# Mesoscale variability in the Western Arabian Sea: dynamical and hydrological description compared to remote-sensing

Léa Criado, Alexandre Barboni, Xavier Carton

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## To cite this version:

Léa Criado, Alexandre Barboni, Xavier Carton. Mesoscale variability in the Western Arabian Sea: dynamical and hydrological description compared to remote-sensing. 2024. hal-04680501

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<table><tr><td>Manuscript Number:</td><td></td></tr><tr><td>Article Type:</td><td>VSI: IIOE-2 Volume 7</td></tr><tr><td>Corresponding Author:</td><td>Alexandre Barboni, Ph.D.<br>Institut de recherche pour le développement Nouvelle-Calédonie<br>FRANCE</td></tr><tr><td>First Author:</td><td>Alexandre Barboni, Ph.D.</td></tr><tr><td rowspan="3">Order of Authors:</td><td>Alexandre Barboni, Ph.D.</td></tr><tr><td>Lea Criado, MSc</td></tr><tr><td>Xavier J Carton, PhD</td></tr><tr><td>Abstract:</td><td>The Arabian Sea remained largely unexplored from the 1990's until the 2010's, and most recent studies with in situ data were focused on climatological and seasonal time scales. Thus, in-situ experiments focusing on mesoscale dynamics in this eddy rich sub-basin, are useful. The PHYSINDIEN campaign in May 2019 collected in-situ measurements of both velocity and hydrology, down to 1100m for the former and mostly to 380m for the latter. Stretching over 3000km in the Northwestern Arabian Sea, between 16 and 25° N, during the spring intermonsoon, it provided an extensive dynamical and hydrological description of 8 mesoscale eddies, 5 anticyclones and 3 cyclones. Two deep cyclonic submesoscale coherent vortices remarkably occured beneath surface anticyclones. Water masses properties show that anticyclones in the Gulf of Oman are associated with lenses of Persian Gulf Waters, while anticyclones further South are shallower lenses formed with Arabian Sea High Salinity Waters. Comparison of in-situ data with the META atlas, a state-of-the-art eddy detection and tracking atlas based on altimetry, reveals that eddy radius is often underestimated. Additionally eddy track is often intermittent due to missing detections. Both hydrology and remote-sensing tracking are however consistent in indicating that anticyclones during the spring intermonsoon along the Southern Omani coast are formed further offshore at the center of the Arabian Sea. These results unveil the wide diversity of surface and subsurface eddying structures in the sparsely explored Arabian Sea, and provide hindsight on the potential bias of their remote detections.</td></tr><tr><td>Suggested Reviewers:</td><td>Lisa Beal, PhD<br>Professor, University of Miami Rosenstiel School of Marine and Atmospheric Science<br>lbeal@miami.edu<br>Expert in in situ data and in the studied region<br><br>Amy Bower, PhD<br>Senior Scientist, Woods Hole Oceanographic Institution<br>abower@whoi.edu<br>Expert in seagoing oceanography and expert in the studied region<br><br>William E. Johns, PhD<br>University of Miami Rosenstiel School of Marine and Atmospheric Science<br>bjohns@miami.edu<br>Dr William E. Johns is a seagoing oceanographer specializing<br>in the use of long-term moored instrumentation to study ocean circulation</td></tr></table>
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Highlights

Mesoscale variability in the Western Arabian Sea : dynamical and
hydrological description compared to remote-sensing

Criado Lea, Barboni Alexandre, Carton Xavier

* Mesoscale structures in the Northwestern Arabian Sea are described from velocities and hydrology

* Cyclonic submesoscale coherent vortices are observed twice beneath surface anticyclones

* Corresponding altimetric detection underestimates eddy radius, and eddy tracking is intermittent
Mesoscale variability in the Western Arabian Sea :
dynamical and hydrological description compared to
remote-sensing

Criado Leaª, Barboni Alexandreª,ᵇ, Carton Xavierª

<sup>a</sup>Laboratoire d'Oceanographie Physique et Spatiale, Technopole
Brest-Iroise, Plouzane, 29280, France

<sup>b</sup>Service Hydrographique et Oceanographique de la Marine, 13 rue du
Chatellier, Brest, 29200, France

Abstract

The Arabian Sea remained largely unexplored from the 1990's until the
2010's, and most recent studies with in situ data were focused on clima-
tological and seasonal time scales. Thus, in-situ experiments focusing on
mesoscale dynamics in this eddy rich sub-basin, are useful. The PHYSIN-
DIEN campaign in May 2019 collected in-situ measurements of both velocity
and hydrology, down to 1100m for the former and mostly to 380m for the
latter. Stretching over 3000km in the Northwestern Arabian Sea, between
16 and 25 °N, during the spring intermonsoon, it provided an extensive dy-
namical and hydrological description of 8 mesoscale eddies, 5 anticyclones
and 3 cyclones. Two deep cyclonic submesoscale coherent vortices remark-
ably occured beneath surface anticyclones. Water masses properties show
that anticyclones in the Gulf of Oman are associated with lenses of Persian
Gulf Waters, while anticyclones further South are shallower lenses formed
with Arabian Sea High Salinity Waters. Comparison of in-situ data with
the META atlas, a state-of-the-art eddy detection and tracking atlas based
on altimetry, reveals that eddy radius is often underestimated. Additionally eddy track is often intermittent due to missing detections. Both hydrology and remote-sensing tracking are however consistent in indicating that anti-cyclones during the spring intermonsoon along the Southern Omani coast are formed further offshore at the center of the Arabian Sea. These results unveil the wide diversity of surface and subsurface eddying structures in the sparsely explored Arabian Sea, and provide hindsight on the potential bias of their remote detections.

*Keywords:* Mesoscale, ADCP, in situ, eddy

# 1. Introduction

The Arabian Sea is encompassed in the Northwestern Indian Ocean between 26 °N and the Equator. It has a particular geographical and climatological situation, being landlocked between the Arabian peninsula and the Indian subcontinent (Tomczak and Godfrey, 1994). Temperature contrasts between landmasses and the ocean drive an intense meridional atmospheric circulation, the monsoon, greatly impacting the Arabian Sea circulation with a pronounced seasonal cycle (Luther and O’Brien, 1985). Seasonal wind patterns drive intense upwelling (Fischer et al., 2002), with two phytoplankton blooms per year (Brock et al., 1991), high biological production and important fishing activity (Currie et al., 1973). Landlocked location together with high biological productivity and high sediment input from the Indus river in the North favors the formation of a strong and thick Oxygen minimum zone (Gupta and Naqvi, 1984), one of the most intense in the global ocean (Morrison et al., 1999).
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Despite its unique characteristics, the Arabian Sea remain poorly studied, while it also faces multiple new threats notably due to rising temperature. Marine heat waves were recently observed in the Gulf of Oman in the North-western Arabian Sea. Harmful algal blooms were observed along the Omani coast with increased frequency (Al-Azri et al., 2015). In the past two decades marine heat waves also stroke the Arabian Sea with increasing frequency (Chatterjee et al., 2022; Kashkooli et al., 2022) and Arabian coast faced the new occurrence of tropical cyclones causing coastal floods (Roy Chowdhury et al., 2020; Terry et al., 2022). In spite of these emerging challenges and intense maritime traffic crossing the basin, in situ data are greatly lacking. After the JGOFS (Joint Ocean Global Flux Study) in the early 1990's, rise of geopolitical tensions led to an extreme scarcity of in situ measurements. This observational lack is problematic because ongoing changes are difficult to monitor, such as the oxygen depletion (Queste et al., 2018). Processes driving changes in the Arabian Sea, with interactions between changes ocean circulation, biology and warming atmosphere, remain to be understood (Al-Azri et al., 2010).

