> In other words, I’m concerned that this is like applying machine learning to the predictions of a set of Tarot cards.
You're not the only one feeling like that. See John's [comment](http://forum.azimuthproject.org/discussion/1358/project-using-climate-networks-for-el-nino-signal-processing/?Focus=10725#Comment_10725). A quote from the paper "To statistically validate our method, we have divided this time interval into two equal parts..." though I don't see any formal test of the success rate. The problem with any formal test is that you don't know how much they tweaked the method, consciously or subconsciously.
As I said in the other thread, it might be better to attempt continuous predictions of an El Niño index like NINO3.4. If one could get decent predictions of that at all times, not just during El Niño events, it would be much more convincing.
I don't think it is quite as bad as Tarot cards. The finding that S(t) tends to decrease during El Niño events seems pretty well supported, and while there is no explicit mechansim, it seems plausible that such a mechansim exists. El Niño events certainly stir things up. If S(t) decreases during El Niño events it must increase between them (assuming no long term trend in S(t)), so any measure of increase in S(t) (such as crossing a threshold) is likely to be positively correlated with future El Niño events. It might be like predicting an avalanche next week if the snow reaches a certain depth this week, in an area where avalanches occur randomly and about once every 4 weeks on average.