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生态学杂志 ›› 2020, Vol. 39 ›› Issue (10): 3463-3470.doi: 10.13292/j.1000-4890.202010.026

• 研究报告 • 上一篇    下一篇

云南省近50年降水量的时空格局与成因分析

刘露露1,2,3,宋亮1,4*,董李勤3*,卢华正1,4,杨斌1,4   

  1. 1中国科学院西双版纳热带植物园热带森林生态学重点实验室, 云南勐仑 666303;2中国科学院大学, 北京 100049;3西南林业大学地理与生态旅游学院, 昆明 650224;4中国科学院核心植物园, 云南勐仑 666303)
  • 出版日期:2020-10-10 发布日期:2021-04-09

Spatiotemporal patterns of precipitation and driving factor analysis in Yunnan Province in recent 50 years.

LIU Lu-lu1,2,3, SONG Liang1,4*, DONG Li-qin3*, LU Hua-zheng1,4, YANG Bin1,4#br#   

  1. (1CAS Key laboratory of Tropical Forest Ecology, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun 666303, Yunnan, China; 2University of Chinese Academy of Sciences, Beijing 100049, China; 3School of Geography and Tourism, Southwest Forestry University, Kunming 650224, China; 4Core Botanical Gardens, Chinese Academy of Sciences, Menglun 666303, Yunnan, China).
  • Online:2020-10-10 Published:2021-04-09

摘要: 随着全球变暖的加剧,中国各区域近50年来的降水量变化呈现出更显著的地域差异。本文选取云南省32个资料序列较长的地面气象观测站1967—2016年逐日降水量数据,通过线性倾向率、Mann-Kendall检验、Morlet小波分析、Kriging插值和广义线性混合模型(GLMM)等方法,分析了云南省1967—2016年降水量时空格局与变化趋势。结果表明:1967—2016年年际降水量波动变化显著,总体呈下降趋势,且湿季主导全年降水;1995年和2002年为云南省降水量发生突变的年份,其中,1995年出现了降水量的急剧上升,2002年出现了降水量的骤然下降;云南省年平均降水量主要有准23 a、准12 a和准4 a三个振荡周期,并以准23 a长周期为主振荡周期,在未来一段时间内云南省降水仍维持在多雨期,但处于降水偏多向降水偏少的过渡阶段;云南省平均年降水量整体表现为滇东北和滇西北地区降水少、滇西南和滇南地区降水多的空间分布格局,且自东北向西南呈条带状递增分布;湿季降水空间分布主要受海拔的影响,在滇南地区海拔较低的江城形成降水中心;干季降水空间分布则受到地形和气流的综合作用,在滇西北地区的贡山形成降水中心。本研究定量解析了云南省降水量的时空演变特征及其驱动机制,证明了云南省近年来降水不稳定性加剧的同时下降速率明显升高,干旱化趋势越来越严重。研究结果为区域气候变化与灾害预警提供了基础数据,对预测区域水文变化趋势、提升水资源利用效率以及制定科学的抗旱减灾决策具有重要的现实意义。

关键词: 气候变化, 时间特征, 空间分布, 影响因素, 云南省

Abstract:

 With the intensification of global warming, changes of precipitation varied greatly in different regions of China in recent 50 years. In this study, spatiotemporal variations of precipitation were analyzed based on daily precipitation data from 32 ground meteorological observation stations in Yunnan Province from 1967 to 2016. The linear regression method and 5-year moving average method were used to analyze the temporal variation of precipitation. The MannKendall test and the moving ttest were used to detect the abrupt change of precipitation. The Morlet wavelet analysis was used to investigate the regularity of the periodic change. The spatial variation of precipitation was analyzed using the Kriging method. The effects of various terrain factors on spatial variation of precipitation were explored by combining generalized linear mixed model (GLMM) analysis and correlation analysis. Annual precipitation showed a fluctuant downward trend, with wet season accounting for 83% of the total. There were abrupt changes of precipitation in 1995 and 2002, with a sharp increase in 1995, and a sudden decrease in 2002. Three periods (i.e., 23 years, 12 years, and 4 years) of oscillations in annual precipitation were observed, in which expectant 23year is the main oscillation period. It was predicted that Yunnan will experience a transitional period from more to less precipitation in the next few years, although still immersed in a pluvial stage. The spatial distribution of precipitation was uneven in Yunnan Province. Precipitation was high in the southwest and southern Yunnan, and decreased progressively to the northeast and northwest. During wet seasons, the spatial distribution of precipitation was mainly determined by elevation. The amount of precipitation increased with decreasing altitude and formed a precipitation center in Jiangcheng in Southern Yunnan. During dry seasons, precipitation center was formed in Gongshan in the Northwest due to the coupling effect of terrain and airflow. Our results showed that the instability of precipitation has aggravated while the decline rate has increased remarkably in recent years, indicating an aridification trend in Yunnan, which provides basic data for regional climate change and disaster warning. Furthermore, our results are important for predicting regional hydrology, improving utilization efficiency of water resources, and making scientific decisions on drought mitigation.

Key words: climate change, temporal characteristics, spatial distribution, influencing factor, Yunnan Province.