Academic literature on the topic 'BGC-ARGO floats'
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Journal articles on the topic "BGC-ARGO floats"
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Ford, David. "Assimilating synthetic Biogeochemical-Argo and ocean colour observations into a global ocean model to inform observing system design." Biogeosciences 18, no. 2 (January 21, 2021): 509–34. http://dx.doi.org/10.5194/bg-18-509-2021.
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Abstract. A set of observing system simulation experiments was performed. This assessed the impact on global ocean biogeochemical reanalyses of assimilating chlorophyll from remotely sensed ocean colour and in situ observations of chlorophyll, nitrate, oxygen, and pH from a proposed array of Biogeochemical-Argo (BGC-Argo) floats. Two potential BGC-Argo array distributions were tested: one for which biogeochemical sensors are placed on all current Argo floats and one for which biogeochemical sensors are placed on a quarter of current Argo floats. Assimilating BGC-Argo data greatly improved model results throughout the water column. This included surface partial pressure of carbon dioxide (pCO2), which is an important output of reanalyses. In terms of surface chlorophyll, assimilating ocean colour effectively constrained the model, with BGC-Argo providing no added benefit at the global scale. The vertical distribution of chlorophyll was improved by assimilating BGC-Argo data. Both BGC-Argo array distributions gave benefits, with greater improvements seen with more observations. From the point of view of ocean reanalysis, it is recommended to proceed with development of BGC-Argo as a priority. The proposed array of 1000 floats will lead to clear improvements in reanalyses, with a larger array likely to bring further benefits. The ocean colour satellite observing system should also be maintained, as ocean colour and BGC-Argo will provide complementary benefits.
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Izett, Robert W., Katja Fennel, Adam C. Stoer, and David P. Nicholson. "Reviews and syntheses: expanding the global coverage of gross primary production and net community production measurements using Biogeochemical-Argo floats." Biogeosciences 21, no. 1 (January 2, 2024): 13–47. http://dx.doi.org/10.5194/bg-21-13-2024.
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Abstract. This paper provides an overview and demonstration of emerging float-based methods for quantifying gross primary production (GPP) and net community production (NCP) using Biogeochemical-Argo (BGC-Argo) float data. Recent publications have described GPP methods that are based on the detection of diurnal oscillations in upper-ocean oxygen or particulate organic carbon concentrations using single profilers or a composite of BGC-Argo floats. NCP methods rely on budget calculations to partition observed tracer variations into physical or biological processes occurring over timescales greater than 1 d. Presently, multi-year NCP time series are feasible at near-weekly resolution, using consecutive or simultaneous float deployments at local scales. Results, however, are sensitive to the choice of tracer used in the budget calculations and uncertainties in the budget parameterizations employed across different NCP approaches. Decadal, basin-wide GPP calculations are currently achievable using data compiled from the entire BGC-Argo array, but finer spatial and temporal resolution requires more float deployments to construct diurnal tracer curves. A projected, global BGC-Argo array of 1000 floats should be sufficient to attain annual GPP estimates at 10∘ latitudinal resolution if floats profile at off-integer intervals (e.g., 5.2 or 10.2 d). Addressing the current limitations of float-based methods should enable enhanced spatial and temporal coverage of marine GPP and NCP measurements, facilitating global-scale determinations of the carbon export potential, training of satellite primary production algorithms, and evaluations of biogeochemical numerical models. This paper aims to facilitate broader uptake of float GPP and NCP methods, as singular or combined tools, by the oceanographic community and to promote their continued development.
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Teruzzi, Anna, Giorgio Bolzon, Laura Feudale, and Gianpiero Cossarini. "Deep chlorophyll maximum and nutricline in the Mediterranean Sea: emerging properties from a multi-platform assimilated biogeochemical model experiment." Biogeosciences 18, no. 23 (November 30, 2021): 6147–66. http://dx.doi.org/10.5194/bg-18-6147-2021.
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Abstract. Data assimilation has led to advancements in biogeochemical modelling and scientific understanding of the ocean. The recent operational availability of data from BGC-Argo (biogeochemical Argo) floats, which provide valuable insights into key vertical biogeochemical processes, stands to further improve biogeochemical modelling through assimilation schemes that include float observations in addition to traditionally assimilated satellite data. In the present work, we demonstrate the feasibility of joint multi-platform assimilation in realistic biogeochemical applications by presenting the results of 1-year simulations of Mediterranean Sea biogeochemistry. Different combinations of satellite chlorophyll data and BGC-Argo nitrate and chlorophyll data have been tested, and validation with respect to available independent non-assimilated and assimilated (before the assimilation) observations showed that assimilation of both satellite and float observations outperformed the assimilation of platforms considered individually. Moreover, the assimilation of BGC-Argo data impacted the vertical structure of nutrients and phytoplankton in terms of deep chlorophyll maximum depth, intensity, and nutricline depth. The outcomes of the model simulation assimilating both satellite data and BGC-Argo data provide a consistent picture of the basin-wide differences in vertical features associated with summer stratified conditions, describing a relatively high variability between the western and eastern Mediterranean, with thinner and shallower but intense deep chlorophyll maxima associated with steeper and narrower nutriclines in the western Mediterranean.
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Mignot, Alexandre, Hervé Claustre, Gianpiero Cossarini, Fabrizio D'Ortenzio, Elodie Gutknecht, Julien Lamouroux, Paolo Lazzari, et al. "Using machine learning and Biogeochemical-Argo (BGC-Argo) floats to assess biogeochemical models and optimize observing system design." Biogeosciences 20, no. 7 (April 12, 2023): 1405–22. http://dx.doi.org/10.5194/bg-20-1405-2023.
