Sebastiaan goed idee om al de "drivers" van het verloop van de komende winter hier te presenteren. Een belangrijk aspect voor Europa is de NAO.Sebastiaan schreef: ↑26-09-2022 18:21https://www.severe-weather.eu/global-we ... europe-fa/
To summarize everything, there are two main things to take away from this development. First, strong high-pressure systems will impact the Polar Vortex more directly. Pressing upwards and sending energy waves, we are seeing a reduction in the power of the Polar Vortex.
The Polar Vortex should be increasing strength steadily from now towards at least early Winter. However, these intermediate disruptions can delay that strengthening process, meaning that the Polar Vortex can arrive weaker into the Winter than it would otherwise.
Another secondary effect of these pressure patterns is the increased snow cover extent over Siberia. As data shows, increased October snow cover over Siberia leads to a stronger high-pressure system over the region.
That high-pressure system helps to send more vertical energy into the Stratosphere during Winter. So that is yet another potential blow for the Polar Vortex in the long term.
Een samenvatting is hier te vinden.
[url]https://scholar.google.com/scholar?outp ... oi=lle[url]
"The variability of the North Atlantic Oscillation (NAO) is a key aspect of Northern Hemisphere atmospheric circulation and has a profound impact upon the weather of the surrounding landmasses.
Recent success with dynamical forecasts predicting the winter NAO at lead times of a few months has the potential to
deliver great socioeconomic impacts. Here, a linear regression model is found to provide skillful predictions of
the winter NAO based on a limited number of statistical predictors. Identified predictors include El Niño,
Arctic sea ice, Atlantic SSTs, and tropical rainfall. These statistical models can show significant skill when
used to make out-of-sample forecasts, and the method is extended to produce probabilistic predictions of the
winter NAO. The statistical hindcasts can achieve similar levels of skill to state-of-the-art dynamical forecast
models, although out-of-sample predictions are less skillful, albeit over a small period. Forecasts over a longer
out-of-sample period suggest there is true skill in the statistical models, comparable with that of dynamical
forecasting models. They can be used both to help evaluate and to offer insight into the sources of predictability and limitations of dynamical models."