Literatura científica selecionada sobre o tema "Nemo-Pisces"

Abstract. The global budget of tropospheric carbonyl sulfide (OCS) is believed to be at equilibrium because background air concentrations have remained roughly stable over at least the last decade. Since the uptakes of OCS by leaves (associated to photosynthesis) and soils have been revised significantly upwards recently, an equilibrated budget can only be obtained with a compensatory source of OCS. It has been assumed that the missing source of OCS comes from the low latitude ocean, following the incident solar flux. The present work uses parameterizations of major production and removal processes of organic compounds in the NEMO-PISCES Ocean General Circulation and Biogeochemistry Model to assess the marine source of OCS. In addition, the OCS photo-production rates computed with the NEMO-PISCES model were evaluated independently using UV absorption coefficient of chromophoric dissolved organic matter (derived from satellite ocean color) and apparent quantum yields available in the literature. Our simulations show global direct marine emissions of COS in the range of 573–3997 Gg S yr−1, depending mostly on the quantification of the absorption rate of chromophoric dissolved organic matter. The high estimates on that range are unlikely, as they correspond to a formulation that most likely overestimate photo-production process. Low and medium (813 Gg S yr−1) estimates derived from the NEMO-PISCES model are however consistent spatially and temporally with the suggested missing source of Berry et al. (2013), allowing thus to close the global budget of OCS given the recent estimates of leaf and soil OCS uptakes.

Abstract. The global budget of tropospheric carbonyl sulfide (OCS) is believed to be at equilibrium because background air concentrations have remained roughly stable over at least the last decade. Since the uptake of OCS by leaves (associated with photosynthesis) and soils have been revised significantly upwards recently, an equilibrated budget can only be obtained with a compensatory source of OCS. It has been assumed that the missing source of OCS comes from the low-latitude ocean, following the incident solar flux. The present work uses parameterizations of major production and removal processes of organic compounds in the NEMO-PISCES (Nucleus for European Modelling of the Ocean, Pelagic Interaction Scheme for Carbon and Ecosystem Studies) ocean general circulation and biogeochemistry model to assess the marine source of OCS. In addition, the OCS photo-production rates computed with the NEMO-PISCES model~were evaluated independently using the UV absorption coefficient of chromophoric dissolved organic matter (derived from satellite ocean color data) and apparent quantum yields available in the literature. Our simulations show global direct marine emissions of OCS in the range of 573–3997 GgS yr−1, depending mostly on the quantification of the absorption rate of chromophoric dissolved organic matter. The high estimates of that range are unlikely, as they correspond to a formulation that most likely overestimate photo-production process. Low and medium (813 GgS yr−1) estimates derived from the NEMO-PISCES model are however consistent spatially and temporally~with the suggested missing source of Berry et al. (2013), allowing us thus to close the global budget of OCS given the recent estimates of leaf and soil OCS uptake.

Abstract. PISCES-v2 is a biogeochemical model which simulates the lower trophic levels of marine ecosystem (phytoplankton, microzooplankton and mesozooplankton) and the biogeochemical cycles of carbon and of the main nutrients (P, N, Fe, and Si). The model is intended to be used for both regional and global configurations at high or low spatial resolutions as well as for short-term (seasonal, interannual) and long-term (climate change, paleoceanography) analyses. There are twenty-four prognostic variables (tracers) including two phytoplankton compartments (diatoms and nanophytoplankton), two zooplankton size-classes (microzooplankton and mesozooplankton) and a description of the carbonate chemistry. Formulations in PISCES-v2 are based on a mixed Monod–Quota formalism: on one hand, stoichiometry of C/N/P is fixed and growth rate of phytoplankton is limited by the external availability in N, P and Si. On the other hand, the iron and silicium quotas are variable and growth rate of phytoplankton is limited by the internal availability in Fe. Various parameterizations can be activated in PISCES-v2, setting for instance the complexity of iron chemistry or the description of particulate organic materials. So far, PISCES-v2 has been coupled to the NEMO and ROMS systems. A full description of PISCES-v2 and of its optional functionalities is provided here. The results of a quasi-steady state simulation are presented and evaluated against diverse observational and satellite-derived data. Finally, some of the new functionalities of PISCES-v2 are tested in a series of sensitivity experiments.

