Diversity of Stratospheric Error Growth across Subseasonal Prediction Systems

Oral Presentation 

The stratosphere has been shown to be a significant source of sub-seasonal tropospheric predictability. The ability of ensemble prediction systems to appropriately exploit this depends on their ability to reproduce the statistical properties of the real atmosphere. In this study, we investigate predictability properties of the coupled stratosphere-troposphere system in the sub-seasonal to seasonal prediction project hindcasts by fitting a simple, minimal model. We diagnose the signal and noise components of each system in the stratosphere and troposphere and their coupling. We find that the method and details of the design of a prediction system has consequences for predictive properties of all parts of the coupled system. While the correlation skill scores are similar in most systems, the signal to noise properties can be substantially different. In the stratosphere, some systems that simulate initial-condition uncertainties using lagged initialization are significantly overconfident, with a quantifiable impact on the tropospheric confidence.