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Seasonal cycle of idealized polar clouds: large eddy simulations driven by a GCM

Zhang, Xiyue and Schneider, Tapio and Shen, Zhaoyi and Pressel, Kyle G. and Eisenman, Ian (2020) Seasonal cycle of idealized polar clouds: large eddy simulations driven by a GCM. . (Unpublished)

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The uncertainty in polar cloud feedbacks calls for process understanding of the cloud response to climate warming. As an initial step, we investigate the seasonal cycle of polar clouds in the current climate by adopting a novel modeling framework using large eddy simulations (LES), which explicitly resolve cloud dynamics. Resolved horizontal and vertical advection of heat and moisture from an idealized GCM are prescribed as forcing in the LES. The LES are also forced with prescribed sea ice thickness, but surface temperature, atmospheric temperature, and moisture evolve freely without nudging. A semigray radiative transfer scheme, without water vapor or cloud feedbacks, allows the GCM and LES to achieve closed energy budgets more easily than would be possible with more complex schemes; this allows the mean states in the two models to be consistently compared, without the added complications from interaction with more comprehensive radiation. We show that the LES closely follow the GCM seasonal cycle, and the seasonal cycle of low clouds in the LES resembles observations: maximum cloud liquid occurs in late summer and early autumn, and winter clouds are dominated by ice in the upper troposphere. Large-scale advection of moisture provides the main source of water vapor for the liquid clouds in summer, while a temperature advection peak in winter makes the atmosphere relatively dry and reduces cloud condensate. The framework we develop and employ can be used broadly for studying cloud processes and the response of polar clouds to climate warming.

Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription Paper ItemGCM and LES codes ItemGCM forcing and LES output files
Zhang, Xiyue0000-0002-6031-7830
Schneider, Tapio0000-0001-5687-2287
Shen, Zhaoyi0000-0002-0444-4720
Pressel, Kyle G.0000-0002-4538-3055
Eisenman, Ian0000-0003-0190-2869
Additional Information:License: Attribution-NonCommercial-NoDerivatives 4.0 International. Published Online: Tue, 9 Jun 2020. X.Z. is supported by an Advanced Study Program postdoctoral fellowship from the National Center for Atmospheric Research. Part of this material is based upon work supported by the National Center for Atmospheric Research, which is a major facility sponsored by the National Science Foundation under Cooperative Agreement No. 1852977. Part of this research was supported by the generosity of Eric and Wendy Schmidt by recommendation of the Schmidt Futures program, by Mountain Philanthropies, and by the National Science Foundation (NSF grant AGS-1835860). Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration. The simulations were performed on Caltech's High Performing Cluster, which is partially supported by a grant from the Gordon and Betty Moore Foundation. The GCM and LES codes are available online at GCM forcing and LES output files are available online at
Funding AgencyGrant Number
National Center for Atmospheric Research (NCAR)UNSPECIFIED
Schmidt Futures ProgramUNSPECIFIED
Mountain PhilanthropiesUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Record Number:CaltechAUTHORS:20201027-125955966
Persistent URL:
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:106301
Deposited By: Tony Diaz
Deposited On:27 Oct 2020 21:06
Last Modified:27 Oct 2020 21:06

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