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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 - PowerPoint PPT Presentation
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1
Soil Moisture Assimilation in NCEP Global Forecast System
Weizhong Zheng1, Jerry Zhan2, Jiarui Dong1, Michael Ek1
1Environmental Modeling Center, National Centers for Environmental Prediction (NCEP/EMC), National
Weather Service, NOAA2National Environmental Satellite, Data and Information
Service/Satellite Applications and Research (NESDIS/STAR), NOAA
3rd COSMOS Workshop, 10-12 December 2012University of Arizona, Tucson, Arizona, USA
2
NOAA Center for Weather and Climate Prediction (NCWCP), College Park, Maryland
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
Soil Moisture Data assimilation in NCEP GFS
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
Testing with SMOS Soil Moisture
GFS_CTL
EnKF-CTL GFS_EnKF
SMOS
Comparison of soil moisture 18Z, 1-17 June 2012
GFS Top Layer SM Validation With USDA-SCAN Measurements
1-17 of June, 2012
East CONUS (28 sites)
West CONUS (25 sites)
Whole CONU
S
RMSE Bias Corr-Coef RMSE Bias Corr-Coef RMSE Bias Corr-Coef
CTL 0.149 0.015 0.458 0.122 0.049 0.488 0.136 0.031 0.472
EnKF 0.139 0.001 0.596 0.117 0.046 0.559 0.129 0.023 0.579
Surface skin Temperature 2 m temperature
Comparison of Tsfc, T2m 18Z, 1-17 June 2010
SMOS soil moisture assimilation generally decreased GFS surface temperature forecasts
Sensible Heat Flux Latent Heat Flux
Comparison of SHF and LHF 18Z, 1-17 June 2010
SMOS soil moisture assimilation increased GFS latent heat flux and decreased sensible heat flux estimates
EnKF: 60-84h
EnKF: 84-108h
CTL: 60-84h Obs
Obs
Precipitation forecast 24h Accum (mm) Ending at 12Z 4 June 2012
CTL: 84-108h Improved !
Topography,Soils
Land Cover, Vegetation Properties
Meteorological Forecasts,
Analyses, and/or Observations
Snow Soil MoistureTemperature
Land Surface Models
Data Assimilation Modules
Soil Moisture &
Temperature
EvaporationSensible Heat
Flux
Runoff
SnowpackProperties
Inputs OutputsPhysics Applications
Weather/Climate
Water Resources
HomelandSecurity
Military Ops
Natural Hazards
NASA Land Information System
From Christa Peters-Lidard (2007)
Assimilating SMOS in NCEP GFSImproved 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
Results Summary