Sub-seasonal prediction of the year-round Atlantic-European weather regimes

crossref(2022)

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摘要
<p>The prediction skill of sub-seasonal forecast models is evaluated for&#160; seven year-round weather regimes in the Atlantic-European region, with a focus on regime onsets and transitions which modulate surface weather in a way that is particularly relevant for the European energy system. Re-forecasts using models from three prediction centers (the European Centre for Medium-Range Weather Forecasts, the National Center for Environmental Prediction and the UK Met Office) for the 2000-2015 period are considered and compared against weather regimes obtained from ERA Interim reanalysis over the same period. We first evaluate their ability to reproduce weather regime life-cycle characteristics, such as their frequency, length, number and transitions. Then, we focus on the assessment of skill, placing emphasis on the differences in the performance for each weather regime depending on the time of the year. Finally, we consider the year-to-year evolution of skill and the role of interannual variability of the atmosphere in this skill.</p><p>Results show that the largest biases in frequency are obtained for Scandinavian Blocking in summer due to an underestimation of the number of life cycles for this regime. The ECMWF model shows the highest skill for most of the weather regimes and seasons, followed closely by the NCEP model. The average regime skill horizon is 3 days longer for ECMWF and NCEP models than for the UKMO model, mainly due to the differences in skill in winter. Greenland Blocking tends to have the longest year-round skill horizon for the three models driven by their performance in winter, which is skillful into week 3 of the forecast period. On the other hand, the skill is lowest for the European Blocking regime for the three models, followed by Scandinavian Blocking. These results demonstrate that weather regime forecasts have the potential to identify periods that may exhibit enhanced forecast skill at sub-seasonal timescales, while at the same time skill depends upon the specific regime.</p>
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