Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 19, issue 13
Articles | Volume 19, issue 13
https://doi.org/10.5194/acp-19-8759-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-19-8759-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 13
Research article
 | 
10 Jul 2019
Research article |  | 10 Jul 2019

Arctic cloud annual cycle biases in climate models

Patrick C. Taylor, Robyn C. Boeke, Ying Li, and David W. J. Thompson

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Cited articles

Barton, N. P., Klein, S. A., Boyle, J. S., and Zhang, Y. Y.: Arctic synoptic regimes: Comparing domain-wide Arctic cloud observations with CAM4 and CAM5 during similar dynamics, J. Geophys. Res.-Atmos., 117, D15205, https://doi.org/10.1029/2012JD017589, 2012. 
Beesley, J. A. and Moritz, R. E.: Toward an Explanation of the Annual Cycle of Cloudiness over the Arctic Ocean, J. Climate, 12, 395–415, https://doi.org/10.1175/1520-0442(1999)012<0395:TAEOTA>2.0.CO;2, 1999. 
Boeke, R. C. and Taylor, P. C.: Evaluation of the Arctic surface radiation budget in CMIP5 models, J. Geophys. Res.-Atmos., 121, 2016JD025099, https://doi.org/10.1002/2016JD025099, 2016. 
Boer, G., de Morrison, H., Shupe, M. D., and Hildner, R.: Evidence of liquid dependent ice nucleation in high-latitude stratiform clouds from surface remote sensors, Geophys. Res. Lett., 38, L01803, https://doi.org/10.1029/2010GL046016, 2011. 
Cesana, G., Kay, J. E., Chepfer, H., English, J. M., and de Boer, G.: Ubiquitous low-level liquid-containing Arctic clouds: New observations and climate model constraints from CALIPSO-GOCCP, Geophys. Res. Lett., 39, L20804, https://doi.org/10.1029/2012GL053385, 2012. 
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Climate projections disagree more in the rapidly changing Arctic than anywhere else. The impact of a 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 a key driver.
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