Investigating dust mixing state, using the backscatter of realistic dust shapes

We investigate the dust mixing state using airborne and ground-based measurements of particle linear depolarization ratio (PLDR) at 1064nm, with the innovation of using scattering calculations considering the realistic shapes of the particles.The accurate modelling of the optical properties of atmospheric mineral dust particles is an open scientific question, particularly for the backscatter, mainly due to the irregular shape and large size of the particles. Scattering calculations considering realistic irregular shapes are computationally costly, and as of yet, are provided in a tabulated form, only from the MOPSMAP scattering database for (cross-section-equivalent) size parameters up to 30, for the irregular shapes presented in Gasteiger et al. (2011) using the ADDA code. We have extended these calculations to size parameters up to 68, for four dust refractive indices ((1.48-1.6) + i(0-0.002)).Our calculations show that the PLDR of dust particles with realistic shapes is 30-40% at 1064nm, regardless the particle size and refractive index (within the range of the latter’s climatological values). Observations that provide smaller values may indicate dust mixed with other aerosol types. We investigate the dust (external) mixing state, using ground-based and airborne PLDR observations, along with airborne in-situ size and aspect ratio distributions, at Cabo Verde, during the ASKOS-ESA and CPEX-CV campaigns in June and September 2022.For size parameters >70 the ADDA calculations are challenging even for high-performance computing (HPC) systems, due to the large number of dipoles needed and the very slow convergence of the iterative solver. Thus, in order to formulate a complete (back)scattering database for dust we further investigate the applicability of the much faster Physical Optics (PO) approximation for dust particles with faceted shapes. Acknowledgements:This work has been financially supported by the Obs3RvE (Optimising 3D RT Earthcare product using geostationary observations and AI) project, funded from the European Space Agency under Contract No. 4000147848/25/I/AG, the CERTAINTY project (Grant Agreement 101137680) funded by Horizon Europe program. It is also based upon work from COST Action EARLICOST, CA24135, supported by COST (European Cooperation in Science and Technology). The calculations using the PO approximation were supported by the Ministry of Science and Higher Education of the Russian Federation (V.E. Zuev Institute of Atmospheric Optics SB RAS). ΑΤ would like to acknowledge COST Action HARMONIA (International network for harmonization of atmospheric aerosol retrievals from ground-based photometers), CA21119, supported by COST (European Cooperation in Science and Technology). We acknowledge the Dust-DN project, funded by the European Union under the Marie Skłodowska-Curie Actions (grant agreement 101168425), and by the corresponding national agencies of the United Kingdom (UKRI) and Switzerland (SERI). The views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union and Marie Skłodowska-Curie Actions (MSCA). Neither the European Union nor MSCA can be held responsible for them.