Implementation of data mining techniques for meteorological applications

The CrossGrid project is one of the ongoing research projects involving GRID technology. One of the main tasks in the Meteorological applications package is the implementation of data mining systems for the analysis of operational and reanalysis databases of atmospheric circulation patterns. Previous parallel data mining algorithms reported in the literature focus on parallel computers with predetermined resources (processing units) and high-performance communications. The main goal in this project is designing adaptive schemes for distributing data and computational load according to the changing resources available for each GRID job submitted. In this paper, some preliminary work regarding two different data mining algorithms (self organizing maps and smoothing filters) is presented. These techniques can be used in combination with databases of observations to provide downscaled local forecasts from operative model outputs. This is a more general and practical framework to look at data mining techniques from the meteorological point of view.