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

Jan Kretzschmar,Johannes Stapf,Daniel Klocke,Manfred Wendisch,Johannes Quaas

doi:10.5194/acp-20-13145-2020

Abstract

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 around Svalbard, Norway, in May–June 2017 and simulations using the ICON (ICOsahedral Non-hydrostatic) model in its numerical weather prediction (NWP) setup at 1.2 km horizontal 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 a function of grid-scale vertical velocity in the microphysical scheme used, but in-cloud turbulence cannot be sufficiently 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.

Highlights

In recent decades, the Arctic has proven to be especially susceptible to global climate change (Screen and Simmonds, 2010), as several positive feedback mechanisms strengthen the warming in high latitudes of the Northern Hemisphere (Serreze and Barry, 2011; Wendisch et al, 2017)
Looking at median values of the spectral components, we find that differences between simulated and observed net surface irradiances are mainly mediated by its solar component, while the median of net terrestrial surface irradiances are well simulated by ICOsahedral Non-hydrostatic (ICON); the shapes of their histograms match better
We focus on particle size distribution of hydrometeors and the respective moments, which have been observed by the Small Ice Detector mark 3 (SID-3), covering a size range of cloud droplets or ice crystals from 5 to 40 μm

Summary

Introduction

The Arctic has proven to be especially susceptible to global climate change (Screen and Simmonds, 2010), as several positive feedback mechanisms strengthen the warming in high latitudes of the Northern Hemisphere (Serreze and Barry, 2011; Wendisch et al, 2017) Among those feedback mechanisms that influence the Arctic climate, the cloud feedback – even though being small in magnitude compared to other feedback mechanisms like the surface albedo or temperature feedbacks – exhibits a relatively large uncertainty (Pithan and Mauritsen, 2014; Block et al, 2020). This affects the quantification of the effect of Arctic clouds on the (surface) energy budget in GCMs (Karlsson and Svensson, 2013).

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Discussion

Conclusion