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Land–atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction models allows for better estimating the spatial and temporal distribution of the dust burden and the characterisation of source and recipient areas. In the presented study, the ECMWF-IFS (European Centre for Medium-Range Weather Forecast – Integrated Forecasting System) outputs, produced with and without the assimilation of Aeolus quality-assured Rayleigh–clear and Mie–cloudy horizontal line-of-sight wind profiles, are used as initial or boundary conditions in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate 2-month periods in the spring and autumn of 2020, focusing on a case study in October. The experiments have been performed over the broader eastern Mediterranean and Middle East (EMME) region, which is frequently subjected to dust transport, as it encompasses some of the most active erodible dust sources. Aerosol- and dust-related model outputs (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground- and satellite-based observations. Ground-based columnar and vertically resolved aerosol optical properties are acquired through AERONET sun photometers and PollyXT lidar, while near-surface concentrations are taken from EMEP. Satellite-derived vertical dust and columnar aerosol optical properties are acquired through LIVAS (LIdar climatology of Vertical Aerosol Structure) and MIDAS (ModIs Dust AeroSol), respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF-Chem simulations are initialised with the meteorological fields of Aeolus wind profiles assimilated by the IFS. The improvement varies in space and time, with the most significant impact observed during the autumn months in the study region. Comparison with observation datasets saw a remarkable improvement in columnar aerosol optical depths, vertically resolved dust mass concentrations and near-surface particulate concentrations in the assimilated run against the control run. Reductions in model biases, either positive or negative, and an increase in the correlation between simulated and observed values was achieved for October 2020.

The German Aerospace Center (Deutsches Zentrum für Luft- und Raumfahrt, DLR) conducted four airborne campaigns for the validation of the Aeolus L2B wind product during the first three years of ESA’s wind lidar mission between 2018 and 2021. After three campaigns in Europe, the Aeolus VAlidation Through Airborne LidaRs in the Tropics (AVATAR-T) campaign was performed around the Cabo Verde archipelago in September 2021 as part of the Joint Aeolus Tropical Atlantic Campaign (JATAC). AVATAR-T employed the DLR Falcon aircraft which carried two Doppler wind lidar (DWL) instruments: the heterodyne-detection 2-µm DWL acting as a high-accuracy reference and the ALADIN Airborne Demonstrator (A2D), representing a prototype of the direct-detection DWL on-board Aeolus with a high degree of commonality in terms of design and measurement principle.In the framework of AVATAR-T, 11 coordinated flights along the Aeolus track were performed covering nearly 11,000 km of the satellite's measurement swath. The research flights yielded a comprehensive set of A2D and 2-µm DWL wind observations to validate the Aeolus wind product under the influence of the Saharan Air Layer (SAL), the African Easterly Jet, the Subtropical Jet and the Intertropical Convergence Zone. In particular, the campaign results give insight into the impact of atmospheric aerosols onto the operational Rayleigh-clear and Mie-cloudy horizontal line-of-sight (HLOS) winds regarding potential errors that arise from crosstalk between the two complementary receiver channels and their respective wind data coverage in the troposphere.Validation of the Aeolus wind product based on 2-µm DWL data shows that the systematic error almost fulfills the mission requirement of being below 0.7 m/s (HLOS) for both Rayleigh-clear and Mie-cloudy winds. The random error, however, is larger than specified (2.5 m/s HLOS), being close to 3 m/s for Mie-cloudy winds and as high as 7 m/s for Rayleigh-clear winds. A more detailed investigation reveals that the Rayleigh-clear random error is increased at lower altitudes in case of signal extinction due to aerosols.The collocated A2D wind observations provide valuable information on the potential optimization of the Aeolus wind retrieval and related quality control (QC) algorithms. For instance, the A2D, unlike ALADIN, delivered a broad vertical and horizontal coverage of Mie winds across the SAL, whereas A2D Rayleigh winds measured in this region, which are affected by Mie contamination through crosstalk and signal extinction, are effectively filtered out. Preliminary studies suggest that a refinement of the Aeolus wind retrieval may improve the Mie wind data coverage in aerosol regions.In addition, we studied the influence of different QC schemes on the validation results and developed a two-step QC approach that ensures effective outlier removal and compliance with the Aeolus mission requirements document. The QC scheme also improves the comparability of different validation studies and thus helps to facilitate the consolidation of the Aeolus error evaluation from different Cal/Val teams.The contribution presents comparative wind observations of Aeolus and the two DLR airborne wind lidar instruments from the JATAC with a focus on the error assessment and a potential improvement of the Aeolus wind data product.

