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32 Research products, page 1 of 4

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  • Open Access English
    Authors: 
    Ortego, M. I.; Egozcue, J. J.; Tolosana-Delgado, R.;
    Project: EC | FIELD_AC (242284)

    It has been suggested that climate change might modify the occurrence rate and magnitude of large ocean-wave and wind storms. The hypothesised reason is the increase of available energy in the atmosphere–ocean system. Forecasting models are commonly used to assess these effects, given that good-quality data series are often too short. However, forecasting systems are often tuned to reproduce the average behaviour, and there are concerns on their relevance for extremal regimes. We present a methodology of simultaneous analysis of observed and hindcast data with the aim of extracting potential time drifts as well as systematic regime discrepancies between the two data sources. The method is based on the peak-over-threshold (POT) approach and the generalized Pareto distribution (GPD) within a Bayesian estimation framework. In this context, storm events are considered points in time, and modelled as a Poisson process. Storm magnitude over a reference threshold is modelled with a GPD, a flexible model that captures the tail behaviour of the magnitude distribution. All model parameters, i.e. shape and location of the magnitude GPD and the Poisson occurrence rate, are affected by a trend in time. Moreover, a systematic difference between parameters of hindcast and observed series is considered. Finally, the posterior joint distribution of all these trend parameters is studied using a conventional Gibbs sampler. This method is applied to compare hindcast and observed series of average wind speed at a deep buoy location off the Catalan coast (NE Spain, western Mediterranean; buoy data from 2001; REMO wind hindcasting from 1958 on). Appropriate scale and domain of attraction are discussed, and the reliability of trends in time is addressed.

  • Open Access English
    Authors: 
    Allen, John T.; Munoz, Cristian; Gardiner, Jim; Reeve, Krissy A.; Alou-Font, Eva; Zarokanellos, Nikolaos;
    Project: EC | JERICO-NEXT (654410)

    Glider vehicles are now perhaps some of the most prolific providers of real-time and near-real-time operational oceanographic data. However, the data from these vehicles can and should be considered to have a long-term legacy value capable of playing a critical role in understanding and separating inter-annual, inter-decadal, and longterm global change. To achieve this, we have to go further than simply assuming the manufacturer’s calibrations, and field correct glider data in a more traditional way, for example, by careful comparison to water bottle calibrated lowered CTD datasets and/or “gold” standard recent climatologies. In this manuscript, we bring into the 21st century a historical technique that has been used manually by oceanographers for many years/decades for field correction/inter-calibration, thermal lag correction, and adjustment for biological fouling. The technique has now been made semi-automatic for machine processing of oceanographic glider data, although its future and indeed its origins have far wider scope. The subject of this manuscript is drawn from the original Description of Work (DoW) for a key task in the recently completed JERICO-NEXT (Joint European Research Infrastructure network for Coastal Observatories) EU-funded program, but goes on to consider future application and the suitability for integration with machine learning. Refereed 14.A Sea surface salinity Subsurface salinity TRL 8 Actual system completed and "mission qualified" through test and demonstration in an operational environment (ground or space) Manual (incl. handbook, guide, cookbook etc) Standard Operating Procedure 2019-12-03

  • Open Access English
    Authors: 
    Hopwood, Mark J.; Sanchez, Nicolas; Polyviou, Despo; Leiknes, Øystein; Gallego-Urrea, Julián Alberto; Achterberg, Eric P.; Ardelan, Murat V.; Aristegui, Javier; Bach, Lennart; Besiktepe, Sengul; +6 more
    Project: EC | OCEAN-CERTAIN (603773)

