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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 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.

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.

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.

In preparation for the Aeolus Doppler Wind Lidar satellite mission, single-component wind information from conventional observations was assimilated into the ECMWF data assimilation system. Various Observing System Experiments have been designed and performed in order to estimate the impact of such information in numerical weather prediction. The evaluation used various adjoint diagnostic tools and traditional statistical verification methods. The importance of assimilating wind observations as either single component or full vector wind is evaluated. Comparisons between the assimilation of wind and mass observations were also made. Wind observations can lead to significant improvement in the upper troposphere, lower stratosphere and in the Tropics. Mass data are more valuable in the midlatitudes, particularly in the lower part of the atmosphere. The comparison of additional mass and wind observations in the Global Observing System is useful to understand the importance of future wind observations. The investigation also highlighted that the impact of zonal wind observations is larger than the meridional wind (Aeolus will mostly measure wind components near the zonal direction). Root mean-squared errors of temperature and wind forecasts when the single wind component (zonal) is assimilated show around 35% degradation up to day 2 forecasts and around 20% after day 2 as compared to assimilating full vector wind. Therefore the single (zonal) wind components can provide a large fraction of the vector wind impact particularly for the medium-range forecast, which is promising for Aeolus.

Since 26 September 2006, refractivity profiles from the CHAMP and GRACE-A satellites have been assimilated in the Met Office operational global numerical weather prediction system. This article presents the results of two experiments, which aim to determine the potential impact on the forecast resulting from the assimilation of this new dataset, and goes on to describe the Met Office operational implementation. Despite the limited number of occultations available for assimilation, the experiments show a significant positive impact on upper troposphere and lower stratosphere temperature and geopotential height fields, mid-tropospheric geopotential heights and pressure at mean sea level in the Southern Hemisphere. © Crown Copyright 2008. Reproduced with permission of Controller of HMSO and Queen's Printer for Scotland. Published by John Wiley & Sons, Ltd.