Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning

被引：28

作者：

Monteleoni, Claire ^{[1
]}

Schmidt, Gavin A. ^{[2
]}

McQuade, Scott ^{[1
]}

机构：

[1] George Washington Univ, Washington, DC 20052 USA

[2] NASA, Goddard Inst Space Studies, Greenbelt, MD 20771 USA

来源：

COMPUTING IN SCIENCE & ENGINEERING | 2013年 / 15卷 / 05期

关键词：

climate informatics; climate science; data mining; machine learning; statistics;

D O I：

10.1109/MCSE.2013.50

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

The goal of climate informatics, an emerging discipline, 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 discussed, along with some of the field's remaining challenges.

引用

页码：32 / 40

页数：9

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