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Discussion papers
https://doi.org/10.5194/acp-2018-1159
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-2018-1159
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 21 Dec 2018

Research article | 21 Dec 2018

Review status
This discussion paper is a preprint. A revision of this manuscript was accepted for the journal Atmospheric Chemistry and Physics (ACP) and is expected to appear here in due course.

Arctic cloud annual cycle biases in climate models

Patrick C. Taylor1, Robyn C. Boeke2, Ying Li3, and David W. J. Thompson3 Patrick C. Taylor et al.
  • 1NASA Langley Research Center, Climate Science Branch, Hampton, Virginia, USA
  • 2Science Systems Applications Inc., Hampton, Virginia, USA
  • 3Colorado State University, Department of Atmospheric Science, Fort Collins, Colorado, USA

Abstract. Arctic clouds exhibit a robust annual cycle with maximum cloudiness in fall and minimum in winter. These variations affect energy flows in the Arctic with a large influence on the surface radiative fluxes. Contemporary climate models struggle to reproduce the observed Arctic cloud amount annual cycle and significantly disagree with each other. The goal of this analysis is to quantify the cloud influencing factors that contribute to winter-summer cloud amount differences, as these seasons are primarily responsible for the model discrepancies with observations. We find that differences in the total cloud amount annual cycle are primarily caused by differences in low, not high, clouds; the largest differences occur between the surface and 950 hPa. Stratifying cloud amount by cloud influencing factors, we find that model groups disagree most under strong lower tropospheric stability, weak to moderate mid-tropospheric subsidence, and cold lower tropospheric air temperatures. Inter-group differences in low cloud amount are found to be a function of the dependence of low cloud amount on the lower tropospheric thermodynamic characteristics. We find that models with a larger low cloud amount in winter produce more cloud ice, whereas models with a larger low cloud amount in summer produce more cloud liquid. Thus, the parameterization of ice microphysics, specifically the ice formation mechanism (deposition vs. immersion freezing) and cloud liquid and ice partitioning, contributes to the inter-model differences in the Arctic cloud annual cycle and provides further evidence of the important role that cloud ice microphysical processes play in the evolution and modeling of the Arctic climate system.

Patrick C. Taylor et al.
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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Interactive discussion
Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Patrick C. Taylor et al.
Patrick C. Taylor et al.
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Short summary
Climate projections disagree more In the rapidly changing Arctic than anywhere else. The impact of a rapid changing Arctic spans food and water security, economics, national security, etc. The representation of Arctic clouds within climate models is a critical roadblock towards improving Arctic climate projections. We explore the potential drivers of the diverse representation of the Arctic cloud annual cycle within climate models providing evidence that microphysical processes are the cause.
Climate projections disagree more In the rapidly changing Arctic than anywhere else. The impact...
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