A 3D land–sea mask is created using the coastline and bathymetry of the General Bathymetric Chart of the Oceans (GEBCO) 30 s topography (Weatherall et al., 2015). The WMED is a relatively small area which necessitates a high-resolution bathymetry to generate a mask at different depth layers. The vertical resolution is set to 19 standard depth levels from the surface to 1500 m: 0, 5, 10, 20, 30, 50, 75, 100, 150, 200, 250, 300, 400, 500, 600, 700, 800, 1000 and 1500 m, corresponding to the most commonly used predefined levels for the sampling of seawater for nutrient analyses. The resulting fields at each depth level are the interpolation on the specified grid. These depth surfaces are the domain on which the interpolation is performed.

Lc indicates the distance over which an observation affects its neighbors. The correlation length can be set by the user or computed using the data distribution.

For the BGC-WMED, this parameter was optimized for the whole time span and at each depth layer. The correlation length has been evaluated by fitting the empirical kernel function to the correlation between data isotropy and homogeneity in correlations. The quality of the fit is dependent on the number of observations (Troupin et al., 2018). The analytical covariance model used in the fit is derived for an infinite domain (Barth et al., 2014). To assess the quality of the fit, the data covariance and the fitted covariance are plotted against the distance between data points (Fig. 5). At 10 m, the correlation length was obtained with a high number of data points, indicating that the empirical covariance used to estimate the covariance and the fitted covariance are in good agreement.

At some depth layers there are irregularities due to an insufficient number of data points, making it necessary to apply a smoothing filter/fit to minimize the effect of these irregularities. It has been tested whether a randomly selected field analysis (nitrate data from 2006 and 2015) obtained with the fitted vertical correlation profile is better than the analysis with zero vertical correlation. A skill score relative to analysis with non-fitted vertical correlation has been computed following Murphy (1988) and Barth et al. (2014): 2skill score=1-rmsno fit2rms2.

A large difference in the global rms between the analysis with the fitted vertical correlation and the analysis with non-fitted vertical correlation used for validation was found. The test shows whether the use of the fit in the correlation profile improves the overall analysis or not. We found that the RMSE (nitrate analysis of 1981–2017) was reduced from 0.696 µmolkg-1 (analysis without fit) to 0.571 µmolkg-1 (analysis with fit) at 10 m depth, which means using the fitted vertical correlation profile in the analysis improves the skill by 32 %, and the fit improves the analysis fields.

Based on the data, DIVA performs a least-squares fit of the data covariance function with a theoretical function. Then, a vertical filter is applied and an average profile over the whole period is used (Fig. 6). This procedure is analogous to what has been used for the EMODnet climatology and the North Atlantic climatology, except that in EMODnet climatology, seasonally averaged profiles were used (Buga et al., 2019) and monthly averaged profiles were used in North Atlantic climatology (Troupin et al., 2010). The filter is applied to discard aberration caused by outliers or scarce observations in some layers, as described above.

Because of the horizontal and vertical inhomogeneity of the data coverage, the analysis was based on a correlation length that varies both horizontally (Fig. 6a) and vertically (Fig. 6b).

As expected, Lc increases with depth (Fig. 6), extending the influence area of the observation, a consequence of the fact that variability at depth is lower and that observations in the deep layer are scarcer (which on the other hand makes the Lc estimate more uncertain).

From the surface to 150–200 m, Lc is rather constant (Fig. 6), while from 200 to 600 m, the horizontal Lc (Fig. 6a) increases for all nutrients. Below 600 m, the horizontal Lc for silicate decreases down to 1000 m and then increases again at 1500 m. For nitrate and phosphate, a similar, but less marked, behavior is observed.

