# New observations confirm the progressive acidification in the Mozambique Channel

Nicolas Metzl, Claire Lo Monaco, Aline Tribollet, Jean-François Ternon, Frédéric Chevallier, Marion Gehlen

► To cite this version:

Nicolas Metzl, Claire Lo Monaco, Aline Tribollet, Jean-François Ternon, Frédéric Chevallier, et al.  
New observations confirm the progressive acidification in the Mozambique Channel. Biogeosciences,  
2025, 22 (22), pp.7187 - 7204. 10.5194/bg-22-7187-2025. hal-05404451

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# New observations confirm the progressive acidification in the Mozambique Channel

Nicolas Metzl<fnref n="1" />, Claire Lo Monaco<fnref n="1" />, Aline Tribollet<fnref n="1" />, Jean-François Ternon<fnref n="2" />, Frédéric Chevallier<fnref n="3" />, and Marion Gehlen<fnref n="3" />

**Correspondence:** Nicolas Metzl (nicolas.metzl@locean.ipsl.fr)

Received: 18 July 2025 – Discussion started: 29 July 2025

Revised: 7 October 2025 – Accepted: 3 November 2025 – Published: 25 November 2025

**Abstract.** New observations obtained in 2021 and 2022 are presented and used to investigate the trend of the carbonate system (including pH~T~ and aragonite saturation state, Ω~ar~) in the southern sector of the Mozambique Channel. Using historical and new data in April–May we observed an acceleration of the acidification ranging from −0.012 decade⁻<fnref n="1" /> in 1963–1995 to −0.027 (±0.003) decade⁻<fnref n="1" /> in 1995–2022. Result from a neural network (FFNN) model for all seasons also suggests faster pH trend in recent decades, −0.011 decade⁻<fnref n="1" /> over 1985–1995 and −0.018 decade⁻<fnref n="1" /> over 1995–2022. In May 2022 we estimated Ω~ar~ of 3.49, about 0.3 lower than observed in May 1963 (Ω~ar~ = 3.86). The lowest Ω~ar~ value of 3.23 was evaluated from the FFNN model in September 2023 that corresponds to the hypothetical critical threshold value (3.25) for coral reefs. In 2025 a marine heat wave was observed in this region (sea surface temperature up to 30 °C) and data from a BGC-Argo float indicate that sea surface pH was the lowest in January 2025 (pH~T~ = 7.95) whereas Ω~ar~ was the lowest in March 2025 (Ω~ar~ = 3.2). A projection of the C~T~ concentrations based on observed anthropogenic CO₂ in subsurface water and future anthropogenic CO₂ emissions scenario, suggests that a risky level for corals (Ω~ar~ < 3) could be reached as soon as year 2034.

## 1 Introduction

The ocean plays a major role in reducing the impact of climate change by absorbing more than 90% of the excess heat in the climate system (Cheng et al., 2025; Forster et al., 2025) and about 25% of human released CO₂ (Friedlingstein et al., 2025). The oceanic CO₂ uptake also changes the chemistry of seawater reducing its buffering capacity (Revelle and Suess, 1957) and leading to a process known as ocean acidification (OA) with potential impacts on marine organisms and ecosystems (Fabry et al., 2008; Doney et al., 2009, 2020; Gattuso et al., 2015; Schönberg et al., 2017; Cornwall et al., 2021). Global ocean models or Earth System Models predict that, due to future anthropogenic CO₂ emissions and global warming, the sea surface pH could decrease by 0.4 and aragonite saturation state (Ω~ar~) could be as low as 3 in the tropics by 2100 (Hoegh-Guldberg et al., 2007; Kwiatkowski et al., 2020; Jiang et al., 2023; Findlay et al., 2025). However, current global ocean models cannot fully replicate observations and not yet simulating all processes that govern ocean acidification (e.g. seasonal cycles of C~T~ and A~T~, accumulation of C~ant~, etc.). Long-term observations of the carbonate system are needed to compare and validate model results (Tilbrook et al., 2019).

The first estimate of the decadal pH change based on CO₂ fugacity (fCO₂) observations in the global ocean (using SOCAT data, Bakker et al., 2014) suggests a decrease of pH ranging between −0.003 decade⁻<fnref n="1" /> (±0.005) in the North Pacific and −0.024 decade⁻<fnref n="1" /> (±0.005) in the Indian Ocean over 1981–2011 (Lauvset et al., 2015). Re-

<footnote n="1">¹Laboratoire LOCEAN/IPSL, Sorbonne Université-CNRS-IRD-MNHN, Paris, 75005, France</footnote>

<footnote n="2">²MARBEC, Université de Montpellier, CNRS, Ifremer, IRD, 34203 Sète, France</footnote>

<footnote n="3">³Laboratoire LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay Gif-sur-Yvette, 91191, France</footnote>
construction methods also based on SOCAT observations evaluated a global ocean decrease of pH in surface waters of -0.0181 (±0.0001) decade⁻¹ (Iida et al., 2021), -0.0166 (±0.0010) decade⁻¹ (Ma et al., 2023) and -0.017 (±0.004) decade⁻¹ (Chau et al., 2024). These studies also highlighted the regional differences of the pH and aragonite saturation state (Ωar) trends. This calls for dedicated studies at regional scale in order to better interpret the inter-annual to multi-decadal changes of the oceanic carbonate system as the trends and associated uncertainties depend on the data available. Compared to other basins, observations are sparse in the Indian Ocean (Lauvset et al., 2015; Bakker et al., 2016, 2024). However, thanks to a new cruise conducted in 2019, it has been shown that the Mozambique Channel experienced an acceleration with respect to the acidification in recent years, a pH trend of -0.023 decade⁻¹ (±0.005) over 1995–2019 (Lo Monaco et al., 2021). In a more recent analysis Chakraborty et al. (2024) used several methods, including a high resolution model dedicated to the Indian Ocean and found an acceleration of the pH trend of -0.011 (±0.00) decade⁻¹ in 1980–1989 to -0.019 (±0.004) decade⁻¹ in 2010–2019. Both studies concluded that strengthening of acidification trend was mainly driven by ocean CO₂ uptake.

In this study, we present new data obtained in January 2021 and April–May 2022 in the Mozambique Channel and used the results of a FFNN model (Chau et al., 2024) extended to 2023 to explore the decadal trends of the carbonate system over 1963–2023. We also use these data to validate a projection of the acidification in the near future. To highlight CO₂ source anomalies when the ocean was exceptionally warm, results from a BGC-Argo float in the Mozambique Channel in 2024–2025 are also presented.

