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Objective Discrimination and Pooling Models in the Ensemble

  • Eugene Genikhovich
  • Tatiana Pavlova
  • Alexander Ziv
Conference paper
Part of the NATO Science for Peace and Security Series C: Environmental Security book series (NAPSC)

Abstract

Data assimilating and pooling the model predictions in the multi-model ensemble, described in this paper, are based on the techniques of approximation and regularization of multidimensional vectors in the linear Euclidean space with the use of the non-orthogonal vector basis. This approach has been successfully applied to (i) the time series of the annual temperatures averaged over the globe and northern hemisphere corresponding to the last 100years, and (ii) the fields of concentrations of atmospheric pollutants over Europe. Quantitative estimates of the efficiency of the proposed technique are presented in the paper.

Keywords

Root Mean Square Error Numerical Weather Prediction Nitrogen Dioxide Objective Discrimination Observational Vector 
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 funded by the Russian Foundation for Basic Research (grant # 08-05-00569-a). We would like to acknowledge the participants of the project GEMS for kindly providing all necessary data sets.

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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Eugene Genikhovich
    • 1
  • Tatiana Pavlova
    • 1
  • Alexander Ziv
    • 1
  1. 1.Voeikov Main Geophysical ObservatorySt. PetersburgRussia

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