Article citationsMore>>
Palmer, P. I., Wainwright, C. M., Dong, B., Maidment, R. I., Wheeler, K. G., Gedney, N., Hickman, J. E., Madani, N., Folwell, S. S., Abdo, G., Allan, R. P., Black, E. C. L., Feng, L., Gudoshava, M., Haines, K., Huntingford, C., Kilavi, M., Lunt, M. F., Shaaban, A., & Turner, A. G. (2023). Drivers and Impacts of Eastern African Rainfall Variability. Nature Reviews Earth and Environment, 4, 254-270.
https://doi.org/10.1038/s43017-023-00397-x
has been cited by the following article:
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TITLE:
Characteristics of Extreme Rainfall Events over Uganda during September to November Rainfall Season
AUTHORS:
Donnata Alupot, Guirong Tan, Kokou Romaric Posset, Peter Natiko
KEYWORDS:
CHIRPS, Variability, Region-Specific, Early Warning, Climate Change
JOURNAL NAME:
Journal of Geoscience and Environment Protection,
Vol.12 No.3,
March
27,
2024
ABSTRACT: Understanding the characteristics of extreme rainfall is crucial for
effective flood management planning, as it enables the incorporation of
insights from past extreme rainfall patterns and their spatiotemporal
distribution. This work investigated the changes in the frequency and pattern
of extreme rainfall over Uganda, using daily datasets sourced from Climate
Hazard Group InfraRed Precipitation with Station
(CHIRPS-v2) for the period 1981 to 2022. The study utilized the extreme weather
Indices provided by the Expert Team on Climate Change Detection and Indices
(ETCCDI). Attention was directed towards September to November (SON) rainfall
season with precise analysis of four indices (Rx1day, Rx5day, R95p, and R99p).
The Sequential Mann-Kendall (SQMK)
non-parametric test was applied to identify abrupt changes in SON extreme rainfall trends. Results showed that October
consistently recorded the highest count of extreme rainfall days across all
four indices. The long-term analysis revealed fluctuations in extreme rainfall
events across years, with certain periods exhibiting heightened
intensity. The analysis portrayed a shift in the decadal variations and region-specific
distribution of extreme rainfall, with Eastern Uganda and areas around Lake
Victoria standing out compared to other regions. The findings further revealed
an increase in extreme rainfall for all indices in the recent decade
(2011-2022) with 2019/2020 standing out as the extreme years of SON for the
study period. While trendlines suggested a slight increase in intense daily
rainfall events, the SQMK tests revealed statistical significance in the trend
of prolonged periods of intense daily rainfall. This study contributes to the
understanding of the spatiotemporal variability and trends of extreme rainfall
events over Uganda during the SON season, which is crucial for the assessment
of climate change impacts and adaptation strategies. It provides valuable
information for seasonal extreme rainfall forecasting, development of early
warning systems, flood risk management, and disaster preparedness plans.
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