Evaluation of the CMIP6 marine subtropical stratocumulus cloud albedo and its controlling factors
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Published:2021-06-30
Issue:12
Volume:21
Page:9809-9828
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ISSN:1680-7324
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Container-title:Atmospheric Chemistry and Physics
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language:en
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Short-container-title:Atmos. Chem. Phys.
Author:
Jian Bida, Li Jiming, Wang Guoyin, Zhao Yuxin, Li Yarong, Wang Jing, Zhang Min, Huang JianpingORCID
Abstract
Abstract. The cloud albedo in the marine subtropical stratocumulus
regions plays a key role in regulating the regional energy budget. Based on
12 years of monthly data from multiple satellite datasets, the long-term,
monthly and seasonal cycle of averaged cloud albedo in five stratocumulus
regions were investigated to intercompare the atmosphere-only simulations
between phases 5 and 6 of the Coupled Model Intercomparison Project (AMIP5
and AMIP6). Statistical results showed that the long-term regressed cloud
albedos were underestimated in most AMIP6 models compared with the
satellite-driven cloud albedos, and the AMIP6 models produced a similar
spread as AMIP5 over all regions. The monthly averaged values and seasonal
cycle of cloud albedo of AMIP6 ensemble mean showed a better correlation
with the satellite-driven observations than that of the AMIP5 ensemble mean.
However, the AMIP6 model still failed to reproduce the values and amplitude
in some regions. By employing the Modern-Era Retrospective Analysis for
Research and Applications Version 2 (MERRA-2) data, this study estimated the relative
contributions of different aerosols and meteorological factors on the
long-term variation of marine stratocumulus cloud albedo under different
cloud liquid water path (LWP) conditions. The multiple regression models can
explain ∼ 65 % of the changes in the cloud albedo. Under
the monthly mean LWP ≤ 65 g m−2, dust and black carbon dominantly
contributed to the changes in the cloud albedo, while dust and sulfur
dioxide aerosol contributed the most under the condition of 65 g m−2 < LWP ≤ 120 g m−2. These results suggest that the
parameterization of cloud–aerosol interactions is crucial for accurately
simulating the cloud albedo in climate models.
Publisher
Copernicus GmbH
Subject
Atmospheric Science
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