The Joint Aeolus Tropical Atlantic Campaign (JATAC) conducted in 2022 in Cabo Verde has provided quantitative lidar measurements, particularly from the NASA Langley High-Altitude Lidar Observatory (HALO) on board DC-8 aircraft, for process-level understanding of tropical dynamics, as well as for satellite validation. For the first time, the optical properties of particles (i.e. backscatter, extinction, attenuated backscatter coefficients, and depolarization ratios) have been measured for extended tropospheric sections collocated with the Aeolus satellite overpasses with limited geolocation and time offsets. This has contributed to the evaluation of the Aeolus Level-2A (L2A) aerosol optical properties product. In addition, localized aerosol profiles were measured by the ground-based multiwavelength Raman polarization and water vapour lidar PollyXT.In this study, we assess the quality of the Aeolus L2A product retrieved with the standard correct algorithm (SCA) and the maximum likelihood estimation (MLE) as part of the September 2022 dataset reprocessed with the L2A processor, version 16. The focus is given to the 355 nm aerosol retrievals given at finer horizontal resolution, i.e. the so-called Aeolus measurement level at approximate to 18 km. They are compared to the 532 nm HALO airborne profiles that are converted to 355 nm using the backscatter & Aring;ngstr & ouml;m exponent. HALO and PollyXT polarization lidars also provide insights into the L2A algorithm's limitations when looking at non-spherical particles such as Saharan dust. Even though it has no cross-polarized component, the Aeolus measurements can be corrected using collocated observations with such instruments that include both co-polarized and cross-polarized components of the backscattered light. Moreover the cross-validation with independent lidar measurements enables estimation of the lower limits for Aeolus backscatter detection.

Dédiée aux sciences de l'atmosphère, au climat et à d'autres domaines connexes, tels que l'océanographie ou la glaciologie, La Météorologie, révisée par des pairs et publiée en français, s'adresse aux professionnels de la météo et du climat, aux enseignants, aux étudiants, aux amateurs et aux utilisateurs. La Météorologie a succédé en 1925 à l'Annuaire de la Société météorologique de France (1852-1924) qui avait lui-même succédé à l'Annuaire météorologique de la France (1849-1851).

Aeolus carried the first Doppler wind lidar to measure wind profiles from space. Aeolus was a European Space Agency explorer mission with the objective to retrieve winds data from the collected atmospheric return signal that is the result of Mie and Rayleigh scattering of laser emitted light by atmospheric molecules and particulates. During the course of the mission the quality of Aeolus winds measured in clear‐air conditions from Rayleigh‐channel‐collected data, so called Rayleigh‐clear winds, improved substantially. The same is true for winds measured in cloudy and aerosol‐rich atmospheric conditions from Mie‐channel‐collected data, the so‐called Mie‐cloudy winds. For the latter conditions, good quality winds can in principle also be obtained from Rayleigh‐channel‐collected data, the so‐called Rayleigh‐cloudy winds, if contamination of the purely molecular signal by Mie scattering is well addressed. We assess a linear and nonlinear correction for Mie contamination, the latter with the aid of numerical weather prediction model data for determing the correction parameters. We show that the nonlinear correction is able to provide unbiased Rayleigh‐cloudy winds. This makes Rayleigh‐cloudy winds suitable for use in numerical weather prediction, but also for direct comparison with other wind observations obtained in cloudy conditions, such as atmospheric motion wind vectors.

