Sub-seasonal to seasonal (S2S) predictability derives from climate processes that evolve on timescales of weeks to months. S2S predictive skill derives from forecast models faithfully simulating and predicting these processes. Stratospheric variability impacts the troposphere on approximately these timescales, making the stratosphere a potentially important source of S2S prediction skill (NAS, 2016; NRC, 2010). The S2S Prediction Project (Vitart et al., 2017) seeks to promote and improve S2S predictions by identifying sources of predictability and understanding systematic model errors that are acting to limit forecast skill. Given the observed impact of the stratosphere on the troposphere, creating a sub-project focused on the stratosphere would be valuable.

In collaboration with S2S during Phase I, the Stratospheric Network for the Assessment of Predictability (SNAP), which is a WCRP/SPARC initiative, focused on the predictability of extreme stratospheric polar variability, especially stratospheric sudden warmings (SSW), and the coupling to the troposphere (Tripathi et al., 2015). Predictability of SSW was demonstrated into the sub-seasonal range but stratospheric model biases and predictability of tropospheric planetary wave were found to limit predictive skill of SSW. In order to fully tap into the predictability that the stratosphere may provide for the troposphere in the sub-seasonal range and several key questions need to be addressed:

The Stratospheric Network for the Assessment of Predictability (SNAP) is a WCRP/SPARC initiative which seeks to understand the role of the stratosphere in tropospheric predictability. In its first phase, SNAP used targeted model simulations to investigate the predictability of the stratosphere on sub-seasonal timescales (Tripathi et al., 2015). The second and current phase of SNAP is focused on evaluating model ensemble forecasts from the S2S project to better determine the role of stratospheric processes on improving tropospheric forecasting skill. A sub-project focused on the stratosphere would therefore strengthen the link between S2S and SNAP, and promote research and collaboration between these two groups.

SNAP is already working to coalesce S2S projects focusing on the role of the stratosphere in an overview paper led by Ms Daniela Domeisen. There are 13 research projects from 20 researchers around the world focused on various aspects of both upward and downward coupling between the troposphere and stratosphere. Each project uses S2S output to evaluate topics such as the role of the Quasi-Biennial Oscillation on Madden-Julian Oscillation predictability, the predictability of surface climate following stratospheric final warming events, or the role of weak or strong polar vortex events in tropospheric predictability. While many of the projects will also produce individual publications, the SNAP S2S paper will provide a broad overview on how both the tropical and extratropical stratosphere may contribute to prediction skill in the S2S models.

For example, Figure 7 shows the prediction skill of the 1000 hPa Northern Annular Mode for week 3 or week 4 in the S2S models, for either neutral stratospheric vortex conditions (top row), or weak vortex conditions (bottom row). It is clear that for most models, skill is higher following weak vortex conditions. Similar results are found following strong vortex conditions. In other words, extremes in the polar stratosphere can improve tropospheric winter climate prediction, during weeks notoriously difficult to skilfully predict. The figure also highlights that there is considerable difference in the size of this gain in skill between the models and a clear priority of the SNAP work will be to quantify and understand the origin of these differences.