Research Summaries

Back Collaborative Research: Framework: Software: HDR: Data-Driven Earth System Modeling

Fiscal Year 2019
Division Graduate School of Engineering & Applied Science
Department Applied Mathematics
Investigator(s) Giraldo, Francis X.
Kozdon, Jeremy E.
Wilcox, Lucas C.
Sponsor National Science Foundation (NSF)
Summary Within 5 years, the consortium (NPS, Caltech, MIT, and JPL) will develop and demonstrate an automatically learning Earth System Model (ESM) open-source framework, including a new atmosphere model, new process models for atmospheric turbulence and clouds and for ocean turbulence that will harness Data Assimilation/Machine Learning (DA/ML) advances, and scalable DA/ML algorithms for learning about parameters in process models -- algorithms that are efficient enough for the high computational demands of ESMs.
Keywords Data Assimilation Earth System Models machine learning
Publications Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal
Data Publications, theses (not shown) and data repositories will be added to the portal record when information is available in FAIRS and brought back to the portal