Efficient biological carbon export to the mesopelagic ocean induced by submesoscale fronts

Domain: earth_science
Published: 2024-01-17
Editorial outcome: major_revision

Abstract
Oceanic submesoscale processes are ubiquitous in the North Pacific Subtropical Gyre (NPSG), where the biological carbon pump is generally ineffective. Due to difficulties in collecting continuous observations, however, it remains uncertain whether episodic submesoscale processes can drive significant changes in particulate organic carbon (POC) export into the mesopelagic ocean. Here we present observations from high-frequency Biogeochemical-Argo floats in the NPSG, which captured the enhanced POC export fluxes during the intensifying stages of a submesoscale front and a cyclonic eddy compared to their other life stages. A higher percentage of POC export flux was found to be transferred to the base of mesopelagic layer at the front compared to that at the intensifying eddy and the mean of previous studies (37% vs. ~10%), suggesting that the POC export efficiency was significantly strengthened by submesoscale dynamics. Such findings highlight the importance of submesoscale fronts for carbon export and sequestration in subtropical gyres.

Introduction
Biological pumping of particulate organic carbon (POC), one of the primary mechanisms that draws atmospheric CO2 to the deep sea, has been reported to be ineffective within oligotrophic gyres, such as the North Pacific Subtropical Gyre (NPSG)1–3. In these regions, weak vertical nutrient supply limits biological productivity4 and consequently reduces carbon export5,6. Furthermore, the downward POC flux attenuates rapidly in the mesopelagic layer due to the dominance of small-size sinking particles7, considerable fragmentation8, and relatively fast remineralization compared to that at high latitudes9–11.

Subtropical gyres have abundant mesoscale eddies characterized by small Rossby numbers (Ro) and large Richardson numbers (Ri), as well as submesoscale fronts characterized by O(1) Ro and Ri12–16. Mesoscale eddies and submesoscale fronts can impact biological pumps in various ways16–24. Generally, mesoscale eddies experience different life stages, such as the intensifying, mature, and decaying stages. The stage during eddy formation and intensification is typically associated with upward isopycnal displacement in cyclonic eddies (CEs) and downward displacement in anticyclonic eddies (ACEs). The upward isopycnal displacement during a CE intensifying stage can increase nutrient supply and primary production25–28, enhancing POC sinking in subtropical gyres (referred to as the biological gravitational pump)29–31. Due to the increase in the lateral buoyancy gradient32, intensifying submesoscale fronts are often accompanied by vertical velocities as high as 10–100 m d−1, which is an order of magnitude greater than the vertical velocities induced by mesoscale eddies14,15. These vertical motions can inject high quantities of POC produced in the euphotic zone into the mesopelagic layer (referred to as subduction pump)17,19,22,24, resulting in carbon sequestration17,19,20,23. The vertical motions induced by submesoscale fronts may also drive the vertical nutrient supply and stimulate the growth of large phytoplankton communities32–36; these large phytoplankton may sink fast and affect the carbon export efficiency by creating particles with fast sinking velocities through food web dynamics16,36,37. At the global scale, submesoscale fronts have the potential to contribute to POC export38,39, which would help to reconcile the imbalance between the upper layer carbon supply and deep ocean carbon consumption9,17,40.

Prior studies have captured anomalous features of elevated POC at depth, which are interpreted as evidence of the subduction pump19,22,23. Despite their potential importance in shaping POC export, direct observations of the downward POC flux and its attenuation in response to submesoscale fronts are scarce17,19–21,23,41. This is largely attributable to their relatively small spatiotemporal scales and the difficulty in obtaining subsurface observations, as well as the possible decoupling between physical and biogeochemical processes at the front41. Mesoscale features have been suggested to be able to change the strength of oceanic carbon export locally29–31,42,43, whereas the effects of submesoscale features are still unclear. Using high-resolution simulations, Omand et al.19 showed that the subduction pump contributes up to 50% of the spring POC flux in the North Atlantic and Southern Ocean. However, Llort et al.23 showed that the contribution ranged between 1% in spring and 14–19% in summer in the Southern Ocean. By using a model covering a subpolar and a subtropical gyre, Resplandy et al.18 suggested that the subduction pump contributes less than 5% to the annual carbon export due to the strong compensation between upward and downward fluxes at the basin scale. Given the large uncertainty among the estimations from different studies, more high-resolution field observations are required.

There are challenges when estimating the POC export flux associated with episodic submesoscale features by either sediment traps or radioactive pairs (mainly the 234Th-238U pair). Biogeochemical-Argo (BGC-Argo) floats can fill observational gaps over small spatial and temporal scales20,23,28,44,45. By tracking the particle accumulation rates in the water column over sustained periods, BGC-Argo data have been used to estimate the downward POC flux8,45–48. BGC-Argo data include variables that may change in both space and time, especially when sampled near mesoscale and submesoscale features. Thus, careful analysis is required to reasonably delineate the temporal rates and/or the spatial variability of measured variables. The BGC-Argo has been used to identify elevated POC in the mesopelagic layer and estimate the carbon flux associated with submesoscale features20,23. However, the transfer efficiency of POC export associated with submesoscale features has rarely been investigated.

In this study, we show the capability of using BGC-Argo floats to estimate the efficiency of POC export in response to submesoscale fronts and eddies. We deployed two high-frequency sampling floats that profiled twice a day in the western NPSG. These two floats captured the intensifying stages of a mesoscale eddy and a submesoscale front, which were used to estimate vertically resolved POC export fluxes and transfer efficiencies. Further data synthesis extrapolating the results to the entire subtropical gyre revealed the important role that submesoscale fronts may play in strengthening the biological POC pump in the mesopelagic ocean.

Results
Site characterization and tracer distributions
Two BGC-Argo floats (WMO numbers 2902753 and 2902756; Fig. 1a, Table S1 and Text S1) were deployed in two cyclonic eddies (identified as CE1 and CE2; Fig. 1a, Table S2 and Text S2) to collect temperature, salinity, nitrate, chlorophyll-a (Chl), dissolved oxygen (DO), particulate backscattering coefficients at 700 nm (bbp(700)) and photosynthetically available radiation (PAR). From 30 March to 20 April 2019, float 2902753 moved gradually from the CE1 core to the CE1 edge with the relative position r/R (r and R were the distance of the float to the eddy center and the eddy radius, respectively) increasing from ~0 to 2 (Fig. 1b and Fig. 2a). During this time, the sea level anomaly (SLA) at the float position increased gradually from −0.1 m to 0.1 m, reflecting the SLA change from the CE1 center to its periphery (Fig. 1b). From 21 April to 3 May 2019, this float moved along one side of a submesoscale front and experienced the intensifying and decaying stages of the front (Fig. 1b). Float 2902756 was deployed and trapped in the core region of CE2 and experienced the intensifying and mature stages of the eddy until 22 April 2019 (Figs. 1c and 2b).

The euphotic depth (ZEu) was on average ~159 m within CE1 and changed slightly along the radial direction (Fig. S1). The floats may have captured the spatial variability of tracers for CE1 as the location of the floats changed from inside to outside the eddy. The satellite-derived sea surface Chl was averaged over the float sampling period and then interpolated onto the relative locations of the float in CE1 to compare with that measured by the float. The float-measured Chl was in agreement with that derived from satellites in the radial direction (Fig. S2a), with a correlation of 0.39 (p=0.01). In contrast, the temporal evolution of satellite-derived Chl averaged inside CE1 was different from that of float-measured Chl (Fig. S2b), as indicated by a low correlation (R=−0.18, p=0.24). Therefore, the float-measured tracers during this period can be used to represent the spatial variability of CE1 along the radial direction. The radial POC distributions of CE1 were constructed from BGC-Argo measurements (Fig. 3). From the center to the edge, the POC distributions in CE1 decreased at the subsurface chlorophyll maximum depth (ZSCM; on average 117.0 ± 9.9 m; Fig. S1) and increased at 200 m depth. The radial POC distributions at 400 m and 600 m changed slightly compared with those at 200 m. As the float moved to the edge of CE1, the temperature displayed an increasing trend, while nitrate, Chl and POC showed a decreasing trend (Fig. S3 and Table S3). This result suggested that nutrients in the euphotic zone were enhanced by the uplift of isotherms within this cyclonic eddy28, leading to higher POC concentrations in the CE1 center than at its edge (Fig. 3). The POC at 200 m reached its peaks at the edge of r/R=~1 and 1.3, which was likely due to subduction of POC from the productive layer by the front17,19,20,23. This observation further supported that the radial distributions of POC measured by the float reflected the spatial variability of the eddy.

POC flux by an intensifying cyclonic eddy (CE2)
We defined the intensifying and mature stages of CE2 based on the temporal change of SLA averaged inside CE2. Data from float 2902756 were then classified into intensifying-stage and mature-stage measurements by comparing the change of SLA near the float with that averaged inside CE2. From 6 April to 14 April 2019, the CE2 intensified with gradually decreasing SLA values (Fig. S4). The SLA near the float also decreased gradually from −0.03 m to -0.09 m until 14 April, almost synchronously with the SLA decrease inside CE2 (Fig. S4). Additionally, the SLA change of the float was positively correlated with the change in temperature and negatively correlated with the changes in NO3−, Chl and POC at the ZSCM (Fig. S5 and Table S3), implying that the float captured the eddy’s intensifying stage. In stages other than the intensifying stage, the correlations between changes in SLA and changes in temperature, NO3−, Chl, and POC at the ZSCM were generally low or even insignificant (Fig. S5). From April 15 to April 22, the SLA near the float and that averaged inside CE2 remained at extremely low values, indicating that the eddy had reached a mature stage. Except for a fluctuation in the relative position (r/R) during the first few days, the float’s r/R value inside CE2 remained approximately 0.7 until 22 April 2019 (Fig. 1c). We thus used the float measurements during 6–14 April to describe the eddy’s intensifying stage and measurements during 15–22 April to describe the eddy’s mature stage.

Since float 2902756 traveled in a quasi-Lagrangian manner inside the eddy during the intensifying and mature eddy stages, we assumed that the variability measured by the float was mostly attributable to temporal changes of the eddy. The POC concentration was first integrated from the base of the mesopelagic layer (900 m) to depth z (integrated POC; noted as P(z) in Eq. (3)), and then the rate at which POC changed over time (denoted as E(z)) was computed by Eq. (4). With multiple sampling profiles, a linear least squared method (slope of the regression line) was used to estimate E(z) during the intensifying (denoted as E_EI(z)) and mature (denoted as E_EM(z)) stages. Negative E_EM(z) values were present at all depths (Fig. 4a, c), which suggested that the POC removal process was dominant for the POC concentration change during the mature stage of the eddy, likely caused by microbial degradation in the mesopelagic layer9,49. Consistent with other observational studies35, the rate of change of POC decreased gradually with depth in the mesopelagic layer. However, there was a significant difference between the E_EI(z) and E_EM(z) profiles (Fig. 4c). The E_EI(z) during the intensifying stage of the eddy was larger than the E_EM(z), and their difference decreased with depth. This suggested a decrease in the rate of change of POC in the mature stage with respect to the intensifying stage, which could be induced by changes in the POC export flux from the top and/or the POC consumption rate in the water column. In addition, the net rate of change of apparent oxygen utilization (AOU) was positive in the upper mesopelagic layer because AOU changed more during the intensifying stage than during the mature stage (Fig. 4e). This may imply enhanced POC consumption by microbial activity during the intensifying stage. The POC inventory change in the water column is the combined result of the POC flux supplied from the top and the POC consumption in the water column. It is thus very likely that the POC export flux was higher during the intensifying stage than during the mature stage, given that both the rate of change of POC and the average AOU were larger during the intensifying stage than during the mature stage.

The enhanced net POC flux during the eddy’s intensifying stage was then calculated using Eq. (5). Note that this flux should be smaller than the actual POC export flux, as POC consumption also increased during the intensifying stage compared with the mature stage (presented as a positive net rate of change of AOU) (Fig. 4e). An enhanced net POC flux of 1.68 ± 0.3 mmol C m−2 d−1 at ZEu was obtained, which was comparable to the estimates of POC export flux in the NPSG by sediment traps (1.92 mmol C m−2 d−1 by Grabowski et al.50 and 2.5 ± 0.7 mmol C m−2 d−1 by Zhou et al.31) and smaller than the estimates of POC export flux in the subpolar northwest Pacific Ocean using the radioactive technique (3.25 and 11.08 mmol C m−2 d−1 by Buesseler and Boyd51; Table S4). For eddies, significant POC export is not sustained throughout their lifespan and is often associated with the physical dynamics of eddies42,52. Observations have shown that intensifying eddies exhibit a large biological response, while eddies in the mature stage do not show a significant biological response or high export flux29,52. We assumed that the magnitude of the export flux during the eddy’s mature stage was low, so the enhanced net POC flux was considered as the approximation of the actual POC flux here. The enhanced POC flux may underestimate the actual POC flux during the eddy’s intensifying stage as F_EI(z) was a flux anomaly relative to the eddy’s mature stage. Because the Martin curve has long been used as the standard for quantifying POC attenuation across the global ocean, F_EI(z) values at different depths in the mesopelagic layer were fitted to the Martin curve (Eq. (8)) to estimate the attenuation coefficient b, yielding a value of 1.14 ± 0.24, which was similar to those estimated in subtropical gyres and higher than those estimated at high latitudes10,39,50,51 (Fig. 4g and Table S4).

POC flux by an intensifying submesoscale front
The sea surface temperature (SST) distribution revealed structures of a submesoscale thermal front with an SST gradient magnitude (GM) of ~0.2 °C km−1 outside of CE1 from 21 April to 3 May 2019 (Fig. S6a–d). During this period, float 2902753 drifted along the warm (upwelling) side of the front (Fig. S6). This was further supported by a Lagrangian particle tracking experiment, which suggested that the float drifted in a quasi-Lagrangian manner along one side of the front (Text S3). The front exhibited a higher temperature in the upper 300 m and lower salinity in the upper 150 m compared to the CE1 core, indicating that similar water masses were sampled in the frontal region. The T-S diagram demonstrated coherent physical characteristics from 21 April to 3 May 2019 (Fig. S7). All these results suggested that the float sampled similar water masses along the warm side of the front.

The float presented a small Richardson number Ri (Ri≈2) in the frontal region, indicating ageostrophic motions at play to a depth of ~250 m (Fig. S8b). The ageostrophic motions at the front can also be indicated by the increased finite-size Lyapunov exponent (FSLE) distributions at the front (Fig. S8c). We defined different stages of the front by examining changes of GM at the float locations. From 21 April to 27 April, the GM was elevated and larger than the background value, indicating that the float was sampling the front’s intensifying stage. From 28 April to 3 May, the GM decreased to the background value, indicative of the front’s decaying stage (Fig. S6e). In addition, the Ri between the MLD and 250 m depth was smaller during the intensifying stage than during the decaying stage (Fig. S8b). Consistent with the change of Ri, the magnitude of the lateral buoyancy frequency (M2) increased during the intensifying stage and decreased during the decaying stage (see the M2 envelope in Fig. S8c). During the intensifying stage, submesoscale dynamics were prone to generating secondary circulations across the front, which in turn changed the temperature and salinity distributions along the front. Due to the heterogeneous evolution and distribution of the front over time, M2 increased in magnitude along the front. The temporal changes in Ri and M2 suggested that submesoscale motions were more active during the intensifying stage than during the decaying stage. During the intensifying stage, the POC inventory in the euphotic zone was elevated (Fig. S9b). Moreover, large particles were detected by spikes of backscattering coefficients in the mesopelagic layer8 (Fig. S9c).

Given the two distinct periods sampled by the float, the rate of change of integrated POC during the intensifying (denoted as E_FI(z)) and decaying (denoted as E_FD(z)) stages of the front were calculated (Fig. 4b, d, f, h). The distribution of E_FD(z) was similar to that of E_EM(z), which decreased with depth (Fig. 4b, d). Following the same method applied to the eddy, the enhanced net POC flux induced by front intensification (denoted as F_FI(z)) was estimated by Eq. (6). In contrast to the eddy, the net rate of change of AOU was very small in the mesopelagic layer (Fig. 4f). The small net rate of change of AOU implies relatively stable POC consumption rates during the intensifying and decaying stages. The enhanced net POC flux (F_FI(z)) was thus mostly contributed by the increased POC export flux during the front intensifying stage (Fig. 4h). The increased POC export flux at the base of the euphotic zone was then approximately estimated as 2.11 ± 0.4 mmol C m−2 d−1, higher than that in the eddy’s intensifying stage. Similar results have been reported in the NPSG, which showed a higher POC flux at a submesoscale front than in a cyclonic eddy nearby (2.2 mmol C m−2 d−1 versus 1.2 mmol C m−2 d−1 in Guidi et al.41). In addition, an attenuation coefficient b of 0.56 ± 0.15 was estimated by fitting F_FI(z) to Eq. (8), which was smaller than that for the intensifying cyclonic eddy, implying deeper transfer of POC in the frontal region.

Methods
BGC-Argo measurement and calibration
Data were collected by sensors equipped on the BGC-Argo floats from depths between ~900 m and the surface. The floats profiled twice a day. The floats sampled the first 30 m at a 0.2 m resolution, between 30–400 m at a 1 m resolution and below 400 m at a 5 m resolution. All profile data were interpolated at a 5 m resolution. Before deployment, the dark currents of the chlorophyll fluorometer and backscattering sensor were corrected (reassigned) based on the dark-current measurements, by masking the optical windows with black tape. The dark-corrected Chl and bbp profiles were smoothed using a 5-point moving median filter to minimize high frequency noise44. The spike of bbp(700), a qualitative proxy index for large particles, was calculated as the difference between the raw and smoothed bbp(700)8. The nitrate distributions from the BGC-Argo floats were calibrated using ship-based nitrate measurements taken along the BGC-Argo trajectories (Text S5 and Fig. S13). The ship-based POC concentrations were also measured during float deployment. Then, a localized statistical relationship between the bbp(700) values measured by the BGC-Argo floats and the ship-based collection of POC concentrations was derived (Text S5, Fig. S14; a total of 32 data points, R2=0.39, p<0.01):

POC (mmol C m−3) = 2083.17 * bbp(700) + 0.06 (1)

The mixed layer depth (MLD) was computed as the depth where the potential density was different from the sea surface density by 0.03 σθ following Jing et al.59. The ZEu was calculated as the depth where PAR was 1% of its surface value60. The AOU was calculated as the difference between the saturated and observed DO:

AOU = DOsat − DO (2)

where DOsat is the saturated DO computed using the measured temperature and salinity. To identify subsurface features resulting from subduction pumps, spiciness that describes thermohaline perturbations not included in potential density was estimated using the BGC-Argo-derived temperature and salinity data. As suggested by Omand et al.19, subsurface water masses originating from the euphotic zone were identified as subsurface anomalies in vertical POC and spiciness distributions.

Other data
Ship-based nitrate and POC measurements were collected at 10 stations near the BGC-Argo trajectories for nitrate calibration and POC calculations (Text S5 and Table S5). Nitrate was measured onboard using a Four-channel Continuous Flow Technicon AA3 Auto-Analyzer (Bran-Lube, GmbH). The POC data were determined using an Elemental vario EL cube CHNS Analyzer, of which the uncertainty was <10%42.

Daily SLA and sea surface Chl were obtained from the Copernicus Marine Environment Monitoring Service (CMEMS) and the Ocean Color Climate Change Initiative (OC-CCI) project, respectively. The dataset from the Mesoscale Eddy Trajectory Atlas was identified and tracked using the methods provided by Pegliasco et al.12 and obtained from the Archiving, Validation, and Interpretation of Satellite Oceanographic Data (AVISO) service. Satellite-derived SST data at a resolution of ~4.5 km (available from the CMEMS) were used to determine the SST gradients of the oceanic fronts.

The rate of change of integrated POC
Since the float drifted along the front or in a relatively fixed position of CE2, we expected that the float sampled similar water masses over time. The POC concentrations derived from the float estimations were integrated from the base of the mesopelagic layer (900 m) to an upper mesopelagic depth z:

P(z) = ∫900m^z POC * dz (3)

where P(z) is the integrated POC, z=[ZEu, 200 m, 300 m, 400 m, 500 m]. The rate of change of integrated POC (denoted as E(z)) was thus considered as the net rate at which POC accumulated between depth z and the base of the mesopelagic layer:

E(z) = ∂P(z)/∂t (4)

where E(z) can be interpreted as the balance between the POC flux supply from depth z and the POC consumption between depth z and the base of the mesopelagic layer, given that the POC flux at the base of the mesopelagic layer is generally negligible10,46. The E(z) was calculated using a linear least squared method (slope of the regression line). Because the balance between supply and consumption is the driver of E(z) changes, we estimated E(z) during the intensifying and mature (decaying) stages of the eddy (front). The E(z) during the intensifying and mature stages of the eddy were denoted as E_EI(z) and E_EM(z), respectively, and those during the intensifying and decaying stages of the front were denoted as E_FI(z) and E_FD(z), respectively. The uncertainty of the linear least squared estimations was shown in Table S6. The enhanced net POC fluxes during the intensifying stages of the eddy (denoted as F_EI(z)) and the front (denoted as F_FI(z)) were calculated as:

F_EI(z) = E_EI(z) − E_EM(z) (5)

F_FI(z) = E_FI(z) − E_FD(z) (6)

A Lagrangian particle tracking experiment was conducted to test whether the float drifted along the front (Text S3). To further verify that the float sampled similar water masses, the physical characteristics along the front were analyzed (Fig. S7).

The AOU multiplied by the Redfield ratios represents the heterotrophic respiration of the total organic carbon (TOC), 50–90% of which is dissolved organic carbon48,61,62. Because the ratio of the POC to TOC and the Redfield ratios in the study region were not measured, we did not use the AOU to reconstruct the remineralized POC and only used the change of AOU over time to demonstrate possible changes in remineralization between different stages. The average AOU from the base of the mesopelagic layer (900 m) to an upper mesopelagic depth z was calculated as

average AOU = 1/(900m − z) * ∫900m^z AOU * dz (7)

where z=[ZEu, 200 m, 300 m, 400 m, 500 m]. The net rate of change of AOU defined as the difference of the temporal rate of AOU between the intensifying and mature (decaying) stages of the eddy (front) was thus estimated using the averaged AOU.

POC flux attenuation
The attenuation of POC flux with depth is quantified by a Martin curve63:

F(z) = F(ZEu) * (z/ZEu)^−b (8)

where F(z) is the POC flux at depth z, normalized to flux F(ZEu) at euphotic depth ZEu, and b is the attenuation coefficient.

The SST gradient
We use the SST gradient to indicate the strength of front. The SST gradient magnitude (GM) is calculated following Belkin and O’Reilly64:

GM = √(Gx^2 + Gy^2) (9)

where Gx and Gy are the zonal and meridional SST gradients that can be quantified as:

Gx = 1/dx * [1 0 −1; 6 0 −6; 1 0 −1] * SST (10)

Gy = 1/dy * [1 6 1; 0 0 0; −1 −6 −1] * SST (11)

where dx, dy and * are the zonal and meridional distances between successive pixels within the SST data and the convolution sign, respectively. Using satellite-derived SST data, the GM at the front where the BGC-Argo passed through (Fig. S6c–e) and at the locations of the sampling site for in-situ POC flux measurements (Fig. 5) were calculated. To extrapolate the relationship between the b value and GM for the NPSG, the spatial distributions of GM during 2003–2019 were also calculated (Text S6).

