Cloud Type Identification Algorithm To Simulate Msg Infrared Radiance Using The Radiative Transfer Model Rttov And Aladin Forecasting Output

Résumé: In numerical weather prediction (NWP), the big challenger in satellite data assimilation is the presence of cloud essentially the convective cloud. In this work, we focus only on the simulation of SEVIRI radiances of MSG2 satellite, using the radiative transfer operator RTTOV in its 9.3 version, by introducing the fields provided by the model ALADIN/Algeria. This simulation can have two objectives. The first one is the validation of the simulated radiances for data assimilation; the second one is to generate synthetic images that will serve as a help tool to the localization of the storms using the short time forecast. Many improvements have been made in the source code for these operators in order to try to resolve this problem. This latest model RTTOV assimilates cumuliform clouds, stratiform clouds and the ones of the upper levels as cirrus. For the simulation of these clouds, we will developed an algorithm for the identification of cloud types and cloud structure, based on the vertical profile of the cloud liquid water (CLW) and the cloud solid water (CSW) forecasted by ALADIN model at all the forty three (43) levels of the RTTOV model. A comparative study using the MSG2 data has shown on a number of weather situations, a good correlation between simulated and observed radiances, but this correlation is locally random for isolated clouds.

Publié dans la revue: Rеvuе des Energies Renouvelables