# 2 Data selection and methods

## 2.1 Data selection

To explore the long-term change of the carbonate system in this region, we selected the fCO₂ SOCAT data, version v2024 (Bakker et al., 2016, 2024). With recent cruises conducted on-board the ship Marion-Dufresne in January 2021 (OISO-31) and April–May 2022 (RESILIENCE) this includes 10 cruises in the Mozambique Channel (Table 1 and Fig. 1). Some of these cruises were previously described to analyze the distribution air-sea CO₂ fluxes and pH changes in the Mozambique Basin and the African coastal zone (Metzl et al., 2025b). Here we focus on the data obtained in the southern Mozambique Channel. To complete the shipboard data after 2022 we also used data from a BGC-Argo float (WMO ID 7902123) that was launched onboard R/V *Sonne* in the Mozambique Channel in late 2024. During some cruises (2004, 2019 and 2021) continuous underway A_T and C_T measurements were also performed (data available in

Metzl et al., 2025a). These A_T and C_T data are used to compare and validate results of the pH trends based on fCO₂ data.

## 2.2 Methods

The methods for surface underway fCO₂ and A_T C_T measurements were described in previous studies (e.g. Lo Monaco et al., 2021). For fCO₂ measurements during OISO-11 (2004), CLIM-EPARSES (2019), OISO-31 (2021) and RESILIENCE (2022) cruises, sea-surface water was continuously equilibrated with a “thin film” type equilibrator thermostated with surface seawater (Poisson et al., 1993) and xCO₂ in the dried gas was measured with a non-dispersive infrared analyzer (NDIR, Siemens Ultramat 6F). Standard gases for calibration (around 280, 350 and 490 ppm) were measured every 6 h. The sea surface temperature (SST) and equilibrium temperature were measured using SBE21 and SBE38 probes (accuracy 0.002 °C) respectively. During the RESILIENCE cruise the difference of SST and equilibrium temperature was on average +0.088 ± 0.066 °C (n = 6416). For all cruises, the sea surface salinity (measured with SBE21) was regularly checked with discrete samples and has been corrected if some drift was observed. The fCO₂ in situ data were corrected for warming using corrections proposed by Copin-Montégut (1988, 1989). Note that when incorporated in the SOCAT data-base, the original fCO₂ data are recomputed (Pfeil et al., 2013) using temperature correction from Takahashi et al. (1993). Given the very small difference between equilibrium temperature and sea surface temperature, the fCO₂ data from SOCAT used in this analysis (Bakker et al., 2024) are almost identical (within 1 µm) to the original fCO₂ values.

During 3 cruises, in January 2004 (OISO-11), April 2019 (CLIM-EPARSES) and January 2021 (OISO-31), A_T and C_T were measured continuously in surface water using a potentiometric titration method (Edmond, 1970) in a closed cell. For calibration, we used the Certified Referenced Materials provided by Andrew Dickson (SIO, University of California). Based on repeatability from duplicate analyses of continuous sea surface sampling at the same location (when the ship was stopped) we estimated the accuracy for both A_T and C_T better than 4 µmol kg⁻¹ (Metzl et al., 2025a). The A_T and C_T data for these cruises are available at the Seanoe platform (https://doi.org/10.17882/102337, Metzl et al., 2024). These data offered comparisons and validation for the calculations of the carbonate system properties using fCO₂ data and A_T / Salinity relationship.

## 2.3 Carbonate system calculation and A_T / Salinity relationship

When two of the carbonate system properties are measured (here either fCO₂, A_T or C_T) they can be used to calculate other species and the saturation state of aragonite (Ωar). Here we used the CO₂sys program (version CO₂sys_v2.5,
<table><caption>**Table 1.** List of cruises in the Mozambique Channel from SOCAT-v2024 (Bakker et al., 2024).</caption><thead><tr><th>EXPOCODE</th><th>Month</th><th>Year</th><th>Reference or Principal Investigator</th></tr></thead><tbody><tr><td>31AR19630216</td><td>5</td><td>1963</td><td>Keeling and Waterman (1968)</td></tr><tr><td>316N19950611</td><td>6</td><td>1995</td><td>R. Key</td></tr><tr><td>33RO19990211</td><td>2</td><td>1999</td><td>R. Wanninkhof</td></tr><tr><td>49NZ20031209</td><td>12</td><td>2003</td><td>A. Murata</td></tr><tr><td>35MF20040106*</td><td>1</td><td>2004</td><td>Metzl (2009)</td></tr><tr><td>06BE20140710</td><td>7</td><td>2014</td><td>T. Steinhoff, A. Koertzinger</td></tr><tr><td>33RO20180423</td><td>4</td><td>2018</td><td>R. Wanninkhof, D. Pierrot</td></tr><tr><td>35MV20190405*</td><td>4</td><td>2019</td><td>Lo Monaco et al. (2021)</td></tr><tr><td>35MV20210113*</td><td>1</td><td>2021</td><td>Metzl et al. (2025b)</td></tr><tr><td>35MV20220420</td><td>4</td><td>2022</td><td>Metzl et al. (2025b)</td></tr></tbody></table>

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Left: Tracks of cruises in the Mozambique Channel in the SOCAT data-base, version v2024 (Bakker et al., 2016, 2024). This includes recent OISO-31 and RESILIENCE cruises in 2021 and 2022. Color code is for Year. Black circles identified the coral reefs locations. Right: Tracks of cruises near the coral reefs area. Figures produced with ODV (Schlitzer, 2018).</figcaption></figure>

Orr et al., 2018) with K1 and K2 dissociation constants from Lueker et al. (2000) and KSO4 constant from Dickson (1990). The total boron concentration is calculated according to Uppström (1974). When using fCO₂ data to derive pHₜ (pHₜ for Total Scale) or Cₜ, one needs Aₜ concentrations that can be derived from salinity (e.g. Millero et al., 1998). Here we used the Aₜ/Salinity relationship adapted to the Mozambique Channel (Lo Monaco et al., 2021).

$$ 
\begin{aligned}
A_T (\mu\text{mol kg}^{-1}) &= 73.841 (\pm 1.15) \cdot \text{SSS} \\
&\quad - 291.02 (\pm 40.4) \\
& (n = 548, r^2 = 0.88)
\end{aligned}
\qquad (1) 
$$

## 2.4 CMEMS-LSCE-FFNN model

The fCO₂ data are not available each year and only for few seasons (Table 1). To complete the observations we used the results from an ensemble of feed-forward neural network model (CMEMS-LSCE-FFNN or FFNN for simplicity here, Chau et al., 2024). Based on the SOCAT gridded datasets this model composes surface ocean carbonate system fields at 0.25 × 0.25 square degree resolution and monthly scale. The reconstructed fCO₂ is used to derive monthly surface Cₜ, pHₜ and aragonite and calcite saturation states, as well as air-sea CO₂ fluxes. A full description of the model is presented in Chau et al. (2024) and the datasets including uncertainties

<footnote>* For these cruises underway $A_T C_T$ data available at https://doi.org/10.17882/102337 (Metzl et al., 2024).</footnote>
are available under the DOI https://doi.org/10.48670/moi-00047 (Copernicus Marine Service, 2024a).

