Floriane Sudre
email: floriane.sudre@mio.osupytheas.fr

Boris Dewitte

Camille Mazoyer

Ve ´ronique Garc ¸on

Joel Sudre

Pierrick Penven

Vincent Rossi

Francisco Machı

Li Yineng

Spatial and seasonal variability of horizontal temperature fronts in the Mozambique Channel for both epipelagic and mesopelagic realms

Keywords: fronts, temperature fronts, seasonal variability, mozambique channel, ROMS-CROCO, Belkin and O'Reilly algorithm, submesoscale, indian ocean

Introduction: Ocean fronts are moving ephemeral biological hotspots forming at the interface of cooler and warmer waters. In the open ocean, this is where marine organisms, ranging from plankton to mesopelagic fish up to megafauna, gather and where most fishing activities concentrate. Fronts are critical ecosystems so that understanding their spatio-temporal variability is essential not only for conservation goals but also to ensure sustainable fisheries. The Mozambique Channel (MC) is an ideal laboratory to study ocean front variability due to its energetic flow at sub-to-mesoscales, its high biodiversity and the currently debated conservation initiatives. Meanwhile, fronts detection relying solely on remotely-sensed Sea Surface Temperature (SST) cannot access aspects of the subsurface frontal activity that may be relevant for understanding ecosystem dynamics.

Method: In this study, we used the Belkin and O'Reilly Algorithm on remotelysensed SST and hindcasts of a high-resolution nested ocean model to investigate the spatial and seasonal variability of temperature fronts at different depths in the MC.

Results: We find that the seasonally varying spatial patterns of frontal activity can be interpreted as resulting from main features of the mean circulation in the MC region. In particular, horizontally, temperature fronts are intense and frequent along continental shelves, in islands' wakes, at the edge of eddies, and in the pathways of both North-East Madagascar Current (NEMC) and South-Frontiers in Marine Science frontiersin.org 01

Introduction

Ocean fronts are ubiquitous discrete features in the ocean which are now more readily available thanks to the everincreasing spatial resolution of satellite data (Belkin et al., 2009;[START_REF] Kartushinsky | Analysis of the variability of temperature gradient in the ocean frontal zones based on satellite data[END_REF][START_REF] Belkin | Remote sensing of ocean fronts in marine ecology and fisheries[END_REF]. Fronts are defined as a sharp transition between waters of different properties (temperature, salinity, chlorophyll-a, nutrients, etc.) and are usually detected by high local horizontal gradients in those same properties [START_REF] Largier | Estuarine fronts: How important are they?[END_REF][START_REF] Cayula | Multi-image edge detection for sst images[END_REF][START_REF] Shimada | Application of an edge detection method to satellite images for distinguishing sea surface temperature fronts near the japanese coast[END_REF]. Frontal phenomena encompass a wide range of space and time scales, from submesoscale structures to thousands of kilometers and from hours to hundreds of years [START_REF] Mcwilliams | Oceanic frontogenesis[END_REF][START_REF] Belkin | Remote sensing of ocean fronts in marine ecology and fisheries[END_REF]. More specifically, some fronts are seasonally persistent [START_REF] Acha | Marine fronts at the continental shelves of austral south america[END_REF][START_REF] Vinayachandran | Reviews and syntheses: Physical and biogeochemical processes associated with upwelling in the indian ocean[END_REF][START_REF] Mcwilliams | Oceanic frontogenesis[END_REF], while others display clear seasonal patterns [START_REF] Park | Thermal and haline fronts in the yellow/east china seas: Surface and subsurface seasonality comparison[END_REF][START_REF] Castelao | Sea surface temperature fronts in the California Current System from geostationary satellite observations[END_REF][START_REF] Bosse | Mean structure and seasonality of the norwegian atlantic front current along the mohn ridge from repeated glider transects[END_REF].

In the open ocean, fronts are dynamic biological hotspots, offering rich habitats to numerous marine species across all trophic levels for migration, reproduction and foraging [START_REF] Largier | Estuarine fronts: How important are they?[END_REF][START_REF] Acha | Marine fronts at the continental shelves of austral south america[END_REF][START_REF] Bakun | Fronts and eddies as key structures in the habitat of marine fish larvae: opportunity, adaptive response and competitive advantage[END_REF][START_REF] Tew Kai | Top marine predators track lagrangian coherent structures[END_REF][START_REF] Tew Kai | Influence of mesoscale eddies on spatial structuring of top predators' communities in the mozambique channel[END_REF][START_REF] Rossi | Cross-shelf variability in the iberian peninsula upwelling system: Impact of a mesoscale filament[END_REF][START_REF] Sabarros | Fine-scale recognition and use of mesoscale fronts by foraging cape gannets in the benguela upwelling region. Deep-sea[END_REF][START_REF] Levy | The role of submesoscale currents in structuring marine ecosystems[END_REF]. Additionally, species of all trophic levels exploit the whole water column around those dynamical structures [START_REF] Bakun | Fronts and eddies as key structures in the habitat of marine fish larvae: opportunity, adaptive response and competitive advantage[END_REF], from phytoplankton communities [START_REF] Barlow | Adaptation of phytoplankton communities to mesoscale eddies in the mozambique channel. Deep-sea[END_REF], to micronekton [START_REF] Annasawmy | Micronekton diel migration, community composition and trophic position within two biogeochemical provinces of the south west indian ocean: Insight from acoustics and stable isotopes[END_REF], and megafauna [START_REF] Brunnschweiler | Deepdiving behaviour of a whale shark rhincodon typus during long-distance movement in the western indian ocean[END_REF], thus increasing the interest for ecological and conservation studies with a vertical component.

Indeed, submesoscale fronts were previously thought to be confined in the mixed layer [START_REF] Fox-Kemper | Parameterization of mixed layer eddies. part i: Theory and diagnosis[END_REF] but recent studies show that fronts could penetrate much deeper than the mixed layer, and reach depths up to 1000m [START_REF] Bettencourt | Oceanic threedimensional lagrangian coherent structures: A study of a mesoscale eddy in the benguela upwelling region[END_REF][START_REF] Yu | An annual cycle of submesoscale vertical flow and restratification in the upper ocean[END_REF][START_REF] Siegelman | Enhanced upward heat transport at deep submesoscale ocean fronts[END_REF]. There is thus an opportunity to infer deep circulation as well as verticallyintegrated biological hotspots from surface mesoscale activity. This is essential for understanding the spatio-temporal variability of these critical ecosystems, at both ocean surface and interior, in order to design conservation management strategies and ensure sustainable resources [START_REF] Alemany | The relationship between marine fronts and fish diversity in the patagonian shelf large marine ecosystem[END_REF][START_REF] Nieblas | Front variability and surface ocean features of the presumed southern bluefin tuna spawning grounds in the tropical southeast indian ocean. Deep-sea[END_REF][START_REF] Watson | Fishermen follow fine-scale physical ocean features for finance[END_REF][START_REF] Scales | Fisheries bycatch risk to marine megafauna is intensified in lagrangian coherent structures[END_REF].

