Developing a Strongly Coupled Land-Atmosphere Data Assimilation for UFS with JEDI

The overarching goal of this study is to implement a strongly coupled land-atmosphere data assimilation capability into the NCEP Unified Forecast System (UFS) using the JCSDA Joint Effort for Data Assimilation Integration (JEDI), focusing on the following areas: 1) Implement into JEDI the capability to assimilate in-situ and satellite-measured soil moisture (e.g., SMAP, SMOS, etc.), conventional surface observations, and surface Mesonet observations (e.g., 2-m temperature and humidity, 10-m wind), along with other atmospheric observations into the UFS through a strongly coupled land-atmosphere data assimilation framework with the Noah-MP land surface model and GFSv17; 2) Examine the influence of the strongly coupled land-atmosphere data assimilation system on near-surface and boundary layer atmospheric conditions as well as their impacts on severe weather forecasting; 3) Evaluate the impacts of the strongly coupled land-atmosphere data assimilation system on medium-range weather forecasting and sub-seasonal to seasonal (S2S) prediction.

We conducted ensemble forecasting experiments in early development with various land surface perturbations. We evaluated the effectiveness of different perturbation methods on medium-range weather prediction using the UFS model. We also examined the cross-covariances between land and atmosphere. The Soil Moisture Active Passive (SMAP) satellite-derived soil moisture observations and near-surface atmospheric data (2-m temperature, humidity, and 10-m wind) are simultaneously assimilated into a coupled land-atmosphere data assimilation configuration. The impacts of the coupled data assimilation on the short and medium-range weather forecast, especially the prediction of near-surface atmospheric conditions with the UFS model, are examined. The progress, ongoing, and future work plan will be presented.