BackgroundSexual size dimorphism (SSD) is a widespread phenomenon in the animal world resulting from differential selection on the sexes. The Northern Pike (Esox lucius) is a freshwater apex predatory fish species that exhibits female-biased SSD, but the degree to which SSD varies among populations and what variables might dictate variation in SSD in this species remain poorly understood.AimWe sought to quantify the degree of variation in SSD among Northern Pike populations across a large portion of their North American range, as well as evaluate associations between the magnitude of SSD in Northern Pike populations with environmental variables and life history traits of populations.MethodsWe quantified SSD in 102 populations of Northern Pike across the province of Ontario, Canada, using a standardized gillnetting database. We further investigated the degree to which both environmental variables (Cisco abundance as catch-per-unit-effort, lake surface area, and latitude) and Northern Pike life-history traits (early growth and mortality rates) explained variation in female-biased SSD using linear models.ResultsFemale-biased SSD in mean weight of Northern Pike increased with increasing Cisco (Coregonus artedi) abundance, and the difference in female and male mean age increased with increasing latitude. Furthermore, SSD was greater in populations with lower female mortality and early growth rates.ConclusionThis study indicates that slow-growing, long-lived populations of Northern Pike should exhibit greater female-biased SSD, and that these conditions may be facilitated by the availability of large, energy-dense prey and cooler temperatures at northern latitudes.

Forecasting volcanic ash atmospheric pathways is of utmost importance for aviation. Volcanic ash can interfere with aircraft navigational instruments and can damage engine parts. Early warning systems, activated after volcanic eruptions can alleviate the impacts on aviation by providing forecasts of the volcanic ash plume dispersion. The quality of these short-term forecasts is subject to the accuracy of the meteorological wind fields used for the initialization of regional models. Here, we use wind profiling data from the first High Spectral Resolution Lidar in Space, Aeolus, to examine the impact of measured wind fields on regional NWP and subsequent volcanic ash dispersion forecasts, focusing on the case of Etna’s eruption on March 2021. The results from this case study demonstrate a significant improvement of the volcanic ash simulation when using Aeolus-assimilated meteorological fields, with differences in wind speed reaching up to 8 m/s when compared to the control run. When comparing the volcanic ash forecast profiles with downwind surface-based aerosol lidar observations, the modeled field is consistent with the measurements only when Aeolus winds are assimilated. This result clearly illustrates the potential and importance of wind profiling from space for volcanic ash forecasting and hence aviation safety.

As the climate warms, northern ecosystems are experiencing warmer winters and seasonal climatic shifts. Vascular plants are expected to respond to climate change by adjusting flowering or seeding periods. To determine how a native mixed-wood boreal floral assemblage has responded to warming temperatures over the 20th century, we collated historical observations made by field-naturalists as well as voucher data from the Thunder Bay region of Ontario, Canada. Combining these datasets, we performed regression analyses on 11 species of spring-flowering vascular plants to evaluate temporal trends and used spring cumulative growing degree day (sGDD0) to determine the influence of climate on flowering times. Four species showed consistent positive temporal trends (i.e., flowered later with time), while four species (three of which also demonstrated temporal trends) showed negative trends with sGDD0 (i.e., flowered earlier with an increased number of degree days above 0°C). The unexpected observation of later flowering times but predicted observation of earlier blooming with increased sGDD0 indicates that the inclusion of climate metrics may be necessary to determine the response of native vascular plants to the onset of changes in their environment. These observations were not statistically significant when field-naturalist or herbarium voucher data were analyzed separately, possibly due to low statistical power. Combining data from both sources, however, revealed common responses to climate warming among species within an ecoregion.