This lack of observation is even more marked concerning the mesoscale activity. Past studies provided a good description of the climatological and seasonal scale driven with monsoon winds. The winter monsoon (usually considered as December to February) blows southwards, while the summer monsoon more intense blows northeastwards from the Somali coast (Pandey et al., 2016). The summer monsoon then drives a coastal upwelling along
the Omani and Somali coast (Kushwaha et al., 2022). Persian Gulf and Red Sea waters (respectively PGW and RSW) outflows were also extensively studied (Bower and Furey, 2012), notably by previous PHYSINDIEN cruises (L'Hégaret et al., 2016). These outflows of dense warm and saline waters have a seasonal signal and can be traced into the whole Arabian Sea (L'Hégaret et al., 2021). They notably interact with eddies which impact their dilution and propagation across the basin (Bower and Furey, 2012; Morvan et al., 2020). Along the Equator, Rossby waves propagates westwards along the southern side of the Arabian Sea, then as Kelvin waves along the Somali coast and accumulate in the Great Whirl anticyclonic structure in summer (Leetmaa et al., 1982; Beal and Donohue, 2013; Vic et al., 2014).

In the rest of the basin, away from the Equator and mostly in its Western part, the Arabian Sea hosts an intense mesoscale activity. This eddy-rich activity is dominant in the intermonsoon period because less structured by regional wind patterns (Tomczak and Godfrey, 1994). The Rossby deformation ranges from 100km around 10 °N to about 40km close in the Gulf of Oman (Chelton et al., 1998). Due to this meridional gradient of Rossby radius, β-drift is strong and mesoscale structures drift westwards (Chelton et al., 2011). Mesoscale activity was already found to be crucial in bringing nutrient supply to the center of the basin (Resplandy et al., 2011; Smitha et al., 2022).

However without further in situ observation, progress in understanding and describing the dynamical structures in the Arabian Sea is difficult, in
particular in the intermonsoon period with less stationary patterns. Over
the past 15 years, ARGO profiling floats helped to investigate this knowl-
edge gap. ARGO is a program coordinating the deployment of autonomous
vertical profilers in the global ocean. Since the first ARGO deployment in
2000 in the Arabian Sea, enough vertical profiles were obtained to provide a
mean description of the mesoscale signature over the mixed layer by Trott
et al. (2019) and their vertical structure eddies by de Marez et al. (2019).
They were however limited to a composite mean structure, masking eddy di-
versity. De Marez et al. (2020) revealed the occurrence of cyclonic subsurface
coherent vortex (SCV), a deep submesoscale structure completely different
from mesoscale eddies in the upper layers. In the past decade other obser-
vation efforts were also done in the Gulf of Aden with gliders. Font et al.
(2024) provides a precise dynamical description of meso and submesoscale
structures encountered along the Northern Omani shelf, but is geographi-
cally limited.

Eddy being defined as swirling rotating structure, their first impact is
on ocean velocities. Velocities measurements from VMADCP remain the
ground truth to observe eddies. For structures reaching size of the Rossby
deformation radius, the flow can be balanced by pressure gradient, giving also
a signature by tilting isopycnals. The objective of the PHYSINDIEN 2019
campaign was not only to obtain new in-depth measurements of water masses
in the region, but also to provide joint velocity and hydrological measure-
ments at meso and submesoscale, near fronts and eddies. The co-existence
of mesoscale and submesoscale features near the surface and at depth is the
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first point shown by our paper.

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Eddies can also be observed using remote-sensing. Swirling structures form filaments delineating eddies, visible in sea surface temperature (SST) images. At the mesoscale, density anomalies are signing in sea surface height (SSH) adjustment, which can be used to detect them (Fang and Morrow, 2003). Numerous eddy detection and tracking algorithms were developed in past two decades (Chaigneau et al., 2008; Chelton et al., 2011; Mason et al., 2014; Le Vu et al., 2018), together with improved satellite altimetry (Fu et al., 2010). Various observation datasets were provided since the global eddy dataset from Chelton et al. (2011) based on Sea Level Anomaly (SLA). This dataset was continued into the *Mesoscale Eddy Tracking Atlas* (META) (Pegliasco et al., 2022), currently available at global scale, daily, based on Absolute Dynamic Topography (ADT) improving eddy detections in land-locked basins (Pegliasco et al., 2021) and also in near-real time.

This eddy observation atlases enables us to identify eddy formation, lifetime, track, and disappearance. They are then very useful to investigate mesoscale activity when in situ observation are not available. In the Arabian Sea, progress was done in understanding mesoscale impact on SST and chlorophyll thanks to eddy detections algorithms (Liu and Li, 2023).

However, these remote-sensing eddy products were not tested in a statistical way to in situ data but only on specific campaign case study. Another point investigated here is whether, given an in-situ dataset sampling mul-
tiple mesoscale structures, can remote-sensing eddy detection efficiency be
estimated in comparison with this dataset ?

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Given the scarcity of observations in the region, observational effort should
be increased. We present here in situ data collected during the PHYSIN-
DIEN 2019 experiment in the Western Arabian Sea, spanning over 3000km
of transect with joint velocity and hydrology measurements. This oceano-
graphic campaign took place in May 2019 during the spring intermonsoon.
We then aim to provide first a statistical description of the eddy diversity in
this under-sampled basin, giving both dynamics and water masses character-
istics. Secondly, we will compare in situ measurements with eddy detections
from META to detail the accuracy of remote-sensing in the Arabian Sea.
Finally, physical processes driving mesoscale stability and impact in terms of
water masses content are discussed.

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## 2. Data and methods

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2.1. *In situ measurements from PHYSINDIEN 2019 campaign*
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The PHYSINDIEN 2019 oceanographic campaign was carried out in May
2019; it provided joint measurements of hydrological characteristics and ve-
locities at depth, during the spring intermonsoon. This period is charac-
terized by weaker winds than the monsoon period, with more heteroge-
neous wind directions. This influences surface dynamics by creating sea-level
anomalies - upwellings/downwellings, eddies, meanders - which then domi-
nate horizontal surface and subsurface circulation offshore (L'Hégaret et al.,
2016). A total of 7 transects were achieved, divided into three legs, covering
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<figure><img src="image_4.png" /><figcaption>Figure 1: Northwestern Arabian Sea bathymetric map with ETOPO1 data, overlaid with PHYSINDIEN 2019 transects. Transects are in chronological order.</figcaption></figure>

over 3000km of subsurface ocean properties screening. The first leg from 2019-05-04 to 2019-05-12 covered the Southern Omani coast up to 400km offshore and lay between 54 and 64°E, and 16 to 22°N. To compare legs with similar duration and length hereafter, the first leg is subdivided into leg 1A (covering transects 1-2 from 2019-05-04 to 2019-05-08) and leg 1B (transects 3-4 from 2019-05-09 to 2019-05-12). After a stopover in Muscat, the second leg covers transects 5 to 7 from 2024-05-21 to 2024-05-25. It ranges from the inner Gulf of Oman to the Northwestern Arabian Sea, between 21 and 25°N (Figure 1).

Velocity data were recorded by a Vessel-Mounted Acoustic Doppler Current Profiler (VMADCP) RDI Teledyne Ocean Surveyor 38 kHz, providing
continuous measurements ranging from 40 to 1150m deep with 15m vertical
grid step. Data were averaged per 2 minutes bins, giving a horizontal reso-
lution around 500m while the ship cruised at about 8 knots.

