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Atmospheric Chemistry and Physics An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/acp-2020-641
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2020-641
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

  02 Jul 2020

02 Jul 2020

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A revised version of this preprint was accepted for the journal ACP and is expected to appear here in due course.

Employing airborne radiation and cloud microphysics observations to improve cloud representation in ICON at kilometer-scale resolution in the Arctic

Jan Kretzschmar1, Johannes Stapf1, Daniel Klocke2,3, Manfred Wendisch1, and Johannes Quaas1 Jan Kretzschmar et al.
  • 1Institute for Meteorology, Universität Leipzig, Leipzig, Germany
  • 2Deutscher Wetterdienst, Offenbach, Germany
  • 3Hans-Ertel-Zentrum für Wetterforschung, Offenbach, Germany

Abstract. Clouds play a potentially important role in Arctic climate change, but are poorly represented in current atmospheric models across scales. To improve the representation of Arctic clouds in models, it is necessary to compare models to observations to consequently reduce this uncertainty. This study compares aircraft observations from the Arctic Cloud Observations Using Airborne Measurements during Polar Day (ACLOUD) campaign in May/June 2017 around Svalbard, Norway – to simulations using the ICON (ICOsahedral Non-hydrostatic) model in its numerical weather prediction (NWP) set-up at 1.2 km resolution. By comparing measurements of solar and terrestrial irradiances during ACLOUD flights to the respective properties in ICON, we showed that the model systematically overestimates the transmissivity of the mostly liquid clouds during the campaign. This model bias is traced back to the way cloud condensation nuclei (CCN) get activated into cloud droplets in the two-moment, bulk microphysical scheme used in this study. This process is parameterized as function of grid-scale vertical velocity in the microphysical scheme used, but in-cloud turbulence cannot sufficiently be resolved at 1.2 km horizontal resolution in Arctic clouds. By parameterizing subgrid-scale vertical motion as a function of turbulent kinetic energy, we are able to achieve a more realistic CCN activation into cloud droplets. Additionally, we showed that by scaling the presently used CCN activation profile, the hydrometeor number concentration could be modified to be in better agreement with ACLOUD observations in our revised CCN activation parameterization. This consequently results in an improved representation of cloud optical properties in our ICON simulations.

Jan Kretzschmar et al.

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Status: closed
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Jan Kretzschmar et al.

Jan Kretzschmar et al.

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Latest update: 29 Sep 2020
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Short summary
This study compares simulations with the ICON model at kilometer-scale to airborne radiation and cloud microphysics observations that have been derived during the ACLOUD aircraft campaign in May/June 2017 around Svalbard, Norway. We find an overestimated surface warming effect of clouds compared to the observations in our set-up. This bias was reduced by considering subgrid-scale vertical motion in the activation of cloud condensation nuclei in the two-moment microphysical scheme used.
This study compares simulations with the ICON model at kilometer-scale to airborne radiation and...
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