In this study, we investigate the temperature fronts in the Mozambique Channel (MC). The MC is part of the greater Agulhas system [START_REF] Lutjeharms | Three decades of research on the greater Agulhas Current[END_REF] starting North of Madagascar and reaching south all the way to South Africa (Figure 1). The circulation in the Mozambique Channel is highly energetic and unstable. The South Equatorial Current (SEC) parts in two at around 17°S east of Madagascar forming the Northeast and Southeast Madagascar currents (SEMC and NEMC, respectively). The MC is characterized by a highly variable Mozambique Current flowing southward along the Mozambican shelf [START_REF] Dimarco | Volume transport and property distributions of the mozambique channel. Deep-sea[END_REF][START_REF] Lutjeharms | On the discontinuous nature of the mozambique current[END_REF] and a succession of mesoscale eddies propagating southward at a speed of about 3 to 6 km/day [START_REF] De Ruijter | Observations of the flow in the mozambique channel: Observations in the mozambique channel[END_REF][START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF]. Eddies in the MC have a typical scale of several hundreds of kilometers [START_REF] De Ruijter | Observations of the flow in the mozambique channel: Observations in the mozambique channel[END_REF][START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF][START_REF] Ternon | In situ measured current structures of the eddy field in the mozambique channel. Deep-sea[END_REF], and a frequency of occurrence of 4 to 7 per year [START_REF] Schouten | Eddies and variability in the mozambique channel. Deep-sea[END_REF]. Those eddies display a strong barotropic component and some are felt all the way to the bottom of the channel (i.e., over -2000m) [START_REF] De Ruijter | Observations of the flow in the mozambique channel: Observations in the mozambique channel[END_REF][START_REF] Ridderinkhof | Moored current observations in the mozambique channel. Deep-sea[END_REF][START_REF] Schouten | Eddies and variability in the mozambique channel. Deep-sea[END_REF][START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF]. The most intense eddies are anticyclonic eddies (AE), also referred to as Mozambique Rings. They form at the narrowest part of the MC around 12-16°S and travel southward along the Mozambican shelf [START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF], where the flow is most intense [START_REF] De Ruijter | Observations of the flow in the mozambique channel: Observations in the mozambique channel[END_REF] and where eddy kinetic energy (EKE) is the highest [START_REF] Biastoch | The role of mesoscale eddies in the source regions of the agulhas current[END_REF]. Cyclonic eddies (CE) are more numerous, yet smaller than AE in the channel [START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF]. They usually form at the edge of bigger AE on the eastern side of the channel and south of 20°S, to then travel to the southwest [START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF][START_REF] Roberts | Interaction of dipole eddies with the western continental slope of the mozambique channel. Deep-sea[END_REF]. The formation of submesoscale filaments and fronts at the edge of mesoscale eddies is a common feature in turbulent regions and has been extensively documented from satellite imagery [START_REF] Munk | Spirals on the sea[END_REF][START_REF] Zhang | Surface chlorophyll enhancement in mesoscale eddies by submesoscale spiral bands[END_REF] and from observations [START_REF] Read | Sub-Mesoscale structure and the development of an eddy in the subantarctic front north of the crozet islands. Deep-sea[END_REF][START_REF] Roberts | Interaction of dipole eddies with the western continental slope of the mozambique channel. Deep-sea[END_REF][START_REF] Adams | Frontal circulation and submesoscale variability during the formation of a southern ocean mesoscale eddy[END_REF]Siegelman et al., 2020a;[START_REF] Tarry | Frontal convergence and vertical velocity measured by drifters in the alboran sea[END_REF]. The highly energetic flow at sub-to-mesoscale of the MC makes it thus ideal to study fronts.

The MC also exhibits a strong seasonal cycle and experiences biannual monsoons north of 20°S [START_REF] Schott | Indian Ocean circulation and climate variability[END_REF]. During the northeast monsoon, from December to March, winds blow from the northwest, while winds blow from the southeast during the southwest monsoon, from June to November. South of 20°S, winds blow from the southeast all year round [START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF]. The monsoon reversals of the north MC also modulate currents intensity [START_REF] Ridderinkhof | Seasonal and interannual variability in the mozambique channel from moored current observations[END_REF][START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF] and create a distinct seasonal pattern, which affects the large anticyclonic eddies forming at 12-16°S [START_REF] Donguy | The mozambique channel revisited[END_REF]. Finally, altimetry-derived EKE climatology for different parts of the MC (Figure 1) shows a strong seasonal variability, especially north of 25°S. The MC energetic turbulent flow, seasonal cycle and exceptional biodiversity [START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF] thus motivate the investigation of temperature front seasonal variability.

Historically, fronts have mostly been detected from satellite imagery. Originally, fronts were simply identified manually from SST images [START_REF] Legeckis | A survey of worldwide sea surface temperature fronts detected by environmental satellites[END_REF], but more sophisticated automatic front detection algorithms have been developed since then. Front detection algorithms are usually based on SST gradients, even though some also use entropy [START_REF] Shimada | Application of an edge detection method to satellite images for distinguishing sea surface temperature fronts near the japanese coast[END_REF], neural networks [START_REF] Torres Arriaza | Competitive neural-net-based system for the automatic detection of oceanic mesoscalar structures on avhrr scenes[END_REF] or singularity exponents [START_REF] Turiel | Reconstructing images from their most singular fractal manifold[END_REF][START_REF] Turiel | Tracking oceanic currents by singularity analysis of microwave sea surface temperature images[END_REF][START_REF] Tamim | Detection of moroccan coastal upwelling fronts in sst images using the microcanonical multiscale formalism[END_REF]. The Canny algorithm [START_REF] Canny | A computational approach to edge detection[END_REF] is often referred to as the original "gradient method" and is based on the high gradient property of fronts. However, this method often results in enhanced noise from the differentiation [START_REF] Belkin | An algorithm for oceanic front detection in chlorophyll and sst satellite imagery[END_REF]. The Cayulla-Cornillon Algorithm (CCA) addresses this shortcoming by operating with histograms to detect the edge between two water masses [START_REF] Cayula | Multi-image edge detection for sst images[END_REF]. This method requires fine-tuning to find the appropriate threshold distinguishing fronts from background noise, but has been successfully used in many different systems: in the Baltic Sea [START_REF] Kahru | Distributions of the sea-surface temperature fronts in the baltic sea as derived from satellite imagery[END_REF], in the Atlantic Ocean [START_REF] Mantas | Partitioning the ocean using dense time series of earth observation data. regions and natural boundaries in the western iberian peninsula[END_REF] or in the South China Sea [START_REF] Wang | Seasonal variability of thermal fronts in the northern south china sea from satellite data[END_REF]. The performance of the CCA was further improved by adding multiple sliding windows [START_REF] Nieto | Mesoscale frontal structures in the canary upwelling system: New front and filament detection algorithms applied to spatial and temporal patterns[END_REF] and then applied in the Indian [START_REF] Nieblas | Front variability and surface ocean features of the presumed southern bluefin tuna spawning grounds in the tropical southeast indian ocean. Deep-sea[END_REF] and Pacific [START_REF] Nieto | How important are coastal fronts to albacore tuna (thunnus alalunga) habitat in the northeast pacific ocean?[END_REF] remove the noise generally produced by other gradient methods, while preserving the shape of the detected front [START_REF] Belkin | An algorithm for oceanic front detection in chlorophyll and sst satellite imagery[END_REF]. The Belkin and O'Reilly algorithm (BOA) produced fronts dataset in the South China Sea [START_REF] Wang | Seasonal variability of thermal fronts in the northern south china sea from satellite data[END_REF], East China Sea [START_REF] Lin | Double fronts in the yellow sea in summertime identified using sea surface temperature data of multi-scale ultra-high resolution analysis[END_REF] and the Kuroshio current [START_REF] Liu | Ocean fronts construct spatial zonation in microfossil assemblages[END_REF].

