This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning
Sept.-Oct. 2013 (vol. 15 no. 5)
pp. 32-40
Claire Monteleoni, George Washington University
Gavin A. Schmidt, NASA Goddard Institute for Space Studies
Scott McQuade, George Washington University
Given the impact of climate change, understanding the climate system is an international priority. The goal of climate informatics is to inspire collaboration between climate scientists and data scientists, in order to develop tools to analyze complex and ever-growing amounts of observed and simulated climate data, and thereby bridge the gap between data and understanding. Here, recent climate informatics work is presented, along with details of some of the remaining challenges.
Index Terms:
Atmospheric measurements,Machine learning,Meteorology,Climate change,Informatics,climate science,machine learning,climate informatics,data mining,statistics
Citation:
Claire Monteleoni, Gavin A. Schmidt, Scott McQuade, "Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning," Computing in Science and Engineering, vol. 15, no. 5, pp. 32-40, Sept.-Oct. 2013, doi:10.1109/MCSE.2013.50
Usage of this product signifies your acceptance of the Terms of Use.