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Discussion papers | Copyright
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 4.0 License.

Development and technical paper 01 Dec 2017

Development and technical paper | 01 Dec 2017

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This discussion paper is a preprint. A revision of the manuscript is under review for the journal Geoscientific Model Development (GMD).

Assessing bias-corrections of oceanic surface conditions for atmospheric models

Julien Beaumet1, Gerhard Krinner1, Michel Déqué2, Rein Haarsma3, and Laurent Li4 Julien Beaumet et al.
  • 1Univ. Grenoble Alpes, CNRS, IRD, Institut des Géosciences de l'Environnement, F-38000, Grenoble, France
  • 2Météo-France, Centre National de Recherche Météorologiques, Toulouse, France
  • 3Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
  • 4Laboratoire de Météorologie Dynamique, Université Pierre-Marie Curie, CNRS, Paris, France

Abstract. Future sea–surface temperature and sea–ice concentration from coupled ocean–atmosphere general circulation models such as those from the CMIP5 experiment are often used as boundary forcing for the downscaling of future climate experiment. Yet, these models show some considerable biases when compared to the observations over present climate. In this paper, existing methods such as an absolute anomaly and a quantile–quantile method for sea surface temperature (SST) as well as a look-up table and a relative anomaly method for sea–ice concentration (SIC) are presented. For SIC, we also propose a new analog method. Each method is objectively evaluated with a perfect model test using CMIP5 model experiment and some real-case applications using observations. With respect to other previously existing methods for SIC, the analog method is a substantial improvement for the bias correction of future sea–ice concentrations.

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Julien Beaumet et al.
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Julien Beaumet et al.
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Short summary
Oceanic surface conditions coming from coupled ocean–atmosphere global climate models bear considerable biases over the historical climate. In this paper, we review and present new methods for bias-correcting sea surface temperatures and sea–ice concentration coming from such models in order to use them as boundary conditions for atmospheric-only GCM. For sea–ice, we propose a new analog method which allow to reproduce more physically consistent future bias corrected sea–ice concentration maps.
Oceanic surface conditions coming from coupled ocean–atmosphere global climate models bear...