Regional and Seasonal Variations in Synoptic Scale Weather Patterns Associated with Extreme Precipitation across the Contiguous United States

Seasonal and spatial variations of synoptic-scale weather patterns concurrent to days above the 95th percentile of the daily precipitation distribution are characterized over a 44 year period (1980-2023) for the Contiguous United States (CONUS). We use a grid-cell centered approach to construct composites for several key atmospheric variables known to be important for extreme precipitation then employ a clustering approach to group patterns spatially. Composite patterns are constructed using atmospheric reanalysis data and include standardized anomalies of sea level-pressure, integrated water vapor transport, 500 hPa geopotential height, and 300 hPa wind. By interpolating composites for each grid cell onto the same polar coordinate grid relative to the grid cell we are able to directly compare composites from any grid cell with each other providing a comprehensive climatology of meteorological drivers of extreme precipitation across the entire CONUS for all four seasons. This grid-cell centered composite approach also facilitates single variate and multivariate spatial clustering of patterns to identify regions with similar pattern characteristics helping diagnose the favored synoptic conditions associated with extreme precipitation at all grid cells in an interpretable format. Example clustering results include a nearly contiguous region in the western US where cool season extreme precipitation days are characterized by a strong area of low pressure to the north/northwest of the grid cell and a strong pressure gradient over the grid cell, indicative of a pattern conducive to atmospheric rivers. Identified regions and circulation patterns vary by season. This methodology may be extensible to evaluating how well climate models simulate the synoptic-scale conditions that drive extreme precipitation.