Abstract
Ocean mesoscale eddies, characterized by substantial eddy kinetic energy (EKE), are ubiquitous throughout the global ocean and play an essential role in ocean circulation, climate, and biogeochemistry. In the North Pacific, high and variable EKE is primarily concentrated in the western Subtropical Gyre. In contrast, the EKE levels in the Subtropical Northeast Pacific are relatively lower. Nevertheless, the EKE in this region remains comparable to the local mean kinetic energy and exhibits significant variability across seasonal to interannual timescales. In this study, we investigated the decadal variability of EKE in the Subtropical Northeast Pacific using observational data from 1993 to 2024. Results reveal that the EKE in this region undergoes remarkable decadal variability with a significant period of 10–11 years. This variability is characterized by a monopole spatial pattern, with the largest amplitude centered northeast of the Hawaiian Archipelago, at approximately 154°W, 26°N. Additionally, the variability is also manifested by decadal changes in the amplitudes of both cyclonic and anticyclonic eddies. Mechanistically, the EKE decadal variability is primarily driven by decadal variations in baroclinic eddy available potential energy (EPE) to EKE conversion through vertical eddy density flux. These decadal variations in baroclinic instability are likely to originate from the Pacific Decadal Oscillation (PDO). The PDO is suggested first to modulate the eddy field of density, subsequently altering the baroclinic EPE to EKE conversion associated with baroclinic instability. Consequently, the EKE fluctuates correspondingly and exhibits significant decadal variability, with the PDO signal leading the observed EKE decadal variability by approximately 15 months. Given the vital role of eddies in the transport of heat and nutrients, the identified decadal variability of EKE is expected to cause significant decadal variations in the coastal ecosystem surrounding the Hawaiian Archipelago.
1 Introduction
Mesoscale processes, including coherent mesoscale eddies, meanders, and fronts, prevail in the global upper ocean (e.g., ; ; ). These processes, mostly in the form of coherent mesoscale eddies, connect oceanic large-scale and smaller-scale phenomena and play an essential role in ocean circulation, watermass formation, climate, and biogeochemistry (see ; ; ; for a review). In particular, mesoscale processes carry tremendous kinetic energy and significantly contribute to the global oceanic energy budget and energy cascade (e.g., ; ; ; ; ). The kinetic energy of mesoscale processes, i.e., the eddy kinetic energy (EKE), is reported to account for about 80% of the total kinetic energy (TKE) over the global ocean (e.g., ; ; ; ; ). Generally, the EKE is comparable to the mean kinetic energy (MKE) in strong current regions due to intense energy conversion via barotropic and baroclinic instabilities (e.g., ; ; ; ; ). In contrast, in the open ocean with weak currents, the EKE typically exceeds the MKE by one to two orders of magnitude (). All these highlight the essential role of mesoscale processes in the oceanic energy reservoir.
In the North Pacific, high EKE levels and large EKE variations are concentrated in the Subtropical Gyre, particularly two zonal bands in its western part (e.g., ; ; ; ; ). One is the Kuroshio Extension region with the highest EKE levels and largest variations, and the other is the Subtropical Countercurrent region in the south between 18°N and 25°N, as shown in Figures 1A, B. Remarkable EKE variabilities on seasonal to decadal time scales are observed in these two regions, and intense studies have been devoted to understanding these variabilities (e.g., ; ; ; ; ; ; ; ).
Figure 1
In contrast, the EKE in the eastern part of the North Pacific Subtropical Gyre, or the Subtropical Northeast Pacific, exhibits relatively smaller magnitude and weaker variations compared to that in the Kuroshio Extension and the Subtropical Countercurrent regions. However, the EKE is comparable to or larger than the local MKE in the Subtropical Northeast Pacific, as the latter is also weak (Figure 1C). It is also worth mentioning that documented that the Subtropical Northeast Pacific is populated with numerous mesoscale eddies, though less energetic. However, our understanding of the EKE variability here is limited. East of the Subtropical Northeast Pacific is the California Current System, where abundant mesoscale eddies with high EKE levels arising from coastal upwelling-induced baroclinic instability exist (e.g., ; ). These energetic eddies can propagate westward towards the Subtropical Northeast Pacific and influence the EKE in the ocean interior. More recently, reported that the EKE in the California Current System is projected to increase significantly under global warming. This suggests that the EKE in the Subtropical Northeast Pacific may experience enhanced eddy activity in the future.