Abstract. PISCES-v2 (Pelagic Interactions Scheme for Carbon and Ecosystem Studies volume 2) is a biogeochemical model which simulates the lower trophic levels of marine ecosystems (phytoplankton, microzooplankton and mesozooplankton) and the biogeochemical cycles of carbon and of the main nutrients (P, N, Fe, and Si). The model is intended to be used for both regional and global configurations at high or low spatial resolutions as well as for short-term (seasonal, interannual) and long-term (climate change, paleoceanography) analyses. There are 24 prognostic variables (tracers) including two phytoplankton compartments (diatoms and nanophytoplankton), two zooplankton size classes (microzooplankton and mesozooplankton) and a description of the carbonate chemistry. Formulations in PISCES-v2 are based on a mixed Monod–quota formalism. On the one hand, stoichiometry of C / N / P is fixed and growth rate of phytoplankton is limited by the external availability in N, P and Si. On the other hand, the iron and silicon quotas are variable and the growth rate of phytoplankton is limited by the internal availability in Fe. Various parameterizations can be activated in PISCES-v2, setting, for instance, the complexity of iron chemistry or the description of particulate organic materials. So far, PISCES-v2 has been coupled to the Nucleus for European Modelling of the Ocean (NEMO) and Regional Ocean Modeling System (ROMS) systems. A full description of PISCES-v2 and of its optional functionalities is provided here. The results of a quasi-steady-state simulation are presented and evaluated against diverse observational and satellite-derived data. Finally, some of the new functionalities of PISCES-v2 are tested in a series of sensitivity experiments.

Dissolved oxygen (DO) is one of the most chemical primary data in supported life for marine organisms. Ministry of Marine Affairs and Fisheries Republic of Indonesia through Infrastructure Development for Space Oceanography (INDESO) Project provides dissolved oxygen data services in Indonesian Seas for 7 days backward and 10 days ahead (9,25 km x 9.25 km, 1 daily). The data based on Biogeochemical model (PISCES) coupled with hydrodynamic model (NEMO), with input data from satellite acquisition. This study investigated the performance and accuracy of dissolved oxygen from PISCES model, by comparing with the measurement in situ data in Indonesian Seas specifically in three outermost islands of Indonesia (Biak Island, Rote Island, and Tanimbar Island). Results of standard deviation values between in situ DO and model are around two (St.dev ± 2). Based on the calculation of linear regression between in situ DO with the standard deviation obtained a high determinant coefficient, greater than 0.9 (R2 ≥ 0.9). Furthermore, RMSE calculation showed a minor error, less than 0.05. These results showed that the equation of the linear regression might be used as a correction equation to gain the verified dissolved oxygen.

Abstract. As part of the Copernicus Marine Environment Monitoring Service (CMEMS), a physical–biogeochemical coupled model system has been developed to monitor and forecast the ocean dynamics and marine ecosystem of the European waters and more specifically on the Iberia–Biscay–Ireland (IBI) area. The CMEMS IBI coupled model covers the north-east Atlantic Ocean from the Canary Islands to Iceland, including the North Sea and the western Mediterranean, with a NEMO-PISCES 1∕36∘ model application. The coupled system has been providing 7 d weekly ocean forecasts for CMEMS since April 2018. Prior to its operational launch, a pre-operational qualification simulation (2010–2016) has allowed assessing the model's capacity to reproduce the main biogeochemical and ecosystem features of the IBI area. The objective of this paper is then to describe the consistency and skill assessment of the PISCES biogeochemical model using this 7-year qualification simulation. The model results are compared with available satellite estimates as well as in situ observations (ICES, EMODnet and BGC-Argo). The simulation successfully reproduces the spatial distribution and seasonal cycles of oxygen, nutrients, chlorophyll a and net primary production, and confirms that PISCES is suitable at such a resolution and can be used for operational analysis and forecast applications. This model system can be a useful tool to better understand the current state and changes in the marine biogeochemistry of European waters and can also provide key variables for developing indicators to monitor the health of marine ecosystems. These indicators may be of interest to scientists, policy makers, environmental agencies and the general public.

