Abstract

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).

Highlights

  • Aeolus is a European Space Agency (ESA) Earth Explorer mission, launched on 22 August 2018 as part of the Living Planet Programme

  • As part of the German initiative EVAA (Experimental Validation and Assimilation of Aeolus observations), this paper presents the evaluation of Aeolus winds using operational collocated radiosonde data from the Global Observing System (GOS) as reference

  • The total variance of the difference between radiosonde observations and Aeolus Horizontal LOS wind component (HLOS) winds σv2al is the sum of the variance resulting from the Aeolus wind instrumental error σA2eolus, the variance resulting from the radiosondes wind observational error σR2S, and the variance caused by the representativeness error σr2_RS (Weissmann et al, 2005)

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Summary

Introduction

Aeolus is a European Space Agency (ESA) Earth Explorer mission, launched on 22 August 2018 as part of the Living Planet Programme. A. Martin et al.: Validation of Aeolus wind observations wind lidar called ALADIN (Atmospheric LAser Doppler INstrument) which is the first European lidar and the first ever Doppler wind lidar (DWL) in space (Stoffelen et al, 2005; Reitebuch, 2012; ESA, 2008). A crucial prerequisite for the use of meteorological observations in NWP data assimilation systems is a good knowledge of their statistical errors and the minimization of systematic observation errors For this purpose, uncertainty assessment and validation through extensive comparisons with reference data is an essential requirement to assimilate these novel observations in NWP models and fully exploit the provided wind information. In preparation for the Aeolus mission, a prototype of the satellite instrument, the ALADIN Airborne Demonstrator (A2D), was deployed to test the wind measurement principles under real atmospheric conditions in several measurement campaigns, and to provide information on quality control algorithms (Lux et al, 2018).

Aeolus L2B wind product
Radiosonde data and collocation criteria
Model data for the validation
Representativeness errors for the Aeolus wind validation
Statistical metrics
Systematic and random differences
Estimation of the Aeolus HLOS wind error
Representativeness error σr
Model error σb and radiosonde wind observational error σRS
Aeolus wind instrumental error σAeolus
Rayleigh wind bias dependence on latitude and orbit phase
Findings
Summary and discussion
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