A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY GLOBAL WARMING SCENARIOS

A KNOWLEDGE DISCOVERY STRATEGY FOR RELATING SEA SURFACE TEMPERATURES TO FREQUENCIES OF TROPICAL STORMS AND GENERATING PREDICTIONS OF HURRICANES UNDER 21ST-CENTURY GLOBAL WARMING SCENARIOS

CAITLIN RACE, MICHAEL STEINBACH, AUROOP GANGULY, FRED SEMAZZI, AND VIPIN KUMAR

Abstract. The connections among greenhouse-gas emissions scenarios, global warming, and frequencies of hurricanes or tropical cyclones are among the least understood in climate science but among the most fiercely debated in the context of adaptation decisions or mitigation policies. Here we show that a knowledge discovery strategy, which leverages observations and climate model simulations, offers the promise of developing credible projections of tropical cyclones based on sea surface temperatures (SST) in a warming environment. While this study motivates the development of new methodologies in statistics and data mining, the ability to solve challenging climate science problems with innovative combinations of traditional and state-of-the-art methods is demonstrated. Here we develop new insights, albeit in a proof-of-concept sense, on the relationship between sea surface temperatures and hurricane frequencies, and generate the most likely projections with uncertainty bounds for storm counts in the 21st-century warming environment based in turn on the Intergovernmental Panel on Climate Change Special Report on Emissions Scenarios. Our preliminary insights point to the benefits that can be achieved for climate science and impacts analysis, as well as adaptation and mitigation policies, by a solution strategy that remains tailored to the climate domain and complements physics-based climate model simulations with a combination of existing and new computational and data science approaches.