Abstract

Abstract. Shortly after the successful launch of the European Space Agency's wind mission Aeolus, co-located airborne wind lidar observations were performed in central Europe; these observations employed a prototype of the satellite instrument – the ALADIN (Atmospheric LAser Doppler INstrument) Airborne Demonstrator (A2D). Like the direct-detection Doppler wind lidar on-board Aeolus, the A2D is composed of a frequency-stabilized ultra-violet (UV) laser, a Cassegrain telescope and a dual-channel receiver to measure line-of-sight (LOS) wind speeds by analysing both Mie and Rayleigh backscatter signals. In the framework of the first airborne validation campaign after the launch and still during the commissioning phase of the mission, four coordinated flights along the satellite swath were conducted in late autumn of 2018, yielding wind data in the troposphere with high coverage of the Rayleigh channel. Owing to the different measurement grids and LOS viewing directions of the satellite and the airborne instrument, intercomparison with the Aeolus wind product requires adequate averaging as well as conversion of the measured A2D LOS wind speeds to the satellite LOS (LOS*). The statistical comparison of the two instruments shows a positive bias (of 2.6 m s−1) of the Aeolus Rayleigh winds (measured along its LOS*) with respect to the A2D Rayleigh winds as well as a standard deviation of 3.6 m s−1. Considering the accuracy and precision of the A2D wind data, which were determined from comparison with a highly accurate coherent wind lidar as well as with the European Centre for Medium-Range Weather Forecasts (ECMWF) model winds, the systematic and random errors of the Aeolus LOS* Rayleigh winds are 1.7 and 2.5 m s−1 respectively. The paper also discusses the influence of different threshold parameters implemented in the comparison algorithm as well as an optimization of the A2D vertical sampling to be used in forthcoming validation campaigns.

Highlights

  • On 22 August 2018, the fifth Earth Explorer mission of the European Space Agency (ESA) – Aeolus – was launched into space, marking an important milestone in the centennial history of atmospheric observing systems (Stith et al, 2018; Kanitz et al, 2019; Reitebuch et al, 2019; Straume et al, 2019)

  • This paper presents the results from the first airborne validation campaign of the Aeolus mission and demonstrates the methodology used to compare the different data sets from the A2D and the satellite instrument

  • An aerial interpolation algorithm was used for the adaptation of the A2D data to the Aeolus measurement grid, whereas conversion of the measured A2D line of sight (LOS) winds to the satellite LOS was realized with the aid of model wind data

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Summary

Introduction

On 22 August 2018, the fifth Earth Explorer mission of the European Space Agency (ESA) – Aeolus – was launched into space, marking an important milestone in the centennial history of atmospheric observing systems (Stith et al, 2018; Kanitz et al, 2019; Reitebuch et al, 2019; Straume et al, 2019). This paper presents the results from the first airborne validation campaign of the Aeolus mission and demonstrates the methodology used to compare the different data sets from the A2D and the satellite instrument. This work shows how to account for the different LOS directions in order to make the wind data sets comparable This procedure is required for the A2D and for any other Cal/Val instrument that measures only one component of the wind vector, such as the LEANDRE New Generation (LNG; Bruneau et al, 2015) that is foreseen to be deployed on airborne campaigns for Aeolus validation. An optimized range gate setting of the A2D is proposed that aims to improve the validation capabilities of the instrument in forthcoming airborne campaigns that are to be conducted during the Aeolus mission (Sect. 4.6)

ALADIN and the ALADIN Airborne Demonstrator
The A2D direct-detection wind lidar system
The Aeolus wind data product
Response calibrations
A2D wind results from the underflight on 22 November 2018
Aeolus wind results from the underflight on 22 November 2018
Assessment of the A2D performance by comparison with the 2 μm DWL
Comparison of A2D and Aeolus wind data
Adaptation of the measurement grid
Consideration of the different viewing geometries
Statistical comparison of A2D and Aeolus with ECMWF data
Statistical comparison of A2D and Aeolus data
Influence of the coverage ratio and mean distance thresholds
Optimization of A2D range gate settings
Findings
Summary and Conclusion
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