D02: Modelling marine organic aerosol and its impact on clouds in the Arctic
Aerosol and clouds impact the Arctic climate by affecting the radiation budget, precipitation and atmospheric dynamics at high and mid-latitudes. Current climate models, however, persistently show a spread in estimates of aerosol and aerosol-cloud effective forcing that is particularly large in the Arctic region. Major modelling challenges are the representation of mixed–phase Arctic clouds, aerosol–cloud interactions and the aerosol life cycle in the Arctic. In phase I, D02 improved the anthropogenic aerosol sources and long-range transport in the aerosol climate model using various data sources. D02 further proposed important revisions to the representation of Arctic clouds in the climate model after identifying shortcomings especially for mixed-phase boundary layer clouds in comparison to satellite observations. Building on these achievements, D02 focuses in the second phase on the role of local marine aerosol sources, and their impact on mixed-phase cloud microphysics and dynamics.
Global and Arctic-focused simulations with the weather and climate ICOsahedral Non-hydrostatic model (ICON) and the new aerosol climate model ICON-HAM will be used to assess current model uncertainties by comparing with field campaign measurements and new satellite remote sensing products of aerosol and cloud properties. While in phase I the focus largely has been on the evaluation of cloud distributions in the model, in phase II it will be the representation of boundary layer dynamics (cloud coupling state), mixed-phase cloud processes, and moisture supply by warm air intrusions from mid-latitudes. In terms of aerosol particles, we will build on our research from phase I, which has particularly addressed the role of black carbon in Arctic climate change, by broadening the focus on marine organic aerosol. The central question will be whether a feedback loop between sea ice retreat, oceanic aerosol emissions, and clouds impacted by extra cloud condensation nuclei (CCN) and ice nucleating particles (INP) does modulate the Arctic amplification.
To achieve the scientific goals, the model development in ICON-HAM will comprise extending the emission scheme for marine organic aerosol to consider different classes of species, such as marine sugars that are potentially highly cloud-active. The evaluation and improvement of the description of clouds and their effects will focus on the cloud thermodynamic phase and boundary layer structure and on exploring scale dependencies of vertical mixing and moisture supply. Newly developed satellite products will be used for model evaluations. The project will benefit greatly from the HALO-(AC)³ and MOSAiC observations, providing rich data on so far unprecedented spatial and temporal scales in the most under-explored parts of the Arctic.
A feedback loop between sea ice retreat, oceanic aerosol emissions, and clouds impacted by extra cloud condensation nuclei and ice nucleating particles enhances the Arctic amplification.
Specifically, D02 will answer the questions:
- When including marine organic aerosol emissions, and improving mixed- and ice-phase cloud microphysics, how much better is the model in comparison to new satellite observations, and in comparison to the reference ship- and airborne observations?
- What feedback loop involving marine organic aerosol and their impact on clouds is simulated by the revised model? What does this imply for Arctic amplification?
Achievements phase I
In D02, the relevant anthropogenic aerosol sources and impact of long-range transport were identified (Schacht et al., 2019). An evaluation of BC emission and transport uncertainties revealed that the latest, transient emission data sets produce 30 % higher BC burden in the Arctic, and that uncertainties in BC emissions may cause 20 % error in the direct radiative forcing estimates over the central Arctic (Schacht et al., 2019). Furthermore, propositions for important revisions of the cloud representation in the atmospheric model were investigated in a thorough evaluation using satellite data (Kretzschmar et al., 2019).
Role within (AC)³
Prof. Dr. Johannes Quaas
University of Leipzig
Leipzig Institute for Meteorology (LIM)
2021: The importance of the representation of DMS oxidation in global chemistry-climate simulations. Geophys. Res. Lett., 48, e2021GL094068. https://doi.org/10.1029/2021GL094068, , , , & ,
Schacht, J., 2021: Black Carbon Aerosol in the Arctic: Ageing, Transport and Radiative Effects, Dissertation, Universität Leipzig.
Kretzschmar, J., Stapf, J., Klocke, D., Wendisch, M., and Quaas, J., 2020: Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic, Atmos. Chem. Phys., 20, 13145–13165, https://doi.org/10.5194/acp-20-13145-2020.
Kretzschmar, J., M. Salzmann, J. Mülmenstädt, and J. Quaas, 2019: Arctic clouds in ECHAM6 and their sensitivity to cloud microphysics and surface fluxes, Atmos. Chem. Phys., 19, 10571–10589, doi:10.5194/acp-19-10571-2019
Schacht, J., B. Heinold, J. Quaas, J. Backman, R. Cherian, A. Ehrlich, A. Herber, W.T.K. Huang, Y. Kondo, A. Massling, P.R. Sinha, B. Weinzierl, M. Zanatta, and I. Tegen, 2019: The importance of the representation of air pollution emissions for the modeled distribution and radiative effects of black carbon in the Arctic, Atmos. Chem. Phys., 19, 11159–11183, https://doi.org/10.5194/acp-19-11159-2019
Wendisch, M., A. Macke, A. Ehrlich, C. Lüpkes, M. Mech, D. Chechin, K. Dethloff, C. Barrientos, H. Bozem, M. Brückner, H.-C. Clemen, S. Crewell, T. Donth, R. Dupuy, C. Dusny, K. Ebell, U. Egerer, R. Engelmann, C. Engler, O. Eppers, M. Gehrmann, X. Gong, M. Gottschalk, C. Gourbeyre, H. Griesche, J. Hartmann, M. Hartmann, B. Heinold, A. Herber, H. Herrmann, G. Heygster, P. Hoor, S. Jafariserajehlou, E. Jäkel, E. Järvinen, O. Jourdan, U. Kästner, S. Kecorius, E.M. Knudsen, F. Köllner, J. Kretzschmar, L. Lelli, D. Leroy, M. Maturilli, L. Mei, S. Mertes, G. Mioche, R. Neuber, M. Nicolaus, T. Nomokonova, J. Notholt, M. Palm, M. van Pinxteren, J. Quaas, P. Richter, E. Ruiz-Donoso, M. Schäfer, K. Schmieder, M. Schnaiter, J. Schneider, A. Schwarzenböck, P. Seifert, M.D. Shupe, H. Siebert, G. Spreen, J. Stapf, F. Stratmann, T. Vogl, A. Welti, H. Wex, A. Wiedensohler, M. Zanatta, S. Zeppenfeld, 2019: The Arctic Cloud Puzzle: Using ACLOUD/PASCAL Multi-Platform Observations to Unravel the Role of Clouds and Aerosol Particles in Arctic Amplification, Bull. Amer. Meteor. Soc., 100 (5), 841–871, doi:10.1175/BAMS-D-18-0072.1
Knudsen, E.M., B. Heinold, S. Dahlke, H. Bozem, S. Crewell, I. V. Gorodetskaya, G. Heygster, D. Kunkel, M. Maturilli, M. Mech, C. Viceto, A. Rinke, H. Schmithüsen, A. Ehrlich, A. Macke, C. Lüpkes, M. Wendisch, 2018: Meteorological conditions during the ACLOUD/PASCAL field campaign near Svalbard in early summer 2017, Atmos. Chem. Phys., 18, 17995-18022, doi:10.5194/acp-18-17995-2018
Wendisch, M., M. Brückner, J. P. Burrows, S. Crewell, K. Dethloff, K. Ebell, Ch. Lüpkes, A. Macke, J. Notholt, J. Quaas, A. Rinke, and I. Tegen, 2017: Understanding causes and effects of rapid warming in the Arctic. Eos, 98, doi:10.1029/2017EO064803