Application of partial least squares regression to the diagnosis of year‐to‐year variations in Pacific Northwest snowpack and Atlantic hurricanes

Application of the method of partial least squares (PLS) regression to geophysical data is illustrated with two cases: (1) finding sea level pressure patterns over the North Pacific associated with dynamically‐induced winter‐to‐winter variations in snowpack in the Cascade mountains of western Washington state and (2) finding patterns of sea surface temperature over the tropical oceans that modulate Atlantic hurricane activity on a year‐to‐year basis. In both examples two robust patterns in the “predictor field” are identified that, in combination, account for over half the variance in the target time series.