青藏高原东部暴雨云团局地强降水响应特征
Characteristics of rainstorm cloud clusters to local heavy precipitation over the eastern Qinghai-Tibet Plateau
- 2014年18卷第2期 页码:405-431
纸质出版日期: 2014
DOI: 10.11834/jrs.20143069
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纸质出版日期: 2014 ,
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[1]朱平,李生辰,王振会,肖建设.青藏高原东部暴雨云团局地强降水响应特征[J].遥感学报,2014,18(02):405-431.
ZHU Ping, LI Shengchen, WANG Zhenhui, et al. Characteristics of rainstorm cloud clusters to local heavy precipitation over the eastern Qinghai-Tibet Plateau[J]. Journal of Remote Sensing, 2014,18(2):405-431.
为研究青藏高原(简称"高原")东部暴雨云团的局地强降水响应特征
使用FY-2卫星红外通道数据
选择降水开始前4小时直到降水结束后2小时的时段
对高原东部19次典型局地暴雨过程分两种方式进行云团分析
第一种方式为针对测站上空7×7像元范围的云团进行云顶温度变化等相关分析
第二种方式为对关键四省范围内的云团进行识别和追踪
并计算对流云团参数。对暴雨云团的雷达回波特征也进行了分析。结果表明:(1)7×7像元范围红外各通道的云顶温度变化趋势一致
降水阶段云顶温度先降后升
云顶温度梯度先升后降。云顶温度梯度极大值Gmax的峰值和半小时内Gmax的最大上升变化值ΔGmax均出现在强降水前(0—11 h)
Gmax峰值次数为1—2次
云顶温度极小值Tmin的谷值多出现在强降水之前
Tmin曲线斜率大值阶段对应Gmax的大值阶段
ΔGmax
Gmax和Tmin的极值分别可达到22.3℃
48.3℃和-90.3℃。(2)用7×7范围云顶温度及温度梯度建立的降水量级预报方程能较好地模拟小时降水量随时间的变化趋势且有一定的预报提前时间
预报误差在1个降水量级内。在考虑了Gmax峰值对强降水的贡献后R2由0.23提高到0.54
模拟的降水量峰值与真值峰值明显接近。(3)对流云团的识别追踪方法更简单有效
对形变较小的云团(相关系数≥0.5)的准确率为100%
对发生了合并或分裂等严重形变的云团(一般相关系数<0.5)的识别结果正确而追踪结果无效;(4)高原东部暴雨云团均为中-β—中-α尺度
水汽柱深厚但强度比低海拔地区更弱
测站暴雨开始之前多数有对流云团覆盖
若对流云团空间参数位置靠近测站
当空间距离至少小于或等于15个像距时降水或强降水将在几小时内产生。(5)暴雨云团在雷达回波图上表现为强降水超级单体风暴特征
且暴雨测站7×7范围Gmax峰值时刻对应有回波顶高度(18 dBz)的梯度极大值
红外1、红外2和红外3通道的Tmin谷值时刻分别对应回波顶高度极大值和垂直累积液态水含量的极大值。本研究结果对高原强对流云团的识别、跟踪及短时降水预报等具有重要参考价值。
To investigate the characteristics of rainstorm clouds to local precipitation
we analyzed 19 typical cases of rainstorm process in the Eastern Qinghai-Tibetan Plateau from four hours before precipitation to two hours after based on the cloud-top t emperature data of FY-2 infrared channels. Two patterns were found
and the first was the trend of temperature at the 7 × 7 pixels region centered at automatic meteorological stations
and the second was the analysis of convection parameters through identification and tracking convective clouds. In addition
the characteristics of radar echo of rainstorm clouds were also analyzed. In this p aper
the maximum temperature gradient on cloud top is represented as Gmax
the maximum amplitude of Gmaxwithin the half-hour is expressed in ΔGmax
and the minimum temperature on cloud top is denoted by Tmin. We found that the variation trend of cloud-top temperature and temperature gradient at infrared channels were consistent
and the cloud-top temperature showed a decrease before increase while the temperature gradient was the opposite in precipitation stage. One or two peaks of Gmaxand ΔGmaxhappened about0 to 11 hours earlier than the heavy precipitation. The multiple regression equation for forecasting precipitation grade was constructed by Tminand Gmax. It showed that the model can well simulate the tendency of hourly precipitation and can also predict heavy rain
and the error of hourly precipitation is within one grade of precipitation. The R2of regression improved from 0. 23 to 0. 54
and the precipitation peak can be better modeled after considering the contribution of Gmaxpeak. The new algorithm of clouds identification and tracking is more simple and effective than other methods. All rainstorm cloud clusters over eastern Plateau are at mid-β to mid-α scale
and their height of water vapor columns are deep but the intensity are weaker than that of the lower altitudes. The p recipitation will happen within several hours when the minimum distance between the position of clouds extremum and the meteorological station is less than 15 pixels. The rainstorm clouds have the characteristics of heavy precipitation super cell storm in r adar echo
and the extremes of Tminand Gmaxcorrespond with the extremes of vertical integrated liquid water content
echo-top height and its gradient. These results are important for identification and tracking strong convective cloud clusters and short-time precipitation forecasting in eastern Qinghai-Tibetan Plateau.
红外通道局地暴雨云团识别和跟踪短时降水预报
infrared channelslocal rainstorms cloud clustersidentification and trackingshort-time precipitation forecasting
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