International audienceThe ADM-Aeolus is primarily a research and demonstration mission flying the first Doppler wind lidar in space. Flexible data processing tools are being developed for use in the operational ground segment and by the meteorological community. We present the algorithms developed to retrieve accurate and representative wind profiles, suitable for assimilation in numerical weather prediction. The algorithms provide a flexible framework for classification and weighting of measurement-scale (1–10 km) data into aggregated, observation-scale (50 km) wind profiles for assimilation. The algorithms account for temperature and pressure effects in the molecular backscatter signal, and so the main remaining scientific challenge is to produce representative winds in inhomogeneous atmospheric conditions, such as strong wind shear, broken clouds, and aerosol layers. The Aeolus instrument provides separate measurements in Rayleigh and Mie channels, representing molecular (clear air) and particulate (aerosol and clouds) backscatter, respectively. The combining of information from the two channels offers possibilities to detect and flag difficult, inhomogeneous conditions. The functionality of a baseline version of the developed software has been demonstrated based on simulation of idealized case
A B S T R A C T ADM-Aeolus, the wind Lidar under development at ESA, is a High Spectral Resolution Lidar that additionally provides separated information on particles (Mie channel) and molecules (Rayleigh channel). Lidar signals will be accumulated in vertical range bins in order to reach sufficient signal-to-noise ratio for reliable wind estimates. The vertical range bin integration may vary from 250 m near the surface up to 2 km in the upper troposphere and lower stratosphere. Significant attenuation in a range bin changes the nature of the retrieval problem. The commonly used Lidar inversion techniques appear to be inadequate to process bin-accumulated signals. This paper presents the 'L2A processor', conceived to use ADM-Aeolus signals to provide information on aerosol and cloud layers optical properties. The altitude, geometrical depth, optical depth, backscatter-to-extinction ratio and scattering ratio are to be retrieved. The L2A processor algorithms provide a new formulation to the inverse problem for various filling cases of a range bin and it includes a credibility criterion (CC) in order to select the best filling approximation. The effective vertical resolution can be two to four times better than the ADM-Aeolus range bins. The basic concept, the processing algorithms, numerical examples and sensitivity tests are here presented.
Abstract. Even just shortly after the successful launch of the European Space Agency satellite Aeolus in August 2018, it turned out that dark current signal anomalies of single pixels (so-called “hot pixels”) on the accumulation charge-coupled devices (ACCDs) of the Aeolus detectors detrimentally impact the quality of the aerosol and wind products, potentially leading to wind errors of up to several meters per second. This paper provides a detailed characterization of the hot pixels that occurred during the first 1.5 years in orbit. The hot pixels are classified according to their characteristics to discuss their impact on wind measurements. Furthermore, mitigation approaches for the wind retrieval are presented and potential root causes for hot pixel occurrence are discussed. The analysis of the dark current signal anomalies reveals a large variety of anomalies ranging from pixels with random telegraph signal (RTS)-like characteristics to pixels with sporadic shifts in the median dark current signal. Moreover, the results indicate that the number of hot pixels almost linearly increased during the observing period between 2 September 2018 and 20 May 2020 with 6 % of the ACCD pixels affected in total at the end of the period leading to 9.5 % at the end of the mission lifetime. This work introduces dedicated instrument calibration modes and ground processors, which allowed for a correction shortly after a hot pixel occurrence. The achieved performance with this approach avoids risky adjustments to the in-flight hardware operation. It is demonstrated that the success of the correction scheme varies depending on the characteristics of each hot pixel itself. With the herein presented categorization, it is shown that multi-level RTS pixels with high fluctuation are the biggest challenge for the hot pixel correction scheme. Despite a detailed analysis in this framework, no conclusion could be drawn about the root cause of the hot pixel issue.
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