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Nonlinear Processes in Geophysics An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/npg-2019-50
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/npg-2019-50
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 10 Oct 2019

Submitted as: research article | 10 Oct 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Nonlinear Processes in Geophysics (NPG).

Seasonal statistical-dynamical prediction of the North Atlantic Oscillation by probabilistic post-processing

André Düsterhus1,2 André Düsterhus
  • 1Institute of Oceanography, Center for Earth System Research and Sustainability (CEN), Universität Hamburg, Germany
  • 2ICARUS, Department of Geography, Maynooth University, Ireland

Abstract. Dynamical models of various centres have shown in recent years seasonal prediction skill of the North Atlantic Oscillation (NAO). By filtering the ensemble members on the basis of statistical predictors, known as subsampling, it is possible to achieve even higher prediction skill. In this study the aim is to design a generalisation of the subsampling approach and establish it as a post-processing procedure. Instead of selecting discrete ensemble members for each year, as the subsampling approach does, the distributions of ensembles and statistical predictors are combined to create a probabilistic prediction of the winter NAO. By comparing the combined statistical-dynamical prediction with the predictions of its single components, it can be shown that it achieves similar results to the statistical prediction. At the same time it can be shown, that unlike the statistical prediction the combined prediction has less years where it performs worse than the dynamical prediction.

By applying the gained distributions to other meteorological variables, like geopotential height, precipitation and surface temperature it can be shown that evaluating prediction skill depends highly on the chosen metric. Besides the common anomaly correlation (ACC) this study also presents a score basing on the Earth Mover’s Distance (EMD), which is designed to evaluate skill of probabilistic predictions. It shows that by evaluating the predictions separately compared to applying a metric on all years at the same time, like correlation based metrics, leads to different interpretations of the analysis.

André Düsterhus
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Latest update: 12 Nov 2019
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Short summary
Seasonal prediction of the of the North Atlantic Oscillation (NAO) has been improved in recent years by improving dynamical models and ensemble predictions. One step therein was the so called sub-sampling, which combines statistical with dynamical prediction. This study generalises this approach and makes it much more accessible. Furthermore, it presents a new verification approach for such predictions.
Seasonal prediction of the of the North Atlantic Oscillation (NAO) has been improved in recent...
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