Survay on Weather Prediction Using Bigdata Analsystics in Dotnet

Huge losses occur all most on a daily basis due to many natural calamities like earth quakes, storms, cyclones etc. that will have adverse effects on the lives of billions of people. In the modern world, the prediction of environmental impact had become a challenging task. A rigorous rainfall prediction system is very useful and important for most of the country like India, because these are mainly depends on agriculture. For investigating the yield productivity, use of water resources and rainfall, prediction is very important. Many Statistical and Predictive models for rainfall forecasting system are available in the literature. This models provides less accuracy prediction models in large-scale rainfall forecasting (Yearly basis) due to the dynamic temperament of climate conditions. Weather damage prediction is an important research issue where it relates, both science and technology in order to forecast the weather damage of a particular location. We have a many good prediction system but there is no proper estimation for future damage because the time span between the present moment and time for which forecasting is being made and released is varied. By collecting previous datasets from datacenters like India Meteorological Departments in a specific location and using regression analysis, we can predict (numerical data) the values of damage. In this paper we mainly discuss about the various weather predictions models proposed by different researchers.