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The deterministic prediction skill of the 10 operational models participating in the subseasonal‐to‐seasonal (S2S) prediction project is assessed for both the extratropical stratosphere and troposphere. Based on the mean squared skill score of 50‐ and 500‐hPa geopotential height forecasts, the overall prediction skill is on average 16 days in the stratosphere and 9 days in the troposphere. The high‐top models with a fully resolved stratosphere typically have a higher prediction skill than the low‐top models. Among them, the European Centre for Medium‐Range Weather Forecasts model shows the best performance in both hemispheres. The decomposition of model errors reveals that eddy errors are more important than zonal‐mean errors in both the stratosphere and troposphere. While the errors in the stratosphere are dominated by planetary‐scale eddies, those in the troposphere are equally influenced by planetary‐ and synoptic‐scale eddies. This result indicates that subseasonal‐to‐seasonal prediction could be improved by better representing planetary‐scale wave activities in the model.

The Monin–Obukhov similarity theory and a generalized formulation of the mixing length for the stable boundary layer are evaluated using the Cooperative Atmosphere–Surface Exchange Study-1999 (CASES-99) data. The large-scale wind forcing is classified into weak, intermediate, and strong winds. Although the stability parameter, z/L, is inversely dependent on the mean wind speed, the speed of the large-scale flow includes independent influences on the flux–gradient relationship. The dimensionless mean wind shear is found to obey existing stability functions when z/L is less than unity, particularly for the strong and intermediate wind classes. For weak mean winds and/or strong stability (z/L > 1), this similarity theory breaks down. Deviations from similarity theory are examined in terms of intermittency. A case study of a weak-wind night indicates important modulation of the turbulence flux by mesoscale motions of unknown origin.

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Abstract. Major disruptions of the winter season, high-latitude stratospheric polar vortices can result in stratospheric anomalies that persist for months. These sudden stratospheric warming events are recognized as an important potential source of forecast skill for surface climate on subseasonal to seasonal timescales. Realizing this skill in operational subseasonal forecast models remains a challenge, as models must capture both the evolution of the stratospheric polar vortices in addition to their coupling to the troposphere. The processes involved in this coupling remain a topic of open research. We present here the Stratospheric Nudging And Predictable Surface Impacts (SNAPSI) project. SNAPSI is a new model intercomparison protocol designed to study the role of the Arctic and Antarctic stratospheric polar vortex disturbances for surface predictability in subseasonal to seasonal forecast models. Based on a set of controlled, subseasonal ensemble forecasts of three recent events, the protocol aims to address four main scientific goals. First, to quantify the impact of improved stratospheric forecasts on near-surface forecast skill. Second, to attribute specific extreme events to stratospheric variability. Third, to assess the mechanisms by which the stratosphere influences the troposphere in the forecast models. Fourth, to investigate the wave processes that lead to the stratospheric anomalies themselves. Although not a primary focus, the experiments are furthermore expected to shed light on coupling between the tropical stratosphere and troposphere. The output requested will allow for a more detailed, process-based community analysis than has been possible with existing databases of subseasonal forecasts.