scholarly journals Climatological distribution of dissolved inorganic nutrients in the western Mediterranean Sea (1981–2017)

2021 ◽  
Vol 13 (12) ◽  
pp. 5915-5949
Author(s):  
Malek Belgacem ◽  
Katrin Schroeder ◽  
Alexander Barth ◽  
Charles Troupin ◽  
Bruno Pavoni ◽  
...  

Abstract. The Western MEDiterranean Sea BioGeochemical Climatology (BGC-WMED, https://doi.org/10.1594/PANGAEA.930447) (Belgacem et al., 2021) presented here is a product derived from quality-controlled in situ observations. Annual mean gridded nutrient fields for the period 1981–2017 and its sub-periods 1981–2004 and 2005–2017 on a horizontal 1/4∘ × 1/4∘ grid have been produced. The biogeochemical climatology is built on 19 depth levels and for the dissolved inorganic nutrients nitrate, phosphate and orthosilicate. To generate smooth and homogeneous interpolated fields, the method of the variational inverse model (VIM) was applied. A sensitivity analysis was carried out to assess the comparability of the data product with the observational data. The BGC-WMED was then compared to other available data products, i.e., the MedBFM biogeochemical reanalysis of the Mediterranean Sea and the World Ocean Atlas 2018 (WOA18) (its biogeochemical part). The new product reproduces common features with more detailed patterns and agrees with previous records. This suggests a good reference for the region and for the scientific community for the understanding of inorganic nutrient variability in the western Mediterranean Sea, in space and in time, but our new climatology can also be used to validate numerical simulations, making it a reference data product.

2021 ◽  
Author(s):  
Malek Belgacem ◽  
Katrin Schroeder ◽  
Alexander Barth ◽  
Charles Troupin ◽  
Bruno Pavoni ◽  
...  

Abstract. The Western MEDiterranean Sea BioGeochemical Climatology (BGC-WMED) presented here is a product derived from in situ observations. Annual mean gridded nutrient fields for the period 1981–2017, and its sub-periods 1981–2004 and 2005–2017, on a horizontal 1/4° × 1/4° grid have been produced. The biogeochemical climatology is built on 19 depth levels and for the dissolved inorganic nutrients nitrate, phosphate and orthosilicate. To generate smooth and homogeneous interpolated fields, the method of the Variational Inverse Model (VIM) was applied. A sensitivity analysis was carried out to assess the comparability of the data product with the observational data. The BGC-WMED has then been compared to other available data products, i.e. the medBFM biogeochemical reanalysis of the Mediterranean Sea and the World Ocean Atlas18 (WOA18) (its biogeochemical part). The BGC-WMED product supports the understanding of inorganic nutrient variability in the western Mediterranean Sea, in space and in time, but can also be used to validate numerical simulations making it a reference data product.


2021 ◽  
Author(s):  
Malek Belgacem ◽  
Jacopo Chiggiato ◽  
Katrin Schroeder ◽  
Alexander Barth ◽  
Charles Troupin ◽  
...  

<p>Ocean life relies on the loads of dissolved inorganic nutrients (nitrate, phosphate and silicate) and other micro-nutrients into the euphotic layer. They fuel phytoplankton growth that maintains the equilibrium of the food web. Ocean circulation and physical processes continually drive the large -scale distribution of chemicals toward a homogeneous distribution (Williams and Follows, 2003). The biological and biochemical processes counteract this tendency. Therefore, describing nutrient dynamics is important to understand the overall ecosystem functioning.</p><p>At global scale, most of the biogeochemical descriptions are based on model simulations and satellite data, since nutrient in situ observations are generally infrequent and not homogeneously distributed in space and time. Climatological mapping is often used to understand the biogeochemical state of the ocean representing monthly, seasonally or annual averaged fields.</p><p>Within this context, the western Mediterranean Sea climatology (BGC-WMED) presented here is a product derived from in situ observations, derived from various data sources: in total, 2253 in-situ inorganic nutrient profiles over the period 1981-2017 have been used (Medar/MEDATLAS, Fichaut et al., 2003; the CNR-WMED biogeochemical dataset, Belgacem et al., 2020; SeaDataNet data product, https://www.seadatanet.org; Mediterranean Ocean Observing System for the Environment, MOOSE, http://www.moose-network.fr/).</p><p>Annual mean gridded nutrient fields for the period 1981-2017, and sub-periods 1981-2004 and 2005-2017, on a horizontal 1/4° × 1/4° grid have been produced. The biogeochemical climatology is built on 19 depth levels and for the dissolved inorganic nutrients nitrate, phosphate and orthosilicate. To generate smooth and homogeneous interpolated fields, an advanced N-dimensional version of DIVA, DIVAnd v2.5.1 (Barth et al., 2014), which is based on the variational inverse method (VIM) (Brasseur et al., 1996), has been used.</p><p>A sensitivity analysis was carried out to assess the comparability of the data product with the observational data. The BGC-WMED has then been compared to other available data products, i.e. the medBFM biogeochemical reanalysis and the biogeochemical component of WOA18.</p><p>Keywords: Mediterranean Sea, climatology, inorganic nutrient, in situ observations. </p>


2020 ◽  
Vol 12 (3) ◽  
pp. 1985-2011
Author(s):  
Malek Belgacem ◽  
Jacopo Chiggiato ◽  
Mireno Borghini ◽  
Bruno Pavoni ◽  
Gabriella Cerrati ◽  
...  