The vertical Lc (Fig. 6b) behaves similarly toward the increase, for nitrate and phosphate, due to the homogeneity of the intermediate water mass, as explained also by Troupin et al. (2010). For silicate, the vertical Lc decreases in the intermediate depth, reaching a minimum at 500 m depth. The different behavior of silicate could be explained by the progressive increase in concentrations from the surface to the deep layer, compared to nitrate and phosphate vertical distribution (a strong gradient between the surface depleted layer and intermediate layer). Lc for silicate has lower values compared to nitrate and phosphate because, horizontally and vertically, it behaves in a different way. Unlike nitrate and phosphate, silicate does not show a strongly increased east–west gradient. This gradient might induce this difference in the horizontal distance over which the sample influences its neighborhood.

Besides, silicate is less utilized by primary producers, and the dissolution of the biogenic silica is slower than that of the other nutrients (DeMaster, 2002), which explains its progressive increase toward deeper layers (Krom et al., 2014). The vertical Lc for all nutrients increases progressively from 400 to 1500 m.

Troupin et al. (2010) and Iona et al. (2018) attributed similar changes observed in Lc for temperature and salinity to the variability in the water masses in each layer. This might also explain the changes found in Lc for nutrients. Indeed, the concentration of nutrients in the WMED increases with depth and is very low at the surface, which explains the constant low values of Lc in this layer.

The signal-to-noise ratio (SNR) is related to the confidence in the measurements. It is the ratio between the variance of the signal and the variance of the measurement noise/error. The SNR defines the representativeness of the measurements relative to the climatological fields; in other words, it is the confidence in the data.

It not only depends on the instrumental error but also on the fact that observations are instantaneous measurements, and since a climatology is a long-term mean, such observations do not represent exactly the same.

Generally, small SNR values favor large deviations from the real measurements to give a smoother climatological field. On the other hand, with a high SNR, DIVAnd keeps the existing observations and interpolates between data points. The need is to find an approximation that does not deviate much from the real observations (further details in Lauvset et al., 2016, and Troupin et al., 2010).

Following the same approach that many climatologies that used the DIVAnd method adopted, i.e., EMODnet climatologies (available on the EMODnet chemistry portal), the Atlantic regional climatologies (Troupin et al., 2010), the Adriatic Sea climatology (Lipizer et al., 2014) and the SeaDataNet regional climatology (Simoncelli et al., 2015), the SNR is set to a constant value (Table 1).

The analysis is performed with a predefined uniform default error variance of 0.5 for all parameters at all depths; we presume that the data sources used to generate the BGC-WMED are consistent products. Three iterations are performed inside DIVAnd to estimate the optimal scale factor of error variance of the observation (following Desroziers et al., 2005). More details can be found at https://gher-ulg.github.io/DIVAnd.jl/latest/#DIVAnd.diva3d (last access: 27 January 2021​​​​​​​)​​​​​​​.

Values of SNR provided by means of a generalized cross-validation (GCV) technique (Brankart and Brasseur, 1998) gave a large estimate of the SNR (of the order of 22) showing a discontinuous analysis field and patterns around the cruise transects that do not represent properly the climatological fields.

The nitrate, phosphate and silicate mean climatological fields over 1981–2017 are presented in Fig. 9a–c, respectively. The mean surface nitrate at 100 m is about 3.58 ± 1.16 µmolkg-1. The highest surface values of nitrate concentrations are found in regions where strong upwelling or vertical mixing occurs, such as the Liguro-Provençal basin and the Alboran Sea (see Fig. 9a), and regions with extensive supply by the Ebro, Rhône, Moulouya and Chelif rivers.

The convection region (Gulf of Lion and Ligurian Sea) is characterized by a eutrophic regime and a spring bloom (Lavigne et al., 2015), unlike the rest of the basin, which shows low nitrate concentrations in the surface layer (< 4 µmolkg-1).

Nutrient patterns in the Alboran Sea have been associated with the distinct vertical mixing that supplies the surface layer with nutrients (Lazzari et al., 2012; Reale et al., 2020).

Indeed, the northern Alboran Sea is known as an upwelling area, where permanent strong winds enhance the regional biological productivity (Reul et al., 2005). The nitrate distribution at 100 m presents a clear distinction between the enriched surface regions in the WMED, under the influence of deep convection processes, and the easternmost depleted regions.