Furthermore, high and variable EKE emerges in the western part of the Subtropical Northeast Pacific, specifically, the northeast of the Hawaiian Archipelago. documented that the EKE here exhibits significant interannual variability. They attributed the observed interannual variability to baroclinic instability associated with the vertical shear of zonal flow. Moreover, the interannual EKE variability is significantly correlated with the Pacific Decadal Oscillation (PDO; ; ), with EKE fluctuations lagging the PDO index by approximately 10–14 months. During the positive phase of the PDO, intensified vertical shear strengthens the baroclinic instability, leading to elevated EKE levels; conversely, the negative PDO phase is characterized by weakened instability and a corresponding reduction in EKE levels.
It is worth noting that the eddy activity and EKE variations have a profound impact on the coastal ecosystems of the California Current System and the Hawaiian Archipelago. In the California Current System, mesoscale eddies and the associated EKE play a crucial role in regulating coastal nutrient supply by modulating vertical exchange between subsurface and surface layers. Enhanced EKE is generally associated with increased upward nutrient flux, whereas reduced EKE tends to suppress vertical exchange and promote downwelling (e.g., ). Similarly, mesoscale eddies in the vicinity of the Hawaiian Archipelago enhance vertical nutrient supply in otherwise oligotrophic waters, leading to elevated primary production and biomass. These highlight the important role of EKE in regulating biogeochemical variability and upper-ocean processes in coastal and near-island regions (e.g., ; ). Understanding EKE variability is critical for assessing the impacts of eddies on coastal ecosystems of the California Current System and the Hawaiian Archipelago.
This study aims to improve our understanding of the low-frequency variability of EKE in the Subtropical Northeast Pacific, an area that has received limited attention. We will show in the following that the EKE here exhibits significant decadal variability that lags behind the PDO. The spatiotemporal characteristics of the EKE decadal variability are presented based on observations, and the mechanism for the variability is investigated by diagnosing the EKE tendency using the ARMOR3D and OMEGA3D datasets. The paper is organized as follows: Section 2 presents the data and methods; Section 3 describes the spatial and temporal characteristics of the decadal variability of EKE in the Subtropical Northeast Pacific; Section 4 explains the causes of the EKE decadal variability; The last section, Section 5, offers a summary and discussion.
2 Data and methods
2.1 Data
To identify cyclonic and anticyclonic eddies and to quantify their radius, amplitude, and number in the Subtropical Northeast Pacific, this study employed gridded SLA (sea level anomaly) data provided by Centre National d’Études Spatiales (CNES) and Collected Localisation Satellites (CLS), and distributed through the Copernicus Marine Environment Monitoring Service (CMEMS). The SLA fields are derived from optimal interpolation of Level-3 along-track observations collected from multiple satellite altimeter missions since 1993, ensuring consistent spatial and temporal coverage. The dataset provides daily SLA on a 1/8°×1/8° regular grid, referenced to a twenty-year climatological mean over the period 1993–2012. The delayed-time daily SLA data for 1993–2024 were obtained from:
https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_MY_008_047/services.
Temperature and salinity from the ARMOR3D reprocessed dataset were also used. This ARMOR3D product integrates satellite and in situ observations through regression and optimal interpolation techniques to reconstruct the ocean state (e.g., ). It is also distributed by the CMEMS and provides global temperature and salinity fields on a 1/8°×1/8° horizontal grid with 50 depth levels from the surface to the ocean bottom since 1993, at a weekly temporal resolution. The 1993–2024 weekly ARMOR3D temperature and salinity data were obtained from:
https://data.marine.copernicus.eu/product/MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012.
Both the horizontal and vertical quasi-geostrophic currents from the OMEGA3D dataset were employed to calculate the EKE and MKE and to diagnose EKE variability. The OMEGA3D dataset provides quasi-geostrophic currents based on the ARMOR3D temperature and salinity fields described above (e.g., ). In particular, the vertical velocity is estimated by solving a diabatic form of the Omega equation, with inputs from the ARMOR3D product and ERA-Interim surface fluxes. The dataset provides weekly horizontal and vertical velocity fields with a horizontal resolution of 1/4°×1/4°, covering depths from the surface to 1500 m since 1993. The vertical velocity w in the OMEGA3D dataset is considered reliable at distances of approximately 100 km from masked coastal areas and is suitable for studies of long-term variability (e.g., ; ). The 1993–2024 weekly OMEGA3D quasi-geostrophic current data were obtained from the CMEMS as well:
https://data.marine.copernicus.eu/product/MULTIOBS_GLO_PHY_W_3D_REP_015_007.
