Abstract
The field of sonification is a subset of auditory display. It brings together interests from data mining, exploratory data analysis, humancomputer interface and musical interfaces. Sonification is the mapping of data to sound; it is a rich and relatively unexplored technique for data mining. The idea behind sonification is that nonverbal sounds can be used to represent numerical data and provide support for information processing activities of many different kinds. In this paper we present three quantification rules for using sonification in data mining. We also present an RPAI (Rain Prediction Auditory Icon) Algorithm to predict rain using auditory icon. This integrates two new areas of research i.e. sonyication and climate data mining. Weather data mining (forecasting) gained a lot of interest in last couple of years due to its large applications on Water, Agriculture, Energy, Health and Retail Market. The use of climate data mining is new and is in its infancy stages of being used for a variety of businesses. This creates the opportunity to explore enhancements to decision strategies through a suite of research analysis and tool development. We perform experiments using RPAI algorithm on rain data from a metrological site and discuss the results.