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By combining a hurricane model and coupled ocean-atmosphere general circulation model to investigate the early Pliocene, Emanuel, Brierley and co-author Alexey Fedorov observed how vertical ocean mixing by hurricanes near the equator caused shallow parcels of water to heat up and later resurface in the eastern equatorial Pacific as part of the ocean wind-driven circulation. The researchers conclude from this pattern that frequent hurricanes in the central Pacific likely strengthened the warm pool in the eastern equatorial Pacific, which in turn increased hurricane frequency — an interaction described by Emanuel as a “two-way feedback process.”�The researchers believe that in addition to creating more hurricanes, the intense hurricane activity likely created a permanent El Nino like state in which very warm water in the eastern Pacific near the equator extended to higher latitudes. The El Nino weather pattern, which is caused when warm water replaces cold water in the Pacific, can impact the global climate by intermittently altering atmospheric circulation, temperature and precipitation patterns.The research suggests that Earth’s climate system may have at least two states — the one we currently live in that has relatively few tropical cyclones and relatively cold water, including in the eastern part of the Pacific, and the one during the Pliocene that featured warm sea surface temperatures, permanent El Nino conditions and high tropical cyclone activity.Although the paper does not suggest a direct link with current climate models, Fedorov said it is possible that future global warming could cause Earth to transition into a different equilibrium state that has more hurricanes and permanent El Nino conditions. “So far, there is no evidence in our simulations that this transition is going to occur at least in the next century. However, it’s still possible that the condition can occur in the future.”�Whether our future world is characterized by a mean state that is more El Nino-like remains one of the most important unanswered questions in climate dynamics, according to Matt Huber, a professor in Purdue University’s Department of Earth and Atmospheric Sciences. The Pliocene was a warmer time than now with high carbon dioxide levels. The present study found that hurricanes influenced by weakened atmospheric circulation — possibly related to high levels of carbon dioxide — contributed to very warm temperatures in the Pacific Ocean, which in turn led to more frequent and intense hurricanes. The research indicates that Earth’s climate may have multiple states based on this feedback cycle, meaning that the climate could change qualitatively in response to the effects of global warming.

Statistical validation of results, as Shaffer described it, simply involves testing the null hypothesis: that the pattern you detect in your data occurs at random. If you can reject the null hypothesis—and science and medicine have settled on rejecting it when there's only a five percent or less chance that it occurred at random—then you accept that your actual finding is significant. The problem now is that we're rapidly expanding our ability to do tests. Various speakers pointed to data sources as diverse as gene expression chips and the Sloan Digital Sky Survey, which provide tens of thousands of individual data points to analyze. At the same time, the growth of computing power has meant that we can ask many questions of these large data sets at once, and each one of these tests increases the prospects than an error will occur in a study; as Shaffer put it, "every decision increases your error prospects." She pointed out that dividing data into subgroups, which can often identify susceptible subpopulations, is also a decision, and increases the chances of a spurious error. Smaller populations are also more prone to random associations. In the end, Young noted, by the time you reach 61 tests, there's a 95 percent chance that you'll get a significant result at random. And, let's face it—researchers want to see a significant result, so there's a strong, unintentional bias towards trying different tests until something pops out. Young went on to describe a study, published in JAMA, that was a multiple testing train wreck: exposures to 275 chemicals were considered, 32 health outcomes were tracked, and 10 demographic variables were used as controls. That was about 8,800 different tests, and as many as 9 million ways of looking at the data once the demographics were considered.