Spatiotemporal Rainfall Variability and Trends Analysis over the Enkangala Escarpment of South Africa (1972–2022)

This study explores rainfall variability and trends in the Enkangala Escarpment of South Africa using station data from 1972 to 2022 (51 years). The coefficient of variation (CV) is indicative of pronounced inter-annual variability in seasonal rainfall totals across the region. The trend-free pre-whitening Mann–Kendall (TFPWMK) test and innovative trend analysis (ITA) were used to determine the presence of monotonic trends in the station records, despite the pronounced inter-annual variability in the time series. Sen’s slope estimator was used to quantify the magnitude of the trends. For a given season, the ITA test, in general, allocates local statistical significance to the time series for more stations compared to the TFPWMK test. For winter, spring and summer, there is spatial coherency of decreasing rainfall trends across the Enkangala Escarpment. These trends also exhibit local significance for spring at most stations, and are indicative of less favorable growing conditions for crops during this season. Reduced spring rainfall is likely to also translate to later planting dates (a shorter growing season) and a longer burning season. Trends for autumn are generally weak and lack in local statistical significance or spatial coherency.

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Publication Details

Journal
Atmosphere
Published
2025-04-03
DOI
https://doi.org/10.3390/atmos16040414
Primary Topic
Climate variability and models
Type
article
Field-Weighted Citation Impact
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article

Spatiotemporal Rainfall Variability and Trends Analysis over the Enkangala Escarpment of South Africa (1972–2022)

François Engelbrecht, Mary C. Scholes, Hadisu Bello Abubakar
Atmosphere
Climate variability and models
article

Spatiotemporal Rainfall Variability and Trends Analysis over the Enkangala Escarpment of South Africa (1972–2022)

François Engelbrecht, Mary C. Scholes, Hadisu Bello Abubakar
article en

Abstract

This study explores rainfall variability and trends in the Enkangala Escarpment of South Africa using station data from 1972 to 2022 (51 years). The coefficient of variation (CV) is indicative of pronounced inter-annual variability in seasonal rainfall totals across the region. The trend-free pre-whitening Mann–Kendall (TFPWMK) test and innovative trend analysis (ITA) were used to determine the presence of monotonic trends in the station records, despite the pronounced inter-annual variability in the time series. Sen’s slope estimator was used to quantify the magnitude of the trends. For a given season, the ITA test, in general, allocates local statistical significance to the time series for more stations compared to the TFPWMK test. For winter, spring and summer, there is spatial coherency of decreasing rainfall trends across the Enkangala Escarpment. These trends also exhibit local significance for spring at most stations, and are indicative of less favorable growing conditions for crops during this season. Reduced spring rainfall is likely to also translate to later planting dates (a shorter growing season) and a longer burning season. Trends for autumn are generally weak and lack in local statistical significance or spatial coherency.

AtmosphereVol. 16(4)
University of the Witwatersrand (ZA)
Openalex Percentile: Top 92%
Climate variability and models
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