Hydrology was measured on the way with a towed undulating instrument,
the SeaSoar, from Chelsea Technology Group (Allen et al., 2002). Except for
short parts of the transects 2, 5 and 6, hydrology was measured jointly with
VMADCP, cumulating about 2800km. The SeaSoar "flies" while being towed
at about 8 knots, modifying its attitude to range underwater between 10 and
380m deep. Temperature and practical salinity are measured with a pumped
Sea Bird Electronic SBE21. With ascending and descending speeds both on
the order of 1 m.s⁻¹, vertical resolution with the SeaSoar is about 1 meter,
similar to a CTD cast. To remedy the small depth range of the SeaSoar,
additional en-route measurements were performed along part of transect 1
with a RapidCast, a free-fall pumpless profiler measuring temperature and
salinity down to 1100m. RapidCast vertical resolution was on the order of
10m. However the free-fall descending phase induced some uncertainty on
the vertical position, and the SeaSoar profiles remained more precise. Note
that on most sections, the resolution of hydrological soundings with both in-
struments was on the order of 1 km (1 NM for a downward-upward SeaSoar
cycle). Potential density σ referenced to 0 dbar was then computed using the
TEOS10 equation (McDougall et al., 2013) implemented in the gsw Python
package (https://teos-10.github.io/GSW-Python/).

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## 2.2. Dynamical parameters

### Geostrophic and ageostrophic velocities vertical gradients

From the hydrology using buoyancy, the thermal wind equilibrium (Eq.1) leads to the vertical gradient of the geostrophic velocity $V_G$. $V_G$ can only balance density gradient at the mesoscale, which means at scale of the deformation radius, about 70km in the studied region. $\sigma$ smoothed with Gaussian window of 20km only on the horizontal, noted $\bar{\sigma}$, is used in the computation with $f = 5 \times 10^{-5} s^{-1}$ Coriolis parameter at 20°N, density scale $\rho_0 = 1026$ kg.m$^{-3}$ and $g = 9.81 m.s^{-1}$. $V_G$ is a scalar, as only buoyancy gradient along the transect ($x$ direction) can be computed:

$$ \partial_z V_G = -\frac{g}{f\rho_0} \partial_x \bar{\sigma} \qquad (1) $$

Recovering the full geostrophic speed requires vertical integration in Eq.1. Hydrological properties being measured only down to 380m, this would require to choose 380m as the reference level where horizontal pressure gradients become negligible. Such an assumption is inaccurate, in particular in this region where PGW forms density gradients between 200 and 500m (L'Hégaret et al., 2021). Therefore, we chose to compare the vertical gradient of geostrophic velocity (thus computed), with the vertical gradient of ageostrophic velocity $V_A$, using the vertical gradient of across-transect velocity $dV_y/dz$ measured by the VMADCP:

$$ \partial_z V_A = \partial_z V_y - \partial_z V_G \qquad (2) $$
196 Potential vorticity

To investigate the possible instabilities of this oceanic flow, Ertel potential vorticity was used. Calling $x$ the direction of the ship transect, any derivative in the $y$ direction remains unknown. This problem is circumvented by neglecting any such derivative when computing potential vorticity. The result is called the *Poor Man's Vorticity (PMV)*:

$$ 
\begin{align} 
PMV &= (\partial_x v + f) \times \partial_z b - \partial_z v \times \partial_x b \tag{3} \\ 
PMV' &= PMV - \overline{PMV}. \nonumber 
\end{align} 
$$

The PMV anomalies ($PMV'$) are computed by subtracting the mean $\overline{PMV}$; this latter is a horizontal average of PMV (at each depth) per transect. A negative PMV indicates that the flow is symmetrically unstable. Changes in sign of $PMV'$ indicate whether the flow is sensitive to barotropic or baroclinic instability. The flow is barotropically unstable if the $PMV'$ gradient changes sign horizontally, and baroclinically unstable if it changes sign vertically (Charney and Stern, 1962).

209 Dimensionless numbers

Three dimensionless numbers are used to characterize the flow, with $U$ the velocity scale, $L$ and $H$ the characteristic horizontal and vertical length scales, $N^2 = -\frac{g}{\rho_0} \frac{\partial \rho}{\partial z}$ the squared Brunt-Väisälä frequency, and $f$ the Coriolis parameter:

$$ Ro = \frac{U}{fL} \tag{4} $$

$$ Ri = \frac{N^2}{\frac{\partial u^2}{\partial z} + \frac{\partial v^2}{\partial z}} \tag{5} $$
$$Bu = \left( \frac{NH}{fL} \right)^2 \qquad (6)$$

The Rossby number ($Ro$) compares the advection of a rotating fluid flow to the impact of the Coriolis force. The geostrophic approximation is valid for $Ro \ll 1$. The Richardson number ($Ri$) indicates the stability of the flow with respect to vertical shear. When values are below the critical threshold of 1/4, this means that the conditions for observing Kelvin-Helmholtz instabilities are met (Kelvin, 1890). The local Burger number ($Bu$) compares the impact of stratification phenomena with the effects of fluid rotation at the scale of the structures observed. It is related to the baroclinic instability of parallel jets and of vortices (Carton, 2001).

$H$ and $L$ are obtained by applying a Fourier transform to the Seasonal temperature transects, separately on the horizontal and the vertical axis. Horizontal wave numbers corresponding to 10 - 500km for $L$, and 1 and 1000m for $H$ were tested. $L$ (respectively $H$) values retained correspond to the peak wave numbers in the horizontal (vertical) Fourier transform averaged over vertical levels (horizontal columns) per transect. $H$ and $L$ are summarized in Table 1.

## 2.3. Remote-sensing eddy detections and tracking

Remote sensing eddy detections are retrieved from the Mesoscale Eddy Trajectories Atlas (META) 3.2 in delayed-time (DT) mode with all altimetric satellite data. META3.2DT was produced and distributed by Archiving, Validation and Interpretation of Satellite Oceanography (AVISO) with support
<table><caption>Table 1: Horizontal and vertical scales associated for each transect in the PHYSINDIEN cruise (see map in Fig.1).</caption><thead><tr><th>Leg</th><th colspan="2">Leg 1A</th><th colspan="2">Leg 1B</th><th colspan="3">Leg 2</th></tr><tr><th>Transect</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th></tr></thead><tbody><tr><th>L (km)</th><td>45</td><td>73</td><td>112</td><td>38</td><td>30</td><td>66</td><td>55</td></tr><tr><th>H (m)</th><td>62</td><td>70</td><td>71</td><td>72</td><td>51</td><td>68</td><td>72</td></tr></tbody></table>

from Centre National d'Etudes Spatiales (CNES). Mesoscale eddy observations in META are detected through the PyEddyTracker algorithm (Mason et al., 2014), which primarily uses SSH closed contours for detections. Eddy tracking from one observation time step to another is performed by selecting the next observation with maximal contour overlap (Pegliasco et al., 2022). Input data in META3.2DT is delayed-time daily global 1/4° resolution ADT, currently available from 1993 to 2022. Compared to META3.1exp detailed in Pegliasco et al. (2022), META3.2DT only differs by the use of improved DT2021 altimetry instead of DT2018, with mostly nearshore improvements (Sánchez-Román et al., 2023).

Mesoscale eddies exhibit regional patterns in the Northwestern Arabian Sea, which are retrieved in META data. Eddies are mostly formed on the Eastern Arabian Sea coast, and drift westwards due to the gradient of planetary vorticity (β-drift, see in Fig.2a), consistent with the global observation from Chelton et al. (2011). Mesoscale eddies, both cyclones and anticyclones, then stack on the Western Arabian Sea coast, and slowly drift southwestwards into the Gulf of Aden (Bower and Furey, 2012; Morvan et al., 2020). Higher
density of mesoscale structures is notably visible in the Western Arabian Sea on META occurrence in Fig.2b for the spring intermonsoon, at the same season and location as in PHYSINDIEN 2019.

