Archive for eddy

Swirling Currents: How Ocean Mesoscale Affects Air-Sea CO2 Exchange

Posted by mmaheigan 
· Friday, October 25th, 2024 

Due to a sparsity of in‐situ observations and the computational burden of eddy‐resolving global simulations, there has been little analysis on how mesoscale processes (e.g., eddies, meanders—lateral scales of 10s to 100s km) influence air‐sea CO2 fluxes from a global perspective. Recently, it became computationally feasible to implement global eddy‐resolving [O (10) km] ocean biogeochemical models. Many questions related to the influence of mesoscale motions on CO2 fluxes remain open, including whether ocean eddies serve as hotspots for CO2 sink or source in specific dynamic regions.

A recent study in Geophysical Research Letters investigated the contribution of ocean mesoscale variability to air-sea CO2 fluxes by analyzing the CO2 flux anomaly within the mesoscale band using a coarse-graining approach in a global eddy-resolving biogeochemical simulation. We found that in eddy-rich mid-latitude regions, ocean mesoscale variability can contribute to over 30% of the total CO2 flux variability. The cumulative net CO2 flux associated with mesoscale motions is on the order of 105 tC per year. The global pattern of cumulative mesoscale-related CO2 flux exhibits significant spatial heterogeneity, with the highest values in western boundary currents, the Antarctic Circumpolar Current, and the equatorial Pacific. The local distribution of cumulative mesoscale-related CO2 flux displays zonal bands alternate between positive (a net source) and negative (a net sink) due to the meandering nature of ocean mesoscale currents, which is related to local relative vorticity and the background cross-stream pCO2 gradient.

Figure caption. Mesoscale (<nominal 2 degree) contribution to air‐sea CO2 flux (F<2°CO2)in the model. (a)–(d) Monthly time series of F<2°CO2 (black lines) and cumulative F<2°CO2 (green/red solid lines) in four locations marked in (e). Dashed lines are the least squares regression of cumulative flux for the period 1982–2000; slopes are indicated in the bottom left; (e) Blue colors imply a CO₂ sink, and red colors represent a source. The figure shows the global distribution of the regressed slopes of cumulative F<2°CO2. Units are converted from mol m-2 per year to kg of CO2 per year using the atomic mass of CO2. This figure shows significant spatial heterogeneity of mesoscale-modulated CO2 flux, showing contributions to both CO₂ sources and sinks across different regions of the ocean, with a magnitude on the order of 105 tC per year.

 

Authors
Yiming Guo (Yale University; now at Woods Hole Oceanographic Institution)
Mary-Louise Timmermans (Yale University)

A close-up view of biomass controls in Southern Ocean eddies

Posted by mmaheigan 
· Thursday, August 20th, 2020 

Southern Ocean biological productivity is instrumental in regulating the global carbon cycle. Previous correlative studies associated widespread mesoscale activity with anomalous chlorophyll levels. However, eddies simultaneously modify both the physical and biogeochemical environments via several competing pathways, making it difficult to discern which mechanisms are responsible for the observed biological anomalies within them. Two recently published papers track Southern Ocean eddies in a global, eddy-resolving, 3-D ocean simulation. By closely examining eddy-induced perturbations to phytoplankton populations, the authors are able to explicitly link eddies to co-located biological anomalies through an underlying mechanistic framework.

Figure caption: Simulated Southern Ocean eddies modify phytoplankton division rates in different directions of depending on the polarity of the eddy and background seasonal conditions. During summer anticyclones (top right panel) deliver extra iron from depth via eddy-induced Ekman pumping and fuel faster phytoplankton division rates. During winter (bottom right panel) the extra iron supply is eclipsed by deeper mixed layer depths and elevated light limitation resulting in slower division rates. The opposite occurs in cyclones.

In the first paper, the authors observe that eddies primarily affect phytoplankton division rates by modifying the supply of iron via eddy-induced Ekman pumping. This results in elevated iron and faster phytoplankton division rates in anticyclones throughout most of the year. However, during deep mixing winter periods, exacerbated light stress driven by anomalously deep mixing in anticyclones can dominate elevated iron and drive division rates down. The opposite response occurs in cyclones.