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Abstract. Numerical models of ocean biogeochemistry are becoming the major tools used to detect and predict the impact of climate change on marine resources and to monitor ocean health. However, with the continuous improvement of model structure and spatial resolution, incorporation of these additional degrees of freedom into fidelity assessment has become increasingly challenging. Here, we propose a new method to provide information on the model predictive skill in a concise way. The method is based on the conjoint use of a k-means clustering technique, assessment metrics, and Biogeochemical-Argo (BGC-Argo) observations. The k-means algorithm and the assessment metrics reduce the number of model data points to be evaluated. The metrics evaluate either the model state accuracy or the skill of the model with respect to capturing emergent properties, such as the deep chlorophyll maximums and oxygen minimum zones. The use of BGC-Argo observations as the sole evaluation data set ensures the accuracy of the data, as it is a homogenous data set with strict sampling methodologies and data quality control procedures. The method is applied to the Global Ocean Biogeochemistry Analysis and Forecast system of the Copernicus Marine Service. The model performance is evaluated using the model efficiency statistical score, which compares the model–observation misfit with the variability in the observations and, thus, objectively quantifies whether the model outperforms the BGC-Argo climatology. We show that, overall, the model surpasses the BGC-Argo climatology in predicting pH, dissolved inorganic carbon, alkalinity, oxygen, nitrate, and phosphate in the mesopelagic and the mixed layers as well as silicate in the mesopelagic layer. However, there are still areas for improvement with respect to reducing the model–data misfit for certain variables such as silicate, pH, and the partial pressure of CO2 in the mixed layer as well as chlorophyll-a-related, oxygen-minimum-zone-related, and particulate-organic-carbon-related metrics. The method proposed here can also aid in refining the design of the BGC-Argo network, in particular regarding the regions in which BGC-Argo observations should be enhanced to improve the model accuracy via the assimilation of BGC-Argo data or process-oriented assessment studies. We strongly recommend increasing the number of observations in the Arctic region while maintaining the existing high-density of observations in the Southern Oceans. The model error in these regions is only slightly less than the variability observed in BGC-Argo measurements. Our study illustrates how the synergic use of modeling and BGC-Argo data can both provide information about the performance of models and improve the design of observing systems.
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Terzić, Elena, Paolo Lazzari, Emanuele Organelli, Cosimo Solidoro, Stefano Salon, Fabrizio D'Ortenzio, and Pascal Conan. "Merging bio-optical data from Biogeochemical-Argo floats and models in marine biogeochemistry." Biogeosciences 16, no. 12 (July 1, 2019): 2527–42. http://dx.doi.org/10.5194/bg-16-2527-2019.
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Abstract. New autonomous robotic platforms for observing the ocean, i.e. Biogeochemical-Argo (BGC-Argo) floats, have drastically increased the number of vertical profiles of irradiance, photosynthetically available radiation (PAR), and algal chlorophyll concentrations around the globe independent of the season. Such data may therefore be a fruitful resource to improve performances of numerical models for marine biogeochemistry. Here we present a work that integrates 1314 vertical profiles of PAR acquired by 31 BGC-Argo floats operated in the Mediterranean Sea between 2012 and 2016 into a one-dimensional model to simulate the vertical and temporal variability of algal chlorophyll concentrations. The model was initially forced with PAR measurements to assess its skill when using quality-controlled light profiles, and subsequently with a number of alternative bio-optical models to analyse the model capability when light observations are not available. Model outputs were evaluated against co-located chlorophyll profiles measured by BGC-Argo floats. Results highlight that the data-driven model is able to reproduce the spatial and temporal variability of deep chlorophyll maxima depth observed at a number of Mediterranean sites well. Further, we illustrate the key role of PAR and vertical mixing in shaping the vertical dynamics of primary producers in the Mediterranean Sea. The comparison of alternative bio-optical models identifies the best simple one to be used, and suggests that model simulations benefit from considering the diel cycle.
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Renosh, Pannimpullath Remanan, Jie Zhang, Raphaëlle Sauzède, and Hervé Claustre. "Vertically Resolved Global Ocean Light Models Using Machine Learning." Remote Sensing 15, no. 24 (December 7, 2023): 5663. http://dx.doi.org/10.3390/rs15245663.
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The vertical distribution of light and its spectral composition are critical factors influencing numerous physical, chemical, and biological processes within the oceanic water column. In this study, we present vertically resolved models of downwelling irradiance (ED) at three different wavelengths and photosynthetically available radiation (PAR) on a global scale. These models rely on the SOCA (Satellite Ocean Color merged with Argo data to infer bio-optical properties to depth) methodology, which is based on an artificial neural network (ANN). The new light models are trained with light profiles (ED/PAR) acquired from BioGeoChemical-Argo (BGC-Argo) floats. The model inputs consist of surface ocean color radiometry data (i.e., Rrs, PAR, and kd(490)) derived by satellite and extracted from the GlobColour database, temperature and salinity profiles originating from BGC-Argo, as well as temporal components (day of the year and local time in cyclic transformation). The model outputs correspond to ED profiles at the three wavelengths of the BGC-Argo measurements (i.e., 380, 412, and 490 nm) and PAR profiles. We assessed the retrieval of light profiles by these light models using three different datasets: BGC-Argo profiles that were not used for the training (i.e., 20% of the initial database); data from four independent BGC-Argo floats that were used neither for the training nor for the 20% validation dataset; and the SeaBASS database (in situ data collected from various oceanic cruises). The light models show satisfactory predictions when thus compared with real measurements. From the 20% validation database, the light models retrieve light variables with high accuracies (root mean squared error (RMSE)) of 76.42 μmol quanta m−2 s−1 for PAR and 0.04, 0.08, and 0.09 W m−2 nm−1 for ED380, ED412, and ED490, respectively. This corresponds to a median absolute percent error (MAPE) that ranges from 37% for ED490 and PAR to 39% for ED380 and ED412. The estimated accuracy metrics across these three validation datasets are consistent and demonstrate the robustness and suitability of these light models for diverse global ocean applications.
