Extended Abstract

From these equations one can see that the only difference is that the base rate p isreplaced in the numerator of SEDS with q. By definition, SEDS > EDS only and if p > q.If the forecasts were to be re-calibrated by having p = q then SEDS would equal EDS.Ferro & Stephenson (2010) very recently proposed two new versions to the “extremedependency score family”, the Extremal Dependency Index EDI and the SymmetricExtremal Dependency Index SEDI:andEDI = ( log F – log H ) / ( log F + log H )SEDI = log F – log H – log ( 1 – F ) + log ( 1 – H )log F + log H + log ( 1 – F ) + log ( 1 – H ).In the former, p and q of EDS and SEDS, respectively, are replaced by the false alarmrate F and, in the latter, there are two additional terms log (1-F) and log (1-H). The roleof these terms is negligible in rare event cases when both H and F would decay towardszero with the rarity of the event (when p approaches 0). These terms are included tomake the score SEDI complement symmetric according to the authors. One reasoningbehind these two new scores is to obtain a base rate independent measure, thus havingthe measures as functions of H and F only.Primo & Ghelli (2009) and Ghelli & Primo (2009) have reported several undesirableproperties of the EDS measure like being dependent on the base rate p and being easyto hedge (i.e. issuing a forecast which would be against one’s judgement). Theseshortcomings were tried to be rectified by the SEDS measure, but the undesirable baserate dependency property still remained. The following table quoted from Ferro &Stephenson (2010) showcases properties related to all of these four measures(for more details, see the original paper):Ferro & Stephenson (2010) elaborate extensively on various properties of the EDS andits derivative scores. They conclude that the new scores, EDI and SEDI, overcome thedisadvantages of the EDS and SEDS. They further recommend that all forecasts shouldbe re-calibrated before adopting and computing any of these scores and that the(frequency) bias should be examined separately. This, however, has not been done inthe present study. We are merely showcasing results from initial experimentationsutilizing real forecast data used as guidance in an operational environment.3. ResultsThe data utilized in this study are seven years of NWP output of QPFs originating fromthe global ECMWF model and the limited area HIRLAM (high resolution) modeloperated by the Finnish Meteorological Institute. Some verification statistics arepresented for the four verification measures, EDS, SEDS, EDI and SEDI, as well as, forcomparison, for two traditional categorical verification measures, namely:-223-