The distribution of phosphate concentration has striking similarities with that of nitrate (Fig. 9b). The mean surface phosphate concentration at 100 m is 0.16 ± 0.06 µmolkg-1. As for nitrate, the highest surface values are found in the Alboran Sea, Balearic Sea, Gulf of Lion and Liguro-Provençal Basin (0.2–0.3 µmolkg-1), while the Tyrrhenian Sea and the Algerian Sea revealed phosphate concentrations that were < 0.2 µmolkg-1. Similar patterns were observed by Lazzari et al. (2016), who argued that the variations in phosphate are regulated by atmospheric and terrestrial inputs. It should be noted that the maximum in the surface is found near river discharges of freshwater, like those of the Ebro and Rhône, i.e., the largest rivers of the WMED (Ludwig et al., 2009).

Concerning the distribution of silicate concentration, the surface layer at 100 m (Fig. 9c) followed the same pattern as those of nitrate and phosphate. Over this layer the mean silicate was about 2.7 ± 0.7 µmolkg-1. As for nitrate and phosphate, the highest values (3–4 µmolkg-1) were recorded in the Alboran Sea, Balearic Sea, Gulf of Lion and Liguro-Provençal Basin and at the southern entrance of the Tyrrhenian Sea. This surface distribution is in good agreement with the findings of Crombet et al. (2011), relating this local silicate surface maximum to the continental input, river discharge and atmospheric deposition (Frings et al., 2016; Sospedra et al., 2018). The spatial minima were reported in the Tyrrhenian Sea and in the Algerian Sea (< 3 µmolkg-1).

At the basin scale, nitrate concentrations increase with depth (Fig. 10a), with the highest concentration found at intermediate levels (250–500 m), ranging between 8.8 and 9.0 µmolkg-1. In this 300 m layer (Fig. 9d), the nitrate concentration average is 7.2 ± 1.06 µmolkg-1. High values (> 6.5 µmolkg-1) are found in the westernmost regions (Alboran Sea, Algerian Sea, Gulf of Lion, Balearic Sea and Liguro-Provençal Basin), while the easternmost regions (Tyrrhenian Sea, Sicily Channel) exhibit much lower concentrations (between 4.5 and 6.5 µmolkg-1).

Similar features are observed in the deep layer, at 1500 m (Fig. 9g), with nitrate concentrations increasing all over the basin, reaching on average 7.8–7.9 µmolkg-1 between 1000 and 1500 m depth (Fig. 10a).

In both layers (300 and 1500 m), the difference between the eastern opening of the basin (Sicily Channel) and the western side (Alboran Sea) is noticeable: the Sicily Channel and the Tyrrhenian Sea are under the direct influence of the water masses coming from the oligotrophic EMED, which then gradually become enriched with nutrients along their paths, as found by Schroeder et al. (2020).

Phosphate concentrations at intermediate depth (see 300 m, Fig. 9e) varied between 0.12 and 0.44 µmolkg-1, and the horizontal map shows the same gradual decrease toward the east, with the highest concentrations in the westernmost regions and minimum values in the eastern regions (< 0.25 µmolkg-1).

The average vertical profile over the entire region (Fig. 10b) reveals a maximum in phosphate concentrations between 300 and 800 m depth, related to an increased remineralization process.

In the deep layer (see 1500 m, Fig. 9h), the phosphate concentration average is 0.36 ± 0.02 µmolkg-1. Generally, the deep layer is homogeneous (Fig. 10b). The difference observed between the westernmost regions and the Tyrrhenian Sea remains, though the latter demonstrates higher phosphate concentrations (∼ 0.3 µmolkg-1). This variation could be due to the difference in the water masses. The IW inflow from the EMED brings relatively young waters that are depleted in nutrients, while the higher concentrations in the deep layer are signatures of the older resident DW of the Tyrrhenian Sea. The change in the biological uptake in the intermediate source water could explain the regional variability in nutrients. The low productivity (D'Ortenzio and Ribera d'Alcalà, 2009) and the pronounced oligotrophic regime of EMED water (Lazzari et al., 2016) may justify the increase in nutrients in the IW.

