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Development of a machine learning method for classification and nowcasting of rainfall using Doppler Weather Radar.

Implementing Organization

Indian Institute of Technology (Indore)
Principal Investigator
PI: Dr. Saurabh Das
Indian Institute of Technology (Indore)
das.saurabh01@gmail.com,saurabh.das@iiti.ac.in
CO-Principal Investigator
Dr. Abhirup Datta
Indian Institute of Technology (Indore)
abhirup.datta@iiti.ac.in

Project Overview

The problem of issuing a nowcasting warning is difficult task for meteorologists, mainly because of the extremely large set of data, which has to be analyzed in a short period of time. Therefore, ML based methods are useful for offering effective solutions for nowcasting by learning relevant patterns from the large amount of weather data and thus improving decision making for high impact weather. Most of the existing operational and semi-operational methods for nowcasting are using the extrapolation of radar data and algorithms mainly based on cell tracking. However, existence of varied rain type and topographic influence are major limiting factor in such prediction methods. Hence, the present proposal aims to introduce machine learning (ML) based methods ( particularly the Deep learning methods) for obtaining effective solutions for the nowcasting problem.
Funding Organization
Funding Organization
Ministry of Earth Sciences (MoES)
Quick Information
Area of Research
Earth, Atmosphere & Environment Sciences
Focus Area
Atmospheric Science
Start Year
2022
Sanction Amount
₹ 71.80 L
Status
Ongoing
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
N/A
Startup (If Any)
00
No. of Patents
Filed :00
Grant :00
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