The second paper tracks how eddy-modified division rates combine with eddy-modified loss rates and physical transport to produce anomalous biomass accumulation. The biomass anomaly is highly variable, but can exhibit an intense seasonal cycle, in which cyclones and anticyclones consistently modify biomass in different directions. This cycle is most apparent in the South Pacific sector of the Antarctic Circumpolar Current, a deep mixing region where the largest biomass anomalies are driven by biological mechanisms rather than lateral transport mechanisms such as eddy stirring or propagation.

It is important to remember that the correlation between chlorophyll and eddy activity observable from space can result from a variety of physical and biological mechanisms. Understanding the nuances of how these mechanisms change regionally and seasonally is integral in both scaling up local observations and parameterizing coarser, non-eddy resolving general circulation models with embedded biogeochemistry.

Authors:
Tyler Rohr (Australian Antarctic Partnership Program, previously at MIT/WHOI)
Cheryl Harrison (University of Texas Rio Grande Valley)
Matthew Long (National Center for Atmospheric Research)
Peter Gaube (University of Washington)
Scott Doney (University of Virginia)

Estimating the large-scale biological pump: Do eddies matter?

Posted by mmaheigan 
· Wednesday, December 4th, 2019 

One factor that limits our capacity to quantify the ocean biological carbon pump is uncertainty associated with the physical injection of particulate (POC) and dissolved (DOC) organic carbon to the ocean interior. It is challenging to integrate the effects of these pumps, which operate at small spatial (<100 km) and temporal (<1 month) scales. Previous observational and fine-scale modeling studies have thus far been unable to quantify these small-scale effects. In a recent study published in Global Biogeochemical Cycles, authors explored the influence of these physical carbon pumps relative to sinking (gravity-driven) particles on annual and regional scales using a high-resolution (2 km) biophysical model of the North Atlantic that simulates intense eddy-driven subduction hotspots that are consistent with observations.

Figure 1: North Atlantic idealized double gyre ocean biophysical model. Top: Sea surface temperature, surface chlorophyll and mixed-layer depth during the spring bloom (March 21). Bottom: total export of organic carbon (POC+DOC) at 100 and individual contributions from the gravitational (particle sinking) and subduction (mixing, eddy advection and Ekman pumping) pumps for one day during the spring bloom (March 21) and averaged annually. Physical subduction hotspots visible on the daily export contribute little to the annual export due to strong compensation of upward and downward motions.

The authors showed that eddy dynamics can transport carbon below the mixed-layer (500-1000 m depth), but this mechanism contributes little (<5%) to annual export at the basin scale due to strong compensation between upward and downward fluxes (Figure 1). Additionally, the authors evidenced that small-scale mixing events intermittently export large amounts of suspended DOC and POC.

These results underscore the need to expand the traditional view of the mixed-layer carbon pump (wintertime export of DOC) to include downward mixing of POC associated with short-lived springtime mixing events, as well as eddy-driven subduction, which can contribute to longer-term ocean carbon storage. High-resolution measurements are needed to validate these model results and constrain the magnitude of the compensation between upward and downward carbon transport by small-scale physical processes.

 

Authors:
Laure Resplandy (Princeton University)
Marina Lévy (Sorbonne Université)
Dennis J. McGillicuddy Jr. (WHOI)

When it comes to carbon export, the mesoscale matters

Posted by hbenway 
· Tuesday, September 11th, 2018 

Figure 1. Difference in annual mean carbon export (ΔPOC flux) between a high resolution (0.1º, Hi-res) and standard resolution (1º, Analog) global climate model simulation using the CESM model. Highlighted regions show areas where vertical (purple boxes) and horizontal (red boxes) changes in nutrient transport drive increases or decreases in export, respectively.

Most Earth System models (ESMs) that are used to study global climate and the carbon cycle do not resolve the most energetic scales in the ocean, the mesoscale (10-100 km), encompassing eddies, coastal jets, and other dynamic features strongly affecting nutrient delivery, productivity, and carbon export. This prompts the question: What are we missing in climate models by not resolving the mesoscale?

Authors of a recent study published in Global Biogeochemical Cycles conducted a comparative analysis of the importance of mesoscale features in biological production and associated carbon export using standard resolution (1°) and mesoscale-resolving (0.1°) ESM simulations. The mesoscale-resolving ESM yielded only a ~2% reduction in globally integrated export production relative to the standard resolution ESM. However, a closer look at the local processes driving export in different basins revealed much larger, compensating differences (Fig. 1). For example, in regions where biological production is driven by natural iron fertilization from shelf sediment sources (Fig. 2), improved representation of coastal jets in the higher-resolution ESM reduces the cross-shelf iron delivery that fuels production (red boxes in Fig. 1). Resolving mesoscale turbulence further reduces the spatial extent of blooms and associated export, yielding a more patchy distribution than in the coarse resolution models. Together, these processes lead to a reduction in export in the Argentine Basin, one of the most productive regions on the planet, of locally up to 50%. In contrast, resolving the mesoscale results in enhanced export production in the Subantarctic (purple box in Fig. 1), where the mesoscale model resolves deeper, narrower mixed layer depths that support stronger nutrient entrainment, in turn enhancing local productivity and export.

