| description abstract | Despite overall improvements in numerical weather prediction and data assimilation, large short-term forecast errors of sea level pressure and 2-m temperature still occur. This is especially true for the west coast of North America where short-term numerical weather forecasts of surface low pressure systems can have large position and central pressure errors. In this study, forecast errors of sea level pressure and temperature in the Pacific Northwest are related to the shape of the large-scale flow aloft. Applying a hierarchical limited-contour clustering algorithm to historical 500-hPa geopotential height data produces four distinct weather regimes. The Rockies ridge regime, which exhibits a ridge near the axis of the Rocky Mountains and nearly zonal flow across the Pacific, experiences the highest magnitude and frequency of large sea level pressure errors. On the other hand, the coastal ridge regime, which exhibits a ridge aligned with the North American west coast, experiences the highest magnitude and frequency of large 2-m minimum temperature errors. | |
