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Canadian ensemble forecasts
The daily ensemble forecasts have been available operationnally since January 24, 1996. They were originally performed with eight members. As of August 24, 1999, eight more members were added creating a 16-member ensemble forecast system. On January 12, 2005, the Optimal Interpolation Technique for the analysis cycle was replaced with the Ensemble Kalman Filter Technique. Starting in July 2007, four more members were added to produce a 20-member ensemble.
Twice a day 20 "perturbed" 16-day weather forecasts are performed as well as an unperturbed 16-day control forecast. The 20 perturbed forecasts and the control forecast are performed with the GEM model. The 20 models have different physics parametrizations, data assimilation cycles and sets of perturbed observations.
10 day mean temperature anomaly
View the forecast of the normalised mean temperature anomaly for the next 10 days. The forecast starts at 00Z of the day indicated in the figure. The anomaly is with respect to the climatological mean temperature. The forecast was obtained by applying a regression equation to the ensemble mean 1000-500 hPa thickness. The contours are 0.43 multiples of the standard deviation.
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.
Calibrated probability of equivalent precipitation
In these figures we show the probabilities that the accumulated amount of (melted or liquid) precipitation in a 12 hour period exceeds thresholds of 2, 5, 10 or 25mm. Raw probability intervals are at less than 22 % (at most 4 members are above the threshold), between 22 and 47 % (5 to 9 members above the threshold), between 47 and 72 % (10 to 14 members above the threshold) or more than 72 % (15 to 20 members above the threshold).
We performed a calibration of our precipitation forecasts. This allowed us to replace the raw probabilities of 22, 47 and 72 % by calibrated values.
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 96 trial fields used in the assimilation cycles of the temperature at eta level 5020 (approximately an altitude of 5 km). 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 to such areas to try to diminish the uncertainty. On the map below, the mean of the 96 trial fields is shown by black solid lines at every 5 degrees Celsius. The standard deviation of the trial fields around the mean is displayed in colour on the same chart. View.