The FSLE field
We use the finite-size Lyapunov exponent (FSLE) to illustrate the frontal region encountered by the BGC-Argo. Daily FSLEs with a spatial resolution of 0.04° were obtained from AVISO. The FSLE is defined as the inverse time of separation of two particles from their initial distance δ0 to final distance δf65. The particles were advected by altimetry velocities and their trajectories were computed by backward-time integration of the altimetry velocities. The FSLE has been suggested to be particularly suited to diagnose filamentary processes generated by mesoscale horizontal shear and strain deformation65. Large backward FSLE values represent regions of strong submesoscale transport66. As such, the FSLE has been employed to delineate submesoscale structures32,66. The FSLE time series was extracted along the path of float 2902753 to capture the strain field and was then compared to the lateral buoyancy frequency (M2) sampled by the float.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "This study presents an observafion-based analysis of the relafionship between parficulate organic carbon (POC) and eddy and frontal dynamics. The authors have leveraged observafions from floats with the objecfive to bring new insights into carbon export dynamics at fine scale. This is a valuable effort; yet there are major issues that need to be addressed before it can be published. The main concerns fall in 4 categories:\nI. Gaps in context and references to prior work in introducfion and discussion of the results, specifically the potenfial impact of frontal subducfion (comment #1)\nII. Missing or weak jusfificafion of the hypotheses used to interpret the data that account for the compounding effects of spafial and temporal variability, specifically the jusfificafion to use a “mostly spafial” or a “mostly temporal” framework depending on the eddy/front considered (comments #2-5)\nIII. Shortcomings with the conclusions and generalizafions of the results that link fronts to POC export and aftenuafion coefficient b, which is the main point of the paper (comments # 6-10).\nIV. Imprecisions on the approach that need clarificafion, issues with text and figures. (comments #11-28).\nDetailed comments and suggesfions on how to address them are provided below. The two reviewers that contributed to this review believe the authors can improve the jusfificafion of their approach, as well as the interpretafion and generalizafion so the manuscript can be acceptable for publicafion.\n1. Gaps in context and references. The sentence of L71 is not true: “In this study, for the first fime, we show the capability of using BGC-Argo floats equipped with opfical sensors to esfimate the carbon export flux and associated verfical aftenuafion in response to submesoscale fronts”\nThe paper is lacking key references, in parficular prior studies idenfifying and quanfifying the role of subducfion by fronts, including with BGC-Argo floats. The manuscript leads us to believe that there were no aftempts to quanfify this subducfion pump before. Yet observafion based (using float AOU, spiciness) and high resolufion modeling papers have been published on this topic (see list of reference below). They need to be included to provide the adequate context in the introducfion but also in the discussion. Note that the process of export by subducfion along fronts explained in this study can be called differently in the literature: eddy pump, eddy subducfion pump etc. Although the term “eddy pump” was often used, it does not usually refer to “Ekman pumping” in eddies but the subducfion by fast velocifies associated with meso and submesoscale fronts, similarly to what is considered in this manuscript.\nSentences that crifically need these references include L56-67 (almost all sentences in this paragraph are missing crifical references), L71 which needs to integrate these prior work. In discussion, please consider how the impact of subducfion would influence your results and discuss considering these prior works.\nReview about export pumps including the physical injecfion pump or eddy pump:\nBoyd, P.W., Claustre, H., Levy, M., Siegel, D.A., Weber, T., 2019. Mulfi-faceted parficle pumps drive carbon sequestrafion in the ocean. Nature 568, 327. hftps://doi.org/10.1038/s41586-019-1098-2\nPapers esfimafing the role the “eddy subducfion pump” using BGC-Argo, cruises and models:\nErickson, Z.K., Thompson, A.F., 2018. The Seasonality of Physically Driven Export at Submesoscales in the Northeast Atlanfic Ocean. Global Biogeochemical Cycles 32. hftps://doi.org/10.1029/2018GB005927\nLacour, L., Llort, J., Briggs, N., Strufton, P.G., Boyd, P.W., 2023. Seasonality of downward carbon export in the Pacific Southern Ocean revealed by mulfi-year robofic observafions. Nat Commun 14, 1278. hftps://doi.org/10.1038/s41467-023-36954-7\nLlort, J., Langlais C., Matear R., Moreau S., Lenton A., Strufton Peter G., 2018. Evaluafing Southern Ocean Carbon Eddy-Pump From Biogeochemical-Argo Floats. Journal of Geophysical Research: Oceans 123, 971–984. hftps://doi.org/10.1002/2017JC012861\nMcGillicuddy, D.J., Resplandy, L., Lévy, M., 2019. Esfimafing parficle export flux from satellite observafions: Challenges associated with spafial and temporal decoupling of producfion and export. Journal of Marine Research 77, 247–258. hftps://doi.org/10.1357/002224019828474331\nOmand, M.M., D’Asaro, E.A., Lee, C.M., Perry, M.J., Briggs, N., Cefinić, I., Mahadevan, A., 2015. Eddy-driven subducfion exports parficulate organic carbon from the spring bloom. Science 348, 222–225. hftps://doi.org/10.1126/science.1260062\nResplandy, L., Lévy, M., McGillicuddy Jr., D.J., 2019. Effects of Eddy-Driven Subducfion on Ocean Biological Carbon Pump. Global Biogeochemical Cycles 33, 1071–1084. hftps://doi.org/10.1029/2018GB006125\nStukel, M.R., Song, H., Goericke, R., Miller, A.J., 2017. The role of subducfion and gravitafional sinking in parficle export, carbon sequestrafion, and the remineralizafion length scale in the California Current Ecosystem: Subducfion and sinking parficle export in the CCE. Limnology and Oceanography 63, 363–383. hftps://doi.org/10.1002/lno.10636\n2. Missing jusfificafion of the hypotheses, specifically the jusfificafion to use a “mostly spafial” or a “mostly temporal” framework to interpret the float data.\nThe authors alternafively interpret the observed changes along the float trajectories as “mostly spafial changes” (CE1 and ACE1, Figure 2), or “mostly temporal changes” i.e. pseudo lagrangian (CE2 and front, Figure 3). The hypothesis of “mostly temporal” is jusfified in the text for CE2 (L128 and 141). However, the jusfificafion to interpret as “mostly spafial” the changes along CE1 and ACE1 is missing, and the hypothesis to interpret as “mostly temporal” the changes aftributed to frontal dynamics seems inadequate (see details in comments 3 and 4 below). We encourage the authors to explain clearly and early these different strategies to orient and prepare the reader.\n3. The authors need to demonstrate why it is jusfified to ignore temporal variafions when analyzing CE1 and ACE1. Figure 2 interprets all POC data as spafial changes (using radial structure of the eddies CE1 and ACE1). The approach is aftracfive, but the text and figures should clearly show that this is a valid hypothesis. Specifically, how much of the signal that is interpreted as spafial variability across the eddy is in fact introduced by the temporal evolufion along the trajectory of the float? At least, the authors could indicate the day of sampling for each data point on Figure 2? [Colors could indicate the day of sampling while symbols could indicate the depth]. This would allow the reader to see how much of the variafions aftributed to the spafial structure of the eddy could be introduced by temporal changes.\n4. The hypothesis of “mostly temporal” is highly disputable for the front. It is ok for eddy CE2 because the float seems to stay stuck close to the center of the eddy, and most changes can be interpreted as temporal changes. In the case of the front, however, the float seems to be sampling different parts of the front. The associated changes in SLA, POC, AOU etc. are therefore likely to come from spafial variafions across the front and not temporal variafions. The authors could demonstrate that it is indeed temporal, however it is unlikely to be successful and convincing given the complexity of the dynamics in the frontal structure. This shortcoming has major implicafions for the result interpretafion and the conclusions of the paper as the authors interpret these changes as temporal changes while they are likely spafial changes. This secfion of the results and associated conclusions needs to be revised.\n5. The sampling context should be befter presented. In Figure 1, eddies and float trajectories appear completely disconnected. This is likely because the black lines show the center of the eddy and not their span. Could you indicate the radius of the eddies around the trajectories so we can see that they were indeed in the eddies? Also we encourage the authors to include a figure similar to Figure S4a to show the float relafive to the eddy/front. Maybe choose snapshots that show the overlap with the front as a funcfion of fime.\n6. Generalizafion between front and carbon export. L214-222. “A strong correlafion between the b value and GM was found …. This stafisfical relafionship implies that a strong front is linked with high POC transfer efficiency to the mesopelagic layer, which could be used as a parameterizafion to account for the impact of fronts on carbon export in large-scale models, once the front intensity at the surface is known”. This conclusion seems not backed up by the results. More complete models seem to show that b can vary according to many other biophysical parameters, making this generalizafion highly debatable (see for instance Ngyuen et al. 2022: Microbes contribute to sefting the ocean carbon flux by altering the fate of sinking parficulates). This is one of the main points of the paper; the caveats need to be discussed properly.\n7. Conclusion about seasonality and export. line 234: You did not take into account that the seasonality of mesoscale and frontal dynamics is different from the seasonality of POC content in the water column. Consequently, the amount of POC transported by the same front strength varies depending on the season. This could completely reverse your conclusion about the seasonal evolufion of the parameter b. Please revise or strengthen these points.\n8. Missing considerafion of subducfion #1. The POC export depth by fronts also depends on the penetrafion depth of the verfical velocifies associated with the fronts (subducfion, see comment #1 for a list of papers that describe this). Shallow fronts do not allow POC to be exported below the pycnocline and would limit the frontal effect on b, further weakening your conclusion and the link established between fronts and POC export/aftenuafion coefficient. Please consider this effect of subducfion in introducfion and importantly in your results and interpretafion. This is one of the weakest point of the paper. See also comment 9 below.\n9. Missing considerafion of subducfion #2. L118: “The POC distribufions aftenuated faster in the CE 1 center than at its edge, which is likely due to the higher remineralizafion of the newly produced and easily degradable organic mafter inside the eddy core8,36,37.” Is this really what is happening here? Couldn’t it be that intense verfical velocifies associated with the frontal dynamics at the boundary of the eddies are transporfing/subducfing material down?\n10. Generalizafion to the subtropical Pacific. The generalizafion to the basin is very hand wavy and unconvincing, and probably not needed here. The results can stand alone without this. The author could in fact point out that the impact at the basin scale and global scale is sfill an open quesfion. The conclusion, abstract (and maybe fitle) should be modified to reflect the changes in conclusions.\nImprecisions on the approach that need clarificafion, issues with text and figures.\nSecfion 2.1\n11. Line 97 and onward. This paragraph about the posifion of the floats is a liftle tedious to read. Maybe the authors could either streamline or fold in some results in there as they describe the trajectory.\n12. Line 107: “The euphofic depth (ZEu) was on average ~159 m within CE 1 and 161 m in ACE” is this difference really significant?\n13. line 115: Correlafions are reversed: change increasing to decreasing and vice versa.\n14. Line 116: “This result suggested that nutrients in the euphofic zone were enhanced by the uplift of isotherms within this cyclonic eddy17,” Don’t you mean that uplift occurs at the edge of CE instead of “within”?\n15. line 123: Trends are reversed: change posifive to negafive and vice versa.\n16. Text on the figure was blurry, small and hard to read in my version.\n17. Zscm is used to discuss the changes in the different properfies measured. Could you explain why? How to separate the effect of the eddy dynamics and the change in sampling depth due to variafions in Zscm? Is the assumpfion that Zscm follows a density layer? Maybe using density instead of depth would be more insighfful?\nSecfion 2.2\n18. Please state clearly that you aftribute change in integrated content over fime to change in flux from the top, and detail and jusfify your assumpfions.\n19. More arguments could be provided to jusfify the reason for comparing the aftenuafion of a flux anomaly (FEI(z)) calculated with the float with the aftenuafion of the total POC flux from the literature.\n20. Write P(z), E(z) on figure 3 to make it easier to understand.\n21. line 153: Is «exponenfially» appropriate? It seems linear.\n22. line 162: The total increase in POC flux could be calculated by reconstrucfing the amount of remineralized POC from AOU and Redfield rafios.\n23. Y-scales of 3g and 3h are making it confusing, maybe 0-700 m could be used.\nSecfion 2.3\n24. L 183: Here, the front is defined by the temperature gradient. Would it be possible to find out whether the front is dynamically acfive and carrying POC at depth or not?\n25. L184/185: Can we really speak of degradafion/intensificafion, since the float crosses the front but doesn't stay there?\n26. L 186 / Fig. S4e: Why is the gradient lower than the background during the decaying stage? Why not equal since the front goes back to background?\n27. L 188: Fig. S4g: How is the strain rate calculated and from which data product? You could physically define the front and add its posifion to your figures to make interpretafion easier.\nMethods\n28. L 313: You could spell out bbp(700) and PAR again.", "reviewer_2": "This study presents an observafion-based analysis of the relafionship between parficulate organic carbon (POC) and eddy and frontal dynamics. The authors have leveraged observafions from floats with the objecfive to bring new insights into carbon export dynamics at fine scale. This is a valuable effort; yet there are major issues that need to be addressed before it can be published. The main concerns fall in 4 categories:\nGaps in context and references to prior work in introducfion and discussion of the results, specifically the potenfial impact of frontal subducfion (comment #1)\nMissing or weak jusfificafion of the hypotheses used to interpret the data that account for the compounding effects of spafial and temporal variability, specifically the jusfificafion to use a “mostly spafial” or a “mostly temporal” framework depending on the eddy/front considered (comments #2-5)\nShortcomings with the conclusions and generalizafions of the results that link fronts to POC export and aftenuafion coefficient b, which is the main point of the paper (comments # 6-10).\nImprecisions on the approach that need clarificafion, issues with text and figures. (comments #11-28).\nDetailed comments and suggesfions on how to address them are provided below. The two reviewers that contributed to this review believe the authors can improve the jusfificafion of their approach, as well as the interpretafion and generalizafion so the manuscript can be acceptable for publicafion.\nGaps in context and references. The sentence of L71 is not true: “In this study, for the first fime, we show the capability of using BGC-Argo floats equipped with opfical sensors to esfimate the carbon export flux and associated verfical aftenuafion in response to submesoscale fronts”\nThe paper is lacking key references, in parficular prior studies idenfifying and quanfifying the role of subducfion by fronts, including with BGC-Argo floats. The manuscript leads us to believe that there were no aftempts to quanfify this subducfion pump before. Yet observafion based (using float AOU, spiciness) and high resolufion modeling papers have been published on this topic (see list of reference below). They need to be included to provide the adequate context in the introducfion but also in the discussion. Note that the process of export by subducfion along fronts explained in this study can be called differently in the literature: eddy pump, eddy subducfion pump etc. Although the term “eddy pump” was often used, it does not usually refer to “Ekman pumping” in eddies but the subducfion by fast velocifies associated with meso and submesoscale fronts, similarly to what is considered in this manuscript.\nSentences that crifically need these references include L56-67 (almost all sentences in this paragraph are missing crifical references), L71 which needs to integrate these prior work. In discussion, please consider how the impact of subducfion would influence your results and discuss considering these prior works.\nReview about export pumps including the physical injecfion pump or eddy pump:\nBoyd, P.W., Claustre, H., Levy, M., Siegel, D.A., Weber, T., 2019. Mulfi-faceted parficle pumps drive carbon sequestrafion in the ocean. Nature 568, 327. hftps://doi.org/10.1038/s41586-019-1098-2\nPapers esfimafing the role the “eddy subducfion pump” using BGC-Argo, cruises and models:\nErickson, Z.K., Thompson, A.F., 2018. The Seasonality of Physically Driven Export at Submesoscales in the Northeast Atlanfic Ocean. Global Biogeochemical Cycles 32. hftps://doi.org/10.1029/2018GB005927\nLacour, L., Llort, J., Briggs, N., Strufton, P.G., Boyd, P.W., 2023. Seasonality of downward carbon export in the Pacific Southern Ocean revealed by mulfi-year robofic observafions. Nat Commun 14, 1278. hftps://doi.org/10.1038/s41467-023-36954-7\nLlort, J., Langlais C., Matear R., Moreau S., Lenton A., Strufton Peter G., 2018. Evaluafing Southern Ocean Carbon Eddy-Pump From Biogeochemical-Argo Floats. Journal of Geophysical Research: Oceans 123, 971–984. hftps://doi.org/10.1002/2017JC012861\nMcGillicuddy, D.J., Resplandy, L., Lévy, M., 2019. Esfimafing parficle export flux from satellite observafions: Challenges associated with spafial and temporal decoupling of producfion and export. Journal of Marine Research 77, 247–258. hftps://doi.org/10.1357/002224019828474331\nOmand, M.M., D’Asaro, E.A., Lee, C.M., Perry, M.J., Briggs, N., Cefinić, I., Mahadevan, A., 2015. Eddy-driven subducfion exports parficulate organic carbon from the spring bloom. Science 348, 222–225. hftps://doi.org/10.1126/science.1260062\nResplandy, L., Lévy, M., McGillicuddy Jr., D.J., 2019. Effects of Eddy-Driven Subducfion on Ocean Biological Carbon Pump. Global Biogeochemical Cycles 33, 1071–1084. hftps://doi.org/10.1029/2018GB006125\nStukel, M.R., Song, H., Goericke, R., Miller, A.J., 2017. The role of subducfion and gravitafional sinking in parficle export, carbon sequestrafion, and the remineralizafion length scale in the California Current Ecosystem: Subducfion and sinking parficle export in the CCE. Limnology and Oceanography 63, 363–383. hftps://doi.org/10.1002/lno.10636\nMissing jusfificafion of the hypotheses, specifically the jusfificafion to use a “mostly spafial” or a “mostly temporal” framework to interpret the float data.\nThe authors alternafively interpret the observed changes along the float trajectories as “mostly spafial changes” (CE1 and ACE1, Figure 2), or “mostly temporal changes” i.e. pseudo lagrangian (CE2 and front, Figure 3). The hypothesis of “mostly temporal” is jusfified in the text for CE2 (L128 and 141). However, the jusfificafion to interpret as “mostly spafial” the changes along CE1 and ACE1 is missing, and the hypothesis to interpret as “mostly temporal” the changes aftributed to frontal dynamics seems inadequate (see details in comments 3 and 4 below). We encourage the authors to explain clearly and early these different strategies to orient and prepare the reader.\nThe authors need to demonstrate why it is jusfified to ignore temporal variafions when analyzing CE1 and ACE1. Figure 2 interprets all POC data as spafial changes (using radial structure of the eddies CE1 and ACE1). The approach is aftracfive, but the text and figures should clearly show that this is a valid hypothesis. Specifically, how much of the signal that is interpreted as spafial variability across the eddy is in fact introduced by the temporal evolufion along the trajectory of the float? At least, the authors could indicate the day of sampling for each data point on Figure 2? [Colors could indicate the day of sampling while symbols could indicate the depth]. This would allow the reader to see how much of the variafions aftributed to the spafial structure of the eddy could be introduced by temporal changes.\nThe hypothesis of “mostly temporal” is highly disputable for the front. It is ok for eddy CE2 because the float seems to stay stuck close to the center of the eddy, and most changes can be interpreted as temporal changes. In the case of the front, however, the float seems to be sampling different parts of the front. The associated changes in SLA, POC, AOU etc. are therefore likely to come from spafial variafions across the front and not temporal variafions. The authors could demonstrate that it is indeed temporal, however it is unlikely to be successful and convincing given the complexity of the dynamics in the frontal structure. This shortcoming has major implicafions for the result interpretafion and the conclusions of the paper as the authors interpret these changes as temporal changes while they are likely spafial changes. This secfion of the results and associated conclusions needs to be revised.\nThe sampling context should be befter presented. In Figure 1, eddies and float trajectories appear completely disconnected. This is likely because the black lines show the center of the eddy and not their span. Could you indicate the radius of the eddies around the trajectories so we can see that they were indeed in the eddies? Also we encourage the authors to include a figure similar to Figure S4a to show the float relafive to the eddy/front. Maybe choose snapshots that show the overlap with the front as a funcfion of fime.\nGeneralizafion between front and carbon export. L214-222. “A strong correlafion between the b value and GM was found …. This stafisfical relafionship implies that a strong front is linked with high POC transfer efficiency to the mesopelagic layer, which could be used as a parameterizafion to account for the impact of fronts on carbon export in large-scale models, once the front intensity at the surface is known”. This conclusion seems not backed up by the results. More complete models seem to show that b can vary according to many other biophysical parameters, making this generalizafion highly debatable (see for instance Ngyuen et al. 2022: Microbes contribute to sefting the ocean carbon flux by altering the fate of sinking parficulates). This is one of the main points of the paper; the caveats need to be discussed properly.\nConclusion about seasonality and export. line 234: You did not take into account that the seasonality of mesoscale and frontal dynamics is different from the seasonality of POC content in the water column. Consequently, the amount of POC transported by the same front strength varies depending on the season. This could completely reverse your conclusion about the seasonal evolufion of the parameter b. Please revise or strengthen these points.\nMissing considerafion of subducfion #1. The POC export depth by fronts also depends on the penetrafion depth of the verfical velocifies associated with the fronts (subducfion, see comment #1 for a list of papers that describe this). Shallow fronts do not allow POC to be exported below the pycnocline and would limit the frontal effect on b, further weakening your conclusion and the link established between fronts and POC export/aftenuafion coefficient. Please consider this effect of subducfion in introducfion and importantly in your results and interpretafion. This is one of the weakest point of the paper. See also comment 9 below.\nMissing considerafion of subducfion #2. L118: “The POC distribufions aftenuated faster in the CE 1 center than at its edge, which is likely due to the higher remineralizafion of the newly produced and easily degradable organic mafter inside the eddy core8,36,37.” Is this really what is happening here? Couldn’t it be that intense verfical velocifies associated with the frontal dynamics at the boundary of the eddies are transporfing/subducfing material down?\nGeneralizafion to the subtropical Pacific. The generalizafion to the basin is very hand wavy and unconvincing, and probably not needed here. The results can stand alone without this. The author could in fact point out that the impact at the basin scale and global scale is sfill an open quesfion. The conclusion, abstract (and maybe fitle) should be modified to reflect the changes in conclusions.\nImprecisions on the approach that need clarificafion, issues with text and figures.\nSecfion 2.1\nLine 97 and onward. This paragraph about the posifion of the floats is a liftle tedious to read. Maybe the authors could either streamline or fold in some results in there as they describe the trajectory.\nLine 107: “The euphofic depth (ZEu) was on average ~159 m within CE 1 and 161 m in ACE” is this difference really significant?\nline 115: Correlafions are reversed: change increasing to decreasing and vice versa.\nLine 116: “This result suggested that nutrients in the euphofic zone were enhanced by the uplift of isotherms within this cyclonic eddy17,” Don’t you mean that uplift occurs at the edge of CE instead of “within”?\nline 123: Trends are reversed: change posifive to negafive and vice versa.\nText on the figure was blurry, small and hard to read in my version.\nZscm is used to discuss the changes in the different properfies measured. Could you explain why? How to separate the effect of the eddy dynamics and the change in sampling depth due to variafions in Zscm? Is the assumpfion that Zscm follows a density layer? Maybe using density instead of depth would be more insighfful?\nSecfion 2.2\nPlease state clearly that you aftribute change in integrated content over fime to change in flux from the top, and detail and jusfify your assumpfions.\nMore arguments could be provided to jusfify the reason for comparing the aftenuafion of a flux anomaly (FEI(z)) calculated with the float with the aftenuafion of the total POC flux from the literature.\nWrite P(z), E(z) on figure 3 to make it easier to understand.\nline 153: Is «exponenfially» appropriate? It seems linear.\nline 162: The total increase in POC flux could be calculated by reconstrucfing the amount of remineralized POC from AOU and Redfield rafios.\nY-scales of 3g and 3h are making it confusing, maybe 0-700 m could be used.\nSecfion 2.3\nL 183: Here, the front is defined by the temperature gradient. Would it be possible to find out whether the front is dynamically acfive and carrying POC at depth or not?\nL184/185: Can we really speak of degradafion/intensificafion, since the float crosses the front but doesn't stay there?\nL 186 / Fig. S4e: Why is the gradient lower than the background during the decaying stage? Why not equal since the front goes back to background?\nL 188: Fig. S4g: How is the strain rate calculated and from which data product? You could physically define the front and add its posifion to your figures to make interpretafion easier.\nMethods\nL 313: You could spell out bbp(700) and PAR again.", "reviewer_3": "Efficient biological carbon export to the mesopelagic ocean induced by submesoscale fronts in subtropical gyres\nGuo, M., Xing, X., et al.\nNature Communicafions\nThis study presents data from BGC-Argo floats along with interpolated satellite remote sensing data to invesfigate the role of processes at the submesoscale in shaping carbon export. The authors find that, in the North Pacific subtropical gyre, processes at the mesoscale and submesoscale may play a significant role in transporfing carbon from the surface to the interior ocean. In parficular, they note that the previous assumpfion of a relafionship of carbon aftenuafion with temperature may be befter considered as a relafionship between aftenuafion and SST gradient magnitude. Their suggested relafionship could help befter constrain carbon cycling in the subtropical gyres in numerical models.\nI would like to thank the authors for a clearly-wriften manuscript with many high-quality figures. I enjoyed reading this manuscript and felt it presented a compelling case for considering carbon export at the submesoscale in the subtropical ocean. Carbon export is an important and fimely topic, and I appreciate the care with which the authors present the data. I have a few concerns that I hope the authors will address in order to make the work more accessible to the reader. In addifion, while the manuscript generally does a nice job at describing limitafions with the work, there are a few addifional constraints to consider, as detailed below. My major concerns are documented below; there were also several minor concerns that I think the manuscript would benefit from addressing.