Abstract. Ocean biogeochemical models are key tools for both scientific and operational applications. Nevertheless the cost of these models is often expensive because of the large number of biogeochemical tracers. This has motivated the development of multi-grid approaches where ocean dynamics and tracer transport are computed on grids of different spatial resolution. However, existing multi-grid approaches to tracer transport in ocean modelling do not allow the computation of ocean dynamics and tracer transport simultaneously. This paper describes a new multi-grid approach developed for accelerating the computation of passive tracer transport in the Nucleus for European Modelling of the Ocean (NEMO) ocean circulation model. In practice, passive tracer transport is computed at runtime on a grid with coarser spatial resolution than the hydrodynamics, which reduces the CPU cost of computing the evolution of tracers. We describe the multi-grid algorithm, its practical implementation in the NEMO ocean model, and discuss its performance on the basis of a series of sensitivity experiments with global ocean model configurations. Our experiments confirm that the spatial resolution of hydrodynamical fields can be coarsened by a factor of 3 in both horizontal directions without significantly affecting the resolved passive tracer fields. Overall, the proposed algorithm yields a reduction by a factor of 7 of the overhead associated with running a full biogeochemical model like PISCES (with 24 passive tracers). Propositions for further reducing this cost without affecting the resolved solution are discussed.

Abstract. Process-based numerical models are a useful tool for studying marine ecosystems and associated biogeochemical processes in ice-covered regions where observations are scarce. To this end, CSIB v1 (Canadian Sea-ice Biogeochemistry version 1), a new sea-ice biogeochemical model, has been developed and embedded into the Nucleus for European Modelling of the Ocean (NEMO) modelling system. This model consists of a three-compartment (ice algae, nitrate, and ammonium) sea-ice ecosystem and a two-compartment (dimethylsulfoniopropionate and dimethylsulfide) sea-ice sulfur cycle which are coupled to pelagic ecosystem and sulfur-cycle models at the sea-ice–ocean interface. In addition to biological and chemical sources and sinks, the model simulates the horizontal transport of biogeochemical state variables within sea ice through a one-way coupling to a dynamic-thermodynamic sea-ice model (LIM2; the Louvain-la-Neuve Sea Ice Model version 2). The model results for 1979 (after a decadal spin-up) are presented and compared to observations and previous model studies for a brief discussion on the model performance. Furthermore, this paper provides discussion on technical aspects of implementing the sea-ice biogeochemistry and assesses the model sensitivity to (1) the temporal resolution of the snowfall forcing data, (2) the representation of light penetration through snow, (3) the horizontal transport of sea-ice biogeochemical state variables, and (4) light attenuation by ice algae. The sea-ice biogeochemical model has been developed within the generic framework of NEMO to facilitate its use within different configurations and domains, and can be adapted for use with other NEMO-based sub-models such as LIM3 (the Louvain-la-Neuve Sea Ice Model version 3) and PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies).

Abstract. Surface chlorophyll concentrations inferred from satellite images suggest a strong influence of the mesoscale activity on biogeochemical variability within the oligotrophic regions of the Gulf of Mexico (GoM). More specifically, long-living anticyclonic Loop Current eddies (LCEs) are shed episodically from the Loop Current and propagate westward. This study addresses the biogeochemical response of the LCEs to seasonal forcing and show their role in driving phytoplankton biomass distribution in the GoM. Using an eddy resolving (1/12∘) interannual regional simulation, it is shown that the LCEs foster a large biomass increase in winter in the upper ocean. It is based on the coupled physical–biogeochemical model NEMO-PISCES (Nucleus for European Modeling of the Ocean and Pelagic Interaction Scheme for Carbon and Ecosystem Studies) that yields a realistic representation of the surface chlorophyll distribution. The primary production in the LCEs is larger than the average rate in the surrounding open waters of the GoM. This behavior cannot be directly identified from surface chlorophyll distribution alone since LCEs are associated with a negative surface chlorophyll anomaly all year long. This anomalous biomass increase in the LCEs is explained by the mixed-layer response to winter convective mixing that reaches deeper and nutrient-richer waters.

