Investigating relationship between drought severity in Botswana and ENSO

Jimmy Byakatonda (), B. P. Parida, Ditiro B. Moalafhi, Piet K. Kenabatho and David Lesolle
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Jimmy Byakatonda: Gulu University
B. P. Parida: University of Botswana
Ditiro B. Moalafhi: University of Botswana
Piet K. Kenabatho: University of Botswana
David Lesolle: University of Botswana

Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, 2020, vol. 100, issue 1, No 14, 255-278

Abstract: Abstract Influences of El Niño southern oscillation (ENSO) on weather systems have increased the frequency and amplitude of extreme events over the last century. This even continues to exacerbate the already warming earth, with 2014–2016 which coincided with the strongest El Niño years observed as the warmest period in recent past. This study presents an approach of characterizing droughts at various timescales and establishes teleconnections between ENSO and drought severity in Botswana. The study uses Standardized Precipitation Evaporation Index (SPEI) at timescales of 1, 3, 6, 12 and 24 month to characterize droughts and Pearson’s correlations to study the teleconnections between SPEIs and ENSO. Results from the study reveal that extreme droughts are a rare occurrence in Botswana though it is more prone to moderate droughts at 12 month SPEI with a probability of 19% in the north. The highest severe drought probability was 7% recorded in the east. Linear trends indicate increasing dryness of around 0.8% per decade. These results have demonstrated that warm sea surface temperatures combined with negative Southern Oscillation Index correspond to persistent negative SPEI values and thus are likely to result in dry conditions. Significant correlations were observed in the mid austral summer in December and January. Due to this relationship, the drought early warning systems could use ENSO as one of the instruments for predicting drought over the study area and hence in its management.

Keywords: Drought vulnerability; Early warning; El Niño; Pearson’s correlation; Standardized Precipitation Evaporation Index (search for similar items in EconPapers)
Date: 2020
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DOI: 10.1007/s11069-019-03810-1

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