Northern Hemisphere Snow Cover, Indo-Pacific SSTs, and Recent Trend as Statistical Predictors of Seasonal North American Temperature

Maximum covariance analysis (MCA) forecasts of gridded seasonal North American temperatures are computed for January–March 1991 through February–April 2014, using as predictors Indo-Pacific sea surface temperatures (SSTs), Eurasian and North American snow-cover extents, and a representation of recent climate nonstationarity, individually and in combination. The most consistent contributor to overall forecast skill is the representation of the ongoing climate warming, implemented by adding the average of the most recent 15 years’ predictand data to the climate anomalies computed by the MCA. For winter and spring forecasts at short (0–1 month) lead times, best forecasts were achieved using the snow-extent predictors together with this representation of the warming trend. The short available period of record for the snow data likely limits the skill that could be achieved using these predictors, as well as limiting the length of the SST training data that can be used simultaneously.