# Deep Ocean Steric Sea Level Change in the Subtropical Northwest Atlantic Ocean

N. Zilberman, W. Llovel, J. Steinberg, B. Meyssignac, M. Ablain, R. Fraudeau

► To cite this version:

N. Zilberman, W. Llovel, J. Steinberg, B. Meyssignac, M. Ablain, et al., Deep Ocean Steric Sea Level Change in the Subtropical Northwest Atlantic Ocean. Geophysical Research Letters, 2025, 52 (16), 10.1029/2024GL114158. [https://doi.org/10.5194/GR-114158]

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Distributed under a Creative Commons Attribution 4.0 International License
# Geophysical Research Letters®

## RESEARCH LETTER

10.1029/2024GL114158

**Key Points:**

* Multi-annual full-depth steric sea level time series are produced using Deep Argo profiles in the subtropical Northwest Atlantic Ocean

* The deep ocean is a stronger contributor to interannual steric sea level variability at the western boundary than over the abyssal plain

* Interannual variations of steric sea level from Deep Argo show good agreement with geodetic estimates

**Supporting Information:**

Supporting Information may be found in the online version of this article.

**Correspondence to:**

N. V. Zilberman,
nzilberman@ucsd.edu

**Citation:**

Zilberman, N. V., Llovel, W., Steinberg, J., Meyssignac, B., Ablain, M., & Fraseau, R. (2025). Deep ocean steric sea level change in the subtropical Northwest Atlantic Ocean. *Geophysical Research Letters*, *52*, e2024GL114158. https://doi.org/10.1029/2024GL114158

Received 13 DEC 2024
Accepted 13 JUL 2025

**Author Contributions:**

**Conceptualization:** N. V. Zilberman,
W. Llovel

**Data curation:** N. V. Zilberman

**Formal analysis:** N. V. Zilberman,
B. Meyssignac, M. Ablain, R. Fraseau

**Funding acquisition:** N. V. Zilberman

**Investigation:** N. V. Zilberman,
W. Llovel, J. Steinberg, B. Meyssignac,
M. Ablain, R. Fraseau

**Methodology:** N. V. Zilberman, W. Llovel

**Project administration:** N. V. Zilberman

**Resources:** N. V. Zilberman

**Software:** N. V. Zilberman

**Supervision:** N. V. Zilberman

**Validation:** N. V. Zilberman, J. Steinberg,
B. Meyssignac, M. Ablain, R. Fraseau

**Visualization:** N. V. Zilberman

**Writing – original draft:** N. V. Zilberman

© 2025. The Author(s).
This is an open access article under the
terms of the Creative Commons
Attribution License, which permits use,
distribution and reproduction in any
medium, provided the original work is
properly cited.

<figure><img src="image_2.png" /></figure>

## Deep Ocean Steric Sea Level Change in the Subtropical Northwest Atlantic Ocean

N. V. Zilberman¹ ID, W. Llovel² ID, J. Steinberg³ ID, B. Meyssignac⁴ ID, M. Ablain⁵ ID, and R. Fraseau⁵

¹Integrative Oceanography Division and Climate, Atmospheric Science, and Physical Oceanography Division, Scripps Institution of Oceanography, University of California, San Diego, CA, USA, ²Laboratoire d'Océanographie Physique et Spatiale (LOPS), University of Brest, CNRS, Ifremer, IRD, IUEM, Plouzané, France, ³NOAA Geophysical Fluid Dynamics Laboratory, Princeton, NJ, USA, ⁴LEGOS, CNES, CNRS, IRD, Universit. Paul Sabatier, Toulouse, France, ⁵MAGELLIUM, Ramonville Saint-Agne, France

**Abstract** The non-closure of the global sea level budget, detected since 2017, stimulates the need to better understand limitations of satellite altimetry and gravimetry measurements, and breakdown in situ measurement contributions and gaps. Here, temperature and salinity profiles collected in the subtropical Northwest Atlantic Ocean between 2017 and 2022 by Deep Argo floats are used to partition steric sea level variability into contributions as a function of depth. Interannual steric sea level variability near the surface is of the same order of magnitude over the western boundary and abyssal plain, but fluctuations below 2,000 m over the western boundary are seven times larger and seem affected by local wind forcing. This analysis demonstrates how Deep Argo enables new evaluation of regional sea level budgets and comparison to geodetic products. Differences between float measurements and GLORYS12 highlight the need for more deep-ocean measurements that can be assimilated in the development of ocean reanalysis products.

