A new snow analysis scheme, based on a 2D Optimum Interpolation, was implemented at ECMWF in 2010. In addition to conventional snow depth observations, the high resolution (4km) NOAA/NESDIS (National Oceanic and Atmospheric Administration - National Environmental Satellite, Data, and Information Service) IMS (Interactive Multisensor Snow and Ice Mapping System) snow cover product is used to analyze snow depth. Performances of the new snow analysis are presented and compared against the previous snow analysis (Cressman analysis using 24km NESDIS IMS data). The new snow analysis is in better agreement with ground observations. In addition, skills are evaluated in terms of screen level parameter forecast skills and atmospheric circulation impact. The new snow analysis is shown to improve 2 meter temperature forecasts. And it is also shown to have a positive and significant impact on the northern hemisphere geopotential field at 500mb for more than 5-day forecasts range.

Soil moisture initialization is also crucial for NWP. New generations of satellites, such as ASCAT (Advanced Scatterometer) and SMOS (Soil Moisture and Ocean Salinity) provide highly suitable data from active and passive microwave sensors for soil moisture remote sensing. For NWP applications, satellite data monitoring provides a continuous evaluation of observations and first guess departures (observation minus model) values at global and regional scales. It also allows identifying systematic features in the data set and supports bias correction activities. Monitoring results of SMOS brightness temperature and ASCAT surface soil moisture data are presented. Based on ground measurements available in Europe, USA, Africa and Australia, ASCAT and SMOS surface soil moisture products are evaluated and compared with ECMWF surface soil moisture analyses. Results show good performances of the three products to capture surface soil moisture annual cycle as well as short term variability. Both monitoring and ground validation results show high complementarity between remotely sensed products and ECMWF soil moisture. This highlights the potential of using satellite data for NWP soil moisture analysis. In order to make it possible to combine use of satellite, in situ and proxy observations to analyze soil moisture, ECMWF implemented an Extended Kalman Filter (EKF) soil moisture analysis which is used for operational NWP. The EKF soil moisture analysis and its recent developments to use active (ASCAT) and passive (SMOS) microwave satellite data are presented. Data assimilation results are presented, and based on a series of numerical experiments the impact of assimilating microwave data on both soil moisture and NWP performances is assessed.

The EKF is well suited for using future satellite data such as Soil Moisture Active and Passive (SMAP) data. It also opens the possibility to analyze other variables, such as Leaf Area Index.