# 3 Results and discussion

## 3.1 A Repeated line in 2019 and 2022

In April 2019 and 2022 underway measurements were conducted for fCO₂. The measurements of A_T and C_T were also performed in 2019. The tracks of the cruises enabled to select the data obtained along the same track and for the same season in the southern Channel in order to compare the observations three years apart (Fig. 2). Given the variability observed around Europa Island and the front identified at 22.5° S in April 2019 (Fig. 2) the data were averaged in the band 23–26° S. The mean values over the same latitudinal band (23–26° S) show significant differences between 2019 and 2022 (Table 2). In 2022 the ocean was slightly colder and saltier. Consequently, A_T concentrations were also higher in 2022 but the salinity normalized A_T (N-A_T normalized at salinity 35) were the same with a difference of +1.1 µmol kg⁻¹. As expected, due to the CO₂ uptake, the oceanic fCO₂ and C_T concentrations were higher in 2022 and pH_T was lower. The increase of oceanic fCO₂ over 3 years (+7.9 µatm) was almost the same as in the atmosphere (+7.0 µatm). At constant A_T, salinity and temperature, the observed fCO₂ change would translate in an increase of +4.4 µmol kg⁻¹ for C_T when we observed an increase of +18 µmol kg⁻¹ (Table 2). We interpret this difference as being due to the regional circulation. In April 2019 southward currents would import low C_T and A_T whereas in April 2022 northward currents would transport colder and saltier waters with higher C_T and A_T. This reversed circulation is confirmed with the ADCP data recorded during the cruises as well as from the geostrophic currents (Metzl et al., 2022; Ternon et al., 2023).

For pH_T, the decrease of -0.005 over three years, i.e. -0.0017 yr⁻¹, is surprisingly close to what is generally observed at global scale and over several decades (-0.0017 ± 0.0004 yr⁻¹, Chau et al., 2024). Finally, we note that the difference between 2019 and 2022 measurements is much higher than that obtained when comparing measured and calculated A_T C_T values (Table 2). This confirms the use of fCO₂ data and adapted A_T/S relationship to derive the carbonate system properties in this region (Lo Monaco et al., 2021; Metzl et al., 2025b), and to explore the seasonal cycles and long-term trends described in the next sections.

## 3.2 Seasonal variations

In the Mozambique Channel, where SST presents large seasonal variations (up to 4 °C), fCO₂ is mainly controlled by temperature like in the Indian subtropics (e.g. Metzl et al., 1998; Takahashi et al., 2002; Bates et al., 2006). In this region, observations are not available for all seasons (Table 1) but the seasonal range derived from the climatology

(Fay et al., 2024) or the FFNN model (Chau et al., 2024) is coherent compared to the data (Figs. 3, S1). The observations and the models indicate that between January and July fCO₂ decreases by about 50 µatm while pH_T increases (0.03 to 0.04 units). This is a large signal compared to the expected decadal change (about +20 µatm decade⁻¹ for fCO₂ and -0.017 decade⁻¹ for pH_T); therefore, to derive and interpret the trends, data have to be selected for the same season. As opposed to fCO₂, C_T presents lower concentrations in February–April and higher ones in July–August (Fig. 4). When the mixed-layer depth (MLD) is shallow in December–March the decrease of C_T is probably linked to biological activity but this is not clearly quantified (Lo Monaco et al., 2021). The progressive C_T increase of about +30 µmol kg⁻¹ from March to August is likely driven by vertical mixing when MLD is deeper in austral winter (Fig. 4).

This seasonality was well observed from repeated measurements at stations located along 25° S in June 1995 and December 2003 (Fig. S2). In June 1995 when the MLD reached 80 m, C_T concentrations were homogeneous within the MLD layer. The same was true for the anthropogenic CO₂ concentrations (C ant) here evaluated using the TrOCA method (Touratier et al., 2007). On the opposite, in December 2003, when the MLD was shallower, C_T presented a sharp increase within the subsurface layer whereas C ant concentrations were unrealistic in surface seawaters. Although from 1995 to 2003 the C_T concentrations would increase by around +7 µmol kg⁻¹ due to the anthropogenic CO₂ uptake in that region (Murata et al., 2010; Metzl et al., 2025b), N-C_T (normalized C_T at salinity 35) in June 1995 were almost the same as in December 2003 coherent with the seasonal cycle derived from the climatology (Fig. 4).

The seasonal variations of fCO₂ and pH_T in the Mozambique Channel appear thus linked to both temperature and mixing process with competition between the two drivers (Fig. S3). In addition to the rising atmospheric CO₂, these two processes probably also drive inter-annual, decadal and long-term change of fCO₂ and pH_T in the region as the Indian Ocean experienced a pronounced warming (Cheng et al., 2025). Specifically, in the southern Mozambique Channel the SST has increased by +0.11 ± 0.009 °C per decade since the 1960s (Fig. S4), a signal that should be taken into account when interpreting the decadal trends of carbonate properties and CO₂ fluxes. In January 2025 the SST anomaly reached +1.6 °C at 25° S in the Channel.

## 3.3 Trends in the Southern Mozambique Channel (1963–2023)

In this region, the ocean is a permanent CO₂ sink leading to a gradual increase of C_T concentrations and decrease of pH_T. The air-sea CO₂ flux derived from the FFNN model is on average -0.249 (±0.063) mol C m⁻² yr⁻¹ (Fig. 5) in the range of the climatology (-0.3 mol C m⁻² yr⁻¹, Fay et al., 2024).
<figure><img src="image_4.png" /><figcaption>**Figure 2.** Distribution of measured fCO₂ (µmol kg⁻¹), calculated C_T (µmol kg⁻¹) and calculated pH_T (TS) along a repeated track in April 2019 (blue) and April 2022 (red) in the southern Mozambique Channel. The dashed red line is for atmospheric fCO₂ in 2022. The underway C_T measurements in 2019 are also shown (open circles) as well as pH_T calculated using measured A_T and C_T. Average values for the latitudinal band 23–26° S are presented in Table 2.</figcaption></figure>

The FFNN model also suggests that the sink reinforced over 2016–2021 with a perceptible faster increase of C_T (Fig. S5).

