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physics.ao-ph2023
Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions
Sandeep Chinta, Xiang Gao, Qing Zhu
Methane (CH4) is the second most critical greenhouse gas after carbon dioxide, contributing to 16-25% of the observed atmospheric warming. Wetlands are the primary natural source o…
physics.ao-ph2023
PAUNet: Precipitation Attention-based U-Net for rain prediction from satellite radiance data
P. Jyoteeshkumar Reddy, Harish Baki, Sandeep Chinta +2
This paper introduces Precipitation Attention-based U-Net (PAUNet), a deep learning architecture for predicting precipitation from satellite radiance data, addressing the challenge…
physics.ao-ph2023
Machine Learning based Parameter Sensitivity of Regional Climate Models -- A Case Study of the WRF Model for Heat Extremes over Southeast Australia
P. Jyoteeshkumar Reddy, Sandeep Chinta, Richard Matear +5
Heatwaves and bushfires cause substantial impacts on society and ecosystems across the globe. Accurate information of heat extremes is needed to support the development of actionab…