\nMajor Concerns\nDefinifion of the submesoscale front: The submesoscale front described in this manuscript is an interesfing feature, but the manuscript does not yet convince me that I am seeing a density front and therefore that the resulfing POC analysis is aftributable to the feature. First, the front is diagnosed from SST and SST gradient. This ignores the potenfial contribufion of salinity. To remedy this, I would like to see secfion plots (fime versus depth) of the float’s temperature and salinity over this period (April 21-May 3) to visualize the depth of this front.\nIn addifion, Figure S4 is stated to be of verfical buoyancy frequency, but that is not possible as in a stable water column, N2 must solely be posifive. I imagine the authors may have instead calculated lateral buoyancy frequency (M2), but the magnitude of the values shown are extremely high for this property; M2 values of strong submesoscale fronts in the Southern Ocean are of O(10^-7) (Siegelman et al. 2020). I urge the authors to check what they are calculafing here. I do appreciate the inclusion of strain rate, and the authors could also consider using Finite Size Lyapunov Exponents (AVISO+", "reviewer_4": "Review comment\nThe manuscript by Wang et al., used two high-frequency sampling BGC-Argo deployed in the western Pacific to invesfigate the impact of the eddies on the POC export. The authors reported enhanced POC export in the regions affected by intensifying submesoscale fronts and further meta-analysis of a global compiled dataset revealed a prevailing relafionship between transfer efficiency and the strength of submesoscale front (indicafive of surface temperature gradient). Finally, the authors upscaled the contribufion of eddies to the carbon export in the enfire northern subtropical Pacific gyre by synthesizing the frequency of eddy occurrence.\nHowever, I find several noteworthy loopholes in the BGC-Argo data analysis, specially related to the observed AOU rate, and its discrepancy with the POC rate. See my explicit comments below:\n1) Unexpected, negafive change of AOU and the discrepancy between AOU and POC rate:\nFigure 3 shows the author derived negafive values for the fime rate of AOU in many cases, the implicafion being that twilight zone oxygen increases over fime. This tendency is somewhat surprising to me, as we generally expect a declining trend of oxygen over fime below the euphofic zone resulfing from biological respirafion, regardless of the relafive change in upper POC flux.\nFurthermore, the reported magnitude of AOU rate appears to be unrealisfically high. The depth-integrated AOU rates between 150m (or 170m) and 900m fall within the range of 250-500 mmol m-2 d-1, equivalent to 90-180 mmol m-2 yr-1. For comparison, the global range of upper carbon export is only typically 1-4 mol C m-2 yr-1. These extremely high AOU rates also are sharply analogous relafive to export flux solved from POC inventory, which falls within the range of 1-2 mmol C m-2 d-1.\nI suspect there are two possible reasons for the discrepancies. It is well known that the evolufion of eddy typically results in a significant displacement of water masses. Thereby, observed AOU and POC change rates along the isobars may reflect a confounding result of both biological and physical processes. Therefore, to befter isolate the biologically-induced tracer change that the authors are interested in, it would be more appropriate to quanfify the fime rate change of AOU (and POC as well) along with the isopycncal surfaces.\nThe second possible reason is the float didn’t exactly track the same water mass and may gradually move towards a region featured with a higher pre-formed oxygen concentrafion. To rule out this possibility, a more rigorous examinafion of the float hydrographic data and comparison with background spafial oxygen gradients from exisfing gridded products (e.g., WOA and GO-BAI oxygen product) and POC gradients (e.g., climatology of remotely sensed POC) is necessary.\n2) Is it reasonable to interpret the decreasing trend of POC inventory as an enhanced POC export?\nIn principle, when there is an enhanced upper layer POC export event, we usually expect to observe an increase in the POC inventory in the mesopelagic zone, along with a simultaneous elevafion of respirafion (reflected by an increase in AOU).\nNevertheless, the author observed a decline in POC inventory. As the authors menfioned, the POC inventory change in the twilight zone reflects a net balance between the supply term from the upper layer and removal due to the local respirafion (net POC inventory change= POC_sinking_upper-respirafion). There are several possible scenarios that can explain the POC inventory decline", "reviewer_including": "n• Enhanced respirafion outpaces the concurrent elevated upper layer POC export (the scenario that authors have speculated).\n• Elevated respirafion occurs in the context of a constant upper layer POC export.\n• A decline in the POC export accompanied by constant respirafion).\nIt is challenging to rule out other possibilifies unless the authors have the informafion on the respirafion rates, which would enable to back-calculate the exact magnitude of upper layer POC export (POC_sinking_upper = respirafion+ net POC inventory change).\nOther comments:\nLine 32: the eddy-induced upwelling also brings subsurface water rich in DIC into the surface, which may drive the CO2 outgains.\nLine 55: it may be worth menfioning the potenfial impact of eddy-driven carbon export on helping reconcile the long-standing paradox regarding the imbalance between the upper layer carbon supply and deep ocean carbon consumpfion.\nLine 86: a in the Chlorophyll-a should be italicized.\nLine 131: What kind of threshold or criteria do you apply to define the start and end period of the intensifying phase of eddy (i.e., the amplitude confinuously increased over more than one week as you menfioned in the SI). I tried to sort it out from Figure 1 but didn’t find a very consistent criterion. It is very important informafion in your study, so it requires clear clarificafion in the main text of the manuscript.\nLine 241: p should be lowercase and italicized.\n.\nLine 302: There is a need to discuss the caveats of the current study and provide a future roadmap to address these challenges.\nLine 303: A more in-depth discussion is required regarding the potenfial implicafions of your work, such as the imbalance between carbon supply and demand. It would be also eye-opening to discuss the depth to which eddies can affect carbon export transfer, and its significance for long-term carbon sequestrafion, considering that carbon sequestrafion fime is posifive with the depth where carbon is eventually delivered.\nLine 311: should provide the sampling informafion of temporal and verfical resolufion.\nLine 314: Why did you use the dark correcfion value collected during the period before the float deployment? In the standard Chl-a quality control procedure, the dark correcfion typically refers to in situ values at the depths around d 200-300m to account for the near-real-fime background noise.\nLine 323: add the sample number and relevant stafisfical informafion (i.e., R2 and p values). There should be a space between “mmol” and “C”.\nFigure 3: Are there uncertainty esfimates for AOU and POC rates? At the very least, it would take into account the error inherited from the linear fifting. What is unit of AOU rate (mmol C or mmol O2)?\nLine 344: Although the authors have briefly described the method to derive the fime rate of POC and AOU inventory in the result secfion, it is sfill worthwhile providing more detailed informafion in the method secfion. It would be more appropriate to quanfify the POC and AOU rate alongside the isopycnal surface to reduce the impact of the tracer rate induced by water verfical displacement.\nFigure 1: What is the temporal scale of background EKE? Should be clarified in the capfion. All the acronyms shown in the figures should be spelled out in the capfion to make the figure self-explanatory. Does the black line indicate the posifion of the core of the eddy? Should make it clear."}, "author_response": "Responses to Reviewers\nWe thank the four reviewers for their constructive comments and suggestions, which\nwe believe have considerably improved our manuscript now entitled ‘Efficient\nbiological carbon export to the mesopelagic ocean induced by submesoscale fronts’.\nWe have responded point-by-point to the reviewers’ questions and comments below.\nAll page/line/reference/figure numbers refer to the tracked manuscript. Reviewers’\ncomments are in regular text, our responses are in blue and new text from the\nmanuscript is in blue italics.\nReviewer #1 (Remarks to the Author):\nThis study presents an observation-based analysis of the relationship between\nparticulate organic carbon (POC) and eddy and frontal dynamics. The authors have\nleveraged observations from floats with the objective to bring new insights into carbon\nexport dynamics at fine scale. This is a valuable effort; yet there are major issues that\nneed to be addressed before it can be published. The main concerns fall in 4 categories:\nI. Gaps in context and references to prior work in introduction and discussion of the\nresults, specifically the potential impact of frontal subduction (comment #1)\nII. Missing or weak justification of the hypotheses used to interpret the data that account\nfor the compounding effects of spatial and temporal variability, specifically the\njustification to use a “mostly spatial” or a “mostly temporal” framework depending on\nthe eddy/front considered (comments #2-5)\nIII. Shortcomings with the conclusions and generalizations of the results that link fronts\nto POC export and attenuation coefficient b, which is the main point of the paper\n(comments # 6-10).\nIV. Imprecisions on the approach that need clarification, issues with text and figures.\n(comments #11-28).\nDetailed comments and suggestions on how to address them are provided below. The\ntwo reviewers that contributed to this review believe the authors can improve the\njustification of their approach, as well as the interpretation and generalization so the\nmanuscript can be acceptable for publication.\nResponse: We thank the reviewer for the thoughtful and constructive suggestions. We\nfind that the paper is significantly strengthened by addressing the four issues you are\nconcerned with. We have responded to these questions and comments point-by-point\nbelow.\n1. Gaps in context and references. The sentence of L71 is not true: “In this study, for\nthe first time, we show the capability of using BGC-Argo floats equipped with optical\nsensors to estimate the carbon export flux and associated vertical attenuation in\nresponse to submesoscale fronts”\nThe paper is lacking key references, in particular prior studies identifying and\nquantifying the role of subduction by fronts, including with BGC-Argo floats. The\nmanuscript leads us to believe that there were no attempts to quantify this subduction\npump before. Yet observation based (using float AOU, spiciness) and high resolution\nmodeling papers have been published on this topic (see list of reference below). They\nneed to be included to provide the adequate context in the introduction but also in the\ndiscussion. Note that the process of export by subduction along fronts explained in this\nstudy can be called differently in the literature: eddy pump, eddy subduction pump etc.\nAlthough the term “eddy pump” was often used, it does not usually refer to “Ekman\npumping” in eddies but the subduction by fast velocities associated with meso and\nsubmesoscale fronts, similarly to what is considered in this manuscript.\nSentences that critically need these references include L56-67 (almost all sentences in\nthis paragraph are missing critical references), L71 which needs to integrate these prior\nwork. In discussion, please consider how the impact of subduction would influence\nyour results and discuss considering these prior works.\nReview about export pumps including the physical injection pump or eddy pump:\nBoyd, P.W., Claustre, H., Levy, M., Siegel, D.A., Weber, T., 2019. Multi-faceted particle\npumps drive carbon sequestration in the ocean. Nature 568, 327.\nhttps://doi.org/10.1038/s41586-019-1098-2\nPapers estimating the role the “eddy subduction pump” using BGC-Argo, cruises and\nmodels:\nErickson, Z.K., Thompson, A.F., 2018. The Seasonality of Physically Driven Export at\nSubmesoscales in the Northeast Atlantic Ocean. Global Biogeochemical Cycles 32.\nhttps://doi.org/10.1029/2018GB005927\nLacour, L., Llort, J., Briggs, N., Strutton, P.G., Boyd, P.W., 2023. Seasonality of\ndownward carbon export in the Pacific Southern Ocean revealed by multi-year robotic\nobservations. Nat Commun 14, 1278. https://doi.org/10.1038/s41467-023-36954-7\nLlort, J., Langlais C., Matear R., Moreau S., Lenton A., Strutton Peter G., 2018.\nEvaluating Southern Ocean Carbon Eddy‐Pump From Biogeochemical‐Argo Floats.\nJournal of Geophysical Research: Oceans 123, 971–984.\nhttps://doi.org/10.1002/2017JC012861\nMcGillicuddy, D.J., Resplandy, L., Lévy, M., 2019. Estimating particle export flux from\nsatellite observations: Challenges associated with spatial and temporal decoupling of\nproduction and export. Journal of Marine Research 77, 247–258.\nhttps://doi.org/10.1357/002224019828474331\nOmand, M.M., D’Asaro, E.A., Lee, C.M., Perry, M.J., Briggs, N., Cetinić, I.,\nMahadevan, A., 2015. Eddy-driven subduction exports particulate organic carbon from\nthe spring bloom. Science 348, 222–225. https://doi.org/10.1126/science.1260062\nResplandy, L., Lévy, M., McGillicuddy Jr., D.J., 2019. Effects of Eddy-Driven\nSubduction on Ocean Biological Carbon Pump. Global Biogeochemical Cycles 33,\n1071–1084. https://doi.org/10.1029/2018GB006125\nStukel, M.R., Song, H., Goericke, R., Miller, A.J., 2017. The role of subduction and\ngravitational sinking in particle export, carbon sequestration, and the remineralization\nlength scale in the California Current Ecosystem: Subduction and sinking particle\nexport in the CCE. Limnology and Oceanography 63, 363–383.\nhttps://doi.org/10.1002/lno.10636\nResponse: Thank you for pointing this out. We agree that prior works on subduction\nby fronts should be included in the introduction, and its impacts on our results should\nbe discussed, as subduction by fronts is one of the most important dynamics by which\nsubmesoscale processes affect local POC distributions. We deleted that inaccurate\nstatement in this revision. The changes in the introduction and discussion sections are\nsummarized below:\n1. Changes in the introduction section\nTo provide a more adequate context in the introduction that the submesoscale process\naffects local POC export, we first added one sentence in Lines 57-60 to mention the\neddy-subduction pump:\n‘The vertical motions can inject high POC produced in the euphotic zone into the\nmesopelagic layer (referred to as eddy subduction pumps)17,19,22,24, resulting in long-\nterm carbon sequestration17,19,20,23.’\nSecond, prior works that attempted to identify and quantify eddy subduction pumps\nhave been acknowledged in Lines 68-71:\n‘Prior studies have captured anomalous features of elevated POC at depth, which are\ninterpreted as evidence of eddy subduction pump19,22,23. Despite their potential\nimportance in shaping POC export, direct observations of the downward POC flux and\nits attenuation in response to submesoscale fronts are scarce17,19-21,23,41.’\nand Lines 76-81 :\n‘Observational and high-resolution modeling studies have suggested that the eddy\nsubduction pump contributes ~19% to 50% to the total export of POC. In contrast,\nResplandy et al. (2019) explored the integrated effects of eddy subduction hot spots on\nthe biological carbon pump and found that they contribute less than 5% to carbon\nexport due to the strong compensation between upward and downward fluxes.’\nAdditionally, key references have been added in Lines 71 (Omand et al., 2015; Llort et\nal., 2018; Erickson et al., 2018; Lacour et al., 2023; Boyd et al., 2019) and Line 86\n(Llort et al., 2018; Lacour et al., 2023).\nFinally, we acknowledge that Llort et al. (2018) was the first to quantify the carbon\nexport flux associated with submesoscale fronts by using BGC-Argo. Previous studies\nthat quantified the carbon export flux at submesoscale using BGC-Argo have also been\ncited in this revision. In comparison, however, these previous studies didn’t consider\nthe vertical attenuation of the carbon flux at submesoscale fronts, which is the main\ncontribution of our study. To integrate the previous efforts and clarify the novelty of\nour results, we have rephrased the sentence as shown below (Lines 91-96):\n‘The BGC-Argo has been used to identify elevated POC in the mesopelagic layer and\nestimate the carbon flux associated with submesoscale features20,23. In this study, we\nfurther show the capability of using BGC-Argo floats to estimate the transfer efficiency\nof carbon export in response to submesoscale fronts.’\n2. Discussion on the impacts of subduction on POC export\nWe agree with comments #8 and #9 that the impacts of subduction by front should be\ntaken into account to interpret our results. More discussion has been added in this\nrevision.\nAs you mentioned in comment #9, the high POC at a depth of 200 m at the edge of CE\n1 could be due to subduction of POC from the productive layer by the front. After a\ndetailed examination, we agree with this comment and have added additional text\n(Lines 376-382) to discuss this point. Please see our response to this comment #9.\nOn the other hand, we found that the influence depth of eddy subduction may not be\ndeep enough to affect the lower mesopelagic layer. The elevated POC concentration\nand flux were only present at depths between Z and ~250 m. We tested different ways\nEu\nto fit the POC flux attenuation coefficient (b) with and without considering the POC\nflux in the subduction layer (Z ~250 m). The b value was about 0.65 excluding the\nEu\nPOC flux in the eddy subduction layer, which was higher than that considering the\nsubduction layer (b=0.56), but was still lower than those estimated in eddies and normal\nconditions. This suggests that submesoscale dynamics affect POC export flux not only\nthrough physical subduction but also through modulating particle properties (e.g., size,\nsinking speed and composition). We have added a paragraph (Lines 373-393) to fully\ndiscuss the impact of eddy subduction on our results. Please find our detailed response\nto comment #8.\nReferences:\nBoyd, P.W., Claustre, H., Levy, M., Siegel, D.A., Weber, T., 2019. Multi-faceted particle\npumps drive carbon sequestration in the ocean. Nature 568, 327–335 (2019).\nResplandy, L., Lévy, M. & Mcgillicuddy, D. J. Effects of eddy-driven subduction on\nocean biological carbon pump. Glob. Biogeochem. Cycles 33, 1071–1084 (2019).\nOmand, M. M. et al. Eddy-driven subduction exports particulate organic carbon from\nthe spring bloom. Science 348, 222–225 (2015).\nLacour, L., Llort, J., Briggs, N. et al. Seasonality of downward carbon export in the\nPacific Southern Ocean revealed by multi-year robotic observations. Nat. Commun. 14,\n1278 (2023).\nErickson, Z. K. & Thompson, A. F. The seasonality of physically driven export at\nsubmesoscales in the Northeast Atlantic Ocean. Global Biogeochem. Cycles 32, 1144–\n1162 (2018).\nStukel, M. R., Song, H., Goericke, R. & Miller, A. J. The role of subduction and\ngravitational sinking in particle export, carbon sequestration, and the remineralization\nlength scale in the California Current Ecosystem. Limnol. Oceanogr. 63, 363–383\n(2018).\nLlort, J. et al. Evaluating Southern Ocean carbon eddy-pump from biogeochemical-\nargo floats. J. Geophys. Res. Ocean. 123, 971–984 (2018).\nMcGillicuddy, D. J. et al. Estimating particle export flux from satellite observations:\nChallenges associated with spatial and temporal decoupling of production and export.\nJ. Mar. Res. 77, 247–258 (2019).\nLévy, M. et al. The Impact of Fine-Scale Currents on Biogeochemical Cycles in a\nChanging Ocean. Annu. Rev. Mar. Sci. 16,1 (2024).\n2. Missing justification of the hypotheses, specifically the justification to use a “mostly\nspatial” or a “mostly temporal” framework to interpret the float data.\nThe authors alternatively interpret the observed changes along the float trajectories as\n“mostly spatial changes” (CE1 and ACE1, Figure 2), or “mostly temporal changes” i.e.\npseudo lagrangian (CE2 and front, Figure 3). The hypothesis of “mostly temporal” is\njustified in the text for CE2 (L128 and 141). However, the justification to interpret as\n“mostly spatial” the changes along CE1 and ACE1 is missing, and the hypothesis to\ninterpret as “mostly temporal” the changes attributed to frontal dynamics seems\ninadequate (see details in comments 3 and 4 below). We encourage the authors to\nexplain clearly and early these different strategies to orient and prepare the reader.\nResponse: Thank you for pointing this out. In this study, we performed different\nanalyses based on different sampling scenarios of the floats to delineate temporal and\nspatial variabilities of the measured variable. For the hypothesis of ‘most spatial\nchanges’ in eddies (CE1 and ACE1), we first showed a radial increase of the relative\ndistance between the float and the eddy center with time. Then, we demonstrated that\nthe change of surface Chl measured by the floats was consistent with the radial variation\nof remote-sensed surface Chl from the eddy core to the eddy edge. In addition, with\nremote sensing data, we can track the temporal evolution of Chl in eddies, and this\ntemporal pattern was completely different from the change of float-measured surface\nChl. Therefore, for this sampling period, we think the float-measured variability of POC\ncan be used to represent the spatial variability of POC from the eddy core to the eddy\nedge.\nFor the hypothesis of ‘most temporal changes’ along a submesoscale front, we added\nmore analysis about the float-measured characteristics of the water masses. We also\nconducted a numerical particle tracking experiment. These new results all suggest that\nthe float continuously drifted along the warm side of the front on which homogeneous\nwater masses were sampled. During this period, the front experienced intensifying and\ndecaying stages, while the float was still sampling along its warm side. As such, the\nfloat observations at the front can be interpreted as a temporal signal due to the stage\nchange of the front.\nFollowing the suggestions, we now justify these two hypotheses early in Sections 2.1\nand 2.3, respectively. Please see more details in our following responses to comments\n#3 and #4.\n3. The authors need to demonstrate why it is justified to ignore temporal variations\nwhen analyzing CE1 and ACE1. Figure 2 interprets all POC data as spatial changes\n(using radial structure of the eddies CE1 and ACE1). The approach is attractive, but the\ntext and figures should clearly show that this is a valid hypothesis. Specifically, how\nmuch of the signal that is interpreted as spatial variability across the eddy is in fact\nintroduced by the temporal evolution along the trajectory of the float? At least, the\nauthors could indicate the day of sampling for each data point on Figure 2? [Colors\ncould indicate the day of sampling while symbols could indicate the depth]. This would\nallow the reader to see how much of the variations attributed to the spatial structure of\nthe eddy could be introduced by temporal changes.\nResponse: Thank you for the constructive comment. For CE 1 and ACE 1, we\ninterpreted the measured variability of POC as the radial structures of eddies based on\nthe following considerations:\nFirstly, there was an increasing relative distance between the float and the eddy center\nwith time. The location of the float changed from inside the eddy to outside the eddy,\nwith a relative distance of r/R between 0.4~2.0 for CE 1 and 0.23~1.2 for ACE 1.\nSecondly, the spatial distribution of Chl in eddies was derived by compositing the\nremote-sensed sea surface Chl over the float sampling period. This satellite-derived Chl\nwas then interpolated onto the relative locations of the float in eddies to compare with\nthat measured by the float. In CE 1, both the satellite- and float-derived Chl decreased\nand then increased in the radial direction, reaching a peak at r/R=1~1.5 (Fig. S2). In\nACE 1, both the satellite- and float-derived Chl showed a double peak pattern along the\nradial direction (Fig. S2a). The correlations between the satellite- and float-derived Chl\nwere 0.39 (p=0.01) and 0.43 (p=0.09) for CE1 and ACE 1, respectively. The relatively\nconsistent changing patterns of Chl between the float and remote sensing data suggest\nthat the float captured the spatial variability of the eddies in the radial direction.\nLastly, it is likely that the temporal signal was also included in the float data as it\nexhibited larger 95% confidence intervals than those derived from satellite observations\n(Fig. S2a). With remote sensing data, we can track the temporal evolution of the Chl in\neddies, and this temporal pattern was completely different from the change of float-\nmeasured surface Chl (Fig. S2b). The correlations between the satellite- and float-\nderived Chl over time were -0.18 (p=0.24) and -0.05 (p=0.82) for CE1 and ACE 1,\nrespectively, suggesting that the variability explained by the temporal evolution of Chl\nof eddies was much small. Therefore, for this sampling period, we think the float-\nmeasured variability of variables can be used to represent the spatial variability of\neddies.\nTo clarify this point, we added the following sentences in Lines 143-154 and Fig. S2\nbefore we presented the radial POC distributions in the text:\n‘The floats may capture the spatial variability of tracers for CE 1 and ACE 1 as the\nlocation of the floats changed from inside the eddies to outside the eddies. The satellite-\nderived sea surface Chl was averaged over the float sampling period and then\ninterpolated onto the relative locations of the float in eddies to compare with that\nmeasured by the float. The float-measured Chl was in good agreement with that derived\nfrom satellites in the radial direction (Fig. S2a), with correlations of 0.39 (p=0.01) for\nCE1 and 0.43 (p=0.09) for ACE 1. In contrast, the temporal evolution of satellite-\nderived Chl averaged inside eddies was completely different from that of float-\nmeasured Chl (Fig. S2b), indicated by low correlations (R= -0.18 (p=0.24) for CE 1\nand R=-0.05 (p=0.82) for ACE 1). Therefore, the float-measured tracers during this\nperiod can be used to represent the spatial variability of the eddies along the radial\ndirection.’\nAnother thing worth mentioning is that the high POC distribution at the edge of CE 1\nwas due to subduction by the front (please see our reply to comment #9). This further\nstrengthens the point that the distributions of POC captured by the float reflect the\nspatial variability of the eddy. We have added the following sentence in Lines 169-170\nto emphasize this point:\n‘This further supports that the radial distributions of POC measured by the float reflect\nthe spatial variability of the eddy.’\nFollowing the reviewer’s suggestion, colors have been indicated in Fig. 2. For CE 1, as\nthe float moved almost monotonically from the eddy core to the edge with time, it is\nstill not easy to tell the influence of the temporal signal from this figure. Figure R1\nshows the variations of the strength of the eddies. It is clear that although CE 1 was\nstrengthened in early May while the float was at r/R=~1.3, the float-measured POC at\nSCM layer was still lower than that measured at the eddy core (Fig. 3), implying\ndominant variability caused by space instead of time.\nFigure S2. Comparison of sea surface Chl between satellite and BGC-Argo\nobservations in both spatial and temporal variability. a Radial distribution of sea surface\nChl at the float locations derived from both the BGC-Argo and satellite observations.\nThe BGC-Argo results are directly obtained from the surface Chl measured by the float.\nThe satellite-derived Chl values are calculated by averaging the Chl from OC-CCI over\nthe float sampling period and then interpolating to the relative locations of the float in\neddies. Because the eddies propagated over time, the location of the float in the eddies\nwas constructed by calculating the azimuthal and radial positions of the float relative to\nthe eddy center. b Satellite-derived Chl averaged inside eddies and sea surface Chl\nderived from BGC-Argo observations. The BGC-Argo results are directly obtained\nfrom the surface Chl measured by the float. The satellite-derived Chl values are\ncalculated by averaging the satellite-derived Chl values inside the eddies at the time\nwhen the float was at the position of r/R.\nFigure 3. POC distributions at different depths within a CE 1 and b ACE 1.\nFigure R1. Evolution of SLA averaged inside eddies.The SLA values are calculated by\naveraging the SLA inside the eddies at the time when the float was at the position of\nr/R.\n4. The hypothesis of “mostly temporal” is highly disputable for the front. It is ok for\neddy CE2 because the float seems to stay stuck close to the center of the eddy, and most\nchanges can be interpreted as temporal changes. In the case of the front, however, the\nfloat seems to be sampling different parts of the front. The associated changes in SLA,\nPOC, AOU etc. are therefore likely to come from spatial variations across the front and\nnot temporal variations. The authors could demonstrate that it is indeed temporal,\nhowever it is unlikely to be successful and convincing given the complexity of the\ndynamics in the frontal structure. This shortcoming has major implications for the result\ninterpretation and the conclusions of the paper as the authors interpret these changes as\ntemporal changes while they are likely spatial changes. This section of the results and\nassociated conclusions needs to be revised.