Notes

Outline

A Synthetic Study of Near-Surface Soil Moisture Assimilation for North America 1,2Jeffrey P. Walker and 2Paul R. Houser 1Universities Space Research Association 2NASA/Goddard Space Flight Center

Why Assimilate Soil Moisture? Accurate soil moisture forecasts are necessary for accurate predictions of precipitation. LSM spin-up does not guarantee correct soil moisture initialization. Errors in soil moisture forecasts result from: The memory of errors in LSM soil moisture initialization. Errors in atmospheric forcing data. Errors in LSM physics. Errors in soil and topographic data.

What is Data Assimilation ? The process of finding the model representation which is most consistent with the observations.

The Kalman-Filter Forecasting Equations States: Covariances: Observation Equation Surface Moisture: Updating Equations States: Covariances:

The Catchment-Based LSM srfexc = srfexc – es – srflow + i + a rzexc  =  rzexc – ev + srflow – rzflow + b catdef = catdef + et – rzflow + baseflow + c where a, b and c are correction terms to            ensure mass balance Using a first-order Taylor series expansion:

Numerical Experiments “Truth” Data Set Spin-up catchment-based LSM for 1987 using ISLSCP forcing data. Run the simulation for 1987 using ISLSCP forcing data and output surface moisture data as “observations”. Open Loop Data Set Degrade the soil moisture prognostic variable spin-up states to make the catchments artificially wet. Run the simulation for 1987 using ISLSCP forcing data. Assimilated Data Set Degrade the soil moisture prognostic variable spin-up states to make the catchments artificially wet (as for the open loop). Run the simulation for 1987 using ISLSCP forcing data. Assimilate the surface “observations” once every 3 days using the Kalman-filter.

Soil Moisture: January 30

Soil Moisture: July 31

Soil Moisture: December 29

“Errors” in Assimilated Moisture: 1

“Errors” in Assimilated Moisture: 2 Soil Depth

Monthly Evapotranspiration

Monthly Runoff

Conclusions A methodology for initialization of seasonal-to- interannual predictions that does not rely on model spin-up has been developed. A surface measurement of soil moisture may be used to correct the entire soil moisture profile. Assimilation of soil moisture has a positive impact on the water and energy budgets. Soil moisture assimilation performs best for regions with shallower soils; particularly depths less than 3m.