Spatial structure of subsurface temperature variability in the California Current, 1950–1993

Abstract

[1] State-space models are used to examine long-term spatial patterns in a set of temperature time series representing the meridional and offshore extent of the California Current System (CCS). We use global one-degree summaries from the World Ocean Database at 11 locations and 10 standard depths in the upper 200 m for the period 1950-1993. Four common trends account for most of the total variance and the important timedependent features of the temperature series. These trends also reveal that different geographical regions and depth strata within the CCS have clearly distinct temporal patterns of interannual to decadal thermal variability: the first common trend reveals a series-long warming tendency at all locations, with the greatest changes occurring in the upper 50 m (75 m) for the coastal (offshore) stations; the second common trend delineates a cross-shore separation, with the coastal locations having greater variance and a stronger impact from most El Niño events and decadal-scale warming and cooling tendencies; the third common trend, with signals strongest in the thermocline, provides a measure of the northern extent of influence of El Niño events and reveals greater interannual variance south of 38°N; the fourth common trend separates the series by depth, revealing significant long-term trends in thermal stratification. These spatially-variant thermal fluctuations identify three characteristic patterns of El Niño influence in the CCS, reflecting both the meridional extent and depth structure of their signals. La Niña signals are less spatially variable in the CCS. We also describe the spatially heterogeneous anomaly structure associated with large-scale decadal climate shifts, such as occurred around 1976. It is shown that this event was a coastal-and surface-intensified acceleration of a warming trend that had begun several years earlier. We briefly discuss the biological consequences of the spatially and temporally varying thermal structure of the CCS revealed by this analysis.INDEX TERMS: 4215 Oceanography: General: Climate and interannual variability (3309); 4516

Nonstationary seasonality of upper ocean temperature in the California Current

“…Temperature fluctuations within the thermocline revealed higher variance south of 38°N, providing a measure of the northern extent of influence of El Niño events. (The main thermocline lies at 50–75 m at these locations [see Mendelssohn et al , 2003, Figure 2].) Most locations also revealed different long‐term trends within the mixed layer and thermocline, reflecting important changes in stratification.…”

Persistent habitat use by Chinook salmon Oncorhynchus tshawytscha in the coastal ocean

“…Given the high degree of spatial variability in oceanographic conditions within the California Current (Hickey 1998, Mendelssohn et al 2003, it is likely that the environment experienced by any individual Chinook salmon will differ from the environment experienced by others at a given point in time.…”

“…The coastal California Current is used by maturing salmon and exhibits short-and long-term cycles in temperature, salinity, upwelling and nutrient supply (Hickey 1998, Mendelssohn et al 2003. Such variation affects the entire California Current food web, changing primary productivity at the base of the food web (Collins et al 2003, Lynn et al 2003 and affecting the abundance, distribution and species composition of animals at higher trophic levels (Pearcy & Schoener 1987, Brodeur et al 2003.…”

Under Pressure: Climate Change, Upwelling, and Eastern Boundary Upwelling Ecosystems

“…In general, regional ocean climate oscillations like the El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO) for the California and Humboldt Current Systems, the Northern Atlantic Oscillation for the Canary/Iberian Current System, and Benguela Niño for the Benguela Current System (Minobe and Mantua, 1999;Lluch-Cota et al, 2001;Mendelssohn et al, 2003;Montecinos et al, 2003;Richter et al, 2010;Seo et al, 2012), impose considerable variability on temperatures and complicate attempts to assess long-term trends (Demarcq, 2009). Indeed, many of the observed trends in recent decades might be associated with these oscillations (Santos et al, 2012;Barton et al, 2013).…”