### 3.3.1 Decadal trend from fCO₂ and A_T C_T data: January 2004 and 2021

We started the analysis of the decadal change by comparing observations obtained in January 2004 and 2021 when data were available for both underway fCO₂, A_T and C_T measurements. The comparison is focused along the tracks occupied in the same region (27–29° S/40–43° E, Fig. 6, Table 3). For both cruises the differences between measurements and calculations are in the range of the errors in the CO₂sys calculations (errors on measurements and constants K₁, K₂, Orr et al., 2018). For example, in January 2004 the pH_T calcu-

lated with A_T and C_T measurements was 8.069 against 8.064 when using the fCO₂ data and the A_T/S relationship. In 2021 the pH_T were respectively 8.030 and 8.032 (Table 3). For C_T the difference between calculated and measured C_T was only 4.4 µmol kg⁻¹ in 2004 and −1.9 µmol kg⁻¹ in 2021 when the observed increase over 17 years is around 28 µmol kg⁻¹. We noticed that in 2021, the properties present a high variability along the track linked to the presence of eddies. The C_T and A_T concentrations could vary by about 20 to 40 µmol kg⁻¹ at meso-scale but this has a small impact on calculated fCO₂ and pH_T, and when properties are averaged along the track (Table 3). For both periods the ocean fCO₂ was close to atmospheric CO₂, i.e. near equilibrium (fCO₂ocean-fCO₂atm = ΔfCO₂ = −0.04 ± 3.11 µatm in 2004 and 0.37 ± 10.04 µatm in 2021). Although there were some differences of pH_T
<table><caption>**Table 2.** Mean values of underway sea surface observations and their difference obtained along the same track in 2019 and 2022 in the region 23–26° S (see Fig. 2). Nb is the number of data. Standard-deviations are in bracket. For 2019 (CLIM-EPARSES cruise), the results from underway $A_T-C_T$ measurements are listed allowing calculation of $fCO_2$ and pH based on the $A_T-C_T$ pairs which permit comparisons with those derived from $fCO_2$ measurements.</caption><thead><tr><th>Cruise Period</th><th>Nb</th><th>SST °C</th><th>SSS -</th><th>A<sub>T</sub> µmol kg<sup>-1</sup></th><th>C<sub>T</sub> µmol kg<sup>-1</sup></th><th>fCO<sub>2</sub> µatm</th><th>pH<sub>T</sub> TS</th><th>Atm. xCO<sub>2</sub> ppm</th></tr></thead><tbody><tr><td>RESILIENCE fCO<sub>2</sub> April 2022</td><td>282</td><td>26.765 (0.608)</td><td>35.423 (0.048)</td><td>2324.6 (3.6)</td><td>2002.0 (5.0)</td><td>394.8 (3.4)</td><td>8.047 (0.003)</td><td>414.7</td></tr><tr><td>CLIM-EPARSES fCO<sub>2</sub> April 2019</td><td>294</td><td>27.497 (0.341)</td><td>35.288 (0.084)</td><td>2314.7 (6.2)</td><td>1984.0 (7.5)</td><td>386.9 (4.9)</td><td>8.053 (0.004)</td><td>407.5</td></tr><tr><td>CLIM-EPARSES A<sub>T</sub>-C<sub>T</sub> April 2019</td><td>70</td><td>27.401 (0.390)</td><td>35.272 (0.099)</td><td>2314.2 (6.7)</td><td>1986.1 (8.8)</td><td>389.7 (7.4)</td><td>8.050 (0.006)</td><td></td></tr><tr><td>Difference Method 2019</td><td></td><td>+0.096</td><td>+0.016</td><td>+0.5</td><td>-2.1</td><td>-2.9</td><td>+0.002</td><td></td></tr><tr><td>Difference 2022–2019</td><td></td><td>-0.732</td><td>+0.135</td><td>+10.0</td><td>+18.0</td><td>+7.9</td><td>-0.005</td><td>+7.2</td></tr></tbody></table>

<figure><img src="image_5.png" /><figcaption>**Figure 3.** Seasonal cycle of (a) $fCO_2$ (µatm) and (b) $pH_T$ in the southern Mozambique Channel (24–30° S). Average observations are presented for each cruise (colored circles). The full seasonal cycles are shown for the monthly climatology (reference year 2010, Fay et al., 2024) and for the FFNN model for years 2010 and 2022 with respective error bars.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 4.** Seasonal cycle of $C_T$ (µmol kg$^{-1}$) in the southern Mozambique Channel (24–30° S). Average observations are presented for each cruise (colored circles). The full seasonal cycles are shown based on the monthly climatology for a reference year 2010 (Fay et al., 2024) and the FFNN-LSCE model for year 2010 (Chau et al., 2024). The mixed-layer depth (MLD in m, blue line) is averaged in this region (from multi-year reprocessed monthly data, ARMOR3D L4, https://doi.org/10.48670/moi-00052, Copernicus Marine Service, 2024b).</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>**Figure 5.** Time-series of air-sea CO₂ flux (black, negative for ocean sink) and $C_T$ concentration (red) averaged in the southern Mozambique Channel (24–30° S) based on the FFNN-LSCE model over 1985–2023. For $C_T$, the result is presented with a 36-month running mean. Also shown is the climatological value of the flux for year 2010 in this region (red circle, Fay et al., 2024).</figcaption></figure>

calculated from the two data-sets (underway fCO₂ or $A_T$ $C_T$ data), the estimated pH_T change of -0.032 or -0.040 over 17 years was large compared to the uncertainty of the CO₂sys calculation. This would correspond to a pH_T trend varying between -0.0019 and -0.0023 yr⁻¹. This comparison of observations in January 2004 and 2021 supports the use of the selected $A_T/S$ relationship for pH calculations based on all fCO₂ data available over 1963–2023 in order to explore the long-term trend described in the next section.

### 3.3.2 Multi-decadal trends from fCO₂ data (1963–2023)

For long-term trends, we used fCO₂ observations and observations-based reconstructions averaged in the region 24–30° S (Table 4). As the observations are not available for all seasons, we selected the period April–May to calculate the trends from the data (same season for the first and the last cruises in 1963 and 2023) whereas the FFNN model offers

information for all seasons. Back in the 1960s, the observations in 1963 indicate that the ocean was a CO₂ sink in May (Fig. 7a), the value of ΔfCO₂ = -32.2 µatm being almost the same as observed in May 2022 (ΔfCO₂ = -32.5 µatm). This suggests a strong link between ocean and atmospheric fCO₂ (Fig. S6).

