| 1990-2019年中亚五国干旱状况时空变化特征及大气涛动驱动分析 |
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| 引用本文： | 彭宇,李发东,徐宁,Rashid Kulmatov,高克昌,王国勤,张永勇,乔云峰,李艳红,杨涵,郝帅,李琦,Sayidjakhon Khasanov.1990-2019年中亚五国干旱状况时空变化特征及大气涛动驱动分析[J].中国生态农业学报,2021,29(2):312-324. |
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| 作者姓名： | 彭宇 李发东 徐宁 Rashid Kulmatov 高克昌 王国勤 张永勇 乔云峰 李艳红 杨涵 郝帅 李琦 Sayidjakhon Khasanov |
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| 作者单位： | 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室 北京 100101;中国科学院大学 北京 100049;中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室 北京 100101;中国科学院大学 北京 100049;石河子大学水利建筑工程学院 石河子 832000;乌兹别克斯坦国立大学 塔什干 100170;华南理工大学 广州 510006;中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室 北京 100101;联合国环境署-国际生态系统管理伙伴计划 北京 100101;中国科学院地理科学与资源研究所陆地水循环及地表过程重点实验室 北京 100101;新疆师范大学 乌鲁木齐 830054;中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室 北京 100101;石河子大学水利建筑工程学院 石河子 832000 |
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| 基金项目： | 中国科学院战略性先导科技专项资助（XDA20040302）、国家自然科学基金项目（U1803244，41761144053）和石河子市科技计划项目（2019ZH13）资助 |
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| 摘 要： | 咸海的迅速萎缩导致中亚五国的干旱问题引起了科学界的特别关注。为厘清中亚五国近30年来水分条件状况,探究影响其变化的气候驱动要素,本文使用帕默尔干旱指数(PDSI)对1990—2019年中亚五国干旱时空变化特征进行评估,并结合交叉小波变换揭示了大气涛动对其干旱状况的驱动影响。结果表明:中亚五国的干旱指数呈现周期性交替变化,年际变化率增大;夏秋旱、冬春湿的季节性干旱特征减弱,不同时间段的PDSI变异程度加剧,并表现出2018年后进入新一轮干期的可能。干旱程度总体呈现自西南向东北逐渐减轻、自东南山区向中西部平原逐步加重的格局;1990—2019年干旱重心由西南内陆腹地向哈萨克斯坦中西部地区转移,帕米尔和西天山山脉干旱程度呈波动上升态势。青藏高原指数(TPI)对PDSI变化表现出明显的驱动作用,在1990—2019年整个时间序列上均有较高的周期性强度,拥有1～3年(1995—2000年)、4～5年(2010—2015年)和8～10年(2015—2019年)3个明显年际尺度的震荡周期。总之, 1990—2019年中亚五国整体干旱状况趋好,干旱变异程度加剧,干旱空间分异明显, TPI在年际尺度上是驱动PDSI变化的大气涛动要素。
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| 关 键 词： | 帕默尔干旱指数(PDSI) 中亚五国 干旱 驱动力 大气涛动 交叉小波分析 |
| 收稿时间： | 2020/11/18 0:00:00 |
| 修稿时间： | 2020/12/30 0:00:00 |
Spatial-temporal variations in drought conditions and their climatic oscillations in Central Asia from 1990 to 2019 |
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| PENG Yu,LI Fadong,XU Ning,Rashid KULMATOV,GAO Kechang,WANG Guoqin,ZHANG Yongyong,QIAO Yunfeng,LI Yanhong,YANG Han,HAO Shuai,LI Qi,Sayidjakhon KHASANOV.Spatial-temporal variations in drought conditions and their climatic oscillations in Central Asia from 1990 to 2019[J].Chinese Journal of Eco-Agriculture,2021,29(2):312-324. |
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| Authors: | PENG Yu LI Fadong XU Ning Rashid KULMATOV GAO Kechang WANG Guoqin ZHANG Yongyong QIAO Yunfeng LI Yanhong YANG Han HAO Shuai LI Qi Sayidjakhon KHASANOV |
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| Institution: | Key Laboratory of Ecosystem Network Observation and Modeling, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China;Key Laboratory of Ecosystem Network Observation and Modeling, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;University of Chinese Academy of Sciences, Beijing 100049, China;College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi 832000, China;National University of Uzbekistan, Tashkent 100170, Uzbekistan;South China University of Technology, Guangzhou 510006, China;Key Laboratory of Ecosystem Network Observation and Modeling, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;United Nations Environment Programme-International Ecosystem Management Partnership(UNEP-IEMP), Beijing 100101, China;Key Laboratory of Water Cycle and Related Land Surface Processes, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;Xinjiang Normal University, Urumqi 830054, China;Key Laboratory of Ecosystem Network Observation and Modeling, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China;College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi 832000, China |
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| Abstract: | The rapid shrinking of the Aral Sea has prompted the scientific community to focus on Central Asian drought. To clarify the moisture conditions of Central Asia over the past 30 years and to investigate the climate drivers of change, in this study, we used the Palmer Drought Index (PDSI) to assess the spatial and temporal characteristics of drought in the five Central Asian countries (Kazakhstan, Uzbekistan, Turkmenistan, Tajikistan and Kyrgyzstan) from 1990 to 2019. PDSI was combined with the cross-wavelet transformation to reveal the driving influence of climate oscillations on drought conditions. The results showed that the drought indicators displayed a cyclical alternation with an increasing variability, a weakening of the dry summer/autumn and wet winter/spring seasonal drought characteristics, and the possibility of a new dry period after 2018. The general drought intensity gradually decreased from the southwest to the northeast and progressively increased from the southeast mountainous area to the central and western plains. The drought center shifted from the southwestern hinterland to the northwestern regions of Kazakhstan. The Pamir and West Tianshan Mountains showed a fluctuating and increasing drought trend. The Tibetan Plateau Index (TPI) showed an apparent driving effect on PDSI changes, with high cyclical intensity throughout the 1990-2019 period (1-3 years1995-2000], 4-5 years2010-2015], 8-10 years2010-2015], and 8-10 years2016-2019]) with three distinct interannual-scale oscillatory cycles. Overall, drought conditions tended to improve, with increased drought variability and significant spatial variability; the TPI is the atmospheric oscillator driving PDSI variability. |
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| Keywords: | Palmer Drought Index (PDSI) Central Asia Drought Driving force Climatic oscillations Cross-wavelet analysis |
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