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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 Polly XT 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. [ABSTRACT FROM AUTHOR]

The long term analysis of 15 years of lidar data derived from a Raman lidar at Thessaloniki is presented here. All measurements have been processed with the latest version 4 of the EARLINET Single Calculus Chain algorithm and are compared with the results from the current operational retrieval algorithm. In this paper we investigate the consistency between the EARLINET database and SCC for the case of Thessaloniki and we identify the issues to be considered when switching from current operations to SCC.

In this study we present some first results on the potential of 15 years of lidar measurements over the lidar station of Thessaloniki to compile a climatology of the aerosol properties for the period 2001-2015. This is examined on a monthly, seasonal and annual basis. Both the profile structure and the columnar properties of the aerosol extinction and backscatter products are examined. The results are compared for consistency against co-located sunphotometer measurements.

Land-atmosphere interactions govern the process of dust emission and transport. An accurate depiction of these physical processes within numerical weather prediction (NWP) 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 are used to simulate two-month long periods in the spring and autumn of 2020, focusing on a case study in October. The ECMWF-IFS outputs are produced with and without assimilation of Aeolus quality-assured Rayleigh-clear and Mie-cloudy Horizontal Line of Sight (HLOS) wind profiles. The experiments have been performed over the broader Eastern Mediterranean and Middle East (EMME) region that 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 and MIDAS, respectively. Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when WRF simulations are initialised with IFS meteorological fields in which Aeolus wind profiles have been assimilated. The improvement varies in space and time, with the most significant impact observed for 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 of model biases, either positive or negative, and an increase in the correlation between simulated and observed values were achieved. [ABSTRACT FROM AUTHOR]