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Improving Forecasts with Machine Learning (IMFORMAL)

Implementing Organization

IIT Delhi, Hauz Khas
Principal Investigator
PI: Dr. Krishna Achuta Rao
IIT Delhi, Hauz Khas, New Delhi-110016
akrishna@cas.iitd.ac.in
CO-Principal Investigator
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
kodamana@chemical.iitd.ac.in,kodamana@ualberta.ca drsbr@iitd.ac.in,sandeep.sukumaran@cas.iitd.ac.in

Project Overview

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.
Funding Organization
Quick Information
Area of Research
Earth, Atmosphere & Environment Sciences
Focus Area
Atmospheric Science
Start Date
2023
Status
ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
Publications
00
No. of Patents
Filed : 00
Grant : 00
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