National Aeronautics and Space Administration

SOIL MOISTURE ASSIMILATION

Accurately initializing soil moisture can improve seasonal forecasts of streamflow and of mid-latitude summer precipitation and air temperature over land. Soil moisture impacts are mediated through land-atmosphere feedback and memory in root zone soil moisture anomalies. Skill in atmospheric forecasts stemming from land initialization demonstrates that such land-atmosphere feedback exists. Land data assimilation systems use numerical land surface models along with observations of soil moisture and precipitation to provide enhanced estimates of soil moisture conditions.

Research highlights

• Quantifying Improvements to Streamflow Forecasts Stemming from Improved Soil Moisture Observations (2013)

• Soil Moisture Assimilation and Precipitation Error Modeling in the Ensemble-based GEOS-5 Land Data Assimilation System (2012)

• Estimating Root Mean Square Errors in Remotely Sensed Soil Moisture over Continental Scale Domains (2012)

• Global Calibration of the GEOS-5 L-band Microwave Radiative Transfer Model over Non-Frozen Land Using SMOS Observations (2012)

• Assimilation of passive and active microwave soil moisture retrievals (2011)

• The MERRA-Land data product: Assessment and enhancement of MERRA land surface hydrology estimates (2011)

• The contributions of precipitation and soil moisture observations to the skill of soil moisture estimates in a land data assimilation system (2010)

• Snow and soil moisture contributions to seasonal streamflow prediction (2009)

• Contribution of soil moisture retrievals to land assimilation products (2008)

• An adaptive ensemble Kalman filter for land data assimilation (2008)