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Abstract:
A new method for assessing forecast skill and predictability that
involves the identification and tracking of extratropical cyclones has
been developed and implemented to obtain detailed information about the
prediction of cyclones that cannot be obtained from more conventional
analysis methodologies. The cyclones were identified and tracked along
the forecast trajectories, and statistics were generated to determine
the rate at which the position and intensity of the forecasted storms
diverge from the analyzed tracks as a function of forecast lead time.
The results show a higher level of skill in predicting the position of
extratropical cyclones than the intensity. They also show that there is
potential to improve the skill in predicting the position by 1 - 1.5
days and the intensity by 2 - 3 days, via improvements to the forecast
model. Further analysis shows that forecasted storms move at a slower
speed than analyzed storms on average and that there is a larger error
in the predicted amplitudes of intense storms than the weaker storms.
The results also show that some storms can be predicted up to 3 days
before they are identified as an 850-hPa vorticity center in the
analyses. In general, the results show a higher level of skill in the
Northern Hemisphere (NH) than the Southern Hemisphere (SH); however, the
rapid growth of NH winter storms is not very well predicted. The impact
that observations of different types have on the prediction of the
extratropical cyclones has also been explored, using forecasts
integrated from analyses that were constructed from reduced observing
systems. A terrestrial, satellite, and surface-based system were
investigated and the results showed that the predictive skill of the
terrestrial system was superior to the satellite system in the NH.
Further analysis showed that the satellite system was not very good at
predicting the growth of the storms. In the SH the terrestrial system
has significantly less skill than the satellite system, highlighting the
dominance of satellite observations in this hemisphere. The surface
system has very poor predictive skill in both hemispheres.
