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Stochastic parameterization toward a new view of weather and climate models

  • Judith Berner
  • , Ulrich Achatz
  • , Lauriane Batté
  • , Lisa Bengtsson
  • , Alvaro De La Cámara
  • , Hannah M. Christensen
  • , Matteo Colangeli
  • , Danielle R.B. Coleman
  • , Daaaan Crommelin
  • , Stamen I. Dolaptchiev
  • , Christian L.E. Franzke
  • , Petra Friederichs
  • , Peter Imkeller
  • , Heikki Järvinen
  • , Stephan Juricke
  • , Vassili Kitsios
  • , François Lott
  • , Valerio Lucarini
  • , Salil Mahajaajaajan
  • , Timothy N. Palmer
  • Cécile Penland, Mirjajana Sakradzijaja, Jin Song Von Storch, Antje Weisheimer, Michael Weniger, Paul D. Williams, Jun Ichi Yano
  • National Center for Atmospheric Research
  • Goethe University Frankfurt
  • Centre National de Recherches Météorologiques
  • Swedish Meteorological and Hydrological Institute
  • University of Oxford
  • Gran Sasso Science Institute
  • University of Amsterdam
  • University of Hamburg
  • University of Bonn
  • Humboldt University of Berlin
  • University of Helsinki
  • CSIRO
  • École normale supérieure
  • University of Reading
  • Oak Ridge National Laboratory
  • National Oceanic and Atmospheric Administration
  • Deutscher Wetterdienst
  • Max Planck Institute for Meteorology

Research output: Contribution to journalArticlepeer-review

324 Scopus citations

Abstract

Stochastic parameterizations-empirically derived or based on rigorous mathematical and statistical concepts-have great potential to increase the predictive capability of next-generation weather and climate models.

Original languageEnglish
Pages (from-to)565-587
Number of pages23
JournalBulletin of the American Meteorological Society
Volume98
Issue number3
DOIs
StatePublished - Mar 2017
Externally publishedYes

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