How sensitive is the sub-seasonal prediction to the choice of dynamical cores in the atmospheric model?

This study investigates the prediction skill of the sub-seasonal prediction model that can depend on the choice of dynamical cores: the finite volume (FV) dynamical core on a latitude-longitude grid system versus spectral element (SE) dynamical core on a cubed-sphere grid system. Recent researches showed that the SE dynamical core on a uniform grid system increases parallel scalability and removes the need for polar filters mitigating uncertainty in climate prediction, particularly for the Arctic region. However, it remains unclear whether the choice of dynamical cores can actually yield significant skill changes or not. To tackle this issue, we implemented a sub-seasonal prediction model based on the Community Atmospheric Model version 5 (CAM5) by incorporating the above two dynamical cores with virtually the same physics schemes. Sub-seasonal prediction skills of the SE dynamical core and FV dynamical core are verified with ERA-interim reanalysis during the early winter (November – December) and the late winter (January – February) from 2001/2002 to 2017/2018. The prediction skills of the two different dynamical cores were significantly different regardless of the virtually same physics schemes. In the ocean, the predictability of the SE dynamical core is similar to the FV dynamical core, mostly because of our simulation configuration imposing the same boundary and initial conditions at the surface. Notable differences in the one-month predictability between the two cores are found for the wintertime Arctic and mid-latitudes, particularly over North America and Eurasia continents. With the one-month lead, SE dynamical core exhibited higher predictability over North America in late winter, whereas the FV dynamical core showed relatively higher predictability in East Asia and Eurasia in early winter. One of the reasons for these differences may be the different manifestations of Arctic-midlatitudes linkage in the two dynamical cores; the SE dynamical core captures warmer Arctic and colder mid-latitudes relatively well than the FV dynamical core. Therefore, we conclude that the careful choice of dynamical cores of sub-seasonal prediction models is needed.