P-29

A coupled land-atmosphere hybrid variational-ensemble data assimilation system for regional climate application

K. Suzuki (JAMSTEC) and M. Zupanski (CIRA/ CSU)

We develop a coupled land-atmosphere hybrid variational-ensemble data assimilation system to address regional climate applications. In particular, we assimilate the AMSR2 microwave radiances and conventional atmospheric observations. The system incorporates a regional climate model (Advanced Research Weather Research and Forecasting (WRF-ARW), and a hybrid variational-ensemble land data assimilation system based on the Maximum Likelihood Ensemble Filter (MLEF). The observation operator includes the Gridpoint Statistical Interpolation (GSI) and the Joint-simulator. In this presentation, we show the details of the coupled land-atmosphere data assimilation algorithm and the experimental results. Given the fundamental role of forecast error covariance in data assimilation, we first examine the structure of the ensemble-based coupled forecast error covariance by performing a single observation experiment. We also include the information content analysis by calculating the Degrees of Freedom for Signal (DFS) from a single observation.