Workshop on Big Data, Data Assimilation and Uncertainty Quantification
Abstract
Methods for assimilating data into physics-based, dynamical models or for building data-driven surrogate models of relevant physical, social or economic phenomena are becoming familiar in many contexts. The climate sciences, though, have been an early and major incentive for their development.The huge size of the datasets and models used in climate studies, together with the pressure to deliver quantitative predictions has led to great scientific and technological achievements in the field of data assimilation. The remarkable increase of available datasets in the big data era, accompanied by a similarly spectacular growth in computing power, have enabled the successful use of fully data-driven approaches even in areas of the physical science where one generally possesses a credible understandingof the physical processes. This data-driven revolution has been greatly stimulated by remarkable successes of machine-learning (ML) techniques ~ e.g., deep learning and neural networks, among others ~ in extracting the underlying dynamical laws from a multivariate dataset and in achievingimpressive predictive skill, as well as in classifying complex types of behavior. Accurate and reliable quantification of the uncertainty is crucial in data assimilation as well as in data-driven approaches: it is required to meaningfully weight the different ingredients of the assimilation process and it is desirablewhen a decision based on the prediction is required.Along this line this proposal is aimed at co-funding the Workshop ~Big data, data assimilation, and uncertainty quantification~ (Paris, 12-15 November 2019) that will bring together climate scientists, applied mathematicians and computer scientists working on big data, data assimilation and uncertainty quantification for problems that originate in the climate sciences. The event is planned so as to benefit from, to transmit, and to further develop the exciting scientific moment these disciplines are experiencing. The workshop is part of a larger initiative, the thematic trimester ~The Mathematics of Climate and the Environment ~ CliMathParis2019~
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Aug 20, 2019
- Source ID
- N000141912567
Entities
People
- Alberto Carrassi
Organizations
- Nansen Environmental and Remote Sensing Center
- Office of Naval Research
- United States Navy