La mer Méditerranée est considérée comme un point chaud du changement climatique. Cette région très peuplée au climat aride devrait voir son climat devenir plus chaud et plus aride encore, tout en subissant une pression anthropique toujours plus forte. Dans ce contexte, de nombreuses données physiques et biogéochimiques sont actuellement relevées en mer Méditerranée, dans le cadre du projet MERMEX, afin de mieux étudier et comprendre les cycles biogéochimiques en mer Méditerranée. Complémentaire aux mesures, la modélisation est un outil unique pour aider à comprendre et quantifier les processus contrôlant la biogéochimie marine de la Méditerranée, ses spécificités et son évolution future. Dans cette étude, nous proposons la mise en place, et l’évaluation d’un modèle régional couplé dynamique - biogéochimie marine (NEMO-PISCES), à haute résolution, qui sera le premier modèle couvrant l’intégralité de la mer Méditerranée disponible pour la communauté MERMEX. Ainsi, après avoir évalué la dynamique du modèle NEMO-MED12, utilisée comme forçage, grâce à une simulation de traceurs passifs (CFC), nous effectuons les premières utilisations de cet outil, avec lequel (i) nous évaluons la quantité de carbone anthropique en mer Méditerranée grâce à une approche par perturbation, ainsi que l’acidification associée des masses d’eau ; (ii) nous effectuons une étude des régimes trophiques en mer Méditerranée, tels que perçus par le modèle, sur différentes couches de la zone euphotique
The Mediterranean Sea is considered as a hot spot of climate change. This arid region, already under high anthropogenic influence, is said to become even warmer and drier, with still an increasing anthropogenic pressure. In this context, numerous physical and biogeochemical data are currently collected in the Mediterranean Sea, within the MERMEX project, enabling to better study and understand the Mediterranean biogeochemical cycles. Complementary to in-situ observations, modelling is an unique tool that helps to understand and quantify biogeochemical controling processes in the Mediterranean Sea, its specificity, and its evolution. In this study, we propose the setting and evaluation of a regional, high resolution, marine dynamicalbiogeochemical coupled model (NEMO-PISCES). It will be the first model available for the MERMEX community, that covers the whole Mediterranean Sea. Therefor, after the evaluation of NEMO-MED12 dynamical forcing fields, within passive tracers simulation (CFC), firsts use of this tool have been made : (i) we have evaluated anthropogenic carbon uptake and induced acidification of the Mediterranean Sea, within a perturbation approach ; (ii) we have analysed Mediterranean Sea trophic regimes, as represented by the model, for different layers of the photic zone

La mer Méditerranée est considérée comme un point chaud du changement climatique. Cette région très peuplée au climat aride devrait voir son climat devenir plus chaud et plus aride encore, tout en subissant une pression anthropique toujours plus forte. Dans ce contexte, de nombreuses données physiques et biogéochimiques sont actuellement relevées en mer Méditerranée, dans le cadre du projet MERMEX, afin de mieux étudier et comprendre les cycles biogéochimiques en mer Méditerranée. Complémentaire aux mesures, la modélisation est un outil unique pour aider à comprendre et quantifier les processus contrôlant la biogéochimie marine de la Méditerranée, ses spécificités et son évolution future. Dans cette étude, nous proposons la mise en place, et l’évaluation d’un modèle régional couplé dynamique - biogéochimie marine (NEMO-PISCES), à haute résolution, qui sera le premier modèle couvrant l’intégralité de la mer Méditerranée disponible pour la communauté MERMEX. Ainsi, après avoir évalué la dynamique du modèle NEMO-MED12, utilisée comme forçage, grâce à une simulation de traceurs passifs (CFC), nous effectuons les premières utilisations de cet outil, avec lequel (i) nous évaluons la quantité de carbone anthropique en mer Méditerranée grâce à une approche par perturbation, ainsi que l’acidification associée des masses d’eau ; (ii) nous effectuons une étude des régimes trophiques en mer Méditerranée, tels que perçus par le modèle, sur différentes couches de la zone euphotique
The Mediterranean Sea is considered as a hot spot of climate change. This arid region, already under high anthropogenic influence, is said to become even warmer and drier, with still an increasing anthropogenic pressure. In this context, numerous physical and biogeochemical data are currently collected in the Mediterranean Sea, within the MERMEX project, enabling to better study and understand the Mediterranean biogeochemical cycles. Complementary to in-situ observations, modelling is an unique tool that helps to understand and quantify biogeochemical controling processes in the Mediterranean Sea, its specificity, and its evolution. In this study, we propose the setting and evaluation of a regional, high resolution, marine dynamicalbiogeochemical coupled model (NEMO-PISCES). It will be the first model available for the MERMEX community, that covers the whole Mediterranean Sea. Therefor, after the evaluation of NEMO-MED12 dynamical forcing fields, within passive tracers simulation (CFC), firsts use of this tool have been made : (i) we have evaluated anthropogenic carbon uptake and induced acidification of the Mediterranean Sea, within a perturbation approach ; (ii) we have analysed Mediterranean Sea trophic regimes, as represented by the model, for different layers of the photic zone