**Plain Language Summary** A better understanding of the processes driving sea level change is crucial to improve our ability to predict sea level. The objective of this work is to describe the contribution of the deep ocean to interannual variations of sea level in the subtropical northwestern part of the Atlantic Ocean. New observations of the deep ocean have been collected from automated robots, Deep Argo floats. Results reveal that interannual sea level variations due to ocean density change integrated between 2000 m and the seafloor are seven times larger at the western boundary than over the abyssal plain. Observed interannual fluctuations in deep-ocean temperature at the western boundary are linked to local wind forcing at the surface that penetrates through the water column. Our analysis demonstrates the scientific value of the Deep Argo fleet to infer temporal and spatial variations in sea level due to ocean density change, synergies between Deep Argo and satellite observations to close the sea level budget, and the need to increase full-depth ocean observations to improve sea level predictions.

## 1. Introduction

Global mean sea level (GMSL) change resulting from thermal expansion of seawater and an increase in ocean mass in response to a loss of terrestrial water storage, is one of the most serious consequences of climate change. Balancing the sea level budget is instrumental in understanding the causes of GMSL variations (Fox-Kemper et al., 2021), assessing the performance of sea level observing systems (WCRP Global Sea Level Budget Group, 2018), and communicating scientific projections to assessment users (Kopp et al., 2023). A mismatch between observed changes in GMSL and the sum of steric and ocean mass contributions has become evident since 2016 (Barnoud et al., 2021; Chen et al., 2022; Llovel et al., 2023). The non closure of the GMSL budget has raised concerns about the ability of the ocean observing network to capture the regional variability of sea level, with recent results highlighting the North Atlantic in particular as contributing to measurement disagreement (Mu et al., 2024).

In order to better predict changes in the frequency and magnitude of extreme sea level events in coastal areas, an improved understanding of regional sea level budgets is necessary (Jevrejeva et al., 2024). Regional sea level is impacted by density (steric) variations induced by buoyancy forcing, ocean mass (manometric) fluctuations resulting from glaciers and ice sheet melt and continental discharge, and ocean dynamics controlling the distribution of ocean water masses (Dangendorf et al., 2024). The heterogeneous sampling of density variations in
Writing – review & editing:

N. V. Zilberman, W. Llovel, J. Steinberg,

B. Meyssignac, R. Fraudieu

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Bathymetry in the regional Deep Argo array of the subtropical Northwest Atlantic Ocean. The study region near the western boundary is indicated in black, and the region over the abyssal plain in red. Deep Argo profiles to 5,000 m depth collected from floats 6,025, 6,026, 6,027 and 6,029 are shown respectively in yellow, black, green, and magenta rounded symbols. The white rounded symbols indicate profiles with monthly overlap between Deep Argo floats within each box; these profiles are not included in our analysis.</figcaption></figure>

the deep ocean below 2,000 m is a likely contributor to the non-closure of the regional sea level budget (Royston et al., 2020).

The deep ocean is poorly sampled, with only 10% of ocean measurements made over the past 50 years extending deeper than 2,000 m (Garcia et al., 2019). Because of large gaps in historical deep-ocean sampling, sea level budget estimates typically use a global average value to characterize deep-ocean steric sea level change, thus underestimating spatial and temporal variability in deep-ocean steric sea level (e.g., Hakuba et al., 2021; Llovel et al., 2019). The global sea level budget group (Cazenave et al., 2019) and Ocean Surface Topography Science Team (OSTST) (Fournier et al., 2023) recommend the global implementation of the Deep Argo float array (Roemmich, Alford, et al., 2019; Zilberman et al., 2023) to increase observations of deep ocean steric sea level variability.