META provides for each daily eddy observation two closed contours : the speed contour corresponds to ADT maximal gradient and hence maximal geostrophic speed, considered as the eddy center border. The *effective* contour corresponds to the last closed SSH contours around the eddy, delimiting its footprint. Similarly to Barboni et al. (2023), collocation between in situ and remote-sensing data is performed with an eddy lag of ±2 days. Eddy contours up to 2 days before and after are used, in situ measurement location being assumed fixed, to investigate the temporal variability of remote-sensing eddy contours (see illustration in Fig.2 in Barboni et al. (2023)). This collocation at ±2 days is reported hereafter in the upper panels of Fig.3-5. If a position falls in between the *effective* and *speed* contours of an eddy, the collocation is labeled as "ambiguous" because it is not inside the detected eddy center.

### 3. Meso- and submesoscale structures observed during PHYSINDIEN 2019 campaign

The PHYSINDIEN 2019 campaign provided new in-depth measurements, but also joint velocity and hydrological measurements over 2800km horizontally at 1 km resolution, enabling to distinguish meso- and submesoscale features. The present section shows in-depth transects of the PHYSINDIEN
<figure><img src="image_5.png" /></figure>

Figure 2: META Atlas data from 1993 to 2022 : (a) anticyclones (respectively cyclones) tracks are shown with a blue (respectively red) line with disappearance location as a black square ; for readability are shown only tracks living longer than 200 days. (b) Occurrence for anticyclonic detections in April and May only, expressed as the time fraction spent by each pixel within the maximal speed contour.

cruise, presented in Fig.3-5, almost in South to North order, following a dynamical and then a hydrological description. Corresponding remote-sensing altimetry and META detections are shown in Fig.8 and all characterized structures are listed in appendix Table.2, distinguishing three categories : anticyclones "AC", cyclones "C" and *Submesoscale Coherent Vortices* (SCV) noted "SC".

## 3.1. Dynamical description

Based on their kinematic definition, eddies should be first described using velocity measurements when available (Nencioli et al., 2010). Figures 3-5 show VMADCP measurements in their lower panel, and we delimit the
structures by using the 30 cm.s⁻¹ magnitude isolines below 100m. This depth ensures to be below the mixed layer, where transient wind induced velocities could mask the mesoscale velocities. Corresponding labels are added in Fig.3-5, and horizontal width and vertical span are reported in appendix Table.2, rounded to 50m.

Leg 1A starts in transect 1 by crossing an anticyclone (AC1), reaching maximal speed about 50 cm.s⁻¹ but with velocities confined in the upper 150m (Fig.3c). Note that because this transect makes a U-turn, it only crosses the anticyclone northern branch and then we do not see the reversal of the meridional speed (see also the map in Fig.8a later). AC1 is crossed from km 50 to 330 in transect 1. A remarkable feature in this transect is the occurrence of subsurface submesoscale cyclonic vortex (SC1) between 350 and 900m deep, and spanning km 140 to 210 with maximal speed exceeding 40 cm.s⁻¹. The description of this structure was detailed in (De Marez et al., 2020). Its radius of around 35 km is significantly below the deformation radius, which is about 70 km at this latitude (Chelton et al., 1998), clearly characterizing this structure as submesoscale.

Transect 2 resumes the cruise from the interior of AC1 (ADT map in Fig.8a), and surface velocities are intense until km 450 of the transect, marking the northeastern edge of AC1 (Fig.3e, second occurrence of AC1 noted as *AC1′* in Table.2). Then the transect enters a cyclonic gyre (C1), clearly visible in ADT (Fig.8a) but more complex from in situ velocity measurements. It seems that the intense jet between km 430 and 450 of the transect
is simultaneously the edge of AC1 and the southwestern edge of C1. This interpretation is confirmed because isopycnals are already very shallow beyond km 450, signing a cyclonic gyre, and because the continued transect reaches a northward jet between km 510 and 540 when making a U-turn, then marking the northern edge of this cyclone. Velocity magnitude at km 530 is weak, indicating that the ship likely did not cross the northern edge of C1 and stays inside until km 720, with corresponding velocities restricted to the upper 150m. The eastern edge of C1 is more marked with a density front and velocities reaching $40 \text{ cm.s}^{-1}$. This uncertainty in C1 delimitation is likely due some unsteadiness of this large cyclonic gyre, as collocation with META atlas varies a lot in the 2 days before and after the transect (Fig.3d). collocation with remote-sensing is further developed in section 3.3 later.

Leg 1B is constituted by the transects 3 and 4, respectively 870 and 270km long. At about km 900 in distance, transect 3 encounters a first structure with a single jet about $30 \text{ cm.s}^{-1}$ (Fig.4c), coincident with isopycnal thinning (Fig.4b). From the ADT in Fig.8b, it seems that this eddy is extreme northern tip of a large cyclone, noted C2. However the transect makes a U-turn and did not investigate this structure further. The cruise plan was to sample it, but as collocation with META atlas showed, this structure evolved significantly in the few days before (Fig.4a). Despite marked changed in salinity (which are analyzed later) when sailing towards the Arabian shelf, no significant dynamical structure is encountered until km 1040-1090. A weak jet about $30 \text{ cm.s}^{-1}$ is measured there, but without obvious related structure, in particular no density signature, then called J1. Later at about km 1140 in
distance the transect enters a wide anticyclonic gyre, noted AC2. Its south-western edge being marked by the shallow northwards jet between km 1140 and 1200. Its northeastern edge is crossed later by the jet between km 1510 and 1580. Similarly to AC1, velocity (Fig.4c) and density (Fig.4b) signatures of AC2 are confined in the upper 150m. Anticyclone AC2 is also very large, 440km of diameter, the transect being almost straight here, giving a very small Burger number, but surprisingly not well detected by altimetry (Fig.4a). Last on this transect and similarly to the first one, a second cyclonic SCV is also observed below AC2, noted SC2, between km 1400 and 1460. Its maximal magnitude is relatively low but its depth range can be approximated to about 400 to 800m.

At the beginning of transect 4, a strong shallow northward jet is observed, linked with an isopycnal tilting and salinity structure (Fig.4f). From the META eddies map, this could be due to the proximity of an anticyclonic eddy further east, not sampled. This structure is then noted J2. While closer to the shelf, a cyclonic structure (C3) is measured between distance km 1750 and 1880, with swirling structure down to 600m deep. Its eastern edge is difficult to delimit because the shallow velocity feature between km 1750-1800 might be independent. This uncertainty is also reflected in variability of the META collocation (Fig.4e).

