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Many variables of interest, such as air pollutants and meteorological parameters, often exhibit complex spatial and temporal variabilities. In particular, these variables contain many temporal scales that are non-periodic and non-stationary, challenging proper quantitative characterization and visualization. The EOF-EEMD analysis-visualization package we complied aims to evaluate the spatiotemporal variability across scales, which can be periodic/stationary or not. As shown in the figure below, the package consists, in order, of an EOF analysis (Lorenz, 1956), an EEMD analysis (Wu et al., 2009), a Hilbert-Huang Transform (HT) with Marginal Spectrum Analysis (MSA), and a visualization step to quantitatively depict the spatial-temporal scales of measurement or model data.
See here (including user guide, a full IDL version, and a partial MATLAB version)
Note that parts of the codes are adopted from Zhaohua Wu in MATLAB, and parts are modified from Jinxuan Chen and May Fu's codes. See user guide for detailed credit descriptions.
v. 4.14