The European Space Agency (ESA) Earth Explorer Mission Aeolus was launched in August 2018, carrying the first Doppler wind lidar in space. Its primary payload, the Atmospheric LAser Doppler INstrument (ALADIN), is an ultraviolet (UV) high-spectral-resolution lidar (HSRL) measuring atmospheric backscatter from air molecules and particles in two separate channels. The primary mission product is globally distributed line-of-sight wind profile observations in the troposphere and lower stratosphere. Atmospheric optical properties are provided as a spin-off product. Being an HSRL, Aeolus is able to independently measure the particle extinction coefficients, co-polarized particle backscatter coefficients and the co-polarized lidar ratio (the cross-polarized return signal is not measured). This way, the retrieval is independent of a priori lidar ratio information. The optical properties are retrieved using the standard correct algorithm (SCA), which is an algebraic inversion scheme and therefore sensitive to measurement noise. In this work, we reformulate the SCA into a physically constrained maximum-likelihood estimation (MLE) problem and demonstrate a predominantly positive impact and considerable noise suppression capabilities. These improvements originate from the use of all available information by the MLE in conjunction with the expected physical bounds concerning positivity and the expected range of the lidar ratio. To consolidate and to illustrate the improvements, the new MLE algorithm is evaluated against the SCA on end-to-end simulations of two homogeneous scenes and for real Aeolus data collocated with measurements by a ground-based lidar and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. The largest improvements were seen in the retrieval precision of the extinction coefficients and lidar ratio ranging up to 1 order of magnitude or more in some cases due to effective noise dampening. In real data cases, the increased precision of MLE with respect to the SCA is demonstrated by increased horizontal homogeneity and better agreement with the ground truth, though proper uncertainty estimation of MLE results is challenged by the constraints, and the accuracy of MLE and SCA retrievals can depend on calibration errors, which have not been considered.

In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design.

The European Space Agency (ESA)’s Earth Explorer Aeolus was launched in August 2018 carrying the world’s first spaceborne wind lidar, the Atmospheric Laser Doppler Instrument (ALADIN). ALADIN uses a high spectral resolution Doppler wind lidar operating at 355nm to determine profiles of line-of-sight wind components in near-real-time (NRT). ALADIN samples the atmosphere from 30km altitude down to the Earth’s surface or to the level where the lidar signal is attenuated by optically thick clouds.The global wind profiles provided by ALADIN help to improve weather forecasting and the understanding of atmospheric dynamics as they fill observational gaps in vertically resolved wind profiles mainly in the tropics, southern hemisphere, and over the northern hemisphere oceans. Since 2020, multiple national and international weather centres (e.g. ECMWF, DWD, Météo France, MetOffice) assimilate Aeolus observations in their operational forecasting. Additionally, the scientific exploitation of the Aeolus dataset has started.A main prerequisite for beneficial impact and scientific exploitation is data of sufficient quality. Such high data quality has been achieved through close collaboration of all involved parties within the Aeolus Data Innovation and Science Cluster (DISC), which was established after launch to study and improve the data quality of Aeolus products. The tasks of the Aeolus DISC include the instrument and platform monitoring, calibration, characterization, retrieval algorithm refinement, processor evolution, quality monitoring, product validation, and impact assessment for NWP.The achievements of the Aeolus DISC for the NRT data quality and the one currently available reprocessed dataset will be presented. The data quality of the Aeolus wind measurements will be described and an outlook on planned improvements of the dataset and processors will be provided.

Since several years, the number of aerosol data coming from lidar has grown and improved in quality. These new datasets are providing a valuable information on the vertical distribution of aerosols which is missing in the AOD (Aerosol Optical Depth), which has been used so far in aerosols analysis. The launch of AEOLUS in 2018 has increased the interest in the assimilation of the aerosol lidar information. In parallel, the ground-based network EARLINET (European Aerosol Research LIdar NETwork) has grown to cover the Europe with good quality data. Assimilation of these data in the ECMWF/CAMS (European Centre for Medium-range Weather Forecasts / Copernicus Atmosphere Monitoring Service) system is expected to provide improvements in the aerosol analyses and forecasts.Three preliminary studies have been done in the past four years using AEOLUS data (A3S-ESA funded) and EARLINET data (ACTRIS-2 and EUNADIC-AV, EU-funded). These studies have allowed the full development of the tangent linear and adjoint code for lidar backscatter in the ECMWF's 4D-VAR system. These developments are now in the operational model version in research mode. The first results are promising and open the path to more intake of aerosol lidar data for assimilation purposes. The future launch of EARTHCARE (Earth-Cloud Aerosol and Radiation Explorer) and later ACCP (Aerosol Cloud, Convention and Precipitation) might even upgrade the use of aerosol lidar data in COMPO-IFS (Composition-Integrated Forecast system).The most recent results using AEOLUS data (for October 2019 and April 2020) and using EARLINET data (October 2020) will be shown in this presentation. The output will be compared to the CAMS operational aerosol forecast as well as to independent data from AERONET (AErosol Robotic NETwork).

