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Comparison of deterministic forecasts generated by computer models and manual methods
Forecasts from NWP models and human forecasters cannot really be compared, because they have different aims:
- NWP modellers try to provide forecast systems with optimum accuracy. Their aim is to model all scales of atmospheric motions, irrespective of whether they are predictable or not. (see Fig6.3-1).
- Weather forecasters do the opposite. They disregard and dampen down unpredictable features in order to improve accuracy and reduce jumpiness in their categorical forecasts (see Fig6.3-2).
Fig6.3-1: Typical root mean square error and variability of good (blue) and poor (red) high-resolution NWP models.
A good NWP model represents the whole spectrum of resolvable atmospheric scales throughout the forecast. Thus errors trend towards a higher level but variability remains fairly constant....
If the reduction in categorical forecast errors occurs:
- duringthe forecast integration, due to deficiencies in the NWP model, then this is "Bad". This is because the whole spectrum of resolvable atmospheric scales has not been captured.
- after the forecast integration, by some subjective or objective post-processing of the NWP output, then it is “Good”. This is because experience allows less likely features to be removed.
Any “competition” between NWP modellers and forecasters has no relevance outside the meteorological community. The usefulness of a forecast depends upon both the NWP forecast and human interpretation.
(FUG Associated with Cy49r1)
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