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蒋 艳, 贺新光, 章新平.长江流域极端降水与当地平均气温的响应关系分析水资源与水工程学报[J].,2023,34(1):40-49
长江流域极端降水与当地平均气温的响应关系分析
Response of extreme precipitation to local average temperature in the Yangtze River Basin
  
DOI:10.11705/j.issn.1672-643X.2023.01.05
中文关键词:  极端降水  当地平均气温  非平稳性  响应关系  Clausius-Clapeyron变率  长江流域
英文关键词:extreme precipitation  local average temperature  non-stationarity  response  Clausius-Clapeyron scaling  the Yangtze River Basin
基金项目:湖南省教育厅创新平台开放基金项目(18K018)
作者单位
蒋 艳1,2, 贺新光1,2, 章新平1,2 (1.湖南师范大学 地理科学学院 湖南 长沙 410081 2.地理空间大数据挖掘与应用湖南省重点实验室 湖南 长沙 410081) 
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中文摘要:
      研究极端降水的非平稳性及对气温的响应有助于应对相关灾害事件带来的消极影响。基于长江流域1961-2020年降水和气温格点数据,建立广义极值模型以确定当日(T0)和前1~9 d(T1-9)当地平均气温是否会引起极端降水的非平稳性,然后通过等样本箱元法、分段线性回归法和指数回归法探讨极端降水对T0T1-9的响应。结果表明:长江流域99.7%格点的极端降水是非平稳的,T0T1-9共驱动74.4%格点的极端降水向非平稳演变,且T1-9对极端降水的影响更大。流域极端降水随T0升高主要呈低温时增加而高温时减少的峰值型结构,且峰值点气温以青藏高原东缘为界西低而东高并分别集中于9 ℃和24 ℃左右;同时,极端降水随T0的变化率介于(-12.3%~53.6%)/℃之间,并以四川盆地为中心向四周呈超CC(Clausius-Clapeyron)、类CC和次CC变率的分布格局。极端降水随T1-9上升在流域西部主要呈增加趋势而在中东部主要为峰值型结构,且峰值点在降水强度最大时出现在25 ℃附近;此外,极端降水随T1-9的变化率由西至东从超CC变率过渡到类CC和次CC变率,并处于(-3.7%~33.8%)/℃之间且集中于4%/℃和10%/℃附近。随着降水极端性的增强,极端降水对气温变化的敏感性降低从而使其变化率的范围缩小;此外,超CC变率可能与对流降水和潜热释放等相联系,而峰值型结构或许与降水的冷却作用以及反气旋活动等有关。
英文摘要:
      Studying the non-stationarity of extreme precipitation and its response to temperature can help the fight against the negative effects from rainfall-related hazards. Based on the grid dataset of daily precipitation and temperature over the Yangtze River Basin from 1961 to 2020, the generalized extreme value models are established to confirm whether the previous 0-day (T0) and the previous 9-day (T1-9) local average temperatures would cause non-stationarity in extreme precipitation. Then the responses of extreme precipitation to T0 and T1-9 are investigated by equal sample binning method, piecewise linear regression and exponential regression. The results showed that the extreme precipitation was non-stationary at 99.7% of the grids of the basin, T0 and T1-9 induced non-stationarity in extreme precipitation at 74.4% of the grids, and T1-9 had a greater impact on extreme precipitation than T0. Extreme precipitation intensity increased at low temperature but decreased at high temperature (peak structure) with the rise of T0 in the basin. Besides, there was an obvious dividing line at the eastern margin of the Tibetan Plateau, and the peak-point temperature was higher (about 24℃) in the east but lower (about 9℃) in the west of this line. Meanwhile, the scaling rate of extreme precipitation with T0 range from -12.3%/℃ to 53.6%/℃ and showed a “super-CC, CC-like and sub-CC scaling” pattern from Sichuan Basin center to the surrounding areas. Extreme precipitation intensity with increasing T1-9 mainly showed an upward trend in the west while peak structure in the east-central region of the basin, and the intensity of the heaviest extreme precipitation reached its peak when the temperature was close to 25 ℃. Furthermore, the scaling rate of extreme precipitation with T1-9 roughly exhibited a pattern of super-CC to CC-like to sub-CC scaling from west to east over the basin, and the scaling rate fell within a range of -3.7%/℃ to 33.8%/℃, which was mainly concentrated in the vicinity of 4%/℃ and 10%/℃. With the increase of precipitation intensity, the range of scaling change shortened owing to the decrease of sensitivity of extreme precipitation to temperature change. In addition, it was speculated that the super-CC scaling could result from convective precipitation, latent heat release and so on, and the peak structure could be related to cooling effect of precipitation, anticyclonic activities, etc.
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