Archive for PDO

WBC Series: Decadal variability of the Kuroshio Extension system and its impact on subtropical mode water formation 

Posted by mmaheigan 
· Friday, November 10th, 2017 

Bo Qiu1, Eitarou Oka2, Stuart P. Bishop3, Shuiming Chen1, Andrea J. Fassbender4

1. University of Hawaii at Manoa
2. The University of Tokyo
3. North Carolina State University
4. Monterey Bay Aquarium Research Institute

 

After separating from the Japanese coast at 36°N, 141°E, the Kuroshio enters the open basin of the North Pacific, where it is renamed the Kuroshio Extension (KE). Free from the constraint of coastal boundaries, the KE has been observed to be an eastward-flowing inertial jet accompanied by large-amplitude meanders and energetic pinched-off eddies (see Qiu 2002 and Kelly et al. 2010 for comprehensive reviews). Compared to its upstream counterpart south of Japan, the Kuroshio, the KE is accompanied by a stronger southern recirculation gyre that increases the KE’s eastward volume transport to more than twice the maximum Sverdrup transport (~ 60Sv) in the subtropical North Pacific Ocean (Wijffels et al. 1998). This has two important consequences. Dynamically, the increased transport enhances the nonlinearity of the KE jet, rendering the region surrounding the KE jet to have the highest mesoscale activity level in the Pacific basin. Thermodynamically, the enhanced KE jet brings a significant amount of tropical-origin warm water to the mid-latitude ocean to be in direct contact with cold, dry air blowing off the Eurasian continent. This results in significant wintertime heat loss from the ocean to atmosphere surrounding the Kuroshio/KE paths, contributing to the formation of North Pacific subtropical mode water (STMW; see Hanawa and Talley (2001) and Oka and Qiu (2012) for comprehensive reviews).

Figure 1. Yearly paths of the Kuroshio and KE plotted every 14 days using satellite SSH data (updated based on Qiu and Chen 2005). KE was in stable state in 1993–94, 2002–05, and 2010–15, and unstable state in 1995-2001, 2006–09, and 2016, respectively.

 

Although the ocean is known to be a turbulent medium, variations in both the level of mesoscale eddy activity and the formation rate of STMW in the KE region are by no means random on interannual and longer timescales. One important feature emerging from recent satellite altimeter measurements and eddy-resolving ocean model simulations is that the KE system exhibits clearly defined decadal modulations between a stable and an unstable dynamical state (e.g., Qiu & Chen 2005, 2010; Taguchi et al. 2007; Qiu et al. 2007; Cebollas et al. 2009; Sugimoto and Hanawa 2009; Sasaki et al. 2013; Pierini 2014; Bishop et al. 2015). As shown in Figure 1, the KE paths were relatively stable in 1993–95, 2002–05, and 2010–15. In contrast, spatially convoluted paths prevailed during 1996–2001 and 2006–09. When the KE jet is in a stable dynamical state, satellite altimeter data further reveal that its eastward transport and latitudinal position tend to increase and migrate northward, its southern recirculation gyre tends to strengthen, and the regional eddy kinetic energy level tends to decrease. The reverse is true when the KE jet switches to an unstable dynamical state. In fact, the time-varying dynamical state of the KE system can be well represented by the KE index, defined by the average of the variance-normalized time series of the southern recirculation gyre intensity, the KE jet intensity, its latitudinal position, and the negative of its path length (Qiu et al. 2014). Figure 2a shows the KE index time series in the satellite altimetry period of 1993–present; here, a positive KE index indicates a stable dynamical state and a negative KE index, an unstable dynamical state. From Figure 2a, it is easy to discern the dominance of the decadal oscillations between the two dynamical states of the KE system.

Figure 2. (a) Time series of the KE index from 1993‑present; available at http://www.soest.hawaii.edu/oceanography/bo/KE_index.asc. (b) Year-mean SSH maps when the KE is in stable (2004 and 2011) versus unstable (1997 and 2008) states. (c) SSH anomalies along the zonal band of 32°-34°N from satellite altimetry measurements. (d) Time series of the PDO index from 1989-present; available at http://jisao.washington.edu/pdo/PDO.latest.

 

Transitions between the KE’s two dynamical states are caused by the basin-scale wind stress curl forcing in the eastern North Pacific related to the Pacific Decadal Oscillation (PDO). Specifically, when the central North Pacific wind stress curl anomalies are positive during the positive PDO phase (see Figure 2d), enhanced Ekman flux divergence generates negative local sea surface height (SSH) anomalies in 170°–150°W along the southern recirculation gyre latitude of 32°–34°N. As these wind-induced negative SSH anomalies propagate westward as baroclinic Rossby waves into the KE region after a delay of 3–4 years (Figure 2c), they weaken the zonal KE jet, leading to an unstable (i.e., negative index) state of the KE system with a reduced recirculation gyre and an active eddy kinetic energy field (Figure 2b). Negative anomalous wind stress curl forcing during the negative PDO phase, on the other hand, generates positive SSH anomalies through the Ekman flux convergence in the eastern North Pacific. After propagating into the KE region in the west, these anomalies stabilize the KE system by increasing the KE transport and by shifting its position northward, leading to a positive index state.

