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dc.contributor.author | Phakula, Steven![]() |
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dc.contributor.author | Landman, Willem Adolf![]() |
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dc.contributor.author | Engelbrecht, Christina Johanna![]() |
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dc.date.accessioned | 2025-02-13T04:39:00Z | |
dc.date.available | 2025-02-13T04:39:00Z | |
dc.date.issued | 2024-01 | |
dc.description | DATA AVAILABILITY STATEMENT : Data openly available in a public repository that issues datasets with DOIs. | en_US |
dc.description.abstract | Subseasonal-to-seasonal (S2S) prediction has gained momentum in the recent past as a need for predictions between the weather forecasting timescale and seasonal timescale exists. The availability of S2S databases makes prediction and predictability studies possible over all the regions of the globe. Most S2S studies are, however, relevant to the northern hemisphere. In this review, the S2S literature relevant to the southern hemisphere (SH) are presented. Predictive skill, sources of predictability, and the application of S2S predictions are discussed. Indications from the subseasonal predictability studies for the SH regions suggest that predictive skill is limited to 2 weeks in general, particularly for temperature and rainfall, which are the variables most frequently investigated. However, temperature has enhanced skill compared to rainfall. More S2S prediction studies that include the quantification of the sources of predictability and the identification of windows of opportunity need to be conducted for the SH, particularly for the southern African region. The African continent is vulnerable to weather- and climate-related disasters, and S2S forecasts can assist in alleviating the risk of such disasters. | en_US |
dc.description.department | Geography, Geoinformatics and Meteorology | en_US |
dc.description.librarian | am2024 | en_US |
dc.description.sdg | SDG-13:Climate action | en_US |
dc.description.sdg | SDG-15:Life on land | en_US |
dc.description.sponsorship | NRF ACCESS through ACyS Project; University of Pretoria Postgraduate Progragramme; South African Weather Service. | en_US |
dc.description.uri | https://rmets.onlinelibrary.wiley.com/journal/14698080 | en_US |
dc.identifier.citation | Phakula, S., Landman, W. A., & Engelbrecht, C. J. (2024). Literature survey of subseasonal-to-seasonal predictions in the southern hemisphere. Meteorological Applications, 31(1), e2170. https://DOI.org/10.1002/met.2170. | en_US |
dc.identifier.issn | 1350-4827 (print) | |
dc.identifier.issn | 1469-8080 (online) | |
dc.identifier.other | 10.1002/met.2170 | |
dc.identifier.uri | http://hdl.handle.net/2263/100799 | |
dc.language.iso | en | en_US |
dc.publisher | Wiley | en_US |
dc.rights | © 2024 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License. | en_US |
dc.subject | S2S Predictions | en_US |
dc.subject | Sources of predictability | en_US |
dc.subject | Southern hemisphere | en_US |
dc.subject | Southern Africa | en_US |
dc.subject | Subseasonal-to-seasonal (S2S) | en_US |
dc.subject | SDG-13: Climate action | en_US |
dc.subject | SDG-15: Life on land | en_US |
dc.title | Literature survey of subseasonal-to-seasonal predictions in the southern hemisphere | en_US |
dc.type | Article | en_US |