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Data mining and knowledge discovery is becoming more and more important for climate change and impacts. The massive volumes of relatively recent climate-related observations from remote and in-situ sensors, proxy observations from the past, as well as simulations from global or regional climate models, need to be mined for predictive insights on climate extremes and to generate projections with uncertainty. Climate extremes could mean extreme hydrological or meteorological events as well as extreme stresses on critical infrastructures and key resources caused by regional and decadal change. Computational data sciences can extract novel insights about climate extremes and regional change, while geographical information sciences can relate climate change and extremes to societal and ecological impacts.
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