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Interactive Ensembles of Imperfect Models: Lorenz 96 System

  • Lasko Basnarkov
  • Ljupčo Kocarev
Chapter
Part of the Understanding Complex Systems book series (UCS)

Abstract

Contemporary numerical weather prediction schemes are based on ensemble forecasting. Ensemble members are obtained by taking different (perturbed) models started with different initial conditions. We introduce one type of improved model that represents interactive ensemble of individual models. The improved model’s performance is tested with the Lorenz 96 toy model. One complex model is considered as reality, while its imperfect models are taken to be structurally simpler and with lower resolution. The improved model is defined as one with tendency that is weighted average of the tendencies of individual models. The weights are calculated from past observations by minimizing the average difference between the improved model’s tendency and that of the reality. It is numerically verified that the improved model has better ability for short term prediction than any of the individual models.

Keywords

Diffusive Coupling Atmospheric Model Individual Model Climate Projection Numerical Weather Prediction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work was partially supported by project ERC Grant # 266722 (SUMO project).

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.Faculty of Computer Science and EngineeringSaints Cyril and Methodius UniversitySkopjeMacedonia
  2. 2.Macedonian Academy of Sciences and ArtsSkopjeMacedonia

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