The dynamical state of the KE system exerts a tremendous influence upon the STMW that forms largely along the paths of the Kuroshio/KE jet and inside of its southern recirculation gyre (e.g., Suga et al. 2004; Qiu et al. 2006; Oka 2009). Figure 3a shows the monthly time series of temperature profile, constructed by averaging available Argo and XBT/CTD/XCTD data inside the KE southern recirculation gyre (see Qiu and Chen 2006 for details on the constructing method). The black line in the plot denotes the base of the mixed layer, defined as where the water temperature drops by 0.5°C from the sea surface temperature. Based on the temperature profiles, Figure 3b shows the monthly time series of potential vorticity. STMW in Figure 3b is characterized by water columns with potential vorticity of less than 2.0 x 10-10 m-1s-1 beneath the mixed layer. From Figure 3, it is clear that both the late winter mixed layer depth and the low-potential vorticity STMW layer underwent significant decadal changes over the past 25 years. Specifically, deep mixed layer and pronounced low-potential vorticity STMW were detected in 1993–95, 2001–05, and 2010–15, and these years corresponded roughly to the periods when the KE index was in the positive phase (cf. Figure 2a).

 

Figure 3. Monthly time series of (a) temperature (°C) and (b) potential vorticity (10-10 m-1 s-1) averaged in the KE’s southern recirculation gyre. The thick black and white lines in (a) and (b) denote the base of the mixed layer, defined as where the temperature drops by 0.5°C from the surface value. Red pluses (at the top of each panel) indicate the individual temperature profiles used in constructing the monthly T(z, t) profiles. The potential vorticity, Q(z,t) = fα∂T(z,t)/∂z, where f is the Coriolis parameter and α the thermal expansion coefficient.

 

The close connection between the dynamical state of the KE system and the STMW formation has been detected by many recent studies based on different observational data sources and analysis approaches (Qiu and Chen 2006; Sugimoto and Hanawa 2010; Rainville et al. 2014; Bishop and Watts 2014; Oka et al. 2012; 2015; Cerovecki and Giglio 2016). Physically, this connection can be understood as follows. When the KE is in an unstable state (or a negative KE index phase), high-regional eddy variability infuses high-potential vorticity KE and subarctic-gyre water into the southern recirculation gyre, increasing the upper-ocean stratification and hindering the development of deep winter mixed layer and formation of STMW. A stable KE path with suppressed eddy variability (in the positive KE index phase), on the other hand, favors the maintenance of a weak stratification in the recirculation gyre, leading to the formation of a deep winter mixed layer and thick STMW.

Since the STMW is renewed each winter, due to combined net surface heat flux and wind stress forcing that modulate on interannual timescales, a question arising naturally is the timescale on which the dynamical state change of the KE system is able to alter the upper ocean stratification and potential vorticity inside the recirculation gyre. If the influence of the KE dynamical state acts on interannual timescales, one may expect a stronger control on the STMW variability by the wintertime atmospheric condition (e.g., Suga and Hanawa 1995; Davis et al. 2011). Intensive observations from the Kuroshio Extension System Study (KESS) program, spanning the period from April 2004 to July 2006, captured the 2004–05 transition of the KE system from a stable to an unstable state. The combined measurements by profiling Argo floats, moored current meter, current and pressure inverted echo sounder (CPIES), and the Kuroshio Extension Observatory (KEO) surface mooring revealed that the KE dynamical state change was able to change the STMW properties both significantly in amplitude and effectively in time (Qiu et al. 2007; Bishop 2013; Cronin et al. 2013; Bishop and Watts 2014). Relative to 2004, the low-potential vorticity signal in the core of STMW was diminished by one-half in 2005, and this weakening of STMW’s intensity occurred within a period of less than seven months. These significant and rapid responses of STMW to the KE dynamical state change suggests that the variability in STMW formation is more sensitive to the dynamical state of the KE than to interannual variations in overlying atmospheric conditions over the past 25 years.

The decadal variability of STMW in the KE’s southern recirculation gyre is able to affect the water property distributions in the entire western part of the North Pacific subtropical gyre (Oka et al. 2015). Measurements by Argo profiling floats during 2005–14 revealed that the volume and spatial extent of STMW decreased (increased) in 2006–09 (after 2010) during the unstable (stable) KE period in its formation region north of ~28°N, as well as in the southern, downstream regions with a time lag of 1-2 years. Such decadal subduction variability affects not only physical but also biogeochemical structures in the downstream, interior subtropical gyre. Shipboard observations at 25°N and along the 137°E repeat hydrographic section of the Japan Meteorological Agency exhibited that, after 2010, enhanced subduction of STMW consistently increased dissolved oxygen, pH, and aragonite saturation state and decreased potential vorticity, apparent oxygen utilization, nitrate, and dissolved inorganic carbon. Changes in dissolved inorganic carbon, pH, and aragonite saturation state were opposite their long-term trends.

KE State and the Ocean Carbon Cycle

Western boundary current (WBC) regions display the largest magnitude air-to-sea carbon dioxide (CO2) fluxes of anywhere in the global ocean. STMW formation processes are thought to account for a majority of the anthropogenic CO2 sequestration that occurs outside of the polar, deep water formation regions (Sabine et al. 2004; Khatiwala et al. 2009). Once subducted and advected away from the formation region, mode waters often remain out of contact with the atmosphere on timescales of decades to hundreds of years, making them short-term carbon silos relative to the abyssal carbon storage reservoirs. One of the physical impacts on carbon uptake via air-sea CO2 flux is due to the temperature dependence of the solubility of pCO2 in the surface waters. Cooler surface waters during the wintertime months reduce the oceanic pCO2 and subsequently enhance the CO2 flux into the ocean. This carbon uptake corresponds with the timing of peak STMW formation.