Regional steric sea level variability along the east coast of the U.S. has been addressed in several observational studies (e.g., Dangendorf et al., 2023; Domingues et al., 2018; Ezer & Dangendorf, 2020; Little et al., 2019; Volkov et al., 2019). Historical observations suggest a limited role played by the deep ocean in decadal steric sea level variability, albeit with strong uncertainties, outside the dense water formation regions of the subpolar Atlantic and Southern oceans (Purkey & Johnson, 2010). Deep ocean contributions to the interannual variability of steric sea level are significant in the subpolar North Atlantic Ocean (Desbruyères et al., 2022) but not well quantified further south.

The objective of this work is to improve our understanding of fluctuations in deep-ocean steric sea level at interannual timescales using measurements from the Deep Argo array in the subtropical Northwest Atlantic Ocean (Figure 1). Deep Argo temperature and salinity profiles are combined to produce time series of steric sea level between 2017 and 2022 in two regions, one near the western boundary and the second, over the abyssal plain offshore (Section 2). The contribution of the deep ocean to interannual variations in steric sea level is studied and forcing mechanisms are described in Section 3. Observations are then compared to steric sea level estimates from an ocean reanalysis and a geodetic product deriving from satellite altimetry and space gravimetry measurements.
## 2. Data and Methods

### 2.1. Deep Argo Profiles

Full-depth profiles collected from 4 Deep SOLO floats deployed in the subtropical Northwest Atlantic Ocean (Figure 1), are used to compute dynamic height

$$DH = - \int_{0}^{p_{\text{ref}}} \delta^{35,0} dp, \qquad (1)$$

where $\delta^{35,0}$ is the specific volume anomaly using standard ocean reference salinity (35.16504 g kg$^{-1}$) and conservative temperature of 0°C, $p$ is the pressure, and $p_{\text{ref}}$ is the reference pressure (e.g., Gill, 1982, p. 215) between 2017 and 2022. Steric height is calculated as $SH = \frac{DH}{g}$ where $g$ is the gravitational acceleration (9.7963 m s$^{-2}$). The Deep SOLO floats used here are early-generation floats programmed to 15-day cycles to maximize float longevity and assess technology performance (Roemmich, Sherman, et al., 2019). All floats are equipped with 6000 m capable SBE61 conductivity temperature depth (CTD) sensors from SeaBird Scientific. A compressibility correction for the conductivity cell is applied to reduce salinity bias using the reference data set (Wong et al., 2020) to ±0.002 PSS-78, consistent with the Deep Argo target (Walicka et al., 2022). After the pressure dependent salinity bias is adjusted, a time-varying correction of salinity is applied if a time-linear drift is detected (Cabanes et al., 2016). Deep Argo profiles are binned and averaged to generate time series of temperature and salinity across 5-degree latitude by 5-degree longitude regions. The size of each bin is chosen to match Deep Argo's targeted spatial sampling (Johnson et al., 2015). Time series are generated in two regions located near the western boundary (21.5–26.5°N, 69.5–74.5°W) in the vicinity of the deep western boundary current, and over the abyssal plain offshore in the ocean interior (24.0–29.0°N, 59.5–64.5°W; Figure 1). We only keep temperature and salinity profiles from one float where measurements from several floats are available for the same month in each region. Temperature and salinity profiles are interpolated vertically on a regular 20-dbar grid and temporally every 15 days. While seafloor depth varies between >6,000 m over the abyssal plain and 5,000 m near the western boundary, we compute SH relative to 5,000 dbar. Target measurement accuracies (±0.002 PSS-78, ±0.001°C, and ±3 dbar) within the latitude range of 24°N (western boundary) to 26.5°N (abyssal plain) result in SH errors of ±0.7, ±0.4, and ±0.2 cm over 0–5,000 dbar, and ±0.4, ±0.2, and ±0.05 cm over 2,000–5,000 dbar. These errors are mostly related to salinity accuracy. This pre-processing results in the creation of 5+ year time series across 0–5000 dbar pressures and enables consideration of inter-annual variability. We recognize that this record is relatively short, but believe that 1–3 years variations are adequately resolved for this analysis purpose.

