Proceedings of the 7th International Workshop on Climate Informatics: CI 2017

For the 2017 workshop, participants convened at the National Center for Atmospheric Research (NCAR) in Boulder, Colorado between September 20-22. The main workshop (September 21-22) featured five invited speakers, a poster session, short talks by several early career scientists, and two panel discussions.

Invited speakers covered many topics from across the spectrum of climate informatics: Alexis Hannart (Ouranos) explained how causal counterfactual theory can be used to attribute events in the climate system; Robert Lund (Clemson University) spoke about statistical challenges posed by analyzing trends in real-world observations; Elisabeth Moyer (University of Chicago) explained how climate models can be most efficiently used to augment limited observations; Prabhat (Lawrence Berkeley National Laboratory) presented recent advances in using deep learning at scale to identify extreme events such as hurricanes and atmospheric rivers; and Sai Ravela (MIT) described how physical constraints can be used to improve machine learning in the context of data assimilation systems.