Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence
Incorporating the Effects of Moisture into a Dynamical Parameter: Moist Vorticity and Moist Divergence
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DOI：
10.1175/waf-d-14-00154.1
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发表时间：
2015-04
影响因子：
2.9
通讯作者：
W. Qian;Jun Du;X. Shan;Ning Jiang
中科院分区：
文献类型：
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作者：
W. Qian;Jun Du;X. Shan;Ning Jiang
摘要适当地将湿度效应纳入动力参数，可以显著提高参数对暴雨位置的诊断能力。分析了基于相对湿度的加权法将湿位涡（MPV）扩展为广义湿位涡（GMPV）的改进。本文采用相同的方法，将湿涡度（MV）和湿散度（MD）两个新的诊断参数纳入传统的涡度和散度中。以1991年7月1日长江流域的一次区域性暴雨为例，并以1998年中国东部洪涝年的41次区域性暴雨为例进行系统评价。结果表明，在适当考虑湿度影响后，这三个参数对暴雨区域的捕获能力显著提高（统计上在99%的置信度下）。
AbstractProperly including moisture effects into a dynamical parameter can significantly increase the parameter’s ability to diagnose heavy rain locations. The relative humidity–based weighting approach used to extend the moist potential vorticity (MPV) to the generalized moist potential vorticity (GMPV) is analyzed and demonstrates such an improvement. Following the same approach, two new diagnostic parameters, moist vorticity (MV) and moist divergence (MD), have been proposed in this study by incorporating moisture effects into the traditional vorticity and divergence. A regional heavy rain event that occurred along the Yangtze River on 1 July 1991 is used as a case study, and 41 daily regional heavy rain events during the notorious flooding year of 1998 in eastern China are used for a systematic evaluation. Results show that after the moisture effects were properly incorporated, the improved ability of all three parameters to capture a heavy rain area is significant (statistically at the 99% confidence...