The monthly PDO index is obtained from the Japan Meteorological Agency. The 1993–2024 monthly PDO index data were downloaded from:
https://ds.data.jma.go.jp/tcc/tcc/products/elnino/decadal/pdo.html.
2.2 Methods
2.2.1 Decomposition of mean and eddy fields
A given variable (e.g., ) can be decomposed into a mean component and an eddy component as , where the overbar denotes the temporally averaged field and the prime represents the eddy field. A smoothing method can be employed to perform the decomposition. In this study, the mean field is obtained by applying a 9-month smoothing to . The eddy field is then calculated as the deviation of from . Additionally, to examine the impact of different smoothing windows on the EKE results, this study calculated and compared the regional mean EKE in the Subtropical Northeast Pacific during 1993–2024 using 7-, 8-, 9-, 10-, 11-, and 12-month smoothing windows. The results indicate that the regional mean EKE is not sensitive to these choices of smoothing windows, with only minor differences in magnitude (not shown). Overall, a 9-month smoothing window is suitable for this study.
2.2.2 Calculations of EKE and MKE
Following the application of a 9-month smoothing, the horizontal ocean current velocity, , is separated into mean and eddy components, denoted as and , respectively. The mean component, , represents the background flow, whereas the eddy component, , corresponds to the eddy field. The TKE per unit volume of seawater is further partitioned into MKE and EKE, expressed as follows (Equation 1):
where is the reference seawater density of 1027 kg/m3, and the horizontal velocity is obtained from the OMEGA3D dataset, which includes both geostrophic and ageostrophic components.
2.2.3 The EKE tendency equation
The EKE tendency equation is commonly employed to diagnose the EKE variability within a given volume of seawater. It describes the rate of EKE change with respect to time () and can be written as follows (Equation 2):
The term on the left-hand side represents the local tendency of EKE within the considered seawater volume. On the right-hand side, the first two terms, BTC1 and BTC2, are barotropic MKE to EKE conversions through momentum fluxes associated with the mean horizontal shear and the mean horizontal Reynolds stresses, respectively. The third term, vertical eddy density flux (VEDF), represents the baroclinic eddy available potential energy (EPE) to EKE conversion through vertical eddy density flux. The fourth term, CONV, denotes the convergence of EKE flux. The remaining terms, , , and , account for pressure work, external forcing (including wind stress and buoyancy fluxes), and viscous dissipation of EKE, respectively.
The BTC1, BTC2, and CONV terms are estimated based on the horizontal velocity fields from the OMEGA3D data, and are formulated as follows (Equations 3–6):
The is the eddy field of perturbation density, and the perturbation density is defined as , where the reference density is chosen as the time-mean and area-mean density in the study region. Note that the is equivalent to the eddy field of density (). The is calculated from the ARMOR3D data according to International Thermodynamic Equation of Seawater-2010 (e.g., ). In addition, the is the eddy field of vertical velocity from the OMEGA3D data.
However, the , , and terms are not evaluated in this study due to the absence of wind stress and buoyancy forcing data, as well as viscosity information, in the ARMOR3D and OMEGA3D datasets.
Notably, to ensure that the spatial grids of the ARMOR3D and OMEGA3D datasets match, the ARMOR3D data (1/8°×1/8°) were horizontally interpolated onto the 1/4°×1/4° grid of the OMEGA3D data using bilinear interpolation. Vertically, Akima interpolation was applied to both datasets to obtain values at 10 m intervals from the surface down to 100 m depth (e.g., ).
2.2.4 Eddy identification
Cyclonic and anticyclonic eddies are identified using the eddy detection and tracking algorithm developed by . This algorithm extracts eddy structures from SLA fields by identifying closed contours that meet predefined geometric constraints. Within each closed contour, the eddy center is determined as the local extremum of SLA. Based on the input SLA fields, the algorithm provides key eddy characteristics, including the center location, amplitude, and radius. In addition to these geometric properties, it also tracks eddies over time, allowing their temporal evolution and life cycles to be examined. The implementation of the eddy detection and tracking algorithm is publicly available at: https://github.com/jfaghm/OceanEddies.
