Abstract

AbstractInstrumental weather records (1880–2020s) from eastern North America were analyzed to characterize the regional patterns and drivers of seasonal extreme weather (snow, rain, high and low temperatures). Using agglomerative hierarchical clustering of extreme weather data, the region was divided into three subregions that are influenced by coastal‐marine gradients and latitudinal factors. Subsequent analyses were performed on high‐quality stations from each subregion and results compared between one another. Long‐term locally weighted linear regressions delineated long‐term changes in extreme weather, and a combination of spectral analysis, continuous wavelet transforms, and cross wavelet transforms were used to identify periodic components in the data. Regional extreme weather is generally periodic, composed of interannual to interdecadal‐scale oscillations and driven by several natural climatic oscillations. The most important such oscillation is the 11‐year Schwabe Solar Cycle, which has a strong and continuous effect on regional extreme weather. The Pacific Decadal Oscillation and Quasi Biennial Oscillation also show considerable influence, but intermittently. The El Niño Southern Oscillation, the Arctic Oscillation, and the North Atlantic Oscillation all have a weaker but interrelated influence. While the Atlantic Multidecadal Oscillation showed the weakest overall influence on regional extreme weather, it demonstrated a clear spatial gradient across the region, unlike the aforementioned oscillations. Long‐term changes in regional extreme weather are not generally important, in that a sustained increase or decrease in extreme weather events is not usually characteristic of the weather records. The primary exception to this result is for extreme minimum temperature events, whose frequency has slightly decreased since the 1880s.

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