Improving the accuracy of short-term numerical weather forecasts for the territory of Belarus using the mesoscale WRF model and earth remote sensing data

Abstract

The problem of improving the WRF numerical weather model performance for the territory of Belarus by assimilating the Earth remote sensing data is considered. It is shown that for the winter period, the use of satellite data of high spatial resolution, including on the structure of land use , albedo, leaf index and photosynthetically active radiation absorbed by the underlying surface can reduce a root-mean-square error of the short-term forecast (up to 48 h) of the air surface temperature by 0.53–1.11 °С. For the summer period, on the basis of numerical experiments the optimal correction factor for the land surface albedo was estimated. This made it possible to reduce a root-mean-square error of temperature forecast at the meteorological stations of Belarus for the lead time of +12, +24, +36, and +48 h by an average of 0.30 °С, 0.10 °С, 0.15 °С, and 0.16 °С, respectively.