### 2.2. GLORYS Ocean Reanalysis

Global Ocean Reanalysis and Simulation, GLORYS12 (Lellouche et al., 2021), offers independent comparison to Deep Argo observations. This product is near-global (60°S–65°N), eddy-resolving, has a 1/12° horizontal resolution, and is built using NEMO (Madec & The NEMO Team, 2008). In deriving this reanalysis, satellite measurements of sea level, sea surface temperature, sea ice concentration, and in situ measurements of temperature and salinity are jointly assimilated using a reduced-order Kalman filter (Brasseur & Verron, 2006). GLORYS12 assimilates core (0–2,000 m) Argo float measurements but does not incorporate Deep Argo data. The Deep Argo based estimates and GLORYS12 predictions of SH presented in this analysis are thus independent. The global ocean physical multi-year product from GLORYS12 covers the period from 1992 to 2020. Here, we use GLORYS12 monthly mean temperature and salinity fields over the 2017–2020 time period to enable direct comparison to Deep Argo observations.

### 2.3. Ekman Pumping

Monthly ERA5 wind stress from the European Center for Medium-Range Weather Forecasts Re-Analysis archive (Hersbach et al., 2023), the same wind stress forcing used in GLORYS12 (Lellouche et al., 2021), is used to calculate Ekman pumping velocities ($w_{Ek}$)

$$w_{Ek} = \frac{\frac{\partial \tau^y}{\partial x} - \frac{\partial \tau^x}{\partial y}}{\rho_0 f}, \qquad (2)$$
where $\tau^y$ is meridional wind stress, $\tau^x$ is zonal wind stress, $x$ is zonal distance, $y$ is meridional distance, $\rho_0$ is the reference density (1,025 kg m$^{-3}$), and $f$ is the Coriolis parameter (e.g., Gill, 1982, pp. 326–327).

## 2.4. Geodetic Steric Sea Level

The space geodetic product developed by LEGOS/Magellium measures full-depth steric sea level from differences between total sea level and manometric sea level (Marti et al., 2022). Sea level changes at regional scales are derived from the Copernicus Climate Change Service (C3S) products. Daily grids of sea level anomalies are based on a reference altimeter mission at each time step, with the addition of a complementary mission to enhance the spatial resolution. An additional elastic correction of 0.1 mm yr$^{-1}$ at global scale is applied to account for ocean bottom deformation due to ocean mass increase (Frederikse et al., 2017). Manometric sea level change is derived from GRACE and GRACE-FO missions. Error sources in GRACE products are mainly due to ancillary data used to correct the geocenter motion, the glacial isostatic adjustment in response to the melting of paleo ice sheets, and the Earth oblateness (Blazquez et al., 2018). An ensemble approach made of different GRACE products is used to characterize these errors. A correction is applied to the total sea level data to account for the glacial isostatic adjustment (Spada & Melini, 2019). Geodetic steric sea level from the LEGOS/Magellium product is provided on a monthly time scale with 1-degree spatial resolution.

Regional-scale uncertainties for altimetry data are provided by Prandi et al. (2021) using an error covariance at yearly timescale and 2-degree resolution. For gravimetry data, uncertainties are based on covariances estimated from a gravimetric ensemble updated from Blazquez et al. (2018). Based on Blazquez et al. (2018) and Prandi et al. (2021), altimetry and gravimetry measurements could each contribute to ± 1 cm steric sea level error at monthly timescales over the western boundary and abyssal regions.