Fronts can originate from the interaction between strong currents and topography anomalies, such as shelf-breaks, islands and seamounts [START_REF] Heywood | The effects of flow disturbance by an oceanic island[END_REF][START_REF] Condie | Formation and stability of shelf break fronts[END_REF][START_REF] Mcwilliams | Oceanic frontogenesis[END_REF]; at the edge of eddies in turbulent areas [START_REF] Munk | Spirals on the sea[END_REF][START_REF] Read | Sub-Mesoscale structure and the development of an eddy in the subantarctic front north of the crozet islands. Deep-sea[END_REF]Siegelman et al., 2020a) and in upwelling zones [START_REF] Bettencourt | Oceanic threedimensional lagrangian coherent structures: A study of a mesoscale eddy in the benguela upwelling region[END_REF][START_REF] Rossi | Cross-shelf variability in the iberian peninsula upwelling system: Impact of a mesoscale filament[END_REF][START_REF] Sabarros | Fine-scale recognition and use of mesoscale fronts by foraging cape gannets in the benguela upwelling region. Deep-sea[END_REF][START_REF] Calil | Filaments, fronts and eddies in the cabo frio coastal upwelling system, brazil[END_REF]. The Island Mass Effect [START_REF] Doty | The island mass effect[END_REF] in particular plays an important role in frontogenesis, as it has been shown to be associated with the generation of vortices in the lee of islands [START_REF] De Falco | Island mass effect: A review of oceanic physical processes[END_REF]. Although it is very rare to attribute clearly a single driver to frontogenesis, it is instead often a complex combination of favorable conditions [START_REF] Mcwilliams | Oceanic frontogenesis[END_REF].

The complex dynamic of processes behind frontogenesis [START_REF] Mcwilliams | Oceanic frontogenesis[END_REF] suggests that fronts detection relying solely on remotely sensed SST might miss important front features and variability at depth, and estimates of the magnitude of SST gradients in satellite products is highly sensitive to resolution and interpolation technique [START_REF] Vazquez-Cuervo | An analysis of sst gradients off the peruvian coast: The impact of going to higher resolution[END_REF]. In this study, we use remotely-sensed SST and outputs of a highresolution realistic ocean model to investigate the spatial and seasonal variability of thermal fronts at different depths in the Mozambique Channel. The paper is organized as follows: we first introduce our material and methods for front detection and we follow with a description of front variability in the Mozambique Channel. The article ends by a discussion and a few concluding remark 2 Material and methods

Domain subregions

Before studying thermal front variability, we divided our domain into 4 subregions, as seen in Figure 1. The rationale for this meridional subdivision is based on a literature review about drivers of oceanic variability (i.e. bathymetry effects, monsoon forcing) in the channel and relies on the dependence of eddy characteristics and therefore fronts to the Coriolis force. The "Islands" subregion (10-13.5°S, 38-49.5°E) starts just above the Comoros archipelago and extends to 13.5°S at the entrance of the Angoche Basin. The "Northern Mozambique Channel" (NMC) subregion (13.5-20°S, 34-48°E) ends at 20°S where the influence of monsoons weakens substantially [START_REF] Schott | Indian Ocean circulation and climate variability[END_REF]. The "South Mozambique Channel" (SMC) subregion (20-25°S, 33-45°E) goes as far south as 25°S, which corresponds to the southern tip of Madagascar island. Finally, the "Agulhas" subregion (25-30°S, 31-50°E) covers the southernmost part of our domain from 25°S to 30°S.

Model configuration

In this study, temperature fronts are derived from a ROMS-CROCO (Regional Ocean Modeling System and Coastal and Regional Ocean COmmunity model) configuration of the MC [START_REF] Shchepetkin | The regional oceanic modeling system (roms): a split-explicit, free-surface, topography-following-coordinate oceanic model[END_REF]. ROMS-CROCO solves the primitive hydrostatic equations for momentum and tracer variables and successfully resolves regional and coastal oceanic processes at high resolution, as well as mesoscale eddies [START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF]. The model configuration consists in 3 nested grids (two-way nesting) with the child domain at the highest resolution of 1/36°used here. 60 vertical sigma (topography following) layers are used. The bathymetry used in the model is from GEBCO 2014 [START_REF] Weatherall | A new digital bathymetric model of the world's oceans: New digital bathymetric model[END_REF]. A bulk formulation [START_REF] Fairall | Bulk parameterization of air-sea fluxes for tropical ocean-global atmosphere coupled-ocean atmosphere response experiment[END_REF] is used to compute surface turbulent heat to force the model, based on ERA-Interim Reanalysis daily mean atmospheric fields (2 m air temperature, relative humidity, surface wind speed, net shortwave and downwelling longwave fluxes, and precipitations). Wind stress forcing is also from the ERA-Interim Reanalysis. At the lateral open boundaries, mixed active-passive conditions are used [START_REF] Marchesiello | Open boundary conditions for long-term integration of regional oceanic models[END_REF] with forcing data from GLORYS reanalysis at 1/4°resolution. The generated daily output covers 22 years, from 1993 to 2014. This 1/36°ROMS-CROCO configuration of the Mozambique Channel, referred to as MOZ36, was first used by [START_REF] Miramontes | The influence of bottom currents on the zambezi valley morphology (mozambique channel, sw indian ocean): In situ current observations and hydrodynamic modelling[END_REF] to document the deep oceanic circulation in the Zambezi turbidite system (SMC subregion in Figure 1)

Climatological and satellite datasets

We used climatological seawater properties from CARS2009 [START_REF] Ridgway | Ocean interpolation by fourdimensional least squares -application to the waters around australia[END_REF] generated from compiled in-situ observations spanning from January 1941 to May 2009, on a 1/ 2°grid. We also retrieved World Ocean Atlas 2018 annual mean temperature [START_REF] Locarnini | World ocean atlas 2018[END_REF] and salinity [START_REF] Zweng | Salinity. A. Mishonov Technical[END_REF]. Remotely-sensed Sea Surface Height (SSH) was taken from Global Total Surface and 15 m Current [START_REF] Rio | Beyond goce for the ocean circulation estimate: Synergetic use of altimetry, gravimetry, and in situ data provides new insight into geostrophic and ekman currents: Ocean circulation beyond goce[END_REF] [START_REF] Chin | A multi-scale high-resolution analysis of global sea surface temperature[END_REF]. In this work, we use the full MUR dataset from January 2003 to December 2020, for the MC. SST MUR data comes with 2 data quality flags. Flag 1 corresponds to the estimated error standard deviation of the SST data and flag 2 is the time lag to most recent 1 km data. Flag 1 is available for the entire dataset while flag 2 is only included after July 2016.

Numerical methods

We use the Brunt-Väisälä frequency N as a proxy for stratification. N is given by:

N 2 = -g r 0 ∂ r ∂ z (1)
Where g is the gravitational constant, r 0 is a reference density set at 1025 kg.m -3 r is the seawater density and z its depth.