In August2018, European Space Agency launched Aeolus satellitewith the first spaceborne Doppler Wind Lidar onboard thatprovided global coverage of the horizontal line-of-sight (HLOS) wind profiles. Despite their lower accuracy compared to conventional wind observations, Aeolus data improved analyses and forecasts in all operational numerical weather prediction (NWP) models that assimilated the HLOS winds The largest improvements by Aeolus are seen in the tropical upper troposphere and lower stratosphere (UTLS) with Aeolus correcting both systematic and random errors. The UTLS is the region with the strongest equatorial wave activity, especially Kelvin waves. It is also the region with the largest amplitudes of analysis and short-term forecast uncertainties in global NWP models.We shall present impact of Aeolus wind profiles on the ECMWF analyses and forecasts in the UTLS focusing on the Kelvin wave, the most prominent large-scale wave in the tropical atmosphere. The analysis is based on the comparison of the observing system experiments (OSE) that includedAeolus winds on top of all other observations and the referent experiment with all (but Aeolus) observations. The OSE was performed for the period from July 2019 to September 2020 using the second reprocessing of the Aeolus measurement from 2022.The work focuses on regions of strong shear of the horizontal wind and on coupling the effects on forecasts with the phase of the quasi-biennial oscillation (QBO) including its major disruption during the studied period., The 28th IUGG General Assembly (IUGG2023) (Berlin 2023)

Land–atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction models allows for better estimating the spatial and temporal distribution of the dust burden and the characterisation of source and recipient areas. In the presented study, the ECMWF-IFS (European Centre for Medium-Range Weather Forecast – Integrated Forecasting System) outputs, produced with and without the assimilation of Aeolus quality-assured Rayleigh–clear and Mie–cloudy horizontal line-of-sight wind profiles, are used as initial or boundary conditions in the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to simulate 2-month periods in the spring and autumn of 2020, focusing on a case study in October. The experiments have been performed over the broader eastern Mediterranean and Middle East (EMME) region, which is frequently subjected to dust transport, as it encompasses some of the most active erodible dust sources. Aerosol- and dust-related model outputs (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground- and satellite-based observations. Ground-based columnar and vertically resolved aerosol optical properties are acquired through AERONET sun photometers and PollyXT lidar, while near-surface concentrations are taken from EMEP. Satellite-derived vertical dust and columnar aerosol optical properties are acquired through LIVAS (LIdar climatology of Vertical Aerosol Structure) and MIDAS (ModIs Dust AeroSol), respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF-Chem simulations are initialised with the meteorological fields of Aeolus wind profiles assimilated by the IFS. The improvement varies in space and time, with the most significant impact observed during the autumn months in the study region. Comparison with observation datasets saw a remarkable improvement in columnar aerosol optical depths, vertically resolved dust mass concentrations and near-surface particulate concentrations in the assimilated run against the control run. Reductions in model biases, either positive or negative, and an increase in the correlation between simulated and observed values was achieved for October 2020.

Nucleic acids released by organisms and isolated from environmental substrates are increasingly being used for molecular biomonitoring. While environmental DNA (eDNA) has received much attention, the potential of environmental RNA as a biomonitoring tool remains under-explored. Several recent studies using paired DNA and RNA metabarcoding of bulk samples suggest that RNA might better reflect "metabolically active" parts of the community. However, such studies mainly capture organismal eDNA and eRNA. For larger eukaryotes, isolation of extra-organismal RNA will be important, but viability needs to be examined in a field-based setting. In this study we evaluate (a) whether extra-organismal eRNA release from macroeukaryotes can be detected given its supposedly rapid degradation, and (b) if the same field collection methods for eDNA can be applied to eRNA. We collected eDNA and eRNA from water in lakes where fish community composition is well documented, enabling a comparison between the two nucleic acids in two different seasons with monitoring using conventional methods. We found that eRNA is released from macroeukaryotes and can be filtered from water and metabarcoded in a similar manner as eDNA to reliably provide species composition information. eRNA had a small but significantly greater true positive rate than eDNA, indicating that it correctly detects more species known to exist in the lakes. Given relatively small differences between the two molecules in describing fish community composition, we conclude that if eRNA provides significant advantages in terms of lability, it is a strong candidate to add to the suite of molecular monitoring tools.