As mentioned above, the formation of STMW is modulated by the dynamic states of the KE, with less STMW forming during unstable states and more during stable states. To complicate matters, more enhanced levels of surface chlorophyll (Chla) have also been observed from satellite ocean color during unstable states (Lin et al. 2014), which points to the potential importance of biophysical interactions on carbon uptake. Elevated levels of Chla can further modify the pCO2 of surface waters and enhance carbon export at depth from sinking of particulate organic matter following an individual bloom. Given that submesoscale processes result from deep wintertime mixed layers and from the presence of the larger mesoscale lateral shear and strain fields (McWilliams 2016), it is expected that submesoscale processes are also important in STMW formation during unstable states of the KE. An open question in the research community is to what extent do elevated levels of mesoscale and submesoscale eddy activity modulate STMW formation and carbon uptake during unstable states of the KE? With large variations in STMW formation occurring in concert with decadal variability in the mesoscale eddy field, it is possible that submesoscale processes may impact STMW formation through restratification of the mixed layer within density classes encompassing STMW and timing of the spring bloom. These mesoscale and submesoscale processes may then also impact the uptake of CO2 in the North Pacific on interannual to decadal timescales.

 

 

References

Bishop, S. P., 2013: Divergent eddy heat fluxes in the Kuroshio Extension at 143°-149°E. Part II: Spatiotemporal variability. J. Phys. Oceanogr., 43, 2416-2431, doi: 10.1175/JPO-D-13-061.1.

Bishop, S. P., and D. R. Watts, 2014: Rapid eddy-induced modification of subtropical mode water during the Kuroshio Extension System Study. J. Phys. Oceanogr., 44, 1941-1953, doi:10.1175/JPO-D-13-0191.1.

Bishop, S. P., F. O. Bryan, and R. J. Small, 2015: Bjerknes-like compensation in the wintertime north Pacific. J. Phys. Oceanogr., 45, 1339-1355, doi:10.1175/JPO-D-14-0157.1.

Ceballos, L., E. Di Lorenzo, C. D. Hoyos, N. Schneider, and B. Taguchi, 2009: North Pacific Gyre oscillation synchronizes climate variability in the eastern and western boundary current systems. J. Climate, 22, 5163-5174, doi:10.1175/2009JCLI2848.1.

Cerovecki, I., and D. Giglio, 2016: North Pacific subtropical mode water volume decrease in 2006–09 estimated from Argo observations: Influence of surface formation and basin-scale oceanic variability. J. Climate, 29, 2177-2199, doi:10.1175/JCLI-D-15-0179.1.

Cronin, M. F., N. A. Bond, J. T. Farrar, H. Ichikawa, S. R. Jayne, Y. Kawai, M. Konda, B. Qiu, L. Rainville, and H. Tomita, 2013: Formation and erosion of the seasonal thermocline in the Kuroshio Extension Recirculation Gyre. Deep-Sea Res. II, 85, 62-74, doi:10.1016/j.dsr2.2012.07.018.

Davis, X. J., L. M. Rothstein, W. K. Dewar, and D. Menemenlis, 2011: Numerical investigations of seasonal and interannual variability of North Pacific subtropical mode water and its implications for Pacific climate variability. J. Climate, 24, 2648-2665, doi:10.1175/2010JCLI3435.1.

Hanawa, K., and L. D. Talley, 2001: Mode waters. Ocean Circulation and Climate: Observing and Modelling the Global Ocean, G. Siedler, J. Church, and J. Gould, Eds., Academic Press, 373-386.

Khatiwala, S., Primeau, F., and Hall, T., 2009: Reconstruction of the history of anthropogenic CO2 concentrations in the ocean. Nature, 462, 346–349, doi:10.1038/nature08526.

Kelly, K. A., R. J. Small, R. M. Samelson, B. Qiu, T. M. Joyce, Y.-O. Kwon, and M. F. Cronin, 2010: Western boundary currents and frontal air-sea interaction: Gulf Stream and Kuroshio Extension. J. Climate, 23, 5644-5667, doi:10.1175/2010JCLI3346.1.

Lin, P., F. Chai, H. Xue, and P. Xiu, 2014: Modulation of decadal oscillation on surface chlorophyll in the Kuroshio Extension. J. Geophys. Res., 119, 187–199, doi:10.1002/2013JC009359.

McWilliams, J. C., 2016: Submesoscale currents in the ocean. Proc. Roy. Soc. A, 472, doi:10.1098/rspa.2016.0117..

Oka, E., 2009: Seasonal and interannual variation of North Pacific subtropical mode water in 2003–2006. J. Oceanogr., 65, 151-164, doi:10.1007/s10872-009-0015-y.

Oka, E., and B. Qiu, 2012: Progress of North Pacific mode water research in the past decade. J. Oceanogr., 68, 5-20, doi:10.1007/s10872-011-0032-5.

Oka, E., B. Qiu, S. Kouketsu, K. Uehara, and T. Suga, 2012: Decadal seesaw of the central and subtropical mode water formation associated with the Kuroshio Extension variability. J. Oceanogr., 68, 355-360, doi: 10.1007/s10872-015-0300-x.

Oka, E., B. Qiu, Y. Takatani, K. Enyo, D. Sasano, N. Kosugi, M. Ishii, T. Nakano, and T. Suga, 2015: Decadal variability of subtropical mode water subduction and its impact on biogeochemistry. J. Oceanogr., 71, 389-400, doi: 10.1007/s10872-015-0300-x.

Pierini, S., 2014: Kuroshio Extension bimodality and the North Pacific Oscillation: A case of intrinsic variability paced by external forcing. J. Climate, 27, 448-454, doi:10.1175/JCLI-D-13-00306.1.

Qiu, B., 2002: The Kuroshio Extension system: Its large-scale variability and role in the midlatitude ocean-atmosphere interaction. J. Oceanogr., 58, 57-75, doi:10.1023/A:1015824717293.

Qiu, B., and S. Chen, 2005: Variability of the Kuroshio Extension jet, recirculation gyre and mesoscale eddies on decadal timescales. J. Phys. Oceanogr., 35, 2090-2103, doi: 10.1175/JPO2807.1.

Qiu, B., and S. Chen, 2006: Decadal variability in the formation of the North Pacific subtropical mode water: Oceanic versus atmospheric control. J. Phys. Oceanogr., 36, 1365-1380, doi: 10.1175/JPO2918.1.