\nResponse: Thank you for the insightful comment. According to the frontogenesis\ntheory, when the front is enhanced, it will generate downwelling on the cold side of the\nfront and upwelling on the warm side of the front. The hypothesis of ‘mostly temporal’\nis that the float drifted along one side of the front so that relatively homogeneous water\nmasses over time were sampled. During this period, the front experienced intensifying and\ndecaying stages, while the float was still sampling along its one side. As such, the\nfloat observations at the front can be interpreted as a temporal signal due to the stage\nchange of the front. We have provided more justifications in the revised text to interpret\nthis hypothesis.\nBy investigating the time series of FSLE along the float trajectory, we found that the\nfloat traveled along the same filament with high FSLEs. This result, in combination\nwith the Chl, SST and SST gradient distributions (already shown), demonstrated that\nthe float continuously traveled along the warm side of a front during that period.\nTo further support that the float drifted along one front, a numerical particle tracking\nexperiment was conducted at the frontal region using the TRACMASS code. The\nparticle was released at the same location as the float on 21 April 2019 and it was moved\npurely by advection using the surface geostrophic current derived from AVISO data.\nThe numerical tracking results showed that the float mainly followed the path of the\nparticle (Fig. S14), suggesting that the float moved in a quasi-Lagrangian manner and\nsampled a similar water mass during the analysis period (supplementary information\nText S3).\nThe homogeneous water masses sampled on one side of the front can be supported by\nthe transect of temperature and salinity anomalies (Fig. S6). The temperature was\nhigher in the upper 300 m and the salinity was lower in the upper 150 m depth compared\nto the CE 1 core. In addition, the T-S diagram presents a coherent physical characteristic\nfrom 21 April to 3 May 2019, suggesting that the float was moving along the front but\nnot across the front.\nOverall, these results support the use of the float data as a time series on the warm side\nof the front during the analysis period.\nWe have clarified this point in the text in Lines 247-250:\n‘This is further supported by a Lagrangian particle tracking experiment, which\nsuggests that the float drifted in a quasi-Lagrangian manner and sampled a similar\nwater mass along one side of the front (Text S3).’\n, and Lines 250-255:\n‘The front exhibited a higher temperature in the upper 300 m and lower salinity in lower salinity in the\nupper 150 m depth compared to the CE 1 core (Fig. S6), suggesting homogeneous water\nmasses sampled at the frontal region. The T-S diagram demonstrates a coherent\nphysical characteristic from 21 April to 3 May 2019 (Fig. S6). All these results suggest\nthat the float sampled homogeneous water masses along the warm side of the front.’\nText S3. Lagrangian particle tracking experiment on the front\nTo investigate whether the float drifted along the front, a numerical particle tracking\nexperiment was conducted using the TRACMASS Lagrangian trajectory code (Döös,\n1995; Blanke & Raynaud, 1997). The particle was released at the same location as the\nfloat on 21 April 2019 and transported purely by surface current. Here, we run the code\nwith the current velocity derived from AVISO. The Lagrangian particle trajectory\nderived from the particle tracking model demonstrated that the virtual particle starting\nat the location of the float moved along the front (Fig S14). The float moved slower\nthan the particle but mainly followed its path, suggesting that the float drifted in a\nquasi-Lagrangian manner during the analysis period. The difference in moving velocity\nis that the particle was only transported by surface current, whereas the motion of the\nfloat was driven by both the surface and deep currents.\nFigure S14. Trajectories of the BGC-Argo and the virtual particle over the period when\nthe float was on the front (21 April - 3 May 2019). The particle was released at the same\nposition as the float on 21 April 2019 and transported by the surface current velocity\nderived from AVISO. The particle trajectory was tracked using the TRACMASS code.\nColor indicates the dates. Blue and red lines are the contour lines of the sea level\nanomaly (SLA). Arrows represent the sea surface current velocity anomaly.\nFigure S6. Physical characteristics of the float measurements. During 21 April - 3 May\n2019, the float was on one side of the front. Time series of a temperature, b salinity, c\ntemperature anomaly and d salinity anomaly measured by float 2902753 from 1 April\nto 3 May 2019. The black, red and cyan lines indicate the mixed layer depth (MLD),\nthe depth of subsurface chlorophyll maximum (Z ) and the euphotic zone (Z ),\nSCM Eu\nrespectively. The white lines are the isopycnals of 23, 24 and 25 kg m-3. The temperature\nand salinity anomalies were defined as the instantaneous values after subtracting the\nfull time mean. e Temperature-salinity diagram with data points from float 2902753\nfrom 1 April to 3 May 2019. The color indicates the sampling date.\n5. The sampling context should be better presented. In Figure 1, eddies and float\ntrajectories appear completely disconnected. This is likely because the black lines show\nthe center of the eddy and not their span. Could you indicate the radius of the eddies\naround the trajectories so we can see that they were indeed in the eddies? Also we\nencourage the authors to include a figure similar to Figure S4a to show the float relative\nto the eddy/front. Maybe choose snapshots that show the overlap with the front as a\nfunction of time.\nResponse: Thank you for this suggestion. The gray lines indicating the eddy radius\nhave been overlapped in Fig. 1a to show the connection of the eddy centers and the\nfloats. Additionally, snapshots showing the locations of the floats relative to the eddies\nand the front have been included in the new Figure 2.\nFigure 2. The BGC-Argo and eddy trajectories. a The locations of (yellow dots) the\nBGC-Argo float (WMO number 2902753) and (orange pentagrams) the center of\ncyclonic eddy 1 (CE 1) during 1-20 April 2019. b The locations of (yellow dots) the\nBGC-Argo float (WMO number 2902753) and (orange pentagrams) the center of\nanticyclonic eddy 1 (ACE 1) during 12 July - 2 September 2019. c The locations of\n(yellow dots) the BGC-Argo float (WMO number 2902756) and (orange pentagrams)\nthe center of cyclonic eddy 2 (CE 2). d The locations of the BGC-Argo floats along the\nfront during 21-27 April 2019. The yellow line is the float trajectory from 21 April to 3\nMay 2019. e The same as d but during 28 April-3 May 2019. Background color and\nisolines represent sea surface chlorophyll and sea level anomalies, respectively. The\narrows are the geostrophic velocity anomaly.\n6. Generalization between front and carbon export. L214-222. “A strong correlation\nbetween the b value and GM was found …. This statistical relationship implies that a\nstrong front is linked with high POC transfer efficiency to the mesopelagic layer, which\ncould be used as a parameterization to account for the impact of fronts on carbon export\nin large-scale models, once the front intensity at the surface is known”. This conclusion\nseems not backed up by the results. More complete models seem to show that b can\nvary according to many other biophysical parameters, making this generalization highly\ndebatable (see for instance Ngyuen et al. 2022: Microbes contribute to setting the ocean\ncarbon flux by altering the fate of sinking particulates). This is one of the main points\nof the paper; the caveats need to be discussed properly.\nResponse: Thank you for pointing this out. We agree that a parametrization of the b\nvalue as a function of the front intensity is inadequate since the efficiency of POC\ntransfer is modulated by complicated physical and biogeochemical processes. We have\nrephrased the sentence as follows to be clearer:\n‘This statistical relationship implies that a strong front is linked with high POC transfer\nefficiency to the mesopelagic layer, which could be used to estimate the impact of fronts\non carbon export at the basin-scale oceans.’\nWe used this relationship to estimate the impacts of fronts on POC transfer efficiency.\nThe underlying mechanism is that submesoscale dynamics play a role through their\nimpact on the particle sinking velocity or particle lability. The following discussion has\nbeen added to the manuscript (Lines 405-413):\n‘The estimation suggests that submesoscale fronts are important in setting the spatial\nand temporal variations in POC transfer efficiency. Previous carbon cycle studies have\nsuggested that the attenuation of the POC flux is determined by the rate of POC\nproduction in the euphotic zone, the sinking velocity of particles, and the rate of POC\nconsumption in the mesopelagic layer5-10,38,39,49-54. Submesoscale dynamics may play a\nrole in POC flux transfer through eddy subduction that directly enhances the particle\nsinking velocity or through its impacts on the plankton community structure in the\neuphotic zone that generates particles with large sinking velocities and/or low\nremineralization rates9,14-23,32.’\nThe caveat of the estimation conducted in this study is that we did not explicitly include\nother physical and biogeochemical processes that affect POC flux attenuation. These\nprocesses include mixed layer pumping, bacterial colonization and consumption,\nzooplankton migration, consumption, and fragmentation. However, there are no clear\ndata or previous studies showing why these processes could be particularly enhanced\nor weakened at fronts. We provide some discussions here. We think inclusion of these\nprocesses may allow a better constraint in estimating POC transfer efficiency, but it\ndefinitely requires future work to examine how submesoscale dynamics affect these\nprocesses. To clarify this point, we have added the following sentences to the text (Lines\n413-425):\n‘Our estimation suggests that submesoscale fronts increase the POC transport\nefficiency in the NPSG. However, it should be kept in mind that other processes that\ncan potentially modulate the b value (e.g., microbial POC consumption49,54, POC\nfragmentation by zooplankton8) were not explicitly included in the estimation.\nQuantifying the mesopelagic fragmentation processes revealed that roughly half of the\nobserved flux attenuation was due to the fragmentation of large particles into small\nparticles8. Ngyuen et al. showed that microbial dynamics may play a significant role in\nshaping the POC flux profiles observed in global oceans54. How these dynamics\nrespond to submesoscale fronts, however, is still not clear. Future work including\ndynamics such as microbial consumption and zooplankton disaggregation of the\nparticles is needed, and may allow for better constraints on the relative contributions\nof submesoscale fronts to the basin-scale carbon transport efficiency.’\n7. Conclusion about seasonality and export. line 234: You did not take into account that\nthe seasonality of mesoscale and frontal dynamics is different from the seasonality of\nPOC content in the water column. Consequently, the amount of POC transported by the\nsame front strength varies depending on the season. This could completely reverse your\nconclusion about the seasonal evolution of the parameter b. Please revise or strengthen\nthese points.\nResponse: Thank you for pointing this out. The relationship between the b value and\nsubmesoscale dynamics was derived from multiple observations in subtropical gyres,\nwhich cover both winter and summer months. This suggests that submesoscale\ndynamics can significantly affect POC transport efficiency in different seasons. As the\nPOC transport efficiency is largely determined by the b value, POC concentration\nusually won’t affect the transport efficiency. Instead, the properties of the POC (e.g.,\nsize, lability) are important in changing the b value. Submesoscale dynamics have been\nsuggested to affect the POC transfer efficiency by stimulating the growth of large\nplankton, which in turn generate large and rapidly sinking particles at the front.\nRegarding the same POC concentration with slow sinking in the background and with\nfast sinking at the front, the POC transfer efficiency will be higher at the front than in\nthe background. Therefore, to derive a robust b value function, the properties of POC\nshould also be considered. However, there are few POC property data available for now.\nWe examined the dataset from Station ALOHA, and found that the relationship between\nthe b value and POC concentration was not clear at the seasonal timescale. At ALOHA,\nlong-term records of the POC flux profiles suggest that the POC transfer efficiency is\nhigher in winter than in summer (Fig. S16). On the other hand, the POC concentrations\nare generally higher in summer than in winter, which is indicated by the averaged\nprofiles of POC at ALOHA (Fig. R2).\nOverall, the result of a lower b value in winter than in summer derived from the\nrelationships of both b and b is in good agreement with the in situ result at ALOHA\nT GM\n(Fig. S16), suggesting that the conclusion is likely robust. To support our results, the\nobservational results of the seasonality of the b value (Fig. S16) have been included in\nthe text.\nFigure S16. The seasonal b value at the ALOHA station. a POC flux profiles and the\ncorresponding Martin curves in summer. Black dots are observational profiles from\nsediment traps. Gray lines are the fitted Martin curves. The blue line is the Martin curve\nderived from the averaged b value and averaged POC flux at 150 m. b is the same as a\nbut in winter. c The b value and R2 for each observational POC flux profile in both\nsummer and winter. We picked up all observational POC flux profiles with at least three\nvertical sampling points for Martin curve fitting. The b values in summer are\nsignificantly different from those in winter, as h=1 and p=0.036 in the two-sample t test\nresult.\nFigure R2. The seasonally averaged POC profiles at ALOHA. a The vertical\ndistributions of POC concentrations in summer averaged over 1998-2021. The bars\nshow the averaged POC at depths of 150 m, 200 m, 250 m, 350 m, 500 m and 750 m.\nThe orange line is the fitted attenuation curve of the averaged POC concentrations with\ndepth. Error bars show one standard deviation for the averaging. b The same as a but\nin winter.\n8. Missing consideration of subduction #1. The POC export depth by fronts also\ndepends on the penetration depth of the vertical velocities associated with the fronts\n(subduction, see comment #1 for a list of papers that describe this). Shallow fronts do\nnot allow POC to be exported below the pycnocline and would limit the frontal effect\non b, further weakening your conclusion and the link established between fronts and\nPOC export/attenuation coefficient. Please consider this effect of subduction in\nintroduction and importantly in your results and interpretation. This is one of the\nweakest point of the paper. See also comment 9 below.\nResponse: Thank you for the constructive suggestion. In this study, we consider two\nmechanisms affecting POC export at fronts, which have been shown to be important in\nother regions in previous studies. The first mechanism is through biological carbon\npump. Strong submesoscale flows can enhance the vertical nutrient supply, alter the\nphytoplankton community structure, and generate particles sinking to depth. Some of\nthe particles generated through this mechanism, if not remineralized quickly, have the\npotential to penetrate the pycnocline and reach the mesopelagic layer via gravitational\nsinking. The second mechanism is through subduction, by which particles are carried\ndownward with the water mass. For this mechanism, the vertical depth the particle can\nreach is largely determined by the subduction velocity and the ventilation depth. Of\ncourse, these two mechanisms could coexist in some cases. Following the reviewers’\ncomments, we added more discussion about the effect of subduction in this revised\nmanuscript.\nFrom our data, two lines of evidence revealed that eddy subduction contributes to POC\nexport at the front. First, a higher POC concentration between Z (bottom of the\nEu\neuphotic zone) and ~250 m depth at the front than that in CE 1 was captured by the\nfloat, which is likely due to subduction of POC from the productive layer by the front\n(see details in Reply #9). Second, the POC fluxes between Z and ~250 m depth were\nEu\nhighest in the vertical direction, which is different from the classical biological carbon\npump curve and implies POC supply from other mechanisms (Fig. S10). As the high\nPOC signal was associated with tilting isopycnals, it was very likely induced by\nsubduction at the front.\nHowever, subduction appeared limited to depths between Z and ~250 m (Figs. S9 and\nEu\nS10). We tested different ways to fit the POC flux attenuation coefficient (b) with and\nwithout considering the POC flux in the subduction layer (Z ~250 m). The b value was\nEu\napproximately 0.65 excluding the POC flux in the subduction layer, which was higher\nthan that considering the subduction layer (b=0.56) but was still lower than those\nestimated in eddies and normal conditions. This suggests that submesoscale dynamics\naffect POC export flux not only through physical subduction but also through\nmodulating particle properties (e.g., size, sinking speed, and composition). Our results\nemphasize the complexity of submesoscale dynamics at play in enhancing POC transfer\nefficiency.\nAs we mentioned in the response to comment #1, the introduction of the effect of the\neddy subduction pump has been included in the introduction section. Additionally, we\nadded one paragraph in the discussion section to interpret and fully discuss the impact\nof the eddy subduction pump on our results (Lines 373-393):\n‘The high transfer efficiency of POC at the front could also result from the physical\nsubduction of POC by the intense submesoscale vertical velocities. Two lines of\nevidence have revealed that the eddy subduction pump contributes to carbon exports at\nthe front. First, frontal dynamics are responsible for the elevated POC at 200 m depth\nat the CE 1 edge of r/R=1 and 1.3 (Fig. 2a). At the positions of r/R=1 and 1.3, the float\nwas right on the filaments of high FSLE accompanied by high M2 and small R in the\ni\nvertical direction, which is suggestive of ongoing intense submesoscale vertical motions\n(Fig S5). Concurrence with the physical dynamics was an elevated POC concentration\nbetween Z and ~250 m compared to those in CE 1 (Fig. S9), which is evidence of eddy\nEu\nsubduction pump suggested in previous studies17,19,20,23. Second, the POC fluxes\nbetween Z and ~250 m influenced by the eddy subduction pump were obviously higher\nEu\nthan those above Z and below 250 m (Fig. S10). We tested different ways to fit the\nEu\nPOC flux attenuation coefficient (b) with and without considering the POC flux in the\nsubduction layer (Z ~250 m). The b value was approximately 0.65 excluding the POC\nEu\nflux in the subduction layer, which was higher than that considering the subduction\nlayer (b=0.56) but was still lower than those estimated in eddies and normal conditions.\nThis suggests that submesoscale dynamics affect POC export flux not only through\nphysical subduction but also through modulating particle properties (e.g., size, sinking\nspeed, and composition). These results emphasize the complexity of submesoscale\ndynamics at play in enhancing POC transfer efficiency.’\nFigure S9. Vertical POC concentration distributions. a-b Time series of a POC\ndistribution and b POC anomaly measured by float 2902753 from 3 April to 3 May\n2019. The black, red and cyan lines indicate the mixed layer depth, depth of the\nsubsurface chlorophyll maximum and euphotic zone, respectively. The POC anomalies\nwere defined as the instantaneous values subtracting the full time mean. c Vertical\ndistributions of the POC anomaly in CE 1 and at the front.\nFigure S10. POC flux profiles. a The POC flux between Z and 250 m that is affected\nEu\nby eddy subduction pump (ESP) is accounted for when estimating the b value. b The\nESP effect is not accounted for when estimating the b value. The black dashed lines and\nerror bars correspond to the euphotic zone depth and one standard deviation,\nrespectively. The red areas represent the euphotic zone.\n9. Missing consideration of subduction #2. L118: “The POC distributions attenuated\nfaster in the CE 1 center than at its edge, which is likely due to the higher\nremineralization of the newly produced and easily degradable organic matter inside the\neddy core8,36,37.” Is this really what is happening here? Couldn’t it be that intense\nvertical velocities associated with the frontal dynamics at the boundary of the eddies\nare transporting/subducting material down?\nResponse: As the reviewer suspected, the POC attenuated more slowly at the CE 1 edge\nthan in its center because the subduction of POC by the front increased the subsurface\nPOC at the edge. Specifically, the POC at 200 m presented a high value at r/R=~1 and\n1.3, where the float was right on filaments undergoing intense submesoscale vertical\nmotions. The proof to support this conclusion comes from the concurrence of high\nFSLE at the surface, large along-track M2 and small R in the vertical direction (see Fig.\ni\nS7). Meanwhile, the POC was higher between Z and ~250 m at the front compared\nEu\nto the eddy edge of other positions, likely due to subduction of POC from the productive\nlayer by the front (Fig. S9). We have therefore rephrased this sentence as follows (Lines\n165-169):\n‘The POC at 200 m reached its peaks at the edge of r/R=~1 and 1.3, which is likely due\nto subduction of POC from the productive layer by the front17,19,20,23’\nMore interpretations of the results have been added in the discussion section,\nspecifically with the group of sentences shown below (Line 376-382):\n‘the frontal dynamics are responsible for the elevated POC at a depth of 200 m at the\nCE 1 edge of r/R=1 and 1.3 (Fig. 3a). At the positions of r/R=1 and 1.3, the float was\nright on the filaments of high FSLE accompanied by high M2 and small R in the vertical\ni\ndirection, which is suggestive of ongoing intense submesoscale vertical motions (Fig\nS5). Concurrence with the physical dynamics was an elevated POC concentration\nbetween Z and ~250 m compared to those in CE 1 (Fig. S9), which is evidence of eddy\nEu\nsubduction pump suggested in previous studies17,19,20,23.’\nFigure S7. The lateral buoyancy frequency ( ), Richardson number (R) and finite-\ni\nsize Lyapunov exponent (FSLE) at the front. a2 BGC-Argo-derived lateral buoyancy\n𝑀\nfrequency during 21 April-3 May 2019. , where s is the along-track\ndirection. The black line represents the m2ixed layer depth. b BGC-Argo-derived\n𝑀 = −𝜕𝑏⁄𝜕𝑠\nRichardson number during 21 April-3 May 2019. , where f and b are the\n2 2\nCoriolis parameter and buoyancy, respectively. T\n𝑅\nh𝑖e\n=\nbl\n𝑓\nack\n𝑏\n𝑧l\n⁄\nin\n𝑏\ne\n𝑠\nrepresents the mixed\nlayer depth. c Surface FSLE at the frontal region (red line) and the lateral buoyancy\nfrequency (blue dashed line) at 100 m during 21 April-3 May 2019. Blue solid lines are\nthe buoyancy frequency envelope.\n10. Generalization to the subtropical Pacific. The generalization to the basin is very\nhand wavy and unconvincing, and probably not needed here. The results can stand alone\nwithout this. The author could in fact point out that the impact at the basin scale and\nglobal scale is still an open question. The conclusion, abstract (and maybe title) should\nbe modified to reflect the changes in conclusions.\nResponse: Thank you for the helpful suggestion. We agree that the submesoscale\nimpact at the basin scale is still an open question and have removed section 2.4 from\nthe main text.\nThe generalization of our results to the Pacific gyre provides an applicable way to\nestimate the effect of fronts on POC transfer efficiency based on satellite data, which\ndefinitely needs further studies to constrain uncertainties but also has the potential for\nfuture studies to explain POC variability in the mesopelagic ocean. In particular, we\nfeel that the reviewers’ comments #6 and #7 have been very helpful in improving this\npart. Based on these considerations, we modified our previous presentations and put\nthis part as a discussion in the supplementary information. The title, abstract and\nconclusions have been modified accordingly. The details are listed below:\nThe title has been changed to ‘Efficient biological carbon export to the mesopelagic\nocean induced by submesoscale fronts’.\nIn the abstract, the following sentences relative to the extrapolation results have been\nremoved (Lines 27-31):\n‘Expanding the results to the subtropical gyre reveals a significant relationship between\nthe Martin curve exponent coefficient (b) and front intensity. The average POC export\nflux at 1000 m may be underestimated by ~20-58% in the NPSG if the contribution of\nsubmesoscale fronts is ignored.’\nFor the previous section 2.4, the presentations have been modified. The section now\nhas been moved to the supplementary information as Text S4.\nIn the discussion section, the following sentences have been added to link the\nobservational results and Text S4 (Lines 396-405):\n‘The impact of fronts on POC transfer efficiency at the basin scale and global scale is\nstill an open question. We combined previous studies that have estimated POC\nattenuation coefficients in the North Pacific and North Atlantic gyres (Table S4, Fig.\nS11). A strong correlation between the b value and GM was found (b =-\nGM\n3.78·GM+1.44; R2=0.52, p<0.01, Fig. 5). The derived relationship between the flux\nattenuation coefficient and the front intensity could be applied to large-scale\napplications. Estimations based on this relationship suggest that the average POC\nexport flux at 1000 m may be underestimated by ~20-58% in the NPSG if the\ncontribution of submesoscale fronts is ignored (Text S4).’\nThe following paragraph has been removed from the discussion section (Lines 330-\n341):\n‘The contribution of eddy intensification to the POC flux of the entire NPSG was\nestimated using eddy dataset. The intensifying cyclonic eddy occupied ~5.7% of the\narea of the NPSG (Fig. S7). This gives an additional POC flux of 0.12±0.03 mmolC m-\n2 d-1 by eddy intensifications in the NPSG in the euphotic zone. Considering the\nobserved mean POC flux of 1.63 mmolC m-2 d-1 from previous studies in this region\n(Table S4), the eddy intensifications can increase the POC flux by ~7.4±1.8% in the\nNPSG. The contribution of front intensifications to the POC flux in the gyre is difficult\nto estimate, but an upper bound is attainable. Given that the fractional areas impacted\nby submesoscale structures are ~5.2% according to Liu et al.42, the upper bound of the\nPOC flux that was increased by front intensification is 0.14±0.03 mmolC m-2 d-1, which\ncorresponds to ~9±1.9% of the POC flux at the base of the euphotic zone in the NPSG.’\nIn the Methods section, the following paragraph has been removed (Lines 561-568):\n‘Contribution of eddy intensification to the POC flux\nThe contribution of eddy intensification to the POC flux of the entire NPSG was\nestimated using the mesoscale eddy trajectory product from the Archiving, Validation\nand Interpretation of Satellite Oceanographic (AVISO) data. During 1993-2019, there\nwere a total of 14539 cyclonic eddies, which, during the intensification stage, occupied\n~5.7% of the area of the NPSG (Fig. S7). The POC export fluxes induced by eddy\nintensifications in the NPSG were calculated as F (Z )×A, where A is the fractional\nEI Eu\narea occupied by cyclonic eddies during the intensification stages.’\nFor figures, the original Figure 5 has been moved to the supplementary information,\nand the original Figure S7 has been removed.\nImprecisions on the approach that need clarification, issues with text and figures.\nSection 2.1\n11. Line 97 and onward. This paragraph about the position of the floats is a little tedious\nto read. Maybe the authors could either streamline or fold in some results in there as\nthey describe the trajectory.\nResponse: Following the reviewer’s suggestion, the descriptions of both the float\nposition and float trajectory have been combined. In the new text, the paragraph you\nmentioned has been removed.\n12. Line 107: “The euphotic depth (ZEu) was on average ~159 m within CE 1 and 161\nm in ACE” is this difference really significant?\nResponse: We conducted a two-sample t test and found that the averaged Z for CE 1\nEu\ndid not statistically differ from that for ACE 1. We have mentioned this in the revised\ntext (Lines 141-142):\n‘A two-sample t test suggests that the averaged Z for CE 1 was not statistically\nEu\ndifferent from that for ACE 1.’\n13. line 115: Correlations are reversed: change increasing to decreasing and vice versa.\nResponse: Done.\n14. Line 116: “This result suggested that nutrients in the euphotic zone were enhanced\nby the uplift of isotherms within this cyclonic eddy17,” Don’t you mean that uplift\noccurs at the edge of CE instead of “within”?\nResponse: We mean that uplift occurs within the CE because the radial distribution of\nnitrate concentration in CE 1 exhibited a higher level of nitrate in the CE 1 core than at\nits edge.