3 Decadal variability of EKE in the subtropical Northeast Pacific
In this study, we take 18°N–36°N and 160°W–120°W as the study region to investigate low-frequency variability of EKE in the Subtropical Northeast Pacific (the black boxes in Figures 1A–C). The region captures the area where EKE values are comparable to local MKE and the ratio values are close to 1.0, as shown in Figure 1C. In contrast, in the North Pacific high latitude, the ratio values are much smaller than 1.0, while to the west of the study region, the EKE values are generally much larger than the local MKE values. The time series of regional mean monthly EKE in the study region between 1993 and 2024 is presented in Figure 2A. The EKE exhibits variability on seasonal and lower-frequency time scales. The seasonal variability of the EKE in the study region is shown in Figure 2B. Clearly, the EKE here has a well-defined seasonal cycle, with a maximum from April to June (spring) and a minimum from October to December (winter). This EKE seasonality resembles that in the Subtropical Countercurrent region to the west (e.g., ; ; ).
Figure 2
In addition to the seasonality, the EKE also exhibits remarkable low-frequency variability, which is the focus of this study. We further removed the seasonal cycle and the 1993–2024 linear trend from the monthly EKE time series and obtained the detrended monthly EKE anomalies. The result is offered in Figure 3A. Over 1993–2024, positive EKE anomalies mainly appeared in 1994–1995, 1997–1999, 2003–2005, and 2015–2019, while negative EKE anomalies primarily emerged in 1993, 1996, 2000–2002, 2006–2014, and 2020–2024. There are about 3 cycles in 32 years. A power spectral analysis was further performed on the EKE anomalies, and the result is demonstrated in Figure 3B. Clearly, the EKE has a significant period of 128 months, or 10–11 years, passing the 95% confidence level. It demonstrates that the EKE in the Subtropical Northeast features a significant decadal variability.
Figure 3
To obtain the spatial pattern of the EKE decadal variability, we regressed the Subtropical Northeast Pacific EKE anomalies onto the normalized, detrended regional mean EKE anomalies shown in Figure 3A. The spatial distribution of regression coefficients is offered in Figure 3C. The EKE decadal variability features a monopole pattern in the Subtropical Northeast Pacific. The largest EKE amplitude is centered in the northeast of the Hawaiian Archipelago at about 154°W, 26°N.
In addition, the EKE decadal variability is manifested in the decadal variations of the mean amplitude of mesoscale eddies in the Subtropical Northeast Pacific. Time series of mean amplitude of cyclonic eddies and anticyclonic eddies in the study region during 1993–2024 are presented in Figures 4A, B, respectively. Also shown is the regional mean EKE. Both the mean amplitude of cyclonic eddies and anticyclonic eddies exhibit low-frequency variations consistent with the EKE. The correlation coefficient between the cyclonic eddies’ mean amplitude and EKE is 0.50, and that between the cyclonic eddies’ mean amplitude and EKE is 0.72. It demonstrates that the EKE decadal variability is manifested by the decadal variations of amplitudes of cyclonic and anticyclonic eddies.
Figure 4
4 Mechanisms
4.1 Primary driver of decadal variability: VEDF
According to previous studies (e.g., ; ; ; ; ; ; ), EKE is mainly generated through baroclinic and barotropic instabilities, while the divergence of EKE flux primarily redistributes EKE spatially. Besides, the pressure work generally plays a minor role in the local EKE budget. In the following, we will perform a diagnostic analysis of the EKE decadal variability according to the EKE tendency equation using 1993–2024 ARMOR3D and OMEGA3D data. Note that a fixed volume of the upper 100 m in the study region is selected for the diagnosis, as the time series of the regional mean 0–100 m depth-averaged EKE in the study region is consistent with that of surface EKE. This is illustrated in Figure 5.
Figure 5
Time series of the regional mean, 0–100 m depth-averaged EKE tendency, BTC1, BTC2, VEDF, and CONV terms in the study region for each year between 1993 and 2024 are offered in Figures 6A–E, respectively. Note that the EKE tendency has a smaller magnitude compared to its four components. Among them, the VEDF is the largest term, followed by the BTC1 and CONV terms. Nevertheless, the BTC2 is quite small and can be ignored. In addition, the VEDF and BTC1 values are mostly positive, indicating they both significantly contribute to the generation of EKE. In contrast, the CONV has both positive and negative values. It is therefore expected that the remaining terms of pressure work, wind stress/buoyancy forcing effects, and EKE dissipation may act to damp the EKE.