After a stopover in Muscat, leg 2 covers the Gulf of Oman West to East, almost from the Strait of Hormuz to the open Northern Arabian Sea (see map in Fig.1). In transect 5 on the western side, the first structure encountered
is the shallow anticyclone AC3 from distance km 1880 to 1980 (delimitation using 20 cm.s⁻¹ isoline). Despite being clearly visible in the density field as a thick layer between 25.3 and 25.0 kg.m⁻³ isopycnals (Fig.5b), velocity signature is weak, 25 cm.s⁻¹ at most. Then transect 6 surveys a large eddy, noted AC4, from km 2160 to 2400 (the western edge being also sampled at the end of transect 5). AC4 occupies the position of the Ras Al-Hadd anticyclone, which is also confirmed by velocities reaching 70 cm.s⁻¹. After a U-turn at km 2480, a shallow jet is surveyed in the upper 150m but could not be linked to any structure in altimetry (Fig.5g). The isopycnal thinning (km 2430-2520, Fig.5f) should indicate a cyclone, noted C4, but the identification is difficult because the transect did not continue straight. On transect 7, a shallow cyclone is clearly identified between km 2660 - 2780, noted C3' (Fig.5k). Given its position, it should correspond to a second section of C3 on its northern side while the cyclone was distorted further North (see Fig.8c). However associated tracks in META changed from 755737 to 774876, and contour shapes also evolved in 12 days. Both C3 and C3' have velocities reaching 20 cm.s⁻¹ at 600m, confirming they might belong to the same structure. Last, the edge of a new anticyclone is visible at the end of the cruise between km 2900-3010, as confirmed by thicker light layers from the Seasoar (Fig.5j). The altimetry map (Fig.8c) suggests this structure is very likely an anticyclone identified by META (track 730581) slightly further North but which size was underestimated. A last SCV, slower than the other two, was surveyed in the Gulf of Oman below C3' from km 2650 to 2670 and centered around 500m deep.

390
<figure><img src="image_6.png" /><figcaption>Figure 3: In-depth transects 1-2 during leg 1A with associated META collocation. (a) META collocation at ±2 days for transect 1, a black arrow reminds time evolution. (b) Vertical section 0-400m of practical salinity from the SeaSoar, overlaid by isopycnals as thin black lines with 0.3 kg.m⁻³ intervals. (c) Vertical section of meridional speed (in cm/s) from the VMADCP, overlaid by speed magnitude contours as thin black line with 10 cm/s intervals. (d) Heading of the ship. (e-h) : same as (a-d) for transect 2.</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Figure 4: Same as Fig.3 for transects 3-4 during leg 1B.</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>Figure 5: Same as Fig.3 for transects 5-7 during leg 2.</figcaption></figure>
3.2. *Hydrological description*

391 Hydrology measured by the SeaSoar can confirm the structure identified
392 just above, in particular by inspecting the isotherms, isohalines, or even bet-
393 ter the isopycnals. Secondly, they can be used to plot T-S diagrams, and
394 thus determine which water masses have been sampled. A RapidCast was
395 also deployed in the same area as transect 1 to perform a second, deeper
396 section on the SC1 lens, enabling analysis of its hydrological characteristics.
397 Appendix Table.2 containing the rest of the dynamic characteristics and hy-
398 drological values is provided.
399

400
401 The main water masses present are ASHSW (Arabian Sea High Salinity Water), IOCW (Indian Ocean Central Water), IODW (Indian Ocean Deep Water), and occasionally PGW (Persian Gulf Water) and RSW (Red Sea Water). Located in the surface layer between 0 and 100m, ASHSW has a temperature between 25 and 28°C and a salinity between 35.4 and 36.6 PSU.
402
403 IOCW is found in the subsurface layer, and is characterized by a temperature varying between 12 and 17°C and a salinity ranging from 34.8 to 35.6 PSU.
404
405
406 IOCW is found in the subsurface layer, and is characterized by a tempera-
407
408
409
410 PGW, it stabilizes at a depth between 200 and 400m, depending on its di-
411 lution - and therefore its distance from the Persian Gulf - at a temperature
412 of 14 to 18°C and a salinity between 35.3 and 36.4 PSU. Finally, the RSW is
413 found between 500 and 800m down, with a temperature between 9 and 14°C
414
415 and a salinity between 35.0 and 36.2 PSU (Kumar et al., 1999). During
the winter monsoon season, north-easterly winds tend to cool surface waters,
particularly north of the Arabian basin. Coupled with high salinity due to
the presence of saltier water masses from the Persian Gulf, a new water mass
can form and be observed until the spring intermonsoon. The latter only
has intermediate characteristics : temperature ranging between 20 and 24°C,
and salinity between 36,0 and 36,5 PSU (Shetye et al., 1994).

For the transect 1 in leg 1A, the salinity section (Figure 3b) shows a
sinking of the surface isolines over the first 160km as it moves away from the
coast and into AC1, then it rises around 100m vertically and from km 160
to 320 as the transect moves towards the coast, before stabilizing and going
back down at the end of the transect, oriented along the coastline. A pinch
of isotherms and isohalines centered on the 13°C isotherm (Figure 6b) and on
the 27.1 kg.m⁻³ isopycnal at around 600m depth is also recorded by Rapid-
Cast. In addition to the warm, salty surface waters - temperature above
27°C and salinity above 35.4 PSU, typical of ASHSW - saltier (35.7 PSU)
and colder (11.7°C) filaments in the vicinity of SC1 are observed. Stabilized
at around 600m deep, their characteristics correspond to RSW more or less
diluted with IOCW as the RSW moves eastwards in the basin (Tomczak and
Godfrey, 1994). The deep water advected to the surface at the center of the
lens has a temperature of no more than 12°C and a salinity of less than 35.5
PSU, so it certainly corresponds to IODW.

The end of leg 1A corresponding to transect 2 shows a subsurface isopycnals and isohalines rise between km 360 and 460 of around 100m (Figure 3f) due to the presence of AC1. They then remain close to the surface -
<figure><img src="image_9.png" /><figcaption>Figure 6: Vertical section of temperature measured by RapidCast at SC1.</figcaption></figure>

to a depth of around 100m - for almost 200km where C1 is located, before dropping back 50 to 100m at the end of the section. Temperature gradients, and above all salinity gradients, reveal the upwelling of deep water around anticyclonic regions (AC1) and in the center of cyclonic zones (C1), where salinity below 35.7 PSU is observed.

Transect 3 (Figure 4b) from leg 1B records a highly variable signal from km 750 to 1100 due to the changing orientation of the vessel and the frontal regime of the area. Isotherms and isohalines curve alternately downwards and then upwards, before curving downwards for the rest of the transect, i.e. almost 400km, with isopycnals dropping between 50 and 75m at AC2. As for transect 4, it corresponds to the crossing of a strong current J2 and a cyclonic region (C3), with a thinning then bulging of the isopycnals between
23.5 and 24.5 kg.m⁻³ in the first 50m of depth - with comparable thermocline dynamics - and very little noisy and relatively flat subsurface isopycnals up to km 1850. However, a steep rise of 50m of isohalines is observed in the subsurface between km 1850 and 1900, corresponding to the right side of C3 (Figure 4f). On these four transects, inclined gradients in temperature and salinity between 150 and 350m depth can be observed, particularly at the margins of anticyclonic eddies such as AC2 and at the center of cyclones.

At the beginning of leg 2, the temperature section of the transect 5 is the most telling. Surface isotherms between 24 and 28°C are grouped together in the first 50m of depth, while 18 to 22°C isotherms curve sharply downwards for almost 300m at AC3. A 200m rise in the 20 and 22°C isotherms was recorded at about km 2000 in distance, i.e. at the boundary between AC3 and AC4, the latter being particularly intense with a surface velocity averaging 58 cm.s⁻¹. The same pattern can be observed with isohalines (Figure 5b). The descent of the isohalines over km 2100 corresponds to the upwelling of a warmer, saltier mass - temperature 20 to 22°C and salinity over 37.0 PSU - at the margin of the frontal zone between AC3 and AC4, then dragged along by the latter. Transect 6 (Figure 5f) is partly unusable, as the SeaSoar did not operate between km 2200 and 2350, a part corresponding mainly to AC4. However, the salinity isolines show an ascent and then a plunge of around 50m from km 2400 to 2550 on the edges and center of C4 respectively. If the surrounding water mass called ASHSW has a salinity equal to or greater than 36.4 PSU, another water mass - stabilized at a depth of around 150m and with a salinity of less than 36.3 PSU - tends to wrap itself around the eddy
in the form of filaments. Another water mass, the PGW, can also be seen
on the section between 150 and 300m depth to the right of the blank area in
the form of patches. As for transect 7 (Figure 5j), it successively crosses the
edge of C5 and AC5 signed by isopycnal bulges, respectively upwards and
downwards, of both 50m on the vertical and 25km on the horizontal.

