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The German Climate Forecast System: GCFS
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  • Kristina Fröhlich,
  • Mikhail Dobrynin,
  • Katharina Isensee,
  • Claudia Gessner,
  • Andreas Paxian,
  • Holger Pohlmann,
  • Helmuth Haak,
  • Sebastian Brune,
  • Barbara Früh,
  • Johanna Baehr
Kristina Fröhlich
Deutscher Wetterdienst, Deutscher Wetterdienst

Corresponding Author:[email protected]

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Mikhail Dobrynin
Deutscher Wetterdienst, Deutscher Wetterdienst
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Katharina Isensee
Deutscher Wetterdienst, Deutscher Wetterdienst
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Claudia Gessner
ETH Zürich, ETH Zürich
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Andreas Paxian
Deutscher Wetterdienst, Deutscher Wetterdienst
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Holger Pohlmann
Deutscher Wetterdienst, Deutscher Wetterdienst
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Helmuth Haak
Max Planck Institute for Meteorology, Max Planck Institute for Meteorology
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Sebastian Brune
CEN Universität Hamburg, CEN Universität Hamburg
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Barbara Früh
Deutscher Wetterdienst, Deutscher Wetterdienst
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Johanna Baehr
CEN Universität Hamburg, CEN Universität Hamburg
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Abstract

Seasonal prediction is one important element in a seamless prediction chain between weather forecast and climate projections. After several years of common development in collaboration with Universität Hamburg and Max Planck Institute for Meteorology, the Deutscher Wetterdienst performs operational seasonal forecasts since 2016 with the German Climate Forecast System, now in Version 2 (GCFS2.0). Here, the configuration of previous system GCFS1.0 and the current GCFS2.0 are described and the performance of the two systems is compared over the common hindcast period of 1990-2014. In GCFS2.0, the forecast skill is improved compared to GCFS1.0 during boreal winter, especially for the Northern Hemisphere where the Pearson correlation has doubled for the North Atlantic Oscillation index. During boreal summer, overall a similar performance of GCFS2.0 in comparison to GCFS1.0 is assessed. Future developments for climate forecasts need a stronger focus on the performance of seasonal dependent processes in a model system.
Feb 2021Published in Journal of Advances in Modeling Earth Systems volume 13 issue 2. 10.1029/2020MS002101