Abstract
<p><span>Issuing skillful forecasts beyond the typical horizon of weather predictability</span> <span>remains a challenge actively addressed by the scientific community. This study evaluates winter subseasonal reforecasts delivered by the</span> <span>CNRM and ECMWF dynamical systems and identifies that the level of skill for predicting temperature in Europe </span><span>varies</span> <span>fairly </span><span>consistently</span><span> in both systems. In particular, forecasts initialized during positive NAO phases tend to be more skillful over Europe at week three in both systems. Composite analyses performed in an atmospheric reanalysis, a long-term climate simulation and both forecast systems unveil very similar temperature and sea-level pressure patterns 3 weeks after NAO+ conditions. Furthermore, regressing these fields onto the 3-week </span><span>pre</span><span>vious</span> <span>NAO index in a reanalysis shows consistent patterns over Europe but also eastern North America, thereby revealing</span> <span>a lagged teleconnection,</span> <span>either related to the persistence or recurrence of the NAO+</span> <span>weather regime. Since this feature is well captured by forecast systems, this </span><span>is </span><span>a key mechanism for determining a priori confidence in the skill of wintertime subseasonal forecasts over Europe and North America.</span></p>
Highlights
Skillful weather and climate predictions for horizons beyond 2 weeks could benefit many users (White et al, 2017)
Given that the spatial extent of these correlation patterns encompasses large parts of the Northern Hemisphere, we evaluate if North Atlantic Oscillation (NAO) initial conditions of winter subseasonal forecasts could translate into enhanced prediction skill beyond Europe and how this relates to the regression patterns described above
The main objective of this study is to determine if the atmospheric circulation pattern in place at the time of initialization can impact the subseasonal predictive skill of forecasts delivered by state-of-the-art forecast systems
Summary
Skillful weather and climate predictions for horizons beyond 2 weeks could benefit many users (White et al, 2017). The S2S horizon has been often considered to be a “predictability desert” based on mean statistics and traditional methods and analyses inspired from seasonal to decadal climate prediction, but the most recent studies reveal instead so-called windows of opportunity based on the fact that under certain circumstances and for specific events and regions, S2S predictability can be considerably increased (Mariotti et al, 2020). This conditional predictability is illustrated by a number of case studies showing the successful anticipation of extreme climate events by dynamical forecast systems beyond 15 d lead time (Domeisen et al, 2021). Their approach allows the most relevant remote tropical regions to be pinpointed, leading to higher forecast skill
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