Qiu, B., and S. Chen, 2010: Eddy-mean flow interaction in the decadally-modulating Kuroshio Extension system. Deep-Sea Res. II, 57, 1098-1110, doi:10.1016/j.dsr2.2008.11.036.

Qiu, B., S. Chen, and P. Hacker, 2007: Effect of mesoscale eddies on subtropical mode water variability from the Kuroshio Extension System Study (KESS). J. Phys. Oceanogr., 37, 982-1000, doi:10.1175/JPO3097.1.

Qiu, B., N. Schneider, and S. Chen, 2007: Coupled decadal variability in the North Pacific: An observationally-constrained idealized model. J. Climate, 20, 3602-3620, doi:10.1175/JCLI4190.1.

Qiu, B., S. Chen, N. Schneider, and B. Taguchi, 2014: A coupled decadal prediction of the dynamic state of the Kuroshio Extension system. J. Climate, 27, 1751-1764, doi:10.1175/JCLI-D-13-00318.1.

Qiu, B., P. Hacker, S. Chen, K. A. Donohue, D. R. Watts, H. Mitsudera, N. G. Hogg and S. R. Jayne, 2006: Observations of the subtropical mode water evolution from the Kuroshio Extension System Study. J. Phys. Oceanogr., 36, 457-473, doi:10.1175/JPO2849.1.

Rainville, L., S. R. Jayne, and M. F. Cronin, 2014: Variations of the North Pacific subtropical mode water from direct observations. J. Climate, 27, 2842-2860, doi:10.1175/JCLI-D-13-00227.1.

Sabine, C. L., Feely, R. A., Gruber, N., Key, R. M., Lee, K., Bullister, J. L., Wanninkhof, R., Wong, C., Wallace, D. W. R., Rilbrook, B., Millero, F. J., Peng, T.-H., Kozyr, A., Ono, T., and Rios, A. F., 2004. The oceanic sink for anthropogenic CO2. Science, 305, 367–371.

Sasaki, Y. N, S. Minobe, and N. Schneider, 2013: Decadal response of the Kuroshio Extension jet to Rossby waves: Observation and thin-jet theory. J. Phys. Oceanogr., 43, 442-456, doi:10.1175/JPO-D-12-096.1.

Suga, T., and K. Hanawa, 1995: Interannual variations of North Pacific subtropical mode water in the 137°E section. J. Phys. Oceanogr., 25, 1012–1017, doi:10.1175/1520-0485(1995)025<1012:IVONPS>2.0.CO;2.

Suga, T., K. Motoki, Y. Aoki, and A. M. MacDonald, 2004: The North Pacific climatology of winter mixed layer and mode waters. J. Phys. Oceanogr., 34, 3–22, doi:10.1175/1520-0485(2004)034<0003:TNPCOW>2.0.CO;2.

Sugimoto, S., and K. Hanawa, 2009: Decadal and interdecadal variations of the Aleutian Low activity and their relation to upper oceanic variations over the North Pacific. J. Meteor. Soc. Japan, 87, 601-614, doi:10.2151/jmsj.87.601.

Sugimoto, S., and K. Hanawa, 2010: Impact of Aleutian Low activity on the STMW formation in the Kuroshio recirculation gyre region. Geophys. Res. Lett., 37, doi:10.1029/ 2009GL041795.

Taguchi, B., S.-P. Xie, N. Schneider, M. Nonaka, H. Sasaki, and Y. Sasai, 2007: Decadal variability of the Kuroshio Extension. Observations and an eddy-resolving model hindcast. J. Climate, 20, 2357-2377, doi:10.1175/JCLI4142.1.

Wijffels, S. E., M. M. Hall, T. Joyce, D. J. Torres, P. Hacker, and E. Firing, 1998: Multiple deep gyres of the western North Pacific: A WOCE section along 149°E. J. Geophys. Res., 103, 12,985-13,009, doi:10.1029/98JC01016.

Untangling the mystery of domoic acid events: A climate-scale perspective

Posted by mmaheigan 
· Thursday, August 3rd, 2017 

The diatom Pseudo-nitzchia produces a neurotoxin called domoic acid, which in high concentrations affects wildlife ranging from mussels and crabs to seabirds and sea lions, as well as humans. In humans, the effects of domoic acid poisoning can range from gastrointestinal distress to memory loss, and even death. Despite being studied in laboratories since the late 1980s, there is no consensus on the environmental conditions that lead to domoic acid events. These events are most frequent and impactful in eastern boundary current regions such as the California Current System, which is bordered by Washington, Oregon, and California. In Oregon alone, there have been six major domoic acid events: 1996, 1998-1999, 2001, 2002-2006, 2010, 2014-2015. McKibben et al. (2017) investigated the regulation of domoic acid at a climate scale to develop and test an applied risk model for the US West Coast” to read “McKibben et al. (2017) investigated the regulation of domoic acid at regional and decadal scales in order to develop and test an applied risk model for the impact of climate on the US West Coast. They used the PDO and ONI climate variability indices, averages of monthly and 3 month running means of SST anomaly values and variability to look at basin-scale ocean conditions. At a local scale, data were from zooplankton sampling every two to four weeks between 1996 to 2015 at hydrographic station offshore of Newport, OR. Additionally, the NOAA NCDC product “Daily Optimum Interpolation, Advanced Very High Resolution Radiometer Only, Version 2, Final+Preliminary SST” was used to obtain the monthly SST anomaly metric, based on combined in situ and satellite data.

