Articles | Volume 7, issue 8
Research article
26 Aug 2014
Research article |  | 26 Aug 2014

The performance of Aeolus in heterogeneous atmospheric conditions using high-resolution radiosonde data

X. J. Sun, R. W. Zhang, G. J. Marseille, A. Stoffelen, D. Donovan, L. Liu, and J. Zhao

Abstract. The European Space Agency Aeolus mission aims to measure wind profiles from space. A major challenge is to retrieve high quality winds in heterogeneous atmospheric conditions, i.e. where both the atmospheric dynamics and optical properties vary strongly within the sampling volume. In preparation for launch we aim to quantify the expected error of retrieved winds from atmospheric heterogeneity, particularly in the vertical, and develop algorithms for wind error correction, as part of the level-2B processor (L2Bp).

We demonstrate that high-resolution data from radiosondes provide valuable input to establish a database of collocated wind and atmospheric optics at 10 m vertical resolution to simulate atmospheric conditions along Aeolus' lines of sight. The database is used to simulate errors of Aeolus winds retrieved from the Mie and Rayleigh channel signals. The non-uniform distribution of molecules in the measurement bin introduces height assignment errors in Rayleigh channel winds up to 2.5% of the measurement bin size in the stratosphere which translates to 0.5 m s−1 bias for typical atmospheric conditions, if not corrected. The presence of cloud or aerosol layers in the measurement bin yields biases in Mie channel winds which cannot be easily corrected and mostly exceed the mission requirement of 0.4 m s−1. The collocated Rayleigh channel wind solution is generally preferred because of smaller biases, in particular for transparent cloud and aerosol layers with one-way transmission above 0.8.

The results show that Aeolus L2Bp, under development, can be improved by the estimation of atmosphere optical properties to correct for height assignment errors and to identify wind solutions potentially detrimental when used in Numerical Weather Prediction.