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Titel |
Reliability of autoregressive error models as post-processors for probabilistic streamflow forecasts |
VerfasserIn |
M. Morawietz, C.-Y. Xu, L. Gottschalk |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1680-7340
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Digitales Dokument |
URL |
Erschienen |
In: Towards practical applications in ensemble hydro-meteorological forecasting ; Nr. 29 (2011-04-27), S.109-118 |
Datensatznummer |
250016941
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Publikation (Nr.) |
copernicus.org/adgeo-29-109-2011.pdf |
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Zusammenfassung |
In this study, the reliability of different versions of autoregressive error
models as post-processors for probabilistic streamflow forecasts is
evaluated. Rank histograms and reliability indices are used as performance
measures. An algorithm for the construction of confidence intervals to
indicate ranges of reliable forecasts within the rank histograms is
presented. To analyse differences in performance of the post-processors,
scatter plots of the standardized residuals of the error models are
generated to assess the homoscedacity of the residuals with respect to
streamflow. A problem of distorted impressions may appear when such plots
are generated with a regular x-scale. The problem is analysed with both
synthetic and real data, and a rank scaled x-axis is proposed to remedy the
problem. The results of the study reveal large differences in the
reliability of the post-processors. Versions with empirical distribution
functions are clearly superior to those with standard normal distribution,
but for validations with independent data their rank histograms still lie
outside of the confidence bands for reliable forecasts. |
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