Leonhard Scheck, Hans-Ertel-Center for weather research, LMU Munich

Using visible and near-infrared satellite observations for convective-scale data assimilation

Bernhard Mayer, Martin Weissmann


Satellite images contain a wealth of information about convective activity and are therefore seen as a important type of observation for convective scale data assimilation (DA). However, in operational DA systems currently only clear sky thermal infrared and microwave radiance observations are used, which mainly provide temperature and humidity information. Sufficiently fast and accurate forward operators for visible and near-infrared radiances, which contain information about cloud properties, are not available. The lack of suitable operators is related to the fact, that multiple scattering makes radiative transfer at solar wavelengths complicated and computationally expensive.

To address this problem, a fast forward operator for visible and near-infrared reflectance observations based on a new method is currently in development. The operator relies on a loop-up table based method that is sufficiently accurate and orders of magnitude faster than conventional radiative transfer solvers for the visible spectrum. A preliminary version of the operator that simulates synthetic MSG-SEVIRI images from COSMO-DE model output has been completed and implemented in the pre-operational km-scale Ensemble Data Assimilation (KENDA) system of DWD. We present this novel operator and first results from assimilation experiments.

File available here