Climate Informatics

• Main Authors: Niculescu-Mizil, Alexandru, Smerdon, Jason E., Steinhaeuser, Karsten, Alexander, Francis J., Banerjee, Arindam, Schmidt, Gavin A., Monteleoni, Claire, Tedesco, Marco, Blumenthal, M. Benno, Tippett, Michael, Ganguly, Auroop R.
• Format: Other/Unknown Material
• Language: unknown
• Published: 2013
• Subjects: Documentation and Information Science; Meteorology and Climatology; Sea ice
• Online Access: http://hdl.handle.net/2060/20150000709

The impacts of present and potential future climate change will be one of the most important scientific and societal challenges in the 21st century. Given observed changes in temperature, sea ice, and sea level, improving our understanding of the climate system is an international priority. This system is characterized by complex phenomena that are imperfectly observed and even more imperfectly simulated. But with an ever-growing supply of climate data from satellites and environmental sensors, the magnitude of data and climate model output is beginning to overwhelm the relatively simple tools currently used to analyze them. A computational approach will therefore be indispensable for these analysis challenges. This chapter introduces the fledgling research discipline climate informatics: collaborations between climate scientists and machine learning researchers in order to bridge this gap between data and understanding. We hope that the study of climate informatics will accelerate discovery in answering pressing questions in climate science.