Machine learning and data mining approaches to climate science : proceedings of the 4th International Workshop on Climate Informatics /

Machine learning and data mining approaches to climate science : proceedings of the 4th International Workshop on Climate Informatics /

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Bibliographic Details
Meeting name:	International Workshop on Climate Informatics (4th : 2014 : Boulder, Colo.)
Imprint:	Cham ; New York : Springer, [2015] ©2015
Description:	1 online resource : illustrations
Language:	English
Series:	Online access with purchase: Springer (t)
Subject:	Climatic changes -- Data processing -- Congresses. Climatology -- Data processing -- Congresses. Environmental sciences -- Data processing -- Congresses. Climatic changes -- Data processing. Climatology -- Data processing. Environmental sciences -- Data processing. Conference papers and proceedings.
Format:	E-Resource Book
URL for this record:	http://pi.lib.uchicago.edu/1001/cat/bib/11094968

Hidden Bibliographic Details
Other authors / contributors:	Lakshmanan, Valliappa, editor. Gilleland, Eric, editor. McGovern, Amy, editor. Tingley, Martin P., editor.
ISBN:	9783319172200 3319172204 3319172190 9783319172194 9783319172194
Notes:	Includes bibliographical references and index. Vendor-supplied metadata.
Summary:	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.
Other form:	Printed edition: 9783319172194
Standard no.:	10.1007/978-3-319-17220-0

Table of Contents:

From the Contents: Machine learning, statistics, or data mining, applied to climate science
Management and processing of large climate datasets
Long and short-term climate prediction
Ensemble characterization of climate model projections
Past (paleo) climate reconstruction.