Optimization of Aeolus Optical Properties Products by Maximum-Likelihood Estimation

Abstract. The European Space Agency (ESA) Earth Explorer Mission, Aeolus, was launched in August 2018 and embarks the first Doppler Wind Lidar in space. Its primary payload, the Aeolus LAser Doppler INstrument (Aladin) is a Ultra Violet (UV) High Spectral Resolution Lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being and HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio. This way, the retrieval is independent of a-priori information. The optical properties are retrieved using the Standard Correct Algorithm (SCA), which is an algebraic inversion scheme to a (partly) ill-posed problem and therefore sensitive to measurement noise. In this work, we rephrase the SCA into a physically constrained Maximum Likelihood Estimation (MLE) problem and demonstrate predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information within the SCA in conjunction with the expected physical bounds concerning the expected range of the lidar ratio. The new MLE algorithm is equally evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aelous data collocated with measurements by a ground-based lidar and the CALIPSO satellite to consolidate and to illustrate the improvements. The largest improvements were seen in the retrieval of the extinction coefficients and lidar ratio ranging up to one order of magnitude or more in some cases due to an effective noise dampening.