Forecast of Tropical Pacific SST Using a Markov Model

contributed by Yan Xue

¹ Climate Prediction Center, National Centers for Environmental Prediction, NOAA, Camp Springs, MD

Forecasts of the tropical Pacific SST anomaly are presented here using a linear statistical model (Markov model). The Markov model is constructed in a reduced multivariate EOF space of observed sea surface temperature (SST), surface wind stress and sea level analysis (Xue et al. 2000). The model is trained for 1980-95 and verified for 1964-79.

The SST from 1964 to 1981 is the reconstruction of historical SST by Smith et al. (1996) and the SST from 1982 to present is the SST analysis by Reynolds and Smith (1994); the surface wind stress is the FSU pseudo wind stress product (Goldenberg and O'Brien 1981); the sea level from 1964 to 1979 is from a model simulation which uses the GFDL MOM1 model forced by the FSU winds and the sea level from 1980 to present is from the ocean analysis at NCEP (Behringer et al. 1998). All the data are monthly values and cover the tropical Pacific region within 20^O of the equator.

The Markov model is built with three multivariate EOFs in which the anomalous fields of SST, wind stress and sea level are equally weighted. The model contains 12 monthly transition matrices. The cross-validated skill for 1980-95 and hindcast skill for 1964-79 have been published in the issue of September 1998 of the Experimental Long-Lead Forecast Bulletin.

SST anomalies were calculated as departures from the 1950-79 adjusted OI climatology (Reynolds and Smith 1995). Fig. 1 shows the time evolution of NINO3.4 forecasts up to 12 month leads by the Markov model initiated monthly from January 1998 to November 2002. The recent predictions initiated from September 2002 to November 2002 are quite consistent, indicating the current El Nino peaks around January 2003, and then decays slowly in spring. It is likely that warm SST anomalies of about 1 degree remains in the central Pacific during summer 2003 (Fig. 1). The seasonal mean SST anomalies from the latest prediction initiated from November 2002 are shown in Fig. 2.

A monthly update of the Markov model forecast is accessible at ftp://ftpprd.ncep.noaa.gov/pub/cpc/wd52yx/web/ENSO_forecast.html.

References:

Behringer, D. W., M. Ji and A. Leetmaa, 1998: An improved coupled model for ENSO prediction and implications for ocean initialization. Part I: The ocean data assimilation system. Mon. Wea. Rev., 126, 1013-1021.

Goldenberg, S. B. and O'Brien, J. J., 1981: Time and space variability of tropical Pacific wind stress. Mon. Wea. Rev., 109, 1190-1207.

Reynolds, R. W., and T. M. Smith, 1994: Improved global sea surface temperature analyses using optimum interpolation. J. Climate, 7, 929-948.

Reynolds, R. W. and T. M. Smith, 1995: A high resolution global sea surface temperature climatology. J. Climate, 8, 1571-1583.

Smith, T. M., R. W. Reynolds, R. E. Livezey, and D. C. Stokes, 1996: Reconstruction of historical sea surface temperatures using empirical orthogonal functions. J. Climate, 9, 1403-1420.

Xue, Y., A. Leetmaa and M. Ji, 2000: ENSO predictions with Markov models: the impact of sea level. J. Climate, 13, 849-871.