Thursday, 1 February 2024: 8:30 AM
325 (The Baltimore Convention Center)
Weather regimes defined through cluster analysis concisely categorize the anomalous regional circulation pattern on any given day. Owing to their persistence and low dimensionality, regimes are increasingly used in subseasonal-to-seasonal prediction and in analysis of climate variability and change. However, a limitation of existing regime classifications for North America is their seasonal dependence, with most existing studies defining regimes for winter only. Here, we normalize the seasonal cycle in daily geopotential height variance and use empirical orthogonal function analysis combined with k-means clustering to define a new set of year-round North American weather regimes: the Pacific Trough, Pacific Ridge, Alaskan Ridge, and Greenland High regimes. We additionally define a No Regime state to represent conditions close to climatology. To demonstrate the robustness of the classification, a thorough assessment of the sensitivity of the clustering solution to various methodological choices is provided. The median persistence of all four regimes, obtained without imposing an explicit persistence criterion, is found to be one week, approximately three times longer than the median persistence of the No Regime state. Regime-associated temperature and precipitation anomalies are reported, together with the relationship between the regimes and modes of climate variability. We also quantify historical trends in the frequency of the regimes since 1979, finding a decrease in the annual frequency of the Pacific Trough regime and an increase in the summertime frequency of the Greenland High regime. This study serves as a foundation for the future use of these regimes in a variety of weather and climate applications across all seasons.

