A document by Tiffany A Shaw. Click on the document to view its contents.

The winter of 2019-20 was dominated by an extremely strong stratospheric polar vortex and positive tropospheric Arctic Oscillation (AO). Here, we analyze forecasts from 6 different prediction systems contributing to the C3S seasonal forecast database. Most performed very strongly, with consistently high skill for January-March 2020 from forecasts launched through October–December 2019. Although the magnitude of the anomalies was underestimated, the performance of most prediction systems was extremely high for a positive AO winter relative to the common hindcast climate. Ensemble members which better predicted the extremely strong stratospheric vortex better predicted the extreme tropospheric state. We find a significant relationship between forecasts of the anomalous mid-latitude tropospheric wave pattern in early winter, which destructively interfered with the climatological stationary waves, and the strength of the stratospheric vortex later in the winter. Our results demonstrate a strong interdependence between the accuracy of stratospheric vortex and AO forecasts.

Many recent studies have confirmed that variability in the stratosphere is a significant source of surface sub-seasonal prediction skill during northern hemisphere winter. It may be beneficial, therefore, to think about times in which there might be windows-of-opportunity for skilful sub-seasonal predictions based on the initial or predicted state of the stratosphere. In this study, we propose a simple, minimal model that can be used to understand the impact of the stratosphere on tropospheric predictability. Our model purposefully excludes state dependent predictability in either the stratosphere or troposphere or in the coupling between the two. Model parameters are set up to broadly represent current sub-seasonal prediction systems by comparison with four dynamical models from the sub-seasonal to seasonal prediction project database. The model can reproduce the increases in correlation skill in sub-sets of forecasts for weak and strong stratospheric states over neutral states despite the lack of dependence of coupling or predictability on the stratospheric state. We demonstrate why different forecast skill diagnostics can give a very different impression of the relative skill in the three sub-sets. Forecasts with large stratospheric signals and low amounts of noise are demonstrated to also be windows-of-opportunity for skilful tropospheric forecasts, but we show that these windows can be obscured by the presence of unrelated tropospheric signals.