What impact do potential cloud-forming particles have on extreme weather events using machine learning and artificial intelligence approach over Central Himalayan Region
Implementing Organization
Hemwati Nandan Bahuguna Garhwal University
Principal Investigator
Dr. Alok Sagar Gautam
Hemwati Nandan Bahuguna Garhwal University
Project Overview
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.