A Time-series based Prediction Analysis of Rainfall Detection

Nowadays climate change is a reality that brings fearful tragic events across the globe. Latitude, Altitude, pressure and wind systems, distance from sea, ocean currents and relief features are the factors affecting the climate of any place. Atmosphere and earth’s surface is getting warmer. Changing rainfall patterns, unusual and unprecedented spells of hot weather are the most important impacts of climate change. Indian climate is mainly described as tropical monsoon with 4 seasons. They are winter, hot weather summer, Rainy south western monsoon, post - monsoon or north east monsoon. Data mining, data analysis can be used on meteorological data to find hidden patterns inside the data. Here the monthly rainfall data of 14 districts of Kerala form year 2008 to 2019 is taken into consideration. The data is classified as seasons consisting of 4 quarters. The purpose of this classification and analysis, is to find the climatic variations of districts that affect the Hevea (Rubber) cultivation. Hevea brasiliensis, the rubber tree is considered as the main source of Natural Rubber (NR) which is the most versatile raw material of nature, having multifarious uses .Meteorological factors and soil fertility are the critical factors that influence the growth of Hevea. Among the meteorological factors, rainfall plays an important role in the growth, and also influences the production. So this paper analyze and study the rainfall data patters of all the districts of Kerala. Here a time series analysis is used to extract the trends in seasonal rainfall and its effect is analyzed. A time series forecasting is used to predict the future rainfall from 2020 to 2030 of all districts of Kerala.