Anticipating a rare event utilizing forecast anomalies: The western U.S. storm of 18–23 January 2010

From 18 to 23 January 2010 a series of winter storms impacted the western United States. In particular a massive storm, which came ashore on 21-22 January, affected the western United States from California eastward through the desert southwest. This record setting system produced severe convection, high winds, heavy rain and heavy snow. The severe weather included several tornadoes reported in California and Arizona as this system moved eastward. High winds, in excess of 40 m s-1 (90 MPH), were associated with an intense squall line affecting Nevada and Arizona. At higher elevations, blizzard conditions were reported in California and Nevada. Snowfall totals in excess of 2.7 m (9 feet) were reported in portions of the Sierra Nevada Mountains and sites in northern Nevada approached all-time state-record storm totals. Heavy rain fell in central and southern California resulting in several devastating mudslides. Finally, all-time minimum pressure records were set across a significant portion of the western United States from Oregon southwest through Arizona.

This was an extraordinary event which was remarkably well predicted 5-7 days in advance. Standardized anomalies derived from the GFS Ensemble Forecast System (GEFS) indicated a potentially historic storm a week in advance. The GEFS forecast near-record mean sea-level pressure (MSLP) anomalies approximately four days ahead of the event. The verifying MSLP anomaly with this event set the record for the largest departure in the western United States in the NCEP reanalysis data set which dates back to 1948.

Both forecast and analyzed anomalies associated with this historic storm will be presented. These data will show how the synoptic-scale anomalies were well correlated with significant weather which impacted the western U.S. and facilitated placing the event in a historical perspective relative to previous events. This case demonstrates the utility of using anomalies to increase forecaster confidence and situational awareness, which enables operational forecasters to provide decision makers with information regarding the potential significance and possible impacts of pending weather events. The event will also be utilized to demonstrate how improved anomaly based situational awareness displays can streamline the identification, and analysis, of significant forecast anomalies.