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    Comments on “Conditional Exceedance Probabilities” 

    Source: Monthly Weather Review:;2011:;volume( 139 ):;issue: 010:;page 3322
    Author(s): Bröcker, Jochen; Siegert, Stefan; Kantz, Holger
    Publisher: American Meteorological Society
    Abstract: n a recent paper, Mason et al. propose a reliability test of ensemble forecasts for a continuous, scalar verification. As noted in the paper, the test relies on a very specific interpretation of ensembles, namely, that the ...
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    Rank Histograms of Stratified Monte Carlo Ensembles 

    Source: Monthly Weather Review:;2012:;volume( 140 ):;issue: 005:;page 1558
    Author(s): Siegert, Stefan; Bröcker, Jochen; Kantz, Holger
    Publisher: American Meteorological Society
    Abstract: he application of forecast ensembles to probabilistic weather prediction has spurred considerable interest in their evaluation. Such ensembles are commonly interpreted as Monte Carlo ensembles meaning that the ensemble ...
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    Detecting Improvements in Forecast Correlation Skill: Statistical Testing and Power Analysis 

    Source: Monthly Weather Review:;2016:;volume( 145 ):;issue: 002:;page 437
    Author(s): Siegert, Stefan; Bellprat, Omar; Ménégoz, Martin; Stephenson, David B.; Doblas-Reyes, Francisco J.
    Publisher: American Meteorological Society
    Abstract: he skill of weather and climate forecast systems is often assessed by calculating the correlation coefficient between past forecasts and their verifying observations. Improvements in forecast skill can thus be quantified ...
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    A Bayesian Framework for Verification and Recalibration of Ensemble Forecasts: How Uncertain is NAO Predictability? 

    Source: Journal of Climate:;2015:;volume( 029 ):;issue: 003:;page 995
    Author(s): Siegert, Stefan; Stephenson, David B.; Sansom, Philip G.; Scaife, Adam A.; Eade, Rosie; Arribas, Alberto
    Publisher: American Meteorological Society
    Abstract: redictability estimates of ensemble prediction systems are uncertain because of limited numbers of past forecasts and observations. To account for such uncertainty, this paper proposes a Bayesian inferential framework that ...
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