Conference on Intelligent Data Understanding 2010 (CIDU)

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.