The silicate concentration distribution at intermediate (300 m, Fig. 9f) and deep (1500 m, Fig. 9i) layers were as expected, showing a notable increase compared to the surface. Here, the silicate average concentration is 5.83 ± 0.66 µmolkg-1. The maximum values were observed below 800 m: > 8.034 µmolkg-1 (Fig. 10c). At 1500 m, the silicate distribution is homogeneous all over the basin (on average 8.35 ± 0.39 µmol kg-1).

Generally, primary producers do not require silicate for their growth as much as they need nitrate and phosphate, which explain the disparity between nutrients patterns. Furthermore, at intermediate levels, the water is warmer than at deep levels, enhancing the dissolution rate and the progressive increase in silicate (DeMaster, 2002). The biogenic silicate is exported to greater depths and continues to dissolve, generating inorganic silicate as it sinks to the bottom. The recycling of silicate within the deep-sea sediments is later on redistributed by the deep currents which explain the homogenous horizontal distribution over the entire basin.

Comparing the three nutrients at the same depth levels, at the surface (100 m) it appears that they all show a local surface maximum, depending on local events such as strong winds, local river discharge and vertical mixing (Ludwig et al., 2010).

In the easternmost areas, the surface depletion in nutrients (Van Cappellen et al., 2014) is attributed to the variation in the thermohaline properties that has impacted primary production (Ozer et al., 2017) and the export of organic matter to intermediate and deep layers leading to the accumulation of nutrients in these depth ranges.

The Tyrrhenian Sea is not directly connected to convection regions. Here, the EMED water inflow plays a major role. Li and Tanhua (2020) found increased ventilation of the intermediate and deep layers during 2001 to 2018 in the Sicily Channel and a constant apparent oxygen utilization (AOU) between 2001–2016, suggesting constant ventilation that explains the peculiar nutrient distribution in that area. On the western side of the WMED, intermediate and deep layers exhibit an increase in nutrients. Schroeder et al. (2020) explained this increase in nitrate and phosphate at the intermediate layer with the increase in the remineralization rate at these depths along the path of IW.

The deficiency of inorganic nutrients is explained by the effect of the anti-estuarine circulation, with the IW coming from the EMED, which is known to be poor in nutrients (Krom et al., 2014; Schroeder et al., 2020), accumulating nutrients along its path. Thus, this relatively nutrient-rich Mediterranean outflow is lost to the Atlantic Ocean.

Overall, in the surface layer, circulation, physical processes and vertical mixing increase nutrient input while the biological pump controls the decrease.

In the deep layer, the variability is lower (standard deviation is reduced toward the bottom for all three nutrients; see Fig. 10); the deep layer accumulates dissolved organic nutrients. In the WMED, the deep layer constitutes a reservoir of inorganic nutrients.

Figures 11–13 show the analysis at the 150 m depth surface for the three nutrients. The BGC-WMED (1981–2017) product reveals detailed aspects of the general features of nitrate (Fig. 11a), phosphate (Fig. 12a) and silicate (Fig. 13a).

For the three nutrients, the new product reproduces patterns similar to the WOA18 all over the region. It shows well-defined fields and higher values of nitrate and phosphate concentrations. In the new product, nitrate concentrations varied between 2.31–7.3 µmolkg-1, the WOA18 values were 2.19–5.99 µmolkg-1. Phosphate ranges were similar between the two products (0.092–0.35 µmolkg-1 (BGC-WMED) and 0.095–0.35 µmolkg-1 (WOA18)). Likewise, silicate range values at 150 m were not different (2.07–4.99 (BGC-WMED) and 1.57–5.75 µmolkg-1 (WOA18)).

