Towards unified land data assimilation at ECMWF: Soil and snow temperature analysis in the Simplified Extended Kalman Filter

Numerical weather prediction requires well-defined initial conditions at the interface between land and atmosphere. Weather centres such as the European Centre for Medium-Range Weather Forecasts (ECMWF) currently rely on a variety of data assimilation schemes to analyze different land variables in their operational forecast system.

Recent activities at ECMWF are towards a unified and more consistent land data assimilation system that can provide more accurate initial conditions for the atmospheric forecast. The first step is to replace the current 1D Optimal Interpolation (1D-OI) so far used for single-layer soil and snow temperature analyses and integrate these variables into the most advanced ensemble-based Simplified Extended Kalman Filter (SEKF) applied in operations for multi-layer soil moisture analysis.

The focus is on the technical developments to integrate the first-layer snow and multi-layer soil temperature into the SEKF control vector and on the evaluation of the new implementation with respect to the impact on the atmospheric forecast skill. A sensitivity analysis regarding Jacobians computed from the covariances between screen-level 2-metre temperature observation and soil and snow temperature reveals better representation of small-scale features associated to land heterogeneity when compared to the empirically obtained sensitivity used in the 1D-OI.

A series of NWP experiments were conducted over a three-month summer and winter period to test the benefit of several configurations of the SEKF. Compared to the 1D-OI, the SEKF leads to significant improvements in the 2-metre temperature forecast with seasonal differences in the verification against own analyses and to slightly improved results in the validation using independent synoptic observations. The work presented will lay the foundation for further developments including the integration of additional land variables, such as snow depth and vegetation-related variables, into the SEKF and the investigation of quasi-strong land-atmosphere coupling.