On the predictability of cyclogenesis and low-land snow in the Pacific Northwest

The proliferation of high-resolution numerical weather prediction efforts over the last decade has led to increasingly ambitious attempts to forecast mesoscale phenomena. However, the inherent predictabilities of many such phenomena are still unknown. In this presentation, initial-condition sensitivities of short-term mesoscale forecasts of cyclogenesis and related snowstorms over the Pacific Northwest of the United States are explored with a 100-member ensemble generated with an ensemble Kalman filter. Ensemble forecasts for two storms that developed in December 2008 will be investigated.

Lowland snow in the Puget Sound region of Washington State may occur in response to mesoscale cyclogenesis off the Pacific Northwest Coast if the 850-hPa temperatures fall below about -4 C in a region of precipitation. For forecast lead times between 24 and 36 hours, substantial variability in the 850-hPa temperature and the cyclone track develops among the ensemble members. Each member is ranked according to its predicted 850-hPa temperature, and subsets of the 17 warmest and 17 coldest members are composited. In both cases the difference between the mean 850-hPa temperatures for the warm and cold subsets grows larger than 6 C during the 36-hr forecast. Furthermore, the location of the mesocyclone differs between the warm and cold subsets by nearly 400 km. Such large error growth within the ensemble suggests that deterministic forecasts of lowland snowstorms induced by mesoscale cyclogenesis in the Pacific Northwest can be subject to significant uncertainty at 36-hour lead time.