The role of the stratosphere in subseasonal to seasonal prediction: 2. Predictability arising from stratosphere ‐ troposphere coupling
Abstract
The stratosphere can have a significant impact on winter surface weather on subseasonal to seasonal (S2S) timescales. This study evaluates the ability of current operational S2S prediction systems to capture two important links between the stratosphere and troposphere: (1) changes in probabilistic prediction skill in the extratropical stratosphere by precursors in the tropics and the extratropical troposphere and (2) changes in surface predictability in the extratropics after stratospheric weak and strong vortex events. Probabilistic skill exists for stratospheric events when including extratropical tropospheric precursors over the North Pacific and Eurasia, though only a limited set of models captures the Eurasian precursors. Tropical teleconnections such as the Madden‐Julian Oscillation, the Quasi‐Biennial Oscillation, and El Niño–Southern Oscillation increase the probabilistic skill of the polar vortex strength, though these are only captured by a limited set of models. At the surface, predictability is increased over the United States, Russia, and the Middle East for weak vortex events, but not for Europe, and the change in predictability is smaller for strong vortex events for all prediction systems. Prediction systems with poorly resolved stratospheric processes represent this skill to a lesser degree. Altogether, the analyses indicate that correctly simulating stratospheric variability and stratosphere‐troposphere dynamical coupling are critical elements for skillful S2S wintertime predictions. Show more
Publication status
publishedExternal links
Journal / series
Journal of Geophysical Research: AtmospheresVolume
Pages / Article No.
Publisher
WileySubject
stratosphere; sub‐seasonal predictability; S2S database; sudden stratospheric warming; stratosphere ‐ troposphere coupling; North Atlantic OscillationOrganisational unit
09612 - Domeisen, Daniela / Domeisen, Daniela
Funding
170523 - Improving the Prediction of Sub-seasonal to Seasonal Weather and Climate – From Theory to Application (SNF)
Related publications and datasets
Continues: http://hdl.handle.net/20.500.11850/379897
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