The Data Innovation and Science Cluster (DISC) is a core element of ESA's data quality strategy for the Aeolus mission, which was launched in August 2018. Aeolus provides for the first-time global observations of vertical profiles of horizontal wind information by using the first Doppler wind lidar in space. The Aeolus DISC is responsible for monitoring and improving the quality of the Aeolus aerosol and wind products, for the upgrade of the operational processors as well as for impact studies and support of data usage. It has been responsible for multiple significant processor upgrades which reduced the systematic error of the Aeolus observations drastically. Only due to the efforts of the Aeolus DISC team members prior to and after launch, the systematic error of the Aeolus wind products could be reduced to a global average below 1 m/s which was an important pre-requisite for making the data available to the public in May 2020 and for its use in operational weather prediction. In 2020, the reprocessing of earlier acquired Aeolus data, another important task of the Aeolus DISC, also started. In this way, also observations from June to December 2019 with significantly better quality could be made available to the public, and more data will follow this and next year. Without the thorough preparations and close collaboration between ESA and the Aeolus DISC over the past decade, many of these achievements would not have been possible.

The Aladin instrument on-board the ESA Earth Explorer satellite Aeolus is a UV high spectral resolution Doppler Wind Lidar. The main mission product is profiles of horizontally projected line-of-sight winds, and the instrument design is therefore optimized to measure Doppler shifts of the atmospheric backscatter signals compared to the UV light emitted at ~355 nm (ESA, 2008; Stoffelen, 2005). Since the lidar backscatter contains information on the location of optically thin aerosol and cloud layers and cloud tops, spin-off products have been developed to retrieve aerosol and cloud backscatter and extinction coefficient and lidar ratio profile products (ESA, 2008; Flamant, 2008; Flamant, 2017). The advantage of a high spectral resolution lidar is that it measures molecular and particle backscatter separately in two dedicated channels. Still, some contributions from molecular backscatter exists in the measurements from the Fizeau channel and vice versa. This channel cross-talk requires correction during the product retrieval. The Aeolus L2A operational aerosol and cloud retrieval algorithm is applying the so-called high spectral resolution retrieval method for the calculation of the particle and extinction backscatter coefficient products. The algorithm, developed at IPSL and Météo-France, is called the Standard Correct Algorithm (SCA) (Flamant, 2008; Flamant, 2017). High signal noise is obtained due to ever-decreasing laser energies and instrument receive path transmission. As a result, the Aeolus SCA optical properties retrieval is hampered. Particularly the ill-posed particle extinction coefficient retrieval is severely affected. In the past, attempts were made to mitigate nonphysical optical properties by measures like zero-flooring or signal accumulation in even coarser range gates (Flamant, 2017). Their success was limited. An alternative noise suppression approach by Maximum Likelihood Estimation has therefore been prototyped that permits the retrieval of extinction coefficients and lidar ratios solely within pre-defined physical bounds. The optical properties are fitted to the 24 Aeolus atmospheric range gates within single atmospheric columns, minimizing the corresponding distance to the observed L1B useful signals measured by both spectrometers. This up to 48-dimensional non-linear regression problem is solved by means of the L-BFGS-B algorithm (Zhu, 1997). The method has proven its usefulness in noise suppression with astonishing efficiency. Particularly, the retrieved extinction coefficient profiles are less noisy, clearly revealing atmospheric layers also visible in the L1B useful signal profiles. The method is validated on end-to-end simulations and in-orbit observations. References ESA, ADM-Aeolus Science Report. ESA SP-1311, ESA Communication Production Office, 121 pp., 2008, available on http://www.esa.int/aeolus. Flamant, P. H., Cuesta, J., Denneulin, M.-L., Dabas, A., Huber, D. ADM-Aeolus retrieval algorithms for aerosol and cloud products, Tellus, 60A, 273-286, 2008, https://doi.org/10.1111/j.1600-0870.2007.00287.x. Flamant, P. et al. ADM-Aeolus L2A Algorithm Theoretical Baseline Document, 2017, available on https://earth.esa.int/aos/AeolusCalVal. Stoffelen, A. et al. The atmospheric dynamics mission for global wind field measurement, Bulletin of the American Meteorological Society, 86, 73-88, 2005, https://doi.org/10.1175/BAMS-86-1-73. Zhu, C., Byrd R. H. and Nocedal, J. L-BFGS-B: Algorithm 778: L-BFGS-B, FORTRAN routines for large scale bound constrained optimization, ACM Transactions on Mathematical Software, 23 (4), 550-560, 1997, https://doi.org/10.1145/279232.279236.