    The extracellular concentration of H2O2 in surface aquatic environments is controlled by a balance between photochemical production and the microbial synthesis of catalase and peroxidase enzymes to remove H2O2 from solution. In any kind of incubation experiment, the formation rates and equilibrium concentrations of reactive oxygen species (ROSs) such as H2O2 may be sensitive to both the experiment design, particularly to the regulation of incident light, and the abundance of different microbial groups, as both cellular H2O2 production and catalase–peroxidase enzyme production rates differ between species. Whilst there are extensive measurements of photochemical H2O2 formation rates and the distribution of H2O2 in the marine environment, it is poorly constrained how different microbial groups affect extracellular H2O2 concentrations, how comparable extracellular H2O2 concentrations within large-scale incubation experiments are to those observed in the surface-mixed layer, and to what extent a mismatch with environmentally relevant concentrations of ROS in incubations could influence biological processes differently to what would be observed in nature. Here we show that both experiment design and bacterial abundance consistently exert control on extracellular H2O2 concentrations across a range of incubation experiments in diverse marine environments. During four large-scale (>1000 L) mesocosm experiments (in Gran Canaria, the Mediterranean, Patagonia and Svalbard) most experimental factors appeared to exert only minor, or no, direct effect on H2O2 concentrations. For example, in three of four experiments where pH was manipulated to 0.4–0.5 below ambient pH, no significant change was evident in extracellular H2O2 concentrations relative to controls. An influence was sometimes inferred from zooplankton density, but not consistently between different incubation experiments, and no change in H2O2 was evident in controlled experiments using different densities of the copepod Calanus finmarchicus grazing on the diatom Skeletonema costatum (<1 % change in [H2O2] comparing copepod densities from 1 to 10 L−1). Instead, the changes in H2O2 concentration contrasting high- and low-zooplankton incubations appeared to arise from the resulting changes in bacterial activity. The correlation between bacterial abundance and extracellular H2O2 was stronger in some incubations than others (R2 range 0.09 to 0.55), yet high bacterial densities were consistently associated with low H2O2. Nonetheless, the main control on H2O2 concentrations during incubation experiments relative to those in ambient, unenclosed waters was the regulation of incident light. In an open (lidless) mesocosm experiment in Gran Canaria, H2O2 was persistently elevated (2–6-fold) above ambient concentrations; whereas using closed high-density polyethylene mesocosms in Crete, Svalbard and Patagonia H2O2 within incubations was always reduced (median 10 %–90 %) relative to ambient waters.

  • Open Access English
    Authors: 
    Cardenete, G.; Abellán-Martínez, E. (Emilia); Hidalgo, M.C.; Morales, A.E.; Arizcun-Arizcun, M. (Marta); Suárez, M.D.; Estévez-Giménez, V.; García del Moral, L.;
    Publisher: Centro Oceanográfico de Murcia
    Country: Spain
  • Open Access English
    Authors: 
    Schuster, U.; McKinley, G. A.; Bates, N.; Chevallier, F.; Doney, S. C.; Fay, A. R.; González-Dávila, M.; Gruber, N.; Jones, S.; Krijnen, J.; +12 more
    Project: EC | GREENCYCLESII (238366), EC | COCOS (212196), EC | GEOCARBON (283080), EC | CARBOCHANGE (264879)

    The Atlantic and Arctic Oceans are critical components of the global carbon cycle. Here we quantify the net sea–air CO2 flux, for the first time, across different methodologies for consistent time and space scales for the Atlantic and Arctic basins. We present the long-term mean, seasonal cycle, interannual variability and trends in sea–air CO2 flux for the period 1990 to 2009, and assign an uncertainty to each. We use regional cuts from global observations and modeling products, specifically a pCO2-based CO2 flux climatology, flux estimates from the inversion of oceanic and atmospheric data, and results from six ocean biogeochemical models. Additionally, we use basin-wide flux estimates from surface ocean pCO2 observations based on two distinct methodologies. Our estimate of the contemporary sea–air flux of CO2 (sum of anthropogenic and natural components) by the Atlantic between 40° S and 79° N is −0.49 ± 0.05 Pg C yr−1, and by the Arctic it is −0.12 ± 0.06 Pg C yr−1, leading to a combined sea–air flux of −0.61 ± 0.06 Pg C yr−1 for the two decades (negative reflects ocean uptake). We do find broad agreement amongst methodologies with respect to the seasonal cycle in the subtropics of both hemispheres, but not elsewhere. Agreement with respect to detailed signals of interannual variability is poor, and correlations to the North Atlantic Oscillation are weaker in the North Atlantic and Arctic than in the equatorial region and southern subtropics. Linear trends for 1995 to 2009 indicate increased uptake and generally correspond between methodologies in the North Atlantic, but there is disagreement amongst methodologies in the equatorial region and southern subtropics.

  • Open Access English
    Authors: 
    Almansa, E. (Eduardo); Martín, M.V. (María Virginia); Iglesias-Estévez, J. (José); Cardenete, G.; Rocha, F.; Perales-Raya, C. (Catalina); Otero-Pinzas, J.J. (Juan José); Morales, A.E.; Rodriguez, E.; Nande, M. (Manuel); +6 more
    Publisher: Centro Oceanográfico de Canarias
    Country: Spain
  • Open Access English
    Authors: 
    Martín, M.V. (María Virginia);
    Publisher: Centro Oceanográfico de Canarias
    Country: Spain
  • Open Access English
    Authors: 
    Bode, A. (Antonio); Olivar, M. Pilar; López-Pérez, Cristina; Hernández-León, Santiago;
    Publisher: PANGAEA - Data Publisher for Earth & Environmental Science
    Country: Spain
    Project: EC | TRIATLAS (817578)