This study sought to reduce the dimensionality of commonly reported spatiotemporal characteristics obtained from Australian Football games to facilitate their practical use and interpretability.A retrospective longitudinal design was utilised with team and individual spatiotemporal variables, measured via global navigation satellite system devices, collected during official Australian Football League matched over three seasons. Two separate principal component analyses were conducted at the team and individual level to reduce correlated spatiotemporal characteristics into a smaller set of uncorrelated components.At the team level, eighteen variables were reduced to five components pertaining to dispersive coordination, lateral predictability and spacing, multidirectional synchrony, longitudinal predictability and longitudinal behaviour whilst maintaining 69% of variance in the original dataset. At the individual level, fifteen variables were reduced to four components pertaining toThis study is the first to provide a simplified, novel method for analysing spatiotemporal behaviour in an Australian Football context with both the team- and individual- derived metrics revealing useful information for coaches and practitioners. Components may provide insight into behaviours that emerge and persist throughout a game and allow coaches to distinguish between different playing/behavioural styles.

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.

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.

International audience; We highlight some of the scientific benefits of the Aeolus Doppler Wind Lidar mission since its launch in August 2018. Its scientific objectives are to improve weather forecasts and to advance the understanding of atmospheric dynamics and its interaction with the atmospheric energy and water cycle. A number of meteorological and science institutes across the world are starting to demonstrate that the Aeolus mission objectives are being met. Its wind product is being operationally assimilated by four Numerical Weather Prediction (NWP) centres, thanks to demonstrated useful positive impact on NWP analyses and forecasts. Applications of its atmospheric optical properties product have been found, e.g., in the detection and tracking of smoke from the extreme Australian wildfires of 2020 and in atmospheric composition data assimilation. The winds are finding novel applications in atmospheric dynamics research, such as tropical phenomena (Quasi-Biennial Oscillation disruption events), detection of atmospheric gravity waves, and in the smoke generated vortex associated with the Australian wildfires. It has been applied in the assessment of other types of satellite derived wind information such as atmospheric motions vectors. Aeolus is already successful with hopefully more to come.

Background While Pace of Life Syndrome predicts behavioural differences between individuals with differential growth and survival, testing these predictions in nature is challenging due to difficulties with measuring individual behaviour in the field. However, recent advances in acoustic telemetry technology have facilitated measurements of individual behaviour at scales not previously possible in aquatic ecosystems. Methods Using a Walleye (Sander vitreus) population inhabiting Black Bay, Lake Superior, we examine whether life history characteristics differ between more and less mobile individuals as predicted by Pace of Life Syndrome. We tracked the movement of 192 individuals from 2016 to 2019 using an acoustic telemetry study, relating patterns in annual migratory behaviour to individual growth, and seasonal changes in optimal thermal-optical habitat. Results We observed two consistent movement patterns in our study population—migratory individuals left Black Bay during late summer to early fall before returning to the bay, whereas residents remained within the bay year-round. The average maximum length of migrant Walleye was 5.5 cm longer than residents, and the sex ratios of Walleye caught during fall surveys was increasingly female-biased towards the mouth of Black Bay, suggesting that a majority of migrants were females. Further, Walleye occupancy outside of Black Bay was positively associated with increasing thermal-optical habitat. Conclusions Walleye in Black Bay appear to conform to Pace of Life Syndrome, with migrant individuals gaining increased fitness through increased maximum size, which, given size-dependent fecundity in this species, likely results in greater reproductive success (via greater egg deposition vs. non-migrants). Further, apparent environmental (thermal) controls on migration suggest that migratory Walleye (more so than residents) may be more sensitive to changing environmental conditions (e.g., warming climate) than residents.