 

(A) Warm and cool ocean regimes, (B) local SST anomaly, and (C and D) biological response. (A) PDO (red or blue vertical bars) and ONI (black line) indices; strong (S) to moderate (M) El Nino (+1) and La Nina (−1) events are labeled. (B) SST anomaly 20 nm off central OR. (C) The CSR anomaly 5 nm off central OR. (D) Monthly OR coastal maximum DA levels in razor clams (vertical bars); horizontal black line is the 20-ppm closure threshold. Black line in D shows the spring biological transition date (right y axis). At the top of the figure, black boxes indicate the duration of upwelling season each year; red vertical bars indicate the timing of annual DA maxima in relationship to upwelling. Gray shaded regions are warm regimes based on the PDO. Dashed vertical lines indicate onset of the six major DA events. The September 2014 arrival of the NE Pacific Warm Anomaly (colloquially termed “The Blob”) to the OR coastal region is labeled on B. “X” symbols along the x axes indicate that no data were available for that month (B–D).

Their findings show that these events have occurred when there is advection of warmer water masses onto the continental shelf from southern or offshore areas. When the warm phase of the Pacific Decadal Oscillation (PDO) and El Niño coincide, the effect is additive. In the warm regime years, there is a later spring biological transition date, weaker alongshore currents, elevated water temperatures, and plankton communities are dominated by subtropical rather than subarctic species. The authors also note relative differences between the prevalence and phenology of domoic acid events in OR, CA and WA, which warrants further study via regional-scale modeling. Overall, this research shows a clear and enhanced risk of toxicity in shellfish during warm phases of natural climate oscillations. If predictions of more extreme warming come to bear, this would potentially lead to increased DA event intensity and frequency in coastal zones around the globe. This will not only affect wildlife, but may cause significant closures of economically important fisheries (e.g., Dungeness crab, anchovy, mussel, and razor clam), which would impact local communities and native populations.

 

Authors:
Morgaine McKibben (Oregon State Univ., NOAA Northwest Fisheries Science Center)
William Peterson (NOAA Northwest Fisheries Science Center)
Michelle Wood (Univ. Oregon)
Vera L. Trainer (NOAA Northwest Fisheries Science Center)
Matthew Hunter (Oregon Dept. Fish & Wildlife)
Angelicque E. White (Oregon State Univ.)

Impact of ENSO on biogeochemistry and lower trophic level response in the California Current System

Posted by mmaheigan 
· Thursday, February 16th, 2017 

El Niño events are one of the “most spectacular instances of interannual variability in the ocean” with “profound consequences for climate and the ocean ecosystem” (Cane 1986). Perturbations in the atmosphere directly influence the ocean with long-term effects on environmental variability in the tropical Pacific Ocean as the El Niño-Southern Oscillation (ENSO) shifts between El Niño, neutral, and La Niña states on a timescale of two to seven years. On longer timescales, teleconnections from the tropics to extratropical regions drive Pacific decadal variability, and these can be both oceanic and atmospheric in nature. Mid-latitude variability of the Pacific Decadal Oscillation (PDO) has been associated with ENSO (e.g., Newman et al. 2003) and is distinguished from ENSO in part by its multidecadal timescale (20-30 years; 50 years). The PDO is dependent upon ENSO as a response to the combined effects of atmospheric noise (Newman et al. 2003), as well as the asymmetry of the ENSO cycle (Rodgers et al. 2004). Therefore, when discussing decadal variability of the northeast Pacific, we are referring to the delayed impacts of ENSO.

Ecosystem impacts of northeast Pacific variability

Given the complex influence of tropical climate on northeast Pacific ecosystems, there is significant overlap between ENSO signals and higher frequency modes of the PDO Index. It is widely recognized that interactions between these two climate modes drive substantial ecosystem variability on a range of time and space scales. Large regime shifts in the North Pacific that have reverberated throughout the ecosystem, from physics to fish, are recurring patterns now associated with low-frequency changes in sea surface temperature (SST) that characterize the PDO (e.g., Mantua et al. 1997). Some of the higher-frequency fluctuations in ecosystem variables of the northeast Pacific that have not been successfully attributed to PDO or ENSO are now thought to be driven by an intermediate mode of variability called the North Pacific Gyre Oscillation (NPGO). While the PDO is characterized as the first empirical orthogonal function (EOF) of SST, NPGO is defined as the first EOF of both SST and sea surface height (SSH) anomalies (Di Lorenzo et al. 2008). Compared to PDO and ENSO, NPGO is more closely tied to variations in salinity, nutrient upwelling, and chlorophyll a (chl-a) in the long-running California Cooperative Oceanic Fisheries Investigations (CalCOFI) time-series. DiLorenzo et al. (2008) suggest that major ecosystem regime shifts require a simultaneous and opposite sign reversal of the NPGO and PDO, as was seen shortly after the massive ENSO event of 1997/98, and all three indices relate back to dynamics in the tropical Pacific. The struggle is to understand how these low- to high(er)-frequency modes of variability in the climate and physics drive fluctuations in biogeochemistry and coastal ecology.

As discussed by Jacox et al. (this post), there is an expected or canonical set of physical conditions associated with ENSO in the California Current System (CCS). This physical response to ENSO generally includes: 1) changes in surface wind stress that alter the strength of coastal upwelling and downwelling; 2) remote oceanic forcing by coastally trapped waves that propagate poleward along the US West Coast and modify thermocline depth and coastal stratification; and 3) changes to alongshore advection (Jacox et al., this post). The ecological response of the coastal marine environment includes changes in primary production and the community composition of plankton and higher trophic levels that can be directly or more subtly related to these physical factors. Primary production is driven by vertical nutrient flux to well-lit surface waters; nutrient supply is related to upwelling magnitude, upwelling source depth, and nutrient concentrations at the source depth. ENSO-related processes are also important for interannual and seasonal variability of oxygen concentrations and carbonate biogeochemistry on the Washington and Oregon Shelves (Siedlecki et al. 2015). In this article, we highlight some of the modeling and observational studies that have successfully attributed ENSO-like variability to specific impacts on the biogeochemistry and lower-trophic level organisms of the northeast Pacific and CCS.

