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Physical Mechanism of Formation of the Bimodal Structure in the Meiyu Front System |
CUI Xiao-Peng1;GAO Shou-Ting1;ZONG Zhi-Ping2;LIU Wen-Ming3;LI Xiao-Fan4 |
1Laboratory of Cloud-Precipitation Physics and Severe Storms (LACS), Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029
2National Meteorological Centre, China Meteorological Administration, Beijing 100081
3Liaoning Meteorological Observatory, Liaoning Meteorological Bureau, Shenyang 110016
4Joint Center for Satellite Data Assimilation and NOAA/NESDIS/Office of Research and Applications, Camp Springs, Maryland 21029, USA |
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Cite this article: |
CUI Xiao-Peng, GAO Shou-Ting, ZONG Zhi-Ping et al 2005 Chin. Phys. Lett. 22 3218-3220 |
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Abstract The bimodal structure of the Meiyu front system is readdressed after Zhou et al.(2005). The physical mechanism of the formation of the bimodal distribution is discussed. The bimodal structure of the Meiyu front system considerably results from atmospheric moisture gradients, though atmospheric temperature gradients are also not negligible. According to the definition of equivalent potential temperature, and by scale analysis, we find that atmospheric equivalent potential temperature gradients, which could be regarded as an indicator of the Meiyu front system, could be mainly attributed to the variations of atmospheric potential temperature gradients with a scaling factor of 1 and moisture gradients multiplied by a scaling factor of an order of about 2.5×103, which means that small variations of atmospheric moisture gradients could lead to large variations of equivalent potential temperature gradients, and thus large variations of the Meiyu front system. Quantitative diagnostics with a mesoscale simulation data in the vicinity of the Meiyu front system show that moisture gradients contribute to equivalent potential temperature gradients more than potential temperature gradients.
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Keywords:
92.60.Jq
92.60.Wc
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Published: 01 December 2005
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PACS: |
92.60.Jq
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(Water in the atmosphere)
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92.60.Wc
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(Weather analysis and prediction)
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