Earth, Atmosphere & Environment Sciences
Title : | What impact do potential cloud-forming particles have on extreme weather events using machine learning and artificial intelligence approach over Central Himalayan Region |
Area of research : | Earth, Atmosphere & Environment Sciences |
Principal Investigator : | Dr. Alok Sagar Gautam, Hemwati Nandan Bahuguna Garhwal University, Uttarakhand |
Timeline Start Year : | 2023 |
Timeline End Year : | 2026 |
Contact info : | phyalok@gmail.com |
Equipments : | Work Station Graphical Processing Unit (GPU), Neural Network Toolbox, with all accessories |
Details
Executive Summary : | It is not the possible to install automatic weather station, Optical particle counter, dust samplers and other instruments, due to extensive cost and manpower. Therefore to resolve this problem, ANN base method can provide a better understanding of data set and extreme weather events. Indian researchers have focused to understand the extreme weather events and prediction across India (Tiwari et al. 2016). Pabreja (2012) have try to predict the cloud bust over Leh but very few machine learning models was found that understand the extreme events over Uttarakhand. We have not found a any suitable literature, which covers the modeling of meteorological parameter to understand the aerosol particle size distribution their chemistry, and CCN growth. In this purposed project we have focused to calculate the aerosol properties based on metrological data set to understand extreme weather events over central Himalayan Region. |
Total Budget (INR): | 22,38,280 |
Organizations involved