Abstract. Long-term time series are a fundamental prerequisite to understanding and detecting climate shifts and trends. Understanding the complex interplay of changing ocean variables and the biological implication for marine ecosystems requires extensive data collection for monitoring, hypothesis testing, and validation of modelling products. In marginal seas, such as the Mediterranean Sea, there are still monitoring gaps, both in time and in space. To contribute to filling these gaps, an extensive dataset of dissolved inorganic nutrient observations (nitrate, phosphate, and silicate) was collected between 2004 and 2017 in the western Mediterranean Sea and subjected to rigorous quality control techniques to provide to the scientific community a publicly available, long-term, quality-controlled, internally consistent biogeochemical data product. The data product includes 870 stations of dissolved inorganic nutrients, including temperature and salinity, sampled during 24 cruises. Details of the quality control (primary and secondary quality control) applied are reported. The data are available in PANGAEA (https://doi.org/10.1594/PANGAEA.904172, Belgacem et al., 2019).


2019 ◽  
Author(s):  
Malek Belgacem ◽  
Jacopo Chiggiato ◽  
Mireno Borghini ◽  
Bruno Pavoni ◽  
Gabriella Cerrati ◽  
...  

Abstract. Long-term time-series are a fundamental prerequisite to understand and detect climate shifts and trends. Understanding the complex interplay of changing ocean variables and the biological implication for marine ecosystems requires extensive data collection for monitoring and hypothesis testing and validation of modelling products. In marginal seas, such as Mediterranean Sea, there are still monitoring gaps, both in time and in space. To contribute filling these gaps, an extensive dataset of dissolved inorganic nutrients profiles (nitrate, NO3; phosphate, PO43−; and silicate, SiO2) have been collected between 2004 and 2017 in the Western Mediterranean Sea and subjected to quality control techniques to provide to the scientific community a publicly available, long-term, quality controlled, internally consistent biogeochemical data product. The database includes 870 stations of dissolved inorganic nutrients sampled during 24 cruises, including temperature and salinity. Details of the quality control (primary and secondary quality control) applied are reported. The data are available in PANGAEA (https://doi.org/10.1594/PANGAEA.904172, Belgacem et al. 2019).


2021 ◽  
Vol 18 (24) ◽  
pp. 6455-6477
Author(s):  
Roxane Tzortzis ◽  
Andrea M. Doglioli ◽  
Stéphanie Barrillon ◽  
Anne A. Petrenko ◽  
Francesco d'Ovidio ◽  
...  

Abstract. Model simulations and remote sensing observations show that ocean dynamics at fine scales (1–100 km in space, day–weeks in time) strongly influence the distribution of phytoplankton. However, only a few in situ-based studies at fine scales have been performed, and most of them concern western boundary currents which may not be representative of less energetic regions. The PROTEVSMED-SWOT cruise took place in the moderately energetic waters of the western Mediterranean Sea (WMS), in the region south of the Balearic Islands. Taking advantage of near-real-time satellite information, we defined a sampling strategy in order to cross a frontal zone separating different water masses. Multi-parametric in situ sensors mounted on the research vessel, on a towed vehicle and on an ocean glider were used to sample physical and biogeochemical variables at a high spatial resolution. Particular attention was given to adapting the sampling route in order to estimate the vertical velocities in the frontal area also. This strategy was successful in sampling quasi-synoptically an oceanic area characterized by the presence of a narrow front with an associated vertical circulation. A multiparametric statistical analysis of the collected data identifies two water masses characterized by different abundances of several phytoplankton cytometric functional groups, as well as different concentrations of chlorophyll a and O2. Here, we focus on moderately energetic fronts induced by fine-scale circulation. Moreover, we explore physical–biological coupling in an oligotrophic region. Our results show that the fronts induced by the fine-scale circulation, even if weaker than the fronts occurring in energetic and nutrient-rich boundary current systems, maintain nevertheless a strong structuring effect on the phytoplankton community by segregating different groups at the surface. Since oligotrophic and moderately energetic regions are representative of a very large part of the world ocean, our results may have global significance when extrapolated.


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