\n15. line 123: Trends are reversed: change positive to negative and vice versa.\nResponse: Done.\n16. Text on the figure was blurry, small and hard to read in my version.\nResponse: We now use a larger font size for the text in Figure S1 and have updated all\nthe figures with a higher resolution.\n17. Zscm is used to discuss the changes in the different properties measured. Could you\nexplain why? How to separate the effect of the eddy dynamics and the change in\nsampling depth due to variations in Zscm? Is the assumption that Zscm follows a\ndensity layer? Maybe using density instead of depth would be more insightful?\nResponse: We used Z to discuss the biogeochemical effects of mesoscale eddies\nscm\nbecause mesoscale eddies have been demonstrated to significantly affect the subsurface\nchlorophyll maximum in the North Pacific subtropical gyre (Xiu & Chai, 2020). As\nshown in Fig. R3a and b, Z mainly follows the density layer σ =23.8 kg m-3 in CE 1\nscm θ\nand σ =23.3 kg m-3 in ACE 1. Due to the regulation of submesoscale frontal dynamics,\nθ\nthe Z at the CE 1 edge was shallower than the depth of σ =23.8 kg m-3 from 28 April\nscm θ\nto 3 May 2019. Linear regressions along the density layer present analogous results to\nthose along the Z for Chl and POC. There are no significant correlations between the\nscm\ntemperature and r/R because the along-isopycnal temperature was almost the same. The\nlinear regression result for NO along σ =23.8 kg m-3 is opposite to that along Z in\n3 θ scm\nCE 1 because the isopycnal reaches a deeper depth where the nitrate level is higher\nfrom 28 April to 3 May 2019. During this period, the isoline σ =23.8 kg m-3 was below\nθ\nthe euphoticzone depth where there is limited phytoplankton photosynthetic activity.\nIn contrast, the Z was within the euphotic zone so that the impacts of the eddy\nSCM\ndynamics on the biological processes can be well reflected. As such, we discussed the\nchanges of different biogeochemical tracers using Z .\nscm\nReference:\nXiu, P. & Chai, F. (2020). Eddies Affect Subsurface Phytoplankton and Oxygen\nDistributions in the North Pacific Subtropical Gyre. Geophys. Res. Lett. 47,\ne2020GL087037\nFigure R3. a-b Vertical distribution of (a) Chl and (b) NO in CE 1. c-d Vertical\n3\ndistribution of (c) Chl and (d) NO in ACE 1. Black, red and white lines in a-d represent\n3\nthe mixed layer depth, the depth of the subsurface chlorophyll maximum and the\nisopycnals, respectively. e-h Radial distributions of c temperature, d NO , e Chl and f\nθ θ\n(blue) ACE 1. The solid lines indicate the linear regression lines.\nSection 2.2\n18. Please state clearly that you attribute change in integrated content over time to\nchange in flux from the top, and detail and justify your assumptions.\nResponse: Thank you for the suggestion. In this study, the rate of change of the\nintegrated POC from depth z to the mesopelagic layer is attributed to the net change\nbetween the POC flux supply from depth z and POC consumption between depth z and\nthe base of the mesopelagic layer. Either changes in POC export or in POC consumption\nin the water column can affect this rate. The underlying assumption is that while the\nfloat drifted along the front, it sampled homogeneous water masses over time. We have\nclarified this point in the Methods section (Lines 495-507). Additionally, the\nassumption that the float sampled data as the time evolution of the front has been\njustified, as we replied to your comment #4.\n19. More arguments could be provided to justify the reason for comparing the\nattenuation of a flux anomaly (FEI(z)) calculated with the float with the attenuation of\nthe total POC flux from the literature.\nResponse: Thank you for the suggestion. For eddies, significant POC export is not\nsustained over their whole lifespan and is often associated with the physical dynamics\nof eddies (Zhou et al., 2020). The temporal evolution of biogeochemical processes in\nthe eddy has been suggested to progress from nutrient injection, biomass buildup, and\nexport enhancement during the eddy intensifying stage to biomass and export decline\nduring the eddy decay stage (Sweeney et al., 2003; Zhou et al., 2020; Zhou et al., 2021).\nObservations have shown that intensifying eddies exhibit a large biological response,\nwhile eddies in the inactive stage do not show a significant biological response or high\nexport flux (Sweeney et al., 2003; Buesseler et al., 2008). We assume that the\nmagnitude of the export flux during the eddy decay stage is negligible, so that the flux\nanomaly approaches the total POC flux, and can be compared with those directly\nestimated from sediment traps or radioactive techniques recorded in the literature.\nNevertheless, our estimated F (z) is a flux anomaly relative to the eddy decay stage,\nEI\nand it could underestimate the real POC export flux during the eddy intensifying stage.\nWe have added this discussion to the text (Lines 227-235).\n‘For eddies, significant POC export is not sustained over their whole lifespan and is\noften associated with the physical dynamics of eddies42,52. Observations have shown\nthat intensifying eddies exhibit a large biological response, while eddies in the inactive\nstage do not show a significant biological response or high export flux 29,31,42,52. We\nassume that the magnitude of the export flux during the eddy decay stage is small, so\nthat the enhanced net POC flux is considered as the approximation of the actual POC\nflux. The enhanced POC flux may underestimate the actual POC flux during the eddy\nintensifying stage as F (z) is a flux anomaly relative to the eddy decay stage.’\nEI\nReferences:\nBuesseler, K. O., Lamborg, C., Cai, P., Escoube, R., Johnson, R., Pike, S., Masque, P.,\nMcGillicuddy, D. & Verdeny, E. Particle fluxes associated with mesoscale eddies in the\nSargasso Sea. Deep-Sea Res. II 55(10–13), 1426–1444 (2008).\nSweeney, E. N., McGillicuddy, D. J. & Buesseler, K. O. Biogeochemical impacts due\nto mesoscale eddy activity in the Sargasso Sea as measured at the Bermuda Time-Series\nStudy (BATS). Deep-Sea Res. II50, 3017–3039 (2003).\nZhou, K., Dai, M. Xiu, P., Wang, L., Hu, J. & Benitez-Nelson, C. R. Transient\nenhancement and decoupling of carbon and opal export in cyclonic eddies. J.\nGeophys. Res. Oceans125, e2020JC016372 (2020).\nZhou, K., Benitez-Nelson, C. R., Huang, J., Xiu, P., Sun, Z. & Dai, M. Cyclonic eddies\nmodulate temporal and spatial decoupling of particulate carbon, nitrogen, and biogenic\nsilica export in the North Pacific Subtropical Gyre. Limnol. Oceanogr. 66, 3508–3522\n(2021).\n20. Write P(z), E(z) on figure 3 to make it easier to understand.\nResponse: The symbols ‘P(z)’ and ‘E(z)=∂P(z)/∂t’ have been added to the new Fig. 4a.\n21. line 153: Is «exponentially» appropriate? It seems linear.\nResponse: We agree. It is not appropriate here. The word ‘exponentially’ has been\nreplaced with ‘gradually’.\n22. line 162: The total increase in POC flux could be calculated by reconstructing the\namount of remineralized POC from AOU and Redfield ratios.\nResponse: Thank you for the suggestion. We tried to quantify remineralized POC from\nAOU as suggested, but it may introduce more uncertainties to our results. The AOU\nmultiplied by the Redfield ratios represents the heterotrophic respiration of the total\norganic carbon (TOC), 50-90% of which is dissolved organic carbon. Because the ratio\nof the POC to TOC and the Redfield ratios in the study region were not measured, we\ndid not use the AOU to reconstruct the remineralized POC and only used AOU change\nto demonstrate possible changes in remineralization between different stages. We have\nadded this discussion to the text (Lines 512-517):\n‘The AOU multiplied by the Redfield ratios represents the heterotrophic respiration of\nthe total organic carbon (TOC), 50-90% of which is dissolved organic carbon48,58,59.\nBecause the ratio of the POC to TOC and the Redfield ratios in the study region were\nnot measured, we did not use the AOU to reconstruct the remineralized POC and only\nused AOU concentration change over time to demonstrate possible changes in\nremineralization between different stages.’\nReferences:\nAbell, J., Emerson, S., & Renaud, P. Distributions of TOP, TON and TOC in the North\nPacific subtropical gyre: Implications for nutrient supply in the surface ocean and\nremineralization in the upper thermocline. J. Mar. Res. 58(2), 203–222 (2000).\nHansell, D. A., & Carlson, C. A. Biogeochemistry of total organic carbon and nitrogen\nin the Sargasso Sea: Control by convective overturn. Deep‐Sea Res. Part II 48(8–9),\n1649–1667 (2001).\nKheireddine, M. et al. Organic carbon export and loss rates in the Red Sea. Global\nBiogeochem. Cycles 34, e2020GB006650 (2020).\n23. Y-scales of 3g and 3h are making it confusing, maybe 0-700 m could be used.\nResponse: The Y-scales of 3g and h have been limited to the range 0-700 m.\nSection 2.3\n24. L 183: Here, the front is defined by the temperature gradient. Would it be possible\nto find out whether the front is dynamically active and carrying POC at depth or not?\nResponse: We diagnosed the frontal dynamics using more physical parameters, such\nas the finite-size Lyapunov exponent (FSLE), lateral buoyancy frequency (M2) and\nRichardson number (R). The concurrence of SST gradients, high FSLE, M2 and small\ni\nR suggests that the front was dynamically active (Fig. S5 and S7). Below the euphotic\ni\nzone depth, we found that the POC concentration was high, which indicated that the\nintense submesoscale vertical velocities subducted high POC downward (Fig. S9).\nThese results have been incorporated in the main text in Lines 256-264.\n25. L184/185: Can we really speak of degradation/intensification, since the float crosses\nthe front but doesn't stay there?\nResponse: According to the frontogenesis theory, when the front is enhanced, it will\ngenerate upwelling on the warm side of the front and downwelling on the cold side of\nthe front. During the sampling period, the front experienced intensifying and decaying\nstages, while the float was continuously sampled along its warm side (not across the\nfront). We conducted an experiment of particle tracking and a T-S characteristic analysis\nof the water mass to justify that the float did drift along one side of the front, on which\nrelatively homogeneous water masses were sampled. As such, the float observations\ncan be interpreted as a temporal signal due to the stage change of the front. Our\nhypothesis is that when the front intensifies, the dynamic and biogeochemical changes\non each side are generally coherent. Please see the details in our reply to comment #4.\n26. L 186 / Fig. S4e: Why is the gradient lower than the background during the decaying\nstage? Why not equal since the front goes back to background?\nResponse: Thank you for the insightful question. Fig. S4e has been updated to exclude\nextremely high GM values when calculating the background GM. It appears reasonable\nnow.\n27. L 188: Fig. S4g: How is the strain rate calculated and from which data product? You\ncould physically define the front and add its position to your figures to make\ninterpretation easier.\nResponse: The strain rate was calculated using satellite-derived altimetry data (sea\nsurface height data) at a resolution of 0.25°∙0.25°. We realized that the spatial resolution\nof the strain rate is inadequate to identify the frontal structure and have removed it in\nthis revision. We have instead used the finite-size Lyapunov exponent (FSLE) to\nidentify the dynamic active regimes of the front calculated from the sea surface height\ndata. The along-track time series of FSLE and lateral buoyancy frequency (M2)\npresented the co-located pattern of high FSLE and M2, suggesting that the frontal region\nwas in active submesoscale motion. Please see Fig. S7.\nMethods\n28. L 313: You could spell out bbp(700) and PAR again.\nResponse: Following the suggestion, the words ‘bbp(700) and PAR’ have been\nreplaced with ‘particulate backscattering coefficients at 700 nm (b (700)) and\nbp\nphotosynthetically available radiation (PAR)’ .\nReviewer #2 (Remarks to the Author):\nThis study presents an observation-based analysis of the relationship between\nparticulate organic carbon (POC) and eddy and frontal dynamics. The authors have\nleveraged observations from floats with the objective to bring new insights into carbon\nexport dynamics at fine scale. This is a valuable effort; yet there are major issues that\nneed to be addressed before it can be published. The main concerns fall in 4 categories:\nI. Gaps in context and references to prior work in introduction and discussion of the\nresults, specifically the potential impact of frontal subduction (comment #1)\nII. Missing or weak justification of the hypotheses used to interpret the data that account\nfor the compounding effects of spatial and temporal variability, specifically the\njustification to use a “mostly spatial” or a “mostly temporal” framework depending on\nthe eddy/front considered (comments #2-5)\nIII. Shortcomings with the conclusions and generalizations of the results that link fronts\nto POC export and attenuation coefficient b, which is the main point of the paper\n(comments # 6-10).\nIV. Imprecisions on the approach that need clarification, issues with text and figures.\n(comments #11-28).\nDetailed comments and suggestions on how to address them are provided below. The\ntwo reviewers that contributed to this review believe the authors can improve the\njustification of their approach, as well as the interpretation and generalization so the\nmanuscript can be acceptable for publication.\nResponse: We thank the reviewer for the thoughtful and constructive suggestions. We\nfind that the paper is significantly strengthened by addressing the four issues you are\nconcerned with. We have responded to these questions and comments point-by-point\nbelow.\n1. Gaps in context and references. The sentence of L71 is not true: “In this study, for\nthe first time, we show the capability of using BGC-Argo floats equipped with optical\nsensors to estimate the carbon export flux and associated vertical attenuation in\nresponse to submesoscale fronts”\nThe paper is lacking key references, in particular prior studies identifying and\nquantifying the role of subduction by fronts, including with BGC-Argo floats. The\nmanuscript leads us to believe that there were no attempts to quantify this subduction\npump before. Yet observation based (using float AOU, spiciness) and high resolution\nmodeling papers have been published on this topic (see list of reference below). They\nneed to be included to provide the adequate context in the introduction but also in the\ndiscussion. Note that the process of export by subduction along fronts explained in this\nstudy can be called differently in the literature: eddy pump, eddy subduction pump etc.\nAlthough the term “eddy pump” was often used, it does not usually refer to “Ekman\npumping” in eddies but the subduction by fast velocities associated with meso and\nsubmesoscale fronts, similarly to what is considered in this manuscript.\nSentences that critically need these references include L56-67 (almost all sentences in\nthis paragraph are missing critical references), L71 which needs to integrate these prior\nwork. In discussion, please consider how the impact of subduction would influence\nyour results and discuss considering these prior works.\nReview about export pumps including the physical injection pump or eddy pump:\nBoyd, P.W., Claustre, H., Levy, M., Siegel, D.A., Weber, T., 2019. Multi-faceted particle\npumps drive carbon sequestration in the ocean. Nature 568, 327.\nhttps://doi.org/10.1038/s41586-019-1098-2\nPapers estimating the role the “eddy subduction pump” using BGC-Argo, cruises and\nmodels:\nErickson, Z.K., Thompson, A.F., 2018. The Seasonality of Physically Driven Export at\nSubmesoscales in the Northeast Atlantic Ocean. Global Biogeochemical Cycles 32.\nhttps://doi.org/10.1029/2018GB005927\nLacour, L., Llort, J., Briggs, N., Strutton, P.G., Boyd, P.W., 2023. Seasonality of\ndownward carbon export in the Pacific Southern Ocean revealed by multi-year robotic\nobservations. Nat Commun 14, 1278. https://doi.org/10.1038/s41467-023-36954-7\nLlort, J., Langlais C., Matear R., Moreau S., Lenton A., Strutton Peter G., 2018.\nEvaluating Southern Ocean Carbon Eddy‐Pump From Biogeochemical‐Argo Floats.\nJournal of Geophysical Research: Oceans 123, 971–984.\nhttps://doi.org/10.1002/2017JC012861\nMcGillicuddy, D.J., Resplandy, L., Lévy, M., 2019. Estimating particle export flux from\nsatellite observations: Challenges associated with spatial and temporal decoupling of\nproduction and export. Journal of Marine Research 77, 247–258.\nhttps://doi.org/10.1357/002224019828474331\nOmand, M.M., D’Asaro, E.A., Lee, C.M., Perry, M.J., Briggs, N., Cetinić, I.,\nMahadevan, A., 2015. Eddy-driven subduction exports particulate organic carbon from\nthe spring bloom. Science 348, 222–225. https://doi.org/10.1126/science.1260062\nResplandy, L., Lévy, M., McGillicuddy Jr., D.J., 2019. Effects of Eddy-Driven\nSubduction on Ocean Biological Carbon Pump. Global Biogeochemical Cycles 33,\n1071–1084. https://doi.org/10.1029/2018GB006125\nStukel, M.R., Song, H., Goericke, R., Miller, A.J., 2017. The role of subduction and\ngravitational sinking in particle export, carbon sequestration, and the remineralization\nlength scale in the California Current Ecosystem: Subduction and sinking particle\nexport in the CCE. Limnology and Oceanography 63, 363–383.\nhttps://doi.org/10.1002/lno.10636\nResponse: Thank you for pointing this out. We agree that prior works on subduction\nby fronts should be included in the introduction, and its impacts on our results should\nbe discussed, as subduction by fronts is one of the most important dynamics by which\nsubmesoscale processes affect local POC distributions. We deleted that inaccurate\nstatement in this revision. The changes in the introduction and discussion sections are\nsummarized below:\n1. Changes in the introduction section\nTo provide a more adequate context in the introduction that the submesoscale process\naffects local POC export, we first added one sentence in Lines 57-60 to mention the\neddy-subduction pump:\n‘The vertical motions can inject high POC produced in the euphotic zone into the\nmesopelagic layer (referred to as eddy subduction pumps)17,19,22,24, resulting in long-\nterm carbon sequestration17,19,20,23.’\nSecond, prior works that attempted to identify and quantify eddy subduction pumps\nhave been acknowledged in Lines 68-71:\n‘Prior studies have captured anomalous features of elevated POC at depth, which are\ninterpreted as evidence of eddy subduction pump19,22,23. Despite their potential\nimportance in shaping POC export, direct observations of the downward POC flux and\nits attenuation in response to submesoscale fronts are scarce17,19-21,23,41.’\nand Lines 76-81 :\n‘Observational and high-resolution modeling studies have suggested that the eddy\nsubduction pump contributes ~19% to 50% to the total export of POC. In contrast,\nResplandy et al. (2019) explored the integrated effects of eddy subduction hot spots on\nthe biological carbon pump and found that they contribute less than 5% to carbon\nexport due to the strong compensation between upward and downward fluxes.’\nAdditionally, key references have been added in Lines 71 (Omand et al., 2015; Llort et\nal., 2018; Erickson et al., 2018; Lacour et al., 2023; Boyd et al., 2019) and Line 86\n(Llort et al., 2018; Lacour et al., 2023).\nFinally, we acknowledge that Llort et al. (2018) was the first to quantify the carbon\nexport flux associated with submesoscale fronts by using BGC-Argo. Previous studies\nthat quantified the carbon export flux at submesoscale using BGC-Argo have also been\ncited in this revision. In comparison, however, these previous studies didn’t consider\nthe vertical attenuation of the carbon flux at submesoscale fronts, which is the main\ncontribution of our study. To integrate the previous efforts and clarify the novelty of\nour results, we have rephrased the sentence as shown below (Lines 91-96):\n‘The BGC-Argo has been used to identify elevated POC in the mesopelagic layer and\nestimate the carbon flux associated with submesoscale features20,23. In this study, we\nfurther show the capability of using BGC-Argo floats to estimate the transfer efficiency\nof carbon export in response to submesoscale fronts.’\n2. Discussion on the impacts of subduction on POC export\nWe agree with comments #8 and #9 that the impacts of subduction by front should be\ntaken into account to interpret our results. More discussion has been added in this\nrevision.\nAs you mentioned in comment #9, the high POC at a depth of 200 m at the edge of CE\n1 could be due to subduction of POC from the productive layer by the front. After a\ndetailed examination, we agree with this comment and have added additional text\n(Lines 376-382) to discuss this point. Please see our response to this comment #9.\nOn the other hand, we found that the influence depth of eddy subduction may not be\ndeep enough to affect the lower mesopelagic layer. The elevated POC concentration\nand flux were only present at depths between Z and ~250 m. We tested different ways\nEu\nto fit the POC flux attenuation coefficient (b) with and without considering the POC\nflux in the subduction layer (Z ~250 m). The b value was about 0.65 excluding the\nEu\nPOC flux in the eddy subduction layer, which was higher than that considering the\nsubduction layer (b=0.56), but was still lower than those estimated in eddies and normal\nconditions. This suggests that submesoscale dynamics affect POC export flux not only\nthrough physical subduction but also through modulating particle properties (e.g., size,\nsinking speed and composition). We have added a paragraph (Lines 373-393) to fully\ndiscuss the impact of eddy subduction on our results. Please find our detailed response\nto comment #8.\nReferences:\nBoyd, P.W., Claustre, H., Levy, M. et al. Multi-faceted particle pumps drive carbon\nsequestration in the ocean. Nature568, 327–335 (2019).\nResplandy, L., Lévy, M. & Mcgillicuddy, D. J. Effects of eddy-driven subduction on\nocean biological carbon pump. Glob. Biogeochem. Cycles 33, 1071–1084 (2019).\nOmand, M. M. et al. Eddy-driven subduction exports particulate organic carbon from\nthe spring bloom. Science348, 222–225 (2015).\nLacour, L., Llort, J., Briggs, N. et al. Seasonality of downward carbon export in the\nPacific Southern Ocean revealed by multi-year robotic observations. Nat. Commun. 14,\n1278 (2023).\nErickson, Z. K. & Thompson, A. F. The seasonality of physically driven export at\nsubmesoscales in the Northeast Atlantic Ocean. Global Biogeochem. Cycles 32, 1144–\n1162 (2018).\nStukel, M. R., Song, H., Goericke, R. & Miller, A. J. The role of subduction and\ngravitational sinking in particle export, carbon sequestration, and the remineralization\nlength scale in the California Current Ecosystem. Limnol. Oceanogr. 63, 363–383\n(2018).\nLlort, J. et al. Evaluating Southern Ocean carbon eddy-pump from biogeochemical-\nargo floats. J. Geophys. Res. Ocean. 123, 971–984 (2018).\nMcGillicuddy, D. J. et al. Estimating particle export flux from satellite observations:\nChallenges associated with spatial and temporal decoupling of production and export.\nJ. Mar. Res. 77, 247–258 (2019).\nLévy, M. et al. The Impact of Fine-Scale Currents on Biogeochemical Cycles in a\nChanging Ocean. Annu. Rev. Mar. Sci. 16,1 (2024).\n2. Missing justification of the hypotheses, specifically the justification to use a “mostly\nspatial” or a “mostly temporal” framework to interpret the float data.\nThe authors alternatively interpret the observed changes along the float trajectories as\n“mostly spatial changes” (CE1 and ACE1, Figure 2), or “mostly temporal changes” i.e.\npseudo lagrangian (CE2 and front, Figure 3). The hypothesis of “mostly temporal” is\njustified in the text for CE2 (L128 and 141). However, the justification to interpret as\n“mostly spatial” the changes along CE1 and ACE1 is missing, and the hypothesis to\ninterpret as “mostly temporal” the changes attributed to frontal dynamics seems\ninadequate (see details in comments 3 and 4 below). We encourage the authors to\nexplain clearly and early these different strategies to orient and prepare the reader.\nResponse: Thank you for pointing this out. In this study, we performed different\nanalyses based on different sampling scenarios of the floats to delineate temporal and\nspatial variabilities of the measured variable. For the hypothesis of ‘most spatial\nchanges’ in eddies (CE1 and ACE1), we first showed a radial increase of the relative\ndistance between the float and the eddy center with time. Then, we demonstrated that\nthe change of surface Chl measured by the floats was consistent with the radial variation\nof remote-sensed surface Chl from the eddy core to the eddy edge. In addition, with\nremote sensing data, we can track the temporal evolution of Chl in eddies, and this\ntemporal pattern was completely different from the change of float-measured surface\nChl. Therefore, for this sampling period, we think the float-measured variability of POC\ncan be used to represent the spatial variability of POC from the eddy core to the eddy\nedge.\nFor the hypothesis of ‘most temporal changes’ along a submesoscale front, we added\nmore analysis about the float-measured characteristics of the water masses. We also\nconducted a numerical particle tracking experiment. These new results all suggest that\nthe float continuously drifted along the warm side of the front on which homogeneous\nwater masses were sampled. During this period, the front experienced intensifying and\ndecaying stages, while the float was still sampling along its warm side. As such, the\nfloat observations at the front can be interpreted as a temporal signal due to the stage\nchange of the front.\nFollowing the suggestions, we now justify these two hypotheses early in Sections 2.1\nand 2.3, respectively. Please see more details in our following responses to comments\n#3 and #4.\n3. The authors need to demonstrate why it is justified to ignore temporal variations\nwhen analyzing CE1 and ACE1. Figure 2 interprets all POC data as spatial changes\n(using radial structure of the eddies CE1 and ACE1). The approach is attractive, but the\ntext and figures should clearly show that this is a valid hypothesis. Specifically, how\nmuch of the signal that is interpreted as spatial variability across the eddy is in fact\nintroduced by the temporal evolution along the trajectory of the float? At least, the\nauthors could indicate the day of sampling for each data point on Figure 2? [Colors\ncould indicate the day of sampling while symbols could indicate the depth]. This would\nallow the reader to see how much of the variations attributed to the spatial structure of\nthe eddy could be introduced by temporal changes.\nResponse: Thank you for the constructive comment. For CE 1 and ACE 1, we\ninterpreted the measured variability of POC as the radial structures of eddies based on\nthe following considerations:\nFirstly, there was an increasing relative distance between the float and the eddy center\nwith time. The location of the float changed from inside the eddy to outside the eddy,\nwith a relative distance of r/R between 0.4~2.0 for CE 1 and 0.23~1.2 for ACE 1.\nSecondly, the spatial distribution of Chl in eddies was derived by compositing the\nremote-sensed sea surface Chl over the float sampling period. This satellite-derived Chl\nwas then interpolated onto the relative locations of the float in eddies to compare with\nthat measured by the float. In CE 1, both the satellite- and float-derived Chl decreased\nand then increased in the radial direction, reaching a peak at r/R=1~1.5 (Fig. S2). In\nACE 1, both the satellite- and float-derived Chl showed a double peak pattern along the\nradial direction (Fig. S2a). The correlations between the satellite- and float-derived Chl\nwere 0.39 (p=0.01) and 0.43 (p=0.09) for CE1 and ACE 1, respectively. The relatively\nconsistent changing patterns of Chl between the float and remote sensing data suggest\nthat the float captured the spatial variability of the eddies in the radial direction.\nLastly, it is likely that the temporal signal was also included in the float data as it\nexhibited larger 95% confidence intervals than those derived from satellite observations\n(Fig. S2a). With remote sensing data, we can track the temporal evolution of the Chl in\neddies, and this temporal pattern was completely different from the change of float-\nmeasured surface Chl (Fig. S2b). The correlations between the satellite- and float-\nderived Chl over time were -0.18 (p=0.24) and -0.05 (p=0.82) for CE1 and ACE 1,\nrespectively, suggesting that the variability explained by the temporal evolution of Chl\nof eddies was much small. Therefore, for this sampling period, we think the float-\nmeasured variability of variables can be used to represent the spatial variability of\neddies.\nTo clarify this point, we added the following sentences in Lines 143-154 and Fig. S2\nbefore we presented the radial POC distributions in the text:\n‘The floats may capture the spatial variability of tracers for CE 1 and ACE 1 as the\nlocation of the floats changed from inside the eddies to outside the eddies. The satellite-\nderived sea surface Chl was averaged over the float sampling period and then\ninterpolated onto the relative locations of the float in eddies to compare with that\nmeasured by the float. The float-measured Chl was in good agreement with that derived\nfrom satellites in the radial direction (Fig. S2a), with correlations of 0.39 (p=0.01) for\nCE1 and 0.43 (p=0.09) for ACE 1. In contrast, the temporal evolution of satellite-\nderived Chl averaged inside eddies was completely different from that of float-\nmeasured Chl (Fig. S2b), indicated by low correlations (R= -0.18 (p=0.24) for CE 1\nand R=-0.05 (p=0.82) for ACE 1). Therefore, the float-measured tracers during this\nperiod can be used to represent the spatial variability of the eddies along the radial\ndirection.’