Evaluation of cloud properties in the NCEP CFSv2 model and its linkage with Indian summer monsoon

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• 作者：Anupam Hazra ; Hemantkumar S. Chaudhari…
• 刊名：Theoretical and Applied Climatology
• 出版年：2016
• 出版时间：April 2016
• 年：2016
• 卷：124
• 期：1-2
• 页码：31-41
• 全文大小：1,548 KB
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• 作者单位：Anupam Hazra (1)
  Hemantkumar S. Chaudhari (1)
  Ashish Dhakate (1)
  
  1. Indian Institute of Tropical Meteorology, Dr. Homi Bhabha Road, Pashan, Pune, India
  
• 刊物类别：Earth and Environmental Science
• 刊物主题：Earth sciences
  Meteorology and Climatology
  Atmospheric Protection, Air Quality Control and Air Pollution
  Climate Change
  Waste Water Technology, Water Pollution Control, Water Management and Aquatic Pollution
  
• 出版者：Springer Wien
• ISSN：1434-4483

文摘

Cloud fraction, which varies greatly among general circulation models, plays a crucial role in simulation of Indian summer monsoon rainfall (ISMR). The NCEP Climate Forecast System version 2 (CFSv2) model is evaluated in terms of its simulation of cloud fraction, cloud condensate, outgoing longwave radiation (OLR), and tropospheric temperature (TT). Biases in these simulated quantities are computed using observations from CALIPSO and reanalysis data from MERRA. It is shown that CFSv2 underestimates (overestimates) high- (mid-) level clouds. The cloud condensate is also examined to see its impact on different types of clouds. The upper-level cloud condensate is underestimated, particularly during the summer monsoon period, which leads to a cold TT and a dry precipitation bias. The unrealistically weak TT gradient between ocean and land is responsible for the underestimation of ISMR. The model-simulated OLR is overestimated which depicts the weaker convective activity. A large underestimate of precipitable water is also seen along the cross-equatorial flow and particularly over the Indian land region collocated with a dry precipitation bias. The linkages among cloud microphysical, thermodynamical, and dynamical processes are identified here. Thus, this study highlights the importance of cloud properties, a major cause of uncertainty in CFSv2, and also proposes a pathway for improvements in its simulation of the Indian summer monsoon.