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Titel |
Verification of a short-range ensemble precipitation prediction system over Iberia |
VerfasserIn |
D. Santos-Muñoz, M. L. Martin, A. Morata, F. Valero, A. Pascual |
Medientyp |
Artikel
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Sprache |
Englisch
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ISSN |
1680-7340
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Digitales Dokument |
URL |
Erschienen |
In: Precipitation: Measurement, Climatology, Remote Sensing, and Modeling (EGU Session 2009) ; Nr. 25 (2010-03-10), S.55-63 |
Datensatznummer |
250015737
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Publikation (Nr.) |
copernicus.org/adgeo-25-55-2010.pdf |
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Zusammenfassung |
The purpose of this paper is the verification of a
short-range ensemble prediction system (SREPS) built with five different
model physical process parameterization schemes and two different initial
conditions from global models, allowing to construct several versions of the
non-hydrostatic mesoscale MM5 model for a 1-month period of October 2006.
From the SREPS, flow-dependent probabilistic forecasts are provided by means
of predictive probability distributions over the Iberian Peninsula down to
10-km grid spacing. In order to carry out the verification, 25 km grid of
observational precipitation records over Spain from the Spanish Climatic
Network has been used to evaluate the ensemble accuracy together with the
mean model performance and forecast variability by means of comparisons
between such records and the ensemble forecasts. This verification has been
carried out upscaling the 10 km probabilistic forecast to the observational
data grid. Temporal evolution of precipitation forecasts for spatial
averaged ensemble members and the ensemble mean is shown, illustrating the
consistency of the SREPS. Such evolutions summarize the SREPS information,
showing each of the members as well as the ensemble mean evolutions. The
Talagrand diagram derived from the SREPS results shows underdispersion which
indicates some bias behaviour. The Relative Operating Characteristic (ROC)
curve shows a very outstanding area, indicating potential usefulness of the
forecasting system. The forecast probability and the mean observed frequency
present good agreement with the SREPS results close to the no-skill line.
Because the probability has a good reliability and a positive contribution
to the brier skill score, a positive value of this skill is obtained.
Moreover, the probabilistic meteogram of the spatial daily mean
precipitation values shows the range of forecast values, providing discrete
probability information in different quantile intervals. The epsgram shows
different daily distributions, indicating the predictability of each day. |
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