As seen above, five water masses are found along the transects. ASHSW
and IOCW are the two most frequently encountered waters, while RSW and
IODW were sampled only on transect 1 due to the presence of RapidCast
and SC1, and PGW is found mainly on the transects of leg 2 located in the
Gulf of Oman. A few surface points also seem to indicate the presence of less
salty surface inlets, either due to the presence of rivers or traces of coastal
upwellings. Similarly, some values stand out from the general structure,
with a density anomaly between 24 and 26 kg.m⁻³ (Figure 5f). These could
correspond to a mixing of ASHSW and PGW (and potentially IOCW too)
induced by winter monsoon winds, with the resulting water mass maintained
until spring (Shetye et al., 1994). Overall, the shape described by the diagram
corresponds to that observed with ARGO data from the same area between
2002 and 2014 (L'Hégaret et al., 2015).

3.3. collocation between in situ and remote-sensing measurements

Remote-sensing altimetry already helped identifying dynamical structures
in section 3.1. Beyond SSH mapping, the META atlas provides automated
and assumed objective eddy detections. The upper panels in Fig.3-5 shows
collocation with META detection with an eddy lag of ± 2 days (collocation
with eddy detections up to 2 days prior or after, cast positions being assumed
<figure><img src="image_10.png" /></figure>

Figure 7: T-S diagrams of all transects in situ in blue with the different characteristic water masses of the study area. Few eddies profiles are shown as examples with the same color code as in Figure 1.

fixed).

As a first indication, one can notice that almost all surface-intensified structures can be linked to META tracks - except for C4 - and reminded in Table 3. However this correspondence between remote-sensing detections and in situ data suffer some uncertainties. As previously detailed, several collocated contours actually disappeared or varied significantly few days before sampling by the ship. Particularly illustrative cases are C2 and C3, for
which the track did not disappear, but the eddy contours quickly changed from one day to another. Change in contour size is also obvious for C1 (track 767574 in Fig.8a) and the in situ measurement do not allow to clearly pinpoint the eddy border, despite the structure being large. Over all mesoscale structures described in this study, anticyclones tend to be more stable as opposed to cyclones, letting the case of AC2 for discussion shortly after. This stability is illustrated in particular in varying contour persistence in Fig.8. It was reported in the Mediterranean Sea that cyclonic detections are less accurate, and eddy detection algorithms tend to smooth in a single cyclonic gyre an ensemble of smaller structures (Stegner et al., 2021). However the Mediterranean Sea is characterized by a very small deformation radius and a high cyclone anti-cyclone asymmetry (Mkhinini et al., 2014). The Arabian Sea is on the opposite a region where the deformation radius is large, from 40 to 100km closer to the Equator (Chelton et al., 1998), hence mesoscale is expected to be accurately resolved with 1/4° altimetry products. An interesting result here is that despite larger structures, remotely detected cyclones seem to be less accurate.

A second comment regarding remote-sensing accuracy is that eddy extent is underestimated in almost all cases. The eddy periphery lies between the border of the eddy core and the edge of the eddy. The first one is often approximated by the maximal speed contour, and the latter by the last closed contour (called *effective* contour in META). In practice due to altimetric error, the last closed SSH contour is very often stuck to, if not confounded with, the maximal speed contour and the eddy periphery can be squeezed by
altimetry (Le Vu et al., 2018). Examples are obvious when comparing eddy width in VMADCP transect versus narrower META collocation in the case of AC1, AC3, AC5 (where from altimetry only the ship did not cross the eddy) and more surprisingly AC4 despite its intensity. Bias in eddy radius was already shown by Souza et al. (2011) for methods based on SSH derivative such as Okubo-Weiss : due to errors in altimetry, radius is underestimated. Following Souza et al. (2011), geometric methods such as the PyEddyTracker algorithm in META are expected to provide better results, but this study was based only on remote-sensing data. To our knowledge we document in the present study for the first time that eddy detection algorithm underestimate the radius, using in situ velocity data, and aiming some statistical redundancy over 8 mesoscale structures.

AC2 deserves additional comment, its collocation being missed by META unlike all other anticyclones. An anticyclonic track (724832) was present until few days before leg 1B (Fig.8a), but disappeared from 2024-05-04 to 2024-05-13, when an anticyclonic contour appeared again but associated with a new track (730099). Obviously, a 440km wide anticyclone associated with isopycnal tilting down to 300m (Fig.4b) can not disappear within a week, then AC2 can be linked to the previous track. The change of track seems to be a classical example of the "missing eddy" problem (Penven et al., 2005). Due to errors in altimetric products, SSH contours may be erroneous and not closed for a given period of time, leading to spurious new eddies. In the case of AC2, this disappearance is surprising, as isopycnal tilting is quite pronounced in the upper 300m, and significant SSH anomaly (see Table .3).
An explanation could be simply eddy contour become too large and do not meet the size limit in META (Pegliasco et al., 2022).

Eddy detection algorithms also enable to track eddy detections in time, and then look back at formation location. Fig.14 shows the backwards tracks associated with observed eddies during PHYSINDIEN 2019, the first appearance being highlighted by a white dot. As expected, most eddies traveled westwards due to the β-drift or were channeled southwestwards by the Arabian coast. Eddy life time (age at the time they were observed, see Table .3) and reveals that both cyclones and anticyclones are relatively young. This tracking is consistent with hydrology, indicating that anticyclones are formed of ASHSW, a type of water mass formed in the center of the Arabian Sea in winter (Kumar and Prasad, 1996). Recent research actually showed that anticyclones associated with warmer surface temperature can increase this process (Thoppil, 2024). Water masses inside eddies in the intermonsoon are then clearly formed at the center of the basin, and are not coming from further East from the Indian coast, as opposed to other long-lived eddy trajectories (Fig.2).

However, as discussed above in the case AC2, some detections being missed for few days might be enough to trigger the re-occurrence of an older eddy as a new track. This situation is also encountered for C3 surveyed during legs 1B and 2, but associated with two different tracks (755737 for C3, 774876 for C3', see Fig.8b-c). Such variability in track labeling encourages to consider it with some caution. Several other tracks could be partly inter-
rupted due to missing detections, and eddies would come from further East. META atlas use the overlapping method for tracking: an eddy next observation is allocated following its overlap with previous observation. Despite being less computationally effective, the cost function method (Penven et al., 2005) was shown to be quite robust, in particular when including the delay from last detection itself into the cost function (Le Vu et al., 2018). The cost function method is then interesting to improve META tracking efficiency.