    The values of natural abundance of stable isotopes were measured in 13 micronekton fish species sampled during the MAFIA cruise (North Atlantic, April 2015). This dataset contains the values obtained for carbon and nitrogen in bulk tissues, and nitrogen values in amino acids. Length data and the number of individuals analysed for each species are also provided. Mesopelagic fishes were collected using a ''Mesopelagos” net (5x7 m mouth opening, 58 m total lenght) equipped with graded-mesh netting (starting with 30 mm and ending with 4 mm) and a multi-sampler for collecting samples from 5 different depth layers (Olivar et al., 2017). For C:N and stable isotope analyses, individual fish were eviscerated, freeze-dried and weighted. Aliquots of muscular tissue (or whole individuals for species of small size) were analyzed in an elemental analyzer (bulk tissues, Olivar et al., 2019) or a gas chromatograph (derivatized amino acids, Mompeán et al., 2016) coupled to isotope-ratio mass spectrometers. This research was funded by projects MAFIA (CTM2012-39587-C04), BATHYPELAGIC (CTM2016-78853-R), and QLOCKS (PID2020-115620RB-100) from the Plan Estatal de I+D+I (Spain), projects SUMMER (Grant Agreement 817806) and TRIATLAS (Grant Agreement 817578), from the European Union (Horizon 2020 Research and Innovation Programme), and the support through the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S).

  • Open Access English
    Authors: 
    Díaz-Conde, M.P. (María Paz); Tornero, J. (Jorge); González-Cabrera, C. (Carmen); Ramos, F. (Fernando); Sánchez-Leal, R.F. (Ricardo Félix); Jiménez, M.P. (María Paz);
    Publisher: Centro Oceanográfico de Cádiz
    Country: Spain

    The Daily Egg Production Method (DEPM) to estimate the Anchovy Spawning Stock Biomass (SSB) in the Gulf of Cádiz (ICES, Subdivision 9a South) is conducted by Spain (Centro Nacional Instituto Español de Oceanografía, CSIC) every three years, since 2005. BOCADEVA 0720 is the sixth survey of the historical DEPM series for anchovy in the Gulf of Cádiz and was delivered on board R/V Ramón Margalef (CNIEO) from the 9th to the 17th of July 2020. The surveyed area extended from Strait of Gibraltar to Cape San Vicente (Spanish and Portuguese waters in the Gulf of Cadiz). Plankton samples, along a grid of 21 transects perpendicular to the coast were obtained for the spawning area delimitation and density estimation of the daily egg production. The survey objectives also included the characterization of the oceanographic and meteorological conditions in the study area. The samples to estimate adult parameters (sex ratio, female mean weight, batch fecundity and spawning fraction) were obtained in the acoustic survey “ECOCADIZ 2020-07”, carried out during the same period. This working document provides a d escription of the survey, laboratory analysis and estimation procedures used to obtain the Gulf of Cadiz Anchovy SSB by DEPM for 2020 in the South-Atlantic Iberian Stock.

  • Other research product . 2018
    Open Access English
    Authors: 
    Rincón Arango, Jaime Andrés;
    Country: Spain

