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

Weiler, Fabian; Kanitz, Thomas; Wernham, Denny; Rennie, Michael; Huber, Dorit; Schillinger, Marc; Saint-Pé, Olivier; Bell, Ray; Parrinello, Tommaso; Reitebuch, Oliver

doi:10.5194/amt-2020-458

Cited by 9 publications

(10 citation statements)

References 38 publications

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“…Thus, on average over the validation period about 70 % of the Rayleigh and 76 % of the Mie winds are available for the analysis. On 14 June 2019 a correction scheme for dark current signal anomalies of single pixels (hot pixels) on the accumulation-charge-coupled devices (ACCDs) of the Aeolus detectors has been implemented into the Aeolus operational processor chain (Weiler et al, 2020). All measurements before 14 June 2019 affected by hot pixels are excluded from the validation statistic.…”

Section: Aeolus L2b Wind Productmentioning

confidence: 99%

Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents

et al. 2021

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Abstract. In August 2018, the first Doppler wind lidar, developed by the European Space Agency (ESA), was launched on board the Aeolus satellite into space. Providing atmospheric wind profiles on a global basis, the Earth Explorer mission is expected to demonstrate improvements in the quality of numerical weather prediction (NWP). For the use of Aeolus observations in NWP data assimilation, a detailed characterization of the quality and the minimization of systematic errors is crucial. This study performs a statistical validation of Aeolus observations, using collocated radiosonde measurements and NWP forecast equivalents from two different global models, the ICOsahedral Nonhydrostatic model (ICON) of Deutscher Wetterdienst (DWD) and the European Centre for Medium-Range Weather Forecast (ECMWF) Integrated Forecast System (IFS) model, as reference data. For the time period from the satellite's launch to the end of December 2019, comparisons for the Northern Hemisphere (23.5–65∘ N) show strong variations of the Aeolus wind bias and differences between the ascending and descending orbit phase. The mean absolute bias for the selected validation area is found to be in the range of 1.8–2.3 m s−1 (Rayleigh) and 1.3–1.9 m s−1 (Mie), showing good agreement between the three independent reference data sets. Due to the greater representativeness errors associated with the comparisons using radiosonde observations, the random differences are larger for the validation with radiosondes compared to the model equivalent statistics. To achieve an estimate for the Aeolus instrumental error, the representativeness errors for the comparisons are determined, as well as the estimation of the model and radiosonde observational error. The resulting Aeolus error estimates are in the range of 4.1–4.4 m s−1 (Rayleigh) and 1.9–3.0 m s−1 (Mie). Investigations of the Rayleigh wind bias on a global scale show that in addition to the satellite flight direction and seasonal differences, the systematic differences vary with latitude. A latitude-based bias correction approach is able to reduce the bias, but a residual bias of 0.4–0.6 m s−1 with a temporal trend remains. Taking additional longitudinal differences into account, the bias can be reduced further by almost 50 %. Longitudinal variations are suggested to be linked to land–sea distribution and tropical convection that influences the thermal emission of the earth. Since 20 April 2020 a telescope temperature-based bias correction scheme has been applied operationally in the L2B processor, developed by the Aeolus Data Innovation and Science Cluster (DISC).

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Section: Aeolus L2b Wind Productmentioning

confidence: 99%

Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents

et al. 2021

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“…Registration (Reitebuch et al, 2018), Down Under Dark Experiment (Weiler et al, 2020) or orbit correction maneuvers. The figure also illustrates the percentage of observations that are affected by enhanced frequency fluctuations.…”

Section: Frequency Stability Of the Aladin Laser Transmittersmentioning

confidence: 99%

“…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, 2020). Secondly, biases that were found to be closely correlated with small variations in the temperature distribution across the primary telescope mirror (Rennie and Isaksen, 2020a) could be corrected.…”