Aeolus carries the Atmospheric LAser Doppler INstrument (ALADIN), the first high-spectral-resolution lidar (HSRL) in space. Although ALADIN is optimized to measure winds, its two measurement channels can also be used to derive optical properties of atmospheric particles, including a direct retrieval of the lidar ratio. This paper presents the standard correct algorithm and the Mie correct algorithm, the two main algorithms of the optical properties product called the Level-2A product, as they are implemented in version 3.12 of the processor, corresponding to the data labelled Baseline 12. The theoretical basis is the same as in Flamant et al. (2008). Here, we also show the in-orbit performance of these algorithms. We also explain the adaptation of the calibration method, which is needed to cope with unforeseen variations of the instrument radiometric performance due to the in-orbit strain of the primary mirror under varying thermal conditions. Then we discuss the limitations of the algorithms and future improvements. We demonstrate that the L2A product provides valuable information about airborne particles; in particular, we demonstrate the capacity to retrieve a useful lidar ratio from Aeolus observations. This is illustrated using Saharan dust aerosol observed in June 2020.

In September 2020, extremely strong wildfires in the western United States of America (i.e., mainly in California) produced large amounts of smoke, which was lifted into the free troposphere. These biomass‐burning‐aerosol (BBA) layers were transported from the US west coast toward central Europe within 3–4 days turning the sky milky and receiving high media attention. The present study characterizes this pronounced smoke plume above Leipzig, Germany, using a ground‐based multiwavelength‐Raman‐polarization lidar and the aerosol/cloud product of ESA’s wind lidar mission Aeolus. An exceptional high smoke‐AOT >0.4 was measured, yielding to a mean mass concentration of 8 μg m −3 . The 355 nm lidar ratio was moderate at around 40–50 sr. The Aeolus‐derived backscatter, extinction and lidar ratio profiles agree well with the observations of the ground‐based lidar PollyXT considering the fact that Aeolus’ aerosol and cloud products are still preliminary and subject to ongoing algorithm improvements.

The European Satellite has the first space-borne high-spectral resolution UV lidar onboard called ALADIN. Two detection channels, a broadband (Rayleigh channel) and a narrowband (Mie channel), are implemented. Carefully calibrated, this combination offers the possibility to derive independent estimates of the backscatter and extinction coefficients of clouds andaerosols, leading to a direct estimation of the lidar ratio, useful for aerosol classification. The presentation will show how the official processor of the mission works for the retrieval of optical properties of cloud and aerosol particles, with a focus on the currently available products (called L2A). The potential of the L2A processor will be illustrated by results obtained on data acquired since Aeolus launch and by comparisons to ground based lidars in the frame of Cal/Val activities. The L2A product will become publicly available during Spring 2021. Thus, this is also an opportunity to introduce a few practical aspects about its usage.

