globalchange  > 影响、适应和脆弱性
DOI: 10.1002/2016JD026404
论文题名:
An investigation of microphysics and subgrid-scale variability in warm-rain clouds using the A-Train observations and a multiscale modeling framework
作者: Takahashi H.; Lebsock M.; Suzuki K.; Stephens G.; Wang M.
刊名: Journal of Geophysical Research: Atmospheres
ISSN: 2169897X
出版年: 2017
卷: 122, 期:14
起始页码: 7493
结束页码: 7504
语种: 英语
英文关键词: multiscale modeling framework ; subgrid-scale variability ; warm-rain clouds
英文摘要: A common problem in climate models is that they are likely to produce rain at a faster rate than is observed and therefore produce too much light rain (e.g., drizzle). Interestingly, the Pacific Northwest National Laboratory (PNNL) multiscale modeling framework (MMF), whose warm-rain formation process is more realistic than other global models, has the opposite problem: the rain formation process in PNNL-MMF is less efficient than the real world. To better understand the microphysical processes in warm cloud, this study documents the model biases in PNNL-MMF and evaluates warm cloud properties, subgrid variability, and microphysics, using A-Train satellite observations to identify sources of model biases in PNNL-MMF. Like other models PNNL-MMF underpredicts the warm cloud fraction with compensating large optical depths. Associated with these compensating errors in cloudiness are compensating errors in the precipitation process. For a given liquid water path, clouds in the PNNL-MMF are less likely to produce rain than are real-world clouds. However, when the model does produce rain it is able to produce stronger precipitation than reality. As a result PNNL-MMF produces about the correct mean rain rate with an incorrect distribution of rates. The subgrid variability in PNNL-MMF is also tested, and results are fairly consistent with observations, suggesting that the possible sources of model biases are likely to be due to errors in its microphysics or dynamics rather than errors in the subgrid-scale variability produced by the embedded cloud resolving model. ©2017. American Geophysical Union. All Rights Reserved.
资助项目: NA15OAR4310153 ; NNN13D455T
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/62621
Appears in Collections:影响、适应和脆弱性
气候减缓与适应

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作者单位: Joint Institute for Regional Earth System Science and Engineering, University of California, Los Angeles, CA, United States; Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, United States; Atmosphere and Ocean Research Institute, University of Tokyo, Chiba, Japan; Department of Meteorology, University of Reading, Reading, United Kingdom; Institute for Climate and Global Change Research, and School of Atmospheric Sciences, Nanjing University, Nanjing, China; Collaborative Innovation Center of Climate Change, Nanjing, China

Recommended Citation:
Takahashi H.,Lebsock M.,Suzuki K.,et al. An investigation of microphysics and subgrid-scale variability in warm-rain clouds using the A-Train observations and a multiscale modeling framework[J]. Journal of Geophysical Research: Atmospheres,2017-01-01,122(14)
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