EGU22-980, updated on 19 Jul 2023
EGU General Assembly 2022
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The impact of assimilating AEOLUS wind data on regional Aeolian dust model simulations using WRF-Chem.

Pantelis Kiriakidis1, Antonis Gkikas2, George Papangelis2, Jonilda Kushta1, Theodoros Christoudias1, Eleni Drakaki2, Emmanouil Proestakis2, Eleni Marinou2, Anna Gialitaki2,3, Anna Kampouri2, Christos Spyrou2, Angela Benedetti4, Michael Rennie4, Anna Grete Straume5, Christian Retscher6, Alexandru Dandocsi6, Jean Sciare1, and Vassilis Amiridis2
Pantelis Kiriakidis et al.
  • 1Environmental Predictions Department, The Cyprus Institute (CyI), Nicosia, Cyprus
  • 2Institute for Astronomy, Astrophysics, Space Applications and Remote Sensing, National Observatory of Athens (IAASARS/NOA), Athens, Greece
  • 3Laboratory of Atmospheric Physics, Aristotle University of Thessaloniki (AUTH), Thessaloniki, Greece
  • 4European Centre for Medium Range Weather Forecasts (ECMWF), Reading, UK
  • 5European Space Agency (ESA/ESTEC), Noordwijk, Netherlands
  • 6European Space Agency (ESA/ESRIN), Frascati, Italy

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 dust monitoring and forEcasting through Aeolus Wind daTa assimilatiON) ESA project. 

Towards this goal, the Weather Research and Forecasting regional atmospheric model 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 (extinction coefficient, optical depth and concentrations) are qualitatively and quantitatively evaluated against ground-based columnar and vertically resolved aerosol optical properties acquired by AERONET sun photometers and PollyXT lidar, as well as near-surface concentrations available through EMEP. Our assessment further includes comparison versus LIVAS and MIDAS satellite-derived datasets providing vertical and columnar dust optical properties, respectively. 

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 varies in 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 the 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 remarkable 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), meanwhile for several AERONET stations there was an average improvement in the correlation of assimilated outputs compared to control ones. 

How to cite: Kiriakidis, P., Gkikas, A., Papangelis, G., Kushta, J., Christoudias, T., Drakaki, E., Proestakis, E., Marinou, E., Gialitaki, A., Kampouri, A., Spyrou, C., Benedetti, A., Rennie, M., Straume, A. G., Retscher, C., Dandocsi, A., Sciare, J., and Amiridis, V.: The impact of assimilating AEOLUS wind data on regional Aeolian dust model simulations using WRF-Chem., EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-980,, 2022.