Summaries - Office of Research & Innovation
Back Collaborative Research: Framework: Software: HDR: Data-Driven Earth System Modeling
|Division||Graduate School of Engineering & Applied Science|
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|