Figure 6
We propose that VEDF primarily drives the decadal variability of EKE. We further compared low-frequency variations of the EKE tendency with those of VEDF, BTC1, and CONV. Time series of their respective anomalies for each year are illustrated in Figures 7A–D, respectively. Note that a 3-year smoothing is also applied. Among the three components, only the VEDF anomalies basically follow the EKE tendency anomalies. When the EKE tendency anomalies are in positive (negative) phases, the VEDF anomalies turn to positive (negative) correspondingly. The correlation coefficient between the smoothed EKE tendency anomalies and the smoothed VEDF anomalies is 0.47, passing the 99% confidence level. In contrast, the smoothed EKE tendency anomalies show insignificant correlations with the BTC1 (correlation coefficient = -0.03) and the CONV (correlation coefficient = 0.19). It suggests that the VEDF significantly contributes to the decadal variability of the EKE.
Figure 7
Moreover, the spatial pattern of the VEDF anomalies is consistent with that of the EKE tendency anomalies. Here, we defined the period when the regional mean, depth-averaged EKE tendency anomalies in the study region are positive (negative) as the positive (negative) phase of EKE tendency. Between 1993 and 2024, the positive phases appeared in 1993–1994, 1997–1998, 2002–2004, 2009–2010, 2013–2016, 2022, 2024, while the negative phases emerged in 1995–1996, 1999–2001, 2005–2008, 2011–2012, 2017–2021, 2023. The composite spatial patterns of the VEDF anomalies during the positive and negative phases are shown in Figure 8A, B, respectively. Similar spatial patterns for the EKE tendency anomalies during the same positive and negative phases are presented in Figures 8C, D, respectively. During the positive phase, the VEDF anomalies are mostly positive and show a monopole pattern, with the largest amplitude concentrated in the northeast of Hawaii at about 154°W, 26°N (Figure 8A). This is consistent with the corresponding spatial pattern of the EKE tendency anomalies (Figure 8C). During the negative phase, the VEDF anomalies are mostly negative and also show a monopole pattern, with the largest amplitude concentrated in the northeast of Hawaii as well (Figure 8B). This is also similar to the corresponding spatial pattern of the EKE anomalies (Figure 8D). It confirms that the VEDF primarily determines the EKE tendency variations and drives the decadal variability of EKE in the Subtropical Northeast Pacific.
Figure 8
4.2 Essential factor in VEDF: eddy field of density
The VEDF term contains two varying factors: the eddy field of perturbation density () and the eddy field of vertical velocity (). Note that this eddy field of perturbation density is also the eddy field of density. So, the decadal variations in VEDF come from or ? To address this question, here we compared the temporal evolution of the VEDF, and . Their time series are presented in Figures 9A, B. Obviously, the shows decadal variations that follow the VEDF, whereas the exhibits high-frequency (interannual) variations inconsistent with the VEDF. The correlation coefficient between the VEDF and the is -0.32, passing the 90% confidence level. In contrast, the correlation coefficient between the VEDF and the is merely -0.17. Hence, the plays an essential role in determining the decadal variability of EKE in the Subtropical Northeast Pacific.
Figure 9
4.3 Potential source of decadal variability: PDO
The PDO dominates the decadal to interdecadal SST variations in the North Pacific (e.g., ; ). We hence performed a lead-lag correlation analysis between the detrended regional mean EKE anomalies in the study region and the PDO index. Figure 10A shows the two time series from 1993 to 2024. The EKE anomalies seem to follow the PDO index, but with lags. The lead-lag correlation result in Figure 10B demonstrates that the correlation coefficient peaks at 0.74 when the PDO leads the EKE decadal variability by about 15 months (passing the 99% confidence level). Previously, showed that interannual EKE variability northeast of the Hawaiian archipelago is significantly correlated with the PDO, with EKE lagging by 10–14 months. This lag reflects PDO-induced changes in large-scale wind forcing associated with the Aleutian Low.
Figure 10
These results suggest that the PDO may act as a potential source of the observed decadal variability of EKE in the Subtropical Northeast Pacific. The large-scale PDO may first modulate the eddy field of density. Then, the baroclinic instability is altered, and the VEDF changes. The EKE hence increases or decreases correspondingly. Finally, the EKE turns to exhibit a significant decadal variability. It takes the PDO signal about 15 months to ultimately cause the decadal variations in EKE in the Subtropical Northeast Pacific.