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Bellacicco, Vellucci, Scardi, Barbieux, Marullo, and D’Ortenzio. "Quantifying the Impact of Linear Regression Model in Deriving Bio-Optical Relationships: The Implications on Ocean Carbon Estimations." Sensors 19, no. 13 (July 9, 2019): 3032. http://dx.doi.org/10.3390/s19133032.
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Linear regression is widely used in applied sciences and, in particular, in satellite optical oceanography, to relate dependent to independent variables. It is often adopted to establish empirical algorithms based on a finite set of measurements, which are later applied to observations on a larger scale from platforms such as autonomous profiling floats equipped with optical instruments (e.g., Biogeochemical Argo floats; BGC-Argo floats) and satellite ocean colour sensors (e.g., SeaWiFS, VIIRS, OLCI). However, different methods can be applied to a given pair of variables to determine the coefficients of the linear equation fitting the data, which are therefore not unique. In this work, we quantify the impact of the choice of “regression method” (i.e., either type-I or type-II) to derive bio-optical relationships, both from theoretical perspectives and by using specific examples. We have applied usual regression methods to an in situ data set of particulate organic carbon (POC), total chlorophyll-a (TChla), optical particulate backscattering coefficient (bbp), and 19 years of monthly TChla and bbp ocean colour data. Results of the regression analysis have been used to calculate phytoplankton carbon biomass (Cphyto) and POC from: i) BGC-Argo float observations; ii) oceanographic cruises, and iii) satellite data. These applications enable highlighting the differences in Cphyto and POC estimates relative to the choice of the method. An analysis of the statistical properties of the dataset and a detailed description of the hypothesis of the work drive the selection of the linear regression method
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Begouen Demeaux, Charlotte, and Emmanuel Boss. "Validation of Remote-Sensing Algorithms for Diffuse Attenuation of Downward Irradiance Using BGC-Argo Floats." Remote Sensing 14, no. 18 (September 9, 2022): 4500. http://dx.doi.org/10.3390/rs14184500.
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Estimates of the diffuse attenuation coefficient (Kd) at two different wavelengths and band-integrated (PAR) were obtained using different published algorithms developed for open ocean waters spanning in type from explicit-empirical, semi-analytical and implicit-empirical and applied to data from spectral radiometers on board six different satellites (MODIS-Aqua, MODIS-Terra, VIIRS–SNPP, VIIRS-JPSS, OLCI-Sentinel 3A and OLCI-Sentinel 3B). The resultant Kds were compared to those inferred from measurements of radiometry from sensors on board autonomous profiling floats (BGC-Argo). Advantages of BGC-Argo measurements compared to ship-based ones include: 1. uniform sampling in time throughout the year, 2. large spatial coverage, and 3. lack of shading by platform. Over 5000 quality-controlled matchups between Kds derived from float and from satellite sensors were found with values ranging from 0.01 to 0.67 m−1. Our results show that although all three algorithm types provided similarly ranging values of Kd to those of the floats, for most sensors, a given algorithm produced statistically different Kd distributions from the two others. Algorithm results diverged the most for low Kd (clearest waters). Algorithm biases were traced to the limitations of the datasets the algorithms were developed and trained with, as well as the neglect of sun angle in some algorithms. This study highlights: 1. the importance of using comprehensive field-based datasets (such as BGC-Argo) for algorithm development, 2. the limitation of using radiative-transfer model simulations only for algorithm development, and 3. the potential for improvement if sun angle is taken into account explicitly to improve empirical Kd algorithms. Recent augmentation of profiling floats with hyper-spectral radiometers should be encouraged as they will provide additional constraints to develop algorithms for upcoming missions such as NASA’s PACE and SBG and ESA’s CHIME, all of which will include a hyper-spectral radiometer.
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Wang, Bin, Katja Fennel, and Liuqian Yu. "Can assimilation of satellite observations improve subsurface biological properties in a numerical model? A case study for the Gulf of Mexico." Ocean Science 17, no. 4 (August 26, 2021): 1141–56. http://dx.doi.org/10.5194/os-17-1141-2021.
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Abstract. Given current threats to ocean ecosystem health, there is a growing demand for accurate biogeochemical hindcasts, nowcasts, and predictions. Provision of such products requires data assimilation, i.e., a comprehensive strategy for incorporating observations into biogeochemical models, but current data streams of biogeochemical observations are generally considered insufficient for the operational provision of such products. This study investigates to what degree the assimilation of satellite observations in combination with a priori model calibration by sparse BGC-Argo profiles can improve subsurface biogeochemical properties. The multivariate deterministic ensemble Kalman filter (DEnKF) has been implemented to assimilate physical and biological observations into a three-dimensional coupled physical–biogeochemical model, the biogeochemical component of which has been calibrated by BGC-Argo float data for the Gulf of Mexico. Specifically, observations of sea surface height, sea surface temperature, and surface chlorophyll were assimilated, and profiles of both physical and biological variables were updated based on the surface information. We assessed whether this leads to improved subsurface distributions, especially of biological properties, using observations from five BGC-Argo floats that were not assimilated. An alternative light parameterization that was tuned a priori using BGC-Argo observations was also applied to test the sensitivity of data assimilation impact on subsurface biological properties. Results show that assimilation of the satellite data improves model representation of major circulation features, which translate into improved three-dimensional distributions of temperature and salinity. The multivariate assimilation also improves the agreement of subsurface nitrate through its tight correlation with temperature, but the improvements in subsurface chlorophyll were modest initially due to suboptimal choices of the model's optical module. Repeating the assimilation run by using the alternative light parameterization greatly improved the subsurface distribution of chlorophyll. Therefore, even sparse BGC-Argo observations can provide substantial benefits for biogeochemical prediction by enabling a priori model tuning. Given that, so far, the abundance of BGC-Argo profiles in the Gulf of Mexico and elsewhere has been insufficient for sequential assimilation, updating 3D biological properties in a model that has been well calibrated is an intermediate step toward full assimilation of the new data types.
