Can Earth System Models Capture Intricate Links between Phytoplankton, Environmental Factors, and Global Carbon?
New research on the key role of phytoplankton in the global carbon cycle was supported by a joint COM, CVP, and GOMO grant.
machine learning
Improving Model Representation of Western US Water Resources Using Machine Learning
To improve water management in the mountainous western US, COM-supported research presents a hybrid model approach to improve simulations of western water flow using both traditional and machine learning methods.
Using Machine Learning to Improve Atmospheric Black Carbon Prediction
Researchers funded by AC4 advance modeling and prediction of black carbon using machine learning techniques.
Improved and Expanded Global Ocean Carbon Product Using Machine Learning
Expanded record of air-sea CO2 fluxes created using machine learning techniques improves our ability to model annual changes in the ocean carbon sink.
Recent Research Supports NOAA Artificial Intelligence Strategy and CPO Water Resources Climate Risk Area
Two recent publications demonstrate the value of machine learning techniques to characterize complex water resources in the western U.S.