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Comparison of a single-model EPS with a multi-model ensemble consisting of a few operational models Cover

Comparison of a single-model EPS with a multi-model ensemble consisting of a few operational models

Open Access
|Jan 2000

Abstract

Since the introduction of operational ensemble forecasts in Numerical Weather Prediction(NWP) more than 5 years ago, the dispute on how to best determine the initial perturbationshas largely dominated the direction of research in the field of ensemble prediction. While it isimportant to consider uncertainties in the initial condition, errors due to model physics or themodel numerics and truncation provide another source of forecast errors and might also beconsidered in ensemble prediction. In this study, we compare the performance of 2 fundamentallydifferent ensemble schemes. First, the ensemble prediction system (EPS) of the European Centrefor Medium Range Forecasts is taken as a representative of the single-model approach basedon the perfect model assumption and thus taking only the uncertainty in the observations intoaccount. Second, a virtual ensemble comprised of the operational forecasts of 4 NWP centersas a “gratis” candidate of the multi-model approach which, in addition, takes model errors intoaccount. The comparison is based on forecasts of 500 hPa fields over Europe for a summer anda winter period in 1997 and on diagnostics ranging from various measures for the performanceof the ensemble means to the statistical consistency and discrimination properties of theensembles. The different sizes of both ensembles poses the main difficulty for the interpretationof the results. If the ensemble size is not considered as a criterion for the evaluation, the resultslead to controversial conclusions; but when penalizing for an overly large and inefficientensemble the results are for the most part consistent, and one has to conclude that the multimodelensemble performs better in most forecast aspects.

Language: English
Page range: 280 - 299
Submitted on: Dec 23, 1998
Accepted on: Dec 16, 1999
Published on: Jan 1, 2000
Published by: Stockholm University Press
In partnership with: Paradigm Publishing Services

© 2000 Christine Ziehmann, published by Stockholm University Press
This work is licensed under the Creative Commons Attribution 4.0 License.