资源环境科技发展态势分析平台

Snow initialization has been previously investigated as a potential source of predictability at the subseasonal-to-seasonal (S2S) timescale 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 and December) retrospective forecasts over the period 1985-2016, with either realistic or degraded snow initialization. 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, we find a weak snow feedback contributing to the maintenance of the negative Arctic Oscillation. By comparing the twin forecasts, we extracted the predictive skill increment due to realistic snow initialization. The prediction of snow itself is greatly improved, and there is increased skill in surface temperature over snow-covered land in the first 10 days, and localized skill increments in the mid-latitude transition regions on the southern flanks of the snow-covered land areas, at lead times longer than 30 days.