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This “regression to the mean”
effect gives rise to
another type of false systematic error. Forecasts produced and
verified over a period characterized by on average anomalous
weather will display a false impression of a model climate drift. A
perfect model will produce natural looking anomalies, independent
of lead time, but since the initial state is already anomalous, the
forecasts are, with decreasing skill, more likely to be less
anomalous than even more anomalous. At a range where there is no
longer any predictive skill, the mean error will be equal to the
observed mean anomaly with the opposite sign (see Figure
64).
Figure
64: A sequence of consecutive NWP
forecasts (thin black lines, their mean (thick black line) and the
observations (red line). Forecasts starting in an anomalous state
are less likely to forecast even more extreme conditions. With
increasing lead time and decreasing skill the forecasts will tend
to cluster increasingly around the climate average and give an
impression of increasing ME. The mean error will therefore give the
false impression of a drift in the model climate.
The ME can be trusted to reflect the
properties of the model’s performance only during periods
with no or small average anomalies.
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