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Germineaud, Cyril, Jean-Michel Brankart, and Pierre Brasseur. "An Ensemble-Based Probabilistic Score Approach to Compare Observation Scenarios: An Application to Biogeochemical-Argo Deployments." Journal of Atmospheric and Oceanic Technology 36, no. 12 (December 2019): 2307–26. http://dx.doi.org/10.1175/jtech-d-19-0002.1.
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AbstractA cross-validation algorithm is developed to perform probabilistic observing system simulation experiments (OSSEs). The use of a probability distribution of “true” states is considered rather than a single “truth” using a cross-validation algorithm in which each member of an ensemble simulation is alternatively used as the “truth” and to simulate synthetic observation data that reflect the observing system to be evaluated. The other available members are used to produce an updated ensemble by assimilating the specific data, while a probabilistic evaluation of the observation impacts is obtained using a comprehensive set of verification skill scores. To showcase this new type of OSSE studies with tractable numerical costs, a simple biogeochemical application under the Horizon 2020 AtlantOS project is presented for a single assimilation time step, in order to investigate the value of adding biogeochemical (BGC)-Argo floats to the existing satellite ocean color observations. Further experiments must be performed in time as well for a rigorous and effective evaluation of the BGC-Argo network design, though some evidence from this preliminary work suggests that assimilating chlorophyll data from a BGC-Argo array of 1000 floats can provide additional error reduction at the surface, where the use of spatial ocean color data is limited (due to cloudy conditions), as well at depths ranging from 50 to 150 m.
Dissertations / Theses on the topic "BGC-ARGO floats"
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Petit, Flavien. "Developement and exploitation of new approaches for observation of phytoplankton community composition from BGC-Argo floats in open ocean." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS112.
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Le phytoplancton joue un rôle clé dans la régulation de nombreux cycles biogéochimiques. Il est responsable de la moitié de la production primaire mondiale, ce qui contribue à la chaîne alimentaire marine et régule les flux de carbone entre l'océan et l'atmosphère. Ces processus varient à la fois en fonction de la biomasse du phytoplancton et de la composition de la communauté. C'est donc un défi crucial que de pouvoir surveiller la biomasse du phytoplancton et la composition de la communauté à l'échelle mondiale. Le programme BioGeoChemical-Argo (BGC-Argo) vise à surveiller et à comprendre les processus biogéochimiques clés à l'échelle mondiale en développant un réseau de flotteurs Argo profilés équipés d'une série de capteurs biogéochimiques. Les flotteurs fournissent des informations sur la communauté phytoplanctonique en mesurant la fluorescence, un indicateur de la concentration en chlorophylle-a, utilisée comme indicateur de la biomasse phytoplanctonique. Cependant, il a été démontré que cette mesure est très variable à l'échelle mondiale. De plus, il reste encore compliqué de décrire la composition de la communauté phytoplanctonique à partir de capteurs in-situ. Dans un premier temps, ce travail de thèse présente le rôle de la communauté phytoplanctonique dans la variabilité de la réponse de fluorescence in-situ. Une base de donnée de mesure de fluorescence et de concentration en Chlorophylle-a a été étudié pour démontrer le role clé de la composition de la communauté phytoplanctonique sur le rapport entre fluorescence et concentration en chlorophylle-a à différentes échelles spatiales et temporelles. Ensuite, nous avons développé deux méthodes différentes pour évaluer la composition de la communauté phytoplanctonique. La première repose sur l'utilisation de la fluorescence multispectrale, pour estimer un indice taxonomique de la composition du phytoplancton. La seconde utilise une combinaison de mesures optiques et hydrographiques pour estimer la concentration de quatre différents groupes de plancton dans le carbone organique et la concentration du carbone organique particulaire total. Ces deux approches reposent sur des méthodes de machine learning. Dans le premier cas, nous avons établis un protocole qui a permis de récolter des données en laboratoire et sur le terrain pour mieux comprendre la réponse de fluorescence à différentes longueurs d’ondes en fonction de la composition de la communauté phytoplanctonique. Pour la deuxième méthode nous avons récolté des données en mer pendant un an pour pouvoir augmenter une base de donnée déjà existante. Ces deux méthodes ont permis de mettre en avant la possibilité d’estimer la composition de la communauté phytoplanctonique à partir des flotteurs profileurs BGC-ArgoPhytoplankton play a key role in the regulation of many biogeochemical cycles. It is responsible for half of the world's primary production, contributing to the marine food chain and regulating carbon fluxes between the ocean and the atmosphere. These processes vary with both phytoplankton biomass and community composition. It is therefore a critical challenge to monitor phytoplankton biomass and community composition on a global scale. The BioGeoChemical-Argo (BGC-Argo) program aims to monitor and understand key biogeochemical processes on a global scale by developing an array of profiled Argo floats equipped with an array of biogeochemical sensors. The floats provide information on the phytoplankton community by measuring fluorescence, an indicator of chlorophyll-a concentration, used as a proxy of phytoplankton biomass. However, this measurement has been shown to be highly variable on a global scale. Moreover, it remains complicated to describe the composition of the phytoplankton community from in-situ sensors. First, this thesis presents the role of the phytoplankton community in the variability of the in-situ fluorescence response. A database of fluorescence and chlorophyll-a concentration measurements was studied to demonstrate the key role of phytoplankton community composition on the relationship between fluorescence and chlorophyll-a concentration at different spatial and temporal scales. Then, we developed two different methods to evaluate the phytoplankton community composition. The first one is based on the use of multispectral fluorescence, to estimate a taxonomic index of phytoplankton composition. The second uses a combination of optical and hydrographic measurements to estimate the concentration of four different plankton groups in organic carbon and total particulate organic carbon concentration. Both approaches are based on machine learning methods. In the first case, we established a protocol that collected laboratory and field data to better understand the fluorescence response at different wavelengths as a function of phytoplankton community composition. For the second method we collected data at sea during one year to increase an already existing database. These two methods allowed us to highlight the possibility of estimating the composition of the phytoplankton community from the BGC-Argo profiling floats
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Cornec, Marin. "La dynamique des Maxima profonds de phytoplancton : une approche globale avec les flotteurs BGC-Argo." Electronic Thesis or Diss., Sorbonne université, 2020. http://www.theses.fr/2020SORUS383.
