Diffusion maps for the description of meteorological data

Abstract

Diffusion Maps is a new powerful technique for dimensionality reduction that can capture geometric structure while taking into account data distribution. In this work we will apply it to time and spatial compression of numerical weather forecasts, showing how it is capable to greatly reduce the initial dimension while still capturing relevant information in the original data. © 2012 Springer-Verlag.