Mineralogy sensitive immersion freezing parameterization in DREAM

Dust aerosols are abundant in the atmosphere and are very efficient ice nucleating particles at temperatures below −15°C. Depending on temperature, dust particles containing certain minerals (i.e., feldspar and quartz) are the most active as ice nuclei. A mineralogy-sensitive immersion freezing parameterization for ice nucleating particle concentration (INPC) is implemented in Dust Regional Atmospheric Model (DREAM) for the first time. Additionally, four mineralogy-indifferent parameterizations are implemented, two for immersion freezing and two for deposition nucleation. Dust concentration and its feldspar and quartz fractions are forecasted by DREAM for a dust episode in the Mediterranean in April 2016. DREAM results are compared with vertical profiles of cloud-relevant dust concentrations and INPC from ground-based lidar measurements in Potenza, Italy and Nicosia, Cyprus. INPC predictions are also compared with vertical profiles of ice crystal number concentration (ICNC) from satellite observations for two overpasses over the dust plume. The model successfully simulates the evolution and vertical extent of the dust plume. Mineralogy-sensitive and mineralogy-indifferent INPC parameterization results generally differ by about an order of magnitude. Forecasted INPC and observed ICNC values differ by an order of magnitude for all parameterizations. Feldspar fraction increase within a dust plume during transport can increase INPC by around 6% at −35°C, and up to 17% at −25°C, but sedimentation can reduce this effect. Over the Atlantic, mineralogy-sensitive parameterization predicts horizontal distribution of clouds with higher probability of success, while in the Mediterranean; the results for different parameterizations show lower variability.Authors LI, AJ, and MK acknowledge funding provided by the Institute of Physics Belgrade, through the grant by the Ministry of Education, Science, and Technological Development of the Republic of Serbia. EM is grateful to Dr. Jean Sciare for hosting the PollyXT-NOA lidar in the Cyprus institute during the INUIT-BACCHUS-ACTRIS experiment. We thank EARLINET (https://www.earlinet.org/, last access: 12 December 2020), ACTRIS (https://www.actris.eu, last access: 12 December 2020) and PollyNET (http://polly.tropos.de, last access: 15March 2021) for the data collection, calibration, processing and dissemination. We thank the PollyNet group for their support during the development and operation of the PollyXT-NOA lidar system. We are grateful to the AERIS/ICARE Data and Services Center for generating and storing the DARDAR products and for providing access to the CALIPSO data used and their computational center (http://www.icare.univ-lille1.fr/, last access: 8 August 2019). We thank the NASA CloudSat Project and NASA/LaRC/ASDC for making available the CloudSat and CALIPSO products, respectively, which are used to build the synergetic DARDAR products. We are grateful to Jann Schrod and Bingemer Heinz G. for the provision of UAV-FRIDGE measurement data. The NUIT-BACCHUS-ACTRIS experiment received support from the Deutsche Forschungsgemeinschaft (grant no. 1525, INUIT), the European Union’s Seventh Frame-work813 Program (grant no. 603445, BACCHUS), the European Union’s Horizon 2020 research and innovation program (654109,ACTRIS-2). EM was funded by the European Research Council (grant no. 725698, D-TECT) and by a DLR VO-R young investigator group and the Deutscher Akademischer Austauschdienst (grant no. 57370121).Peer ReviewedPostprint (author's final draft