For the first observational period, the changes between 1963 and 1995 indicated a pH_T decrease of -0.040. Over 32 years this pH_T change was driven by the $C_T$ increase (effect on pH_T = -0.045), the $A_T$ increase (effect on pH_T = +0.012) and the warming of 0.95 °C (effect on pH_T = -0.015). Between 1995 and 2022 the observed decrease accelerated to -0.0027 (±0.0003) yr⁻¹ (Table 4). In contrast, the neural network suggested smaller pH_T trends. However, as in the observations, the annual pH_T change from the model was faster in recent decades (-0.0018 yr⁻¹ over 1995–2022 against -0.0011 yr⁻¹ over 1985–1995, Table 4). The model also suggested different trends depending on the season. The
<figure><img src="image_8.png" /><figcaption>**Figure 6.** Distribution of measured or calculated $C_T$ (a, µmol kg$^{-1}$), $A_T$ (b, µmol kg$^{-1}$), fCO$_2$ (c, µatm) and pH$_T$ (d) along the same track in January 2004 (black symbols) and January 2021 (grey symbols). Values derived from fCO$_2$ measurements are in filled symbols/lines, those from the $A_T C_T$ measurements in open symbols/dashed lines. In (e) the red lines represent the atmospheric CO$_2$ in 2004 and 2021. Average values and their differences are presented in Table 3.</figcaption></figure>

<table><caption>**Table 3.** Mean values of underway sea surface observations and their difference obtained in the same region (27–29° S/40–43° E) in January 2004 and 2021. Nb is the number of data. Standard-deviations are in bracket. The results are presented for both methods (underway fCO$_2$ or $A_T C_T$ measurements) and fCO$_2$, pH$_T$ calculated with $A_T C_T$ pairs compared with those derived from fCO$_2$ measurements. The last lines are the difference for 2021 minus 2004 and errors associated to the measurements or calculations (*).</caption><thead><tr><th>Cruise Method<br>Period</th><th>Nb</th><th>SST<br>°C</th><th>SSS<br>–</th><th>A<sub>T</sub><br>µmol kg<sup>-1</sup></th><th>C<sub>T</sub><br>µmol kg<sup>-1</sup></th><th>fCO<sub>2</sub><br>µatm</th><th>pH<sub>T</sub><br>TS</th><th>Atm. xCO<sub>2</sub><br>ppm</th></tr></thead><tbody><tr><td>OISO-11 fCO<sub>2</sub><br>January 2004</td><td>140</td><td>27.293<br>(0.331)</td><td>35.282<br>(0.050)</td><td>2314.2<br>(3.7)</td><td>1978.5<br>(6.7)</td><td>374.7<br>(3.2)</td><td>8.064<br>(0.002)</td><td>374.8</td></tr><tr><td>OISO-11 A<sub>T</sub>–C<sub>T</sub><br>January 2004</td><td>30</td><td>27.516<br>(0.609)</td><td>35.248<br>(0.042)</td><td>2315.4<br>(7.2)</td><td>1974.1<br>(9.8)</td><td>368.7<br>(7.6)</td><td>8.069<br>(0.007)</td><td></td></tr><tr><td>OISO-31 fCO<sub>2</sub><br>January 2021</td><td>102</td><td>27.825<br>(0.793)</td><td>35.508<br>(0.118)</td><td>2330.9<br>(8.7)</td><td>2006.8<br>(14.1)</td><td>412.5<br>(10.0)</td><td>8.032<br>(0.008)</td><td>412.2</td></tr><tr><td>OISO-31 A<sub>T</sub>–C<sub>T</sub><br>January 2021</td><td>17</td><td>27.916<br>(0.678)</td><td>35.515<br>(0.139)</td><td>2326.9<br>(9.6)</td><td>2003.5<br>(18.7)</td><td>414.4<br>(21.2)</td><td>8.030<br>(0.017)</td><td></td></tr><tr><td colspan="9">Difference 2021–2004</td></tr><tr><td>Underway fCO<sub>2</sub></td><td></td><td>0.532</td><td>0.225</td><td>16.7</td><td>28.3</td><td>37.8</td><td>-0.032</td><td>37.4</td></tr><tr><td>Underway A<sub>T</sub>–C<sub>T</sub></td><td></td><td>0.400</td><td>0.267</td><td>11.5</td><td>29.4</td><td>45.7</td><td>-0.040</td><td></td></tr><tr><td>Error using fCO<sub>2</sub></td><td></td><td>0.01</td><td>0.01</td><td>4</td><td>7.3*</td><td>2</td><td>0.014*</td><td></td></tr><tr><td>Error using A<sub>T</sub>–C<sub>T</sub></td><td></td><td>0.01</td><td>0.01</td><td>4</td><td>4</td><td>13.9*</td><td>0.007*</td><td></td></tr></tbody></table>

pH$_T$ trend appeared indeed faster in July (when the ocean CO$_2$ sink is stronger) than in January or April (Table 4).

The new data in 2021 and 2022 and the FFNN model extended to 2023 confirmed a previous analysis in the Mozambique Channel (Lo Monaco et al., 2021) with a pH$_T$ trend

of -0.0023 yr$^{-1}$ (±0.00048) over 1995–2019. Our new results in the southern Mozambique Channel are also in the range of the pH$_T$ trends previously evaluated at basin scale in the Indian Ocean, -0.0027 yr$^{-1}$ (±0.0005) over 1991–2011 (Lauvset et al., 2015). High resolution ocean models applied
<table><caption>**Table 4.** Trends of properties in the southern Mozambique Channel derived from observations and the FFNN model. For observations, the trends are evaluated for April–May season only (based on few data-points identified as red circles in Fig. 7). For FFNN, trends are estimated for all seasons or only for January, April, May and July. Standard-deviations are in bracket.</caption><thead><tr><th>Method</th><th>Period</th><th>fCO<sub>2</sub><br>μatm yr<sup>-1</sup></th><th>C<sub>T</sub><br>μmol kg yr<sup>-1</sup></th><th>A<sub>T</sub><br>μmol kg yr<sup>-1</sup></th><th>pH<sub>T</sub><br>TS yr<sup>-1</sup></th></tr></thead><tbody><tr><td>Obs April–May</td><td>1963–1995</td><td>1.11</td><td>0.91</td><td>0.52</td><td>-0.0012</td></tr><tr><td>Obs April–May</td><td>1963–2022</td><td>1.84<br>(0.21)</td><td>0.69<br>(0.20)</td><td>0.08<br>(0.13)</td><td>-0.0020<br>(0.0002)</td></tr><tr><td>Obs April–May</td><td>1995–2022</td><td>2.57<br>(0.30)</td><td>0.49<br>(0.52)</td><td>-0.34<br>(0.22)</td><td>-0.0027<br>(0.0003)</td></tr><tr><td>FFNN annual</td><td>1985–2023</td><td>1.76<br>(0.05)</td><td>0.99<br>(0.04)</td><td>0.02<br>(0.02)</td><td>-0.0017<br>(0.0001)</td></tr><tr><td>FFNN annual</td><td>1985–1995</td><td>1.15<br>(0.34)</td><td>1.03<br>(0.29)</td><td>0.00<br>(0.08)</td><td>-0.0011<br>(0.0004)</td></tr><tr><td>FFNN annual</td><td>1995–2022</td><td>1.84<br>(0.09)</td><td>1.10<br>(0.07)</td><td>0.06<br>(0.03)</td><td>-0.0018<br>(0.0001)</td></tr><tr><td>FFNN January</td><td>1985–2023</td><td>1.61<br>(0.03)</td><td>0.75<br>(0.07)</td><td>0.00<br>(0.05)</td><td>-0.0015<br>(0.0000)</td></tr><tr><td>FFNN April</td><td>1985–2023</td><td>1.74<br>(0.03)</td><td>1.01<br>(0.07)</td><td>0.03<br>(0.07)</td><td>-0.0017<br>(0.0000)</td></tr><tr><td>FFNN May</td><td>1985–2023</td><td>1.71<br>(0.03)</td><td>1.07<br>(0.05)</td><td>0.07<br>(0.05)</td><td>-0.0017<br>(0.0000)</td></tr><tr><td>FFNN July</td><td>1985–2023</td><td>1.97<br>(0.04)</td><td>1.17<br>(0.05)</td><td>0.04<br>(0.02)</td><td>-0.0020<br>(0.0000)</td></tr></tbody></table>

