Changing Rainfall Patterns and Their Climatic Drivers in One of the Rainiest Places on Earth, Debundscha, Gulf of Guinea

ABSTRACT Debundscha is ranked amongst the top rainiest places on Earth, yet there is a paucity of information on rainfall trends and their drivers in the area. However, the increasing frequency and intensity of hydrometeorological disasters, declining crop yields, and rising water scarcity in the area underscore the urgent need to investigate changing rainfall patterns and the climatic modes influencing rainfall in the area. Trend analysis using the Mann‐Kendall test shows non‐statistically significant declining trends in annual and seasonal rainfall in Debundscha (1972–2009) and other stations, except Limbe, which exhibits statistically significant increasing trends in annual and seasonal rainfall (1985–2015). Statistical analysis using partial least squares regression reveals that the Atlantic Multidecadal Oscillation (AMO), Southern Oscillation Index, Indian Ocean Dipole Western Pool Index, global sea surface temperature (GSST), Multivariate ENSO Index, and El Niño‐Southern Oscillation are the dominant climatic modes influencing annual and seasonal rainfall in the study area. However, a different set of climatic modes affects rainfall at each station, with AMO and GSST strongly associated with annual rainfall in Debundscha. Analysing rainfall in high precipitation areas like Debundscha is essential for understanding how these regions are affected by changing climate patterns. On the other hand, identifying the main climatic modes influencing local rainfall is crucial for creating accurate seasonal and sub‐seasonal forecasts. These forecasts can help reduce hydrometeorological risks, improve water management, and increase agricultural productivity.

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Publication Details

Journal
International Journal of Climatology
Published
2025-06-19
DOI
https://doi.org/10.1002/joc.70009
Citations
2
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
2.21
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article

Changing Rainfall Patterns and Their Climatic Drivers in One of the Rainiest Places on Earth, Debundscha, Gulf of Guinea

Suiven John Paul Tume, Elias Nkiaka
2 citations
International Journal of Climatology
Climate variability and models
2.21
article

Changing Rainfall Patterns and Their Climatic Drivers in One of the Rainiest Places on Earth, Debundscha, Gulf of Guinea

Suiven John Paul Tume, Elias Nkiaka
article en
2 citations

Abstract

ABSTRACT Debundscha is ranked amongst the top rainiest places on Earth, yet there is a paucity of information on rainfall trends and their drivers in the area. However, the increasing frequency and intensity of hydrometeorological disasters, declining crop yields, and rising water scarcity in the area underscore the urgent need to investigate changing rainfall patterns and the climatic modes influencing rainfall in the area. Trend analysis using the Mann‐Kendall test shows non‐statistically significant declining trends in annual and seasonal rainfall in Debundscha (1972–2009) and other stations, except Limbe, which exhibits statistically significant increasing trends in annual and seasonal rainfall (1985–2015). Statistical analysis using partial least squares regression reveals that the Atlantic Multidecadal Oscillation (AMO), Southern Oscillation Index, Indian Ocean Dipole Western Pool Index, global sea surface temperature (GSST), Multivariate ENSO Index, and El Niño‐Southern Oscillation are the dominant climatic modes influencing annual and seasonal rainfall in the study area. However, a different set of climatic modes affects rainfall at each station, with AMO and GSST strongly associated with annual rainfall in Debundscha. Analysing rainfall in high precipitation areas like Debundscha is essential for understanding how these regions are affected by changing climate patterns. On the other hand, identifying the main climatic modes influencing local rainfall is crucial for creating accurate seasonal and sub‐seasonal forecasts. These forecasts can help reduce hydrometeorological risks, improve water management, and increase agricultural productivity.

International Journal of ClimatologyVol. 45(11)
University of Bamenda (CM), University of Lincoln (GB)
Openalex Percentile: Top 13%
Climate variability and models
2.21
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