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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Discussion papers
https://doi.org/10.5194/gmd-2019-203
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-2019-203
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: development and technical paper 09 Aug 2019

Submitted as: development and technical paper | 09 Aug 2019

Review status
This discussion paper is a preprint. It is a manuscript under review for the journal Geoscientific Model Development (GMD).

Weakly coupled atmospheric-ocean data assimilation in the Canadian global prediction system (v1)

Sergey Skachko1, Mark Buehner1, Stéphane Laroche1, Ervig Lapalme3, Gregory Smith2, François Roy2, Dorina Surcel-Colan3, Jean-Marc Bélanger2, and Louis Garand1 Sergey Skachko et al.
  • 1Data Assimilation and Satellite Meteorology Section, Meteorological Research Division, Environment and Climatic ChangeCanada, Dorval, Québec, Canada
  • 2Environmental Numerical Prediction Research Section, Meteorological Research Division, Environment and Climatic Change Canada, Dorval, Québec, Canada
  • 3National Prediction Development Division, Meteorological Service of Canada, Environment and Climate Change Canada, Dorval, Quebec, Canada

Abstract. A fully coupled atmosphere-ocean-ice model has been used to produce global weather forecasts at Environment and Climate Change Canada (ECCC) since November 2017. Currently, the system relies on four uncoupled data assimilation (DA) components for initializing the fully coupled global atmosphere-ocean-ice forecast model: atmosphere, ocean, sea ice and sea surface temperature (SST). The goal of the present study is to implement a weakly coupled data assimilation (WCDA) between the atmosphere and the ocean components and evaluate its performance against uncoupled DA. The WCDA system uses coupled atmosphere-ocean-ice short-term forecasts as background states for the atmospheric and the ocean DA components that independently compute atmospheric and ocean analyses. This system leads to better agreement between the coupled atmosphere-ocean analyses and the coupled atmosphere-ocean-ice forecasts than between the uncoupled analyses and the coupled forecasts. The use of WCDA improves the atmospheric forecast score near the surface, but a slight increase in the atmospheric temperature bias is observed. A small positive impact from using the short-term SST forecast on the satellite radiance Observation-minus-Forecast statistics is noted. Ocean temperature and salinity forecasts are also improved near the surface. Next steps toward stronger DA coupling are highlighted.

Sergey Skachko et al.
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Status: open (until 04 Oct 2019)
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Sergey Skachko et al.
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Short summary
The study presents the first prototype of the weakly coupled atmosphere-ocean data assimilation system and compares its performance against the uncoupled system.
The study presents the first prototype of the weakly coupled atmosphere-ocean data assimilation...
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