Intra-seasonal and inter-annual eddy kinetic energy (EKE) were computed following a similar method to Dewitte et al. [START_REF] Dewitte | Understanding the impact of climate change on the oceanic circulation in the chilean island ecoregions[END_REF]. First, intra-seasonal current anomalies (u IS and v IS ) were estimated by subtracting monthly mean currents to the daily velocity dataset. Then, the mean intra-seasonal EKE was computed as:

〈 EKE IS 〉 = 〈 u 2 IS + v 2 IS À Á 2 〉 (2)
Second, inter-annual current anomalies (u IA and v IA ) were computed by subtracting the climatology to the daily velocity dataset. Then, the mean inter-annual EKE was computed as:

〈 EKE IA 〉 = 〈 u 2 IA + v 2 IA À Á 2 〉 (3)
Following the same methodology, MOZ36 intra-seasonal EKE was also computed at -100 m, -500 m and -1000 m.

We chose the Belkin and O'Reilly algorithm [START_REF] Belkin | An algorithm for oceanic front detection in chlorophyll and sst satellite imagery[END_REF] to detect the location and intensity of temperature fronts in the MC. More specifically, we use Ben Galuardi's BOA pseudo-code written in R and publicly available on https://github.com/galuardi/boaR (accessed on 19 May 2022). BOA first applies a contextual median filter until convergence to reduce noise originating from natural variability and artifacts. The algorithm then uses 3x3 kernel Sobel operator to compute the gradient magnitude [START_REF] Belkin | An algorithm for oceanic front detection in chlorophyll and sst satellite imagery[END_REF]. BOA temperature gradients were computed on MUR SST but also on MOZ36 temperatures between 0 and -1000 m, leveraging the fact that the model is not limited to the surface, as would be satellite datasets. From the surface to -300 m, the model outputs were interpolated on a 10 m vertical resolution grid, while below -300 m we use a resolution of 50 m.

We derive several statistics to characterize temperature fronts and to evaluate their variability. BOA being a gradient-based method of front detection, the algorithm produces a continuous field of temperature gradient magnitude, or front intensity in °C/ km. As such, a threshold must be determined to define what is considered a front. Choosing a high threshold might prevent weak fronts from being recorded, while a weak threshold might blur any meaningful signal into noise. We thus define front pixels as pixels whose temperature gradient magnitude is equal or above the chosen threshold. We finally define the probability of front occurrence per month for each ocean pixel as the percentage of days when the gradient value qualifies as "front", i.e. when the pixel gradient magnitude is over the threshold, over the total number of days for each month of simulation.

Finally, we computed sea level anomalies (SLA) from the mean MOZ36 sea-surface heights in order to link frontal activity with (sub)-mesoscale features in the MC. And dominant timefrequencies were studied based on 1-D discrete fast Fourier transforms (FFT) computed with the scipy.fft package.

Model validation 2.5.1 EKE

To validate MOZ36 (sub-)mesoscale structures on intraseasonal and inter-annual time scales, we evaluated the mean eddy kinetic energy (EKE) derived from the model and remotely-sensed currents (see supplementary material Figure S1). The spatial EKE patterns are similar in both model and satellite data: the EKE is most intense on the western part of the MC and in its southern part, in the wake of the SEMC. Note that, the slightly higher EKE from the model could be well-explained by its higher resolution.

Hydrography

When comparing the SST variability in the MC from MOZ36 and from MUR SST (Figure S2), both datasets exhibit comparable seasonal and spatial SST patterns. Additionally, and to further validate seawater properties of MOZ36, we compared World Ocean Atlas 2018 temperature [START_REF] Locarnini | World ocean atlas 2018[END_REF] and salinity [START_REF] Zweng | Salinity. A. Mishonov Technical[END_REF] annually-averaged vertical profiles on a meridional section at 42.125°E, in the center of the channel (Figure S3). Observed and modelled vertical profiles show good consistency, confirming that MOZ36 is suitable to study temperature fronts in the MC.

Stratification

We used CARS2009 [START_REF] Ridgway | Ocean interpolation by fourdimensional least squares -application to the waters around australia[END_REF] temperature and salinity profiles to evaluate the realism of the modelled vertical stratification thanks to the Brunt-Väisälä frequency from the surface to -1000 m. The comparison between the mean model and CARS2009 squared Brunt-Väisälä frequencies for the 4 MC subregions (Figure S4) reveals that MOZ36 is able to reproduce a range of values similar to observations, with a maximum N 2 of about 0.2*10 -3 s -2 . For both datasets, N 2 in the Agulhas region is markedly smaller than the other 3 subregions and peaks at -60 m. The Islands, NMC and SMC subregions peaks between -60 and -100 m in the model and between -80 and -125 m in CARS2009. Overall the model reproduces a rather realistic mean thermocline structure, providing high confidence in its ability to simulate well the main aspects of ocean dynamics.

Results

Front threshold definition

We define a single temperature front threshold for all depths using statistical distribution and quantiles of MOZ36 temperature front intensity for all ocean pixels across the 22 years of simulation and 4 depth levels: surface, -100 m, -500 m, and -1000 m (Figure S5). Surface temperature gradients go up to 2.3°C/km, and 70% of those are below 0.05°C/km. We subsequently define front pixels as pixels whose temperature gradient magnitude is equal or above 0.05°C/km, and the probability of front occurrence per month for each ocean pixel as the percentage of days when the pixel gradient magnitude is over 0.05°C/km, over the total number of days for each month of simulation.

Spatial variability

Surface

The mean surface temperature front intensity and probability maps (Figures 2A,B) reveals that SST fronts derived from the model are more intense and more likely to appear along the continental shelves, in the wake of both Northeast and Southeast Madagascar currents (NEMC and SEMC) and more generally southward of 25°S.

The equivalent mean maps of temperature front intensity and probability derived from the MUR dataset exhibit a spatial distribution similar to that of the modelled fronts (Figures 2C,D), despite a slightly lower range of values.

Ocean interior

Figure 3 represents the mean vertical profiles of front intensity in °C/km from MOZ36, the shading around the mean corresponds to the seasonal standard variation. The vertical profiles reveal three distinct regimes, similar in all 4 subregions of the MC:

1. From the surface to about -100 m, the frontal activity increases abruptly to reach its maximum to 0.75-0.9°C/ km at -100 to -200 m, in the vicinity of the mean thermocline. 2. From -200 m to -500 m, the front intensity decreases sharply to reach 0.35°C/km in the NMC region and around 0.05°C/km in the Islands, NMC and Agulhas regions. 3. From -500 m and deeper, frontal intensities decrease at a slower rate with depth. At -1000 m the NMC region exhibits the lowest frontal activity, followed by the Islands regions. The SMC and the Agulhas region show less of a vertical difference between surface and depth, than the NMC and the Islands regions.

The vertical distribution of temperature front intensity is very similar to MOZ36 and CARS2009 stratification profiles (Figure S4). Indeed, the Islands (Agulhas) subregion has the Frontal activity peaks at around -100 m, in the vicinity of the mean thermocline (Figure 3). The resulting 22-year map of mean front intensity at -100 m (Figure 4C) indicates stronger frontal activity than at the surface, as expected from the front intensity distribution (Figure S5). The frontal activity is specifically stronger along the continental shelves, in the wake of the NEMC and SEMC and in the central part of the MC, in between Bassas da India and Juan de Nova islands across the Angoche Basin.

-500 m and -1000 m temperature fronts are most intense along the Mozambican shelf, near Maputo and in the path of the NEMC and SEMC (Figure 4).

Front typology

Selected snapshots of temperature front intensity at different depth and time of the year allowed us to distinguish three types of temperature fronts based on their signature behaviors (Figure 5). A summary of the front typology and locations can be found in Table 1.

