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摘要
The use of kilometre-scale ensembles in operational weather forecasting provides new challenges for forecast interpretation and evaluation to account for uncertainty on the convective scale. A new neighbourhood-based method is presented for evaluating and characterizing the local predictability variations from convective-scale ensembles. Spatial scales over which ensemble forecasts agree (agreement scales, S-A) are calculated at each grid point ij, providing a map of the spatial agreement between forecasts. By comparing the average agreement scale obtained from ensemble member pairs (S-ij(A((mm) over bar))) with that between members and radar observations (S-ij(A((mo) over bar))), this approach allows the location-dependent spatial spread-skill relationship of the ensemble to be assessed. The properties of the agreement scales are demonstrated using an idealized experiment. To demonstrate the methods in an operational context, S-ij(A((mm) over bar)) and S-ij(A((mo) over bar)) are calculated for six convective cases run with the Met Office UK Ensemble Prediction System (MOGREPS-UK). S-ij(A((mm) over bar)) highlights predictability differences between cases, which can be linked to physical processes. Maps of S-ij(A((mm) over bar)) are found to summarize the spatial predictability in a compact and physically meaningful manner that is useful for forecasting and model interpretation. Comparison of S-ij(A((mm) over bar)) and S(ij)(A((mo) over bar))demonstrates the case-by-case and temporal variability of the spatial spread-skill, which can again be linked to physical processes.
- 出版日期2016-7
