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	Development of a remotely sensing seasonal vegetation-based Palmer Drought Severity Index and its application of global drought monitoring over 1982-2011
	Yan H.; Yu Q.
	2014
关键词	leaf-area index potential evapotranspiration el-nino part ii evaporation variability moisture climate decline events
英文摘要	Vegetation effects are currently disregarded in Palmer Drought Severity Index (PDSI), and the sensitivity of PDSI to the choice of potential evaporation (E-P) parameterization is often a concern. We developed a revised self-calibrating PDSI model that replaces E-P with leaf area index-based total evapotranspiration (ARTS E-0). It also included a simple snowmelt module. Using a unique satellite leaf area index data set and climate data, we calculated and compared ARTS E-0, three other types of E-P (i.e., Thornthwaite E-P_Th, Allen E-P_Al, and Penman-Monteith E-P_PM), and corresponding PDSI values (i.e., PDSI_ARTS, PDSI_Th, PDSI_Al, and PDSI_PM) for the period 1982-2011. The results of PDSI_ARTS, PDSI_Al, and PDSI_PM show that global land became wetter mainly due to increased precipitation and El Nino-Southern Oscillation (ENSO) effect for the period, which confirms the ongoing intensification of global hydrologic cycle with global temperature increase. However, only PDSI_Th gave a trend of global drying, which confirms that PDSI_Th overestimates the global drying in response to global warming; i.e., PDSI values are sensitive to the parameterizations for E-p. Thus, ARTS E-0, E-P_Al, and E-P_PM are preferred to E-P_Th in global drought monitoring. In short, global warming affects global drought condition in two opposite ways. One is to contribute to the increases of E-P and hence drought; the other is to increase global precipitation that contributes to global wetting. These results suggest that precipitation trend and its interaction with global warming and ENSO should be given much attention to correctly quantify past and future trends of drought.
出处	Journal of Geophysical Research-Atmospheres
卷	119
期	15
页	9419-9440
收录类别	SCI
语种	英语
ISSN号	2169-897X
内容类型	SCI/SSCI论文
源URL	[http://ir.igsnrr.ac.cn/handle/311030/29477]
专题	地理科学与资源研究所_历年回溯文献
推荐引用方式 GB/T 7714	Yan H.,Yu Q.. Development of a remotely sensing seasonal vegetation-based Palmer Drought Severity Index and its application of global drought monitoring over 1982-2011. 2014.

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