En Atlantique Nord, le gyre subpolaire (GSP) joue un rôle clé dans le cycle du carbone et la variabilité du climat. Il est le siège d'un bloom phytoplanctonique printanier vigoureux, entretenu par le transport saisonnier de nutriments et modulé par la lumière. Les macro-nutriments (NO3, PO4, DSi) sont principalement apportés à la couche de mélange (CM) par transport latéral depuis les hautes latitudes (principalement par les détroits de Davis et d'Hudson), et les basses latitudes par le Courant Nord-Atlantique (NAC), ou par transport vertical depuis la base de la CM où des concentrations plus élevées sont présentes. Il a été suggéré que ces processus d'approvisionnement varient en fonction de l'Oscillation Nord-Atlantique (NAO), un mode majeur de variabilité climatique naturelle. Lorsque l'indice de NAO est négatif, comme ce fut le cas du milieu des années 1990 à la fin des années 2000, les conditions physiques sont similaires à celles prévues sous changement climatique (i.e. réchauffement et réduction de la salinité et de la convection profonde (CP), ralentissement de la circulation méridienne de retournement de l'Atlantique, augmentation de la stratification). Dans la même période, une baisse des concentrations en nutriments a été observée dans toute la région, conduisant à l'hypothèse que les processus sous-jacents pourraient être similaires à ceux qui agissent sous changement climatique pour réduire les niveaux de nutriments dans la CM.L'objectif principal de cette thèse est d'analyser et de quantifier les contributions des processus dynamiques (i.e. le transport latéral et vertical) à la variabilité observée des concentrations en nutriments dans la CM du GSP entre 1980 et 2015. L'analyse utilise un modèle couplé physique-biogéochimie (NEMO-PISCES) discrétisé sur une grille au quart de degré. Une évaluation de la variabilité spatiale et temporelle des concentrations en nutriments et des principaux processus physiques du modèle, tels que la CP dans la mer du Labrador et le transport latéral d'eau et de nutriments, a été réalisée en comparaison avec des données d'observation. L'accent a d'abord été mis sur la mer du Labrador, qui est une région caractérisée par une CP hivernale intense et variable, cela en fait un laboratoire idéal pour distinguer le rôle de la variabilité de la CP hivernale de celui de la circulation du GSP et des apports Arctique. Malgré son affaiblissement, la contribution du transport de DSi arctique à travers les détroits de Davis et d'Hudson à la variabilité observée des nutriments s'est avérée négligeable (= 3 %). La CP a été identifiée comme le principal moteur de la baisse des concentrations de DSi pré-bloom en mer du Labrador. L'étude a ensuite été étendue à l'ensemble du GSP avec une évaluation de la variabilité récente des concentrations en nutriments dans la CM par l'analyse de la variabilité des transports latéraux et verticaux entre les périodes de forte NAO positive, de NAO négative et la période qui suit. Outre la variabilité temporelle des concentrations en réponse au forçage atmosphérique, des différences régionales apparaissent, avec une contribution dominée par le transport vertical dans les mers du Labrador et d'Irminger, induites par des variations de la profondeur de la CM. La variabilité des transports de nutriments traversant le GSP est cohérente avec la variabilité des nutriments au sein du GSP, mais découplée des nutriments transportés par le Gulf stream via le NAC à l'ouest de 38°N.Dans cette thèse, j'ai mis en évidence la prédominance du mélange vertical dans la variabilité contemporaine des concentrations de nutriments par rapport aux apports latéraux. Je montre qu'un ralentissement de la circulation générale associé à une stratification de la colonne d'eau conduit à l'affaiblissement des flux verticaux de nutriments. Ainsi, une réduction des concentrations futures en nutriments et potentiellement de la production primaire dans le GSP est attendue sous changement climatique
