Aeolus is the first Doppler wind lidar (DWL) to measure wind profiles from space. Aeolus is an ESA (European Space Agency) explorer mission with the objective to retrieve winds from the collected atmospheric return signal which is the result of Mie and Rayleigh scattering of laser-emitted light by atmospheric molecules and particulates. The focus of this paper is on winds retrieved from instrument Mie channel collected data, that is, originating from Mie scattering by atmospheric aerosols and clouds. The use of simulated data from numerical weather prediction (NWP) models is a widely accepted and proven concept for the monitoring of the performance of many meteorological instruments, including Aeolus. Continuous monitoring of Aeolus Mie channel winds against model winds from the European Centre for Medium-Range Weather Forecasts (ECMWF) has revealed systematic errors in retrieved Mie winds. Following a reverse engineering approach, the systematic errors could be traced back to imperfections of the data in the calibration tables which serve as input for the on-ground wind processing algorithms. A new algorithm, denoted NWP calibration, makes use of NWP model winds to generate an updated calibration table. It is shown that Mie winds retrieved by making use of the NWP-based calibration tables show reduced systematic errors, not only when compared to NWP model winds but also when compared to an independent dataset of very-high-resolution aircraft wind data. The latter gives high confidence that the NWP-based calibration algorithm does not introduce model-related errors into retrieved Aeolus Mie winds. Based on the presented results in this paper, the NWP-based calibration table, as part of the level-2B wind processing, has become part of the operational processing chain since 01 July 2021.
Gert-Jan Marseille, Jos de Kloe, Uwe Marksteiner, Oliver Reitebuch, Michael Rennie, Siebren de Haan. NWP calibration applied to Aeolus Mie channel winds
Journal: Quarterly Journal of the Royal Meteorological Society, Volume: 148, Year: 2022, First page: 1020, Last page: 1034, doi: https://doi.org/10.1002/qj.4244