Already shortly after the successful launch of the European Space Agency satellite Aeolus in August 2018, it turned out that dark current signal anomalies of single pixels (so-called hot pixels) on the Accumulation-Charge-Coupled Devices (ACCDs) of the Aeolus detectors detrimentally impact the quality of the aerosol and wind products potentially leading to wind errors of up to 4 m/s. This paper provides a detailed characterization of the hot pixels which occurred during the first one and a half years in orbit. The hot pixels are classified according to their characteristics to discuss their impact on wind measurements. Furthermore, mitigation approaches for the wind retrieval are presented and potential root causes for the hot pixel occurrence are discussed. The analysis of the dark current signal anomalies reveals a large variety of anomalies ranging from pixels with Random Telegraph Signal (RTS)-like characteristics to pixels with sporadic shifts in the median dark current signal. Moreover, the results indicate that the number of hot pixels has almost linearly increased during the observing period between 2018-09-02 until 2020-05-20 with 6 % of the ACCD pixels affected in total at the end of the period leading to 9.5 % at the end of mission lifetime. This work introduces dedicated instrument calibration modes and ground processors which allowed for a correction shortly after a hot pixel occurrence. The achieved performance with this approach avoids risky adjustments to the inflight hardware operation. It is demonstrated that the success of the correction scheme varies depending on the characteristics of each hot pixel itself. With the herein presented categorization, it is shown that multi-level RTS pixels with high fluctuation are the biggest challenge for the hot pixel correction scheme. Despite a detailed analysis in this framework, no conclusion could be drawn about the root cause of the hot pixel issue.

The unique European Space Agency (ESA) Earth Explorer Aeolus Doppler Wind Lidar (DWL) is a success with beneficial impacts in weather and climate. At the IGARSS ‘21 venue we will share our results internationally and present initial studies that look into an operational Aeolus follow-on mission and describe lessons learned on the instrument, data processing and application of the winds. The ESA Aeolus mission now demonstrates the unique benefits of direct measurements of the atmospheric wind fieldon atmospheric dynamical analyses and forecasts. The many lessons learned from the Aeolus instrument development, its operation and data processing development are being exploited to help develop the requirements and design of an Aeolus follow-on mission in order to further enhance its application benefit globally. An overview of preliminary Aeolus and future DWL requirements will be presented to initiate a discussion with the international community gathered at IGARSS ‘21.

The European Space Agency satellite Aeolus provides continuous profiles of the horizontal line-of-sight wind component at a global scale. It was successfully launched into space in August 2018 with the goal to improve numerical weather prediction (NWP). Aeolus data has already been successfully assimilated into several NWP models and has already helped to significantly improve the quality of weather forecasts. To achieve this major milestone the identification and correction of several systematic error sources was necessary. One of them is related to small temperatures fluctuations across the 1.5 m diameter primary mirror of the telescope which cause varying wind biases along the orbit of up to 8 m/s. This paper presents a detailed overview of the influence of the telescope temperature variations on the Aeolus wind products and describes the approach to correct for this systematic error source in the operational near-real-time (NRT) processing. It was shown that the telescope temperature variations along the orbit are due to changes of the top-of-atmosphere short- and long-wave radiation of the Earth and the response of the telescope’s thermal control system to that. To correct for this effect ECMWF model-equivalent winds are used as bias reference to describe the wind bias in a multiple linear regression model as a function of various temperature sensors located on the primary telescope mirror. This correction scheme has been in operational use at ECMWF since April 2020 and is capable of reducing a large part of the telescope-induced wind bias. In cases where the influence of the temperature variations is particularly strong it was shown that the bias correction can improve the orbital bias variation by up to 53 %. Moreover, it was demonstrated that the approach of using ECMWF model-equivalent winds is justified by the fact that the global bias of models u-component winds w.r.t to radiosondes is smaller than 0.3 m/s. However, this paper also presents the alternative of using Aeolus ground return winds which serve as zero wind reference in the multiple linear regression model. The results show that the approach based on ground return winds only performs 10.8 % worse than the ECMWF model-based approach and thus has good potential for future applications for upcoming reprocessing campaigns or even in the NRT processing of Aeolus wind products.

