On the Level and Origin of Seasonal Forecast Skill in Northern Europe

Abstract

This study examines the level and origin of seasonal forecast skill of surface air temperature in northern Europe. The forecasts are based on an empirical methodology, canonical correlation analysis (CCA), which is a method designed to find correlated patterns between predictor and predictand fields. A modified form of CCA is used where a prefiltering step precedes the CCA as proposed by T. P. Barnett and R. Preisendorfer. The predictive potential of four fields is investigated, namely, (a) surface air temperature (i.e., the predictand field itself ), (b) local sea surface temperature (SST) in the northern European area on a dense grid, (c) Northern Hemisphere 700-hPa geopotential height, and (d) quasi-global SST on a coarse grid. The design is such that four contiguous predictor periods (of 3 months each) are followed by a lead time and then a single predictand period (3 months long). The shortest lead time is 1 month and the longest is 15 months. The skill of the CCAbased forecasts is estimated for the 39-yr time period 1955-93, using cross-validated hindcasting. Skill estimates are expressed as the temporal correlation between the forecasts and the respective verifying observations.