A hierarchy of data-based ENSO models

@inproceedings{Kondrashov2004AHO,
  title={A hierarchy of data-based ENSO models},
  author={Dmitri Kondrashov and Sergey Kravtsov and Andrew W Robertson and Michael Ghil},
  year={2004}
}
Global sea-surface temperature (SST) evolution is analyzed by constructing predictive models that best describe the data set’s statistics, assuming that the system’s variability is driven by spatially coherent, additive noise that is white in time. The inverse models are constructed in the phase space of the data set’s leading empirical orthogonal functions. Multiple linear regression has been widely used to obtain inverse stochastic models; it is generalized here in two ways. First, the… CONTINUE READING
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