Assimilation of SMOS brightness temperatures in the ECMWF Integrated Forecasting System

The assimilation of Soil Moisture and Ocean Salinity (SMOS) brightness temperature (T-B) data in numerical weather prediction systems influences the state of the soil, which in turn affects the exchange of energy and water fluxes between the soil and the near-surface atmosphere, with potential implications for the prediction of atmospheric variables. In this paper, the impact of assimilating SMOS T-B alone or in combination with screen-level observations and Advanced Scatterometer (ASCAT) soil moisture retrievals is assessed. Independent quality controlled insitu soil moisture observations belonging to several networks included in the International Soil Moisture Network, were used to validate the quality of both the new soil moisture analyses and the skill to predict soil moisture up to 5 days ahead. The impact on atmospheric variables is indirect and was evaluated through computation of the forecast skill at different lead times. The analysis period was selected to be around the boreal summer, a period of the year when evaporatranspiration fluxes are stronger, and when it is therefore expected that the assimilation of remote-sensing data provides the largest impact on the state of the soil. The results show that the soil moisture state benefits from the direct assimilation of SMOS T-B, especially in better representing the temporal variations of soil moisture. The skill of atmospheric variables is mainly driven by the screen-level observations. Despite the clear benefits to the soil state, remote-sensing data need to be used with screen-level variables to add value to the state of the atmosphere, pointing to inconsistencies in the physical coupling between the land and near-surface components of the ECMWF Earth system.