The average rms difference (RMSD) calculated from the difference between the WOA18 and the BGC-WMED all over the region at 150 m is about 1.14 µmolkg-1 for nitrate (Fig. 11c), 0.055 µmolkg-1 for phosphate (Fig. 12c) and 0.91 µmolkg-1 for silicate (Fig. 13c). Overall, the RMSE values were low, indicating limited disparity between the two products.

The difference field for every grid point reflects this discrepancy and shows areas with limited agreement between the two products that can have a difference of > 2 µmolkg-1 for nitrate (Fig. 11c), > 0.1 µmolkg-1 for phosphate (Fig. 12c) and > 1.5 µmolkg-1 for silicate (Fig. 13c). This dissimilarity is also noted with the low r2 (Fig. 14) (0.34, 0.20 and 0.095 for nitrate, phosphate and silicate, respectively)

The distribution of the surface nitrate concentrations (at 150 m) (Fig. 11a) of the new product is similar to that shown in the WOA18 (Fig. 11b). The largest difference between the two products occurs in northwest areas and in the Alboran Sea (Fig. 11c), areas of higher concentrations with more nutrient-rich surface water as described in Sect. 4.1. The difference is pronounced in these regions likely because of the occurrence of upwellings along the African coast and seasonal vertical mixing in the northern WMED, contributing to the upload of nutrients to the surface which could explain the high nitrate and phosphate concentration in the BGC-WMED. The WOA18 maps show weaker values of nutrient concentrations compared to the new product, which does not mean that there are fewer physical drivers, but it might indicate that the new product holds more in situ observations than the WOA18 in the WMED.

Phosphate surface concentrations (Fig. 12) show similar differences to those of nitrate. The largest difference with the surface phosphate of the WOA18 is found in the Alboran Sea, northern WMED and Sicily region (Fig. 12c).

As for silicate, the surface distribution shows large differences (Fig. 13c). The highest values are observed in the northwest area of the new product and in the Alboran Sea in the WOA18 climatology; this again accounts for the data coverage difference.

The inorganic nutrient mean concentrations resulting from the climatology of this work (period 2005–2017) and from both the MedBFM reanalysis product and the WOA18 are compared in the upper layer of 12 subregions of the WMED (in Table 4 and Fig. 15, including definitions of the subregion codes in Table 4).

Results show a general agreement between the BGC-WMED and the other two products in some subregions; nonetheless, there are some differences as shown in Sect. 4.3.1.

Upper-layer nitrate average concentrations (Fig. 15a) decrease eastward, from the Alboran Sea (DS1) to the Algerian Basin (DS3, DS4) and the Balearic Sea (DS2). The western part of the basin is an area under the direct influence of the inflowing Atlantic surface waters, where nitrate is known to be present in excess compared to phosphate, probably due to atmospheric N2 input (Lucea et al., 2003). In DS1, BGC-WMED nitrate levels are lower than the WOA18 nitrate levels, while in DS3, DS2 and DS4 the average nitrate concentrations are similar to those of the WOA18.

From the Algerian Basin (DS4, DF1) to the Liguro-Provençal (DF3) regions, there is an increase in the average nitrate in all products; this is the south–north gradient. Some differences arise where the new product is lower than the WOA18.

In the eastern regions, the lowest average concentrations of the WMED are found. Here, the difference between products is smaller, with MedBFM reanalysis being lower the new product and the WOA18.

As for phosphate (Fig. 15b), known to be the limiting nutrient of the WMED, because it is rapidly consumed by phytoplankton (Lucea et al., 2003), its average levels are low in DS1, DS3, DS2 and DS4, in the WOA18, MedBFM reanalysis and BGC-WMED. The latter product did not agree well with the other products in DS2, where it was slightly higher. Phosphate average concentrations slightly increase in DF1, DF2 and DF3 in all three products. The increase is explained by the vertical mixing process occurring in the northern WMED.

Upper-surface phosphate concentration averages start to decrease progressively through the Ligurian East (DF4), Tyrrhenian Sea (DT1, DT3), Sardinia Channel (DI1) and Sicily Channel (DI3). The BGC-WMED was in agreement with MedBFM reanalysis in those subregions aside from concentrations in DI3, where the new product showed higher levels.

