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Meteorology and Atmospheric Physics

, Volume 129, Issue 2, pp 131–144 | Cite as

Temporal and spatial variability of temperature and precipitation over East Africa from 1951 to 2010

  • Victor Ongoma
  • Haishan ChenEmail author
Original Paper

Abstract

This study presents temporal and spatial changes in temperature and precipitation over East Africa (EA) from 1951 to 2010. The study utilized monthly Climate Research Unit (CRU) rainfall and temperature datasets, and Global Precipitation Climate Centre (GPCC) rainfall datasets. Sequential Mann–Kendall test statistic was used for trend analysis. The CRU data performs better than GPCC data in reproducing EA annual rainfall cycle. Overall decrease and increase in rainfall and temperature trends were observed, respectively, with the reduction in the March–May rainfall being significant. The highest rate of change in annual rainfall was experienced in the 1960s at −21.76 mm/year. Although there has been increase in temperature from the late 1960s to date, sudden change in its trend change happened in 1994. The increase in temperature reached a significant level in the year 1992. The highest warming rate of 0.05 °C/year was observed in the 1990s. The highest drying rate was recorded in the 1960s at −21.76 mm/year. There was an observed change in rainfall trend in the year 1953 and about four times in 1980, although the changes are insignificant throughout the study period except for 1963 when a positive significant change occurred at 5 % significance level. The highest amount of rainfall was recorded in the 1960s. Generally, positive rainfall and temperature anomalies are observed over the northern sector of the study area and opposite conditions are noted in the southern sector. The results of this study provide a reliable basis for future climate monitoring, as well as investigating extreme weather phenomena in EA.

Keywords

Extreme Weather Event Climate Research Unit Significant Positive Change Climate Research Unit Data East Africa 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

The authors express their appreciation to Nanjing University of Information Science and Technology (NUIST) for providing an environment that foster research. Special thanks go to Kenya Meteorological Department (KMD), Climate Research Unit (CRU) and Global Precipitation Climate Centre (GPCC) for providing data used in the study.

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© Springer-Verlag Wien 2016

Authors and Affiliations

  1. 1.Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environment Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters (CIC-FEMD)Nanjing University of Information Science & Technology (NUIST)NanjingChina
  2. 2.Department of MeteorologySouth Eastern Kenya UniversityKituiKenya

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