Abstract
Abstract A statistical prediction model for weekly rainfall during winter over western North America is developed that uses tropical outgoing longwave radiation (OLR) anomalies as a predictor. The effects of El Nino–Southern Oscillation (ENSO) are linearly removed from the OLR to isolate the predictive utility of subseasonal variations in tropical convection. A single canonical correlation (CCA) mode accounts for most of the predictable signal. The rank correlation between this mode and observed rainfall anomalies over southern California is 0.2 for a 2-week lag, which is comparable to correlation between a weekly ENSO index and weekly rainfall in this region. This corresponds to a doubling of the risk of extreme rainfall in southern California when the projection of tropical OLR on the leading CCA mode two weeks prior is extremely large, as compared with times when it is extremely small. “Extreme” is defined as being in the upper or lower quintile of the probability distribution. The leading CCA mode rep...
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