SOIL MOISTURE MEASUREMENTS FROM MICROWAVE SENSORS AT NOAA/NESDIS: DATA PRODUCTS AND APPLICATIONS

S. Kalluri¹, X. Zhan¹, L. Zhou¹, J. Yin², J. Liu²

¹NOAA NESDIS, ²ESSIC/CISESS, University of Maryland at College Park

Soil moisture is a vital state variable influencing land surface dynamics across hydrological, meteorological, and climatological contexts. The Soil Moisture Operational Product System (SMOPS), developed by the National Environmental Satellite, Data, and Information Service (NESDIS) of National Oceanic and Atmospheric Administration (NOAA), has been operationally providing satellite soil moisture observational data products for scientific studies and numerical weather and water predictions. The SMOPS algorithm retrieves soil moisture from a variety of microwave sensors including AMSR series, ASCAT series, and the dedicated soil moisture missions, SMAP and SMOS. New satellite observations capable of measure soil moisture are continuously evaluated as older missions go off line. However, inconsistencies in measuring capabilities of the soil moisture constellation sensors, gaps in spatial coverage led to pronounced fluctuations in data quality across distinct versions and notable uncertainties for climatological studies and prolonged data assimilation operations. To address disconnects, a machine learning algorithm has been developed and implemented to create a consistently processed soil moisture date record from 2002 to present. This presentation will highlight this effort as well as showcase some high impact applications of the NESDIS soil moisture product.