Soft Computing Techniques for Weather and Climate Change Studies

The Weather is a continuous, data-intensive, multidimensional, dynamic process that makes weather forecasting a formidable challenge. Weather forecasting involves predicting how the present state of the atmosphere will change. Climate is the long-term effect of the sun's radiation on the rotating earth's varied surface and atmosphere. The Day-byday variations in a given area constitute the weather, whereas climate is the long-term synthesis of such variations. A simple, long-term summary of weather changes, however, is still not a true picture of climate. To obtain this requires the analysis of daily, monthly, and yearly patterns. This paper presents the use of Self Organizing Maps (SOM) and CoActive Neuro Fuzzy Inference System (CANFIS) soft computing techniques for weather and climate change studies using historical data collected from the city of Ibadan, Nigeria between 1951 and 2009. The results show that the soft computing techniques can be used for knowledge discovery in weather prediction and climate change studies.