Figure 2. An iron-driven plankton bloom structured by mesoscale features in the South Atlantic. Left is simulated dissolved iron (Fe), the limiting nutrient for this region, and right is iron in all phytoplankton classes, a proxy for biomass (phytoFe, shown in log10 scale), on January 11, the height of the bloom. Plankton blooms in the Subantarctic Atlantic are fueled by horizontal iron transport off coastal and island shelves and vertical injection from seamounts, whereas farther south in the Southern Ocean, winter vertical mixing is the primary driver of iron delivery. Mesoscale circulation, largely an unstructured mix of interacting jets and vortices, strongly affects the location and timing of carbon production and export. Click here for an animation.

In regions with very short productivity seasons like the North Pacific and Subantarctic, internally generated mesoscale variability (captured in the higher resolution ESM) yields significant interannual variation in local carbon export. In these regions, a few eddies, filaments or more amorphous mesoscale features can structure the entire production and export pattern for the short bloom season. These findings document the importance of resolving mesoscale features in ESMs to more accurately quantify carbon export, and the different roles mesoscale variability can play in different oceanographic settings.

Determining how to best sample these mesoscale turbulence-dominated blooms and scale up these measurements to regional and longer time means, is an outstanding joint challenge for modelers and observationalists. A key piece is obtaining the high temporal and spatial resolution data sets needed for validating modeled carbon export in bloom regions strongly impacted by mesoscale dynamics, which represent a large portion of the global carbon export.

Authors
Cheryl Harrison (NCAR, University of Colorado Boulder)
Matthew Long (NCAR)
Nicole Lovenduski (University of Colorado Boulder)
J. Keith Moore (University of California Irvine)

Hotspots of biological production: Submesoscale changes in respiration and production

Posted by mmaheigan 
· Thursday, April 26th, 2018 

The biological pump is complex and variable. To better understand it, scientists have often focused on variations in biological parameters such as fluorescence and community structure, and have less often observed variations in rates of production. Production rates can be estimated using oxygen as a tracer, since photosynthesis produces oxygen and respiration consumes it. In a recent article in Deep Sea Research Part I, the authors presented high-resolution maps of oxygen in the upper 140 m of the ocean in the subtropical and tropical Atlantic, produced from a towed undulating instrument. This provides a synoptic, high-resolution view of oxygen anomalies in the surface ocean. These data reveal remarkable hotspots of biological production and respiration co-located with areas of elevated fluorescence. These hotspots are often several kilometers wide (horizontal) and ~10 m long (vertical). They are preferentially associated with edges of eddies, but not all edges sampled contained hotspots. Although this study captures only two-dimensional glimpses of these hotspots, precluding formal calculations of production rates, likely estimates of source water suggest that many of these hotspots may actually be areas of enhanced respiration rather than enhanced photosynthesis. The paper describes a conceptual model of nutrients, new production, respiration, fluorescence, and oxygen during the formation and decline of these hotspots. These data raise intriguing questions–if the hotspots do indeed have substantially different rates of production and respiration than surrounding waters, then they could lead to significant changes in estimates of production in the upper ocean. Additionally, understanding the mechanisms that produce these hotspots could be critical for predicting the effects of climate change on the magnitude of the biological pump.

(a) Oxygen concentrations and (b) fluorescence at ~1 km resolution over 300 km from 15.13°N, 57.47°W to 12.30°N, 56.42° W, as measured by sensors attached to the (c) Video Plankton Recorder II. Note that no contouring was used for this plot – every pixel represents an actual data point. Figure modified from Stanley et al., 2017. VPR image photograph by Phil Alatalo.

Authors:
Rachel H. R. Stanley (Wellesley College)
Dennis J. McGillicuddy Jr. (WHOI)
Zoe O. Sandwith (WHOI)
Haley Pleskow (Wellesley College)

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.

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