In August 2018, the European Space Agency (ESA) launched the first Doppler wind lidar into space, which has since then been providing continuous profiles of the horizontal line-of-sight wind component at a global scale. Aeolus data have been successfully assimilated into several numerical weather prediction (NWP) models and demonstrated a positive impact on the quality of the weather forecasts. To provide valuable input data for NWP models, a detailed characterization of the Aeolus instrumental performance as well as the realization and minimization of systematic error sources is crucial. In this paper, Aeolus interferometer spectral drifts and their potential as systematic error sources for the aerosol and wind products are investigated by means of instrument spectral registration (ISR) measurements that are performed on a weekly basis. During these measurements, the laser frequency is scanned over a range of 11 GHz in steps of 25 MHz and thus spectrally resolves the transmission curves of the Fizeau interferometer and the Fabry–Pérot interferometers (FPIs) used in Aeolus. Mathematical model functions are derived to analyze the measured transmission curves by means of non-linear fit procedures. The obtained fit parameters are used to draw conclusions about the Aeolus instrumental alignment and potentially ongoing drifts. The introduced instrumental functions and analysis tools may also be applied for upcoming missions using similar spectrometers as for instance EarthCARE (ESA), which is based on the Aeolus FPI design.

The Aeolus mission objectives are to improve numerical weather prediction (NWP) and enhance the understanding and modeling of atmospheric dynamics on global and regional scale. Given the first successes of Aeolus in NWP, it is time to look forward to future vertical wind profiling capability to fulfill the rolling requirements in operational meteorology. Requirements for wind profiles and information on vertical wind shear are constantly evolving. The need for high-quality wind and profile information to capture and initialize small-amplitude, fast-evolving, and mesoscale dynamical structures increases, as the resolution of global NWP improved well into the 3D turbulence regime on horizontal scales smaller than 500 km. In addition, advanced requirements to describe the transport and dispersion of atmospheric constituents and better depict the circulation on climate scales are well recognized. Direct wind profile observations over the oceans, tropics, and Southern Hemisphere are not provided by the current global observing system. Looking to the future, most other wind observation techniques rely on cloud or regions of water vapor and are necessarily restricted in coverage. Therefore, after its full demonstration, an operational Aeolus -like follow-on mission obtaining globally distributed wind profiles in clear air by exploiting molecular scattering remains unique.

Soon after its successful launch in August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) on-board ESA’s Earth Explorer satellite Aeolus has demonstrated to provide atmospheric wind profiles on a global scale. Being the first ever Doppler Wind Lidar (DWL) instrument in space, ALADIN contributes to the improvement in numerical weather prediction (NWP) by measuring one component of the horizontal wind vector. The performance of the ALADIN instrument was assessed by a team from ESA, DLR, industry, and NWP centers during the first months of operation. The current knowledge about the main contributors to the random and systematic errors from the instrument will be discussed. First validation results from an airborne campaign with two wind lidars on-board the DLR Falcon aircraft will be shown.

A field experiment took place from July to October 2018 in a narrow valley of the central Pyrenees in order to study local flows and their impacts. This field experiment is a joint effort by CNRM, Laboratoire d'Aerologie and University of the Balearic Islands. It emerged from a recent numerical study done by the University of the Balearic Islands (Jiménez et al. 2019). This study suggests that under clear-sky conditions a jet forms in the valley and can be observed several kilometers away from the valley exit. Several instruments including a Doppler scanning lidar and three meteorological stations were deployed on the main site at the valley exit, where the jet maximum is expected, and on two other sites up valley. Data from the Atmospheric Research Center (part of the Pyrenean Platform for the Observation of the Atmosphere P2OA) in Lannemezan are also used. They include radio-soundings specifically planned for the field experiment. This instrumented platform of Laboratoire d'Aerologie, located about 10 km away from the valley exit, is an important asset for the project. An overview of the field experiment as well as the valley exit jet main features will be presented. A comparison with outputs from the NWP model AROME will be also shown.

