Characterization of dark current signal measurements of the ACCDs used on board the Aeolus satellite

Abstract

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.

The impact of Aeolus wind retrievals on ECMWF global weather forecasts

“…The Rayleigh-clear random error increased during the FM-A laser period (from mission start to mid-June 2019), with the rate of degradation increasing with time; this is evident in the troposphere and the lower stratosphere, as seen on Figure 2. This was due to: an increasing percentage of uncorrected "hot pixels" (Weiler et al, 2020); a downward trend in atmospheric signal levels due to decreasing output laser energy (Lux et al, 2020a;Reitebuch et al, 2020a); and seasonal changes in the M1-mirror-temperature dependent bias variations (which are largest at Northern Hemisphere summer solstice; see Section 3.4), which manifests as increased random error in daily average statistics.…”

“…During the mission so far, the ECMWF monitoring has helped to detect several Aeolus anomalies, and explanations have been found in collaboration within the Aeolus DISC, for example, Weiler et al (2020). Also, the NWP monitoring has supported ESA and industry to perform instrument adjustments, which has led to improvements in the quality of the wind retrievals.…”

ALADIN laser frequency stability and its impact on the Aeolus wind error

“…4a, where the standard deviation is plotted for each observation of the regarded period. Data gaps in the timeline are due to special operations that are regularly performed in each week, such as instrument spectral registration (ISR; Reitebuch et al, 2018), the so-called down under dark experiment (Weiler et al, 2021a) or orbit correction maneuvers. The figure also illustrates the percentage of observations that are affected by enhanced frequency fluctuations.…”

“…The wind error assessment is based on the data from 2 weeks of FM-B operation in August and September/October 2020, as listed in Tables 1 and 4. These datasets already include the correction for the influence of the temperature variations across the primary telescope mirror on the wind results (M1 correction), which was implemented prior to the operational assimilation of the Aeolus wind data in NWP by various weather services Weiler et al, 2021b). The Rayleigh and Mie wind observations were extracted from the L2C product, which, in addition to a copy of the Aeolus L2B product, includes ECMWF model winds (analysis and background) provided on the same horizontal and vertical grid.…”

“…This was made possible by the identification of and correction for large systematic errors which had strongly degraded the wind data quality in the initial phase of the mission (Kanitz et al, 2020;. Firstly, dark current signal anomalies on single ("hot") pixels of the Aeolus detectors which had led to wind errors of up to 4 m s −1 were recognized and successfully accounted for by the implementation of dedicated calibration instrument modes (Weiler et al, 2021a). Secondly, biases that were found to be closely correlated with small variations in the temperature distribution across the primary telescope mirror Weiler et al, 2021b) were corrected.…”