Assimilation of screen level observations by variational soil moisture analysis

Inaccurate specification of soil moisture contents can result in forecast errors up to several degrees centigrade. Since direct measurements are rarely available, a variational method has been developed that assimilates synoptic measurements of 2m-temperature in order to specify the moisture contents of the two soil layers of the Local Model at Deutscher Wetterdienst. The analyzed values minimize a cost functional that expresses the differences between model forecast and observed screen-level temperatures. The minimization is performed highly efficiently and only two additional forecasts are required but neither tangent linear nor adjoint. Background state and background error covariance matrix are updated at each analysis step in a Kalman-filter-like cycled scheme, which takes a model error into account. The soil moisture assimilation shows improved 2m-temperature forecasts in case of high radiative forcing by up to 3 degreesC for small areas in the presented 6-week trial run. It proved stability and robustness for general weather conditions and has become operational at DWD for the LM on 14 March 2000.