\nAnother thing worth mentioning is that the high POC distribution at the edge of CE 1\nwas due to subduction by the front (please see our reply to comment #9). This further\nstrengthens the point that the distributions of POC captured by the float reflect the\nspatial variability of the eddy. We have added the following sentence in Lines 169-170\nto emphasize this point:\n‘This further supports that the radial distributions of POC measured by the float reflect\nthe spatial variability of the eddy.’\nFollowing the reviewer’s suggestion, colors have been indicated in Fig. 2. For CE 1, as\nthe float moved almost monotonically from the eddy core to the edge with time, it is\nstill not easy to tell the influence of the temporal signal from this figure. Figure R1\nshows the variations of the strength of the eddies. It is clear that although CE 1 was\nstrengthened in early May while the float was at r/R=~1.3, the float-measured POC at\nSCM layer was still lower than that measured at the eddy core (Fig. 3), implying\ndominant variability caused by space instead of time.\nFigure S2. Comparison of sea surface Chl between satellite and BGC-Argo\nobservations in both spatial and temporal variability. a Radial distribution of sea surface\nChl at the float locations derived from both the BGC-Argo and satellite observations.\nThe BGC-Argo results are directly obtained from the surface Chl measured by the float.\nThe satellite-derived Chl values are calculated by averaging the Chl from OC-CCI over\nthe float sampling period and then interpolating to the relative locations of the float in\neddies. Because the eddies propagated over time, the location of the float in the eddies\nwas constructed by calculating the azimuthal and radial positions of the float relative to\nthe eddy center. b Satellite-derived Chl averaged inside eddies and sea surface Chl\nderived from BGC-Argo observations. The BGC-Argo results are directly obtained\nfrom the surface Chl measured by the float. The satellite-derived Chl values are\ncalculated by averaging the satellite-derived Chl values inside the eddies at the time\nwhen the float was at the position of r/R.\nFigure 3. POC distributions at different depths within a CE 1 and b ACE 1.\nFigure R1. Evolution of SLA averaged inside eddies.The SLA values are calculated by\naveraging the SLA inside the eddies at the time when the float was at the position of\nr/R.\n4. The hypothesis of “mostly temporal” is highly disputable for the front. It is ok for\neddy CE2 because the float seems to stay stuck close to the center of the eddy, and most\nchanges can be interpreted as temporal changes. In the case of the front, however, the\nfloat seems to be sampling different parts of the front. The associated changes in SLA,\nPOC, AOU etc. are therefore likely to come from spatial variations across the front and\nnot temporal variations. The authors could demonstrate that it is indeed temporal,\nhowever it is unlikely to be successful and convincing given the complexity of the\ndynamics in the frontal structure. This shortcoming has major implications for the result\ninterpretation and the conclusions of the paper as the authors interpret these changes as\ntemporal changes while they are likely spatial changes. This section of the results and\nassociated conclusions needs to be revised.\nResponse: Thank you for the insightful comment. According to the frontogenesis\ntheory, when the front is enhanced, it will generate downwelling on the cold side of the\nfront and upwelling on the warm side of the front. The hypothesis of ‘mostly temporal’\nis that the float drifted along one side of the front so that relatively homogeneous water\nmasses over time were sampled. During this period, the front experienced intensifying and\ndecaying stages, while the float was still sampling along its one side. As such, the\nfloat observations at the front can be interpreted as a temporal signal due to the stage\nchange of the front. We have provided more justifications in the revised text to interpret\nthis hypothesis.\nBy investigating the time series of FSLE along the float trajectory, we found that the\nfloat traveled along the same filament with high FSLEs. This result, in combination\nwith the Chl, SST and SST gradient distributions (already shown), demonstrated that\nthe float continuously traveled along the warm side of a front during that period.\nTo further support that the float drifted along one front, a numerical particle tracking\nexperiment was conducted at the frontal region using the TRACMASS code. The\nparticle was released at the same location as the float on 21 April 2019 and it was moved\npurely by advection using the surface geostrophic current derived from AVISO data.\nThe numerical tracking results showed that the float mainly followed the path of the\nparticle (Fig. S14), suggesting that the float moved in a quasi-Lagrangian manner and\nsampled a similar water mass during the analysis period (supplementary information\nText S3).\nThe homogeneous water masses sampled on one side of the front can be supported by\nthe transect of temperature and salinity anomalies (Fig. S6). The temperature was\nhigher in the upper 300 m and the salinity was lower in the upper 150 m depth compared\nto the CE 1 core. In addition, the T-S diagram presents a coherent physical characteristic\nfrom 21 April to 3 May 2019, suggesting that the float was moving along the front but\nnot across the front.\nOverall, these results support the use of the float data as a time series on the warm side\nof the front during the analysis period.\nWe have clarified this point in the text in Lines 247-250:\n‘This is further supported by a Lagrangian particle tracking experiment, which\nsuggests that the float drifted in a quasi-Lagrangian manner and sampled a similar\nwater mass along one side of the front (Text S3).’\n, and Lines 250-255:\n‘The front exhibited a higher temperature in the upper 300 m and in lower salinity in the\nupper 150 m depth compared to the CE 1 core (Fig. S6), suggesting homogeneous water\nmasses sampled at the frontal region. The T-S diagram demonstrates a coherent\nphysical characteristic from 21 April to 3 May 2019 (Fig. S6). All these results suggest\nthat the float sampled homogeneous water masses along the warm side of the front.’\nText S3. Lagrangian particle tracking experiment on the front\nTo investigate whether the float drifted along the front, a numerical particle tracking\nexperiment was conducted using the TRACMASS Lagrangian trajectory code (Döös,\n1995; Blanke & Raynaud, 1997). The particle was released at the same location as the\nfloat on 21 April 2019 and transported purely by surface current. Here, we run the code\nwith the current velocity derived from AVISO. The Lagrangian particle trajectory\nderived from the particle tracking model demonstrated that the virtual particle starting\nat the location of the float moved along the front (Fig S14). The float moved slower\nthan the particle but mainly followed its path, suggesting that the float drifted in a\nquasi-Lagrangian manner during the analysis period. The difference in moving velocity\nis that the particle was only transported by surface current, whereas the motion of the\nfloat was driven by both the surface and deep currents.\nFigure S14. Trajectories of the BGC-Argo and the virtual particle over the period when\nthe float was on the front (21 April - 3 May 2019). The particle was released at the same\nposition as the float on 21 April 2019 and transported by the surface current velocity\nderived from AVISO. The particle trajectory was tracked using the TRACMASS code.\nColor indicates the dates. Blue and red lines are the contour lines of the sea level\nanomaly (SLA). Arrows represent the sea surface current velocity anomaly.\nFigure S6. Physical characteristics of the float measurements. During 21 April - 3 May\n2019, the float was on one side of the front. Time series of a temperature, b salinity, c\ntemperature anomaly and d salinity anomaly measured by float 2902753 from 1 April\nto 3 May 2019. The black, red and cyan lines indicate the mixed layer depth (MLD),\nthe depth of subsurface chlorophyll maximum (Z ) and the euphotic zone (Z ),\nSCM Eu\nrespectively. The white lines are the isopycnals of 23, 24 and 25 kg m-3. The temperature\nand salinity anomalies were defined as the instantaneous values after subtracting the\nfull time mean. e Temperature-salinity diagram with data points from float 2902753\nfrom 1 April to 3 May 2019. The color indicates the sampling date.\n5. The sampling context should be better presented. In Figure 1, eddies and float\ntrajectories appear completely disconnected. This is likely because the black lines show\nthe center of the eddy and not their span. Could you indicate the radius of the eddies\naround the trajectories so we can see that they were indeed in the eddies? Also we\nencourage the authors to include a figure similar to Figure S4a to show the float relative\nto the eddy/front. Maybe choose snapshots that show the overlap with the front as a\nfunction of time.\nResponse: Thank you for this suggestion. The gray lines indicating the eddy radius\nhave been overlapped in Fig. 1a to show the connection of the eddy centers and the\nfloats. Additionally, snapshots showing the locations of the floats relative to the eddies\nand the front have been included in the new Figure 2.\nFigure 2. The BGC-Argo and eddy trajectories. a The locations of (yellow dots) the\nBGC-Argo float (WMO number 2902753) and (orange pentagrams) the center of\ncyclonic eddy 1 (CE 1) during 1-20 April 2019. b The locations of (yellow dots) the\nBGC-Argo float (WMO number 2902753) and (orange pentagrams) the center of\nanticyclonic eddy 1 (ACE 1) during 12 July - 2 September 2019. c The locations of\n(yellow dots) the BGC-Argo float (WMO number 2902756) and (orange pentagrams)\nthe center of cyclonic eddy 2 (CE 2). d The locations of the BGC-Argo floats along the\nfront during 21-27 April 2019. The yellow line is the float trajectory from 21 April to 3\nMay 2019. e The same as d but during 28 April-3 May 2019. Background color and\nisolines represent sea surface chlorophyll and sea level anomalies, respectively. The\narrows are the geostrophic velocity anomaly.\n6. Generalization between front and carbon export. L214-222. “A strong correlation\nbetween the b value and GM was found …. This statistical relationship implies that a\nstrong front is linked with high POC transfer efficiency to the mesopelagic layer, which\ncould be used as a parameterization to account for the impact of fronts on carbon export\nin large-scale models, once the front intensity at the surface is known”. This conclusion\nseems not backed up by the results. More complete models seem to show that b can\nvary according to many other biophysical parameters, making this generalization highly\ndebatable (see for instance Ngyuen et al. 2022: Microbes contribute to setting the ocean\ncarbon flux by altering the fate of sinking particulates). This is one of the main points\nof the paper; the caveats need to be discussed properly.\nResponse: Thank you for pointing this out. We agree that a parametrization of the b\nvalue as a function of the front intensity is inadequate since the efficiency of POC\ntransfer is modulated by complicated physical and biogeochemical processes. We have\nrephrased the sentence as follows to be clearer:\n‘This statistical relationship implies that a strong front is linked with high POC transfer\nefficiency to the mesopelagic layer, which could be used to estimate the impact of fronts\non carbon export at the basin-scale oceans.’\nWe used this relationship to estimate the impacts of fronts on POC transfer efficiency.\nThe underlying mechanism is that submesoscale dynamics play a role through their\nimpact on the particle sinking velocity or particle lability. The following discussion has\nbeen added to the manuscript (Lines 405-413):\n‘The estimation suggests that submesoscale fronts are important in setting the spatial\nand temporal variations in POC transfer efficiency. Previous carbon cycle studies have\nsuggested that the attenuation of the POC flux is determined by the rate of POC\nproduction in the euphotic zone, the sinking velocity of particles, and the rate of POC\nconsumption in the mesopelagic layer5-10,38,39,49-54. Submesoscale dynamics may play a\nrole in POC flux transfer through eddy subduction that directly enhances the particle\nsinking velocity or through its impacts on the plankton community structure in the\neuphotic zone that generates particles with large sinking velocities and/or low\nremineralization rates9,14-23,32.’\nThe caveat of the estimation conducted in this study is that we did not explicitly include\nother physical and biogeochemical processes that affect POC flux attenuation. These\nprocesses include mixed layer pumping, bacterial colonization and consumption,\nzooplankton migration, consumption, and fragmentation. However, there are no clear\ndata or previous studies showing why these processes could be particularly enhanced\nor weakened at fronts. We provide some discussions here. We think inclusion of these\nprocesses may allow a better constraint in estimating POC transfer efficiency, but it\ndefinitely requires future work to examine how submesoscale dynamics affect these\nprocesses. To clarify this point, we have added the following sentences to the text (Lines\n413-425):\n‘Our estimation suggests that submesoscale fronts increase the POC transport\nefficiency in the NPSG. However, it should be kept in mind that other processes that\ncan potentially modulate the b value (e.g., microbial POC consumption49,54, POC\nfragmentation by zooplankton8) were not explicitly included in the estimation.\nQuantifying the mesopelagic fragmentation processes revealed that roughly half of the\nobserved flux attenuation was due to the fragmentation of large particles into small\nparticles8. Ngyuen et al. showed that microbial dynamics may play a significant role in\nshaping the POC flux profiles observed in global oceans54. How these dynamics\nrespond to submesoscale fronts, however, is still not clear. Future work including\ndynamics such as microbial consumption and zooplankton disaggregation of the\nparticles is needed, and may allow for better constraints on the relative contributions\nof submesoscale fronts to the basin-scale carbon transport efficiency.’\n7. Conclusion about seasonality and export. line 234: You did not take into account that\nthe seasonality of mesoscale and frontal dynamics is different from the seasonality of\nPOC content in the water column. Consequently, the amount of POC transported by the\nsame front strength varies depending on the season. This could completely reverse your\nconclusion about the seasonal evolution of the parameter b. Please revise or strengthen\nthese points.\nResponse: Thank you for pointing this out. The relationship between the b value and\nsubmesoscale dynamics was derived from multiple observations in subtropical gyres,\nwhich cover both winter and summer months. This suggests that submesoscale\ndynamics can significantly affect POC transport efficiency in different seasons. As the\nPOC transport efficiency is largely determined by the b value, POC concentration\nusually won’t affect the transport efficiency. Instead, the properties of the POC (e.g.,\nsize, lability) are important in changing the b value. Submesoscale dynamics have been\nsuggested to affect the POC transfer efficiency by stimulating the growth of large\nplankton, which in turn generate large and rapidly sinking particles at the front.\nRegarding the same POC concentration with slow sinking in the background and with\nfast sinking at the front, the POC transfer efficiency will be higher at the front than in\nthe background. Therefore, to derive a robust b value function, the properties of POC\nshould also be considered. However, there are few POC property data available for now.\nWe examined the dataset from Station ALOHA, and found that the relationship between\nthe b value and POC concentration was not clear at the seasonal timescale. At ALOHA,\nlong-term records of the POC flux profiles suggest that the POC transfer efficiency is\nhigher in winter than in summer (Fig. S16). On the other hand, the POC concentrations\nare generally higher in summer than in winter, which is indicated by the averaged\nprofiles of POC at ALOHA (Fig. R2).\nOverall, the result of a lower b value in winter than in summer derived from the\nrelationships of both b and b is in good agreement with the in situ result at ALOHA\nT GM\n(Fig. S16), suggesting that the conclusion is likely robust. To support our results, the\nobservational results of the seasonality of the b value (Fig. S16) have been included in\nthe text.\nFigure S16. The seasonal b value at the ALOHA station. a POC flux profiles and the\ncorresponding Martin curves in summer. Black dots are observational profiles from\nsediment traps. Gray lines are the fitted Martin curves. The blue line is the Martin curve\nderived from the averaged b value and averaged POC flux at 150 m. b is the same as a\nbut in winter. c The b value and R2 for each observational POC flux profile in both\nsummer and winter. We picked up all observational POC flux profiles with at least three\nvertical sampling points for Martin curve fitting. The b values in summer are\nsignificantly different from those in winter, as h=1 and p=0.036 in the two-sample t test\nresult.\nFigure R2. The seasonally averaged POC profiles at ALOHA. a The vertical\ndistributions of POC concentrations in summer averaged over 1998-2021. The bars\nshow the averaged POC at depths of 150 m, 200 m, 250 m, 350 m, 500 m and 750 m.\nThe orange line is the fitted attenuation curve of the averaged POC concentrations with\ndepth. Error bars show one standard deviation for the averaging. b The same as a but\nin winter.\n8. Missing consideration of subduction #1. The POC export depth by fronts also\ndepends on the penetration depth of the vertical velocities associated with the fronts\n(subduction, see comment #1 for a list of papers that describe this). Shallow fronts do\nnot allow POC to be exported below the pycnocline and would limit the frontal effect\non b, further weakening your conclusion and the link established between fronts and\nPOC export/attenuation coefficient. Please consider this effect of subduction in\nintroduction and importantly in your results and interpretation. This is one of the\nweakest point of the paper. See also comment 9 below.\nResponse: Thank you for the constructive suggestion. In this study, we consider two\nmechanisms affecting POC export at fronts, which have been shown to be important in\nother regions in previous studies. The first mechanism is through biological carbon\npump. Strong submesoscale flows can enhance the vertical nutrient supply, alter the\nphytoplankton community structure, and generate particles sinking to depth. Some of\nthe particles generated through this mechanism, if not remineralized quickly, have the\npotential to penetrate the pycnocline and reach the mesopelagic layer via gravitational\nsinking. The second mechanism is through subduction, by which particles are carried\ndownward with the water mass. For this mechanism, the vertical depth the particle can\nreach is largely determined by the subduction velocity and the ventilation depth. Of\ncourse, these two mechanisms could coexist in some cases. Following the reviewers’\ncomments, we added more discussion about the effect of subduction in this revised\nmanuscript.\nFrom our data, two lines of evidence revealed that eddy subduction contributes to POC\nexport at the front. First, a higher POC concentration between Z (bottom of the\nEu\neuphotic zone) and ~250 m depth at the front than that in CE 1 was captured by the\nfloat, which is likely due to subduction of POC from the productive layer by the front\n(see details in Reply #9). Second, the POC fluxes between Z and ~250 m depth were\nEu\nhighest in the vertical direction, which is different from the classical biological carbon\npump curve and implies POC supply from other mechanisms (Fig. S10). As the high\nPOC signal was associated with tilting isopycnals, it was very likely induced by\nsubduction at the front.\nHowever, subduction appeared limited to depths between Z and ~250 m (Figs. S9 and\nEu\nS10). We tested different ways to fit the POC flux attenuation coefficient (b) with and\nwithout considering the POC flux in the subduction layer (Z ~250 m). The b value was\nEu\napproximately 0.65 excluding the POC flux in the subduction layer, which was higher\nthan that considering the subduction layer (b=0.56) but was still lower than those\nestimated in eddies and normal conditions. This suggests that submesoscale dynamics\naffect POC export flux not only through physical subduction but also through\nmodulating particle properties (e.g., size, sinking speed, and composition). Our results\nemphasize the complexity of submesoscale dynamics at play in enhancing POC transfer\nefficiency.\nAs we mentioned in the response to comment #1, the introduction of the effect of the\neddy subduction pump has been included in the introduction section. Additionally, we\nadded one paragraph in the discussion section to interpret and fully discuss the impact\nof the eddy subduction pump on our results (Lines 373-393):\n‘The high transfer efficiency of POC at the front could also result from the physical\nsubduction of POC by the intense submesoscale vertical velocities. Two lines of\nevidence have revealed that the eddy subduction pump contributes to carbon exports at\nthe front. First, frontal dynamics are responsible for the elevated POC at 200 m depth\nat the CE 1 edge of r/R=1 and 1.3 (Fig. 2a). At the positions of r/R=1 and 1.3, the float\nwas right on the filaments of high FSLE accompanied by high M2 and small R in the\ni\nvertical direction, which is suggestive of ongoing intense submesoscale vertical motions\n(Fig S5). Concurrence with the physical dynamics was an elevated POC concentration\nbetween Z and ~250 m compared to those in CE 1 (Fig. S9), which is evidence of eddy\nEu\nsubduction pump suggested in previous studies17,19,20,23. Second, the POC fluxes\nbetween Z and ~250 m influenced by the eddy subduction pump were obviously higher\nEu\nthan those above Z and below 250 m (Fig. S10). We tested different ways to fit the\nEu\nPOC flux attenuation coefficient (b) with and without considering the POC flux in the\nsubduction layer (Z ~250 m). The b value was approximately 0.65 excluding the POC\nEu\nflux in the subduction layer, which was higher than that considering the subduction\nlayer (b=0.56) but was still lower than those estimated in eddies and normal conditions.\nThis suggests that submesoscale dynamics affect POC export flux not only through\nphysical subduction but also through modulating particle properties (e.g., size, sinking\nspeed, and composition). These results emphasize the complexity of submesoscale\ndynamics at play in enhancing POC transfer efficiency.’\nFigure S9. Vertical POC concentration distributions. a-b Time series of a POC\ndistribution and b POC anomaly measured by float 2902753 from 3 April to 3 May\n2019. The black, red and cyan lines indicate the mixed layer depth, depth of the\nsubsurface chlorophyll maximum and euphotic zone, respectively. The POC anomalies\nwere defined as the instantaneous values subtracting the full time mean. c Vertical\ndistributions of the POC anomaly in CE 1 and at the front.\nFigure S10. POC flux profiles. a The POC flux between Z and 250 m that is affected\nEu\nby eddy subduction pump (ESP) is accounted for when estimating the b value. b The\nESP effect is not accounted for when estimating the b value. The black dashed lines and\nerror bars correspond to the euphotic zone depth and one standard deviation,\nrespectively. The red areas represent the euphotic zone.\n9. Missing consideration of subduction #2. L118: “The POC distributions attenuated\nfaster in the CE 1 center than at its edge, which is likely due to the higher\nremineralization of the newly produced and easily degradable organic matter inside the\neddy core8,36,37.” Is this really what is happening here? Couldn’t it be that intense\nvertical velocities associated with the frontal dynamics at the boundary of the eddies\nare transporting/subducting material down?\nResponse: As the reviewer suspected, the POC attenuated more slowly at the CE 1 edge\nthan in its center because the subduction of POC by the front increased the subsurface\nPOC at the edge. Specifically, the POC at 200 m presented a high value at r/R=~1 and\n1.3, where the float was right on filaments undergoing intense submesoscale vertical\nmotions. The proof to support this conclusion comes from the concurrence of high\nFSLE at the surface, large along-track M2 and small R in the vertical direction (see Fig.\ni\nS7). Meanwhile, the POC was higher between Z and ~250 m at the front compared\nEu\nto the eddy edge of other positions, likely due to subduction of POC from the productive\nlayer by the front (Fig. S9). We have therefore rephrased this sentence as follows (Lines\n165-169):\n‘The POC at 200 m reached its peaks at the edge of r/R=~1 and 1.3, which is likely due\nto subduction of POC from the productive layer by the front17,19,20,23’\nMore interpretations of the results have been added in the discussion section,\nspecifically with the group of sentences shown below (Line 376-382):\n‘the frontal dynamics are responsible for the elevated POC at a depth of 200 m at the\nCE 1 edge of r/R=1 and 1.3 (Fig. 3a). At the positions of r/R=1 and 1.3, the float was\nright on the filaments of high FSLE accompanied by high M2 and small R in the vertical\ni\ndirection, which is suggestive of ongoing intense submesoscale vertical motions (Fig\nS5). Concurrence with the physical dynamics was an elevated POC concentration\nbetween Z and ~250 m compared to those in CE 1 (Fig. S9), which is evidence of eddy\nEu\nsubduction pump suggested in previous studies17,19,20,23.’\nFigure S7. The lateral buoyancy frequency ( ), Richardson number (R) and finite-\ni\nsize Lyapunov exponent (FSLE) at the front. a2 BGC-Argo-derived lateral buoyancy\n𝑀\nfrequency during 21 April-3 May 2019. , where s is the along-track\ndirection. The black line represents the m2ixed layer depth. b BGC-Argo-derived\n𝑀 = −𝜕𝑏⁄𝜕𝑠\nRichardson number during 21 April-3 May 2019. , where f and b are the\n2 2\nCoriolis parameter and buoyancy, respectively. T\n𝑅\nh𝑖e\n=\nbl\n𝑓\nack\n𝑏\n𝑧l\n⁄\nin\n𝑏\ne\n𝑠\nrepresents the mixed\nlayer depth. c Surface FSLE at the frontal region (red line) and the lateral buoyancy\nfrequency (blue dashed line) at 100 m during 21 April-3 May 2019. Blue solid lines are\nthe buoyancy frequency envelope.\n10. Generalization to the subtropical Pacific. The generalization to the basin is very\nhand wavy and unconvincing, and probably not needed here. The results can stand alone\nwithout this. The author could in fact point out that the impact at the basin scale and\nglobal scale is still an open question. The conclusion, abstract (and maybe title) should\nbe modified to reflect the changes in conclusions.\nResponse: Thank you for the helpful suggestion. We agree that the submesoscale\nimpact at the basin scale is still an open question and have removed section 2.4 from\nthe main text.\nThe generalization of our results to the Pacific gyre provides an applicable way to\nestimate the effect of fronts on POC transfer efficiency based on satellite data, which\ndefinitely needs further studies to constrain uncertainties but also has the potential for\nfuture studies to explain POC variability in the mesopelagic ocean. In particular, we\nfeel that the reviewers’ comments #6 and #7 have been very helpful in improving this\npart. Based on these considerations, we modified our previous presentations and put\nthis part as a discussion in the supplementary information. The title, abstract and\nconclusions have been modified accordingly. The details are listed below:\nThe title has been changed to ‘Efficient biological carbon export to the mesopelagic\nocean induced by submesoscale fronts’.\nIn the abstract, the following sentences relative to the extrapolation results have been\nremoved (Lines 27-31):\n‘Expanding the results to the subtropical gyre reveals a significant relationship between\nthe Martin curve exponent coefficient (b) and front intensity. The average POC export\nflux at 1000 m may be underestimated by ~20-58% in the NPSG if the contribution of\nsubmesoscale fronts is ignored.’\nFor the previous section 2.4, the presentations have been modified. The section now\nhas been moved to the supplementary information as Text S4.\nIn the discussion section, the following sentences have been added to link the\nobservational results and Text S4 (Lines 396-405):\n‘The impact of fronts on POC transfer efficiency at the basin scale and global scale is\nstill an open question. We combined previous studies that have estimated POC\nattenuation coefficients in the North Pacific and North Atlantic gyres (Table S4, Fig.\nS11). A strong correlation between the b value and GM was found (b =-\nGM\n3.78·GM+1.44; R2=0.52, p<0.01, Fig. 5). The derived relationship between the flux\nattenuation coefficient and the front intensity could be applied to large-scale\napplications. Estimations based on this relationship suggest that the average POC\nexport flux at 1000 m may be underestimated by ~20-58% in the NPSG if the\ncontribution of submesoscale fronts is ignored (Text S4).’