A New Methodology for Assimilation of Initial Soil Moisture Fields in Weather Prediction Models Using Meteosat and NOAA Data

Abstract

In this study, a simple method is described and tested for deriving initial soil moisture fields for numerical weather prediction purposes using satellite imagery. Recently, an algorithm was developed to determine surface evaporation maps from high- and low-resolution satellite data, which does not require information on land use and synoptic data. A correction to initial soil moisture was calculated from a comparison between the evaporation fields produced by a numerical weather prediction model and the satellite algorithm. As a case study, the method was applied to the Iberian Peninsula during a 7-day period in the summer of 1994. Two series of short-term forecasts, initialized from a similar initial soil moisture field, were run in parallel: a control run in which soil moisture evolved freely and an experimental run in which soil moisture was updated daily using the simple assimilation procedure. The simple assimilation resulted in a decrease of the bias of temperature and specific humidity at 2-m height during the daytime and a small decrease of the root-mean-square error of these quantities. The results show that the surface evaporation maps, derived from the satellite data, contain a signal that may be used to assimilate soil moisture in numerical weather prediction models.