Drivers of Subsurface Temperature Variability in the Northern California Current

Abstract

AbstractJISAO's Seasonal Coastal Ocean Prediction of the Ecosystem (J‐SCOPE) was developed to carry out experimental seasonal forecasts of ocean conditions in the Northern California Coastal System (N‐CCS). This system relies on NOAA's Coupled Forecast System (CFS) global climate model to provide initial and boundary conditions for dynamical downscaling with a high‐resolution numerical ocean model. Experiments with J‐SCOPE show that the bottom temperature on the shelf is more predictable than the sea surface temperature (SST) on seasonal time scales. While seasonal forecasts have been shown to have positive skill in terms of SST for the CCS due to El Niño‐Southern Oscillation (ENSO), the mechanism(s) responsible for subsurface predictability in the N‐CCS have yet to be determined. This study quantifies the relative importance of North Pacific and Tropical Pacific properties in determining the variations in temperatures at depth (TDs) on the N‐CCS shelf. A multivariable linear regression (MLR) model with selected predictors explains almost 83% of the N‐CCS TD variability with oceanic teleconnections from the North Pacific dominating the variance. The N‐CCS TD is related to (i) coastally trapped waves (CTWs) related to ENSO, originating in Tropical Pacific, (ii) west‐central Pacific spice anomalies, (iii) seasonal Pacific Decadal Oscillation (PDO) variation, and a more local influence from (iv) anomalies south of N‐CCS, originating in North Pacific. ENSO and CTW can each impact the depth of the California Undercurrent (CUC) core with the latter most prominently following ENSO events. The results on potential sources of predictability are relevant to the continued development of current seasonal forecasting efforts off the U.S. West coast.