In November of 2024, a 'bomb' cyclone rapidly intensified off the U.S. Pacific Northwest Coast, with the minimum central pressure dropping 64 millibars in 24 hours. The pressure drop at 44.5 degrees North latitude was equivalent to 3.4 Bergeron, a scale developed by Tor Bergeron and further refined by Sanders and Gyakum to define ‘bomb’ cyclones. Not only did the intense extratropical cyclone result in a multitude of marine hazards, but an impactful atmospheric river also crashed ashore the Northern California Coast. The National Weather Service (NWS) Ocean Prediction Center (OPC) had issued forecasts out to 96 hours to message the hurricane-force low, while the NWS Weather Prediction Center (WPC) had issued a rare High Risk Day 3 Excessive Rainfall Outlook. In a region with limited observations, satellite imagery and products were key in monitoring the evolution of the system and its associated impacts. An overview of select satellite-derived observations, such as those provided by scatterometry, and experimental machine-learning products like the GOES Radar Estimation via Machine Learning to Inform NWP (GREMLIN), will be provided.
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