DOI: 10.1175/JCLI-D-17-0274.1
Scopus记录号: 2-s2.0-85042064100
论文题名: Attribution analysis of the Ethiopian drought of 2015
作者: Philip S. ; Kew S.F. ; van Oldenborgh G.J. ; Otto F. ; O'Keefe S. ; Haustein K. ; King A. ; Zegeye A. ; Eshetu Z. ; Hailemariam K. ; Singh R. ; Jjemba E. ; Funk C. ; Cullen H.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期: 6 起始页码: 2465
结束页码: 2486
语种: 英语
英文关键词: Africa
; Climate change
; Climate models
; Drought
; ENSO
; Statistical techniques
Scopus关键词: Climate models
; Climatology
; Drought
; Precipitation (meteorology)
; Probability
; Rain
; Soil moisture
; Africa
; Anthropogenic climate changes
; Confidence interval
; ENSO
; Large-scale precipitation
; Natural variability
; Satellite observations
; Statistical techniques
; Climate change
; climate change
; climate modeling
; computer simulation
; confidence interval
; drought
; El Nino-Southern Oscillation
; hydrological response
; numerical model
; precipitation intensity
; probability
; rainfall
; Ethiopia
英文摘要: In northern and central Ethiopia, 2015 was a very dry year. Rainfall was only from one-half to three-quarters of the usual amount, with both the "belg" (February-May) and "kiremt" rains (June-September) affected. The timing of the rains that did fall was also erratic. Many crops failed, causing food shortages for many millions of people. The role of climate change in the probability of a drought like this is investigated, focusing on the large-scale precipitation deficit in February-September 2015 in northern and central Ethiopia. Using a gridded analysis that combines station data with satellite observations, it is estimated that the return period of this drought was more than 60 years (lower bound 95% confidence interval), with a most likely value of several hundred years. No trend is detected in the observations, but the large natural variability and short time series means large trends could go undetected in the observations. Two out of three large climate model ensembles that simulated rainfall reasonably well show no trend while the third shows an increased probability of drought. Taking the model spread into account the drought still cannot be clearly attributed to anthropogenic climate change, with the 95% confidence interval ranging from a probability decrease between preindustrial and today of a factor of 0.3 and an increase of a factor of 5 for a drought like this one or worse. A soil moisture dataset also shows a nonsignificant drying trend. According to ENSO correlations in the observations, the strong 2015 El Niño did increase the severity of the drought. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111613
Appears in Collections: 气候减缓与适应
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作者单位: Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands; Environmental Change Institute, University of Oxford, Oxford, United Kingdom; School of Earth Sciences and Australian Research Council, Centre of Excellence for Climate System Science, University of Melbourne, Melbourne, VIC, Australia; Addis Ababa University, Addis Ababa, Ethiopia; National Meteorology Agency, Addis Ababa, Ethiopia; Red Cross Red Crescent Climate Centre, The Hague, Netherlands; U.S. Geological Survey, University of California, Santa Barbara, Santa Barbara, CA, United States; Climate Central, Princeton, NJ, United States
Recommended Citation:
Philip S.,Kew S.F.,van Oldenborgh G.J.,et al. Attribution analysis of the Ethiopian drought of 2015[J]. Journal of Climate,2018-01-01,31(6)