## 2.5. Interannual Variability

To enable direct comparison to Deep Argo measurements, time series of Ekman pumping from ERA5, potential temperature ($\theta$) and salinity from GLORYS12, and steric sea level from the geodetic product are interpolated at times and locations of Deep Argo measurements. All profiles are then averaged across two regions, the first located near the western boundary (21.5–26.5°N, 69.5–74.5°W) and the second over the abyssal plain (24.0–29.0°N, 59.5–64.5°W). All time series are detrended by removing a linear fit. In Deep Argo comparisons with the geodetic product and Ekman pumping estimates, interannual anomalies are derived by first smoothing in time with a 12-month running mean and then subtracting a 2017–2022 mean. In Deep Argo comparisons with GLORYS12, interannual anomalies are derived in the same manner, but only over the 2017–2020 period.

## 2.6. Heave and Spice

Interannual anomalies in $\theta$ are decomposed into heave ($\theta'_{heave}$), vertical displacement of isopycnals, and spice ($\theta'_{spice}$), changes in water mass properties along isopycnals, components following Desbruyères et al. (2022) and Chandler et al. (2024) to study mechanisms driving steric sea level variability:

$$ \theta' = \theta'|_{\rho} + \frac{d\theta}{dp} p'|_{\rho} \quad (3) $$

where $p$ is pressure, and $\theta'|_{\rho}$ defines interannual anomalies of $\theta$ on an isopycnal. The first term on the right defines the spice component $\theta'_{spice}$ computed on the $\sigma_4$ grid and interpolated back to the original pressure grid. The second term on the right defines the heave component $\theta'_{heave}$. Both $\frac{d\theta}{dp}$ and $p$ are linearly interpolated onto the $\sigma_4$ grid then interpolated back to the original pressure grid.

# 3. Results

## 3.1. Interannual Steric Sea Level From Deep Argo

The depth structure of interannual SH variability estimated from Deep Argo measurements is shown for the western boundary region (Figure 2a) and over the abyssal plain (Figure 2b). At each depth, SH is calculated as the vertical integral from 5,000 dbar. In the western boundary (black box in Figure 1), interannual SH shows strong (±2–4 cm) anomalies near the surface slowly decreasing with depth to 5,000 dbar. The interannual SH variability
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Interannual anomalies of SH (cm) relative to 5,000 dbar between 2017 and 2022 using Deep Argo (a, b). Red indicates positive anomalies, and blue negative anomalies. The black line shows zero values. Solid colored contours indicate ±2 cm, dashed contours ±1 cm, and dotted contours ±0.2 cm. SH interannual anomalies at the surface relative to 5,000 dbar from Deep Argo and steric sea level at the surface from the geodetic product between 2017 and 2022, are shown in cm (c, d). SH at 0 dbar relative to 2,000 dbar and SH at 2,000 dbar relative to 5,000 dbar from Deep Argo are also indicated. Correlations between Deep Argo and GLORYS12 at each pressure level and between 2017 and 2020 (e, f). Results are indicated for the western boundary region (a, c, e), and over the abyssal plain (b, d, f).</figcaption></figure>

over the abyssal plain (red box in Figure 1) is intensified near the surface (Figure 2b). As at the western boundary, interannual anomalies over the abyssal plain show a slow decrease with depth but they do not penetrate as deep. For example, ±1 cm SH anomalies extend to 3,000 dbar in the western boundary, compared to 1,000 dbar over the
abyssal plain. At the western boundary, deep interannual SH anomalies at 2,000 dbar (±1.4 cm; Figure 2c) are seven times stronger than over the abyssal plain (±0.2 cm; Figure 2d).