<figure><img src="image_11.png" /><figcaption>Figure 8: (a) ADT map for 2019-05-06 during leg 1A, identified structured from in situ data highlighted. (b) ADT map for 2019-05-11 during leg 1B. (c) ADT map for 2019-05-19 during leg 2. (d) Remote-sensing eddy detection from META atlas, color intensity marking persistence in days, overlaid by the ship track in back line. (e) and (f) : same (d) for leg 1B and 2 respectively.</figcaption></figure>
594

# 4. Discussion

595

## 4.1. Dynamical diagnostic of meso and submesoscale structures

596

597

598

599

600

601

602

603

604

605

606

607

608

609

610

611

In this section, two transects (2 and 3) will be analyzed as representative of the other transects. Vertical velocity gradients can be used to define the boundaries of mesoscale structures, thanks to their sign change and intensity, which give an indication of variations in horizontal movements in the case of the geostrophic gradient ($\partial_z V_G$), and vertical movements in the case of the ageostrophic gradient ($\partial_z V_A$). For transect 2, the geostrophic vertical gradient shows values ranging from -0.20 to 0.16 $s^{-1}$ for the 5% and 95 % quantiles, while they range from -0.23 to 0.25 $s^{-1}$ for the ageostrophic vertical gradient. Vertical variations are therefore generally more intense than horizontal ones. The strongest values of the ageostrophic gradient coincide with the vertical delimitation of the AC1 and C2 surface eddies, as well as at their center (C2). However, it is the change in sign that best delimits the AC1 and C2 eddies. The front between these two is visible on both the geostrophic and ageostrophic parts, thanks to a vertical alternation in the sign of the gradients. Finally, the geostrophic gradient is clearly delineated at a depth of 300m.

612

613

614

615

616

617

618

The *PMV* (Equation 3) shows a vertical distribution very similar to the vertical gradient of geostrophic velocity. The *PMV* anomaly is qualitatively similar to the *PMV* in the upper 150m of the water column. The PMV vanishes only at the edge of eddies, showing a possible symmetric instability there. Below (in the following 150m of the water column), the sign of *PMV'* is opposite to that of *PMV*; globally *PMV'* is weak in that layer but it
intensifies at the center of the eddies and between them (this might be the signature of a vorticity filament).

<figure><img src="image_12.png" /><figcaption>Figure 9: Vertical sections of (a) the PMV and (b) its anomaly PMV' for the second transect</figcaption></figure>

Several dimensionless quantities are also described, providing a better understanding of the phenomena influencing the dynamic structures studied so far. The latter is one of the transect along which SCVs were detected. Firstly, the Rossby number (Equation 4) was calculated, which feature sub-surface cyclonic structures 60km wide on transect 3. Overall, values are below 0.5, except at the SCV level, where values close to 1 are observed. Advection therefore predominates over the geostrophic effect in these structures. One can notice that *Ro* is positive within cyclones, negative in anticyclones, and changes sign at the edges of eddies.

The transect 2 is then used to calculate the Richardson number (Equation 5). Values are well above 10 in the layer of the first 150m, but decrease drastically below, and are generally between 0 and 3. A descent of the high
<figure><img src="image_13.png" /><figcaption>Figure 10: Vertical section of the Rossby number on part of transect 3</figcaption></figure>

values can be observed, however, particularly at the edges of surface eddies. Lowest intensities of Ri, i.e. below 0.5, appear to be found mainly at depth beneath the edges of mesoscale structures.

Finally, the Burger number (Equation 6) is calculated along transects 2 and 3. On the first one, surface and subsurface values are above 0.5, forming a distribution reminiscent of isopycnals or *PMV*. On transect 3, on the other hand, these values are of the order of 0.2 to 0.3, although their distribution is also similar to these values. The AC1 and C1 eddies can be located. In both cases, *Bu* values at depth remain below 0.2 or even 0.1.

The presence of various structures mentioned above was confirmed by the various variables measured and represented, namely current speed and direction, but also by the behavior of isolines of hydrological quantities (tem-
<figure><img src="image_14.png" /><figcaption>Figure 11: Vertical sections of Burger number for transect 2.</figcaption></figure>

perature, density) and sea level maps for surface eddies. Diagnostic analysis provides a better understanding of the dynamic mechanisms at work. In particular, the ageostrophic velocity gradient shows the zones of most intense variation in vertical movements, concentrated at the edges and centers of eddies. The delimitation observed at a depth of 300m corresponds with the base of the thermocline. Indeed, the temperature and density isolines - in addition to the fine-scale variations due to internal waves - show a quasi-barotropic signature at this depth. Similarly, the mean value of the ageostrophic gradient at 300m is $-2.4 \times 10^{-4} s^{-1}$, i.e. almost zero. This delimitation can also be seen with the *PMV*, with intense, positive values above and weak, negative values below. This implies a situation of diminished vorticity and barotropic stability, as the *PMV'* has a positive sign on the horizontal. Similarly, between 150 and 300m depth, *PMV* is positive overall, except at the edges of AC1 and C2. Again, this implies weak symmetric and barotropic instabilities. The vertical gradient of *PMV'* may allow a stronger baroclinic
instability (Charney and Stern, 1962).

665

The Richardson number shows stratification dominating vertical shear in the surface layer and at the edges of eddies in the subsurface layer, and vertical shear dominating the rest of the water column. When $Ri < 1/4$, Kelvin-Helmholtz instabilities can form. Similarly, when $Ri < 1$, frontal instabilities can occur, but the resolution of the data does not allow us to observe these very small-scale instabilities. Data can be compared with work done on glider measurements carried out between 2021 and 2022 in the Southern Gulf of Oman (Font et al., 2024). Although May data are missing, $Ri$ values during the spring intermonsoon remain relatively high all along the water column, in contrast to the winter monsoon when $Ri$ is globally below the threshold of 1/4 above the MLD (*Mixed Layer Depth*). As the MLD remains close to the surface (less than 50m deep) during the campaign, it is logical to observe few vertical instabilities at the surface. On the other hand, lower $Ri$ values were observed beyond 300m in the Gulf of Oman, compared with 200m in the Arabian Sea. This difference can be explained by the greater number of more intense surface eddies in this zone, which influence subsurface vertical mixing.

682

Finally, Burger's number shows that stratification is indeed present in the first 50m of depth, but also subsurface at the base of AC1 and F1. Over the rest of the section, and particularly below 150m, flow remains largely influenced by terrestrial rotation. For SCV, the Rossby number is close to 1, as it indicates the presence of a quasi-symmetrical instability. Moreover, positive values at the center and negative values at the edges are characteristic of a

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688
689 cyclonic signature.

690 4.2. Interaction with coastal upwelling

691 The SST is the best spatially resolved complementary data, enabling
692 us to better understand the influence of mesoscale and fine-scale dynamics
693 on the distribution and movement of water masses. A highly significant
694 seasonality is observed, with variations of sometimes more than 5°C in just
695 one month (Figure 12). However, a North-South gradient - with temperatures
696 above 30°C in the center of the Arabian Sea, and lower towards the Gulf of
697 Oman - seems to be present throughout the campaign, although it diminishes
698 towards the end of May. Coastal upwelling - with temperatures below 27°C
699 - is visible throughout the period, even after surface waters warm up at the
700 end of May (Figure 12c). The cold-water patches are seen mainly at the
701 three bays and headlands that define the coastline of southern Oman. Two
702 filaments detaching from the outer patches can also be seen, propagating
703 perpendicularly to the coast before spreading southwards.

<figure><img src="image_15.png" /><figcaption>Figure 12: SST maps dated (a) April 29, (b) May 13 and (c) May 27, 2019</figcaption></figure>
The SST shows an overall intensification of temperature as the summer monsoon approaches, whose winds and associated ocean currents seem to advect the propagation of deep waters upwelled offshore. The difference in temperature in the Persian Gulf confirms its role as an evaporation basin. Now that the characteristics of the Arabian Sea's surface waters are known, it is possible to delineate the regions where less salty deep waters have been advected to the surface (Figure 13). The surface temperature limit is set at 27°C, as this corresponds to the ASHSW temperature minimum. This figure is confirmed by the 1995 upwelling study (Shi et al., 2000), where an average horizontal section of the ASHSW was carried out. The upwelling zone corresponds to the first 100km, where the SST varies between 23 and 27°C. Overall, four upwelling subregions were detected: the first three are located in the three main bays forming the South Oman coastline, and the last is located just before the mouth of the Gulf of Oman, just below the tip of Ras Al-Hadd. Once the coastal upwelling sets in - during the summer monsoon season - the four zones join to form a single, larger and more seaward-facing zone.