5 Summary and discussion
This study reported decadal variability of EKE in the Subtropical Northeast Pacific based on the observational data of ARMOR3D and OMEGA3D from 1993 to 2024. The EKE here exhibits remarkable decadal variability with a significant period of 10–11 years. Between 1993 and 2024, high levels of EKE appeared in the 1994–1995, 1997–1999, 2003–2005, and 2015–2019, while low levels of EKE emerged in 1993, 1996, 2000–2002, 2006–2014, and 2020–2024. The decadal variability of EKE displays a monopole spatial pattern in the Subtropical Northeast Pacific, with the largest amplitude centered in the northeast of the Hawaiian Archipelago, at approximately 154°W, 26°N. In addition, this decadal variability is also manifested by decadal changes in the amplitudes of both cyclonic and anticyclonic eddies.
The decadal variability of EKE in the Subtropical Northeast Pacific is primarily driven by decadal variations in baroclinic EPE to EKE conversion through vertical eddy density flux. When the baroclinic conversion associated with baroclinic instability increases (decreases) on the decadal time scale, the EKE levels increase (decrease) correspondingly. Furthermore, the decadal variability of EKE is likely to originate from the PDO, with the PDO leading the EKE by 15 months. The PDO is suggested first modulate the eddy field of density in the upper layer of the Subtropical Northeast Pacific. Then, the decadal variations in the eddy field of density alter the baroclinic EPE to EKE conversion. The EKE hence increases or decreases correspondingly. Finally, the EKE turns to exhibit significant decadal variability. It takes the PDO signal about 15 months to ultimately drive the decadal variability of EKE in the Subtropical Northeast Pacific.
We noticed that decadal EKE variability is more strongly correlated with the amplitude of anticyclonic eddies than with that of cyclonic eddies in the Subtropical Northeast Pacific. Previous studies have shown that, overall, anticyclonic eddies generated in the California Current System have longer lifespans than cyclonic eddies (e.g., ; ). Anticyclonic eddies with longer lifespans may potentially be influenced by the PDO over a longer duration in the Subtropical Northeast Pacific. Based on this, we will further investigate why the decadal variability of EKE tends to be manifested by decadal changes in the amplitudes of anticyclonic eddies.
As mentioned above, the decadal variability of EKE here is manifested by the decadal variations in the amplitude of both cyclonic and anticyclonic eddies. In the oligotrophic North Pacific Subtropical Gyre, eddies can trap and transport biogeochemical materials from coastal waters and carry upwelled nutrients beyond their formation regions, thereby exerting both local and remote influences on regional productivity (e.g., ; ; ; ). Hence, the identified decadal variability of EKE is expected to cause remarkable decadal variations in the coastal ecosystem surrounding the Hawaiian Archipelago and near the California Current System. More work is needed to shed light on the decadal variations in these coastal ecosystems and their causes in the future.
Statements
Data availability statement
The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.
Author contributions
ZX: Formal analysis, Methodology, Data curation, Writing – original draft, Visualization, Software, Validation, Investigation. YG: Conceptualization, Formal analysis, Methodology, Supervision, Writing – review & editing, Funding acquisition, Resources, Writing – original draft, Project administration.
Funding
The author(s) declared that financial support was received for this work and/or its publication. This research was funded by the National Natural Science Foundation of China (Grant number: 42106019), the Natural Science Foundation of Zhejiang Province (Exploratory Project) (Grant number: LMS26D060001), and the Zhoushan Science and Technology Project-Zhejiang Ocean University Special Project from Bureau of Science and Technology of Zhoushan (Grant number: 2022C41020).
Acknowledgments
ZX and YG would like to thank Ji Qi for his valuable help in this study. Qi provided data support for the validation work of this study.
Conflict of interest
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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Summary
Keywords
decadal variability, eddy kinetic energy, mesoscale eddies, Pacific Decadal Oscillation, subtropical Northeast Pacific
Citation
Xu Z and Guo Y (2026) Decadal variability of eddy kinetic energy in the subtropical Northeast Pacific. Front. Mar. Sci. 13:1839014. doi: 10.3389/fmars.2026.1839014
Received
25 March 2026
Revised
05 April 2026
Accepted
13 April 2026
Published
23 April 2026
Volume
13 - 2026
Edited by
Jiliang Xuan, Second Institute of Oceanography, China
Reviewed by
Yongcan Zu, First Institute of Oceanography, China
Feilong Lin, Second Institute of Oceanography, China
Updates
Copyright
© 2026 Xu and Guo.
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*Correspondence: Yongqing Guo, guoyongqing@zjou.edu.cn
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