## 3.2. Validation of Geodetic Estimates of Steric Sea Level Using Deep Argo

The ability of the geodetic product to capture interannual anomalies in full-depth steric sea level is considered by comparison to Deep Argo over the western boundary and abyssal plain (Figures 2c and 2d). Geodetic steric sea level anomalies show overall good agreement with Deep Argo SH anomalies at the surface relative to 5,000 dbar in the subtropical Northwest Atlantic basin, with better consistency observed over the abyssal plain (correlation coefficient *R* of = 0.9; rms = 1.1 cm) compared to the western boundary (*R* = 0.7; rms = 1.4 cm). In the western boundary, out-of-phase anomalies and discrepancies higher than steric sea level error for Deep Argo (±0.7 cm inferred from salinity) and the geodetic product (±2 cm) are seen between 2017 and mid-2019. Deep Argo analysis reveals no peculiarity in CTD sensor performance over this time period, suggesting that differences with the geodetic approach stem from measurement errors in satellite observations. A data gap between GRACE and GRACE-FO from July 2017 to September 2018 may have resulted in significantly lower data quality during this time period, introducing errors into the 2017–2019 manometric sea level estimates. However, no obvious relationship is observed between the data gap in space gravimetry and correlation between Deep Argo SH and geodetic steric sea level anomalies for the case of the abyssal plain. Stronger misfit between Deep Argo and the geodetic product in the western boundary than abyssal plain offshore is consistent with continental leakage error in the GRACE/GRACE-FO estimates that has decreasing impact on sea level with increasing distance from the coastline, and local ocean bottom pressure variability along the shelf’s slope that is not resolved by GRACE/GRACE-FO (Cazenave & Moreira, 2022; Chambers & Bonin, 2012). Inaccuracies in satellite altimetry estimates of sea level may also contribute to discrepancies between the Deep Argo and geodetic estimates, but our results suggest that space gravimetry estimates of manometric sea level due to ocean mass variations is the main contributor, and imply that gravimetry measurements in the western boundary region contribute to larger steric sea level error amounts than based on Prandi et al. (2021) and Blazquez et al. (2018).

## 3.3. Deep Argo Comparisons With GLORYS12

The ability of GLORYS12 to resolve interannual fluctuations of SH is considered in both western boundary and abyssal plain regions. Comparisons between Deep Argo and GLORYS12 predictions of 2017–2020 illustrate the limited capacity of the ocean reanalysis to resolve the depth structure of interannual SH variability, particularly in the western boundary region (Figure S1). In the western boundary, interannual variations of GLORYS12 SH show limited correlation (<0.5) with Deep Argo between 0 and 2,000 dbar (Figures 2e and Figures S1a and S1c). The correlation between SH anomalies decays with increasing pressure and changes sign below 4,000 dbar. Over the abyssal plain, interannual GLORYS12 SH variations are more highly correlated (>0.5) with Deep Argo, with highest values (>0.75) between 0 and 1,000 dbar that then decrease with increasing pressure (Figure 2f and Figures S1b and S1d). Deep Argo profiles are not assimilated in GLORYS12 but the core (0–2,000 m) Argo array constitutes a large source of subsurface observations. Part of the SH discrepancy between Deep Argo and GLORYS12 in the upper 2,000 m at the western boundary may be due to the tendency of core Argo floats typically parking at 1,000 dbar to quickly transit the western boundary current region, therefore limiting Argo sampling density. Differences between GLORYS12 and Deep Argo SH may also be the result of a dearth of assimilated measurements collected at depths greater than 2,000 dbar. In GLORYS12’s data assimilative framework, errors may accumulate in the deep ocean such that differences between upper ocean or surface measurements and the reanalysis fields are minimized.