 

Carbon dioxide

Numerical models are widely employed to diagnose climatic forcing of the physical and biogeochemical conditions of the northeast Pacific. For instance, using a fully coupled ocean and biogeochemical model, Xiu and Chai (2014) found that after accounting for atmospheric effects, the air-sea flux and resulting pCO2 of sea water in the Pacific was significantly correlated (0.6) to the Multivariate ENSO Index (MEI) with a lag of ten months. Similarly, Wong et al. (2010) found that sea surface pCO2 was significantly correlated with the MEI in the northeast Pacific. Biogeochemical models of different complexity have also highlighted the connection between PDO and the interannual variability of air-sea CO2 fluxes (e.g., McKinley et al. 2006). These studies also demonstrate that the individual components controlling surface ocean pCO2 in the northeast Pacific respond to PDO with significant amplitudes, but that their combined influence has a relatively small effect on the CO2 fluxes in this region. Xiu and Chai (2014) showed that the dominant driver of North Pacific pCO2 variability is anthropogenic CO2, whereas air-sea CO2 flux is more closely correlated with the PDO and the NPGO.

 

Nutrients and chlorophyll

In the coastal regions of the northeast Pacific, such as the CCS, ENSO significantly impacts the nutrient supply due to modifications of upwelling and source waters mentioned above (Jacox et al., this post). At the peak of the El Niño season in December-January, Frischknecht et al. (2016) found a pattern in the development of chlorophyll events through a modeling study focused on the CCS. Around the onset of the El Niño year, chlorophyll anomalies were consistently low. This pattern was even more pronounced during the spring of the following year. In spring of the second year (i.e. with the onset of the upwelling season), all events shared the development of a strong negative chlorophyll anomaly. Frischknecht et al. (2016) attributed this phenomenon to a persistent lack of nutrients to support production driven by a combination of physical mechanisms impacting the thermocline (Jacox et al. 2015; 2016; this post) and light limitation at the onset of the upwelling season. Consequently, El Niño events disrupt the biogeochemical cycling in these systems for months, even years, after the event is over. The observations in Oregon, from the Newport line in Fisher et al. (2015), detail the nitrate anomalies from 1995 to 2015, and the nitrate anomalies remain negative long after the Niño-3.4 SST anomaly suggested that the event was over. This may contribute to the success surrounding seasonal forecast systems like J-SCOPE, in which forecasts of biogeochemical parameters (e.g., bottom oxygen) outperformed those of physical variables (e.g., SST) in terms of predictive skill (Siedlecki et al. 2016).

Oxygen and carbon

The relationship between ENSO and nutrient availability from source waters can serve as an analog for oxygen and carbon content. We would expect from observed stoichiometry that when nutrients are low, oxygen is relatively high and carbon is low. In California, this has been documented: El Niño events correlate to higher oxygen and pH, while La Niña events are correlated with lower oxygen and pH (e.g., Nam et al. 2011). In the northern CCS along the Washington and Oregon coasts, the interannual variability in oxygen content of source waters has been correlated to NPGO more than ENSO (Peterson et al. 2013). Consistent with these findings, oxygen has been increasing since 2010 and aragonite saturation state (a measure of the availability of carbonate ion to calcifying organisms) has been elevated in 2015-2016 relative to the year prior in both Oregon and California (McClatchie et al. 2016).

 

Primary production & particle export

As an eastern boundary upwelling region, the CCS is among the most productive in the world in terms of primary production and fisheries. The suppression of nutrient availability described above can be thought of as reduced “upwelling efficacy” that leads to reduced primary production in the CCS, while La Niña often has the opposite effect due to associated increases in the upwelling efficacy (Jacox et al. 2015). In the southern CCS, the 1997/1998 El Niño led to a significant deepening of the nutricline, with the strongest effects along CalCOFI Line 80, and a pronounced regional reduction of primary production (Bograd and Lynn 2001). The uptake of silicon increased in central California (Santa Barbara Channel) during the onset of the 1997 event, suggesting that diatoms were major drivers of the primary productivity prior to the 1998 spring season when overall productivity was reduced in response to density surface adjustments (Shipe and Brzezinski 2003). Despite reductions in surface layer primary productivity in response to the El Niño, export ratios of particulate organic carbon and particulate organic nitrogen increased during the spring of 1998 relative to the 1994-1997 period, while biogenic Si flux decreased in response to the El Niño (Shipe et al. 2002). This counterintuitive result appears to be due to an increase in particulate material exported to depth. By 1999, ratios of Si/N and Si/C had not recovered to pre-El Nino conditions.

 

Phytoplankton community composition

Warmer waters and changes in nutrient supply associated with ENSO can lead to phytoplankton community shifts such as an influx of coccolithophores or an increase in harmful algal blooms (HABs). The most common harmful algal bloom organism in the CCS is the diatom genus Pseudo-nitzschia. McCabe et al. (2016) recently observed a link between the Oceanic Niño Index (ONI), the Pseudo-nitzschia growth rate anomaly determined from temperature-growth relationships, and domoic acid levels in razor clams over a 16-year period (Figure 1), implicating El Niño-driven warming in the unprecedented 2015 HAB along the US West Coast. Similarly, McKibben et al. (2017) linked warm phases of the PDO and ONI to domoic acid in shellfish in the northern CCS. The toxic blooms off Newport in 2015 were the most prolonged (late-April through October 2015) and among the most toxic ever observed off Oregon (Du et al. 2015; McKibben et al. 2017). Conversely, Santa Barbara Basin sediment trap data showed no significant correlation between a 15-year record of domoic acid levels and PDO, NPGO, or ENSO indices; however, there was a strong change point in the frequency and toxicity of these blooms following the 1997/1998 ENSO (Sekula-Wood et al. 2011).