Seasonal variability

Islands and NMC subregions

In the Islands (10°S-13°S) and NMC (13°S-20°S) regions, SST fronts are strongest in the wake of the NEMC between the Mean temperature front intensity for each MOZ36 subregion in °C/km. The shading shows the seasonal standard deviation from the mean. The dashed horizontal lines mark the depth below which the seasonal standard deviation of temperature front intensity is lower than 5% of its mean.

northwestern tip of Madagascar and the Comoros archipelago (Figure 4) and along the Madagascar and Mozambican continental shelves. Most of the fronts in the Islands region are identified as topographic fronts, generated by the interaction between NEMC and the local topography, while fronts in the NMC are mostly topographic fronts and ADF. The FFT analysis of the 22-year daily time series of surface temperature front intensity from MOZ36 in the Island and NMC regions reveals a predominant 6-month and a moderate 1-year periods (Figure 6, additional depths are provided in supplementary material (Figure S6). Indeed, SST front intensity climatology shows two peaks: a moderate one in May and a greater one in November (Figure 7).

General location Subregion

Surface -100m -500m -1000m Note that the surface climatology of front intensity from MUR SST (Figure 7) shows little seasonal variability compared to the model. This aspect is explored later in the discussion part, where quality flags explain well why the seasonal cycle is significantly dampened compared to the model.

In the Islands subregion, the -100 m front intensity is greater than at the surface and peaks in late austral autumn (June). The signature 2-peak of the surface signal seems to have disappeared entirely, leaving only one clear maximum in winter. In the NMC area, the -100 m front intensity is higher than at the surface and peaks in austral summer, with a second local maximum in austral winter. At -500 m and -1000 m, there is not much seasonal variation anymore (Figure 7).

SMC and Agulhas subregions

In the SMC (20°S-25°S) and in the Agulhas (25°S-30°S) subregions, surface temperature fronts are more intense along the continental shelves and in the wake of the SEMC. The FFT analysis of the 22-year daily time series of SST front intensity from MOZ36 in the two southernmost regions reveals both 6month and 1-year periods, but this time the yearly signal exhibits stronger magnitude than the biannual one (Figure 6). The climatology of surface temperature front intensity (Figure 7) shows stronger frontal activity during austral winter and spring, with a slight increase in December in the SMC.

Similarly to the NMC, the -100 m temperature front climatology in the SMC is stronger than at the surface and reveals two local maxima with comparable range, in austral summer and winter (Figure 7). In the Agulhas region, the -100 m front climatology (Figure 7) shows a much weaker seasonal variation, also seen on the FFT analysis (Figure 6), with a slight maximum in austral winter.

At -500 m and -1000 m, little seasonal variation is seen in frontal activity (Figure 7). However, even though the fronts become less intense with depth, -500 m and -1000 m fronts in the SMC and Agulhas subregions are still more intense than in the Islands and NMC regions. Indeed, the interaction between the SEMC and local topography fosters the formation of cyclonic eddies and thus of CDF, which have shown to have a strong deep signature in the model (Figure 5).

Discussion

Data and method

The extended MOZ36 validation process conducted in this work and in [START_REF] Miramontes | The influence of bottom currents on the zambezi valley morphology (mozambique channel, sw indian ocean): In situ current observations and hydrodynamic modelling[END_REF] has confirmed its suitability in depicting realistic basin-scale and regional dynamics of the MC. Yet, the temperature front seasonal 8A) and on both flags for 2017-2020 (Figure 8B). If we only take flag 1 into account, 50-90% of the dataset is acceptable, while if we consider both flags then only 10-50% of the dataset is suitable to study seasonal variability of submesoscale fronts in the MC. Regardless of how many flags are considered, a bigger proportion of pixels are not suitable in austral summer, compared to austral winter, providing a good explanation as to why so little seasonality is seen from MUR SST front intensity in Figure 7. Indeed, the difference between seasons in frontal activity could be significantly dampened by the cloud cover. Additionally, the seasonality in mean EKE is comparable between observations (altimetry) and the model (not shown), which also suggests the limitations of the MUR dataset.

Other tracer-based front detection algorithms, such as the objective Cayulla Cornillon Algorithm [START_REF] Cayula | Multi-image edge detection for sst images[END_REF] and the Nieto method [START_REF] Nieto | Mesoscale frontal structures in the canary upwelling system: New front and filament detection algorithms applied to spatial and temporal patterns[END_REF], could have been used to detect temperature fronts in the MC, but they do not provide gradient magnitudes. Moreover, we did find a temperature front intensity threshold and spatial variability similar to what is documented in [START_REF] Nieblas | Front variability and surface ocean features of the presumed southern bluefin tuna spawning grounds in the tropical southeast indian ocean. Deep-sea[END_REF], despite using a different front detection algorithm.

Finally, it would be interesting to use Lyapunov Exponents as in [START_REF] Hernańdez-Carrasco | Seasonal and regional characterization of horizontal stirring in the global ocean[END_REF]; [START_REF] Bettencourt | Oceanic threedimensional lagrangian coherent structures: A study of a mesoscale eddy in the benguela upwelling region[END_REF] and [START_REF] Siegelman | Enhanced upward heat transport at deep submesoscale ocean fronts[END_REF]2020a) to bring a dynamic-based approach to our multidecadal tracer-based front database.

Spatial variability

We have leveraged the 3D component of the well-validated MOZ36 to go beyond the surface and explore temperature front activity in the MC ocean interior as well. To our knowledge, this is the first temperature front spatial and seasonal variability analysis extending to the ocean interior in the MC.

The mean maps of frontal intensity and probability (Figure 2) from MOZ36 and MUR SST present similar spatial patterns to what is shown in [START_REF] Nieblas | Front variability and surface ocean features of the presumed southern bluefin tuna spawning grounds in the tropical southeast indian ocean. Deep-sea[END_REF]. Additionally, the vertical distribution of temperature front intensity is consistent with the stratification profiles from MOZ36 and CARS2009 (Figure S4). Indeed, the Islands (resp. Agulhas) region has the deepest (resp. shallowest) thermocline and frontal intensity peak, at about -200 m (-80 m). It is worth noting that as MOZ36 does not consider the run-off from the Zambeze river, we expect thermal shelfs fronts over the SofalaBank to be underestimated. In all 4 regions, front intensity is maximum at around -100 m, in the vicinity of the mean thermocline. The maximum intensity fronts at around -100 m may be explained by strain-induced vertical velocities at the edge of eddies, which intensify below the mixed layer and up to -400 m below it [START_REF] Keppler | Observed characteristics and vertical structure of mesoscale eddies in the southwest tropical pacific[END_REF]Siegelman et al., 2020a).

ADF develop at the border of large anticyclonic eddies, or Mozambique Rings, on the western side of the MC, as observed by [START_REF] Biastoch | The role of mesoscale eddies in the source regions of the agulhas current[END_REF] and [START_REF] Schouten | Eddies and variability in the mozambique channel. Deep-sea[END_REF]. On the other side of the channel, CDF form at the edge of smaller cyclonic eddies, mostly on the southeastern side of the channel and driven by the SMEC, as seen in Gründlingh's work [START_REF] Gründlingh | Tracking eddies in the southeast atlantic and southwest indian oceans with topex/poseidon[END_REF]. In MOZ36, the temperature front signature of the anticyclonic Mozambique Rings seems to be limited to the upper layers of the water column. However, some discrete observations [START_REF] De Ruijter | Observations of the flow in the mozambique channel: Observations in the mozambique channel[END_REF] and MOZ36 modelled current [START_REF] Miramontes | The influence of bottom currents on the zambezi valley morphology (mozambique channel, sw indian ocean): In situ current observations and hydrodynamic modelling[END_REF] have shown that the dynamics of the Mozambique Rings could indeed reach the bottom. It is still unclear why the temperature front signature of these anticyclonic rings remains weak below 500 m while their associated currents have been previously reported at much deeper levels in the model.

