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Canadian Ensemble Forecasts (MSC)

Global ensemble forecasts are made twice a day using the canadian GEM model to generate potential weather scenarios up to 16 days. 20 "perturbed" weather forecasts are performed as well as an unperturbed 16-day control forecast. The 20 models have different physics parametrizations, data assimilation cycles and sets of perturbed observations.

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Spaghetti plots

In the spaghetti plots one can see both the position of a contour line and its uncertainty. We also show the standard deviation for the 500 hPa height (with the background colour). It may happen that the contour lines are far apart but that the gradients are not very important. In such a case, the forecasts may still be considered to be reliable.

Accumulated quantity of precipitation

First we show a contour plot of the ensemble mean forecast. On this plot we put small red numbers for the precipitation centres of the corresponding members. The verifying analysis is added on with the dashed red line. The next plots show the forecasts of the global GEM, control and the 20 ensemble members.

Sea level pressure centres

First we show a contour plot of the ensemble mean forecast. On this plot we put small red numbers for low centres and small blue numbers for high centres of the corresponding members. The verifying analysis is added on with the dashed red line. The next plots show the forecasts of the global GEM, control and the 20 ensemble members.

GZ 500 maps

First we show a contour plot of the ensemble mean forecast. On this plot we put small red numbers for low centres and small blue numbers for high centres of the corresponding members. The verifying analysis is added on with the dashed red line. The next plots show the forecasts of the global GEM, control and the 20 ensemble members.

Ensemble spread of trial fields

Every 6 hours, we compute the standard deviation, in Celsius, from the trial fields used in the assimilation cycles of the temperature at a level at approximately 5 km of altitude. Where the standard deviation of the trial fields is large, the incertitude is large. It is important to have good observations for these uncertain areas. One might target additional observations in such areas to try to diminish the uncertainty.

Information on the system

Digital data access

Access to ensemble data in digital format:

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