Government weather forecasters love El Nino. For years they have used this fluctuating current in the Pacific Ocean (in El Nino years, sea surface temperatures in the western tropical Pacific rise, while in La Nina years they fall) to forecast winter weather months in advance. In El Nino years, they basically expect the northeast to be a little warmer than the historical average, the southern tier to be colder, and the southeast to be snowier. La Nina years are supposed to bring balmier winters to almost all the continental U.S.

In fact, government forecasters love El Nino so much that even when a better basis for seasonal prediction comes along, they stick with the kid.

Since 1999, scientists led by meteorologist Judah Cohen, director of seasonal forecasting at AER Inc., of Lexington, Mass., have been gathering more and more evidence that there’s a better way. As he and physicist Christopher Fletcher of the University of Toronto report in the August issue of the Journal of Climate, the predictive power of El Nino, at least outside the tropics where its effects are directly felt, can’t hold a candle to an alternative: using the amount of snowcover in October in Eurasia and, especially, Siberia to predict upcoming winter temperatures and snowfall for the high- and mid-latitudes of the Northern Hemisphere—basically, the eastern U.S. and northern Europe and Asia. They call their predictive model sCast, where the "s" stands for snow.