Abstract. 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. 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. 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.
<p>The long&#8211;range transport of larger than expected dust particles has been established in numerous observational studies. However, dust transport models struggle to simulate the observed particle size distributions. Studies utilizing a new version of WRF-chem code that contains the full size range of dust particles (0.2-100&#956;m in diameter), estimated that approximately 80% reduction in the particles&#8217; settling velocity is required for the particles to be transported from the desert towards the Cape Verde. Here, we examine the effect of the dust particles&#8217; shape in the dynamics of coarse and giant long-range transport. We specifically apply a new drag coefficient for spheroids in idealized atmospheric WRF-chem simulations above the Atlantic Ocean. Additionally, since there is much confusion about the definition of the size of non-spherical dust particles, where some studies define size as the diameter of a sphere with the same volume, while others as the particles&#8217; maximum, we perform simulations comparing the spherical and spheroid dust particles using both those two different approaches. The results are encouraging for the explanation of long &#8211;range dust transport, however more processes should be re-visited, including the dust radiation effects of non-spherical articles.</p><p><strong>Acknowledgements</strong></p><p>This research was supported by D-TECT (Grant Agreement 725698) funded by the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme. Eleni Drakaki is funded by Stavros Niarchos Foundation (SNF) Fellowship.</p><p>&#160;</p>
Abstract. 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.
<div> <p><span>One of the most important factors towards improved mineral dust mobilization and transport modelling is the representation of wind fields, which determine dust emission and atmospheric lifetime. The potential improvements on regional dust simulations attributed to the assimilation of Aeolus wind profiles is the core objective of the NEWTON (ImproviNg&#160;dust monitoring and&#160;forEcasting&#160;through Aeolus Wind&#160;daTa&#160;assimilatiON) ESA project.</span><span>&#160;</span></p> </div><div> <p><span>Towards this goal, the Weather Research and Forecas</span><span>ting regional atmospheric model</span><span>&#160;</span><span>coupled with chemistry (WRF/Chem) is used to simulate the airborne dust concentrations for two-month long periods in the spring and fall season of 2020, with special focus on a dust case in October 2020. The model is driven by ECMWF IFS outputs produced with (hel4) and without (hel1) assimilation of Aeolus quality-assured Rayleigh-clear and Mie-cloudy wind profiles. Our experiments are performed over the broader Eastern Mediterranean region that is subjected frequently to dust transport, encompassing the major natural erodible dust sources of the planet. Dust-related model outputs&#160;(</span><span>extinction coefficient,&#160;</span><span>optical depth and concentrations)&#160;are&#160;qualitatively and quantitatively evaluated against ground-based columnar and vertically resolved aerosol optical properties acquired by AERONET sun</span><span>&#160;</span><span>photometers and&#160;PollyXT&#160;lidar, as well as&#160;</span><span>near-surface&#160;</span><span>c</span><span>oncentrations available through EMEP. Our assessment further includes comparison versus LIVAS and MIDAS satellite-derived datasets providing vertical and columnar dust optical properties, respectively.</span><span>&#160;</span></p> </div><div> <p><span>Overall, in cases of either high or low aerosol loadings, the model predictive skill is improved when the regional simulations are initialized with Aeolus wind assimilation (hel4). The improvement&#160;va</span><span>ries in</span><span>&#160;space and time, with the inclusion of the assimilated wind profiles into IFS meteorological fields having a larger impact on the spatiotemporal distribution of dust particles during the fall compared to the spring months. During&#160;the&#160;case study of interest in October 2020, there is strong evidence of a better representation of the Mediterranean desert dust outbreak spatiotemporal patterns based on the hel4 experiment. Such improvements are driven by wind fields throughout the atmosphere affecting mobilization mechanisms through surface winds, and transport and removal processes. Comparison with MIDAS saw a</span><span>&#160;</span><span>remarkable</span><span>&#160;improvement for the hel4 against the hel1 simulated AODs, over the central and eastern sectors of the Mediterranean and Middle East regions. Confirmed by the drastically reductions of the model biases (either positive or negative) and the increased correlation (up to 0.28</span><span>), meanwhile</span><span>&#160;for several AERONET stations there was an average improvement in the correlation of assimilated outputs compared to control ones.</span><span>&#160;</span></p> </div>
Abstract. 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.
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