The superior influence of Darwin Sea level pressure anomalies over ENSO as a simple drought predictor for Southern Africa |
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| Authors: | D Manatsa W Chingombe H Matsikwa C H Matarira |
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| Institution: | (1) Faculty of Science, Bindura University of Science Education, Bindura, Zimbabwe;(2) Faculty of Environmental Science, National University of Lesotho, Lesotho |
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| Abstract: | Summary The dominant climatic mode responsible for seasonal rainfall variability across central southern Africa has been well-established
as ENSO. Hence, the El Ni?o signal of the equatorial Pacific has been used extensively to predict droughts in this sub-region.
Although this paper acknowledges that El Ni?o influences rainfall deficits over eastern southern Africa, an earlier signal
of extreme positive sea level pressure (SLP) anomalies at Darwin for the averaged March to June period (MAMJ Darwin) has proved
to have a superior remote connection to droughts in the sub-region. Simple linear statistical tools including composite techniques
and correlation methods have been employed on century long data sets (1901–2000) to identify the emerging paramount connection
between MAMJ Darwin SLP anomalies and southern African rainfall.
Both MAMJ Darwin SLP anomalies and the Zimbabwe seasonal rainfall time series are significantly correlated (above the 95%
significant level) with sea surface temperature anomalies. These represent the Indian Ocean Dipole mode in the tropical Indian
Ocean and ENSO in the tropical Pacific for the averaged September to December period. ‘Pure’ MAMJ Darwin (that occur in the
absence of El Ni?o in the Pacific) coincide with droughts more significantly (83% hit rate) than ‘pure’ El Ni?o events (not
preceded by a high MAMJ Darwin) (38% hit rate). Co-occurrences (MAMJ Darwin preceded by El Ni?o) do not only have the highest
hit rate of 93% but subsequent droughts are noticeably more severe. The ‘pure’ El Ni?os however, are not only poorly related
to Zimbabwe seasonal rainfall deficits, but are apparently not connected to extreme droughts of the 20th century. Thus, MAMJ Darwin is a good simple predictor of droughts associated with or without ENSO in the Pacific. The high
prediction skill of these results, especially the inherent longer lead-time than ENSO, makes MAMJ Darwin SLP anomalies an
ideal additional input candidate for sub-regional drought monitoring and forecasting schemes. In this way, drought early warning
and disaster preparedness activities can be enhanced over the sub-region.
Authors’ addresses: D. Manatsa, W. Chingombe, H. Matsikwa, Faculty of Science, Bindura University of Science Education, P.
Bag 1020, Bindura, Zimbabwe; C. H. Matarira, Department of Geography and Environmental Science, National University of Lesotho,
Roma 180, Lesotho. |
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