From June to September of every year India come under heavy rainfall often talked about as the Indian summer monsoon. During this time about 90% of the yearly precipitation falls on central India with over 250mm of rain on average falling per month. It is no surprise that this rain is accompanied by the scientifically named “severe thunderstorms.” In the pre-monsoon months these thunderstorms act as a herald bringing thunder, lightening and devastating tornadoes which spread havoc and are rarely predicted with accuracy. Weather of this type is caused by convection currents which are in turn caused by the heating of the land. The swift urbanisation changing farmland to concrete can have acute effects on rainfall and related features.
It has always been assumed, due to the nature of the monsoon, that only conditions spread on a large scale could have any effect on the storms and so only the land state was used to create models to predict when they would come. This study has aimed to improve the weather forecasts by predicting the extreme convention generated in small areas in the Indian monsoon region based on data gathered about the local soil moisture and temperature. By gathering large amounts of high resolution information further predictions could then be made about the surface moisture in different areas which were fount to be about 90% accurate when the moisture was actually taken. With this model verified it can be used as a precursor to the actual storm predictions by predicting the important moisture information. Knowing this made the estimations of air humidity, temperature and wind speed more accurate also which then can be used to see when a storm is likely to develop. By taking real life cases it becomes clear that the surface characteristics of the land in the Indian monsoon zone are important features determine local and large scale convection and so through our understanding of these features we gain a greater ability to foresee and mitigate the negative effects.