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Soil Moisture Assimilation in NCEP Global Forecast System

Weizhong Zheng 1 , Jerry Zhan 2 , Jiarui Dong 1 , Michael Ek 1 1 Environmental Modeling Center , National Centers for Environmental Prediction ( NCEP/EMC), National Weather Service, NOAA

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Soil Moisture Assimilation in NCEP Global Forecast System

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  1. Weizhong Zheng1, Jerry Zhan2, Jiarui Dong1, Michael Ek1 1Environmental ModelingCenter, National Centers for Environmental Prediction (NCEP/EMC), National Weather Service, NOAA 2National Environmental Satellite, Data and Information Service/Satellite Applications and Research (NESDIS/STAR), NOAA Soil Moisture Assimilation in NCEP Global Forecast System 3rd COSMOS Workshop, 10-12 December 2012 University of Arizona, Tucson, Arizona, USA

  2. NOAA Center for Weather and Climate Prediction (NCWCP), College Park, Maryland

  3. Soil Moisture Data assimilation in NCEP GFS • The simplified ensemble Kalman Filter (EnKF) was embedded in the NCEP GFS to assimilate satellite soil moisture observation. • Future plan: Test assimilation of COSMOS soil moisture measurements. • Data assimilation via the NASA Land Information System (LIS) • Other in situ soil moisture data sets/networks, e.g. Soil Climate Analysis Network (SCAN; www.wcc.nrcs.usda.gov/scan), and others identified by the International Soil Moisture Network (www.ipf.tuwien.ac.at/insitu). • KEY REQUIREMENT FOR NWP OPERATIONS: RELIABLE, NEAR-REALTIME

  4. Testing with SMOS Soil Moisture • Method: A Simple Ensemble Kalman Filter (EnKF) embedded in latest version of GFS latest version • Assimilation time period: 00Z May 1 – June 18, 2012. (GFS/GSI) • Experiments: CTL: Control run EnKF: Sensitivity run • Perturbations: Precipitation, 4 layer soil moisture states

  5. Comparison of soil moisture 18Z, 1-17 June 2012 SMOS GFS_CTL EnKF-CTL GFS_EnKF

  6. GFS Top Layer SM Validation With USDA-SCAN Measurements 1-17 of June, 2012

  7. Comparison of Tsfc, T2m 18Z, 1-17 June 2010 2 m temperature Surface skin Temperature SMOS soil moisture assimilation generally decreased GFS surface temperature forecasts

  8. Comparison of SHF and LHF 18Z, 1-17 June 2010 Sensible Heat Flux Latent Heat Flux SMOS soil moisture assimilation increased GFS latent heat flux and decreased sensible heat flux estimates

  9. Precipitation forecast 24h Accum (mm) Ending at 12Z 4 June 2012 CTL: 60-84h Obs EnKF: 60-84h Obs EnKF: 84-108h CTL: 84-108h Improved !

  10. NASA Land Information System Inputs Physics Outputs Applications Topography, Soils Land Surface Models Soil Moisture & Temperature Weather/ Climate Water Resources Homeland Security Military Ops Natural Hazards Land Cover, Vegetation Properties Evaporation Sensible Heat Flux Meteorological Forecasts, Analyses, and/or Observations Runoff Snow Soil Moisture Temperature Data Assimilation Modules Snowpack Properties From Christa Peters-Lidard (2007)

  11. Results Summary • Assimilating SMOS in NCEP GFS • Improved GFS deeper layer soil moisture estimates comparing with in situ measurements • reduced GFS temperature forecast biases positively; • increased latent heat and decreased sensible heat fluxes for most CONUS regions; • had positve impact on precipitation forecasts. • Future: assimilate SMAP (remote sensing), COSMOS & other in situ measurements

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