How can we pick the best index for the job
{"Image DocumentName": "How can we pick the best index for the job?", "Image ImageDescription": "\u2022 Philosophically, the MEI has intuitive appeal, since it at least tries to address the multivariate \u2018nature of the beast\u2019; Ni\u00f1o 3.4 SST was only introduced a decade ago (Barnston et al., 1997), but has become the standard ENSO index in the U.S.; \u2022 From an impact perspective, one can compare the explained variance of, say, global temperature and precipitation fields based on various ENSO indices to decide which index is best (MEI beats Ni\u00f1o 3.4 and SOI in Western U.S.); \u2022 From an operational perspective, there is a need for an ENSO index that is most reliable (lowest False Alarm Rate, etc.) - initial results from Australia favor MEI over Ni\u00f1o 3.4 and SOI; \u2022 From a modeling perspective, a whole generation of coupled ocean- atmosphere models has been \u2018trained\u2019 to generate Ni\u00f1o 3.4 SST forecasts, but there has been a plateau in skill lately. Could it be that modeling and predicting the key features of the MEI is a more rewarding target?!", "Image XResolution": "37", "Image YResolution": "37", "Image ResolutionUnit": "Pixels/Centimeter", "Image Software": "SlidePlayer", "Image YCbCrPositioning": "Centered"}