Seasonal variability

Our EKE mean maps (Figure 4) and seasonal variability analysis (Figure 9 Seasonal variability in the MC ceases to be significant below -150 m for the Islands subregion, below -350 m and -450 m for the NMC and SMC subregions (respectively) and below -70 m in the Agulhas subregion (Figure 3). This is aligned with the types of fronts that characterize each subregion, as summarized in Table 1. The NMC and SMC subregions are eddy-rich subregions generating mostly ADF and CDF fronts which are more likely to reach deeper in the water column than topographic fronts, and thus propagate surface seasonal signals at depth. We suspect this explains why the seasonal variability in the NMC and SMC subregions reaches deeper layers in the water column. Potential drivers of the seasonal variability for each region are summarized in Table 2.

Islands and NMC subregions

In the Islands and NMC regions, SST front intensity climatology shows two local maxima: a moderate one in May and a greater one in November (Figure 7). A similar semi-annual cycle at the Seychelles Chagos thermocline ridge [START_REF] Hermes | Annual cycle of the South Indian Ocean (Seychelles-Chagos) thermocline ridge in a regional ocean model[END_REF] suggests that the Seychelle-Chagos upwelled waters might be one of the possible drivers of temperature front seasonal variability at the surface of both northernmost regions. Additionally, the presence of "cool water" events near Angoche during August to March [START_REF] Malauene | Cool, elevated chlorophyll-a waters off northern mozambique. Deep-sea[END_REF], and upwelling along the Mozambican coast at 11-16°S during the North East monsoon (November-March) [START_REF] Saetre | The circulation of the mozambique channel. Deep-sea[END_REF] could explain the higher intensity of the second peak in austral spring and summer, especially in the NMC. Another driver behind the local winter maximum could be the elevated EKE in this area responding to the seasonal increase of the NEMC (Figure 9) [START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF].

In the Islands subregion, the -100 m front intensity is greater than at the surface and peaks in late austral autumn. The signature 2-peak of the surface signal has disappeared entirely, leaving only one clear maximum in May-June (Figure 7). This suggests that the -100 m fronts may not be driven by the same processes than the surface ones. Since most fronts in the Islands region belong to the topographic class, and since the NEMC peaks in austral winter [START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF], -100 m temperature fronts in the Islands region seem to be driven solely by seasonal variations of the NEMC and its subsequent interactions with the local topography.

In the NMC area, the -100m front intensity is higher than at the surface and peaks in austral summer, with a second local maximum in austral winter (Figure 7). Those two peaks can be explained by the types of front predominantly found in this region: topographic fronts, and especially ADF (Table 1). On the first hand, as seen in the Islands subregion, topographic fronts follow the variability of the NEMC, which is stronger in austral winter [START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF], explaining the winter peak of frontal activity. On the other hand, ADF are shaped at the edge of anticyclonic eddies forming in this region [START_REF] Schouten | Eddies and variability in the mozambique channel. Deep-sea[END_REF][START_REF] Halo | Eddy properties in the mozambique channel: A comparison between observations and two numerical ocean circulation models[END_REF] and are thus likely linked to variations of EKE, which would explain the frontal activity maximum in austral summer, coinciding with peaks of EKE (Figure 9)

At -500 m and -1000 m, there is not much seasonal variation anymore and frontal activity weakens with depth (Figure 9). This is consistent with our preliminary front typology since ADF and topographic fronts, which represent the majority of fronts in Islands and NMC regions, have been found to present a weak deep signature.

SMC and Agulhas subregions

The FFT periodograms of the two southernmost subregions show that the yearly signal is stronger than the biannual one (Figure 6). The weaker biannual signal can be explained by the lesser influence of the monsoon below 20°S [START_REF] Schott | Indian Ocean circulation and climate variability[END_REF]. The climatology of surface temperature front intensity in the SMC and Agulhas regions (Figure 7) shows stronger frontal activity during austral winter and spring which coincides with upwelling cells at the southern tip of Madagascar driven by the SEMC [START_REF] Ho | Seawifs observations of upwelling south of madagascar: long-term variability and interaction with east madagascar current. Deep-sea[END_REF][START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF] and the local winds [START_REF] Lutjeharms | An upwelling cell inshore of the east madagascar current. Deep-sea[END_REF][START_REF] Dimarco | Satellite observations of upwelling on the continental shelf south of madagascar[END_REF].

Frontal activity in the SMC and Agulhas regions also show a slight increase around December (Figure 7). One possible explanation is the Angoche upwelling cell, which brings cooler water to the surface in austral summer [START_REF] Malauene | Cool, elevated chlorophyll-a waters off northern mozambique. Deep-sea[END_REF].

Another possible driver could be the eddy activity, which peaks in austral summer in these regions. Indeed, since the SMC and Agulhas regions seems to host mostly CDF and topographic fronts, it is likely that the temperature front variability in these regions depends on EKE variability.

In the SMC at -100m depth, the first local maximum in austral summer (Figure 7) coincides with a -100 m EKE peak (Figure 9), which suggests that frontal activity there is driven by MC eddies. The second peak in austral winter can be attributed to the local upwelling cells south of Madagascar island [START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF], which was also the main driver of surface frontal activity in this region. In the Agulhas region, the -100 m front climatology (Figure 7) shows much weaker seasonal variation, also seen on the FFT analysis (Figure 6), with a slight maximum in austral winter, when the South Madagascar upwelling cells are most active [START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF]. The absence of austral summer peak, like it is observed in NMC and SMC, can be explained by the comparably weaker EKE seasonal variations in the Agulhas region (Figure 9). It is worth noting that the FFT analysis (Figure 6, and Figure S6) does not show a clear annual or bi-annual period for the SMC and Agulhas regions from -100 m depth and below, which could be linked to the higher inter-annual variability observed in this region [START_REF] Palastanga | A link between low-frequency mesoscale eddy variability around madagascar and the large-scale indian ocean variability[END_REF].

-500 m and -1000 m fronts in the SMC and Agulhas subregions are more intense than in the Islands and NMC at the same depth, possibly due to the specific typology of fronts most often encountered in the south MC (Table 1). In the SMC and Agulhas, the majority of fronts belong to the CDF category, which have a stronger depth signature, hence the greater -500 and -1000 m front intensity compared to regions where ADF dominate.

Finally, a modest peak at about 4-month can be identified in the FFT analysis periodograms (Figure 6), especially at the surface of the Islands, SMC and Agulhas subregions. This could be attributed to Indian Ocean basin resonance characterized by 120-day period, as detected by both idealized and realistic models [START_REF] Han | Basin resonances in the equatorial indian ocean[END_REF].

