Academic literature on the topic 'BGC-Argo profiling floats'

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.

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

Measurements of daytime radiometry in the ocean are necessary to constrain processes such as photosynthesis, photo-chemistry and radiative heating. Profiles of downwelling irradiance provide a means to compute the concentration of a variety of in-water constituents. However, radiometers record a non-negligible signal when no light is available, and this signal is temperature dependent (called the dark current). Here, we devise and evaluate two consistent methods for correction of BGC-Argo radiometry measurements for dark current: one based on measurements during the day, the other based on night measurements. A daytime data correction is needed because some floats never measure at night. The corrections are based on modeling the temperature of the radiometer and show an average bias in the measured value of nearly 0.01 W m−2 nm−1, 3 orders of magnitude larger than the reported uncertainty of 2.5×10−5 W m−2 nm−1 for the sensors deployed on BGC-Argo floats (SeaBird scientific OCR504 radiometers). The methods are designed to be simple and robust, requiring pressure, temperature and irradiance data. The correction based on nighttime profiles is recommended as the primary method as it captures dark measurements with the largest dynamic range of temperature. Surprisingly, more than 28% of daytime profiles (130,674 in total) were found to record significant downwelling irradiance at 240–250 dbar. The correction is shown to be small relative to near-surface radiance and thus most useful for studies investigating light fields in the twilight zone and the impacts of radiance on deep organisms. Based on these findings, we recommend that BGC-Argo floats profile occasionally at night and to depths greater than 250 dbar. We provide codes to perform the dark corrections.

Biogeochemical-Argo (BGC-Argo) is a network of profiling floats carrying sensors that enable observation of as many as six essential biogeochemical and bio-optical variables: oxygen, nitrate, pH, chlorophyll a, suspended particles, and downwelling irradiance. This sensor network represents today's most promising strategy for collecting temporally and vertically resolved observations of biogeochemical properties throughout the ocean. All data are freely available within 24 hours of transmission. These data fill large gaps in ocean-observing systems and support three ambitions: gaining a better understanding of biogeochemical processes (e.g., the biological carbon pump and air–sea CO2 exchanges) and evaluating ongoing changes resulting from increasing anthropogenic pressure (e.g., acidification and deoxygenation); managing the ocean (e.g., improving the global carbon budget and developing sustainable fisheries); and carrying out exploration for potential discoveries. The BGC-Argo network has already delivered extensive high-quality global data sets that have resulted in unique scientific outcomes from regional to global scales. With the proposed expansion of BGC-Argo in the near future, this network has the potential to become a pivotal observation system that links satellite and ship-based observations in a transformative manner.

Abstract The Global Ocean Biogeochemistry (GO-BGC) Array is a project funded by the US National Science Foundation to build a global network of chemical and biological sensors on Argo profiling floats. The network will monitor biogeochemical cycles and ocean health. The floats will collect from a depth of 2,000 meters to the surface, augmenting the existing <ext-link ext-link-type="uri" xlink:href="https://argo.ucsd.edu/">Argo array</ext-link> that monitors ocean temperature and salinity. Data will be made freely available within a day of being collected via the Argo data system. These data will allow scientists to pursue fundamental questions concerning ocean ecosystems, monitor ocean health and productivity, and observe the elemental cycles of carbon, oxygen, and nitrogen through all seasons of the year. Such essential data are needed to improve computer models of ocean fisheries and climate, to monitor and forecast the effects of ocean warming and ocean acidification on sea life, and to address key questions identified in “Sea Change: 2015‐2025 Decadal Survey of Ocean Sciences” such as: What is the ocean's role in regulating the carbon cycle? What are the natural and anthropogenic drivers of open ocean deoxygenation? What are the consequences of ocean acidification? How do physical changes in mixing and circulation affect nutrient availability and ocean productivity?

Abstract. As commonly observed in oligotrophic stratified waters, a subsurface (or deep) chlorophyll maximum (SCM) frequently characterizes the vertical distribution of phytoplankton chlorophyll in the Mediterranean Sea. Occurring far from the surface layer “seen” by ocean colour satellites, SCMs are difficult to observe with adequate spatio-temporal resolution and their biogeochemical impact remains unknown. Biogeochemical-Argo (BGC-Argo) profiling floats represent appropriate tools for studying the dynamics of SCMs. Based on data collected from 36 BGC-Argo floats deployed in the Mediterranean Sea, our study aims to address two main questions. (1) What are the different types of SCMs in the Mediterranean Sea? (2) Which environmental factors control their occurrence and dynamics? First, we analysed the seasonal and regional variations in the chlorophyll concentration (Chl a), particulate backscattering coefficient (bbp), a proxy of the particulate organic carbon (POC) and environmental parameters (photosynthetically active radiation and nitrates) within the SCM layer over the Mediterranean Basin. The vertical profiles of Chl a and bbp were then statistically classified and the seasonal occurrence of each of the different types of SCMs quantified. Finally, a case study was performed on two contrasted regions and the environmental conditions at depth were further investigated to understand the main controls on the SCMs. In the eastern basin, SCMs result, at a first order, from a photoacclimation process. Conversely, SCMs in the western basin reflect a biomass increase at depth benefiting from both light and nitrate resources. Our results also suggest that a variety of intermediate types of SCMs are encountered between these two endmember situations.