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L’objectif de cette thèse consiste à cartographier la distribution régionale et saisonnière des maxima profonds de chlorophylle a (« Deep Chlorophyll Maxima », DCM) dans l’océan global, à comprendre les paramètres environnementaux qui contrôlent leur formation et leur persistance, et à estimer leur contribution dans les bilans de production primaire (PP) à l’échelle globale. Cette approche se base sur les mesures des flotteurs profileurs Biogéochimique-Argo (BGC-Argo). Une méthode de détection des DCMs et de leur typologie ( maxima de biomasse ou de photoacclimatation) a été développée et appliquée sur ~60,000 profils de fluorescence de la chlorophylle a et du coefficient de rétrodiffusion particulaire (estimateurs respectifs de la concentration en chlorophylle a [Chla], et du carbone organique particulaire). A partir de cette classification, l’occurrence spatiale et temporelle des DCMs a été décrite dans 28 régions de l’océan mondial, permettant d’affiner la description de leurs caractéristiques, de grouper ces régions en quatre types selon leurs similarité, et d'en décrire les principales configurations environnementales (profils d'éclairement et de nitrates). Dans un second temps, l’impact des tourbillons de mésoéchelle a été étudié sur la présence des DCMs et sur leurs propriétés par la co-localisation de la base de profils BGC-Argo avec un atlas de tourbillons de mésoéchelle détectés par altimétrie satellite. Enfin une estimation de la contribution des DCMs à la PP globale a été estimée ainsi qu’une analyse de performance de deux modèles d’estimation des profils verticaux de [Chla] à partir des observations satellites en comparaison avec les mesures BGC-ArgoThe main objective of this thesis is to map the regional and seasonal distribution of Deep Chlorophyll Maxima (DCM) in the global ocean, to understand the environmental parameters that control their formation and persistence, and to estimate their contribution to global primary production (PP) budgets. This approach is based on measurements from the Biogeochemical-Argo Profiling Floats (BGC-Argo). A method for the detection of DCMs and their typology (biomass or photoacclimation maxima) has been developed and applied to ~60,000 chlorophyll a fluorescence profiles and particle backscatter coefficient (respective proxies of chlorophyll a concentration [Chla], and particulate organic carbon). From this classification, the spatial and temporal occurrence of DCMs was described in 28 regions of the world ocean, allowing to refine the description of their main characteristics (i.e. depth and intensity), and to group the regions into four main types according to the similarity of their DCMs. The estimation of vertical profiles of nitrate concentration and downward irradiance then allowed to describe the main environmental configurations of the different types of regions. In a second step, the impact of mesoscale eddies was studied on the presence of DCMs and their properties by co-locating the BGC-Argo profile database with an atlas of mesoscale eddies detected by satellite altimetry. Finally, an estimate of the contribution of DCMs to global PP was estimated, as well as a regional performance analysis of two models for estimating the vertical profiles of [Chla] from satellite observations, compared to the [Chla] profiles of the BGC-Argo database
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Ricour, Florian. "Towards a new insight of the carbon transport in the global ocean." Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS191.
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L'océan est connu pour jouer un rôle clé dans le cycle du carbone. Sans lui, les niveaux de CO2 atmosphérique seraient bien plus élevés qu'aujourd'hui grâce à la présence de pompes à carbone qui maintiennent un gradient de carbone inorganique dissous (DIC) entre la surface et le fond de l'océan. La pompe à carbone biologique (BCP) est principalement responsable de ce gradient. Elle consiste en une série de processus océaniques au cours desquels le carbone inorganique est converti en matière organique via la photosynthèse dans les eaux de surface, puis transporté vers l'intérieur de l'océan et éventuellement les sédiments où il sera séquestré par rapport à l'atmosphère pour des millions d'années. La BCP était longtemps considérée comme étant uniquement la déposition gravitationnelle de carbone organique particulaire (POC). Cependant, un nouveau paradigme pour la BCP a récemment été défini dans lequel des pompes d’origine physique et biologique d'injection de particules ont été ajoutées à la définition originale. Les pompes physiques d'injection de particules fournissent un moyen de mieux comprendre le transport de carbone organique dissous (DOC), tandis que les pompes biologique d'injection de particules se concentrent sur le transport de POC par des animaux migrant verticalement, quotidiennement ou saisonnièrement. Par conséquent, une meilleure compréhension de ces processus pourrait aider à combler l'écart entre le carbone quittant la surface et la demande de carbone dans l'océan profond. Pour aborder ce nouveau paradigme, ce travail bénéficiera de l'arrivée de capteurs récents équipant une nouvelle génération de flotteurs Biogéochimiques-Argo (BGC-Argo). La première partie se concentre sur le développement d'un modèle embarqué de classification de zooplancton pour l’Underwater Vision Profiler 6 (UVP6) avec des contraintes techniques et énergétiques strictes. La deuxième partie étudie les flux de particules et de carbone dans la mer du Labrador en utilisant des flotteurs BGC-Argo équipés pour la première fois de l'UVP6 et d'un piège à sédiments optique (OST), fournissant deux mesures indépendantes des particules. La dernière partie consiste à revisiter la BCP en utilisant un nouveau cadre appelé CONVERSE qui fait référence à la séquestration verticale continue du carbone dans la colonne d'eau. Avec cette nouvelle approche, nous réévaluons le carbone total séquestré par rapport à l'atmosphère (> 100 ans) par la BCP et ses voies de transport sur toute la colonne d'eau, par opposition à la séquestration de carbone généralement supposée