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 circulation, and the subsequent Canadian surface temperature and precipitation have been developed. Here, we present the forecasts for Apr-June 1998 using the predictor fields through March 1998. This is a 3-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 3 month period of Apr-June 1998 expressed as standardized anomaly. Table 1 shows the value of standard deviation in °C at selected stations. The mean skill over all 51 stations is given in the caption beneath each forecast map. The field significance is also shown, reflecting the probability of randomly obtaining overall map skill equal to higher than that which actually occurred. Field significance is evaluated using a Monte Carlo procedure in which the forecast versus observation correspondences are shuffled randomly 1000 times. The field of cross-validated historical skill (correlation) for the forecast time period is shown in Figure 2. The forecast has a modest expected skill: a mean national score of 0.20 and a field significance of 0.082. The skill of the temperature forecast is the highest in winter and somewhat lower in spring in Canada. Local skill are highest throughout western Canada and Ontario. A large area of central Canada from the Northwest Territories through Ontario is expected to have negative temperature anomaly; positive temperature anomalies are forecast over western Canada and over most of eastern Canada.

Figure 3 shows the CCA-based precipitation forecast for the 3 month period of Apr-June 1998 expressed as standardized anomaly. Table 1 shows the value of standard deviation (in millimetres) at a selected few stations. Cross-validated historical skill (correlation) for this time period is shown in Figure 4. The forecast has a very modest expected skill: a mean national score of 0.13 and a field significance of 0.053. Local skills are rather low throughout most of Canada. Areas between the Rocky Mountains and the upper Great Lakes are expected to have a deficit in Apr-June precipitation Southern British Columbia and Atlantic Canada are expected to have above normal precipitation.

Both atmospheric and oceanic indices have been showing a strong warm phase of ENSO for several months. Most statistical and dynamical models are predicting the current warm ENSO episode to weaken considerably during late spring and early summer 1998. Analysis of past moderate to strong episodes show a tendency for milder than normal conditions to persist through the early spring season in western Canada and then weaken in early summer. The Apr-June 1998 forecast recognizes the waning influence of the warm El Nino episode on the Canadian climate over the forecast period.

Table 1. Standard deviation of temperature (Temp) and precipitation (Prcp) for the 3 month period April through June at selected Canadian stations.

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. 

Fig. 1. CCA-based temperature forecast for the 3 month mean period of Apr-May-June 1998. 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 0.20. Field significance is 0.082.

Fig. 3. CCA-based precipitation forecast for the 3 month mean period of Apr-May-June 1998. 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 0.13. Field significance is 0.053.