Figure 1. Records of razor clam toxicity and the potential growth rate anomaly for Pseudo-nitzschia spp. are plotted below the Oceanic Niño Index (gold = El Niño, blue = La Niña, gray = neutral) to illustrate the association between ENSO events and harmful algal blooms in the northern CCS. The potential for Pseudo–nitzschia growth does not always coincide with records of high domoic acid in shellfish, e.g., 1997 El Niño. Figure adapted from McCabe et al. (2016).

 

Zooplankton community composition

Off the Oregon coast, a 21-year time-series of fortnightly hydrography and plankton sampling of shelf and slope waters showed that the water masses (and thus the plankton) that dominate shelf and slope waters vary seasonally, interannually, and on decadal scales. Thus, it is a simple matter to track the timing of summer or winter arrival, ENSO events, and changes in sign of the PDO (Figure 2). During summer months, northerly winds drive surface waters offshore (Ekman transport), which are replaced by the upwelling of cold nutrient-rich waters that penetrate the continental shelf and fuel high primary production. Northerly winds also enhance the southward transport of water (and plankton) from the coastal Gulf of Alaska into the coastal northern CCS, and these species are referred to as ‘cold water’ or ‘northern species.’ During winter, the winds reverse and the poleward Davidson current transports warm coastal water from southern California to the northern CCS, bringing with it ‘southern species’ of plankton. On longer timescales (5-10 years), cold-water, northern copepods are largely replaced by warm-water, southern copepods during El Niño events (Fisher et al. 2015) and during the positive phase of the PDO (Keister et al. 2011). Incorporating the physiological response of these zooplankton groups into biogeochemical-ecosystem models (in addition to the effects of physical transport) will be essential for advancing our predictive capacity of plankton communities in the CCS.

Figure 2. Monthly time series of the Pacific Decadal Oscillation and Oceanic Niño Index (upper) and monthly-averaged biomass anomalies of northern copepods (middle) and southern copepods (lower). Note the high coherence between the PDO and ONI with the copepod time series – positive anomalies of northern copepods are correlated with negative PDO and ONI; positive anomalies of southern copepods are correlated with positive PDO and ONI.

 

Predicting ecosystem response to ENSO: Now and in the future

State-of-the-art models, in situ measurements, and available satellite observations are all required to adequately characterize short- and long-term physical dynamics associated with ENSO and Pacific decadal variability. Seasonal-to-interannual forecasting of the ecosystem response to ENSO in the CCS and throughout the northeast Pacific will depend on our understanding of how interannual climate variability alters ocean biogeochemistry and productivity at the base of the food web, and therefore how predictive models should be modified to capture the dynamic range introduced by these anomalous events. Unusual warm water anomalies, as observed during large ENSO events, may serve as important analogs for assessing the impacts of long-term warming on the pelagic ecosystem of the CCS. Regional simulations suggest similarities between the physical drivers leading to biogeochemical variability from ENSO and those in projected future upwelling systems (Rykaczewski and Dunne 2010). Further exploration of the mechanisms and predictive skill of forecasts on seasonal timescales will enhance our understanding and improve our projections further into the future. Global climate models are unable to anticipate anomalous warming events such as major ENSO events. As such, they are unable to detect large-scale events related to shifts in the distribution of pelagic species or track ecological changes associated with such events. Furthermore, the evaluation of model-based forecasts and projections of ecosystem variations and changes across timescales requires that long-term physical, biogeochemical, and ecological observation programs are maintained and others initiated. High-resolution modeling approaches for forecasts and projections should also be prioritized, so that ecosystem impacts of future climate anomalies can be anticipated and understood in greater detail.

 

Authors

Clarissa Anderson (Scripps Institution of Oceanography)
Samantha Siedlecki (University of Washington)
Cecile Rousseaux (NASA Goddard Space Flight Center, Universities Space Research Association)
Brian Powell (University of Hawaii, Manoa)
Bill Peterson (NOAA Northwest Fisheries Science Center)
Chris Edwards (University of California, Santa Cruz)

References

Bograd, S. J., & Lynn, R. J. (2001). Physical‐biological coupling in the California Current during the 1997–99 El Niño‐La Niña Cycle. Geophysical Research Letters, 28(2), 275-278.

Cane, M. A., S. E. Zebiak, and S. C. Dolan, 1986: Experimental forecasts of El Niño. Nature 321, 827–832, doi:10.1038/321827a0.

Di Lorenzo, E., and Coauthors, 2008: North Pacific Gyre Oscillation links ocean climate and ecosystem change. Geophys. Res. Lett., 35, doi:10.1029/2007gl032838.

Du, X., W. Peterson, and L. O’Higgins, 2015: Interannual variations in phytoplankton community structure in the northern California Current during the upwelling seasons of 2001-2010. Mar. Ecol. Prog. Ser., 519, 75-87, doi: 10.3354/meps11097.

Fisher, J. L., W. T. Peterson, and R. Rykaczewski, 2015: The impact of El Niño events on the pelagic food chain in the northern California Current. Global Change Bio., 21, 4401-4414, doi:10.1111/gbc.13054.

Frischknecht, M., M. Münnich, and N. Gruber, 2016: Local atmospheric forcing driving an unexpected California Current System response during the 2015–2016 El Niño, Geophys. Res. Lett., 43, doi:10.1002/2016GL071316.

Jacox, M. G., J. Fiechter, A. M. Moore, and C. A. Edwards, 2015: ENSO and the California Current coastal upwelling response. J. Geophys. Res., 120, 1691–1702, doi: 10.1002/2014JC010650..

