This study assesses the quality of Aeolus wind measurements over the tropical Atlantic. The results identified the accuracy and precision of the Aeolus wind measurements and the potential source of errors. For instance, the study revealed atmospheric conditions that can deteriorate the measurement quality, such as weaker laser signal in cloudy or dusty conditions, and confirmed the presence of an orbital-dependant bias. These results can help to improve the Aeolus wind measurement algorithm.

Quasi-biennial oscillation (QBO) of the stratospheric tropical winds is an important mode of climate variability but is not well reproduced in free-running climate models. We use the novel global wind observations by the Aeolus satellite and radiosondes to show that the QBO is captured well in three modern reanalyses (ERA-5, JRA-55, and MERRA-2). Good agreement is also found also between Aeolus and reanalyses for large-scale tropical wave modes in the upper troposphere and lower stratosphere.

With the launch of the Aeolus satellite, higher-accuracy wind products became available. This research was carried out to validate the assimilated wind products by testing their effect on the WRF-Chem model predictive ability of dust processes. This was carried out for the eastern Mediterranean and Middle East region for two 2-month periods in autumn and spring 2020. The use of the assimilated products improved the dust forecasts of the autumn season (both quantitatively and qualitatively).

Global wind profiles from the Aeolus satellite mission are an important recent substitute for the Global Observing System, showing an overall positive impact on numerical weather prediction forecasts. This study highlights atmospheric dynamic phenomena constituting pathways for significant improvement of Aeolus for future studies, including large-scale tropical circulation systems and the interaction of tropical cyclones undergoing an extratropical transition with the midlatitude waveguide.

This study investigates vertical localization based on a convection-permitting 1000-member ensemble simulation. We derive an empirical optimal localization (EOL) that minimizes sampling error in 40-member sub-sample correlations assuming 1000-member correlations as truth. The results will provide guidance for localization in convective-scale ensemble data assimilation systems.

A comprehensive data set of airborne lidar water vapour profiles is compared with ERA5 reanalyses for a robust characterization of the vertical structure of the mid-latitude lower-stratospheric moist bias. We confirm a moist bias of up to 55 % at 1.3 km altitude above the tropopause and uncover a decreasing bias beyond. Collocated O₃ and H₂O observations reveal a particularly strong bias in the mixing layer, indicating insufficiently modelled transport processes fostering the bias.

In August 2018, the first wind lidar Aeolus was launched into space and has since then been providing data of the global wind field. The primary goal of Aeolus was the improvement of numerical weather prediction. To verify the quality of Aeolus wind data, DLR performed four airborne validation campaigns with two wind lidar systems. In this paper, we report on results from the two later campaigns, performed in Iceland and the tropics.

We discuss the influence of different quality control schemes on the results of Aeolus wind product validation and present statistical tools for ensuring consistency and comparability among diverse validation studies with regard to the specific error characteristics of the Rayleigh-clear and Mie-cloudy winds. The developed methods are applied for the validation of Aeolus winds against an ECMWF model background and airborne wind lidar data from the Joint Aeolus Tropical Atlantic Campaign.

The Aeolus satellite measures global height resolved profiles of wind along a certain line-of-sight. However, for atmospheric dynamics research, wind measurements along the three cardinal axes are most useful. This paper presents methods to convert the measurements into zonal and meridional wind components. By combining the measurements during ascending and descending orbits, we achieve good derivation of zonal wind (equatorward of 80° latitude) and meridional wind (poleward of 70° latitude).

In August 2018, the ESA launched the first Doppler wind lidar into space. In order to calibrate the instrument and to monitor the overall instrument conditions, instrument spectral registration measurements have been performed with Aeolus on a weekly basis. Based on these measurements, the alignment drift of the Aeolus satellite instrument is estimated by applying tools and mathematical model functions to analyze the spectrometer transmission curves.

The article discusses modifications in the wind retrieval of the ALADIN Airborne Demonstrator (A2D) – one of the key instruments for the validation of Aeolus. Thanks to the retrieval refinements, which are demonstrated in the context of two airborne campaigns in 2019, the systematic and random wind errors of the A2D were significantly reduced, thereby enhancing its validation capabilities. Finally, wind comparisons between A2D and Aeolus for the validation of the satellite data are presented.

During the VAL-OUC campaign, we established a coherent Doppler lidar (CDL) network over China to verify the Level 2B (L2B) products from Aeolus. By the simultaneous wind measurements with CDLs at 17 stations, the L2B products from Aeolus are compared with those from CDLs. To our knowledge, the VAL-OUC campaign is the most extensive so far between CDLs and Aeolus in the lower troposphere for different atmospheric scenes. The vertical velocity impact on the HLOS retrieval from Aeolus is evaluated.

This paper summarizes the identification and correction of one of the most important systematic error sources for the wind measurements of the ESA satellite Aeolus. It depicts the effects of small temperature variations in the primary telescope mirror on the quality of the wind products and describes the approach to correct for it in the near-real-time processing. Moreover, the performance of the correction approach is assessed, and alternative approaches are discussed.

The work assesses the frequency stability of the laser transmitters on board Aeolus and discusses its influence on the quality of the global wind data. Excellent frequency stability of the space lasers is evident, although enhanced frequency noise occurs at certain locations along the orbit due to micro-vibrations that are introduced by the satellite’s reaction wheels. The study elaborates on this finding and investigates the extent to which the enhanced frequency noise increases the wind error.

This study demonstrates the benefits of using both visible and infrared satellite channels to evaluate clouds in numerical weather prediction models. Combining these highly resolved observations provides significantly more and complementary information than using only infrared observations. The visible observations are particularly sensitive to subgrid water clouds, which are not well constrained by other observations.

This paper reports on dark current signal anomalies of the detectors used on board the ESA's Earth Explorer satellite Aeolus during the first 1.5 years in orbit. After introducing sophisticated algorithms to classify dark current anomalies according to their characteristics, the impact of the different kinds of anomalies on wind measurements is discussed. In addition, mitigation approaches for the wind retrieval are presented and potential root causes are discussed.