en-dessous d'une profondeur de référence fixeThe ocean is known to play a key role in the carbon cycle. Without it, atmospheric CO2 levels would be much higher than what they are today thanks to the presence of carbon pumps that maintain a gradient of dissolved inorganic carbon (DIC) between the surface and the deep ocean. The biological carbon pump (BCP) is primarily responsible for this gradient. It consists in a series of ocean processes through which inorganic carbon is fixed as organic matter by photosynthesis in sunlit surface waters and then transported to the ocean interior and possibly the sediment where it will be sequestered from the atmosphere for millions of years. The BCP was long thought as solely the gravitational settling of particulate organic carbon (POC). However, a new paradigm for the BCP has recently been defined in which physically and biologically mediated particle injection pumps have been added to the original definition. Physically mediated particle injection pumps provide a pathway to better understand the transport of dissolved organic carbon (DOC) whereas biologically mediated particle injection pumps focus on the transport of POC by vertically migrating animals, either daily or seasonally. Therefore, a better understanding of these processes could help bridge the gap between carbon leaving the surface and carbon demand in the ocean interior. To address this new paradigm, this work will benefit from the advent of recent sensors that equip a new generation of Biogeochemical-Argo floats (BGC-Argo). The first part focuses on the development of an embedded zooplankton classification model for the Underwater Vision Profiler 6 (UVP6) under strict technical and energy constraints. The second part studies particle and carbon fluxes in the Labrador Sea using BGC-Argo floats equipped for the first time with the UVP6 and an optical sediment trap (OST), providing two independent measurements of sinking particles. The last part consists in revisiting the BCP using a new framework called CONVERSE for Continuous Vertical Sequestration. With this new approach, we re-evaluate the total carbon sequestered from the atmosphere (> 100 years) by the BCP and its transport pathways on the entire water column, in contrast to the carbon sequestration typically assumed below a fixed reference depth
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Terrats, Louis. "Le flux de carbone particulaire et le lien avec la communauté phytoplanctonique : une approche par flotteurs-profileurs biogéochimiques." Electronic Thesis or Diss., Sorbonne université, 2022. https://accesdistant.sorbonne-universite.fr/login?url=https://theses-intra.sorbonne-universite.fr/2022SORUS550.pdf.
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L'Océan est un acteur majeur du climat en échangeant avec l'atmosphère de grandes quantités de carbone. Le carbone atmosphérique est fixé à la surface de l’océan par le phytoplancton qui le transforme en carbone biogène, dont une partie est transportée vers l’océan profond par des mécanismes physiques et biologiques; il s’agit de la Pompe Biologique de Carbone (BCP). Une infime partie de ce carbone biogène atteindra des profondeurs suffisantes pour être séquestré durant plusieurs siècles avant qu'il ne retourne dans l'atmosphère, régulant les concentrations atmosphériques de CO2. Aujourd'hui, nous en savons assez sur la BCP pour reconnaitre son importance dans le climat, mais nos connaissances sur son fonctionnement sont limitées en raison d’un échantillonnage insuffisant des flux de carbone biogène. Dans ce travail de thèse, nous avons utilisé les flotteurs BioGéoChimique-Argo, plateformes d’observations conçues pour résoudre le problème du sous-échantillonnage, afin d’explorer un mécanisme majeur de la BCP qui est la pompe gravitationnelle. La pompe gravitationnelle est le transport du carbone biogène sous la forme de particules organiques (POC) qui sédimentent de la surface vers l’océan profond. Notre étude de la pompe gravitationnelle se divise en trois axes. Le premier axe consiste au développement d’une méthode pour détecter les floraisons de coccolithophoridés, groupe phytoplanctonique majeur qui a potentiellement un contrôle important sur le transport du POC en profondeur. Le deuxième axe est centré sur la variabilité saisonnière et régionale des flux de POC dans l’Océan Austral, qui est une zone sous-échantillonnée mais dans laquelle plusieurs flotteurs ont été déployés avec une trappe optique à sédiments (OST). Seuls une dizaine de flotteurs sont équipés d’OST, ce qui est faible en comparaison avec l’ensemble de la flotte BGC-Argo (i.e. plusieurs centaines de flotteurs). C’est pourquoi nous avons développé, dans le troisième axe, une méthode pour estimer le flux de POC avec les capteurs standards du programme BGC-Argo. Cette méthode a ensuite été appliquée à une centaine de flotteurs pour décrire la variabilité saisonnière du flux de POC dans de nombreuses régions océaniques. Dans ce travail de thèse, nous mettons également en évidence le lien entre la variabilité des flux et la nature des particules en surface. Par exemple, nous avons calculé des relations entre la composition de la communauté phytoplanctonique et les flux de POC à 1000m. En utilisant ces relations, nous avons ensuite utilisé les observations satellites pour extrapoler les flux de POC à de larges échelles spatiales, comme à l’ensemble de l’Océan Austral et de l’océan globalThe ocean plays a key role in the climate by exchanging large quantities of carbon with the atmosphere. Atmospheric carbon is fixed at the ocean surface by phytoplankton that transforms it into biogenic carbon, part of which is transported to the deep ocean by physical and biological mechanisms; this is the Biological Carbon Pump (BCP). A tiny fraction of this biogenic carbon reaches sufficient depths to be sequestered for several centuries before it returns to the atmosphere, thus regulating concentrations of atmospheric CO2. Today, we know enough about the BCP to recognize its importance in climate, but our knowledge of its functioning is limited due to insufficient sampling of biogenic carbon fluxes. Here, we used BioGeoChimical-Argo floats, observational