to the northern Indian Ocean also suggest an acceleration of the acidification, with pH<sub>T</sub> trend reaching -0.0019 yr<sup>-1</sup> (±0.0004) in 2010–2019 (Chakraborty et al., 2024), somehow lower than our estimate based on observations at regional scale in the Mozambique Channel (-0.0027 yr<sup>-1</sup> ±0.0003 in 1995–2022, Table 4).

The aragonite saturation state (Ω<sub>ar</sub>) was lower during annual summer (July–September). In May 1963, we estimated an aragonite saturation state of 3.86 (Fig. 7c). It dropped to 3.49 in May 2022, a value close to that observed in July 2014 (3.47). The lowest Ω<sub>ar</sub> value of 3.23 was identified in September 2023 from the FFNN model. At that period, Ω<sub>ar</sub> was lower than 3.3 in the south of 20° S in the Mozambique Channel (Fig. S7). This is close to the hypothetical critical threshold of Ω<sub>ar</sub> = 3.25, i.e. a risky level for coral reefs in the ocean claimed by Hoegh-Guldberg et al. (2007). Note that there are reefs know to thrive at Ω<sub>ar</sub> < 3.0 like at volcanic CO<sub>2</sub> seeps in Papua New Guinea (Ω<sub>ar</sub> = 2.41, Strahl et al., 2015; see also review by Camp et al., 2018) but that their species composition and coral cover are different than at ambient conditions (i.e. Ω<sub>ar</sub> > 3.3 considering Hoegh-Guldberg et al., 2007). However, Strahl et al. (2015) showed that calcification rate seems to vary among coral species, suggesting take conclusions of Hoegh-Guldberg et al. (2007) with

caution. With an annual trend of -0.010 yr<sup>-1</sup> for Ω<sub>ar</sub> over 1985–2023, a value of 3.3 would be reached in 2060 in summer whereas it was already observed in 2020 in winter with possible consequences on reef species composition and functioning (Tribollet et al., 2009, 2019; Schönberg et al., 2017; Camp et al., 2018; Eyre et al., 2018; Cornwall et al., 2021).

Although there are differences depending on the season and the method (in-situ observations, extrapolation of sparse in-situ observations through a FFNN model) all results suggest an acceleration of the acidification in the last few years (Table 4, Fig. 7) and a decrease of Ω<sub>ar</sub> that are mainly driven by the C<sub>T</sub> increase through continuous ocean CO<sub>2</sub> uptake (Ma et al., 2023). Given the rapid change of atmospheric CO<sub>2</sub> in the recent years (up to +3.77 ppm yr<sup>-1</sup> in 2024, Lan et al., 2025) how the carbonate system will change in the near future in this region and will impact corals reefs that are abundant (from Europa to Mayotte in the Mozambique Channel) and subject to global warming, marine heat waves (e.g. Mawren et al., 2022; Alaguarda et al., 2022), ocean acidification, higher frequency of tropical cyclones and anthropogenic pressures (overfishing for instance), remains an important question.
<figure><img src="image_9.png" /><figcaption>Figure 7. Time-series of fCO₂ (a), pH_T (b) and Ωₐₗ (c) in the southern Mozambique Channel (24–30° S) based on averaged observations (circles) and the FFNN-LSCE model over 1985–2023. In (a) the red line represents the atmospheric CO₂. Available observations are shown for all seasons but the trends (Table 4) evaluated using only April–May data (red circles).</figcaption></figure>

## 3.4 Projection in the near future

A recent analysis found that the Cₐₗt concentrations in sub-surface water in the Mozambique Basin were positively related to atmospheric CO₂ with a slope of +0.512 ± 0.050 µmol kg⁻¹ µatm⁻¹ (Metzl et al., 2025b, Fig. S8). Here, we assume that this relationship is valid for the southern Mozambique Channel. To reconstruct the past and future change of the carbonate system properties we calculated the C_T concentration over 1960–2100 by correcting C_T for each year using the relationship between Cₐₗt and atmospheric

CO₂.

$$C_T(t) = C_T(t-1) + C_{ant}(t) - C_{ant}(t-1) \quad (2)$$

For future atmospheric CO₂, we used two SSP emissions scenarios (Shared Socioeconomic Pathways, Meinshausen et al., 2020), a “high” emission scenario SSP5-8.5 and a stabilization scenario SSP2-4.5 (Fig. 8a). To explore the change of the aragonite saturation state, we applied this model (Eq. 2) for August when Ωₐₗ is the lowest. Temperature and salinity were fixed from the climatology in August (SST = 22.685 °C; SSS = 35.303) and fCO₂, pH_T and Ωₐₗ were calculated each year with the C_T A_T pairs using ver-
<figure><img src="image_10.png" /><figcaption>**Figure 8.** Time-series of (a) atmospheric and oceanic fCO₂, (b) C_T concentrations, (c) pH_T and (d) Ω_ar in the southern Mozambique Channel based on a reconstruction for August for two scenario (SSP85, black line, SSP45 grey lines). Averaged observations (all seasons, July in blue) and the FFNN-LSCE model over 1985–2023 in August (orange) are also shown.</figcaption></figure>

sion CO2sys_v2.5 (Orr et al., 2018). The reconstructed C_T, fCO₂, pH_T and Ω_ar for August compared well with the observations (in July) and with the FFNN model in August (Fig. 8; Table S1, Fig. S9) indicating that the simulation captured the decadal evolution of the properties. For the future, differences between the two scenarios (SSP5-8.5 and SSP2-4.5) are pronounced after 2030 (Fig. 8). For the high scenario the C_T concentrations reaches 2060 µmol kg⁻¹ in 2040 and pH_T is as low as 8. In both scenarios, the carbonate ion concentrations dropped below 200 µmol kg⁻¹ in 2028. As noted above, the aragonite saturation state based on observations was 3.47 in July 2014 (Fig. 7c and blue symbol in Fig. 8d) and the lowest Ω_ar value of 3.23 occurred in August–September 2023 (from the FFNN model, Figs. 7c and 8d). The same is estimated in the projection (Fig. 7d), close to the critical threshold of Ω_ar = 3.25 for tropical coral reef.

