Impact of snow initialisation in subseasonal-to-seasonal winter forecasts with the Norwegian Climate Prediction Model

Snow initialisation has been previously investigated as a potential source of predictability at the subseasonal-to-seasonal (S2S) timescales in winter and spring, through its local radiative, thermodynamical and hydrological feedbacks. However, previous studies were conducted with low-top models over short periods only. Furthermore, the potential role of the land surface–stratosphere connection upon the S2S predictability had remained unclear. To this end, we have carried out twin 30-member ensembles of 2-month (November–January) retrospective forecasts over the period 1985–2016, with either realistic or degraded snow initialisation. A high-top version of the Norwegian Climate Prediction Model is used, based on the Whole Atmosphere Community Climate Model, to insure improved coupling with the stratosphere. In a composite difference of high versus low initial Eurasian snow, the surface temperature is strongly impacted by the presence of snow, and wave activity fluxes into the stratosphere are enhanced at a 1-month lag, leading to a weakened polar vortex. Focusing further on 7 years characterized by a strongly negative phase of the Arctic Oscillation (AO), we find a weak snow feedback contributing to the maintenance of the negative AO. By comparing the twin forecasts, we extracted the predictive skill increment due to realistic snow initialisation. The prediction of snow itself is greatly improved and there is increased skill in surface temperature over snow-covered land at the 0-day lead time, and localized skill increment in the transition regions at the southern edge of the snow-covered land areas, over parts of midlatitude continents, at lead times longer than 30 days.