Technical Implementation of SMOS Data in the ECMWF Integrated Forecasting System

Abstract

The launch of the Soil Moisture and Ocean Salinity (SMOS) satellite of the European Space Agency opens the way to using a new type of satellite data that are very sensitive to soil moisture for numerical weather prediction. The European Centre for Medium-Range Weather Forecasts (ECMWF) has developed an operational chain which makes it possible to process SMOS data in near real time (NRT) and compare it with a model equivalent. This process has been very challenging. The main reasons are the particular characteristics of the SMOS observation system and the large volume of data. Despite these obstacles, SMOS data are being processed successfully in NRT within the ECMWF Integrated Forecasting System (IFS). The ultimate objective is to assimilate these data in the IFS. It is expected to have an impact on the weather forecast at short and medium ranges. Prior to assimilation experiments, the quality of the data has to be assessed. This can be done through monitoring activities. Monitoring is a routine task performed with all satellite data, and among other things, it makes it possible to localize temporal (or spatial) bias or drifts in the data, thus providing NRT reports to the calibration and validation teams, which can act accordingly. In this letter, the implementation of SMOS data in the ECMWF IFS for monitoring purposes is discussed. The system was developed using a simulated file for the NRT processor, and it was tested using real data from the first year since the launch date.