The Subpolar Gyre (SPG) of the North Atlantic plays a key role in the carbon cycle and climate variability. It is the site of a vigorous spring phytoplankton bloom, maintained by the seasonal transport of nutrients in association with light. Macro-nutrients (NO3, PO4, DSi) are supplied predominantly to the mixed layer by lateral transport from high latitudes (mainly through the Davis and Hudson Straits), from lower latitudes by the North Atlantic Current, or by vertical transport from below the mixed layer where higher concentrations are present. These supply processes have been suggested to vary in response to the North Atlantic Oscillation, a major mode of natural climate variability. When the NAO index is negative, as it was the case from the mid-1990s to the end of the 2000s, physical conditions are similar to those projected under climate change (i.e. , warming and freshening, weakening of deep convection, slowing down of the Atlantic Meridional Overturning Circulation, increasing straatification. During the same period, a decline in macro-nutrient concentrations was observed throughout the region leading to the hypothesis that underlying processes could be similar to those acting under global warming to reduce mixed layer nutrient levels. The main objective of this thesis was to analyze and quantify the contributions of dynamic processes (i.e., lateral and vertical transport) to the observed variability in macro-nutrient mixed layer concentrations over the SPG between 1980 and 2015. The analysis used a coupled physical-biogeochemical model (NEMO-PISCES) discretized on a quarter-degree grid. An assessment of the model's representation of the spatial and temporal variability of macro-nutrient concentrations and the main physical processes, such as deep convection in the Labrador Sea, and the lateral transport of water and nutrients, was carried out in comparison with data from observations. An initial focus was on the Labrador Sea, which is a region characterized by deep, intense, and variable winter convection, making it an ideal laboratory for distinguishing the role of variability in deep winter convection from that of the Subpolar Gyre circulation and inputs from the Arctic Ocean. Despite some weakening, the contribution of changes of Arctic DSi transport through the Davis and Hudson Straits to observed nutrient variability was shown to be negligible (= 3%). Deep convection was identified as the main driver of the decline in pre-bloom DSi concentrations in the Labrador Sea. The study was extended next to the broader SPG, with assessment of the recent variability of macro-nutrient concentrations in the mixed layer through analysis of the variability of lateral and vertical transports between a period of strong positive NAO, a period of negative NAO, and the period following. In addition to the temporal variability of concentrations in response to atmospheric forcing, regional differences emerge, with a contribution dominated by vertical transport in the Labrador and Irminger Seas, led by variations in the depth of the mixed layer. Zonally-integrated nutrient transport east and north of the SPG are coherent with the variability of nutrient within the SPG but decoupled from nutrient transported by the Gulf stream via the North Atlantic Current west of 38°N. In this thesis, I highlighted the predominance of vertical mixing in the contemporary variability of nutrient concentrations compared with lateral inputs. I show that a slowing of the general circulation associated with stratification of the water column leading to the weakening of vertical nutrient fluxes, as is the case under projected climate change conditions, would lead to a reduction in macronutrient concentrations and potential future primary production in the SPG