Abstract. This study assesses marine community production based on the diel variability of bio-optical properties monitored by two BioGeoChemical-Argo (BGC-Argo) floats. Experiments were conducted in two distinct Mediterranean systems, the northwestern Ligurian Sea and the central Ionian Sea, during summer months. We derived particulate organic carbon (POC) stock and gross community production integrated within the surface, euphotic and subsurface chlorophyll maximum (SCM) layers, using an existing approach applied to diel cycle measurements of the particulate beam attenuation (cp) and backscattering (bbp) coefficients. The diel cycle of cp provided a robust proxy for quantifying biological production in both systems; that of bbp was comparatively less robust. Derived primary production estimates vary by a factor of 2 depending upon the choice of the bio-optical relationship that converts the measured optical coefficient to POC, which is thus a critical step to constrain. Our results indicate a substantial contribution to the water column production of the SCM layer (16 %–42 %), which varies largely with the considered system. In the Ligurian Sea, the SCM is a seasonal feature that behaves as a subsurface biomass maximum (SBM) with the ability to respond to episodic abiotic forcing by increasing production. In contrast, in the Ionian Sea, the SCM is permanent, primarily induced by phytoplankton photoacclimation, and contributes moderately to water column production. These results clearly demonstrate the strong potential for transmissometers deployed on BGC-Argo profiling floats to quantify non-intrusively in situ biological production of organic carbon in the water column of stratified oligotrophic systems with recurring or permanent SCMs, which are widespread features in the global ocean.

Abstract. Typhoons are assumed to stimulate primary ocean production through the upward mixing of nutrients into the ocean surface. This assumption is based largely on observations of increased surface chlorophyll concentrations following the passage of typhoons. This surface chlorophyll enhancement, occasionally detected by satellites, is often undetected due to intense cloud coverage. Daily data from a BGC-Argo profiling float revealed the upper-ocean response to Typhoon Trami in the northwest Pacific Ocean. Temperature and chlorophyll changed rapidly, with a significant drop in sea surface temperature and a surge in surface chlorophyll associated with strong vertical mixing, which was only partially captured by satellite observations. However, no net increase in vertically integrated chlorophyll was observed during Typhoon Trami or in its wake. In contrast to the prevailing dogma, the result shows that typhoons likely have a limited effect on net primary ocean production. Observed surface chlorophyll enhancements during and immediately following typhoons in tropical and subtropical waters are more likely to be associated with surface entrainment of deep chlorophyll maxima. Moreover, the findings demonstrate that remote sensing data alone can overestimate the impact of storms on primary production in all oceans. Full understanding of the impact of storms on upper-ocean productivity can only be achieved with ocean-observing robots dedicated to high-resolution temporal sampling in the path of storms.

Biogeochemical- (BGC-) Argo aims to deploy and maintain a global array of autonomous profiling floats to monitor ocean biogeochemistry. With over 250,000 profiles collected so far, the BGC-Argo network is rapidly expanding toward the target of a sustained fleet of 1,000 floats. These floats prioritize the measurement of six key properties: oxygen, nitrate, pH, chlorophyll-a, suspended particles, and downwelling light. To assess the current biogeochemical state of the ocean, its variability, and trends with confidence, it is crucial to quality control these measurements. Accordingly, BGC-Argo maintains a quality control system using manual inspection and parameter-specific algorithms for flagging and adjusting data. In this study, we provide a census of the quantity and quality of measurements from BGC-Argo based on their quality flagging system. The purpose of this census is to assess the current status of the array in terms of data quality, how data quality has changed over time, and to provide a better understanding of the quality-controlled data to current and future users. Alongside increasing profile numbers and spatial coverage, we report that for most parameters between 80 and 95% of the profiles collected so far contain high-quality BGC data, with an exception for pH. The quality of pH profiles has seen a large improvement in the last five years and is on track to match the data quality of other BGC parameters. We highlight how BGC-Argo is improving and discuss strategies to increase the quality and quantity of BGC profiles available to users. This census shows that tracking percentages of high-quality data through time is useful for monitoring float sensor technology and helpful for ensuring the long-term success of BGC-Argo.

The NOAA Pacific Environmental Laboratory (PMEL) has contributed to the revolutionary Argo ocean observing system since its inception, developing CTD calibration algorithms and software that have been adopted by the international Argo community. PMEL has provided over 1,440 Argo floats—~13% of the global array—with ~500 currently active. PMEL scientific contributions using Argo data have ranged from regional to global analyses of ocean circulation and water-mass variability, to ocean warming and its contributions to sea level rise and Earth’s energy imbalance, to estimates of global ocean deoxygenation. In recent years, PMEL has initiated both Deep Argo (with a regional pilot array of full-ocean-depth profiling floats in the rapidly changing and dynamic western South Atlantic) and Biogeochemical (BGC) Argo (with a pilot array in the biogeochemically diverse and economically important California Current Large Marine Ecosystem). PMEL is also developing innovative near-global maps of ocean physical and biogeochemical parameters using machine learning algorithms that enable investigations of societally important oceanographic phenomena, and an Adopt-A-Float program. Future challenges include growing the financial, infrastructure, and human resources necessary to take the Deep and BGC Argo missions global and to fulfill the One Argo mission of a global, full-depth, multidisciplinary ocean observing array.

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-Argo
The 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

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 occidentale
The 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