Jacox, M., E. L. Hazen, K. D. Zaba, D. L. Rudnick, C. A. Edwards, A. M. Moore, and S. J. Bograd, 2016: Impacts of the 2015–2016 El Niño on the California Current System: Early assessment and comparison to past events. Geophys. Res. Lett. 43, 7072-7080, doi:10.1002/2016GL069716.

Keister, J. E., E. Di Lorenzo, C. A. Morgan, V. Combes, and W. T. Peterson, 2011: Zooplankton species composition is linked to ocean transport in the Northern California Current. Glob. Change Bio., 17, 2498-2511, doi: 10.1111/j.1365-2486.2010.02383.x.

Liu, Z., and M. Alexander, 2007: Atmospheric bridge, oceanic tunnel, and global climatic teleconnections. Rev. Geophy., 45, doi: 10.1029/2005RG000172.

Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C. Francis, 1997: A Pacific interdecadal climate oscillation with impacts on salmon production. Bull. Amer. Meteorol. Soc., 78, 1069–1079, doi: 10.1175/1520-0477(1997)078<1069:APICOW>2.0.CO;2.

McCabe, R. M., and Coauthors, 2016: An unprecedented coastwide toxic algal bloom linked to anomalous ocean conditions. Geoph. Res. Lett., 43, doi: 10.1002/2016GL070023.

McClatchie, S., A. R. Thompson, S. R. Alin, S. Siedlecki, W. Watson, and S. J. Bograd, 2016: The influence of Pacific Equatorial Water on fish diversity in the southern California Current System. J. Geophy. Res., 121, 6121-6136, doi: 10.1002/2016JC011672.

McKibben, S. M., W. Peterson, M. Wood, V. L. Trainer, M. Hunter, and A. E. White, 2017: Climatic regulation of the neurotoxin domoic acid. Proc. Nat. Acad. Sci., 114, 239-244, doi: 10.1073/pnas.1606798114.

Mckinley, G.A., and Coauthors, 2006: North Pacific carbon cycle response to climate variability on seasonal to decadal timescales. J. Geophy. Res., 111, doi: 10.1029/2005JC003173.

Nam, S., H. J. Kim, and W. Send, 2011: Amplification of hypoxic and acidic events by La Niña conditions on the continental shelf off California. Geophy. Res. Lett., 38, doi: 10.1029/2011GL049549.

Newman, M., G. P. Compo, and M. A. Alexander, 2003: ENSO-forced variability of the Pacific decadal oscillation. J. Climate, 16, 3853-3857, doi: 10.1175/1520-0442(2003)016<3853:EVOTPD>2.0.CO;2.

Peterson, J. O., C. A. Morgan, W. T. Peterson, and E. Di Lorenzo, 2013: Seasonal and interannual variation in the extent of hypoxia in the northern California Current from 1998–2012. Limnol. Oceanogr., 58, 2279-2292, doi: 10.4319/lo.2013.58.6.2279.

Rodgers, K. B., P. Friederichs, and M. Latif, 2004: Tropical Pacific decadal variability and its relation to decadal modulations of ENSO. J. Climate, 17, 3761-3774, doi: 10.1175/1520-0442(2004)017<3761:TPDVAI>2.0.CO;2.

Rykaczewski, R. R., and J. P. Dunne, 2010: Enhanced nutrient supply to the California Current Ecosystem with global warming and increased stratification in an earth system model. Geophy. Res. Lett., 37, doi: 10.1029/2010GL045019.

Sekula-Wood, E., C. Benitez-Nelson, S. Morton, C. Anderson, C. Burrell, and R. Thunell, 2011: Pseudo-nitzschia and domoic acid fluxes in Santa Barbara Basin (CA) from 1993 to 2008. Harmful Algae, 10, 567–575, doi: 10.1016/j.hal.2011.04.009.

Shipe, R. F., Passow, U., Brzezinski, M. A., Graham, W. M., Pak, D. K., Siegel, D. A., & Alldredge, A. L. (2002). Effects of the 1997–98 El Nino on seasonal variations in suspended and sinking particles in the Santa Barbara basin. Progress in Oceanography, 54(1), 105-127.

Shipe, R. F., and M. A. Brzezinski, 2003: Siliceous plankton dominate primary and new productivity during the onset of El Niño conditions in the Santa Barbara Basin, California. J. Mar. Sys., 42, 127-143, doi: 10.1016/S0924-7963(03)00071-X.

Siedlecki, S. A., N. S. Banas, K. A. Davis, S. Giddings, B. M. Hickey, P. MacCready, T. Connolly, and S. Geier, 2015: Seasonal and interannual oxygen variability on the Washington and Oregon continental shelves. J. Geophy. Res., 120. 608-633, doi: 10.1002/2014JC010254.

Siedlecki, S. A., I. C. Kaplan, A. J. Hermann, T. T. Nguyen, N. A. Bond, J. A. Newton, G. D. Williams, W. T. Peterson, S. R. Alin, and R. A. Feely, 2016: Experiments with seasonal forecasts of ocean conditions for the northern region of the California Current upwelling system. Sci. Rep., 6, 27203, doi: 10.1038/srep27203.

Valsala, V., S. Maksyutov, M. Telszewski, S. Nakaoka, Y. Nojiri, M. Ikeda, and R. Murtugudde, 2012: Climate impacts on the structures of the North Pacific air-sea CO2 flux variability. Biogeosci., 9, 477, doi: 10.5194/bg-9-477-2012.

Xiu, P., and F. Chai, 2014: Variability of oceanic carbon cycle in the North Pacific from seasonal to decadal scales. J. Geophy. Res.,119, 5270-5288, doi: 10.1002/2013JC009505.

 

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