期刊文献+

Spatio-temporal patterns of drought evolution over the Beijing-Tianjin-Hebei region, China 被引量:6

京津冀干旱时空演变规律分析(英文)
原文传递
导出
摘要 Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei(BTH) region of China were analyzed using the Palmer Drought Severity index(PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions(EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode(48.5%), the temporal variability(Principal Components, PC1) was highly positively correlated with annual series of PDSI(r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale(r=0.71, p<0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming(P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1. Spatio-temporal patterns of drought from 1961 to 2013 over the Beijing-Tianjin-Hebei(BTH) region of China were analyzed using the Palmer Drought Severity index(PDSI) based on 21 meteorological stations. Overall, changes in the mean-state of drought detected in recent decades were due to decreases in precipitation and potential evapotranspiration. The Empirical Orthogonal Functions(EOF) method was used to decompose drought into spatio-temporal patterns, and the first two EOF modes were analyzed. According to the first leading EOF mode(48.5%), the temporal variability(Principal Components, PC1) was highly positively correlated with annual series of PDSI(r=+0.99). The variance decomposition method was further applied to explain the inter-decadal temporal and spatial variations of drought relative to the total variation. We find that 90% of total variance was explained by time variance, and both total and time variance dramatically decreased from 1982 to 2013. The total variance was consistent with extreme climate events at the inter-decadal scale(r=0.71, p<0.01). Comparing the influence of climate change on the annual drought in two different long-term periods characterized by dramatic global warming(P1: 1961–1989 and P2: 1990–2013), we find that temperature sensitivity in the P2 was three times more than that in the P1.
作者 ZHANG Jie SUN Fubao LIU Wenbin LIU Jiahong WANG Hong 章杰;孙福宝;刘文彬;刘家宏;王红(Key Laboratory of Water Cycle and Related Land Surface Processes,Institute of Geographic Science and Natural Resources Research,CAS;Key Laboratory of Simulation and Regulation of Water Cycle in River Basin,China Institute of Water Resources and Hydropower Research)
出处 《Journal of Geographical Sciences》 SCIE CSCD 2019年第6期863-876,共14页 地理学报(英文版)
基金 National Key Research and Development Program of China,No.2016YFC0401401,No.2016YFA0602402 Key Program of the Chinese Academy of Sciences,No.ZDRW-ZS-2017-3-1 The Chinese Academy of Sciences(CAS)Pioneer Hundred Talents Program National Natural Science Foundation of China,No.41601035
关键词 PDSI SPATIAL and TEMPORAL PATTERNS sensitivity analysis global WARMING PDSI spatial and temporal patterns sensitivity analysis global warming
  • 相关文献

参考文献2

二级参考文献41

共引文献66

同被引文献92

引证文献6

二级引证文献89

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部