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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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彭宇1, 2,,
李发东1, 2, 3,,,
徐宁1, 2,
KulmatovRashid4,
高克昌5,
王国勤1, 6,
张永勇7,
乔云峰1, 2,
李艳红8,
杨涵8,
郝帅8,
李琦1, 3,
KhasanovSayidjakhon1, 2
1.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
2.中国科学院大学 北京 100049
3.石河子大学水利建筑工程学院 石河子 832000
4.乌兹别克斯坦国立大学 塔什干 100170
5.华南理工大学 广州 510006
6.联合国环境署-国际生态系统管理伙伴计划 北京 100101
7.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
8.新疆师范大学 乌鲁木齐 830054
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
国家自然科学基金项目41761144053
石河子市科技计划项目2019ZH13

详细信息
作者简介:彭宇, 主要从事环境遥感-信息学与流域模拟研究。E-mail: pengyu181@mails.ucas.ac.cn
通讯作者:李发东, 主要从事生态系统过程与环境研究。E-mail: lifadong@igsnrr.ac.cn
中图分类号:X21;P95

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出版历程

收稿日期:2020-11-18
录用日期:2020-12-30
刊出日期:2021-02-01

Spatial-temporal variations in drought conditions and their climatic oscillations in Central Asia from 1990 to 2019

PENG Yu1, 2,,
LI Fadong1, 2, 3,,,
XU Ning1, 2,
KULMATOV Rashid4,
GAO Kechang5,
WANG Guoqin1, 6,
ZHANG Yongyong7,
QIAO Yunfeng1, 2,
LI Yanhong8,
YANG Han8,
HAO Shuai8,
LI Qi1, 3,
KHASANOV Sayidjakhon1, 2
1. Key Laboratory of Ecosystem Network Observation and Modeling, Institution of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2. University of Chinese Academy of Sciences, Beijing 100049, China
3. College of Water Conservancy and Architectural Engineering, Shihezi University, Shihezi 832000, China
4. National University of Uzbekistan, Tashkent 100170, Uzbekistan
5. South China University of Technology, Guangzhou 510006, China
6. United Nations Environment Programme-International Ecosystem Management Partnership(UNEP-IEMP), Beijing 100101, China
7. 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
8. Xinjiang Normal University, Urumqi 830054, China
Funds: the Strategic Priority Research Program of Chinese Academy of SciencesXDA20040302
the National Natural Science Foundation of ChinaU1803244
the National Natural Science Foundation of China41761144053
the Science and Technology Planning Project of Shihezi City, Xinjiang2019ZH13

More Information
Corresponding author:LI Fadong, E-mail: lifadong@igsnrr.ac.cn


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摘要
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。
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
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 years [1995-2000], 4-5 years [2010-2015], 8-10 years [2010-2015], and 8-10 years [2016-2019]) 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.
Key words:Palmer Drought Index (PDSI)/
Central Asia/
Drought/
Driving force/
Climatic oscillations/
Cross-wavelet analysis

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图12019年中亚五国地区干旱指数和主要水系空间分布
地图底图为天地图在线影像图, 数据来源为自然资源部及NavInfo。地图中国境边界数据来自公开发表的LSIB数据集, 图中边界和名称以及使用的称号仅以说明为目的, 不代表官方正式认可。
Figure1.Drought index and spatial stream distribution in the five countries of Central Asia in 2019
The base map is an online image from TianDiTu, and the source data is from the Ministry of Natural Resources of China and NavInfo. The boundary data for the map are from the publicly available LSIB dataset. Here, the boundaries, names, and designations are for illustrative purposes only and do not represent an official endorsement.


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图21990-2019年中亚五国年均帕默尔干旱指数时序变化趋势
黑色、黄色、橙色和红色水平线表示年际PDSI值分别等于-0.5、-2、-3和-4, 以表示轻度、中度、重度和极端干旱。
Figure2.Annual time series trends of Palmer Drought Severity Index (PDSI) in Central Asia from 1990 to 2019
The black, yellow, orange and red horizontal lines represent annual PDSI values equal to-0.5, -2, -3 and -4, which indicate mild, moderate, severe and extreme drought.


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图31990-2019年中亚五国各干旱区间的月度帕默尔干旱指数分布趋势
E1-E6为干旱区间, 具体见图 2。黄色、橙色和红色水平线表示月际PDSI值分别等于-2、-3和-4, 以表示中度干旱、重度和极端干旱。不同颜色散点以区分季节, 定义春季为3-5月、夏季为6-8月、秋季为9-11月、冬季为12-翌年2月。
Figure3.Monthly Palmer Drought Severity Index (PDSI) change in different drought events in Central Asia from 1990 to 2019
E1 to E6 are drought events shown in the figure 2. The yellow, orange and red horizontal lines represent inter-monthly PDSI values equal to-2, -3 and-4, which indicate moderate, severe and extreme drought. Different color scatters are used to distinguish the seasons, defined as March-May for spring, June-August for summer, September-November for autumn and December-February for winter.