## 3.4. Forcing Mechanisms of Deep Steric Sea Level Variability

Deep interannual variations in Deep Argo $\theta$ are also considered in the western boundary (Figure 3a) and abyssal plain (Figure 3e) regions to infer the contributions from heave (Figures 3b and 3f) and spice change (Figures 3c and 3g). In both regions, interannual changes in $\theta$ appear more similar to the heave component, indicating the dominance of heave (Figures 3b and 3f) over spice (Figures 3c and 3g). Overall, interannual fluctuations in $\theta$ at the western boundary are higher than the abyssal plain by a factor of 2–3, and show differences in depth structure. At the western boundary, $\theta$ fluctuations are strongest (±0.05–0.12°C) between 2,000 and 4,000 dbar and decrease with increasing pressure. In contrast, increased $\theta$ anomalies (±0.025–0.04°C) in the abyssal region are seen at two
<figure><img src="image_5.png" /><figcaption>**Figure 3.** Interannual anomalies in (a, e) potential temperature ($\theta$), and decomposed into (b,f) heave and (c, g) spice in the western boundary region and abyssal region respectively. The black line shows zero values (d,h) Comparison of SH at 2,000 dbar relative to 5,000 dbar (cm) and Ekman pumping (m s$^{-1}$) in the western boundary region and abyssal region respectively. The sign of Ekman pumping in (d) is reversed to facilitate comparison with SH anomalies.</figcaption></figure>
distinct pressure ranges within 2,000–2,500 dbar and 4,500–5,000 dbar. The contribution of salinity to interannual fluctuations of deep-ocean SH is one order of magnitude smaller than θ and not shown here.

In an attempt to identify potential drivers of isopycnal vertical displacement, the dominant source of SH vari-
ability, the contribution of wind forcing is assessed, and fluctuations in Deep Argo SH at 2,000 dbar are compared
to local Ekman pumping (see Section 2.3; Figures 3d and 3h). Anomalies in SH at the western boundary (std
±1.4 cm) are stronger than Deep Argo error (see Section 2.1) indicative of the robustness of SH variability. Our
results show an evident relationship (R = −0.7) between local Ekman pumping and deep SH anomalies
(Figure 3d). Positive Ekman pumping anomalies lifting isopycnals upward coincide with deep-ocean cooling and
steric contraction. Negative Ekman pumping anomalies pushing isopycnals downward coincide with deep-ocean
warming and steric expansion. In-phase isopycnal heaving and Ekman pumping anomalies suggest that Ekman
pumping plays a significant role in deep SH variations at the western boundary. Smaller SH anomalies over the
abyssal plain (std ±0.2 cm) are consistent with the smaller mean amplitude of the wind stress curl averaged
between 2017 and 2022 (−0.3 × 10⁻⁶ ± 1.2 × 10⁻⁶ m/s) than at the western boundary
(−1.5 × 10⁻⁶ ± 0.8 × 10⁻⁶ m/s). In contrast to the western boundary, anomalies in SH over the abyssal plain are
within Deep Argo error and hence should be interpreted with caution. The reduced vertical displacement cor-
relation with Ekman pumping (R = −0.3; Figure 3h) is consistent with smaller influence of local wind forcing
over the abyssal plain, and may be affected by Deep Argo error due to CTD accuracy. Other forcing mechanisms,
likely related to ocean dynamics driving temperature and salinity variability may further increase discrepancies in
the ocean's isopycnal displacement response (e.g., Small et al., 2020; Tesdal & Abernathey, 2021). An in-depth
analysis of the vertical structure of θ anomalies and drivers of θ variability is not feasible due to the dearth of deep
ocean observations in the subtropical Northwest Atlantic Ocean and limited performance of ocean reanalysis (see
Section 3.3). Here, we explore potentially relevant dynamics supplemental to Ekman pumping. The region
referred to as western boundary in our analysis is located at the edge between the southward flow of the DWBC
and northward recirculation in the Abaco gyre (Hogg & Johns, 1995). There, interannual DWBC transport
variability is affected by westward Rossby wave-like features (Meinen & Garzoli, 2014), southward propagating
cyclonic eddies (Biló & Johns, 2020), and large northward propagating anticyclonic eddies (Biló et al., 2020). The
formation mechanisms of these anticyclonic eddies is still under debate although Biló and Johns's (2020) analysis
identifies intrinsic instabilities of the DWBC, and reflection of long Rossby waves at the western boundary into
short Rossby waves as potential sources. The vertical displacement correlation with Ekman pumping seen in our
analysis suggests that the advection of heat in the DWBC recirculation system may be amplified by local wind
forcing. The comparatively weaker and less variable ocean circulation in the abyssal plain outside of the DWBC
and recirculation system (Biló et al., 2020) is consistent with reduced fluctuations in the deep-ocean temperature
and salinity fields. Further confirmation will be obtained through increased deep ocean sampling and is left for a
future study.

