Analyzing state-dependent model–data comparison in multi-regime systems
Analyzing state-dependent model–data comparison in multi-regime systems
Date
2011-01-07
Authors
Aretxabaleta, Alfredo L.
Smith, Keston W.
Smith, Keston W.
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Keywords
Skill assessment
Data clustering
Gaussian Mixture Models
ENSO
Data clustering
Gaussian Mixture Models
ENSO
Abstract
An approach to analyze regime change in spatial time series data sets is
followed and extended to jointly analyze a dynamical model depicting regime shift
and observational data informing the same process. We analyze changes in the joint
model-data regime and covariability within each regime. The method is applied to two
observational data sets of equatorial sea surface temperature (TAO/TRITON array and
satellite) and compared with the predicted data by the ECCO-JPL modeling system.
Description
Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of Springer for personal use, not for redistribution. The definitive version was published in Computational Geosciences 15 (2011): 627-636, doi:10.1007/s10596-011-9229-3.