Neural-dynamical hybrid coupled model forecasts of the tropical Pacific sea surface temperatures

Youmin Tang and William Hsieh


The forecast model is the neural-dynamical hybrid coupled model used in our previous forecasts (Tang and Hsieh 2001a), but NCEP sea level height anomaly (SLHA) data (instead of the heat content anomaly data) are assimilated to initiate the forecasts, as the NCEP SLHA data are updated more regularly. Assimilating NCEP SLHA yields similar improvement to forecast skills as assimilating heat content anomalies (Tang and Hsieh 2001b). Fig. 1 shows the correlation skills of the predicted sea surface temperature anomalies (SSTA) in the NINO3 region in the equatorial eastern Pacific during 1990-1999 using our model with SLHA assimilation. The predictions were made at three months intervals (starting on 1 January, 1 April, 1 July and 1 October) and continued until a lead time of 15 months.

Fig.1 Correlation skills of predicted NINO3 SSTA



Fig. 2 shows the prediction of the NINO3 SSTA starting from 1994 to 2001 at lead times of 6 months and 12 months.

Fig.2 Observed and predicted NINO3 SSTA at lead times of 6 and 12 months


Fig 3 shows our latest forecasts (initialized using data till the end of July, 2001), indicating that the slightly cool conditions in the equatorial Pacific during winter, 2001 will intensify by spring, 2002, turning into a La Nina by summer, 2002.

Fig.3 Predicted SSTA of the tropical Pacific


Contour intervals are 0.5 degree Celsius, with positive anomalies indicated by solid contours, negative anomalies by dashed contours, and zero by thick contours. Positive anomalies above 1 degree are shaded in red, negative anomalies below -1 degree are in blue, and the zero contour is in purple.


References:

  • Tang, Y. and W.W. Hsieh, 2001a: Neural-dynamical hybrid coupled model forecasts of the tropical Pacific sea surface temperatures. Experimental Long-Lead Forecast Bulletin, 10(1):1-4.


  • Tang, Y. and W. W. Hsieh, 2001b: Impact of data assimilation on ENSO simulations and predictions in a hybrid coupled model framework. J. of Climate (submitted). [http://www.ocgy.ubc.ca/~tym/papers.html]


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