The European Space Agency (ESA)’s wind mission, Aeolus, was launched on 22 August 2018. It is a member of the ESA Earth Explorer family and its main objective is to demonstrate the potential of Doppler wind Lidars in space for improving weather forecast and to understand the role of atmospheric dynamics in climate variability. Aeolus carries a single instrument called ALADIN: a high sophisticated spectral resolution Doppler wind Lidar which operates at 355 which is the first of its kind to be flown in space.Aeolus provides profiles of single horizontal line-of-sight winds (primary product) in near-real-time (NRT), and profiles of atmospheric backscatter and extinction. The instrument samples the atmosphere from about 30 km down to the Earth’s surface, or down to optically thick clouds. The required precision of the wind observations is 1-2.5 m/s in the troposphere and 3-5 m/s in the stratosphere while the systematic error requirement be less than 0.7 m/s. The mission spin-off product includes information about aerosol and cloud layers. The satellite flies in a polar dusk/dawn orbit (6 am/pm local time), providing ~16 orbits per 24 hours with an orbit repeat cycle of 7 days. Global scientific payload data acquisition is guaranteed with the combined usage of Svalbard and Troll X-band receiving stations.After almost three years in orbit and despite performance issues related to its instrument ALADIN, Aeolus has achieved most of its objectives. Positive impact on the weather forecast has been demonstrated by multiple NWP centres world-wide with four European meteorological centres now are assimilating Aeolus winds operationally. Other world-wide meteo centers wull start to assimilate data in 2021. The status of the Aeolus mission will be presented, including overall performance, planned operations and exploitation. Scope of the paper is also to inform about the programmatic highlights and future challenges.

The latest results on the assessment of the impact of Aeolus Level-2B horizontal line-of-sight wind retrievals in global Numerical Weather Prediction at ECMWF will be presented. Aeolus has been operationally assimilated at ECMWF since 9 January 2020.Random and systematic error estimates were derived from observation minus background departure statistics. The HLOS wind random error standard deviation is estimated to vary over the range 4.0-7.0 m/s for the Rayleigh-clear and 2.8-3.6 m/s for the Mie-cloudy; depending on atmospheric signal levels which in turn depends on instrument performance, atmospheric backscatter properties and the processing algorithms.In Observing System Experiments (OSEs) Aeolus provides statistically significant improvement in short-range forecasts as verified by observations sensitive to temperature, wind and humidity. Longer forecast range verification shows positive impact that is strongest at the 2-3 day forecast range; ~2% improvement in root mean square error for vector wind and temperature in the tropical upper troposphere and lower stratosphere and polar troposphere. Positive impact up to 9 days is found in the tropical lower stratosphere. Both Rayleigh-clear and Mie-cloudy winds provide positive impact, but the Rayleigh accounts for most tropical impact. The Forecast Sensitivity Observation Impact (FSOI) metric is available since Aeolus was operationally assimilated, which confirms Aeolus is a useful contribution to the global observing system; with the Rayleigh-clear and Mie-cloudy winds providing similar overall short-range impact in 2020. If the OSEs are ready in time, we will present the impact of the first reprocessed Aeolus data for the July-December 2019 period.

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 winds 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 independent reference data sets. Due to lower representativeness, the random differences are larger for the validation using radiosonde observations compared to the model equivalent statistics. To achieve an estimate for the Aeolus instrumental error, the representativeness errors for the comparisons are determined, besides the estimation of the model and radiosonde observational error. The resulting Aeolus errors 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 depend on 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 bias correction scheme has been applied operationally in the L2B processor, developed by the Aeolus Data Innovation and Science Cluster (DISC).

