Seasonal-to-Interannual Drivers of Bottom Temperature Conditions in the Northern California Current System

Seasonal forecasting of ocean conditions benefit from studying the mechanisms that drives its predictability (Jacox et al. submitted). The subsurface temperatures on the Washington/Oregon shelf are more predictable on seasonal timescales than surface conditions (Siedlecki et al. 2016). While seasonal forecasts are possible because of ENSO teleconnections - which has been shown to be the case for SST in the CCS (Jacox et al. 2017; Stock et al. 2015), the actual mechanism that generates this subsurface predictability in the N-CCS has yet to be identified. This study quantifies the relative importance of existing physical mechanisms of variability in the North Pacific and tropical Pacific in predicting bottom shelf water conditions (temperature, salinity) in the N-CCS via oceanic pathways in the global climate model. Based on lagged spatial correlation analysis, predictors were selected from particular oceanic regions, and with temporal lags that significantly influence N-CCS water properties. A Multivariable Linear Regression (MLR) model composed of these selected predictors explains almost 82% of the N-CCS bottom temperature variability. Moreover, we find strong correlations of summer bottom temperatures within N-CCS to conditions the winter prior - especially during Neutral years, suggesting this local signal is not necessarily associated with ENSO. Coastally trapped waves (CTW) influences the N-CCS bottom temperatures via coastal wave guide mechanism. The isopycnal depth in N-CCS and the summer temperatures along the isopycnal are influenced by the CTW originating at the equator, as well as the depth of California Undercurrent (CUC) core, primarily following ENSO events. Including the remote forcings of large-scale atmospheric circulation of the North Pacific, through Pacific Decadal Oscillation (PDO), the CTW dominates the variability in N-CCS bottom temperatures between 1979-2017. The results are relevant to the continued development of current seasonal forecasting efforts off the US West coast, which rely on these mechanisms for their predictability.