platforms designed to solve the undersampling problem, to explore a major mechanism of the BCP called the gravitational pump. The gravitational pump is the transport of biogenic carbon in the form of organic particles (POC) that sink from the surface into the deep ocean. Our study of the gravitational pump is divided into three axes. The first axis consisted of developing a method to detect blooms of coccolithophores, a major phytoplankton group that potentially has an important control on the transport of POC at depth. The second axis focused on the seasonal and regional variability of POC fluxes in the Southern Ocean, an undersampled area in which several floats have been deployed with an optical sediment trap (OST). Only ten floats were equipped with an OST, which is low compared to the whole BGC-Argo fleet (i.e. several hundred floats). Therefore, in the third axis, we developed a method to estimate the POC flux with the standard sensors of BGC-Argo floats. This method was then applied to hundreds of floats to describe the seasonal variability of the POC flux in many regions. In this study, we also highlighted the link between the POC flux and the nature of surface particles. For example, we calculated relationships between phytoplankton community composition and POC flux at 1000m. Using these relationships, we then used satellite observations to extrapolate POC flux to large spatial scales, such as the entire Southern Ocean and the global ocean
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Barbieux, Marie. "Étude des relations bio-optiques dans l’océan global et du fonctionnement biogéochimique des maxima de subsurface de chlorophylle en Méditerranée à partir des mesures des flotteurs profileurs BGC-Argo." Electronic Thesis or Diss., Sorbonne université, 2019. http://www.theses.fr/2019SORUS490.
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Cette thèse a pour objectif principal de mieux appréhender la dynamique spatio-temporelle et verticale de la biomasse phytoplanctonique dans l’océan ouvert. Dans un premier temps, nous avons étudié la variabilité de la relation entre le coefficient de rétrodiffusion particulaire (bbp), un estimateur bio-optique du carbone organique particulaire, et la concentration en chlorophylle a (Chla) à l’échelle globale. Dans les régimes subpolaires, des changements concomitants de Chla et bbp correspondent à des variations de la biomasse du phytoplancton. Au contraire, dans les régimes subtropicaux oligotrophes, un découplage entre les deux variables peut être attribué aux processus de photoacclimation du phytoplancton ou à un changement de l'abondance relative des particules non algales au sein de l’assemblage particulaire. La Mer Méditerranée constitue, quant à elle, un régime intermédiaire à ces deux situations extrêmes. En utilisant le couplage entre bbp et Chla nous avons, dans un second temps, analysé la dynamique saisonnière et régionale des maxima profonds de Chla (SCMs) à l’échelle du bassin méditerranéen en développant notamment une classification des profils verticaux de Chla et de bbp. En Méditerranée orientale, des SCMs correspondant à une augmentation de la Chla intracellulaire des cellules phytoplanctoniques (photoacclimatation) ont été identifiés. Au contraire, des SCMs résultant d’une réelle augmentation de la biomasse carbonée en profondeur (SBMs) ont été observés de manière récurrente en Méditerranée occidentale. Suivant la piste d’une contribution potentiellement significative des SCMs à la production de carbone dans l’océan global, la production communautaire brute dans la couche de subsurface a été, dans un troisième temps, quantifiée. Pour cela, une méthode bio-optique d’estimation de la production basée sur le cycle diurne des propriétés bio-optiques a été utilisée dans deux régions distinctes de la Méditerranée durant la période estivale oligotrophe. Nous avons ainsi mis en évidence une importante contribution des SCMs à la production totale réalisée dans la couche productive, pouvant atteindre plus de 40% en Méditerranée occidentaleThe main objective of this thesis is to improve our understanding of the spatio-temporal and vertical variability of phytoplankton biomass in the open ocean. First, we investigated the variability of the relationship between the particulate backscattering coefficient (bbp), a bio-optical proxy of the particulate organic carbon, and the chlorophyll a concentration (Chla) at a global scale. In subpolar regimes, concomitant changes in Chla and bbp correspond to variations in phytoplankton biomass. In contrast, in subtropical regimes, a decoupling between the two variables was attributed to photoacclimation processes or a change in the relative abundance of non-algal particles to the particulate assemblage. The Mediterranean Sea stands as an intermediate regime between these two end-members. Next, we analysed the seasonal and regional dynamics of subsurface Chla maxima (SCMs) in the Mediterranean basin by developing a classification of the vertical profiles of Chla and bbp. In the Eastern Mediterranean, SCMs corresponded to an increase in the intracellular Chla induced by photoacclimation of phytoplankton cells. However, in the Western basin of the Mediterranean Sea SCMs corresponded to an actual increase in carbon biomass at depth (SBMs). Lastly, we investigated the potentially significant contribution of SCMs to carbon production, by quantifying the gross community production in the subsurface layer. A method based on the diurnal cycle of bio-optical properties was used in order to estimate production in two distinct regions of the Mediterranean Sea during the oligotrophic season. Our study revealed that SCMs might contribute over 40% of the depth-integrated production in some areas, thereby suggesting the potentially important biogeochemical role of SCMs
Conference papers on the topic "BGC-ARGO floats"
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Jemai, Ahlem, Hendrik Bunger, Rohan Henkel, Daniela Vos, Jochen Wollschlager, and Oliver Zielinski. "Hyperspectral underwater light field sensing onboard BGC-Argo Floats." In OCEANS 2021: San Diego – Porto. IEEE, 2021. http://dx.doi.org/10.23919/oceans44145.2021.9705770.
