Precip Soothsaying of Analyzing Data Networks

Abstract

Rainfall is important for food production plan, water resource management.
India is an agricultural country and its economy is largely based upon productivity. Thus
rainfall prediction becomes a significant factor in agricultural countries like India. On the
growing importance of Rainfall studies in the climate change scenario and High
Performance Computing, different Users starting from a farmer to a scientist to a policy
maker needs the rainfall prediction well in advance for their application like crop planning,
water storage etc. Data discovery from temporal, spatial and spatio- temporal data is
critical for rainfall analysis. However, recent growth in observations and model outputs,
combined with the increased availability of geographical data, presents new opportunities
for the users to implement new techniques such as predictive analytics for developing a
predictor which can be used for multi-scale forecasting of rainfall that is from 24 hour
forecast to long-range forecast say 2-3 month in advance forecast. Hence we developed
predictive analytics system for the efficient and real time prediction of rainfall over India.