Section: Introductionmentioning

confidence: 99%

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

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Lemmerz

Weiler

et al. 2021

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Abstract. The acquisition of atmospheric wind profiles on a global scale was realized by the launch of the Aeolus satellite, carrying the unique Atmospheric LAser Doppler INstrument (ALADIN), the first Doppler wind lidar in space. One major component of ALADIN is its high-power, ultraviolet (UV) laser transmitter which is based on an injection-seeded, frequency-tripled Nd:YAG laser and fulfills a set of demanding requirements in terms of pulse energy, pulse length, repetition rate as well as spatial and spectral beam properties. In particular, the frequency stability of the laser emission is an essential parameter which determines the performance of the lidar instrument, as the Doppler frequency shifts to be detected are on the order of 108 smaller than the frequency of the emitted UV light. This article reports the assessment of the ALADIN laser frequency stability and its influence on the quality of the Aeolus wind data. Excellent frequency stability with pulse-to-pulse variations of about 10 MHz (root mean square) is evident for over more than two years of operations in space despite the permanent occurrence of short periods with significantly enhanced frequency noise (> 30 MHz). The latter were found to coincide with specific rotation speeds of the satellite's reaction wheels, suggesting that the root cause are micro-vibrations that deteriorate the laser stability on time scales of a few tens of seconds. Analysis of the Aeolus wind error with respect to ECMWF model winds shows that the temporally degraded frequency stability of the ALADIN laser transmitter has only minor influence on the wind data quality on a global scale, which is primarily due to the small percentage of wind measurements for which the frequency fluctuations are considerably enhanced. Hence, although the Mie wind bias is increased by 0.3 m·s−1 at times when the frequency stability is worse than 20 MHz, the small contribution of 4 % from all wind results renders this effect insignificant (

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“…This is an official reprocessing from PDGS and contains a number of improvements of several deficiencies closely examined by ESA and DISC. This is an improved treatment for removing spurious outliers induced by dark current signals (hot pixels) (Weiler et al, 2020).…”

Section: Datasets and Level-2b Processingmentioning

confidence: 99%

“…Such is a systematic error arising due to a so-called dark current signal anomalies of single Accumulation Charge-Coupled Device (ACCD) pixels (i.e. "hot pixel") (Weiler et al, 2020) or a significant source of wind systematic error which has been found to be correlated with the temperature gradients across the Atmospheric averaged), the main goal of this paper is to explore the impact of uncertainty in modelled temperature and pressure fields for the retrieval of Rayleigh HLOS winds.…”

Section: Introductionmentioning

confidence: 99%

Comment on amt-2021-38

2021

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The retrieval of wind from the first Doppler wind lidar of Europen Space Agency (ESA) launched in space in August 2018 is based on a series of corrections necessary to provide observations of a quality useful for Numerical Weather Prediction (NWP). In this paper we examine properties of the Rayleigh-Brillouin correction necessary for the retrieval of horizontal lineof-sight wind (HLOS) from a Fabry-Perot interferometer. This correction is taking into account the atmospheric stratification, namely temperature and pressure information that are provided by a NWP model as suggested prior launch. Since NWP models contain errors the main goal in the study is to evaluate the impact of these errors on the HLOS sensitivity by comparing the Integrated Forecast System (IFS) and Action de Recherche Petite Echelle Grande Echelle (ARPEGE) global model temperature and pressure short term forecasts collocated with the Aeolus orbit. The model error is currently not taken into account in the computation of the HLOS error estimate since its contribution is believed small. This study largely confirms this statement to be a valid assumption, although it also shows that model errors could locally (i.e. jet-stream regions, below 700 hPa over both earth poles and as well in stratosphere) be significant. For a future Aeolus follow-on missions this study suggests to consider realistic estimations of model errors in the HLOS retrieval algorithms, since this will lead to an improved estimation of the Rayleigh-Brillouin sensitivity uncertainty contributing to the HLOS error estimate and better exploitation of space lidar winds in NWP systems.

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

Cited by 9 publications

References 38 publications

Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents

Validation of Aeolus winds using radiosonde observations and numerical weather prediction model equivalents

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

Comment on amt-2021-38

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