\nThe following paragraph has been removed from the discussion section (Lines 330-\n341):\n‘The contribution of eddy intensification to the POC flux of the entire NPSG was\nestimated using eddy dataset. The intensifying cyclonic eddy occupied ~5.7% of the\narea of the NPSG (Fig. S7). This gives an additional POC flux of 0.12±0.03 mmolC m-\n2 d-1 by eddy intensifications in the NPSG in the euphotic zone. Considering the\nobserved mean POC flux of 1.63 mmolC m-2 d-1 from previous studies in this region\n(Table S4), the eddy intensifications can increase the POC flux by ~7.4±1.8% in the\nNPSG. The contribution of front intensifications to the POC flux in the gyre is difficult\nto estimate, but an upper bound is attainable. Given that the fractional areas impacted\nby submesoscale structures are ~5.2% according to Liu et al.42, the upper bound of the\nPOC flux that was increased by front intensification is 0.14±0.03 mmolC m-2 d-1, which\ncorresponds to ~9±1.9% of the POC flux at the base of the euphotic zone in the NPSG.’\nIn the Methods section, the following paragraph has been removed (Lines 561-568):\n‘Contribution of eddy intensification to the POC flux\nThe contribution of eddy intensification to the POC flux of the entire NPSG was\nestimated using the mesoscale eddy trajectory product from the Archiving, Validation\nand Interpretation of Satellite Oceanographic (AVISO) data. During 1993-2019, there\nwere a total of 14539 cyclonic eddies, which, during the intensification stage, occupied\n~5.7% of the area of the NPSG (Fig. S7). The POC export fluxes induced by eddy\nintensifications in the NPSG were calculated as F (Z )×A, where A is the fractional\nEI Eu\narea occupied by cyclonic eddies during the intensification stages.’\nFor figures, the original Figure 5 has been moved to the supplementary information,\nand the original Figure S7 has been removed.\nImprecisions on the approach that need clarification, issues with text and figures.\nSection 2.1\n11. Line 97 and onward. This paragraph about the position of the floats is a little tedious\nto read. Maybe the authors could either streamline or fold in some results in there as\nthey describe the trajectory.\nResponse: Following the reviewer’s suggestion, the descriptions of both the float\nposition and float trajectory have been combined. In the new text, the paragraph you\nmentioned has been removed.\n12. Line 107: “The euphotic depth (ZEu) was on average ~159 m within CE 1 and 161\nm in ACE” is this difference really significant?\nResponse: We conducted a two-sample t test and found that the averaged Z for CE 1\nEu\ndid not statistically differ from that for ACE 1. We have mentioned this in the revised\ntext (Lines 141-142):\n‘A two-sample t test suggests that the averaged Z for CE 1 was not statistically\nEu\ndifferent from that for ACE 1.’\n13. line 115: Correlations are reversed: change increasing to decreasing and vice versa.\nResponse: Done.\n14. Line 116: “This result suggested that nutrients in the euphotic zone were enhanced\nby the uplift of isotherms within this cyclonic eddy17,” Don’t you mean that uplift\noccurs at the edge of CE instead of “within”?\nResponse: We mean that uplift occurs within the CE because the radial distribution of\nnitrate concentration in CE 1 exhibited a higher level of nitrate in the CE 1 core than at\nits edge.\n15. line 123: Trends are reversed: change positive to negative and vice versa.\nResponse: Done.\n16. Text on the figure was blurry, small and hard to read in my version.\nResponse: We now use a larger font size for the text in Figure S1 and have updated all\nthe figures with a higher resolution.\n17. Zscm is used to discuss the changes in the different properties measured. Could you\nexplain why? How to separate the effect of the eddy dynamics and the change in\nsampling depth due to variations in Zscm? Is the assumption that Zscm follows a\ndensity layer? Maybe using density instead of depth would be more insightful?\nResponse: We used Z to discuss the biogeochemical effects of mesoscale eddies\nscm\nbecause mesoscale eddies have been demonstrated to significantly affect the subsurface\nchlorophyll maximum in the North Pacific subtropical gyre (Xiu & Chai, 2020). As\nshown in Fig. R3a and b, Z mainly follows the density layer σ =23.8 kg m-3 in CE 1\nscm θ\nand σ =23.3 kg m-3 in ACE 1. Due to the regulation of submesoscale frontal dynamics,\nθ\nthe Z at the CE 1 edge was shallower than the depth of σ =23.8 kg m-3 from 28 April\nscm θ\nto 3 May 2019. Linear regressions along the density layer present analogous results to\nthose along the Z for Chl and POC. There are no significant correlations between the\nscm\ntemperature and r/R because the along-isopycnal temperature was almost the same. The\nlinear regression result for NO along σ =23.8 kg m-3 is opposite to that along Z in\n3 θ scm\nCE 1 because the isopycnal reaches a deeper depth where the nitrate level is higher\nfrom 28 April to 3 May 2019. During this period, the isoline σ =23.8 kg m-3 was below\nθ\nthe euphoticzone depth where there is limited phytoplankton photosynthetic activity.\nIn contrast, the Z was within the euphotic zone so that the impacts of the eddy\nSCM\ndynamics on the biological processes can be well reflected. As such, we discussed the\nchanges of different biogeochemical tracers using Z .\nscm\nReference:\nXiu, P. & Chai, F. (2020). Eddies Affect Subsurface Phytoplankton and Oxygen\nDistributions in the North Pacific Subtropical Gyre. Geophys. Res. Lett. 47,\ne2020GL087037\nFigure R3. a-b Vertical distribution of (a) Chl and (b) NO in CE 1. c-d Vertical\n3\ndistribution of (c) Chl and (d) NO in ACE 1. Black, red and white lines in a-d represent\n3\nthe mixed layer depth, the depth of the subsurface chlorophyll maximum and the\nisopycnals, respectively. e-h Radial distributions of c temperature, d NO , e Chl and f\nθ θ\n(blue) ACE 1. The solid lines indicate the linear regression lines.\nSection 2.2\n18. Please state clearly that you attribute change in integrated content over time to\nchange in flux from the top, and detail and justify your assumptions.\nResponse: Thank you for the suggestion. In this study, the rate of change of the\nintegrated POC from depth z to the mesopelagic layer is attributed to the net change\nbetween the POC flux supply from depth z and POC consumption between depth z and\nthe base of the mesopelagic layer. Either changes in POC export or in POC consumption\nin the water column can affect this rate. The underlying assumption is that while the\nfloat drifted along the front, it sampled homogeneous water masses over time. We have\nclarified this point in the Methods section (Lines 495-507). Additionally, the\nassumption that the float sampled data as the time evolution of the front has been\njustified, as we replied to your comment #4.\n19. More arguments could be provided to justify the reason for comparing the\nattenuation of a flux anomaly (FEI(z)) calculated with the float with the attenuation of\nthe total POC flux from the literature.\nResponse: Thank you for the suggestion. For eddies, significant POC export is not\nsustained over their whole lifespan and is often associated with the physical dynamics\nof eddies (Zhou et al., 2020). The temporal evolution of biogeochemical processes in\nthe eddy has been suggested to progress from nutrient injection, biomass buildup, and\nexport enhancement during the eddy intensifying stage to biomass and export decline\nduring the eddy decay stage (Sweeney et al., 2003; Zhou et al., 2020; Zhou et al., 2021).\nObservations have shown that intensifying eddies exhibit a large biological response,\nwhile eddies in the inactive stage do not show a significant biological response or high\nexport flux (Sweeney et al., 2003; Buesseler et al., 2008). We assume that the\nmagnitude of the export flux during the eddy decay stage is negligible, so that the flux\nanomaly approaches the total POC flux, and can be compared with those directly\nestimated from sediment traps or radioactive techniques recorded in the literature.\nNevertheless, our estimated F (z) is a flux anomaly relative to the eddy decay stage,\nEI\nand it could underestimate the real POC export flux during the eddy intensifying stage.\nWe have added this discussion to the text (Lines 227-235).\n‘For eddies, significant POC export is not sustained over their whole lifespan and is\noften associated with the physical dynamics of eddies42,52. Observations have shown\nthat intensifying eddies exhibit a large biological response, while eddies in the inactive\nstage do not show a significant biological response or high export flux 29,31,42,52. We\nassume that the magnitude of the export flux during the eddy decay stage is small, so\nthat the enhanced net POC flux is considered as the approximation of the actual POC\nflux. The enhanced POC flux may underestimate the actual POC flux during the eddy\nintensifying stage as F (z) is a flux anomaly relative to the eddy decay stage.’\nEI\nReferences:\nBuesseler, K. O., Lamborg, C., Cai, P., Escoube, R., Johnson, R., Pike, S., Masque, P.,\nMcGillicuddy, D. & Verdeny, E. Particle fluxes associated with mesoscale eddies in the\nSargasso Sea. Deep-Sea Res. II 55(10–13), 1426–1444 (2008).\nSweeney, E. N., McGillicuddy, D. J. & Buesseler, K. O. Biogeochemical impacts due\nto mesoscale eddy activity in the Sargasso Sea as measured at the Bermuda Time-Series\nStudy (BATS). Deep-Sea Res. II50, 3017–3039 (2003).\nZhou, K., Dai, M. Xiu, P., Wang, L., Hu, J. & Benitez-Nelson, C. R. Transient\nenhancement and decoupling of carbon and opal export in cyclonic eddies. J.\nGeophys. Res. Oceans125, e2020JC016372 (2020).\nZhou, K., Benitez-Nelson, C. R., Huang, J., Xiu, P., Sun, Z. & Dai, M. Cyclonic eddies\nmodulate temporal and spatial decoupling of particulate carbon, nitrogen, and biogenic\nsilica export in the North Pacific Subtropical Gyre. Limnol. Oceanogr. 66, 3508–3522\n(2021).\n20. Write P(z), E(z) on figure 3 to make it easier to understand.\nResponse: The symbols ‘P(z)’ and ‘E(z)=∂P(z)/∂t’ have been added to the new Fig. 4a.\n21. line 153: Is «exponentially» appropriate? It seems linear.\nResponse: We agree. It is not appropriate here. The word ‘exponentially’ has been\nreplaced with ‘gradually’.\n22. line 162: The total increase in POC flux could be calculated by reconstructing the\namount of remineralized POC from AOU and Redfield ratios.\nResponse: Thank you for the suggestion. We tried to quantify remineralized POC from\nAOU as suggested, but it may introduce more uncertainties to our results. The AOU\nmultiplied by the Redfield ratios represents the heterotrophic respiration of the total\norganic carbon (TOC), 50-90% of which is dissolved organic carbon. Because the ratio\nof the POC to TOC and the Redfield ratios in the study region were not measured, we\ndid not use the AOU to reconstruct the remineralized POC and only used AOU change\nto demonstrate possible changes in remineralization between different stages. We have\nadded this discussion to the text (Lines 512-517):\n‘The AOU multiplied by the Redfield ratios represents the heterotrophic respiration of\nthe total organic carbon (TOC), 50-90% of which is dissolved organic carbon48,58,59.\nBecause the ratio of the POC to TOC and the Redfield ratios in the study region were\nnot measured, we did not use the AOU to reconstruct the remineralized POC and only\nused AOU concentration change over time to demonstrate possible changes in\nremineralization between different stages.’\nReferences:\nAbell, J., Emerson, S., & Renaud, P. Distributions of TOP, TON and TOC in the North\nPacific subtropical gyre: Implications for nutrient supply in the surface ocean and\nremineralization in the upper thermocline. J. Mar. Res. 58(2), 203–222 (2000).\nHansell, D. A., & Carlson, C. A. Biogeochemistry of total organic carbon and nitrogen\nin the Sargasso Sea: Control by convective overturn. Deep‐Sea Res. Part II 48(8–9),\n1649–1667 (2001).\nKheireddine, M. et al. Organic carbon export and loss rates in the Red Sea. Global\nBiogeochem. Cycles 34, e2020GB006650 (2020).\n23. Y-scales of 3g and 3h are making it confusing, maybe 0-700 m could be used.\nResponse: The Y-scales of 3g and h have been limited to the range 0-700 m.\nSection 2.3\n24. L 183: Here, the front is defined by the temperature gradient. Would it be possible\nto find out whether the front is dynamically active and carrying POC at depth or not?\nResponse: We diagnosed the frontal dynamics using more physical parameters, such\nas the finite-size Lyapunov exponent (FSLE), lateral buoyancy frequency (M2) and\nRichardson number (R). The concurrence of SST gradients, high FSLE, M2 and small\ni\nR suggests that the front was dynamically active (Fig. S5 and S7). Below the euphotic\ni\nzone depth, we found that the POC concentration was high, which indicated that the\nintense submesoscale vertical velocities subducted high POC downward (Fig. S9).\nThese results have been incorporated in the main text in Lines 256-264.\n25. L184/185: Can we really speak of degradation/intensification, since the float crosses\nthe front but doesn't stay there?\nResponse: According to the frontogenesis theory, when the front is enhanced, it will\ngenerate upwelling on the warm side of the front and downwelling on the cold side of\nthe front. During the sampling period, the front experienced intensifying and decaying\nstages, while the float was continuously sampled along its warm side (not across the\nfront). We conducted an experiment of particle tracking and a T-S characteristic analysis\nof the water mass to justify that the float did drift along one side of the front, on which\nrelatively homogeneous water masses were sampled. As such, the float observations\ncan be interpreted as a temporal signal due to the stage change of the front. Our\nhypothesis is that when the front intensifies, the dynamic and biogeochemical changes\non each side are generally coherent. Please see the details in our reply to comment #4.\n26. L 186 / Fig. S4e: Why is the gradient lower than the background during the decaying\nstage? Why not equal since the front goes back to background?\nResponse: Thank you for the insightful question. Fig. S4e has been updated to exclude\nextremely high GM values when calculating the background GM. It appears reasonable\nnow.\n27. L 188: Fig. S4g: How is the strain rate calculated and from which data product? You\ncould physically define the front and add its position to your figures to make\ninterpretation easier.\nResponse: The strain rate was calculated using satellite-derived altimetry data (sea\nsurface height data) at a resolution of 0.25°∙0.25°. We realized that the spatial resolution\nof the strain rate is inadequate to identify the frontal structure and have removed it in\nthis revision. We have instead used the finite-size Lyapunov exponent (FSLE) to\nidentify the dynamic active regimes of the front calculated from the sea surface height\ndata. The along-track time series of FSLE and lateral buoyancy frequency (M2)\npresented the co-located pattern of high FSLE and M2, suggesting that the frontal region\nwas in active submesoscale motion. Please see Fig. S7.\nMethods\n28. L 313: You could spell out bbp(700) and PAR again.\nResponse: Following the suggestion, the words ‘bbp(700) and PAR’ have been\nreplaced with ‘particulate backscattering coefficients at 700 nm (b (700)) and\nbp\nphotosynthetically available radiation (PAR)’ .\nReviewer #3 (Remarks to the Author):\nEfficient biological carbon export to the mesopelagic ocean induced by submesoscale\nfronts in subtropical gyres\nGuo, M., Xing, X., et al.\nNature Communications\nThis study presents data from BGC-Argo floats along with interpolated satellite remote\nsensing data to investigate the role of processes at the submesoscale in shaping carbon\nexport. The authors find that, in the North Pacific subtropical gyre, processes at the\nmesoscale and submesoscale may play a significant role in transporting carbon from\nthe surface to the interior ocean. In particular, they note that the previous assumption\nof a relationship of carbon attenuation with temperature may be better considered as a\nrelationship between attenuation and SST gradient magnitude. Their suggested\nrelationship could help better constrain carbon cycling in the subtropical gyres in\nnumerical models.\nI would like to thank the authors for a clearly-written manuscript with many high-\nquality figures. I enjoyed reading this manuscript and felt it presented a compelling case\nfor considering carbon export at the submesoscale in the subtropical ocean. Carbon\nexport is an important and timely topic, and I appreciate the care with which the authors\npresent the data. I have a few concerns that I hope the authors will address in order to\nmake the work more accessible to the reader. In addition, while the manuscript\ngenerally does a nice job at describing limitations with the work, there are a few\nadditional constraints to consider, as detailed below. My major concerns are\ndocumented below; there were also several minor concerns that I think the manuscript\nwould benefit from addressing.\nResponse: Thank you so much for the helpful comments and suggestions for this\nmanuscript. We have addressed all your questions and concerns accordingly. We think\nthis manuscript has been much improved with your constructive inputs. Please see the\nfollowing details.\nMajor Concerns\nDefinition of the submesoscale front: The submesoscale front described in this\nmanuscript is an interesting feature, but the manuscript does not yet convince me that I\nam seeing a density front and therefore that the resulting POC analysis is attributable\nto the feature. First, the front is diagnosed from SST and SST gradient. This ignores the\npotential contribution of salinity. To remedy this, I would like to see section plots (time\nversus depth) of the float’s temperature and salinity over this period (April 21-May 3)\nto visualize the depth of this front.\nResponse: Thank you for the helpful suggestion. As the float did not cross the front but\ndrifted along the front, we first plotted the vertical transects of temperature, salinity,\nand their anomalies obtained by subtracting the time averages from the instantaneous\nvalues (Fig. S6). As recorded by the float, the temperature was higher and salinity was\nlower at the frontal region than inside CE 1, suggesting a relatively light water mass\nconsistent with the satellite-derived sea surface temperature. Because the float drifted\nalong the front, the water mass sampled showed a coherent physical characteristic (Fig.\nS6e).\nSecondly, the float was drifting on one side of a strong current (Fig. 2). According to\nthe geostrophic balance, the float should be on the low-density side of the front,\nconsistent with the observations.\nThirdly, we calculated the Richardson number R defined as (Fig. S7).\ni\n2 2\nSmall R\ni\nvalues (R\ni\n<2) were found below the MLD to ~200 m\n𝑅\nd𝑖u\n=\nrin\n𝑓\ng 2\n𝑏\n1𝑧-\\⁄\n2\n𝑏\n8\n𝑠\nApril 2019,\nhighlighting the ageostrophic character of the dynamical regime encountered by the\nfloat and the expected strong frontogenesis processes at play. As suggested by\nSiegelman et al. (2020), frontogenesis presented as a small R is prone to generate\ni\nenhanced vertical velocities in the ocean interior below the mixed layer.\nLastly, we also showed the finite-size Lyapunov exponent (FSLE) and lateral buoyancy\nfrequency (M2) values (Fig. S7). All these dynamic variables suggest that the float was\nsampling on one side of the front and that the front experienced different stages during\nthe sampling period.\nThe above information has been incorporated in the revised manuscript (Lines 247-\n261).\nFigure S6. Physical characteristics of the front. Time series of a temperature, b salinity,\nc temperature anomaly and d salinity anomaly measured by float 2902753 from 1 April\nto 3 May 2019. The black, red and cyan lines indicate the mixed layer depth (MLD),\nthe depth of subsurface chlorophyll maximum (Z ) and the euphotic zone (Z ),\nSCM Eu\nrespectively. The white lines are the isopycnals of 23, 24 and 25 kg m-3. The temperature\nand salinity anomalies were defined as the instantaneous values subtracting the full time\nmean. e Temperature-salinity diagram with data points from float 2902753 from 1 April\nto 3 May 2019. Color indicates the sampling date.\nFigure S7. The lateral buoyancy frequency ( ), finite-size Lyapunov exponent (FSLE)\nand Richardson number (R\ni\n) at the front. 2a BGC-Argo-derived lateral buoyancy\n𝑀\nfrequency during 21 April-3 May 2019. , where s is the along-track\ndirection. The black line represents the m2ixed layer depth. b BGC-Argo-derived\n𝑀 = −𝜕𝑏⁄𝜕𝑠\nRichardson number during 21 April-3 May 2019. , where f and b are the\n2 2\nCoriolis parameter and buoyancy, respectively. T\n𝑅\nh𝑖e\n=\nbl\n𝑓\nack\n𝑏\n𝑧l\n⁄\nin\n𝑏\ne\n𝑠\nrepresents the mixed\nlayer depth. c Surface FSLE at the frontal region (red line) and the lateral buoyancy\nfrequency (blue dashed line) at 100 m during 21 April-3 May 2019. Blue solid lines are\nthe buoyancy frequency envelope.\nIn addition, Figure S4 is stated to be of vertical buoyancy frequency, but that is not\npossible as in a stable water column, N2 must solely be positive. I imagine the authors\nmay have instead calculated lateral buoyancy frequency (M2), but the magnitude of the\nvalues shown are extremely high for this property; M2 values of strong submesoscale\nfronts in the Southern Ocean are of O(10^-7) (Siegelman et al. 2020). I urge the authors\nto check what they are calculating here. I do appreciate the inclusion of strain rate, and\nthe authors could also consider using Finite Size Lyapunov Exponents (AVISO+,\nhttps://www.aviso.altimetry.fr/en/data/products/value-added-products/fsle-finite-size-\nlyapunov-exponents.html) to demonstrate the presence of the frontal structure.\nResponse: Thank you for pointing this out. Yes, we identified the frontal structure using\nthe lateral buoyancy frequency but not the vertical buoyancy frequency. The lateral\nbuoyancy frequency is calculated as M2=∂b/∂s, where b is the buoyancy and s is the\nalong-track direction. By converting the unit of s from km to m, we finally obtained a\nvalue of M2 in a reasonable range, as reported in Siegelman et al. (2020). As such, Fig.\nS4 has been corrected. Please see the new Fig. S6.\nThe strain rate was calculated using satellite-derived altimetry data at a resolution of\n0.25°∙0.25°. We realized that the spatial resolution of the strain rate calculated based on\nsatellite altimetry data is inadequate to identify the frontal structure and have removed\nit from Fig. S6.\nFollowing the reviewer’s suggestion, the FSLEs have been used to illustrate the frontal\nstructure that float 2902753 encountered. As illustrated in Fig. S7, the float passed the\nregions with high FSLEs from 24 April to 1 May 2019. During this period, high FSLEs\nand M2 were often collocated, which was consistent with Siegelman et al. (2020). Fig.\nS6 has been incorporated into the results, and the method using FSLEs to illustrate the\nfrontal structure has been included in the Methods section with the following paragraph:\n‘The FSLE field\nWe use the finite-size Lyapunov exponent (FSLE) to illustrate the frontal region\nencountered by the BGC-Argo. Daily FSLEs with a spatial resolution of 0.04° were\nobtained from the Archiving, Validation, and Interpretation of Satellite Oceanographic\ndata (AVISO) service. The FSLE is defined as the inverse time of separation of two\nparticles from their initial distance δ to final distance δ (d’Ovidio et al., 2008). The\n0 f\nparticles were advected by altimetry velocities and their trajectories were computed by\nbackward-time integration of the altimetry velocities. The FSLE has been suggested to\nbe particularly suited to diagnose filamentary processes generated by mesoscale\nhorizontal shear and strain deformation (d’Ovidio et al., 2008). Large backward FSLE\nvalues represent regions of strong submesoscale transport. (Calil et al., 2010;\nSiegelman et al., 2020). As such, the FSLE from AVISO has been employed to delineate\nsubmesoscale structures (Meunier & LaCasce, 2021; Guo et al., 2022). The FSLE time\nseries was extracted along the path of float 2902753 to capture the strain field and was\nthen compared to the lateral buoyancy frequency (M2) sampled by the float.’\nSea level anomaly data: I greatly appreciate the authors’ use of in situ data combined\nwith remote sensing data. However, sea surface height data provided by AVISO\ntypically has a footprint of approximately ¼ degree. While this can be manageable for\nmesoscale work, it is often too coarse for detection of submesoscale features. I am less\nfamiliar with satellite SST footprint, but I imagine it is of similar scale. I would like to\nsee the authors discuss this potential limitation and how it might impact their results. I\nappreciate that there is some discussion of how the calculations from the SST gradient\nmagnitude:attenuation rate relationship, and I think a discussion of how even remote\nsensing does not capture the submesoscale fully would fit in here. Addressing this\nconcern, as well as my other concerns above and below, would help me feel more\ncomfortable in the extrapolation of data from two eddies to the full Northern\nHemisphere subtropical gyres.\nResponse: We agree that the current spatial resolution of sea level anomaly data is\ninsufficient for identifying submesoscale structures, so the SLA-calculated strain rate\nhas been removed from frontal structure analysis. The SLA was only used to describe\nmesoscale eddies. The SST data we used have a 4 km resolution, which has the potential\nto demonstrate submesoscale structures.\nThe submesoscale fronts induced by frontogenesis are characterized by sharp density\ngradients. In much of the world’s upper oceans, temperature variations govern the\nspatial gradients and seasonal variations of density, whereas salinity plays a secondary\nrole. By analyzing a high-resolution dataset with similar horizontal resolutions for\ntemperature and salinity, Rivière et al. (2019) suggested that over 90% of submesoscale\ndensity fronts can be identified using SST gradients. Therefore, the satellite-derived\nSST gradient as an indicator of submesoscale fronts has been suggested to be useful to\ninvestigate the spatiotemporal variation in submesoscale fronts. We have added the\nfollowing sentences to clarify this point (Lines 80-85 in SI):\n‘In submesoscale frontal regions, frontogenesis within the developing stage leads to\nsharpening of the lateral density gradients13,14,16,35. In much of the world’s ocean,\ntemperature variations play a leading role in controlling the spatial near-surface\ndensity gradients, while salinity plays a secondary role66. Sea-surface temperature\ngradients derived from satellites at a 4-km resolution have been used to study fronts\nand filaments at scales of O(1 to 10) km67,68.’\nOn the other hand, the SST gradients cannot cover all the density fronts. In regions that\nare strongly influenced by freshwater runoff and rain or have close-to-freezing surface\ntemperatures, salinity variations govern the near-surface density gradients. Therefore,\nthe spatial and temporal variation in the b value may be overestimated in this study.\nWith more submesoscale structures identified in the region, a higher POC transfer\nefficiency is expected. We have added the following sentences to present the limitations\nof using SST gradients as an indicator of fronts and discussed their potential impacts\non our results (Lines 105-108 in SI):\n‘Note that the GM cannot identify density fronts governed by salinity variations70. The\nspatial and temporal variation in the b value may be overestimated in this study. With\nmore submesoscale structures identified in the region, a higher POC transfer efficiency\nis expected.’\nReferences:\nRivière, P., Jaud, T., Siegelman, L., Klein, P., Cotté, C., Le Sommer, J., Dencausse, G.\n& Guinet, C. Sub-mesoscale fronts modify elephant seals foraging behavior. Limnol.\nOceanogr. Lett. 4, 193-204 (2019)\nJohnson, G. C., Schmidtko, S., & Lyman, J. M. Relative contributions of temperature\nand salinity to seasonal mixed layer density changes and horizontal density gradients.\nJ. Geophys. Res. Oceans 117, C04015 (2012).\nDong, J., & Zhong, Y. Submesoscale fronts observed by satellites over the northern\nSouth China Sea shelf. Dyn. Atmospheres Oceans 91, 101161 (2020).\nGualtiero, S. J. & Mahadevan, A. Submesoscale-selective compensation of fronts in a\nsalinity-stratified ocean. Sci. Adv. 4,e1701504 (2018).\nMinor Concerns\nLine 26: unnecessary “however”\nResponse: We have deleted the word ‘however’.\nLine 32: Is it clear that submesoscale motions would result in a net sink of CO2 in the\nsubtropical gyres, or is there evidence that high DIC water from the mesopelagic could\nbe brought up to the service and outgas?\nResponse: The carbon exported to the mesopelagic layer generally has a ventilation\ntime scale of ~100 years. Previous studies have shown that deep water upwelling often\noccurs in regions with sharp topographic changes, such as the regions around sea\nmountains and islands. However, overall, the impacts of submesoscale processes on\natmospheric carbon sinks are still an open question. Although some regional studies\nhave shown strong carbon export associated with submesoscale processes, basin-scale\nstudies are still lacking. Therefore, we have removed the phrase ‘that can potentially\ndrive atmospheric CO sinks’ in this sentence.\nregion(s) you are comparing remineralization rate against?\nResponse: The word ‘of’ has been deleted. We have added the phrase ‘compared to that\nat high latitudes’ at the end of this sentence.\nLine 42: unnecessary and confusing “on the other hand”\nResponse: The phrase ‘on the other hand’ has been deleted.\nLine 48: I suggest changing “leading to” to “resulting in”\nResponse: We have replaced ‘leading to’ with ‘resulting in’.