The BGC-WMED shows reasonable agreement in the upper average concentrations of nitrate and phosphate that are similar in their order of magnitude to the other products (Fig. 15). The difference with the WOA18 resides in the wider temporal window of the observation (starting from 1955). The new climatology in some subregions has a better spatial coverage of in situ observation than the WOA18 (Garcia et al., 2019) and the MedBFM reanalysis (Teruzzi et al., 2019).

On the other hand, the average silicate (Fig. 15c) of the new product and the WOA18 varied between regions. A significant difference is found between the two products in DS2, DS4, DF1, DF2, DT1, DT3, DI1 and DI3, while in DS1, DS3 and DF4 the mean silicate is consistent between the two products.

Overall, the three products show strongly similar features between regions (similar curve shape).

As the last step in the comparison between the different products, it is investigated how the new climatology represents the vertical distribution by comparing the new climatological values for the period 2005–2017 with the MedBFM reanalysis and the WOA18.

We extracted data values along a longitudinal transect across the Algerian Basin in the west–east direction (Fig. 16). The transect was selected according to previous studies (D'Ortenzio and Ribera d'Alcalà, 2009; Lazzari et al., 2012; Reale et al., 2020), and since the easternmost part of the domain shows marked features, a transect across the Tyrrhenian Sea is extracted as well (Fig. 16). Silicate is not included as it was not represented in the MedBFM model.

Vertical sections of nitrate and phosphate in the Algerian Sea show a common agreement between products regarding the main patterns found along the water column, i.e., the nutrient-depleted surface layer and the gradual increase toward intermediate depths; we note as well the west-to-east decreasing gradient in the three products, yet there are some inequalities.

Below 100 m, there is a significant difference between products and a poor qualitative agreement. The nitrate distribution is dominated by the nutrient-enriched IW, with high values (> 7 µmolkg-1) increasing from east to west (Fig. 16). Phosphate shows similar patterns in the surface layer, exhibiting very low concentration and a progressive increase down to 300 m (> 0.35 µmolkg-1), also noted in the WOA18. The reanalysis showed a more smoothed field below 100–300 m, with phosphate concentration between 0.20 and 0.30 µmolkg-1. The highest values for phosphate were found below 250 m from 0 to 3∘ E in the new product. The BGC-WMED transect defines very well the different depth layers; the upper intermediate layer is rich in nutrient concentration with > 8 µmolkg-1 for nitrate (BGC-WMED) and > 0.35 µmolkg-1 for phosphate (BGC-WMED and WOA18).

The vertical section along the Tyrrhenian Sea (Fig. 16) also shows a decrease from west to east in nitrate concentrations. The same gradient is also found in phosphate in agreement with nutrient distribution shown from the WOA18. From the section of the MedBFM reanalysis, it is not easy to identify the west–east gradient that we mentioned before. It could be suggested that the model underestimates the vertical features in the eastern part (Tyrrhenian Sea, 100–300 m, nitrate varies between 1.4 and 4.2 µmolkg-1 and phosphate between 0.13 and 0.20 µmolkg-1) and western part (Algerian Basin, 100–300 m, nitrate varies between 2.1 and 5.4 µmolkg-1 and phosphate between 0.15 and 0.255 µmolkg-1). These values are lower than the ones found in the BGC-WMED (Tyrrhenian Sea, 100–300 m, nitrate ranges between 3 and 6 µmolkg-1 and phosphate values oscillate between 0.10–0.27 µmolkg-1; Algerian Basin, 100–300 m, nitrate ranges between 3.6 and 8 µmolkg-1 and phosphate values oscillate between 0.18–0.36 µmolkg-1).

