An Extended Procedure for Implementing the Relative Operating Characteristic Graphical Method

Abstract

Abstract The functional relationship between the relative operating characteristic (ROC) and the economic value (EV) graphical methods have been exploited to develop a hybrid procedure called the extended ROC (EROC) method. The EROC retains the appealing simplicity of the traditional ROC method and the ability of the EV method to provide evaluation of the performance of an ensemble climate prediction system (EPS) for a hypothetical end user defined by the cost–loss ratio (μ = C/L). An inequality defining the lower and upper theoretical bounds of μ has been derived. Outside these limits, the EPS yields no added benefits for end user μ relative to the use of climatological persistence as an alternative prediction system. In the traditional ROC graphical method, the ROC skill (ROCS) is often expressed in terms of the area between the ROC graph and the diagonal baseline passing through the origin with slope m = 1. Thus, ROCS = 2A − 1, where A is the area under the ROC graph. In the proposed EROC approach, a more general procedure is recommended based on the construction of user-specific baselines that do not necessarily pass through the origin and, in general, have slope m ≠ 1. The skill of a particular EPS computed from the EROC method is proportional to the corresponding estimated value based on the EV graphical method. Therefore, the EROC geometry conveys the same basic information as the EV method. The Semazzi–Mera skill score (SMSS) is proposed as a convenient and compact way of expressing the combined verification based on the ROC and EV methods. The ROCS estimate is a special case of the SMSS. The near-horizontal trail-like geometry sometimes exhibited by EV graphs is also examined. It is shown to occur when either the hit-rate or false-alarm term dominates in the formula for EV, unlike the more typical situation in which both terms are comparable in magnitude.