Earth, Atmosphere & Environment Sciences
Title : | Improving Forecasts with Machine Learning (IMFORMAL) |
Area of research : | Earth, Atmosphere & Environment Sciences |
Focus area : | Atmospheric Science |
Principal Investigator : | PI: Dr. Krishna Achuta Rao, IIT Delhi, Hauz Khas, New Delhi-110016 |
Timeline Start Year : | 2023 |
Details
Executive Summary : | The main objective of the project is to demonstrate the usefulness of AI/ML techniques in improving model forecasts at time and space scales, which are then applied to few selected area such as extremes, renewable energy and landslides. The application of AI/ML techniques has seen explosive growth in recent years including inimproving forecasts from physics based models. While many international forecasting centres (ECMWF& UK MetOffice) have made substantial investments in the use of AI/ML, the same is not the case with the modeling centres in India. This project proposes using state-of-the-art deep learning algorithms to improve and add value to the forecasts from existing models run by the MoES modeling centres.Additionally, a new generation of manpower versatile in both atmospheric and data sciences will be trained. |
Co-PI: | Prof. Somnath Baidya Roy, Centre for Atmospheric Sciences, IIT Delhi Hauz Khas, New Delhi-110016, Prof. Sandeep Sukumaran, CAS, IIT Delhi Hauz Khas, New Delhi-110016, Prof. Hariprasad Kodamana, Department of Chemical Engineering, IIT Delhi Hauz Khas, New Delhi-110016 |
Total Budget (INR): | 84,17,080 |
Organizations involved