In the last several issues of this Bulletin, forecasts of Canadian temperature and precipitation using the multivariate statistical technique of canonical correlation analysis (CCA) were presented. For Canada, predictive relationships between evolving large scale patterns of quasi-global sea surface temperature, Northern Hemisphere 500 mb, and the subsequent Canadian surface temperature and precipitation have been developed. Here, we present the forecasts for Dec-Jan-Feb 1999 using the predictor fields through May 1998. This is a 9-month lead forecast. More details about the Canadian CCA-based seasonal climate prediction can be found in Shabbar (1996a, 1996b) and Shabbar and Barnston (1996).

Figure 1 shows the CCA-based temperature forecast for the Dec-Jan-Feb 1999 period expressed as a standardized anomaly. Table 1 shows the value of the standard deviation in ^oC at selected stations. The field of cross-validated historical skill (correlation) for the Dec-Jan-Feb forecast time period at this lead is shown in Fig. 2. The forecast has a modest expected skill - a mean national score of 0.25. The field significance is 0.016, which surpasses the traditional 0.05 rejection cutoff. Field significance reflects the probability of randomly obtaining an overall map skill equal to or higher than that which actually occurred. It is evaluated using a Monte Carlo procedure in which the forecast versus observation correspondences are shuffled randomly 1000 times. The skill of the temperature forecast is highest in winter even at the 9-month lead time. Local skill is highest from southern prairies through central and northern Ontario into central Quebec, and over extreme northwestern Arctic Islands. A large area of central and eastern Canada from Saskatchewan to Atlantic Canada is expected to have negative temperature anomaly; positive temperature anomalies are forecast over northwestern Canada, whereas Alberta and British Columbia are expected to have near normal temperatures.

Figure 3 shows the CCA-based precipitation forecast for the Dec-Jan-Feb 1999 period, expressed as a standardized anomaly. Table 1 shows the value of the standard deviation (in millimeters) at a selected few stations. The spatial field of cross-validated historical skill (correlation) for this lead and time period is shown in Fig. 4. The forecast has a rather modest expected skill: a mean national score of 0.18 and a field significance of 0.025. Local skill is low throughout most of Canada except over southern prairies and northwestern Arctic Islands. Areas north of the upper Great Lakes are expected to have above normal precipitation, and this is in keeping with the expectation of La Niña conditions.

Both atmospheric and oceanic indices have been showing rapidly decaying stages of the warm phase of ENSO for several weeks now. Most of the statistical and dynamical models are predicting the warm ENSO episode which just ended to switch to a cold phase of ENSO by the winter of 1998-99. The Dec-Jan-Feb 1998-99 forecast recognizes the emergence of the La Niña episode and its influence on the Canadian climate over the forecast period.

References:

Shabbar, A., 1996a: Seasonal prediction of Canadian surface temperature and precipitation by canonical correlation analysis. Proceedings of the 20th Annual Climate Diagnostic Workshop, Seattle, Washington, Oct. 23-27, 1995, 421-424. 

Shabbar, A., 1996b: Seasonal forecast of Canadian surface temperature by canonical correlation analysis. 13th Conference on Probability and Statistics in Atmospheric Sciences. American Meteorological Society, San Francisco, California, Feb. 21-23, 339-342.

Shabbar, A. and A. G. Barnston, 1996: Skill of seasonal climate forecasts in Canada using canonical correlation analysis. Mon. Wea. Rev., 124, 2370-2385.

Figure Captions: 

Fig. 1. CCA-based temperature forecast for the 3 month mean period of Dec-Jan-Feb 1999. Forecasts are represented as standardized anomalies.

Fig. 2. Geographical distribution of cross-validated historical skill for the forecast shown in Fig. 1, calculated as temporal correlation coefficient between forecasts and observations. Areas having forecast skill of 0.30 or higher are considered to have utility. The mean score over 51 stations is 0.25. Field significance is 0.016.

Fig. 3. CCA-based precipitation forecast for the 3 month mean period of Dec-Jan-Feb 1999. Forecasts are represented as standardized anomalies.

Fig. 4. Geographical distribution of cross-validated historical skill for the forecast shown in Fig. 1, calculated as temporal correlation coefficient between forecasts and observations. Areas having forecast skill of 0.30 or higher are considered to have utility. The mean score over 69 stations is 0.18. Field significance is 0.025.