Understanding and Anticipating Anomalous Surface Impacts During Large‐Scale Regimes

Abstract

Weather regimes describe the large-scale atmospheric circulation in the mid-latitudes in terms of a few circulation states that modulate regional surface weather conditions on time scales of multiple days to a few weeks. This low-dimensional representation of weather has proven useful for the study of large-scale dynamics, climate trends, flow-dependent predictability, and as proxies for applied medium- to extended-range forecasting in the energy sector, for example. Previous studies have often focused on the mean surface weather associated with a regime, with only a few commenting quantitatively on intra-regime variability. In this paper, we comprehensively quantify variability of daily surface weather within regimes and show that it cannot be ignored as mean-composite approaches can be misleading. Signal-to-noise metrics highlight regime configurations that provide windows of predictive opportunity, where surface dynamics are well controlled by the large-scale regime. We discuss in detail wintertime temperature and wind speed regime anomalies for four selected countries (Spain, Norway, Germany, and the United Kingdom) and show that in each case there is impactful intra-regime variability that can be explained by different subtypes and life cycle stages of a regime. This nuance can be captured by continuous regime indices, allowing a refined application of weather regimes on the pan-European scale. This relatively simple guidance on regime interpretation and operational use comes without the need to change the underlying regime framework. An accompanying interactive archive, documenting intra-regime variability in national-scale, energy-relevant variables, supports immediate practical application of our regime analysis for all European countries.