9A.5 Land Surface Modeling and Data Assimilation at NASA/SPoRT for Improved Situational Awareness and Local Model Initialization

Wednesday, 1 July 2015: 11:15 AM
Salon A-2 (Hilton Chicago)
Bradley T. Zavodsky, NASA/MSFC, Huntsville, AL; and J. L. Case, C. B. Blankenship, and K. D. White

The Short-term Prediction Research and Transition (SPoRT) Center has been running an experimental real-time version of the NASA Land Information System (LIS) since summer 2010 (hereafter “SPoRT-LIS”) over a portion of the Contiguous U.S. The real-time SPoRT-LIS runs the Noah land surface model (LSM) in an offline capacity apart from a numerical weather prediction model, using input operational atmospheric and precipitation analyses from the NCEP Environmental Modeling Center to drive the Noah LSM integration at ~3-km resolution. Its objectives are to (1) produce local-scale information about the soil state for NOAA/National Weather Service (NWS) situational awareness applications such as drought monitoring and assessing areal flooding potential, and (2) provide land surface initialization fields for local modeling initiatives. The SPoRT-LIS ingests real-time vegetation information derived from MODIS to improve energy fluxes and evapotranspiration as vegetation responds to anomalous weather and climatic periods. Recent activities this past year have included ingesting and displaying SPoRT-LIS data into the next generation Advanced Weather Interactive Processing System (AWIPS II) at select NOAA/NWS partnering weather forecast offices (WFOs), evaluating select output fields for applications in drought monitoring and assessing flooding potential, and improving soil moisture estimates through land data assimilation research.

Several initiatives are underway to further improve the character of output SPoRT-LIS land surface fields for better situational awareness and increased accuracy of modeled soil moisture. Retrieved soil moisture estimates from the European Space Agency's Soil Moisture Ocean Salinity (SMOS) mission are assimilated into a research configuration of the SPoRT-LIS. The impact of unique land-cover-based bias correction is explored to optimally assimilate the SMOS retrievals, with validation statistics generated against in situ soil moisture networks. Real-time vegetation is being upgraded to the global daily 4-km VIIRS-based green vegetation fraction that recently went operational at NESDIS. The impact of the VIIRS vegetation on the Noah LSM will be examined and validated against available field campaign data, flux measurements, and/or in situ observations. Additionally, a climatological run of SPoRT-LIS over a full contiguous domain is run at ~3-km resolution to generate county-scale climatologies of total column soil moisture to compare current values against local historical soil moisture for any day of the year. This climatology is expected to greatly improve situational awareness, especially for agricultural-based drought that is typically correlated to dry soil moisture anomalies. This presentation will provide an overview of the land surface modeling activities at SPoRT Center, highlighting the current research activities to improve modeled soil moisture estimates and interactions with NOAA/NWS forecasters using SPoRT-LIS data.

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