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.
ML
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 Combat the Urban Heat Island Effect
In a new COM-funded study, machine learning techniques are used to create a model of heat and carbon processes in the urban environment to provide resources for mitigation.
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.