Already within the first weeks after the launch of ESA's Earth Explorer mission Aeolus on 22 August 2018, the spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) provided atmospheric backscatter measurements on 5 September and wind profiles on 12 September 2018. This swift availability of observations from ALADIN after launch is considered as a great success for ESA, space industry and algorithm and processor developer teams. These teams from scientific institutes, numerical weather prediction (NWP) centres, companies and ESA continuously improved and tested the retrieval algorithms and processors using sophisticated end-to-end simulation tools and experience gained with the airborne demonstrator for Aeolus for more than 15 years before launch. This cooperation from the pre-launch phase of Aeolus was extended within a new framework for exploitation activities of Earth Explorer missions named Data Innovation and Science Cluster (DISC) starting in January 2019. The Aeolus DISC activities range from instrument monitoring including calibration to algorithm refinement resulting in updates of the complete processor chain for all product levels every 6 months. DISC teams perform continuous monitoring of the product quality and provide regular reports in supports of external validation teams and ESA. Finally, wind product monitoring and impact experiments with NWP models are building an essential activity within the Aeolus DISC in order to achieve the objective of the Aeolus mission. In order to cover the broad range of activities, a multi-disciplinary team of experts, institutes and companies was established for the Aeolus DISC coordinated by DLR with ECMWF, KNMI, CNRS/Meteo-France, DoRIT, ABB, S&T and Serco. During the presentation the Aeolus instrument performance for wind products, the discovered causes of the systematic errors and their correction will be discussed. Main achievements in this area are related to the characterization and correction of enhanced dark signal levels for single hot pixels in June 2019, the identification of the harmonic error contribution caused by the varying telescope primary mirror temperature variation in September- October 2019, the error in the on-board computation of the satellite induced Doppler frequency shift, and finally the observed temporal drift of a constant bias caused by drifts in the internal reference path. An outlook to the implementation of these corrections for real-time and reprocessed data products will be given.

Fog strongly perturbs the aviation, marine and land transportation, leading to human losses and high financial costs. The primary objective of SOFOG3D is to advance our understanding of fog processes at the smallest scale to improve forecasts of fog events by numerical weather prediction (NWP) models. Specifically, SOFOG3D conducts process studies on very well documented situations, using synergy between 3D high-resolution Large Eddy Simulation (LES) and unprecedented 3D detailed observations. SOFOG3D will particularly focus on the impact of surface heterogeneities (types of vegetation, rivers, orography) on the fog life cycle, on fog microphysics properties, on entrainment at fog top, on the surface energy budget, and on the impact of aerosols. SOFOG3D will also investigate how improving the initial conditions of NWP models can improve fog forecasts. To that end, data from a ground-based MWR network will be assimilated using an innovative ensemble-based variational data assimilation scheme. A 6 months field experiment took place during wintertime 2019/2020 in the South-West of France to provide 3D mapping of the boundary layer during fog events. The observation strategy is to combine vertical profiles derived from new remote sensing instruments (microwave radiometer (MWR), Doppler cloud radar and Doppler lidars) and balloon-borne in-situ measurements, with local observations provided by a network of surface stations, and a fleet of Unmanned Aerial Vehicles (UAV) to explore fog spatial heterogeneities. Three nested domains has been instrumented with increasing density to provide observations from regional scale (300x200 km) down to local scale on the super-site (10x10 km), thanks to Meteo France and U.K. Meteorological Office sensors. On the super site, meteorological conditions, visibility, aerosol optical, microphysical and hygroscopic properties, fog microphysics and liquid water content, water deposition, radiation budget, heat and momentum fluxes on flux-masts has been performed on different areas to investigate the impacts of surface heterogeneities on fog processes, as well as turbulence anisotropy. Combination of cloud radar and MWR measurements will allow optimal retrieval of temperature, humidity and liquid water content profiles. We will present the instrumental set-up that has been deployed during this campaign and discuss the main objectives of the project. An overview of fog events that occurred during the 6 months experiment will be given, and preliminary analysis of data collected during IOPs with a tethered balloon and UAVs will be presented.