FY 2020

Drivers of subsurface temperature variability in the Northern California Current

Ray, S., S.A. Siedlecki, M.A. Alexander, N.A. Bond, and A.J. Hermann

J. Geophys. Res., 125(8), e2020JC016227, doi: 10.1029/2020JC016227, View online (2020)

JISAO'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.

Plain Language Summary. The Washington/Oregon shelf is a productive habitat with important commercial fisheries. One of the most valuable species is Dungeness crab, which resides on the subsurface shelf and is sensitive to near‐bottom ocean properties such as temperatures and oxygen concentrations. The predictability of these properties on seasonal time scales is being investigated using JISAO's Seasonal Coastal Ocean Prediction of the Ecosystem (J‐SCOPE). Previous studies have explored the driving mechanisms of surface temperature predictability, with a focus on linkages to ENSO; this study investigates their counterparts for subsurface temperatures. We find that remote forcings primarily from the North Pacific have strong influences on the subsurface temperatures. A relatively simple statistical model explains 83% of the subsurface temperature variability. The results on potential sources of predictability are relevant to the continued development of current seasonal forecasting efforts off the U.S. West Coast.