A priori Identification of Windows of Opportunity for Weather Regime Forecasts using Atmospheric Flow Conditions

Despite continuous advancements, the forecast skill of quasi-stationary, large-scale atmospheric circulation patterns, so-called weather regimes, is on average still limited to two weeks (Büeler et al. 2021). However, situations exist during which forecasts are skillful up to 3 or 4 weeks ahead and thus provide windows of opportunity for the subseasonal time-scale. The overarching aim of our study is to provide probabilistic information about the possible occurence of such windows of opportunity for weather regimes using information prior to and at the time of forecast initialisation (i.e., a-priori information only).

For this purpose, we employ a year-round definition of 7 weather regimes for the North Atlantic-European region (Grams et al. 2017) and identify these in ERA5 and subseasonal reforecasts provided by ECMWF. On the basis of reanalysis data, we first examine how specific atmospheric states - characterised by the phases of the Madden-Julian Oscillation (MJO) and the strength of the stratospheric polar vortex (SPV) - affect the likelihood of weather regime occurrence on the subseasonal time-scale. We thereby distinguish between windows of opportunity due to climatological or seasonal factors and due to enhanced model skill under certain atmospheric flow conditions. For example, we find in agreement with previous literature that a strong SPV at initial time increases the probability of the zonal weather regime three weeks later. This relation between the strength of the SPV and the anomalous occurrence frequency of the zonal weather regime is also adequately captured by the numerical model. In a second step, we combine the likelihood of weather regime occurrence based on these atmospheric states together with subseasonal reforecast data using machine learning models. The aim is to improve the reliability of large-scale circulation patterns on the subseasonal range, at least in situations when the windows of opportunity are present. In the long-term, this advancement of weather regime forecasts could lead to more effective weather preparedness and decision-making.

References:
Büeler, D., Ferranti, L., Magnusson, L., Quinting, J.F. & Grams, C.M. (2021) Year-round sub-seasonal forecast skill for Atlantic-European weather regimes. Quarterly Journal of the Royal Meteorological Society, 147, 4283–4309. Available from: https://doi.org/10.1002/qj.4178

Grams, C.M., Beerli, R., Pfenninger, S., Staffell, I. & Wernli, H. (2017) Balancing Europe's wind-power output through spatial deployment informed by weather regimes. Nature Climate Change, 7, 557–562. Available from: https://doi.org/10.1038/NCLIMATE3338