The impact of filtering self-organizing maps: A case study with australian pressure and rainfall

Abstract

This study presents a semi-objective set of criteria for filtering the time series of a self-organizing map (SOM, a method for collapsing a complex data set onto a series of typical instances/nodes). The purpose of the filter (or selection process) is to avoid the problem of associating anomalous time steps with SOM nodes that do not adequately describe that time step. The filter is based on measures of the match of the original field to the nearest SOM node. We demonstrate the method by using 21 years of MSLP reanalysis data for the Australian region from the European Centre for Medium Range Weather Forecasting product, ERA-Interim. We show that there are instances in which the SOM is incap..