    A lo largo de los últimos años, los sistemas multi-agente (SMA) han demostrado ser un paradigma potente y versátil, con un gran potencial a la hora de resolver problemas complejos en entornos dinámicos y distribuidos. Este potencial no se debe principalmente a sus características individuales (como son su autonomía, su capacidad de percepción, reacción y de razonamiento), sino que también a la capacidad de comunicación y cooperación a la hora de conseguir un objetivo. De hecho, su capacidad social es la que más llama la atención, es este comportamiento social el que dota de potencial a los sistemas multi-agente. Estas características han hecho de los SMA, la herramienta de inteligencia artificial (IA) más utilizada para el diseño de entornos virtuales inteligentes (IVE), los cuales son herramientas de simulación compleja basadas en agentes. Sin embargo, los IVE incorporan restricciones físicas (como gravedad, fuerzas, rozamientos, etc.), así como una representación 3D de lo que se quiere simular. Así mismo, estas herramientas no son sólo utilizadas para la realización de simulaciones. Con la aparición de nuevas aplicaciones como \emph{Internet of Things (IoT)}, \emph{Ambient Intelligence (AmI)}, robot asistentes, entre otras, las cuales están en contacto directo con el ser humano. Este contacto plantea nuevos retos a la hora de interactuar con estas aplicaciones. Una nueva forma de interacción que ha despertado un especial interés, es el que se relaciona con la detección y/o simulación de estados emocionales. Esto ha permitido que estas aplicaciones no sólo puedan detectar nuestros estados emocionales, sino que puedan simular y expresar sus propias emociones mejorando así la experiencia del usuario con dichas aplicaciones. Con el fin de mejorar la experiencia humano-máquina, esta tesis plantea como objetivo principal la creación de modelos emocionales sociales, los cuales podrán ser utilizados en aplicaciones MAS permitiendo a los agentes interpretar y/o emular diferentes estados emocionales y, además, emular fenómenos de contagio emocional. Estos modelos permitirán realizar simulaciones complejas basadas en emociones y aplicaciones más realistas en dominios como IoT, AIm, SH. Al llarg dels últims anys, els sistemes multi-agent (SMA) han demostrat ser un paradigma potent i versàtil, amb un gran potencial a l'hora de resoldre problemes complexos en entorns dinàmics i distribuïts. Aquest potencial no es deu principalment a les seues característiques individuals (com són la seua autonomia, la seua capacitat de percepció, reacció i de raonament), sinó que també a la capacitat de comunicació i cooperació a l'hora d'aconseguir un objectiu. De fet, la seua capacitat social és la que més crida l'atenció, és aquest comportament social el que dota de potencial als sistemes multi-agent. Aquestes característiques han fet dels SMA, l'eina d'intel·ligència artificial (IA) més utilitzada per al disseny d'entorns virtuals intel·ligents (IVE), els quals són eines de simulació complexa basades en agents. No obstant això, els IVE incorporen restriccions físiques (com gravetat, forces, fregaments, etc.), així com una representació 3D del que es vol simular. Així mateix, aquestes eines no són només utilitzades per a la realització de simulacions. Amb l'aparició de noves aplicacions com \emph{Internet of Things (IOT)}, \emph{Ambient Intelligence (AmI)}, robot assistents, entre altres, les quals estan en contacte directe amb l'ésser humà. Aquest contacte planteja nous reptes a l'hora d'interactuar amb aquestes aplicacions. Una nova forma d'interacció que ha despertat un especial interès, és el que es relaciona amb la detecció i/o simulació d'estats emocionals. Això ha permès que aquestes aplicacions no només puguen detectar els nostres estats emocionals, sinó que puguen simular i expressar les seues pròpies emocions millorant així l'experiència de l'usuari amb aquestes aplicacions. Per tal de millorar l'experiència humà-màquina, aquesta tesi planteja com a objectiu principal la creació de models emocionals socials, els quals podran ser utilitzats en aplicacions MAS permetent als agents interpretar i/o emular diferents estats emocionals i, a més, emular fenòmens de contagi emocional. Aquests models permetran realitzar simulacions complexes basades en emocions i aplicacions més realistes en dominis com IoT, AIM, SH. Over the past few years, multi-agent systems (SMA) have proven to be a powerful and versatile paradigm, with great potential for solving complex problems in dynamic and distributed environments. This potential is not primarily due to their individual characteristics (such as their autonomy, their capacity for perception, reaction and reasoning), but also the ability to communicate and cooperate in achieving a goal. In fact, its social capacity is the one that draws the most attention, it is this social behavior that gives potential to multi-agent systems. These characteristics have made the SMA, the artificial intelligence (AI) tool most used for the design of intelligent virtual environments (IVE), which are complex agent-based simulation tools. However, IVE incorporates physical constraints (such as gravity, forces, friction, etc.), as well as a 3D representation of what you want to simulate. Also, these tools are not only used for simulations. With the emergence of new applications such as \emph {Internet of Things (IoT)}, \emph {Ambient Intelligence (AmI)}, robot assistants, among others, which are in direct contact with humans. This contact poses new challenges when it comes to interacting with these applications. A new form of interaction that has aroused a special interest is that which is related to the detection and / or simulation of emotional states. This has allowed these applications not only to detect our emotional states, but also to simulate and express their own emotions, thus improving the user experience with those applications. In order to improve the human-machine experience, this thesis aims to create social emotional models, which can be used in MAS applications, allowing agents to interpret and / or emulate different emotional states, and emulate phenomena of emotional contagion. These models will allow complex simulations based on emotions and more realistic applications in domains like IoT, AIm, SH. Rincón Arango, JA. (2018). Social Emotions in Multiagent Systems. http://hdl.handle.net/10251/98090 TESIS