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.
