Seasonal prediction of North American wintertime cold extremes in GFDL SPEAR forecast system

Skillful prediction of wintertime cold extremes on seasonal time scales is beneficial for multiple sectors. This study demonstrates that North American cold extremes, measured by the frequency of cold days in winter, are predictable several months in advance in Geophysical Fluid Dynamics Laboratory’s SPEAR seasonal (Seamless system for Prediction and EArth system Research) forecast system. Two predictable components of cold extremes over North American land areas are found to be skillfully predicted on seasonal scales. One is a trend component, which shows a continent-wide decrease in the frequency of cold extremes and is attributable to external radiative forcing. This trend component is predictable at least 9 months ahead. The other predictable component displays a dipole structure over North America, with negative signs in the northwest and positive signs in the southeast. This dipole component is predictable with significant correlation skill for 2 months and is a response to the central Pacific El Nino as revealed from SPEAR AMIP-like simulations.