**4. Conclusions**

Full-depth temperature and salinity profiles collected by Deep Argo floats between 2017 and 2022 provide new opportunities to study the interannual variability of steric sea level in two dynamically distinct regions of the subtropical Northwest Atlantic. Our analysis shows interannual SH variations in the deep ocean seven times stronger at the western boundary than over the abyssal plain. Local wind forcing appears to be a driving mechanism shaping this interannual variability only in the deep western boundary region. In both western boundary and abyssal plain regions, steric sea level reflects only part of the total sea surface height interannual variability, with mass contributing ±0.6 cm and ±0.7 cm. These results suggest that at these timescales, ocean mass changes are not insignificant, and both mass and full-depth density changes must be observed to best interpret more abundant sea surface height measurements.

The limited agreement between Deep Argo and GLORYS12 SH emphasizes the need to increase sampling of the deep ocean such that more measurements can be assimilated in ocean reanalysis, but also to realize a closure of the sea level budget. Improving the skill of these ocean reanalysis products will enable more robust evaluation of deep-ocean temperature and salinity fluctuations, and permit attribution of deep-ocean SH variability to specific drivers. The close agreement between Deep Argo SH variations and geodetic steric sea level underscores the scientific value of both data sets, but highlights how a fully implemented 1,200 Deep Argo float array could be used to close the sea level budget and reveal currently unresolved regional variability.
Results from this study can also play a key role in analyses of coastal sea level variability and enable attribution of local sea level change to regional ocean heat content and mass change. Steric sea level changes at depths greater than the continental shelf break can impart a shelf and coastal sea level response realized as a mass redistribution resulting from offshore subsurface ocean density change. Recent analyses of high-resolution ocean model output (Steinberg et al., 2024) show that this mechanism can influence sea level rise in and around the Bahamas in particular. Monitoring density changes over the full water column thus provides an opportunity to identify drivers of coastal sea level change. Continued and new Deep Argo observations will enable the decomposition of coastal sea level change into contributing factors, particularly offshore density and circulation change across depths. In summary, this analysis demonstrates how Deep Argo measurements can be used to better understand regional sea level variability and determine if and where the deep ocean is responsible for the non-closure of the sea level budget.

## Data Availability Statement

The Argo data is collected and made available by the International Argo Program and the national programs that contribute to it (Argo, 2025). GLORYS data is available from the EU Copernicus Marine Service (CMEMS, 2018). ERA5 data is available from the Copernicus Climate Change Service (Hersbach et al., 2023). This work utilized the Gibbs-SeaWater Oceanographic Toolbox (McDougall & Barker, 2011). The bathymetry data is from the ETOPO2 data set by the US National Geophysical Data Center (NOAA National Geophysical Data Center, 2006).

## Acknowledgments

We would like to acknowledge the crew of the RRS James Cook for their work in deploying the Deep Argo floats used in this study, and John Gilson for conducting Deep Argo delayed-mode quality control. NZ received support from the NOAA Global Ocean Monitoring and Observing Program through Award NA20OAR4320278, NSF (OCE-2242742) and Seabed2030 (UNH2042102). WL is supported by the EERIE project (Grant Agreement No 101081383) funded by the European Union and the GREAT project, which is supported by the Centre National d'Etudes Spatiales (CNES) through the Ocean Surface Topography Science Team (OSTST). BM, MA and RF and WL are supported by the ESA Climate Space Programme under the Sea level budget closure project. BM is supported by the CNES TOSCA project for the use of Sentinel 6 data. MA and RF are supported by CNES and ESA in the frame of the MOHEACAN project.

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