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    Reading: Predictive verification for the design of partially exchangeable multi-model ensembles

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    Original Research Papers

    Predictive verification for the design of partially exchangeable multi-model ensembles

    Authors:

    Zied Ben Bouallégue ,

    The European Centre for Medium-Range Weather Forecasts, ECMWF, GB
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    Christopher A. T. Ferro,

    Department of Mathematics, University of Exeter, GB
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    Martin Leutbecher,

    The European Centre for Medium-Range Weather Forecasts, ECMWF, GB
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    David S. Richardson

    The European Centre for Medium-Range Weather Forecasts, ECMWF, GB
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    Abstract

    The performance of an ensemble forecast, as measured by scoring rules, depends on its number of members. Under the assumption of ensemble member exchangeability, ensemble-adjusted scores provide unbiased estimates of the ensemble-size effect. In this study, the concept of ensemble-adjusted scores is revisited and exploited in the general context of multi-model ensemble forecasting. In particular, an ensemble-size adjustment is proposed for the continuous ranked probability score in a multi-model ensemble setting. The method requires that the ensemble forecasts satisfy generalised multi-model exchangeability conditions. These conditions do not require the models themselves to be exchangeable. The adjusted scores are tested here on a dual-resolution ensemble, an ensemble which combines members drawn from the same numerical model but run at two different grid resolutions. It is shown that performance of different ensemble combinations can be robustly estimated based on a small subset of members from each model. At no additional cost, the ensemble-size effect is investigated not only considering the pooling of potential extra-members but also including the impact of optimal weighting strategies. With simple and efficient tools, the proposed methodology paves the way for predictive verification of multi-model ensemble forecasts; the derived statistics can provide guidance for the design of future operational ensemble configurations without having to run additional ensemble forecast experiments for all the potential configurations.

    Keywords: Multi-model ensemble, ensemble size, optimal weighting, predictive verification
    How to Cite: Ben Bouallégue, Z., Ferro, C.A.T., Leutbecher, M. and Richardson, D.S., 2020. Predictive verification for the design of partially exchangeable multi-model ensembles. Tellus A: Dynamic Meteorology and Oceanography, 72(1), p.1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165
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      Published on 01 Jan 2020
    Peer Reviewed
     CC BY 4.0

    Ben Bouallégue, Z., Ferro, C.A.T., Leutbecher, M. and Richardson, D.S., 2020. Predictive verification for the design of partially exchangeable multi-model ensembles. Tellus A: Dynamic Meteorology and Oceanography, 72(1), p.1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue Z, Ferro CAT, Leutbecher M, Richardson DS. Predictive verification for the design of partially exchangeable multi-model ensembles. Tellus A: Dynamic Meteorology and Oceanography. 2020;72(1):1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue, Z., Ferro, C. A. T., Leutbecher, M., & Richardson, D. S. (2020). Predictive verification for the design of partially exchangeable multi-model ensembles. Tellus A: Dynamic Meteorology and Oceanography, 72(1), 1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    1. Ben Bouallégue Z, Ferro CAT, Leutbecher M, Richardson DS. Predictive verification for the design of partially exchangeable multi-model ensembles. Tellus A: Dynamic Meteorology and Oceanography. 2020;72(1):1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue Z and others, ‘Predictive Verification for the Design of Partially Exchangeable Multi-model Ensembles’ (2020) 72 Tellus A: Dynamic Meteorology and Oceanography 1697165 DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue, Zied, Christopher A. T. Ferro, Martin Leutbecher, and David S. Richardson. 2020. “Predictive Verification for the Design of Partially Exchangeable Multi-model Ensembles”. Tellus A: Dynamic Meteorology and Oceanography 72 (1): 1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue, Zied, Christopher A. T. Ferro, Martin Leutbecher, and David S. Richardson. “Predictive Verification for the Design of Partially Exchangeable Multi-model Ensembles”. Tellus A: Dynamic Meteorology and Oceanography 72, no. 1 (2020): 1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

    Ben Bouallégue, Z, et al.. “Predictive verification for the design of partially exchangeable multi-model ensembles”. Tellus A: Dynamic Meteorology and Oceanography, vol. 72, no. 1, 2020, p. 1697165. DOI: http://doi.org/10.1080/16000870.2019.1697165

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