## 721 Conclusions

The analyses carried out here characterized the main meso- and submesoscale dynamical structures sampled in the Arabian Sea by the PHYSIN-DIEN 2019 campaign. Following an initial description of the structures, a dynamical and hydrological analysis was carried out. This analysis used complementary tools and databases as the META atlas to detect eddies by remote-sensing. Beyond the characterization of mesoscale eddies, the first
<figure><img src="image_16.png" /><figcaption>Figure 13: Representation of upwelling areas at the coast during May 2019 according to the number of days with SST below 27°C</figcaption></figure>

main result of this work was the observation of cyclonic subsurface eddies, carrying water from the Red Sea and possibly from the Persian Gulf. The previous PHYSINDIEN campaigns and other campaigns carried out in the 1990s had already detected subsurface SCVs in this region, but only with an anticyclonic signature. A second main result of this study was the comparison of the surface signature of eddies (in altimetry) with their in-situ structure, and thus the validation (or not) of eddy detection methods. It appeared that eddy detection methods can miss a few structures. Dynamically, these eddies were shown to be mostly stable (the criteria allowing only weak barotropic and symmetric instabilities). They also interacted with the
738 coastal upwelling by pulling out long cold filaments from the coast. Fur-

739 ther comparison with model results (a regional simulation with the HYCOM

740 model) will be a logical complement to this first study, in the future.

741
<table><caption>Table .2: List of main meso and submesoscale structures described in Fig.3-5 encountered with their dynamical and hydrological characteristics. The ' indicates when the same structure is surveyed for the second time.</caption><thead><tr><th>Transect</th><th>Structure</th><th>Distance [km]</th><th>Depth [m]</th><th>Speed [cm.s<sup>-1</sup>]</th><th>Temperature [°C]</th><th>Salinity [g.kg<sup>-1</sup>]</th><th>σ<sub>0</sub> [kg.m<sup>-3</sup>]</th></tr></thead><tbody><tr><td rowspan="2">1</td><td>AC1</td><td>50 - 310</td><td>0 - 150</td><td>50</td><td>25.0 - 29.0</td><td>36.2 - 36.3</td><td>70</td></tr><tr><td>SC1</td><td>140 - 210</td><td>350 - 800</td><td>45</td><td>11.7</td><td>35.7</td><td>27.1</td></tr><tr><td rowspan="2">2</td><td>AC1'</td><td>330 - 440</td><td>0 - 150</td><td>60</td><td>25.0 - 29.0</td><td>36.2 - 36.4</td><td>22.8 - 24.3</td></tr><tr><td>C1</td><td>440 - 650</td><td>0 - 150</td><td>35</td><td>15 - 20</td><td>35.7</td><td>25.0 - 26.5</td></tr><tr><td rowspan="4">3</td><td>C2</td><td>900 - 930</td><td>0 - 100</td><td>35</td><td>12.7 - 27.8</td><td>35.6 - 36.5</td><td>22.5 - 26.7</td></tr><tr><td>J1</td><td>1040 - 1090</td><td>0 - 100</td><td>35</td><td>/</td><td>/</td><td>/</td></tr><tr><td>AC2</td><td>1140 - 1580</td><td>0 - 150</td><td>60</td><td>17.7 - 27.9</td><td>35.7 - 36.4</td><td>23.0 - 26.7</td></tr><tr><td>SC2</td><td>1400 - 1460</td><td>400 - 800</td><td>25</td><td>/</td><td>/</td><td>/</td></tr><tr><td rowspan="2">4</td><td>J2</td><td>1600 - 1650</td><td>0 - 200</td><td>55</td><td>21.0 - 28.0</td><td>35.7 - 36.5</td><td>23.2 - 25.5</td></tr><tr><td>C3</td><td>1750 - 1880</td><td>0 - 600</td><td>40</td><td>13.5 - 19.0</td><td>35.7 - 36.6</td><td>25.7 - 26.7</td></tr><tr><td>5</td><td>AC3</td><td>1880 - 1980</td><td>0 - 150</td><td>25</td><td>17.0 - 24.0</td><td>36.1 - 37.4</td><td>24.3 - 26.6</td></tr><tr><td rowspan="2">6</td><td>AC4</td><td>2160 - 2400</td><td>0 - 250</td><td>70</td><td>16.0 - 28.4</td><td>36.0 - 36.8</td><td>23.2 - 26.7</td></tr><tr><td>C4</td><td>2430 - 2520</td><td>0 - 100</td><td>30</td><td>15.0 - 29.5</td><td>35.8 - 36.6</td><td>23.0 - 26.7</td></tr><tr><td rowspan="2">7</td><td>C3'</td><td>2660 - 2780</td><td>0 - 800</td><td>30</td><td>14.2 - 22.8</td><td>35.8 - 36.4</td><td>25.0 - 26.7</td></tr><tr><td>AC5</td><td>2940 - 3010</td><td>0 - 200</td><td>35</td><td>14.3 - 29.5</td><td>35.8 - 36.6</td><td>22.9 - 26.7</td></tr></tbody></table>
<table><caption>Table .3: List of mesoscale structures described in Fig.3-5 and associated META tracks and characteristics. δSSH correspond to associated sea level fluctuation as provided in META. Life time is the eddy age at the time of in situ observation. As detailed in Section 3.3, structure C3 is associated with 2 different tracks, and C4 is missed by META.</caption><thead><tr><th>Structure</th><th>Tracks</th><th>δSSH [m]</th><th>Life time [days]</th></tr></thead><tbody><tr><td>AC1</td><td>726696</td><td>0.16</td><td>36</td></tr><tr><td>C1</td><td>767574</td><td>-0.14</td><td>83</td></tr><tr><td>C2</td><td>772152</td><td>-0.06</td><td>27</td></tr><tr><td>AC2</td><td>724832</td><td>0.178</td><td>62</td></tr><tr><td>C3</td><td>755737</td><td>-0.18</td><td>236</td></tr><tr><td>AC3</td><td>724643</td><td>0.07</td><td>77</td></tr><tr><td>AC4</td><td>722801</td><td>0.16</td><td>103</td></tr><tr><td>C4</td><td>/</td><td>/</td><td>/</td></tr><tr><td>C3'</td><td>774876</td><td>-0.17</td><td>9</td></tr><tr><td>AC5</td><td>730581</td><td>0.05</td><td>4</td></tr></tbody></table>
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<figure><img src="image_17.png" /><figcaption>Figure .14: Past META tracks associated with in situ observed mesoscale eddies in Table.3.</figcaption></figure>
<figure><img src="image_18.png" /></figure>

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<figure><img src="image_19.png" /></figure>

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**Declaration of interests**

[x] The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

[ ] The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
META eddy Atlas (1993-2022)

<figure><img src="image_20.png" /></figure>

<figure><img src="image_21.png" /></figure>
<figure><img src="image_22.png" /><figcaption>Fig1</figcaption></figure>
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ADT

Leg 1A (05/04 - 05/08)

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Leg 1B (05/09 - 05/12)

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Leg 2 (05/21 - 05/25)

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META

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