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| Titel |
A comparison of predictors of the error of weather forecasts |
| VerfasserIn |
M. S. Roulston |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1023-5809
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| Digitales Dokument |
URL |
| Erschienen |
In: Nonlinear Processes in Geophysics ; 12, no. 6 ; Nr. 12, no. 6 (2005-12-20), S.1021-1032 |
| Datensatznummer |
250010904
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| Publikation (Nr.) |
 copernicus.org/npg-12-1021-2005.pdf |
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| Zusammenfassung |
Three different potential predictors of forecast error -
ensemble spread, mean errors of recent forecasts and the local
gradient of the predicted field - were compared. The comparison
was performed using the forecasts of 500hPa geopotential and
2-m temperature of the ECMWF ensemble prediction system at lead times
of 96, 168 and 240h, over North America for each day in 2004.
Ensemble spread was found to be the best overall predictor of
absolute forecast error. The mean absolute error of recent forecasts
(past 30 days) was found to contain some information, however, and
the local gradient of the geopotential also provided some information
about the error in the prediction of this variable.
Ensemble spatial error covariance and the mean spatial error covariance
of recent forecasts (past 30 days) were also compared as predictors
of actual spatial error covariance. Both were found to provide some
predictive information, although the ensemble error covariance was
found to provide substantially more information for both variables
tested at all three lead times.
The results of the study suggest that past errors and local
field gradients should not be ignored as predictors of forecast error
as they can be computed cheaply from single forecasts when an ensemble
is not available. Alternatively, in some cases, they could be used
to supplement the information about forecast error provided by an
ensemble to provide a better prediction of forecast skill. |
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