55 citations · 108 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
WRF model parameter calibration to improve the prediction of tropical cyclones over the Bay of Bengal using Machine Learning-based Multiobjective Optimization
Harish Baki, Sandeep Chinta, C. Balaji +1
The prediction skill of a numerical model can be enhanced by calibrating the sensitive parameters that significantly influence the model forecast. The objective of the present stud…
Determining the sensitive parameters of WRF model for the prediction of Tropical cyclones in Bay of Bengal using Global sensitivity analysis and Machine learning
Harish Baki, Sandeep Chinta, C. Balaji +1
The present study focuses on identifying the parameters from the Weather Research and Forecasting (WRF) model that strongly influence the prediction of tropical cyclones over the B…
Assessment of WRF model parameter sensitivity for high-intensity precipitation events during the Indian summer monsoon
Sandeep Chinta, Yaswanth Sai Jetti, C Balaji
Default values for many model parameters in Numerical Weather Prediction models are typically adopted based on theoretical or experimental investigations by scheme designers. Short…