4.5 Article

Variability of extreme weather events over the equatorial East Africa, a case study of rainfall in Kenya and Uganda

Journal

THEORETICAL AND APPLIED CLIMATOLOGY
Volume 131, Issue 1-2, Pages 295-308

Publisher

SPRINGER WIEN
DOI: 10.1007/s00704-016-1973-9

Keywords

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Funding

  1. Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions
  2. Nanjing University of Information Science and Technology (NUIST)
  3. Chinese Scholarship Council (CSC)

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This study investigates the variability of extreme rainfall events over East Africa (EA), using indices from the World Meteorological Organization (WMO) Expert Team on Climate Change Detection and Indices (ETCCDI). The analysis was based on observed daily rainfall from 23 weather stations, with length varying within 1961 and 2010. The indices considered are: wet days (R >= 1 mm), annual total precipitation in wet days (PRCPTOT), simple daily intensity index (SDII), heavy precipitation days (R >= 10 mm), very heavy precipitation days (R >= 20 mm), and severe precipitation (R >= 50 mm). The non-parametric Mann-Kendall statistical analysis was carried out to identify trends in the data. Temporal precipitation distribution was different from station to station. Almost all indices considered are decreasing with time. The analysis shows that the PRCPTOT, very heavy precipitation, and severe precipitation are generally declining insignificantly at 5 % significant level. The PRCPTOT is evidently decreasing over Arid and SemiArid Land (ASAL) as compared to other parts of EA. The number of days that recorded heavy rainfall is generally decreasing but starts to rise in the last decade although the changes are insignificant. Both PRCPTOT and heavy precipitation show a recovery in trend starting in the 1990s. The SDII shows a reduction in most areas, especially the in ASAL. The changes give a possible indication of the ongoing climate variability and change which modify the rainfall regime of EA. The results form a basis for further research, utilizing longer datasets over the entire region to reduce the generalizations made herein. Continuous monitoring of extreme events in EAis critical, given that rainfall is projected to increase in the twenty-first century.

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