Characterization of Aeolus Measurement Errors by Triple Collocation Analysis Over Western Europe

Abstract

The resolution of regional numerical weather prediction (NWP) models has continuously been increased over the past decades, in part, thanks to the improved computational capabilities. At such small scales, the fast weather evolution is driven by wind rather than by temperature and pressure. Over the ocean and in the free troposphere, where global NWP models are not able to resolve wind scales below 150 km, regional models provide wind dynamics and variance equivalent to 25 km or lower. However, although this variance is realistic, it often results in spurious circulation (e.g., moist convection systems), thus misleading weather forecasts and interpretation. An accurate and consistent initialization of the evolution of the 3-dimensional (3-D) wind structure is therefore essential in regional weather analysis. The wind profiles provided by the ESA Aeolus satellite mission will help filling the observational gap in the upper air and hopefully improve regional weather forecast. For a correct assimilation into NWP models, the observations need to be characterized in terms of their spatial scales and measurement errors. To this end, the triple collocation method, widely used in scatterometry, is applied to Aeolus observations collocated with Mode-S aircraft observations and ECMWF model output. An algorithm for collocating 4D wind observations from Aeolus, Mode-S and ECMWF over a region of Western Europe will be presented, along with measurement errors obtained from triple collocation.