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三江源地区1980—2019年积雪时空动态特征及其对气候变化的响应
引用本文:陈龙飞,张万昌,高会然.三江源地区1980—2019年积雪时空动态特征及其对气候变化的响应[J].冰川冻土,2022,44(1):133-146.
作者姓名:陈龙飞  张万昌  高会然
作者单位:1.中国科学院 空天信息创新研究院 数字地球重点实验室,北京 100094;2.中国科学院大学,北京 100049
基金项目:青海省重点研发与转化计划项目
摘    要:三江源地区气象站点稀疏,依靠地面台站数据难以反映地面真实积雪情况。利用卫星遥感数据引入重心模型分析了三江源地区1980—2019年4个积雪参数(积雪日数、积雪深度、积雪初日和积雪终日)的时空动态特征,利用Mann-Kendall检验和Sen斜率估计分析了积雪和气候因子的变化趋势,并探究积雪对气候变化的响应。结果表明:1980—2019年三江源地区呈现积雪日数和积雪深度减少、积雪初日推迟、积雪终日提前的变化趋势,而该区域同期的气温和降水量则呈现上升趋势;4个积雪参数重心均呈现出东移趋势,而同期气温重心则呈现西移趋势,气温重心位置西移速率分别是积雪日数和积雪深度重心位置东移速率的6倍和2倍。这表明该区域4个积雪参数以及气候因子的变化趋势具有较强的空间异质性,西部气温升高速率大于东部,导致西部积雪日数和积雪深度减少速率同样大于东部,从而导致气温重心西移而积雪参数重心东移。澜沧江源区积雪日数减少、积雪深度减少、积雪初日推迟以及积雪终日提前的速率最大,其次是长江源区和黄河源区。进一步的相关性分析表明,三江源地区年平均气温的升高是导致积雪日数和积雪深度减少、积雪初日推迟、积雪终日提前的主要影响因子,积雪日数对气温升高响应最敏感,其次是积雪深度、初日和终日;而年降水量与4个积雪参数的相关性均不显著。研究可为三江源地区水资源和生态环境保护提供基础资料和理论依据。

关 键 词:三江源地区  积雪  重心模型  气候变化  
收稿时间:2021-08-21
修稿时间:2022-02-03

Spatiotemporal dynamic characteristics of snow cover from 1980 to 2019 in the Three-River-Source region and its response to climate change
CHEN Longfei,ZHANG Wanchang,GAO Huiran.Spatiotemporal dynamic characteristics of snow cover from 1980 to 2019 in the Three-River-Source region and its response to climate change[J].Journal of Glaciology and Geocryology,2022,44(1):133-146.
Authors:CHEN Longfei  ZHANG Wanchang  GAO Huiran
Institution:1.Key Laboratory of Digital Earth Science,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100094,China;2.University of Chinese Academy of Sciences,Beijing 100049,China
Abstract:Meteorological stations in the Three-River-Source region is sparse, and only analyzing ground station data fails to reflect true snow cover on ground. In this study, based on remote sensing data, we applied gravity center model to analyze spatiotemporal dynamic characteristics of four snow cover parameters including snow cover days, snow depth, snow cover onset date and snow cover end date from 1980 to 2019. Mann-Kendall test and Sen’s slope estimation were used to analyze trends of the four snow cover parameters and climate factors. We finally explored its response to variations in annual mean air temperature and annual precipitation in the Three-River-Source region. The results indicated that snow cover days and snow depth showed downward trends, and snow cover onset date delayed and snow cover end date advanced from 1980 to 2019 in the Three-River-Source region, while air temperature and precipitation showed upward trends. Gravity center of the four snow cover parameters showed eastward trends, while gravity center of air temperature showed a westward trend. The westward speed of gravity center of air temperature was 6 times and 2 times the eastward speed of snow cover days and snow depth, respectively. These indicated that trends of the four snow cover parameters and climate factors in this region showed strong spatial heterogeneity. The increase rate of air temperature in the west was greater than that in the east, which leads to a greater decrease rate of snow cover days and snow depth in the west than in the east. It was responsible for the westward of gravity center of air temperature, and the eastward of gravity center of snow cover parameters. The Lancang River Source region had the highest rate of decrease in snow cover days and snow depth, delay of snow cover onset date and advance of snow cover end date, followed by the Yangtze River Source region and the Yellow River Source region. Further correlation analysis indicated that the increase in air temperature was primarily responsible for the decrease in snow cover days and snow depth, delay of snow cover onset date and advance of snow cover end date. Snow cover days was most sensitive to air temperature rise, followed by snow depth, snow cover onset date and end date. The correlation between annual precipitation and the four snow cover parameters was not significant. This research can provide basic data and theoretical basis for the protection of water resources and ecological environment in the Three-River-Source region.
Keywords:Three-River-Source region  snow cover  gravity center model  climate change  
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