Interdisciplinary Science Session: Can Machine Learning and Data-driven Science Lead to Breakthroughs in Earth System Modeling and Analysis?; Aspen, Colorado; June 7-11, 2021

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Recent years have seen an explosion in the use of machine learning (ML) and other data science techniques in applications from self-driving cars to targeted advertising to medical diagnosis. Meanwhile climate and earth system science have become increasingly data intensive, as the volume of data from observing systems and computer models has increased almost exponentially. There is thus considerable interest in finding ways to apply the tools of data science to the problems of climate and earth system science.This workshop brings together a group of researchers from the fields of climate, earth system science, statistics, data science, and related disciplines to seek novel and productive ways to apply data science tools to climate and earth system science. One application to be considered is the use of ML as a means of representing small-scale processes in climate and earth system models. Another is the use of ML and similar techniques for the analysis of large volumes of data. Particular challenges to be considered include the incorporation of physical constraints into ML algorithms and the extent to which results of ML-based analysis can be interpreted in physically meaningful ways.The workshop has broader impacts through its attempt to introduce new and powerful tools into climate and earth system science. Data science tools have the potential to enhance the societal value of research results, for example by allowing scientists to provide better guidance to planners and stakeholders facing threats posed by extreme weather, climate change, and other earth system phenomena. Public outreach will be performed through a keynote lecture and web-accessible videos of workshop presentations, and a perspective paper will be published as a result of the meeting. The workshop is planned for the week of 7 June 2021.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.