The impact of assimilating AEOLUS wind data on regional Aeolian dust model simulations using WRF-Chem.&#160; (2022)

&amp;lt;div&amp;gt; &amp;lt;p&amp;gt;&amp;lt;span&amp;gt;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&amp;amp;#160;dust monitoring and&amp;amp;#160;forEcasting&amp;amp;#160;through Aeolus Wind&amp;amp;#160;daTa&amp;amp;#160;assimilatiON) ESA project.&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;/div&amp;gt;&amp;lt;div&amp;gt; &amp;lt;p&amp;gt;&amp;lt;span&amp;gt;Towards this goal, the Weather Research and Forecas&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;ting regional atmospheric model&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;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&amp;amp;#160;(&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;extinction coefficient,&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;optical depth and concentrations)&amp;amp;#160;are&amp;amp;#160;qualitatively and quantitatively evaluated against ground-based columnar and vertically resolved aerosol optical properties acquired by AERONET sun&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;photometers and&amp;amp;#160;PollyXT&amp;amp;#160;lidar, as well as&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;near-surface&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;c&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;oncentrations available through EMEP. Our assessment further includes comparison versus LIVAS and MIDAS satellite-derived datasets providing vertical and columnar dust optical properties, respectively.&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;/div&amp;gt;&amp;lt;div&amp;gt; &amp;lt;p&amp;gt;&amp;lt;span&amp;gt;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&amp;amp;#160;va&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;ries in&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#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&amp;amp;#160;the&amp;amp;#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&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;remarkable&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#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&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;), meanwhile&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;for several AERONET stations there was an average improvement in the correlation of assimilated outputs compared to control ones.&amp;lt;/span&amp;gt;&amp;lt;span&amp;gt;&amp;amp;#160;&amp;lt;/span&amp;gt;&amp;lt;/p&amp;gt; &amp;lt;/div&amp;gt;