soil moisture assimilation in ncep global forecast system

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