Assimilating Advanced Scatterometer Winds in a High-Resolution Limited Area Model Over Northern Europe

Abstract

Satellite-based scatterometer ocean surface wind measurements have been shown to improve global weather forecasts through data assimilation. However, these scatterometer data are not yet widely assimilated operationally in high-resolution regional models. This paper demonstrates the impact of assimilating Advanced Scatterometer (ASCAT) winds on the analysis and forecasts in observation system experiments using the convection-resolving operational HARMONIE-AROME model system over Northern Europe. At high latitudes, ASCAT provides dense observational data of meteorological phenomena, such as cold-air mesocyclones, particular in this region. Observation errors for ASCAT used in assimilation were found to be consistent with what was found in analysis of observation versus model background statistics, and no spatial error correlations were found on the 50 km separation distances. The largest impact of the assimilation of ASCAT winds was found over the ocean and in the coastal regions. Forecast verification against synoptic observations at coastal stations showed on average improvements for mean sea-level pressure and to some extent for 10-m wind speed on short forecast range. This varied only a little when changing the assimilation settings. Decreasing the data thinning distance from 100 to 50 km further improved forecasts, while shortening the assimilation window from 3 to 1 h did not yield a consistent forecast impact. The observation system experiments have confirmed that scatterometer winds contribute to improved analysis and forecasts in high-resolution regional modeling. This demonstrates general applicability of scatterometer observations for improving weather forecasts at high latitudes.

Keywords

• Satellite applications
• weather forecasting
• wind