Articles | Volume 17
https://doi.org/10.5194/asr-17-39-2020
https://doi.org/10.5194/asr-17-39-2020
03 Jun 2020
 | 03 Jun 2020

A possibilistic interpretation of ensemble forecasts: experiments on the imperfect Lorenz 96 system

Noémie Le Carrer and Peter L. Green

Cited articles

Allen, S., Ferro, C. A., and Kwasniok, F.: Regime-dependent statistical post-processing of ensemble forecasts, Q. J. Roy. Meteor. Soc., 145, 3535–3552, 2019. a
Berger, J. O. and Smith, L. A.: On the statistical formalism of uncertainty quantification, Annu. Rev. Stat. Appl., 6, 433–460, 2019. a
Bröcker, J. and Smith, L. A.: Increasing the reliability of reliability diagrams, Weather Forecast., 22, 651–661, 2007. a
Bröcker, J. and Smith, L. A.: From ensemble forecasts to predictive distribution functions, Tellus A, 60, 663–678, 2008. a, b, c
Buizza, R.: Ensemble forecasting and the need for calibration, in: Statistical Postprocessing of Ensemble Forecasts, Elsevier, 15–48, 2018. a
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Short summary
Ensemble forecasting has gained popularity as a means of handling the limitations inherent to predicting the behavior of high dimensional systems with strong sensitivity to initial conditions. Initial conditions are sampled and propagated through the model equations, leading to a set of predictions. So far, this set has been interpreted in a probabilistic way. Here, we question this choice and show that possibility theory may be a sounder approach, especially in the case of extreme events.