Predictability in California Current System: the role of the North Pacific forcing and the asymmetric response to La Niña vs El Niño

It has been well-established that El Niño Southern Oscillation (ENSO) drives variability in the North Pacific and by extension along the North American West Coast. Yet, in the California Current System (CCS), the response to ENSO remains unclear and El Niño appears to have different regional impacts on physical and biological variability. Using the last 70 years of ocean observations and reanalysis, we develop a Linear Inverse Model to study the monthly sea surface temperature predictability in CCS for lead times ranging from 1 to 12 month. By partitioning the simulated Pacific into multiple subregions, including equatorial tropics and North Pacific, we systematically quantify and isolate the patterns and regions that influence the predictability of CCS. Our results showed that the equatorial tropical Pacific has a very limited influence on CCS predictability, and that the North Pacific is a major contributor. Furthermore, consistent with other recent studies, we find an asymmetric response of the CCS variability to El Niño versus La Niña, such that La Niña related CCS variability is more predictable compared to El Niño. The predictability related to El Niño is no better than that obtain from “persistence” of the current conditions. More interestingly, by further investigating the regional influence during El Niño versus during La Niña, our results show that even during El Niño, the influence from the tropical Pacific is still very limited and the CCS predictability is dominated by the North Pacific. However, during La Niña, the contribution from different regions on the CCS predictability is more evenly distributed among regions.