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Stahl, Frederic, Lars Nolle, Oliver Zielinski, and Ahlem Jemai. "A Model for Predicting the Amount of Photosynthetically Available Radiation from BGC-ARGO Float Observations in the Water Column." In 36th ECMS International Conference on Modelling and Simulation. ECMS, 2022. http://dx.doi.org/10.7148/2022-0174.
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Modern oceanography uses, amongst other platforms, automated diving devices, which are drifting with the ocean current whilst continuously collecting vertical profiles of environmental parameters. One of the important parameters is photosynthetically available radiation (PAR). It was studied in this work whether the PAR values can be reconstructed by combinations of measurements from the remaining onboard sensors with specific wavelength. If a reconstruction of PAR is possible, this would allow allocating the sensor with a further specific wavelength instead of PAR. Having available more spectral information could for example enable natural science researchers to better distinguish phytoplankton or UV radiation. Therefore, data from three different expeditions from different regions of the world were used to model PAR using multiple linear regression and regression trees (RT). multiple linear regression achieved an R2 value of 0.970 for the combined dataset and RT achieved an R2 value of 0.960. Hence, the models are accurate enough to predict the PAR parameter without the need for a dedicated PAR sensor. Thus the PAR sensor could be allocated instead with a further specific wavelength.
Reports on the topic "BGC-ARGO floats"
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Cossarini, Gianpiero. Results of the BGC data assimilation. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.10.
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This document presents the results of simulations that include glider profiles assimilation. Simulations are performed with the Marine Copernicus operational biogeochemical model system of the Mediterranean Sea. The deliverable shows that the assimilation of BGC-glider is feasible in the contest of biogeochemical operational systems and that it is built upon the experience of BGC-Argo float data assimilation. Different configuration of the assimilation of glider data have been tested to assess the impact of the physical and biogeochemical glider observations. The deliverable also describes the pre-processing activities of the BGC-glider data to provide qualified observations for the data assimilation and the cross validation of chlorophyll glider data with other sensors (ocean colour and BGC-Argo floats). Results of the simulations show that BGC-glider data assimilation, as already shown for BGC-Argo floats, provides complementary information with respect to Ocean Colour data (which is the only or the most commonly assimilated data in biogeochemical operational systems). Beside their relatively limited horizontal spatial impact, the assimilation of BGC profiles can constrain model simulations for relevant biogeochemical processes in specific periods (summer and transition periods) and layers (surface and subsurface). Results also highlight the importance of the assimilation modelling systems that can efficiently resolve the inconsistencies between chlorophyll observations of different sensors. (EuroSea Deliverable ; D4.10)
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Wimart-Rousseau, Cathy, Marine Fourrier, and Fiedler Björn. Development of BGCArgo data quality validation based on an integrative multiplatform approach. EuroSea, 2022. http://dx.doi.org/10.3289/eurosea_d7.2.
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This report presents the results of Task 7.3 on “Development of BGC-Argo data quality validation based on an integrative multiplatform approach”. Observing changes in ocean conditions on the spatiotemporal scales necessary to constrain carbon uptake is a challenge. Defined as an Essential Ocean Variable (EOV) by the Global Ocean Observing System (GOOS, e.g., Tanhua et al., 2019), pH is relevant to assess numerous crucial questions regarding the oceanic evolution in response to the current global changes. However, the large spatiotemporal variability of this carbonate system parameter requires sustained observations to decipher trends and punctual events. Within this scope, numerous pH sensors suitable for deployments both on autonomous observing tools and fixed stations have been developed. Nevertheless, as interpreting changes relies on accurate data, and because offsets or drifts in pH data might appear in response to changes in the sensor k0 constant, a consistent and rigorous correction procedure to quality-control and process the data has been implemented. This report presents the application of this method to pH data acquired by BGC-Argo floats launched in the Tropical Atlantic area. (EuroSea Deliverable, D7.2)
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Fourrier, Marine. Integration of in situ and satellite multi-platform data (estimation of carbon flux for trop. Atlantic). EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d7.6.
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This report presents the results of task 7.3 on “Quantification of improvements in carbon flux data for the tropical Atlantic based on the multi-platform and neural network approach”. To better constrain changes in the ocean’s capture and sequestration of CO2 emitted by human activities, in situ measurements are needed. Tropical regions are considered to be mostly sources of CO2 to the atmosphere due to specific circulation features, with large interannual variability mainly controlled by physical drivers (Padin et al., 2010). The tropical Atlantic is the second largest source, after the tropical Pacific, of CO2 to the atmosphere (Landschützer et al., 2014). However, it is not a homogeneous zone, as it is affected by many physical and biogeochemical processes that vary on many time scales and affect surrounding areas (Foltz et al., 2019). The Tropical Atlantic Observing System (TAOS) has progressed substantially over the past two decades. Still, many challenges and uncertainties remain to require further studies into the area’s role in terms of carbon fluxes (Foltz et al., 2019). Monitoring and sustained observations of surface oceanic CO2 are critical for understanding the fate of CO2 as it penetrates the ocean and during its sequestration at depth. This deliverable relies on different observing platforms deployed specifically as part of the EuroSea project (a Saildrone, and 5 pH-equipped BGC-Argo floats) as well as on the platforms as part of the TAOS (CO2-equipped moorings, cruises, models, and data products). It also builds on the work done in D7.1 and D7.2 on the deployment and quality control of pH-equipped BGC-Argo floats and Saildrone data. Indeed, high-quality homogeneously calibrated carbonate variable measurements are mandatory to be able to compute air-sea CO2 fluxes at a basin scale from multiple observing platforms. (EuroSea Deliverable, D7.6)