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The proportion of previous forecasts that are "better" than the latest ones increases with lead-time:
- at short lead-times a small but significant proportion appear better (~15% at Day2),
- at longer lead-times a larger a larger proportion appear better (~40% at Day6). (Fig7.2-5).
There is only a very small correlation between forecast jumpiness and the quality of the latest forecast (Fig7.2-6).
Beyond about Day3 the ensemble mean, by using results from all ensemble members, provides more consistent forecasts than the ensemble control. This benefit gradually increases with forecast range. The frequency of a flip (single jump) is very similar for both the ensemble mean and ensemble control.The frequency of flip-flopping occurs clearly less frequently in the ensemble mean than in the ensemble control.Persson and Strauss (1995), Zsótér et al. (2009) found:
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the connection between forecast inconsistency (flip-flopping etc) and forecast error is weak,the average error of the ensemble mean relates quite strongly to the absolute spread in the ensemble. on average, larger spread implies larger errors (this does not apply to the ensemble median or ensemble control, even if they happen to lie mid-range within the ensemble)....
(Note: In older material there may be references to issues that have subsequently been addressed)
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Nil currently.