ESA deployed the first Doppler wind lidar in space within its Earth Explorer Mission Aeolus in August 2018. Since then global wind profiles have been acquired for the improvement of weather forecasts on short and medium term. Current calibration and validation activities indicate the demanded positive impact from different forecast centers. In addition, Aeolus provides profiles of atmospheric backscatter and extinction coefficients that are supposed to become input for air quality models. The talk will provide an overview of the encountered technical challenges in flight and some preliminary results from impact studies.

The European Space Agency, ESA deployed the first Doppler wind lidar in space within its Earth Explorer Mission Aeolus in August 2018. After the initial commissioning of the satellite and the single payload ALADIN, the mission has started to demonstrate the capability of Doppler lidar to measure wind from space. In order to provide the best Aeolus wind product possible, detailed monitoring of the instrument is crucial for analysis of system health, but also for the assessment of measurement performance and data product calibration. Within the last 1.2 years the different instrument modes to assess instrument and laser health, as well as the nominal wind processing indicated longterm instrument drifts. The laser beam profile has been monitored and showed an energy redistribution within the beam. The line of sight has slowly drifted, resulting in a change of incidence angle at spectrometer level. The impact of these observed drifts on the wind product are compensated on demand by updates of dedicated ground processing calibration files. This contribution will provide an overview about the Aeolus instrument modes and the observed stability that are needed to provide the Aeolus wind product. The current Aeolus performance has been assessed by various Numerical Weather Prediction centers. The positive outcome is represented by ECMWF’s decision to start using Aeolus data operationally on 9th January 2020.

ESA deployed the first Doppler Wind lidar in space within its Earth Explorer Mission Aeolus. The objective of Aeolus is to provide tropospheric and lower stratospheric wind profiles globally for the improvement of weather forecasts on short and medium term. Spin-off products are profiles of atmospheric backscatter and extinctions coefficients and lidar ratio. The observations will also be used as input to air quality models and to verify climate model parameterization and predictability. After the successful launch in late August this year an intensive commissioning phase is taking place in the first three month of the mission, including the first switch on of the instrument ALADIN and its calibration in flight. First preliminary results will be presented during the talk.

ESA deployed the first Doppler Wind lidar in space within its Earth Explorer Mission Aeolus. The objective of Aeolus is to provide tropospheric and lower stratospheric wind profiles globally for the improvement of weather forecasts on short and medium term. Spin-off products are profiles of atmospheric backscatter and extinction coefficients and lidar ratio that can input for air quality models. After the successful launch in late August 2018 and following commissioning phase, the Calibration and Validation phase started in Decemeber 2018. The talk will recap the highlights of these phases and present the status of the mission.

This paper investigates the accuracy of simulated long-duration super-pressure balloon trajectories in the lower stratosphere. The observed trajectories were made during the (tropical) Pre-Concordiasi and (polar) Concordiasi campaigns in 2010, while the simulated trajectories are computed using analyses and forecasts from the European Centre for Medium-Range Weather Forecasts (ECMWF) Integrated Forecast System model. In contrast with the polar stratosphere situation, modelling accurate winds in the tropical lower stratosphere remains challenging for numerical weather prediction systems. The accuracy of the simulated tropical trajectories are quantified with the operational products of 2010 and 2016 in order to understand the impact of model physics and vertical resolution improvements. The median errors in these trajectories are large (typically ≳ 250 km after 24 h), with a significant negative bias in longitude, for both model versions. In contrast, using analyses in which the balloon-borne winds have been assimilated reduces the median error in the balloon position after 24 h to &sim, 60 km. For future campaigns, we describe operational strategies that take advantage of the geographic distribution and the episodic nature of large error events to anticipate the amplitude of error in trajectory forecasts. We finally stress the importance of a high vertical resolution in the model, given the intense shears encountered in the tropical lower stratosphere.

