Seasonal temperature prediction skill over Southern Africa and human health

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dc.contributor.author Lazenby, Melissa J.
dc.contributor.author Landman, W.A. (Willem Adolf), 1964-
dc.contributor.author Garland, Rebecca M.
dc.contributor.author DeWitt, David G.
dc.date.accessioned 2015-09-18T13:00:38Z
dc.date.issued 2014-10
dc.description.abstract An assessment of probabilistic prediction skill of seasonal temperature extremes over southern African is presented. Verification results are presented for six run-on seasons; September to November, October to December, November to January, December to February, January to March and February to April over a 15- year retroactive period. Comparisons are drawn between downscaled seasonal 850 hPa geopotential height field forecasts of a two-tiered system versus downscaled height forecasts from a coupled ocean-atmosphere system. The ECHAM4.5 atmospheric general circulation model is used for both systems; in the one-tiered system the ECHAM4.5 is directly coupled to the ocean model MOM3, and the two-tiered system the ECHAM4.5 is forced with Van den Dool SST hindcasts. Model output statistic equations are developed using canonical correlation analysis to reduce system deficiencies. Probabilistic verification is conducted using the relative operating characteristic (ROC) and reliability diagram. The coupled model performs best in capturing seasonal maximum temperature extremes. Seasons demonstrating the highest ROC scores coincide with the period of highest seasonal temperatures found over southern Africa. The above-normal category of the one-tiered system indicates the highest skill in predicting maximum temperature extremes, implying the coupled model skilfully predicts when there is a high likelihood of experiencing extremely high seasonal maximum temperatures during mid to late summer. The downscaled coupled maximum temperature hindcasts are additionally evaluated in terms of their monetary value and quality to the general public. The seasonal forecast system presented here should be able to reduce risks in decision making by the health industry in southern Africa. en_ZA
dc.description.embargo 2015-10-31
dc.description.librarian hb2015 en_ZA
dc.description.uri http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1469-8080 en_ZA
dc.identifier.citation Lazenby, MJ, Landman, WA, Garland, RM & DeWitt, DG 2014, 'Seasonal temperature prediction skill over Southern Africa and human health', Meteorological Applications, vol. 21, no. 4, pp. 963-974. en_ZA
dc.identifier.issn 1350-4827 (print)
dc.identifier.issn 1469-8080 (online)
dc.identifier.other 10.1002/met.1449
dc.identifier.uri http://hdl.handle.net/2263/49998
dc.language.iso en en_ZA
dc.publisher Wiley en_ZA
dc.rights © 2014 Royal Meteorological Society. This is the pre-peer reviewed version of the following article : Seasonal temperature prediction skill over Southern Africa and human health, Meteorological Applications, vol. 21, no. 4, pp. 963-974, 2014, doi :10.1002/met.1449. The definite version is available at : http://onlinelibrary.wiley.com/journal/10.1002/(ISSN)1469-8080. en_ZA
dc.subject One- and two-tiered forecasting systems en_ZA
dc.subject Seasonal temperature extremes en_ZA
dc.subject Downscaling en_ZA
dc.subject Probabilistic en_ZA
dc.subject General public value en_ZA
dc.subject Health implications en_ZA
dc.title Seasonal temperature prediction skill over Southern Africa and human health en_ZA
dc.type Postprint Article en_ZA


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