Title :
Climate Informatics: Accelerating Discovering in Climate Science with Machine Learning
Author :
Monteleoni, Claire ; Schmidt, Gavin A. ; McQuade, Scott
Author_Institution :
George Washington Univ., Washington, DC, USA
Abstract :
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.
Keywords :
climate mitigation; geophysics computing; learning (artificial intelligence); climate change; climate informatics; climate science; machine learning; Atmospheric measurements; Climate change; Informatics; Machine learning; Meteorology; climate informatics; climate science; data mining; machine learning; statistics;
Journal_Title :
Computing in Science & Engineering
DOI :
10.1109/MCSE.2013.50