The European Space Agency (ESA) wind mission, Aeolus, hosts the first space-based Doppler Wind Lidar (DWL) world-wide. The primary mission objective is to demonstrate the DWL technique for measuring wind profiles from space, intended for assimilation in Numerical Weather Prediction (NWP) models. The wind observations will also be used to advance atmospheric dynamics research and for evaluation of climate models. Mission spin-off products are profiles of cloud and aerosol optical properties. Aeolus was launched on 22 August 2018, and the Atmospheric LAser Doppler INstrument (Aladin) instrument switch-on was completed with first high energy output in wind mode on 4 September 2018 [1], [2]. The on-ground data processing facility worked excellent, allowing L2 product output in near-real-time from the start of the mission. First results from the wind profile product (L2B) assessment show that the winds are of very high quality, with random errors in the free Troposphere within (cloud/aerosol backscatter winds: 2.1 m/s) and larger (molecular backscatter winds: 4.3 m/s) than the requirements (2.5 m/s), but still allowing significant positive impact in first preliminary NWP impact experiments. The higher than expected random errors at the time of writing are amongst others due to a lower instrument out-and input photon budget than designed. The instrument calibration is working well, and some of the data processing steps are currently being refined to allow to fully correct instrument alignment related drifts and elevated detector dark currents causing biases in the first data product version. The optical properties spin-off product (L2A) is being compared e.g. to NWP model clouds, air quality model forecasts, and collocated ground-based observations. Features including optically thick and thin particle and hydrometeor layers are clearly identified and are being validated.

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.

ESAs Earth Explorer Aeolus was launched in August 2018. Aboard the first spaceborne wind lidar ALADIN (Atmospheric LAser Doppler INstrument) was switched on in early September 2018 and demonstrated the capability to provide atmospheric wind profiles globally from particle and molecular backscatter. In doing so, it will contribute to the improvement in numerical weather prediction (NWP) and the understanding of global dynamics. At the same, it is a major step for powerful and frequency stabilized ultraviolet (UV) lasers for space applications. In parallel, ESA and its partners continue the development of this technology by setting up further ground tests based on Aeolus, and preparing the next milestone with ATLID (ATmospheric LIDar) for the Earth Cloud, Aerosol and Radiation Explorer (EarthCARE) mission. ATLID is currently fully integrated and getting prepared for its on-ground testing.

The Department of Communication and Applied Behavioural Science is one of the three departments in the academic faculty at the Royal Military Academy Sandhurst. The aim of the Department is to equip officer cadets with the skills, knowledge and personal qualities in order for them to develop their own potential, as both individuals and leaders in the British Army. The members of the Department have a range of backgrounds, with most having served in various capacities across UK Defence, both in uniformed and/or civilian crown servant contexts. Several members of the faculty are qualified psychologists, while others have related academic and professional backgrounds. The academic and applied discipline of psychology is the fundamental thread that runs through the various courses and projects delivered by the Department. This paper provides a brief overview of the activities undertaken by the Department, with a specific focus on the psychology components of the academic and applied activities. Although mainly serving in academic teaching roles, this paper illustrates the work of the psychologists outside the classroom, such as via field exercises and deployments overseas. It also touches on the importance of the outreach undertaken by the psychologists in the Department, which supports their ongoing research.

Single-component wind observations have been assimilated into the ECMWF data assimilation system. Various Observing System Experiments have been performed in order to estimate the impact of such information in numerical weather prediction. The investigations on the impact of the horizontal line-of-sight wind on the ECMWF analysis and forecast system is described in a two-part article. Part I evaluates the impact of wind observations with respect to mass observations and the impact of assimilating different single wind components versus wind vector information. Part II assesses the forecast system performance in the presence of varying levels of random and systematic error in the line-of-sight wind measurements. The aim is to understand the sensitivity of weather forecasts with respect to possible observation error scenarios of the Doppler Wind Lidar (DWL) measurements from the Aeolus mission. It was found that even small wind observation biases (of the order of 1 m s−1) can deteriorate the forecast quality by 3–4% in terms of mean integrated total energy of the 24 h forecast error. This is particularly true for observation biases in the Tropics, in the upper troposphere and lower stratosphere. A 2 m s−1 bias degrades the forecasts by 15%. The increase of the line-of-sight random errors (from 25 to 100%) adds only 1–2% forecast skill degradation.