As of January 2025, the atmospheric CO₂ is 426 and 450 ppm should be reached in 2030 in the high scenario SSP5-8.5 (Fig. 8a). In a global ocean model it has been suggested that at 450 ppm Ω_ar would be around 3 in the South Indian Ocean and the Mozambique Channel, against 4 for pre-industrial Ω_ar (Fig. 4 in Hoegh-Guldberg et al., 2007). In our simulation, at 450 ppm, Ω_ar is equal to 3.13 against 3.8 based on observations in May 1963. Extrapolating our result back in time, we estimated pH_T at 8.18 and Ω_ar equal to 4 at 280 ppm, close to the pre-industrial value estimated from dedicated reconstructions (Lo Monaco et al., 2021) or in global ocean models (Hoegh-Guldberg et al., 2007; Jiang et al., 2023).

Our calculation suggests that for a high emission scenario a risky level for corals ($\Omega_{ar} < 3$, Hoegh-Guldberg et al., 2007) could be reached as soon as year 2034, i.e. in the next 10 years. This calls for maintaining regular carbonate system observations in this region, if possible at all seasons, in order to follow at best their evolution and the potential impact on the channel ecosystem and especially coral reefs in the context of global warming and acidification that will dramatically persist in the near future.

## 3.5 A large anomaly observed in 2025

As mentioned above, fCO₂ data are relatively sparse in the Mozambique Channel and should be obtained for all seasons. To complete the shipboard observations, biogeochemical (BGC) Argo floats have been developed and successfully used for 10 years for air-sea CO₂ flux estimates and/or acidification especially in the Southern Ocean in the frame of the SOCCOM project (e.g. Sarmiento et al., 2023; Mazloff et al., 2023). The floats record profiles down to 1000 or 2000 m at a 10 d frequency. In November 2024, a BGC-Argo float (WMO ID 7902123) was launched in the Mozambique Channel at 38.51°E/22.65°S (last profile used here recorded on 4 May 2025). The fCO₂ and Ω_ar from the pH_T float data were calculated using CO2sys as for the shipboard data (Sect. 2.3). Interestingly, the float recorded high temperature in January 2025 (up to 29.8 °C, Fig. 9a), a signal probably linked to a MHW (Fig. S10) that occurred at high frequency in this region (Mawren et al., 2022). Sea surface
<figure><img src="image_11.png" /><figcaption>**Figure 9.** Time-series of (a) SST and pH<sub>T</sub>, and (b) fCO<sub>2</sub> and Ω<sub>ar</sub> in the southern Mozambique Channel based on BGC-Argo data (WMO7902123) in November 2024 to May 2025 (location of data in the insert map). Data from https://www.mbari.org/products/data-repository/, last access 9 May 2025. Insert map produced with ODV (Schlitzer, 2018).</figcaption></figure>

temperature from reanalysis products suggests a temperature
as high as 31 °C in this region in January 2025 (Fig. S10).
Consequently, the sea surface fCO₂ derived from the float
pH_T data reached values above 480 µatm (Fig. 9b). This leads
to a strong CO₂ source anomaly, in line with CO₂ fluxes
anomalies associated to MHW in the South Indian subtropics
(e.g. Li et al., 2024). The lowest pH_T of 7.95 was recorded
on 11 January 2025, i.e. lower than the pH_T derived from
the FFNN model (Fig. 7b). The aragonite saturation state de-
rived from the BGC-Argo data reached 3.2 in March 2025,
the same as that which we estimate in 2025 from the sim-
ulation (Fig. 8d). The observations from the BGC-Argo of-
fer important information to complement the shipboard data
and should be used along with SOCAT data to test constraint
data-based products.

# 4 Summary and concluding remarks

New observations in 2021 and 2022 and historical fCO₂ data
available since 1963 in the Mozambique Channel were used
to evaluate the decadal trends of the carbonate system in this
region. With adapted A_T/S relationship for this region, we

calculated C_T concentrations, pH_T and Ω_ar. This calculation
is first validated with in-situ A_T and C_T measurements ob-
tained in January 2004, April 2019 and January 2021. Based
on the data in January 2004 and 2021, we found a pH_T de-
crease of -0.032 (using fCO₂ data) and -0.040 (using A_T
C_T data) over 17 years. Because the seasonality is large, the
decadal trends based on fCO₂ observations in 1963-2022 are
evaluated for one season only (April-May). A FFNN model
that reconstructed the monthly fields of the carbonate sys-
tem is also used to investigate the trends for all seasons, but
restricted to the period 1985-2023.

In this region where the ocean is a permanent CO₂ sink
of -0.25 (±0.06) mol C m⁻² yr⁻¹, fCO₂ observations avail-
able in April-May translate an acceleration of the acid-
ification ranging from -0.012 decade⁻¹ in 1963-1995 to
-0.027 (±0.003) decade⁻¹ in 1995-2022. Result from the
FFNN model for all seasons suggest smaller pH_T trends
but, like in the observations, the decrease of pH_T was faster
in recent decades, -0.011 decade⁻¹ over 1985-1995 and
-0.018 decade⁻¹ over 1995-2022. The FFNN model also
suggests a faster trend in austral winter when the ocean CO₂
sink is stronger and when the aragonite saturation state (Ω_ar)
is low. In May 2022 we estimated $\Omega_{ar} = 3.49$, about 0.3 lower than observed in May 1963 ($\Omega_{ar} = 3.86$). The lowest $\Omega_{ar}$ value of 3.23 was evaluated from the FFNN model in September 2023 that corresponds to the potential critical threshold value (3.25) for net reef accretion (Hoegh-Guldberg et al., 2007) and could conduct to net reef dissolution (Eyre et al., 2018; Tribollet et al., 2019; Cornwall et al., 2021).