En dépit de progrès croissants durant la dernière décennie, la complexité des écosystèmes marins est encore imparfaitement simulée par les modèles.Les formulations des processus biogéochimiques sont en général établies de manière empirique et contraintes par une multitude de paramètres.Il est ainsi généralement admis que leurs incertitudes impactent fortement l'estimation de la production primaire, dont le rôle dans le cycle du carbone est primordial.Analyser les impacts de l'incertitude des modèles est donc nécessaire pour améliorer la représentation des caractéristiques biogéochimiques de l'océan.Dans le contexte d'assimilation de données de la couleur de l'océan, la définition des erreurs de prévision représente de plus un important verrou aux performances des systèmes.Ces points seront analysés dans cette thèse. L'objectif sera d'examiner, dans un contexte de modélisation/assimilation, la pertinence d'utiliser une approche probabiliste basée sur une simulation explicite des incertitudes biogéochimiques du modèle couplé au 1/4° NEMO/PISCES sur l'océan Atlantique Nord.A partir d'une simulation déterministe du modèle PISCES, nous proposerons une méthode pour générer des processus aléatoires, AR(1), permettant d'inclure des structures spatiales et temporelles de corrélations.A chaque pas de temps, ces perturbations aléatoires seront ensuite introduites dans le modèle par l'intermédiaire de paramétrisations stochastiques.Elles simuleront 2 différentes classes d'incertitudes: les incertitudes sur les paramètres biogéochimiques du modèle et les incertitudes dues aux échelles non résolues dans le cas d'équations non linéaires. L'utilisation de paramétrisations stochastiques permettra ainsi d'élaborer une version probabiliste du modèle PISCES, à partir de laquelle nous pourrons réaliser une simulation d'ensemble de 60 membres.La pertinence de cette simulation d'ensemble sera évaluée par comparaison avec les observations de la couleur de l'océan SeaWIFS. Nous montrerons en particulier que la simulation d'ensemble conserve les structures de grande échelle présentes dans la simulation déterministe.En utilisant les distributions de probabilité définies par les membres de l'ensemble, nous montrerons que l'ensemble capture l'information des observations avec une bonne estimation de leurs statistiques d'erreur (fiabilité statistique). L'intérêt de l'approche probabiliste sera ainsi d'abord évalué dans un contexte de modélisation biogéochimique
In spite of recent advances, biogeochemical models are still unable to represent the full complexity of marine ecosystems.Since mathematical formulations are still based on empirical laws involving many parameters, it is now well established that the uncertainties inherent to the biogeochemical complexity strongly impact the model response.Improving model representation therefore requires to properly describe model uncertainties and their consequences.Moreover, in the context of ocean color data assimilation, one of the major issue rely on our ability to characterize the model uncertainty (or equivalently the model error) in order to maximize the efficiency of the assimilation system.This is exactly the purpose of this PhD which investigates the potential of using random processes to simulate some biogeochemical uncertaintiesof the 1/4° coupled physical–biogeochemical NEMO/PISCES model of the North Atlantic ocean.Starting from a deterministic simulation performed with the original PISCES formulation, we propose a genericmethod based on AR(1) random processes to generate perturbations with temporal and spatial correlations.These perturbations are introduced into the model formulations to simulate 2 classes of uncertainties: theuncertainties on biogeochemical parameters and the uncertainties induced by unresolved scales in the presenceof non-linear processes. Using these stochastic parameterizations, a probabilistic version of PISCES is designedand a 60-member ensemble simulation is performed.The implications of this probabilistic approach is assessed using the information of the probability distributions given of this ensemble simulationThe relevance and the impacts of the stochastic parameterizations are assessed from a comparison with SeaWIFS satellite data.In particular, it is shown that the ensemble simulation is able to produce a better estimate of the surface chlorophyll concentration than the first guess deterministic simulation.Using SeaWIFS ocean color data observations, the statistical consistency (reliability) of this prior ensemble is demonstrated using rank histograms.Finally, the relevance of our approach in the prospect of ocean color data assimilation is demonstrated by considering a 3D optimal analysis of the ensemble (one updateat one time step) performed from the statistic errors of the stochastic ensemble simulation previously stated.During this experiment, the high resolution SeaWIFS ocean color data are assimilated using a Ensemble Transform Kalman Filter (ETKF) analysis scheme and the non gaussian behaviour and non linear relationshipbetween variables are taken into account using anamorphic transformations.More specifically, we show that the analysis of SeaWIFS data improves the representation and the ensemble statistics of chlorophyll concentrations