Machine Learning and Data Mining Approaches to Climate Science

Machine Learning and Data Mining Approaches to Climate Science

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This book presents innovative work in Climate Informatics, a new field that reflects the application of data mining methods to climate science, and shows where this new and fast growing field is headed. Given its interdisciplinary nature, Climate Informatics offers insights, tools and methods that are increasingly needed in order to understand the climate system, an aspect which in turn has become crucial because of the threat of climate change. There has been a veritable explosion in the amount of data produced by satellites, environmental sensors and climate models that monitor, measure and forecast the earth system. In order to meaningfully pursue knowledge discovery on the basis of such voluminous and diverse datasets, it is necessary to apply machine learning methods, and Climate Informatics lies at the intersection of machine learning and climate science. This book grew out of the fourth workshop on Climate Informatics held in Boulder, Colorado in Sep. 2014.Dimensions. The atmosphere is truly three dimensional, so it would be more appropriate to develop spatial models that can be used to ... 2014), at a later time. ... Furthermore, PC stable is ideal for parallelization and introducing multithreading yielded another factor of 4 on a standard laptop or PC (e.g., MacBook Pro).


Title:Machine Learning and Data Mining Approaches to Climate Science
Author: Valliappa Lakshmanan, Eric Gilleland, Amy McGovern, Martin Tingley
Publisher:Springer - 2015-06-30
ISBN-13:

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