A simple reconstruction and projection of the $C_T$ concentrations based on anthropogenic $CO_2$ in subsurface water and emissions scenario, suggests that the aragonite saturation state could be as low as 3 in the next 10 years. Following a previous work (Lo Monaco et al., 2021), the new data presented here clearly reveal the progressive acidification in the Mozambique Channel and its acceleration in the recent decade with potential impacts on ecosystem including corals reefs areas like at Europa and Bassa de India. In a context where there is no sign of a slowdown in anthropogenic emissions, this already obvious acidification is alarming for the ocean health (Gattuso et al., 2015) and potential feedback on the ocean carbon cycle in general (e.g. Barrett et al., 2025). Understanding and quantifying the future response of phytoplanktonic and reef species in the context of global warming and acidification calls for adapted ocean biogeochemical models (Cornwall et al., 2021) to take into account dynamics of bioerosion processes (see Schönberg et al., 2017). In the Mozambique Channel, observations are still very sparse and the new observations presented here, including recent BGC-Agro data, offer important information to validate regional and global biogeochemical models that are not yet able to simulate correctly the seasonal cycle and decadal variability of the oceanic carbonate system. We strongly claim for maintaining regular sampling of ocean carbonate system parameters to reduce the model uncertainties and for adapted strategies at both scientific and political actions in the future.

**Data availability.** Data used in this study are available in SOCAT (Bakker et al., 2016, http://www.socat.info, last access: 10 June 2025) for $fCO_2$ surface data, in GLODAP (Lauvset et al., 2022a, b, http://www.glodap.info, last access: 10 June 2025) for water-column data. The $A_T$ and $C_T$ underway data from OISO and CLIM-EPARSES cruises are available in Seanoe (https://www.seanoe.org, last access: 10 June 2025, https://doi.org/10.17882/95414, Metzl et al., 2023, and https://doi.org/10.17882/102337, Metzl et al., 2024). The BGC-Argo float data with derived carbon parameters are available from SOCCOM (https://soccom.org, last access: 2 October 2024, https://www.mbari.org/products/data-repository/, last access: 10 May 2025). The CMEMS-LSCE-FFNN model data are available at E.U. Copernicus Marine Service Information (https://resources.marine.copernicus.eu/products, last access: 3 May 2025, https://doi.org/10.48670/moi-00047, Copernicus Marine Service, 2024a). The Mixed layer depth data are publicly available on the CMEMS website: https://data.marine.copernicus.eu/products (last access: 17 April

2025, Multi Observation Global Ocean ARMOR3D L4 MULTI-OBS_GLO PHY_TSUV_3D_MYNRT_015_012).

**Supplement.** The supplement related to this article is available online at https://doi.org/10.5194/bg-22-7187-2025-supplement.

**Author contributions.** CLM and NM are co-investigators of the ongoing OISO project. AT was chief scientist of the CLIM-EPARSES 2019 cruise and JFT was chief scientist of the RESILIENCE cruise. MG and FC developed the CMEMS-LSCE-FFNN model and provided the model results. NM started the analysis, wrote the draft of the manuscript and prepared the figures with contributions from all co-authors.

**Competing interests.** The contact author has declared that none of the authors has any competing interests.

**Disclaimer.** Publisher's note: Copernicus Publications remains neutral with regard to jurisdictional claims made in the text, published maps, institutional affiliations, or any other geographical representation in this paper. While Copernicus Publications makes every effort to include appropriate place names, the final responsibility lies with the authors. Views expressed in the text are those of the authors and do not necessarily reflect the views of the publisher.

**Acknowledgements.** The OISO program was supported by the French institutes INSU (Institut National des Sciences de l'Univers) and IPEV (Institut Polaire Paul-Emile Victor), OSU Ecce-Terra (at Sorbonne Université), the French programs SOERE/Great-Gases and ICOS-France. We thank the French Oceanographic Fleet for financial and logistic support for the OISO program (https://campagnes.flotteoceanographique.fr/series/228/, last access: 10 January 2025). The CLIM-EPARSES project was supported by TAAF (Terres Australes et Antarctic Françaises), IRD (Institut de Recherche pour le Développement), Fondaion Prince Albert II de Monaco (http://www.fpa2.org, last access: 3 November 2025), INSU (Institut National des Sciences de l'Univers), CNRS (Centre National de Recherche Scientifique), Museum National d'Histoire Naturelle (MNHN), UMRs LOCEAN-IPSL, ENTROPIE and LSCE. The RESILIENCE cruise (https://doi.org/10.17600/18001917, Ternon et al., 2023) was supported by the French National Oceanographic Fleet, by the Belmont Forum Ocean Front Change project, by the ISblue project and by the French National program LEFE (Les Enveloppes Fluides et l'Environnement). We thank the captains and crew of R.R.V. Marion-Dufresne and the staff at IFREMER, GENAVIR and IPEV. We also thank Guillaume Barut, Jonathan Fin and Claude Mignon for their help during the OISO, CLIM-EPARSES and RESILIENCE cruises. The development of the neural network model benefited from funding by the French INSU-GMMC project PPR-Green-Grog (grant no. 5-DS-PPR-GGREOG), the EU H2020 project AtlanOS (grant no. 633211), as well as through the Copernicus Marine Environment Monitoring Service (project 83-CMEMS-TAC-MOB). We acknowledge the Southern Ocean Carbon and Climate
Observations and Modeling (SOCCOM) Project funded by the Na-
tional Science Foundation, Division of Polar Programs (NSF PLR-
1425989 and OPP-1936222). We thank all colleagues who con-
tributed to the quality control of ocean data made available through
GLODAP (http://www.glodap.info, last access: 10 June 2025). The
Surface Ocean CO₂ Atlas (SOCAT, http://www.socat.info, last ac-
cess: 10 June 2025) is an international effort, endorsed by the Inter-
national Ocean Carbon Coordination Project (IOCCP), the Surface
Ocean Lower Atmosphere Study (SOLAS) to deliver a uniformly
quality-controlled surface ocean CO₂ database. We thank Hermann
Bange associate editor, and anonymous reviewers for their positive
reports and comments that helped revising the manuscript.

*Financial support.* This research has been supported by the Centre National de la Recherche Scientifique (SNO OISO; SOERE/Great-Gases; CLIM-EPARSES; RESILIENCE and PPR-Green-Grog, grant no. 5-DSPPR-GGREOG), the Sorbonne Université (SNO OISO), the Institut de Recherche pour le Développement (CLIM-EPARSES and RESILIENCE), and the European Commission Horizon 2020 framework program (AtlantOS, grant no. 633211).

*Review statement.* This paper was edited by Hermann Bange and reviewed by two anonymous referees.

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