CPC Markov Model   Statistical Model

NOAA Climate Prediction Center
Camp Springs, Maryland, U.S.

A seasonally varying linear Markov model is built in a reduced multiple empirical orthogonal function (MEOF) space of the sea surface temperature anomaly, sea level and wind stress anomaly fields for 1980-1995. The Markov model operates through 12 monthly dependent and predetermined transition matrices built in the MEOF space.

Details can be found in Xue et al. 2000, and on Dr. Xue's personal web page housed at CPC.

Contact: Dr. Yan Xue: yan.xue@noaa.gov

References:
Xue, Y., A. Leetmaa, and M. Ji, 2000: ENSO prediction with Markov models: The impact of sea level. J. Climate, 13, 849-871.
Xue, Y., M. A. Cane, S. E. Zebiak, and B. Blumenthal, 1994: On the prediction of ENSO: a study with a low-order Markov model. Tellus, 46A, 512-528.