GOES Evapotranspiration and Drought Product System (GET-D)

Monitoring evapotranspiration (ET) and the extent and severity of agricultural drought is an important component of food and water security and world crop market assessment. However, no spatially distributed land surface ET product is available operationally from satellite observations at present. ET products are in high demand in National Center for Environmental Prediction (NCEP) for validating the Noah land surface model output and satellite based drought data products for monthly drought briefings. Additionally, ET/drought information is greatly needed by USDA FAS/NASS/ARS for world crop forecasts and US agricultural production monitoring. Under these circumstances, a GOES Evapotranspiration and Drought Product System (GET-D) has been developed to operationally generate daily ET and drought maps over the North America domain using GOES land surface temperature (LST), satellite-based vegetation information and solar insolation observations. The operational ET and drought monitoring system is generated with the Atmosphere-Land Exchange Inverse model (ALEXI), which is built on the two-source energy (TSEB) approach and partitions the composite surface radiometric temperature into characteristic soil and canopy temperatures, based on the fraction of vegetation cover. The ALEXI surface energy balance model was specifically designed to minimize the need for ancillary meteorological data while maintaining a physically realistic representation of land-atmosphere exchange of energy and water over a wide range of vegetation cover conditions. The advantages make the ALEXI model capable of routine, long-term mapping of ET and soil moisture stress. The outputs of the GET-D system include the daily ET product and 2, 4, 8 and 12 week composite of the Evaporative Stress Index (ESI) computed from the ET daily estimates over North America at a spatial resolution of 8 km. The ET and drought monitoring products from GET-D are validated against multi-source in situ ET observations and various existing drought indices, e.g. US Drought Monitor, Standardized Precipitation Index (SPI), etc. The software structure, system components and validation results will be presented.