The threat of climate change is one of the greatest challenges currently facing society. Given the profound impact machine learning has made on the natural sciences to which it has been applied, such as the field of bioinformatics, we are forging and encouraging collaborations between machine learning (as well as data mining and statistics) and climate science in order to accelerate progress in answering pressing questions in climate science.
The goal of this workshop is to incubate this new field, climate informatics. Recent progress on climate informatics reveals that collaborations with climate scientists also open interesting new problems for machine learning. There are myriad collaborations possible at the intersection of these two fields. We hope that every workshop attendee leaves with a new collaboration in climate informatics. The format of the workshop will emphasize communication among the various fields, with a strong emphasis on brainstorming and break-out sessions, as well as a panel discussion. We will also generate a white paper on climate informatics as a result of the workshop.
Focusing on topics at the interface of climate science with machine learning, data mining, statistics, and related fields, the workshop's topics will include, but not be limited to:
- • Machine learning, data mining, or statistics as applied to climate science
- • Long-term climate prediction
- • Short-term climate prediction
- • Combining the predictions of climate model ensembles
- • Past climate reconstruction
- • Uncertainty quantification
- • Spatio-temporal methods applied to climate data
- • Time series methods applied to climate data
- • Methods for modeling and predicting climate extremes
- • Climate change attribution
- • Dependence and causality among climate variables
- • Data assimilation
- • Hybrid methods
- • Modeling of climate data
Networking reception to follow.
Additional information available on the climate informatics workshop wiki.
Information Science and Technology Center at Los Alamos National Laboratory
Columbia University Department of Statistics
Image credit: Michael Tippett. Colors show deviations of sea-surface temperatures from their climatological values in the equatorial Pacific from January 1997 to April 2000 with time going counter-clockwise.