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Climate InformaticsThe impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science.
Document ID
20150000709
Acquisition Source
Goddard Space Flight Center
Document Type
Book Chapter
Authors
Monteleoni, Claire
(George Washington Univ. Washington, DC, United States)
Schmidt, Gavin A.
(NASA Goddard Inst. for Space Studies New York, NY United States)
Alexander, Francis J.
(Los Alamos National Lab. Albuquerque, NM, United States)
Niculescu-Mizil, Alexandru
(NEC Laboratories America, Inc. Princeton, NJ, United States)
Steinhaeuser, Karsten
(Minnesota Univ. Minneapolis, MN, United States)
Tippett, Michael
(Columbia Univ. Dobbs Ferry, NY, United States)
Banerjee, Arindam
(Minnesota Univ. Minneapolis, MN, United States)
Blumenthal, M. Benno
(Columbia Univ. Dobbs Ferry, NY, United States)
Ganguly, Auroop R.
(Northeastern Univ. Boston, MA, United States)
Smerdon, Jason E.
(Columbia Univ. Dobbs Ferry, NY, United States)
Tedesco, Marco
(City Univ. of New York NY, United States)
Date Acquired
January 22, 2015
Publication Date
April 4, 2013
Publication Information
Publication: Computational Intelligent Data Analysis for Sustainable Development
Publisher: CRC Press
ISBN: 978-1439895948
Subject Category
Documentation And Information Science
Meteorology And Climatology
Report/Patent Number
GSFC-E-DAA-TN19114
Report Number: GSFC-E-DAA-TN19114
ISBN: 978-1439895948
Funding Number(s)
CONTRACT_GRANT: NOAA NA10OAR4320137
CONTRACT_GRANT: NSF ATM0902436
CONTRACT_GRANT: NOAA NA07OAR4310060
CONTRACT_GRANT: NSF ARC0909388
CONTRACT_GRANT: NSF 1029166
WBS: WBS 509496.02.08.04.24
CONTRACT_GRANT: NSF IIS-0916750
CONTRACT_GRANT: NSF IIS-0812183
CONTRACT_GRANT: NSF IIS-0953274
CONTRACT_GRANT: NSF 1029711
CONTRACT_GRANT: NSF IIS-1029711
CONTRACT_GRANT: NOAA NA05OAR4311004
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Climate change
Machine learning
Climate modeling
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