Main drivers of frontogenesis in the MC

We have thus documented thermal front seasonal variability in the MC. The next section addresses the relative importance of the main drivers of frontogenesis in the region. A clear distinction between those physical processes would require carrying dynamical diagnostics such as eddy kinetic budgets [e.g., [START_REF] Conejero | Enso diversity driving low-frequency change in mesoscale activity off peru and chile[END_REF]], eddy kinetic energy decompositions [e.g., Martínez-Moreno et al. (2019;2022] or frontogenesis function decompositions [e.g., [START_REF] Koseki | Frontogenesis of the angola-benguela frontal zone[END_REF]] based on the model outputs, which would fall beyond the scope of this work. We nonetheless argue that thermal fronts in the MC depends on mean and seasonal circulation, seasonal upwellings and variations of EKE. To do so, we first define our seasonal division: In the Mozambique Channel monsoon reversals occur first in April to June and then in October to November, marking the separation between winter and summer [START_REF] Collins | The dynamics and physical processes of the Comoros basin[END_REF][START_REF] Obura | Chapter 4 -The Northern Mozambique Channel, World Seas: an Environmental Evaluation[END_REF]. We thus define winter as the period from April to September, and summer as the period from October to March.

Mean circulation

We can infer the role of the mean circulation on thermal front intensity (especially on the quasi-permanent fronts since no seasonal variability is involved here) from mean maps of surface current (northward and eastward velocities) and SST generated by the MOZ36 configuration (Figure S7). From the mean SST map (Figure S7.B), we can observe a strong thermal front at the northern tip of Madagascar, following the path of the North East Madagascar Current (NEMC), also visible in the mean current map (Figure S7.A) and the mean thermal front intensity (Figure 2). Similarly at the southwestern tip of Madagascar, a strong thermal front follows the path of the South East Madagascar Current (SEMC) toward the Agulhas current. Additionally, we can identify along-shelf thermal gradients of moderate intensity at the southeastern tip of Madagascar and off Maputo (Delagoa Bay), which are probably due to quasi-permanent coastal upwelling cells [START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF], as well as a colder tongue extending along the outer parts of the Sofala Bank, which could be indicating the presence of a quasi-permanent shelfbreak upwelling there, as documented by [START_REF] Hill | A theory of upwelling over the shelf break[END_REF]; [START_REF] Gibbs | Observations and simulations of a transient shelfbreak front over the narrow shelf at sydney, southeastern australia[END_REF] and [START_REF] Rossi | Effect of the wind on the shelf dynamics: Formation of a secondary upwelling along the continental margin[END_REF].

Seasonal upwellings

Seasonal upwelling cells such as the Seychelles-Chagos upwelling [START_REF] Hermes | Annual cycle of the South Indian Ocean (Seychelles-Chagos) thermocline ridge in a regional ocean model[END_REF], the Angoche upwelling [START_REF] Malauene | Cool, elevated chlorophyll-a waters off northern mozambique. Deep-sea[END_REF] and, to a lesser extent, the South Madagascar upwelling cells [START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF] mentioned in this work are strongly localized in space and time. The Seychelles-Chagos upwelling turns on in austral winter [START_REF] Hermes | Annual cycle of the South Indian Ocean (Seychelles-Chagos) thermocline ridge in a regional ocean model[END_REF], while the Angoche upwelling is active during the August-March period [START_REF] Malauene | Cool, elevated chlorophyll-a waters off northern mozambique. Deep-sea[END_REF]. The first upwelling core south of Madagascar is present all year round but reaches its maximum at the end of austral winter, while the second (much weaker) core is most active from October to January [START_REF] Ramanantsoa | Coastal upwelling south of madagascar: Temporal and spatial variability[END_REF]. In the Islands and NMC regions, the mean thermal front intensity peaks first in May-June (Figure 7), which corresponds to the first active period of the Seychelles-Chagos upwelling system. This front intensity peak is mostly felt in the Islands subregion which is closest to the Seychelles-Chagos upwelling cell. We thus postulate that this first front intensity peak at surface and -100 m depth in both Islands and NMC subregions depends on the Seychelles-Chagos upwelling system. The second peak of frontal intensity in the same two northern subregions happens in November-December (Figure 7), and especially in the NMC region. We argue that this second peak is driven first by the Angoche upwelling and to a lesser extent by the Seychelles-Chagos upwelling. The seasonality of this second peak coincides with the Angoche most active period, which is located in the NMC, and the second (weaker) upwelling maximum in the Seychelles-Chagos located further upstream. The South Madagascar upwelling cells reach their maximum in winter, when the thermal front intensity peaks in both NMC and Agulhas subregions Figure 7). It thus suggests that the South Madagascar upwelling cells play an important role in the increased front intensity documented in the southernmost subregion during winter.

Seasonal current and EKE variability

Some quasi-permanent thermal fronts are found in the path of the NEMC, the SEMC and the Mozambique Current. The seasonal variability of these currents induces in turn variability of instabilities. We suggest that these instabilities, in turn, produce the sub to mesoscale activity that affects the intensity of those thermal fronts. The NEMC, and the EKE associated to its instabilities, are both stronger in winter (Figure S8 and S9), which also corresponds to a higher thermal front intensity in the northern Islands subregion, especially at -100 m (Figure S10 and S11). The Mozambique Current and the EKE in the western MC are stronger in summer (Figure S8 and S9), which also corresponds to higher thermal front intensity in the western half of the MC, especially in NMC and SMC subregions (Figure S10 and S11).

Finally, the suspected main drivers of seasonal variability of thermal front intensity, for each season and each subregion, and at both surface and -100 m, are summarized in Tables 2 andTable S1.

Conclusion and perspectives

We presented here the first thermal front seasonality analysis in the Mozambique Channel from the surface down to -1000 m depth. This work demonstrates that front dynamics in the MC are complex, and we suggest several possibilities to link temperature front seasonal variability to regional and remote ocean dynamics. Temperature fronts are generally more intense and more likely to occur over continental shelves, in the wake of the NEMC and SEMC, on the lee of islands, and at the edge of eddies. We show that temperature front intensity peaks below the mixed layer, between -100 and -200 m depth, which indicates that they are largely associated to aspects of the ocean dynamics rather than to mixed-layer processes. This consistent with the energetic mesoscale dynamics in this region.

Seasonal variations are felt down to -150 m in the Islands subregion, -350 m and -450 m in the NMC and SMC subregions (respectively) and -70 m in the Agulhas subregion. We argue that the main drivers of thermal front seasonal variability in the MC are upwelling cells (Angoche, South Madagascar, Seychelles-Chagos), current seasonal variability (NEMC, SEMC, and the Mozambique Current) and variations in EKE.

Since the MC circulation is connected to equatorial circulation in the Indian ocean, it is expected that temperature fronts experience fluctuations at interannual timescales. The Indian Ocean Dipole (IOD) seems to affect the variability of the transport [START_REF] Ridderinkhof | Seasonal and interannual variability in the mozambique channel from moored current observations[END_REF] and the SSH in the channel [START_REF] Palastanga | A link between low-frequency mesoscale eddy variability around madagascar and the large-scale indian ocean variability[END_REF] through planetary wave propagation. A positive (negative) IOD event is linked to a weaker (stronger) NEMC [START_REF] Ridderinkhof | Seasonal and interannual variability in the mozambique channel from moored current observations[END_REF] which could potentially affect the intensity of fronts in the Islands and NMC subregions through fluctuations in current instabilities. Additionally, a change in SSH would also modulate the interactions between currents at the entrance or within the MC, which affects not only the EKE in the MC [START_REF] Palastanga | A link between low-frequency mesoscale eddy variability around madagascar and the large-scale indian ocean variability[END_REF] but also the production of temperature front at the edge of eddies.

