Analysis of climate variability and droughts in East Africa using high-resolution climate data products

被引:39
|
作者
Gebrechorkos, Solomon H. [1 ,2 ]
Huelsmann, Stephan [1 ,3 ]
Bernhofer, Christian [4 ]
机构
[1] United Nations Univ Inst Integrated Management Ma, D-01067 Dresden, Germany
[2] Univ Southampton, Sch Geog & Environm Sci, Southampton SO17 1BJ, Hants, England
[3] Global Change Res Inst CAS, Brno 60300, Czech Republic
[4] Tech Univ Dresden, Fac Environm Sci, Inst Hydrol & Meteorol, D-01062 Dresden, Germany
关键词
East Africa; Climate variability; High-resolution climate datasets; Droughts; Nino3.4; RAINFALL VARIABILITY; GREATER HORN; TRENDS; REANALYSIS; FAMINE; MODELS;
D O I
10.1016/j.gloplacha.2020.103130
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Analysis of climate variability and change as a basis for adaptation and mitigation strategies requires long-term observations. However, the limited availability of ground station data constrains studies focusing on detecting variability and changes in climate and drought monitoring, particularly in developing countries of East Africa. Here, we use high-resolution precipitation (1981-2016) and maximum and minimum temperature (T-max and T-min) (1979-2012) datasets from international databases like the Climate Hazard Group (CHG), representing the most accurate data sources for the region. We assessed seasonal, annual, and decadal variability in rainfall, T-max and T-min and drought conditions using the Standardized Precipitation Index (SPI). The impact of changes in Sea Surface Temperature on rainfall variability and droughts is assessed using the Nino3.4 and Indian Ocean Dipole (IOD) indices. The results show maximum variability in rainfall during October-December (OND, short rainy season) followed by March-May (MAM, long rainy season). Rainfall variability during OND showed a significant correlation with IOD in Ethiopia (69%), Kenya (80%), and Tanzania (63%). In Ethiopia, the period June-September (JJAS) showed a significant negative correlation (-56%) with the Nino3.4. Based on the 12-month SPI, the eastern and western parts of the region are getting drier and wetter, respectively with an average of mild, moderate, and severe droughts of more than 37%, 6%, and 2% of the study period, respectively. The observed severe droughts (e.g., 1999/2000) and extreme floods (e.g., 1997/1998) were found to be linked to respective negative and positive anomalies of the Nino3.4. In general, climate data products with high spatial resolution and accuracy help detect changes and variability in climate at local scale where adaptation is required.
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收藏
页数:11
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