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

Sergey Skachko Mark Buehner Stéphane Laroche Ervig Lapalme Gregory Smith François Roy Dorina Surcel-Colan Jean-Marc Bélanger Louis Garand

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 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. The next steps toward stronger DA coupling are highlighted.