Discovering knowledge from low-quality meterological databases

Meteorological societies and universities worldwide frequently collect vast amounts of data from satellites and weather stations. Given a collection of datasets, we were asked to examine a sample of such data and look for patterns which may exist between certain geographical locations over time. The overall aim of the work is to generate a set of rules which can be used to predict certain grid squares a number of months in advance; these predictions can be used by meteorologists to make mid-long-term forecasts.