Another relevant path of investigation is suggested by Martıńez-Moreno et al. (2021) in their global multidecadal study on altimetry and SST satellite-based observations. Their analysis shows that, even though SST gradients in the northern part of the MC have generally weakened between 1993 and 2020, the EKE has significantly increased during the same period in the northern MC and decreased in the southwest MC. This multidecadal trend suggests that climate change could have a significant impact on eddy-driven frontogenesis in the channel, as temperature fronts could be weaker but more numerous. [START_REF] Li | Increasing ocean stratification over the past half-century[END_REF] have also demonstrated a significant increase of stratification over the past half-century in the MC, especially in the Islands and NMC subregions. This suggests a possible enhancing of frontal activity due to climate change, especially in the two northernmost subregions, yet to be studied.

Thermal fronts, within and below the mixed layer, are thought to create transitory biodiverse hotspots across all trophic levels. Our analyses of their variability sheds light on where and when they are the strongest, with each subregion behaving differently. Altogether, it provides critical insights about where, horizontally and vertically, it is more relevant to survey bio-physical interactions and to consider protection initiatives in the MC. Conservation stakeholders could indeed use our synthetic analyses of front spatial and seasonal variability to elaborate rules for an adaptive and dynamic management of both epipelagic and mesopelagic realms, as also suggested in [START_REF] Brito-Morales | Climate velocity reveals increasing exposure of deep-ocean biodiversity to future warming[END_REF] work on climate velocities. More research is needed to better apprehend climate change implications for front variability and their associated biological impacts to design an effective and climate-resilient network of pelagic and coastal marine reserves in the MC.

1

 1 FIGURE 1Major currents in the Mozambique Channel, its 4 subregions (A), and their respective EKE climatology (B-E). The subregions are defined in the text as "Islands" (10°S-13.5°S), "North Mozambique Channel" (NMC: 13.5°S-20°S), "South Mozambique Channel" (SMC: 20°S-25°S) and "Agulhas" (25°S-30°S). The major currents, South Equatorial Current (SEC), North East Madagascar Current (NEMC), South East Madagascar Current (SEMC) and the Agulhas Current (AC) are indicated by arrows. The background contours represent isobaths at -200, -1000, -2000, -3000 and -4000 m.

2

 2 FIGURE 2 Mean surface temperature front intensity (A, C) and probability (B, D) for MOZ36 (A, B) and MUR SST (C, D).

•

  Topographic fronts, as defined by McWilliams McWilliams, (2021) are formed where currents encounter land masses or other sharp topographic changes such as seamounts. In this study, topographic fronts are found along Mozambique and Madagascar shelves and around islands (French Scattered Islands, Comoros Archipelago), they reach maximum intensity at -100 m. NEMC and SEMC paths can clearly be identified from the front intensity patterns at the north and south tips of Madagascar Island (Figure 4). • The next two types of fronts correspond to the "deformation fronts" in McWilliams's typology. They form at the edge of eddies. • Anticyclonic deformation fronts (ADF) are located at the edge of anticyclonic eddies (AE) in the MC. AE usually form at the entrance of the Angoche Valley at 15°S and travel southward close to the Mozambican shelf to then merge or dissipate around 22°S and feed the Agulhas Current. ADF reach their maximum intensity at around -100 m and then weaken substantially at -500 m, to disappear completely by -1000 m. • Cyclonic deformation fronts (CDF) form at the edge of cyclonic eddies (CE), generally south of 23°S. Most of those CE are driven by the SEMC: some go slightly northward up the southern tip of the Madagascar shelf, but most go southwest following the SEMC track towards the Agulhas current. CDF reach their maximum intensity at -500 m and can still be detected at -1000 m.

FIGURE 3

 3 FIGURE 3

  FIGURE 4 Mean temperature front intensity (A, C, E, G) and EKE (B, D, F, H) from MOZ36 at the surface (A, B), -100 m (C, D), -500 m (E, F) and -1000 m (G, H).

Fast

  FIGURE 6Fast Fourrier Transform analysis periodograms of MOZ36 front intensity in the 4 subregions: Islands (A, E), NMC (B, F), SMC (C, G), Agulhas (D, H) and at two depths: surface (A-D), -100 m (E-H). The dashed vertical lines represent periods of 6 and 12 months. -500 m and -1000 m periodograms are not shown here because they did not show any significant magnitude peak, they are available as Supplementary Material, FigureS6.

  FIGURE 7 Temperature front intensity climatology for each subregion at surface (A-D), -100 m (E-H), -500 m (I-L), -1000 m (M-P). At surface (A-D), data from MOZ36 (full line) and from SST MUR (dashed line) are represented. Please note the different y axis range.

  ) in the MC are consistent with Martıńez-Moreno et al. (2022) work on EKE seasonality in the Southern Hemisphere.

  FIGURE 9 MOZ36 EKE climatology for each subregion at surface (A-D), -100 m (E-H), -500 m (I-L), -1000 m (M-P). Please note the different y-axis range.

TABLE 1

 1 Front typology based on behavior and depth signatures.

TABLE 2

 2 Summary of the main drivers of thermal front seasonal variability in the Mozambique Channel, at surface and -100 m.

		Surface
		Summer	Winter
	Islands	Angoche upwelling + Mozambique Current + EKE (western MC)	Seychelles-Chagos upwelling + NEMC + EKE (Comoros basin)
	NMC	Angoche upwelling + Mozambique Current + EKE (western MC)	Seychelles-Chagos upwelling + NEMC + EKE (Comoros basin)
	SMC	Angoche upwelling + Mozambique Current + EKE (western MC)	Seychelles-Chagos upwelling + South Madagascar upwelling
	Agulhas	Angoche upwelling + Mozambique Current + EKE (western MC)	SEMC + EKE (SW madagascar) + South Madagascar upwelling
		100m
		Summer	Winter
	Islands	n/a	Seychelles-Chagos upwelling + NEMC + EKE (Comoros basin)
	NMC	Angoche upwelling + Mozambique Current + EKE (western MC)	Seychelles-Chagos upwelling + NEMC + EKE (Comoros basin)
	SMC	Angoche upwelling + Mozambique Current + EKE (western MC)	Seychelles-Chagos upwelling + South Madagascar upwelling
	Agulhas	Mozambique Current + EKE (western MC)	South Madagascar upwelling

Frontiers in Marine Science frontiersin.org

Acknowledgments

This work was supported by the Mediterranean Institute of Oceanography (MIO) and the French National Institute for Sustainable Development (IRD). The authors wish to thank J. Lecubin and C. Yohia for technical assistance with the local high performance computers and two reviewers for their helpful and constructive comments.

Data availability statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Author contributions

FS with VR, BD, and VG designed the study. PP provided MOZ36 model output, and guidance for model analyses. JS retrieved the remotely sensed MUR SST data. FS produced the front database and subsequent analysis of the results. CM assisted with the High Performance Computing. VR, BD, and VG supervised the findings of this work and provided critical feedbacks. FS produced the figures and wrote the manuscript with input from all authors. All authors contributed to the article and approved the submitted version.

Funding

The authors acknowledge funding from the "Ocean Front Change" project, funded by the Belmont Forum and implemented through the French National Research Agency (ANR-20-BFOC-0006-04).

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

Supplementary material

The Supplementary Material for this article can be found online at: https://www.frontiersin.org/articles/10.3389/ fmars.2022.1045136/full#supplementary-material