Theory-Guided Data Science for Climate Change

To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.

Saved in:
Bibliographic Details
Published inComputer (Long Beach, Calif.) Vol. 47; no. 11; pp. 74 - 78
Main Authors Faghmous, James H., Banerjee, Arindam, Shekhar, Shashi, Steinbach, Michael, Kumar, Vipin, Ganguly, Auroop R., Samatova, Nagiza
Format Journal Article
LanguageEnglish
Published New York IEEE 01.11.2014
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
big data
Climate
Climate change
Climate science
data analysis
data mining
discovery analytics
Information science
Meteorology
Ocean temperature
scientific computing
Spatiotemporal phenomena
Statistical analysis
Temperature distribution
theory-guided data science
Online AccessGet full text

Cover

More Information
Summary:To adequately address climate change, we need novel data-science methods that account for the spatiotemporal and physical nature of climate phenomena. Only then will we be able to move from statistical analysis to scientific insights.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:0018-9162
1558-0814
DOI:10.1109/MC.2014.335