中国农业气象 ›› 2019, Vol. 40 ›› Issue (01): 1-14.doi: 10.3969/j.issn.1000-6362.2019.01.001

• 论文 •    下一篇

中国西南部区域雨季极端降水指数时空变化特征

王昊,姜超,王鹤松,孙建新   

  1. 北京林业大学林学院,北京 100083
  • 出版日期:2019-01-20 发布日期:2019-01-22
  • 作者简介:王昊(1994?),硕士生,主要研究方向为全球变化生态学。E-mail:wh260012@163.com
  • 基金资助:

    国家重点研发计划(2016YFC0502104)

Spatial and Temporal Variation of Extreme Precipitation Indices in Southwestern China in the Rainy Season

WANG Hao, JIANG Chao, WANG He-song, SUN Jian-xin   

  1. College of Forestry, Beijing Forestry University, Beijing 100083, China
  • Online:2019-01-20 Published:2019-01-22

摘要:

基于1971-2013年中国西南部区域7省市477个气象站点的逐日降水观测资料,选取11个极端降水指数,运用线性倾向法、Mann-Kendall突变检验法和滑动t检验法分析了西南部地区雨季极端降水指数的时空分布及变化特征,并探究极端降水指数多年平均以及变化趋势与海拔高度的关系。结果表明:(1)近43a来,西南部地区雨季PRCPTOT、CWD、R1mm、R10mm以及SDII分别以12.6mm·10a?1、0.23d·10a-1、1.57d·10a-1、0.49d·10a-1和0.31mm·d-1·10a-1的速率下降(P<0.05),CDD上升速率为0.37d·10a-1(P<0.05),而Rx1day、Rx5day、R95、R99以及R20mm的变化不显著。(2)雨季CDD、R1mm、Rx1day的突变集中发生在20世纪80年代,而PRCPTOT、R10mm、Rx5day和SDII的突变主要发生在2003年前后;PRCPTOT、CDD、R1mm、R10mm、Rx1day和SDII在突变年份以前表现出一定的稳定性,而在突变年份以后则会发生显著的上升或下降趋势。(3)从变化趋势空间分布的角度看并非所有地区均表现出干旱化趋势,云南、贵州及广西三省交界处雨季干旱化程度较严重,广西东南部地区雨季发生暴雨洪涝灾害的风险较大,而横断山脉地区雨季更加湿润。(4)从贡献率变化的角度,西南部地区雨季降水占比的变化趋势具有很强的区域特征,四川北部和西藏地区雨季指数对全年贡献率逐年下降,而广西东南部地区雨季指数对全年贡献率逐渐上升。(5)综合11个指数与海拔高度的关系来看,一方面,西南高海拔地区R1mm较高,降水以中小雨为主,并且PRCPTOT、R1mm、R10mm以及R20mm的多年平均值均表现出不同程度的上升趋势。因此,43a来西南高海拔地区变得更加湿润。另一方面,低海拔地区R1mm较低,而R95、R99、Rx1day、Rx5day以及SDII均较高,并且在低海拔地区CWD和CDD均呈现上升趋势,因此,雨季低海拔地区面临洪涝及干旱的风险相对较大。

关键词: 极端降水指数, 雨季降水, 西南地区, 降水日数, 降水强度

Abstract:

Based on the daily precipitation data of 477 meteorological stations from 1971 to 2013 in southwestern China, the spatial distribution and variation features of 11 extreme precipitation indices were analyzed by using the linear regression, Mann-Kendall test and moving t test. Besides, the relationship among the multi-year average of extreme precipitation indices,variation trend and altitude were also discussed. The results were as follows: (1) in the past 43 years, the decline rates of PRCPTOT, CWD, R1mm, R10mm and SDII in the rainy season of southwest China were 12.6mm·10y-1, 0.23d·10y-1, 1.57d·10y-1, 0.49d·10y-1 and 0.31mm·d-1·10y-1(P<0.05) respectively, the growth rate of CDD is 0.37d·10y-1 (P<0.05), while the changes in Rx1day, Rx5day, R95, R99, and R20mm were not significant. (2) The mutations of CDD, R1mm, and Rx1day in the rainy season occurred in the 1980s intensively, while the mutations of PRCPTOT, R10mm, Rx5day, and SDII occurred mainly around 2003. RCPTOT, CDD, R1mm, R10mm, Rx1day, and SDII showed certain stability before mutation year and a significant increase or decrease trend after mutation year. (3) From the perspective of spatial distribution, not all regions showed the tendency of drought. The extent of drought in rainy season at the junction of Yunnan, Guizhou and Guangxi provinces was more serious, the risk of heavy rain and flood disaster in the rainy season in southeastern Guangxi was greater, while rainy season in the Hengduan Mountains was more humid. (4) In terms of the contribution rate, variation trend of precipitation proportion in rainy season in southwestern had a strong regional characteristic: the contribution rate of rainy season indices for the whole year in northern Sichuan and Tibet had declined year by year, while in southeastern Guangxi it had gradually increased. (5) Judging from the relationship between the 11 indices and altitude, in high altitude regions of southwestern, the R1mm value was higher and the precipitation was mainly moderate and light rain. Besides, the multi-year average values of PRCPTOT, R1mm, R10mm and R20mm showed different degrees of upward trend. Therefore, the climate had become more humid in the past 43 years. On the other hand, in low altitude regions, R1mm was lower, while R95, R99, Rx1day, Rx5day, and SDII were higher and CWD, CDD showed an upward trend. Therefore, the risk of flooding and drought in the low altitude regions during the rainy season was relatively larger.

Key words: Extreme precipitation index, Rainy season precipitation, Southwestern China, Precipitation days, Precipitation intensity