The WOA18 reproduces similar patterns to the new climatology (Tyrrhenian Sea, 100–300 m, nitrate varies between 1.8 and 5.7 µmolkg-1 and phosphate between 0.33 and 0.20 µmolkg-1) and western part (Algerian Basin, 100–300 m, nitrate varies between 2.8 and 6.8 µmolkg-1 and phosphate between 0.16 and 0.34 µmolkg-1).

The products illustrate the nutrient-poor water on the eastern side (Tyrrhenian Sea) and the relatively nutrient-rich water found in the western transect (Algerian Basin).

The BGC-WMED product captures details shown in Fig. 16 about the longitudinal gradient in nitrate and phosphate, along the water column where nutrients sink deeper from west to east as previously seen in Pujo-Pay et al. (2011) and Krom et al. (2014) and there is increased oligotrophy from west to east with higher concentrations in the two nutrients on the western side of the section and a more oligotrophic character toward the east.

The differences between products could be explained by the difference in the data coverage and time span and the difference in methods used to construct the climatological fields.

The variability in nitrate and phosphate fields along the transect extracted from the BGC-WMED reflects the high resolution of the product, allowing the screening of vertical structure controlling nutrient contents. Based on a visual comparison, the new product is able to reproduce similar patterns to those of the WOA18 and to a lesser extent of the MedBFM reanalysis.

Figure 17 examines the vertical difference in nitrate and phosphate concentration for the BGC-WMED with the MedBFM reanalysis along the Algerian Basin (Fig. 17a, nitrate; Fig. 17b, phosphate) and WOA18 (Fig. 17c, nitrate; Fig. 17d, phosphate).

The vertical section shows a strong agreement at the surface for nitrate between the BGC-WMED and the MedBFM reanalysis (Fig. 17a), while the vertical difference with the WOA18 demonstrates that nitrate values in the new product are lower than those of the WOA18 at 50–75 m (Fig. 17c).

The difference increases with depth: below 100 m, the BGC-WMED nitrate climatology is higher than that of MedBFM, with a difference ranging between 0.6 and 2.4 µmolkg-1; a similar observation is noted in the WOA18 (Fig. 17c). In Fig. 17a and c, we identify patterns in the vertical structure of nitrate in the eastern portion of the transect.

Regarding phosphate, differences between the new climatology and the MedBFM reanalysis are noted (Fig. 17b) where the BGC-WMED shows high concentrations in the first 100 m and between 150 and 300 m (differences of 0.02–0.08 µmolkg-1); this difference decreases at 100–150 m. At the eastern portion of the transect (6 to 7.5∘ E), we find an agreement between the two products.

Conversely, the vertical sections of the differences between the BGC-WMED and WOA18 in phosphate (Fig. 17d) show similarities, with the new product being lower than the WOA18 in the first 50 m. A large difference is found on both sides of the transect below 100 m, while in the center of the transect, the difference in phosphate is reduced to 0–0.02 µmolkg-1.

Figure 18 compares the vertical difference in nitrate and phosphate along the Tyrrhenian Sea transect. In general, the difference transect in the Tyrrhenian Sea shows similar features between MedBFM reanalysis and the WOA18 as in the Algerian Basin. Figure 18d captures the west-to-east gradient in phosphate. The WOA18 overestimated phosphate in the surface layer.

Based on the new climatology comparison with the WOA18 and the reanalysis, it is concluded that the new product is consistent with the main features of previous products, shows the large-scale patterns and underlines well the characteristics of the water mass layers.

The study also provides an examination of the nitrate and phosphate distributions along a longitudinal transect across the Algerian Basin (western WMED) and across the Tyrrhenian Sea (eastern WMED). We have shown that the western basin is relatively high in nutrients compared to the eastern basin. The increased oligotrophic gradient from west to east could be attributed to the difference in the hydrodynamic patterns related to the water-mass-specific properties that are affected by the EMED and the Atlantic ocean inflows and to the local sources of nutrients (Ribera d'Alcalà et al., 2003; Schroeder et al., 2010). The study of Crispi et al. (2001) inferred the biological activity that is responsible for the oligotrophic gradient.