Abstract

Climate Change is a long-term change in the statistical distribution of weather patterns over periods of time that range from decades to millions of years. It may be a change in the average weather conditions or a change in the distribution of weather events with respect to an average, for example, greater or fewer extreme weather events. It is of keen interest to identify climatological behaviour to discover spatial relationships in climate variables, so that the trend of the climatic changes can be analyzed and studied. Data Mining is a technology that blends traditional data analysis methods with sophisticated algorithms for processing large volumes of data. It has also opened up exciting opportunities for exploring and analyzing new types of data and for analyzing old types of data in new ways. As Data Mining is an analytic process designed to explore data in search of consistent patterns and systematic relationships between variables and then to validate the findings by applying the detected patterns to new subsets of data, the present study has been conducted to apply various Data Mining techniques to the climatic data collected and to study the trend, pattern and finally to predict.