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图41990-2019年中亚五国4类干旱特征指数变化趋势
DP指数表示干旱峰值, DD指数表示干旱持续时间, DS指数表示干旱严重程度, DI指数表示干旱强度。6个Events为1990-2019年的6个干旱区间, 具体见图 2
Figure4.Trends in 4 drought characteristic indices in Central Asia from 1990 to 2019
DP indicates the drought peak, DD indicates drought duration, DS indicates drought severity, and DI indicates drought intensity. Events 1 to 6 are 6 drought events from 1995 to 2019 shown in the figure 2.


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图51990-2019年中亚五国干旱强度空间分布
E1-E6为干旱区间, 具体见图 2。DI为1990-2019年中亚五国干旱强度值, 即整个研究时段的PDSI均值。图中字母代表地区, a为卡拉库姆沙漠, b为田吉兹湖, c为萨雅克草原, d为库尔干秋别, e为阿什哈巴德, f为库斯塔奈州, g为撒马尔罕, h为卡拉博加兹湾。
Figure5.Drought intensity spatial distribution in Central Asia from 1990-2019
E1 to E6 are drought events shown in the figure 2. In the map, DI is the drought intensity for Central Asia from 1990 to 2019, i.e., the average PDSI value for the entire study period. The letters in the figures indicate different regions: a is the Karakum Desert, b is Tengiz Lake, c is Saryarka, d is Qurghonteppa, e is Ashgabat, f is Kostanay, g is Samarkand, and h is Karabogaz Bay.


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图6中亚五国帕默尔干旱指数(PDSI)与气候涛动相关性分析
TPIA和TPIB分别为青藏高原指数A和B。AO为北极涛动指数, ENSO为厄尔尼诺现象南方涛动指数, NAO为北大西洋涛动指数。左图中右上侧圆圈大小和颜色共同表示P值大小, ***、**和*分别表示P < 0.001、P < 0.01和P < 0.05水平显著相关; 左下侧数值表示所对应的相关性系数。右图中5种气候指数为自变量, PDSI为因变量。
Figure6.Correlation analysis between Palmer Drought Severity Index (PDSI) and climate oscillation indexes of the five countries in Central Asia
TPIA and TPIB are the Tibetan Plateau Index A and B, respectively. AO is the Arctic Oscillation, ENSO is the El Niño Southern Oscillation, and NAO is the North Atlantic Oscillation. In the left panel, the size and color of the circles in the upper right panel together indicate the P-value; ***, ** and * indicate significant correlation at P < 0.001, P < 0.01 and P < 0.05 levels, respectively. In the lower-left panel, data are the corresponding correlation coefficients. In the right panel, the five climate indices are independent variables, and PDSI is the dependent variable.


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图71990-2019年中亚地区帕默尔干旱指数(PDSI)与青藏高原指数(TPI)小波凝聚谱及小波功率谱
小波功率谱(图 7上)色柱代表所在周期的信号震荡强度, 数值越高置信度检验越显著; 小波凝聚谱(图 7下)色柱数值表示小波相关系数的平方, 数值越大代表PDSI指数与该驱动因素在该局部时频域的相关性越高。锥形区域为有效的谱值区, 黑色框线区域为显著性水平超过95%的置信区间。右向箭头表示PDSI指数与驱动因素变化位相一致, 左向箭头表示变化位相相反, 向上箭头表示驱动因素变化早于PDSI指数, 向下箭头表示迟于PDSI指数。
Figure7.Wavelet coalescence spectrum (WTC) and power spectrum (XWT) of the Palmer Drought Severity Index (PDSI) and Tibetan Plateau Index (TPI) in Central Asia from 1990 to 2019
The color bars in XWT (top two figures) represent the strength of signal oscillation in the period, with higher values representing more significant confidence tests; the color bars in WTC (bottom two figures) represent the square of wavelet correlation coefficient, where larger values represent a higher correlation between PDSI index and the drivers in the local time-frequency domain. The tapered area is the valid spectral area, and the black-boxed area is the confidence interval for significance levels above 95%. The right arrow indicates that the PDSI is in phase with the driver change. The left arrow indicates the opposite. The up arrow indicates that the driver changes earlier than the PDSI, and the down arrow indicates that it changes later than the PDSI.


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表15类用于驱动力分析的大气涛动指数
Table1.Five oscillator indexes used to analysis climatic driving
气候指标
Oscillator index
全称
Full name
数据时间
Period
数据来源
Source
数据链接
Link
ENSO 厄尔尼诺现象南方涛动
El Nino southern oscillation
1990-2019 美国国家海洋和大气管理局
National Oceanic and Atmospheric Administration (NOAA)
https://psl.noaa.gov/enso/mei/
NAO 北大西洋涛动指数
North Atlantic Oscillation
1990-2019 美国国家海洋和大气管理局
National Oceanic and Atmospheric Administration (NOAA)
http://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtml
AO 北极涛动指数
Arctic Oscillation
1990-2019 美国国家海洋和大气管理局
National Oceanic and Atmospheric Administration (NOAA)
http://www.cpc.ncep.noaa.gov/data/teledoc/nao.shtml
TPIA/B 青藏高原指数A/B
Tibet Plateau IndexA/B
1990-2019 中国气象局气候变化中心
China Meteorological Administration (CMA)
http://cmdp.ncc-cma.net/Monitoring/cn_index_130.php


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