (MODIS) deep blue aerosol product, as well as dynamic dust source areas based on the satellite land cover and vegetation index products for the past decade. The temporal changes of the dust events are discussed in relation to the dynamics of land surface (soil moisture and vegetation) and atmospheric weather conditions (e.g., winds). We first explore the relationships between the dynamic dust source areas and dust activity in Arizona, USA with the ESA Climate Change Initiative (CCI) soil moisture product v03.2, for the period of 2005-2015. This analysis extends what’s been shown in Huang et al. (2015) using an earlier version of the CCI product for the 2005-2013 period. We then relate the interannual variability of dust events in multiple regions (East Asia, Africa, Western US) in the Northern Hemisphere with the NASA Soil Moisture Active Passive (SMAP) soil moisture product and Weather Research and Forecasting (WRF) modeled weather fields, for 2015 and 2016. The variability of identified dust events is shown related to observed or/and simulated weather patterns and surface conditions, suggesting a potential for use of satellite soil moisture and other products to help interpret and predict dust activity. Although multiple WRF simulations show qualitatively consistent soil moisture interannual variability to SMAP, we demonstrate that a number of factors affect the detailed model performance.
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