CGCS Directory

Research Interests

Dr. Chinta's work focuses on using machine learning methods and observations to improve the parameterization of the land surface biogeochemistry model and to understand the key processes and controls underlying methane emissions. He conducts modeling experiments with the state-of-the-art methane biogeochemistry model (i.e., CESM2 community land model). He uses machine learning to emulate model-simulated methane emissions for model sensitivity analysis and parameter calibration. He has previously worked on improving the short-range prediction of heavy rainfall events during Indian monsoon and tropical cyclones using data assimilation and machine learning.