GSTDTAP  > 气候变化
DOI10.3354/cr01554
Characterising spatiotemporal variability of South Asia's climate extremes in past decades
Chen, Yun1; Xu, Tingbao2; Shui, Junfeng3; Liu, Rui4; Wahid, Shahriar1; Shi, Kaifang5; Yang, Haichang6; Cheng, Zhibo6
2019
发表期刊CLIMATE RESEARCH
ISSN0936-577X
EISSN1616-1572
出版年2019
卷号77期号:3页码:249-265
文章类型Article
语种英语
国家Australia; Peoples R China
英文摘要

We systematically examined past spatiotemporal changes in climate variability to gain some cross-regional insights into South Asia's vulnerability to extreme conditions. Gridded Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation (APHRODITE) precipitation and Princeton Global Meteorological Forcing Dataset (PRINCETON) temperature data from 1975-2004 were used to derive a suite of annual extreme indices. Long-term mean and decadal variations of these indices were mapped. Long-term change tendencies were also detected from a suite of 'slope' maps composed by the 30 yr change trend at each grid cell in the region. Most precipitation indices indicated a tendency towards drier conditions, whereas all temperature indices marked a steady coherent warming trend. The extremely wet day precipitation index exhibited the largest change, indicating an increase in heavy precipitation in South Asia. The highest maximum temperature extreme showed increases, indicating more unbearable heatwaves in the region. These trends present a previously unrecognised regional picture of the patterns and trends in historical climate extremes, with each grid cell representing spatiotemporal characteristics of changes. The present study is superior to most studies that only summarise an averaged regional trend from tendencies over large areas, and therefore will improve trans-boundary understanding of extreme climates in South Asia. Our study also exemplifies the application of existing gridded regional/global data sets. It provides valuable means of cross-regional information for bridging gaps where gauging observations are unavailable, particularly in data-poor developing countries.


英文关键词Climate variables Indices of extreme conditions Gridded daily climate data Change trend
领域气候变化
收录类别SCI-E
WOS记录号WOS:000482742100005
WOS关键词KOSHI RIVER-BASIN ; LONG-TERM TRENDS ; PRECIPITATION DISTRIBUTION ; TIBETAN PLATEAU ; DATA SET ; TEMPERATURE ; RAINFALL ; 20TH-CENTURY ; ELEVATION ; AEROSOLS
WOS类目Environmental Sciences ; Meteorology & Atmospheric Sciences
WOS研究方向Environmental Sciences & Ecology ; Meteorology & Atmospheric Sciences
引用统计
文献类型期刊论文
条目标识符http://119.78.100.173/C666/handle/2XK7JSWQ/181256
专题气候变化
作者单位1.CSIRO Land & Water, Canberra, ACT 2601, Australia;
2.Australian Natl Univ, Canberra, ACT 0200, Australia;
3.Northwest A&F Univ, Xian 712100, Shaanxi, Peoples R China;
4.Capital Normal Univ, Beijing 100048, Peoples R China;
5.Southwest Univ, Chongqing 400715, Peoples R China;
6.Shihezi Univ, Xinjiang 832003, Peoples R China
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GB/T 7714
Chen, Yun,Xu, Tingbao,Shui, Junfeng,et al. Characterising spatiotemporal variability of South Asia's climate extremes in past decades[J]. CLIMATE RESEARCH,2019,77(3):249-265.
APA Chen, Yun.,Xu, Tingbao.,Shui, Junfeng.,Liu, Rui.,Wahid, Shahriar.,...&Cheng, Zhibo.(2019).Characterising spatiotemporal variability of South Asia's climate extremes in past decades.CLIMATE RESEARCH,77(3),249-265.
MLA Chen, Yun,et al."Characterising spatiotemporal variability of South Asia's climate extremes in past decades".CLIMATE RESEARCH 77.3(2019):249-265.
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