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Quantifying rainfall seasonality across South Africa on the basis of the relationship between rainfall and temperature

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Abstract

South Africa spans the subtropics at the interface between tropical, subtropical, and temperate weather systems, and consequently experiences distinct summer-, winter- and year-round rainfall zones (SRZ, WRZ and YRZ). Spatio-temporal characteristics of the various weather systems are broadly understood, however, the rainfall seasonality classification at the transition between these rainfall zones remains disputed. This surrounds the complexity of rainfall regimes, however, metrics with dissimilar rainfall seasonality definitions have been applied, hindering comparability. To address this dispute, meteorological data spanning 1987–2016 from 46 weather stations is used to assess the utility of a metric posited to quantify rainfall seasonality through a seasonality score derived from a ratio of monthly rainfall: temperature. This score statistically discriminates SRZ, WRZ and YRZ conditions, fulfilling an important requirement for a metric applied to South Africa. Nelspruit (NEL; score = 1.59) represents the strongest SRZ conditions across 30 eastern and central locations with scores > 0.30. Cape Town Wo (CTW; score = − 1.04) represents the strongest WRZ conditions across seven southwestern Cape and west coast locations with scores < − 0.30. Characterising the SRZ-to-WRZ transition region with scores from − 0.30 to 0.30, nine YRZ locations were classified. With the weakest score, Oudtshoorn (OUD; score = − 0.05), within the Cape Fold mountains, most represents YRZ conditions. Applicability across all weather stations, compatibility with known rainfall drivers, and agreement with known spatial rainfall seasonality characteristics demonstrates the ratio’s utility. Strong correspondence of scores between station and gridded data applications demonstrates additional confidence in the ratio, establishing its value for further application.

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Acknowledgements

This work was supported by the National Research Foundation (NRF), South Africa under Grant No. 107742 and the University of the Witwatersrand Faculty of Science Research Committee grant, both awarded to SJR. JMF is funded by the DSI-NRF Centre of Excellence for Palaeoscience. The authors acknowledge the South African Weather Service (SAWS) for providing station-based meteorological data, and the National Oceanographic and Atmospheric Administration (NOAA) for the publically available gridded climate data. We gratefully thank Marike Kluyts for editorial assistance during the preparation of this paper. We wish to acknowledge and express much gratitude to Prof Albertus J. Smit for his assistance with R code to perform the gridded data application presented herein. We additionally wish to acknowledge the anonymous reviewers whose insightful comments and suggestions have greatly improved this paper.

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  1. School of Geography, Archaeology and Environmental Studies, University of the Witwatersrand, Johannesburg, South Africa

    Sarah J. Roffe, Jennifer M. Fitchett & Christopher J. Curtis

  2. Department of Geography, Environmental Management and Energy Studies, University of Johannesburg, Johannesburg, South Africa

    Christopher J. Curtis

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  1. Sarah J. Roffe
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Roffe, S.J., Fitchett, J.M. & Curtis, C.J. Quantifying rainfall seasonality across South Africa on the basis of the relationship between rainfall and temperature. Clim Dyn 56, 2431–2450 (2021). https://doi.org/10.1007/s00382-020-05597-5

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