\nLines 49-52: Consider adding citations to Mahadevan (2016) (doi: 10.1146/annurev-\nmarine-010814-015912) and Klein & Lapeyre (2009) (doi:\n10.1146/annurev.marine.010908.163704).\nResponse: The review papers by Mahadevan (2006) and Klein and Lapeyre (2009)\nhave been cited.\nReferences:\nplankton. Annu. Rev. Mar. Sci. 8, 161–184 (2016).\nsubmesoscale turbulence. Ann. Rev. Mar. Sci. 1, 351–375 (2009).\nLines 54-55: Consider providing a short summary of why plankton size distribution\nimpacts POC export rates (I imagine because of differing contributions by the\ngravitational pump?)\nResponse: Both the gravitational pump by phytoplankton itself and marine food web\ndynamics can affect POC export rates. Serra-Pompei et al. (2022) used a global\nmechanistic size-spectrum model to investigate the relation between particulate export\nand plankton community metrics. They found that the size structure of the plankton\ncommunity can affect export efficiency, as the size structure of the community can\ndetermine how efficiently energy and biomass reach larger organisms, and larger\norganisms tend to create particles (e.g., dense zooplankton fecal pellets) with faster\nsinking velocities. We have therefore added the sentences ‘The vertical motions induced\nby the submesoscale front may also drive the vertical nutrient supply and stimulate the\ngrowth of large phytoplankton communities32–36; these large phytoplankton may sink\nfast and affect the carbon export efficiency by creating particles with fast sinking\nvelocities through food web dynamics16,36,37’ in Line 62.\nReference:\nSerra-Pompei, C., Ward, B. A., Pinti, J., Visser, A. W., Kiørboe, T., & Andersen, K. H.\nLinking plankton size spectra and community composition to carbon export and its\nefficiency. Global Biogeochem. Cycles 36, e2021GB007275. (2022).\nLine 56: Consider changing “However,” to “Despite their potential importance to shape\nPOC export,” to make continuity stronger\nResponse: Done.\nLines 71-73: Have the authors seen Llort et al. (2018) (doi:\nhttps://doi.org/10.1002/2017JC012861). While they use a different method, I suggest\ntheir work was among the first to estimate carbon flux from BGC-Argo. I do agree that\nthis manuscript’s work looking at vertical attenuation is novel, so I suggest rephrasing\nthis sentence to recognize previous efforts and clarify the novel elements of this\nmanuscript.\nResponse: We thank the reviewer for this good suggestion. We acknowledge that Llort\net al. (2018) identified subduction events and quantified the carbon export flux\nassociated with submesoscale fronts by using BGC-Argo for the first time. We have\ncited their paper and rephrased the sentence as follows (Lines 91-96):\n‘The BGC-Argo can be used to identify elevated POC in the mesopelagic layer and\nestimate the carbon flux associated with submesoscale features20,23. In this study, we\nfurther show the capability of using BGC-Argo floats to estimate the transfer efficiency\nof the carbon export flux in response to submesoscale fronts.’\nSomewhere in the introduction, it would enhance your paper’s reach to introduce the\nterms “mesoscale” and “submesoscale” dynamically - potentially defining them with\nthe Rossby number or some other scaling.\nResponse: Thank you for the nice suggestion. We agree that the ‘mesoscale’ and\n‘submesoscale’ terms should be introduced dynamically and have defined them using\nthe Rossby number and Richardson number in the following sentence (Lines 44-47):\n‘Subtropical gyres have abundant mesoscale eddies that are characterized by a small\nRossby number (R ) and a large Richardson number (R), as well as submesoscale fronts\n0 i\nthat are characterized by O(1) R and R12-16’.\n0 i\nLine 90: Please point the reader to Figure 1b at this point - I got quite lost reading until\nI was able to match up with the figure.\nResponse: We have cited Fig. 1b at the end of this sentence.\nLines 90-92: I am confused by this sentence - are you saying that you look at the slope\nof the isopycnals to determine intensification?\nResponse: We determined the intensification by comparing the SST gradient\nmagnitude (GM) of the front with that of the background.\nLine 93: Again, please cite Figure 1c.\nResponse: Done.\nLines 95-96: As someone who is used to working with BGC-Argo floats that are\nsampling at the traditional rate of 10 days, it would help to know earlier that the floats\nhad more regular sampling. Please consider moving the content of this sentence to\nearlier in the paragraph.\nResponse: The content of this sentence has been moved to the introduction section in\nLines 98-99.\nFigure 1: Change blue and red dots to colors that are more visible on the chosen colorbar\nas the representations for NO3- and POC sampling stations.\nResponse: The blue and red dots have been replaced with black dots and yellow\npentagrams in Fig. 1a.\nLine 111: What was the average depth of the subsurface chlorophyll maximum?\nResponse: The average depth of the subsurface chlorophyll maximum (Z ) is\nscm\n117.0±9.9 m for CE 1 and 127.1±16.8 m for ACE 1, as shown in Fig. S1. We have\nspecified the Z values explicitly in the text. Please see line 157.\nscm\nLines 116-118: I generally agree with the statement that there are higher POC\nconcentrations in the CE center than the edge, but I would appreciate some commentary\non the POC peaks at r/R =~ 1 and 1.3 at 200 m.\nResponse: Thank you for pointing this out. The float at r/R = ~ 1 and 1.3 was right on\nfilaments with active submesoscale dynamics. The high POC at the edge of CE 1 was\nlikely due to the subduction of POC by intense submesoscale vertical motions. We have\nclarified this point in the main text in Lines 165-169:\n‘The POC at 200 m reached its peaks at the edge of r/R=~1 and 1.3, which is likely due\nto the subduction of POC by intense submesoscale vertical velocity at the edge17,19,20,23’\nLine 122: Add a semicolon before “that is”\nResponse: Done.\nLines 124-125: Perhaps I am missing something obvious, but Figure 2b illustrates to\nme that POC concentrations are higher at the ACE center than the edge at 200 m?\nResponse: The original description is not correct. We have rephrased the sentence as\nfollows:\n‘The POC concentrations were lower at the Z and higher at 200 m in the ACE 1\nSCM\ncenter than at its edge, probably suggesting a slower vertical attenuation of POC in\nACE1 center.’\nFigure 2: Why are standard deviations only shaded for some points?\nResponse: The shades are the 95% confidence intervals of the fitting results using a\nsmoothing algorithm by Eilers (2003). The value of the confidence interval at both the\nleft and right edges of the data is missing by using Eilers’ algorithm. Therefore, the\nshades are not displayed at the boundaries of the data.\nReference:\nEilers, P. H. C. A Perfect Smoother. Anal. Chem. 75(14), 3631?3636. (2003).\nLine 130: Specifically cite Figure 1d.\nResponse: The citation ‘Fig 1’ has been changed to ‘Fig. 1d’.\nLine 142: Note that you are defining stable based on changes in r/R.\nResponse: The daily snapshots of BGC-Argo show that the float was likely trapped by\nthe eddy (Fig. R1). During the observational period, the float drifted counterclockwise\naround the eddy center. By quantifying the position of the float relative to the eddy\ncenter, we found that the float stayed in a stable position relative to the eddy center.\nWe therefore define the stable locations based on changes in r/R.\nFigure R1. Daily snapshots of the float location in CE 2. Black and orange dots\nrepresent the eddy center and the float, respectively. Dashed contours are the isolines\nof SLA. Gray lines indicate the eddy radius. The black solid contour is the boundary of\nthe eddy.\nLines 146-148: Can this linear least squares regression plot be included in the\nsupplemental information to provide a sense of how different the calculated E(z) values\nare? Alternatively, one could include error bars on Figures 3c and 3d.\nResponse: Thank you for the suggestion. The linear least squares regression\ninformation has been included in the SI. Information on the rate of change of integrated\nPOC, the standard error and the R2 is shown in Table S6. Error bars were also added to\nthis figure (now Fig. 4c, d).\nComment only: I really like the inclusion of AOU/oxygen utilization rate to investigate\nbiological activity!\nResponse: Thank you for your positive comment!\nLine 174: Consider mentioning that the Martin curve has long been used as the standard\nfor understanding POC attenuation across the global ocean for those who are not\nfamiliar with the concept.\nResponse: We have followed this suggestion to add the phrase ‘Because the Martin\ncurve has long been used as the standard for understanding POC attenuation across\nthe global ocean’ in Lines 235-237.\nSection 2.4: The manuscript appears to argue that the relationship between SST gradient\nmagnitude and the b value is consistent across both mesoscale eddies and submesoscale\nfronts (as implied in Figure 4). However, the authors do a nice job in the introduction\nexplaining why there are different rates of export by mesoscale and submesoscale\nprocesses, so I am not so sure that the two can be compared in this way. I’d appreciate\nsome explanation or breakdown of the limitations of the SST GM:b relationship,\nparticularly with respect to spatiotemporal scales.\nResponse: Thank you for the insightful comment. Yes, we put figure 4 in a broad\nperspective including all available data that were collected in different mesoscale and\nlarge-scale conditions. The assumption is that submesoscale processes are generally\nubiquitous in the ocean and can occur in both mesoscale eddy core and edge regions.\nThe submesoscale fronts at the eddy edge are often stronger than those at the eddy core,\nas demonstrated in Fig. 4. With the relationship in this figure, we can use one variable\n(GM) to estimate the b value, and we do not need to know whether the study region is\nin mesoscale and submesoscale conditions first.\nFurthermore, because the spatial near-surface density gradients can be mainly explained\nby SST variations in much of the world’s oceans, the satellite-derived SST GM is used\nto identify the spatiotemporal variations of submesoscale fronts in this study. However,\nsubmesoscale fronts formed by freshwater runoff, rain and in regions of near-freezing\ntemperature cannot be identified by SST GM. Therefore, the POC transfer efficiency\nmay be underestimated by extrapolating the SST GM: b relationship to the whole basin\nscale. As mentioned in our reply to main comment #3, we have acknowledged the\nlimitations of this method in the revised text.\nFigure S6: A different colorbar (perhaps cmocean’s “algae” colorbar,\nhttps://matplotlib.org/cmocean/) would be a better choice for this figure.\nResponse: We thank the reviewer for the good suggestion. The cmoean’s algae\ncolormap works better for Fig. S6 (updated as Fig. S11) because the locations of the\nsample points are displayed more clearly compared to those in the previous Fig. S6:\nFigure S11. Locations of the POC flux data from previous studies (Fig. 5, Table S4) in\nsubtropical gyres. The background color is the mean chlorophyll concentration from\nsatellite data, and the black contour is the chlorophyll concentration of 0.1 mg m-3.\nFigure 5: Please consider using different colorbars for panels a and c versus b and d. At\nfirst glance, instinct is to compare a and b versus c and d. Different colorbars will make\nthe story more clear and enhance understanding of your discussion.\nResponse: Done. The color bar for panels b and d is now different from that for panels\na and c.\nFigure S15. Transfer efficiency of POC flux at 1000 m estimated based on attenuation\ncoefficient b. a-b Spatial distributions of attenuation coefficient b derived from GM\n(b ) on 25 April 2019 (a) and its transfer efficiency of POC flux at 1000 m (T (b ))\nGM eff GM\n(b). c-d Spatial distributions of the attenuation coefficient b derived from the median\ntemperature of the upper 500 m (b ) on 25 April 2019 (c) and its transfer efficiency of\nT\nPOC flux at 1000 m (T (b )) (d).\neff T\nFigure S7: Is it possible to put the eddies investigated in this study (CE 1 and 2) on\npanel b as a comparison? This could go a long way in solidifying the application of\nyour parameterization.\nResponse: As suggested by reviewers 1 and 2, the generalization of the BGC-Argo\nresults to the entire gyre and Figure S7 have been removed in this revision, as there\nmay exist large uncertainties.\nLines 304-307: While I agree that BGC-Argo floats can be used for this type of\ninvestigation, as evidenced by the nice work in this manuscript, I would include a caveat\nthat the current 10-day sampling regime employed by the Argo programme runs the risk\nof not capturing the submesoscale and mesoscale processes described in this paper.\nResponse: Thank you for the suggestion. We agree with the reviewer that the current\n10-day sampling strategy of the BGC-Argo program is not feasible for capturing the\neffect of carbon export by fine-scale oceanic processes. We have included the caveat\ndiscussion in the text and highlighted the need for high-frequency profiling to address\nthe challenges with the following sentences (Lines 431-438):\n‘The current 10-day sampling strategy employed by the BGC-Argo program runs the\nrisk of not capturing carbon export induced by the fine-sale processes. This study\ndemonstrated the unique application of BGC-Argo floats for studying these structures\nusing a sampling strategy of twice a day for the operation of BGC-Argo. By deploying\na large number of autonomous platforms sampling in high resolutions in the ocean, our\nunderstanding on ocean biological carbon pumps at different temporal and spatial\nscales will improve.’\nReviewer #4 (Remarks to the Author):\nReview comment\nThe manuscript by Wang et al., used two high-frequency sampling BGC-Argo deployed\nin the western Pacific to investigate the impact of the eddies on the POC export. The\nauthors reported enhanced POC export in the regions affected by intensifying\nsubmesoscale fronts and further meta-analysis of a global compiled dataset revealed a\nprevailing relationship between transfer efficiency and the strength of submesoscale\nfront (indicative of surface temperature gradient). Finally, the authors upscaled the\ncontribution of eddies to the carbon export in the entire northern subtropical Pacific\ngyre by synthesizing the frequency of eddy occurrence.\nHowever, I find several noteworthy loopholes in the BGC-Argo data analysis, specially\nrelated to the observed AOU rate, and its discrepancy with the POC rate. See my explicit\ncomments below:\nResponse: We thank the reviewer for providing helpful suggestions and pointing out\nthe discrepancy between the AOU and POC results. We have responded to these\nquestions and comments point-by-point below. We find that the paper is significantly\nstrengthened by addressing these issues.\n1) Unexpected, negative change of AOU and the discrepancy between AOU and POC\nrate:\nFigure 3 shows the author derived negative values for the time rate of AOU in many\ncases, the implication being that twilight zone oxygen increases over time. This\ntendency is somewhat surprising to me, as we generally expect a declining trend of\noxygen over time below the euphotic zone resulting from biological respiration,\nregardless of the relative change in upper POC flux.\nFurthermore, the reported magnitude of AOU rate appears to be unrealistically high.\nThe depth-integrated AOU rates between 150m (or 170m) and 900m fall within the\nrange of 250-500 mmol m-2 d-1, equivalent to 90-180 mol m-2 yr-1. For comparison,\nthe global range of upper carbon export is only typically 1-4 mol C m-2 yr-1. These\nextremely high AOU rates also are sharply analogous relative to export flux solved from\nPOC inventory, which falls within the range of 1-2 mmol C m-2 d-1.\nI suspect there are two possible reasons for the discrepancies. It is well known that the\nevolution of eddy typically results in a significant displacement of water masses.\nThereby, observed AOU and POC change rates along the isobars may reflect a\nconfounding result of both biological and physical processes. Therefore, to better\nisolate the biologically-induced tracer change that the authors are interested in, it would\nbe more appropriate to quantify the time rate change of AOU (and POC as well) along\nwith the isopycncal surfaces.\nThe second possible reason is the float didn’t exactly track the same water mass and\nmay gradually move towards a region featured with a higher pre-formed oxygen\nconcentration. To rule out this possibility, a more rigorous examination of the float\nhydrographic data and comparison with background spatial oxygen gradients from\nexisting gridded products (e.g., WOA and GO-BAI oxygen product) and POC gradients\n(e.g., climatology of remotely sensed POC) is necessary.\nResponse: Thank you for pointing this out and providing helpful suggestions to\nexamine this issue. For eddies, the changes of the POC inventory, AOU and O during\n2\nthe intensifying and mature stages of CE 2 were actually in agreement with what the\nreviewer expected. As illustrated in Fig. R1, the mesopelagic POC inventories decrease\nand the AOU increases over time during both the intensifying and mature stages.\nMeanwhile, the O decreased over time. All these results support the mechanism by\n2\nwhich the POC inventories were consumed by heterotrophic respiration. There was\nelevated POC export during the intensifying stage of CE 2, as the rate of change of POC\ninventories was larger than that during the mature stage. As demonstrated by the larger\nrate of change of AOU in the intensifying stage than in the mature stage, biological\nrespiration was also elevated during the intensifying stage.\nIn the frontal region, the AOU change rates are negative, as pointed out by the reviewer.\nThe following have been conducted to examine this issue.\nFirstly, we prove that the float sampled a similar water mass during the period.\nAccording to the frontogenesis theory, when the front is enhanced, it will generate\nupwelling on the warm side of the front and downwelling on the cold side of the front.\nDuring the sampling period, the front experienced intensifying and decaying stages,\nwhile the float was continuously sampling along its warm side (not across the front).\nAs such, the float observations can be interpreted as a temporal signal due to the stage\nchange of the front. Our hypothesis is that when the front intensifies, the dynamic and\nbiogeochemical changes on each side are generally coherent. The spatial distributions\nof satellite temperature data have demonstrated that the float was actually on one side\nof the front. To justify that the float drifted along the front, we conducted a numerical\nparticle tracking experiment by releasing particles at the beginning position of the float\n(Fig. S14). The particle tracking results suggest that the float drifted along the front in\na quasi-Lagrangian manner (Text S3). In addition, the T-S diagram demonstrates a\ncoherent physical characteristic of the water masses along the front, suggesting that\nhomogeneous water masses have been sampled by the float (Fig. S6).\nSecondly, we followed the reviewer’s suggestion to compare the background O\n2\ngradients and sea surface POC (remote sensing product) with those derived from BGC-\nArgo (Fig. R2 and R3). The background O from GOBAI did not change significantly\n2\ncompared with the float data. During the sampling period, the depth-averaged O first\n2\nincreased, then decreased, and then increased again without a clear trend. Satellite POC\ndata also showed a variable pattern without a clear trend (Fig. R2 and R3). These results\nindicate that the background condition did not change largely in space during the float’s\nmovement.\nWe thus think there may be two possible reasons for the negative change of AOU over\ntime along the front. First, there are errors in estimating the rate of change of both the\nAOU and POC inventories, as the float did not sample exactly the same water mass but\nsimilar ones. Due to atmosphere-ocean oxygen disequilibrium, AOU has been\nsuggested to overestimate true oxygen utilization (Sulpis et al., 2023; DeVries & Holzer,\n2019; Duteil et al., 2013; Holzer, 2022; Ito et al., 2004; Koeve & Kähler, 2016). The\noverestimation of O utilization for each individual water mass brings larger\n2\nuncertainties in the AOU rate estimation compared to the rate of POC inventory\nestimation (see larger standard deviations in Fig. R4b compared to Fig. R4a). Second,\nthe negative AOU trend may reflect that biological respiration decreased with time in\nthe study region. The sampled front was close to the mesoscale eddy CE 1, and the float\nwas actually inside CE 1 on March 31-April 14, during which CE 1 weakened (Fig.\nR5). After that, the float moved from CE 1 to the frontal region during April 21- May\n3; therefore, the condition in the frontal region may be connected with that inside CE\n1. While the float was inside CE 1, the eddy weakened gradually with decreased POC\nexport and decreased AOU, as similarly demonstrated in CE 2. The water mass\nassociated with the float moved from CE 1 to the frontal region and may thus show a\ngradually decreasing AOU trend, which we call the mesoscale background.\nSuperimposed on this mesoscale background, frontal dynamics further modified the\nPOC and AOU in the water mass. Therefore, we think this negative AOU trend may\nresult from the mesoscale background, as both stages of the front showed a similar\nnegative trend. To identify the impact of front, we removed this background AOU trend\nfor both front stages in this revision. By removing the background AOU trend, the rate\nof change of AOU shifted toward positive values. Overall, the net rate of change of\nAOU (defined as E (z)-E (z) or E (z)-E (z)) is much larger for CE 2 than for the\nEI EM FI FM\nfront (Fig. 4e and f), which is consistent with the result of high POC transfer efficiency\nalong the front and low POC transfer efficiency in CE 2. Based on the analysis above,\nwe present the net rate of change of AOU in Figure 4 in this revision.\nRegarding the high AOU-based respiration rate, we checked our calculations and\ncompared them with a previous study by Kheireddine et al. (2020). Comparing the\ndepth-averaged AOU rate ( ) with that estimated in the Red Sea\n1 𝑧\n𝜕(𝑍𝑏𝑎𝑠𝑒−𝑍∫𝑍𝑏𝑎𝑠𝑒 𝐴𝑂𝑈𝑑𝑧) \n(Kheireddine et al., 2020), we find that the rates of change of the averaged AOU are in\n𝜕𝑡\na similar range between the two studies (the maximum AOU rate is 0.72 mmol O m-3\n2\nd-1 in this study and 0.24 mmol O m-3 d-1 in the Red Sea). In Kheireddine et al. (2020),\n2\nthe mesopelagic zone was divided into 5 layers, and the averaged AOU rate was\nindicated to represent the average remineralization rate in each layer. By multiplying\nthe Redfield value (∆C: ∆O ≈0.688) and the thickness of each layer, the AOU-based\n2\nremineralization rate in their study was calculated, i.e., 0.24 mmol O m-3 d-1 * Redfield\n2\n*66 m=10.8 mmol C m-2 d-1 (3.9 mol C m-2 y-1). The AOU-based remineralization rates\nfor the first layer of CE 2 and the front are 24.8 mmol C m-2 d-1 (9 mol C m-2 y-1) and\n7.8 mmol C m-2 d-1 (2.9 mol C m-2 y-1), respectively, in this study (Table R1).\nHowever, the AOU-based remineralization rate was still higher than the POC loss rate.\nIn the Red Sea, the AOU-based remineralization rate was reported to be 25-fold higher\nthan that estimated from the change of POC inventory (Kheireddine et al., 2020). The\ndiscrepancy is likely because the AOU reflects a consumption of total organic carbons,\nin which 50-90% have been reported to be dissolved organic carbon (Abell et al., 2000;\nHansell & Carlson, 2001). In agreement with Kheireddine et al. (2020), we find that the\nPOC loss rate accounts for a small proportion of organic carbon remineralization.\nAnalyses of global and regional ocean carbon budgets have identified conspicuous\nimbalances in the mesopelagic zone by up to an order of magnitude between\nheterotrophic carbon demand and upper layer carbon supply (Burd et al., 2010;\nSteinberg et al., 2008; Giering et al., 2014; Boyd et al., 2019). Fully addressing this\nissue requires further field work and is beyond the scope of this study. Therefore, using\nthe AOU rate to quantify the POC remineralization rate is not feasible here. We only\nused the difference of the AOU rate between the two stages to qualitatively demonstrate\nwhether the remineralization rate was increased or decreased. To make this clear, we\nnow present the averaged AOU rate instead of the integrated AOU rate in Figure 4.\nTo present the results of averaged AOU, we have added the following sentences in the\nmain text (Lines 209-213 and 271-273):\n‘In addition, the net apparent oxygen utilization (AOU) changing rate was positive in\nthe upper mesopelagic layer because the AOU rate was larger during the intensifying\nstage than the mature stage (Fig. 4e). This may imply enhanced POC consumption by\nmicrobial activity during the intensifying stage.’\n‘Different from the eddy, the net AOU changing rate was very small in the mesopelagic\nlayer (Fig. 4f). The small net AOU changing rate implies relatively stable POC\nconsumption rates during both the intensifying and decaying stages.’\nTo clarify why we used the averaged AOU rate instead of the AOU-based\nremineralization rate and how we calculated the averaged AOU rate, we have added the\nfollowing paragraph to the Methods section (Lines 512-522):\nThe AOU multiplied by the Redfield ratios represents the heterotrophic respiration of\nthe total organic carbon (TOC), 50-90% of which is dissolved organic carbon48,58,59.\nBecause the ratio of the POC to TOC and the Redfield ratios in the study region were\nnot measured, we did not use the AOU to reconstruct the remineralized POC and only\nused AOU concentration change over time to demonstrate possible changes in\nremineralization between different stages. The averaged AOU from the base of the\nmesopelagic layer (900 m) to an upper mesopelagic depth z was calculated as\n(z= [Z , 200 m, 300 m, 400 m, 500 m]). The net rate of\nEu\n1 𝑧\n(900 𝑚−𝑍)∫900 𝑚𝐴𝑂𝑈∙𝑑𝑧\nchange of AOU defined as the difference of the time rate of AOU between the\nintensifying and mature (decaying) stages of the eddy (front) was thus estimated using\nthe averaged AOU.\nReferences:\nAbell, J., Emerson, S., & Renaud, P. Distributions of TOP, TON and TOC in the North\nPacific subtropical gyre: Implications for nutrient supply in the surface ocean and\nremineralization in the upper thermocline. J. Mar. Res. 58(2), 203–222 (2000).\nBurd, A. B. et al. Assessing the apparent imbalance between geochemical and\nbiochemical indicators of meso- and bathypelagic biological activity: what the @$é!\nis wrong with present calculations of carbon budgets? Deep-Sea Res. II 57, 1557–\n1571 (2010)\nBoyd, P.W., Claustre, H., Levy, M. et al. Multifaceted particle pumps drive carbon\nsequestration in the ocean. Nature568, 327–335 (2019).\nDeVries, T., & Holzer, M. Radiocarbon and helium isotope constraints on deep ocean\nventilation and Mantle- 3He Sources. J. Geophys. Res. Oceans 124(5), 3036–3057\n(2019).\nDuteil, O., Koeve, W., Oschlies, A., Bianchi, D., Galbraith, E., Kriest, I., & Matear, R.\nA novel estimate of ocean oxygen utilization points to a reduced rate of respiration in\nthe ocean interior. Biogeosciences10(11), 7723–7738. (2013).\nGiering, S., Sanders, R., Lampitt, R. et al. Reconciliation of the carbon budget in the\nocean’s twilight zone. Nature 507, 480–483 (2014).\nHansell, D. A., & Carlson, C. A. Biogeochemistry of total organic carbon and nitrogen\nin the Sargasso Sea: Control by convective overturn. Deep‐Sea Res. Part II 48(8–9),\n1649–1667 (2001).\nHolzer, M. The fate of oxygen in the ocean and its sensitivity to local changes in\nbiological production. J. Geophys. Res. Oceans127(8), e2022JC018802. (2022).\nIto, T., Follows, M. J., & Boyle, E. A. Is AOU a good measure of respiration in the\noceans? Geophys. Res. Lett.31(17), L17305. (2004).\nKoeve, W., & Kähler, P. Oxygen utilization rate (OUR) underestimates ocean\nrespiration: A model study. Global Biogeochem. Cycles30(8), 1166–1182. (2016).\nKheireddine, M. et al. Organic carbon export and loss rates in the Red Sea. Global\nBiogeochem. Cycles 34, e2020GB006650 (2020).\nSteinberg, D. K., Van Mooy, B. A. S., Buesseler, K. O., Boyd, P. W., Kobari, T., & Karl,\nD. M. Bacterial vs. zooplankton control of sinking particle flux in the ocean's twilight\nzone. Limnol. Oceanogr. 53(4), 1327–1338. (2008).\nSulpis, O., Trossman, D. S., Holzer, M., Jeansson, E., Lauvset, S. K., & Middelburg, J.\nJ. Respiration patterns in the dark ocean. Global Biogeochem. Cycles 37,\ne2023GB007747. (2023).\nFigure R1. The rates of change of the POC inventory, AOU and O during the\n2\nintensifying and mature stages of CE 2.\nFigure R2. Comparison of the O between GOBAI and BGC-Argo along the float\n2\ntrajectory. The O2 concentrations were averaged between 0-900 m for both the GOBAI\nand BGC-Argo data.\nFigure R3. Comparison of the sea surface POC between the climatology of remote\nsensing and the BGC-Argo float measurement. The remote sensing POC data were\nderived from MODIS (https://oceancolor.gsfc. nasa.gov/l3/. References) and averaged\nfrom 2002 to 2022.\nFigure R4. The rates of change of the POC inventory, AOU and AOU subtracting the\nbackground AOU trend (denoted as AOU’) during the intensifying and decaying stages\nof the front.\nFigure R5. Time series of the averaged sea level anomaly (SLA) in CE 1.\nTable R1. AOU-based remineralization rate\nAveraged AOU Redfield Ratio Remineralization Remineralization\nThickness\nrate referred to rate rate refs\n[m]\n[mmol O m-3 d-1"}]

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