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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 Fig63Fig6.A3-1).
- 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 Fig63Fig6.B3-2).
Fig63Fig6.A3-1: 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.A poor NWP model suffers from a gradual reduction of atmospheric scales through the forecast (due to excessive diffusion or coarse numerical resolution). Thus errors trend towards those of a forecast using climate alone and the variability decreases.
Fig63Fig6.B3-2: Typical root mean square error and variability of experienced (blue) and naïve (red) forecast practices:
An experienced forecaster or process (blue) disregards or damps less likely synoptic features. Thus errors tend towards those of a forecast using climate alone and variability reduces. This is because the less predictable scales are gradually removed....
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