24 resultados para global ocean economy


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Satellite ocean-colour sensors have life spans lasting typically five-to-ten years. Detection of long-term trends in chlorophyll-a concentration (Chl-a) using satellite ocean colour thus requires the combination of different ocean-colour missions with sufficient overlap to allow for cross-calibration. A further requirement is that the different sensors perform at a sufficient standard to capture seasonal and inter-annual fluctuations in ocean colour. For over eight years, the SeaWiFS, MODIS-Aqua and MERIS ocean-colour sensors operated in parallel. In this paper, we evaluate the temporal consistency in the monthly Chl-a time-series and in monthly inter-annual variations in Chl-a among these three sensors over the 2002–2010 time period. By subsampling the monthly Chl-a data from the three sensors consistently, we found that the Chl-a time-series and Chl-a anomalies among sensors were significantly correlated for >90% of the global ocean. These correlations were also relatively insensitive to the choice of three Chl-a algorithms and two atmospheric-correction algorithms. Furthermore, on the subsampled time-series, correlations between Chl-a and time, and correlations between Chl-a and physical variables (sea-surface temperature and sea-surface height) were not significantly different for >92% of the global ocean. The correlations in Chl-a and physical variables observed for all three sensors also reflect previous theories on coupling between physical processes and phytoplankton biomass. The results support the combining of Chl-a data from SeaWiFS, MODIS-Aqua and MERIS sensors, for use in long-term Chl-a trend analysis, and highlight the importance of accounting for differences in spatial sampling among sensors when combining ocean-colour observations.

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The Arctic Ocean is, on average, the shallowest of Earth’s oceans. Its vast continental shelf areas, which account for approximately half of the Arctic Ocean’s total area, are heavily influenced by the surrounding land masses through river run-off and coastal erosion. As a main area of deep water formation, the Arctic is one of the main «engines» of global ocean circulation, due to large freshwater inputs, it is also strongly stratified. The Arctic Ocean’s complex oceanographic configuration is tightly linked to the atmosphere, the land, and the cryosphere. The physical dynamics not only drive important climate and global circulation patterns, but also control biogeochemical cycles and ecosystem dynamics. Current changes in Arctic sea-ice thickness and distribution, air and water temperatures, and water column stability are resulting in measurable shifts in the properties and functioning of the ocean and its ecosystems. The Arctic Ocean is forecast to shift to a seasonally ice-free ocean resulting in changes to physical, chemical, and biological processes. These include the exchange of gases across the atmosphere-ocean interface, the wind-driven ciruclation and mixing regimes, light and nutrient availability for primary production, food web dynamics, and export of material to the deep ocean. In anticipation of these changes, extending our knowledge of the present Arctic oceanography and these complex changes has never been more urgent.

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Current global inventories of ammonia emissions identify the ocean as the largest natural source. This source depends on seawater pH, temperature, and the concentration of total seawater ammonia (NHx(sw)), which reflects a balance between remineralization of organic matter, uptake by plankton, and nitrification. Here we compare [NHx(sw)] from two global ocean biogeochemical models (BEC and COBALT) against extensive ocean observations. Simulated [NHx(sw)] are generally biased high. Improved simulation can be achieved in COBALT by increasing the plankton affinity for NHx within observed ranges. The resulting global ocean emissions is 2.5 TgN a−1, much lower than current literature values (7–23 TgN a−1), including the widely used Global Emissions InitiAtive (GEIA) inventory (8 TgN a−1). Such a weak ocean source implies that continental sources contribute more than half of atmospheric NHx over most of the ocean in the Northern Hemisphere. Ammonia emitted from oceanic sources is insufficient to neutralize sulfate aerosol acidity, consistent with observations. There is evidence over the Equatorial Pacific for a missing source of atmospheric ammonia that could be due to photolysis of marine organic nitrogen at the ocean surface or in the atmosphere. Accommodating this possible missing source yields a global ocean emission of ammonia in the range 2–5 TgN a−1, comparable in magnitude to other natural sources from open fires and soils.

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Mercury (Hg) natural biogeochemical cycle is complex and a significant portion of biological and chemical transformation occurs in the marine environment. To better understand the presence and abundance of Hg species in the remote ocean regions, waters of South Atlantic Ocean along 40°S parallel were investigated during UK-GEOTRACES cruise GA10. Total mercury (THg), methylated mercury (MeHg), and dissolved gaseous mercury (DGM) concentrations were determined. The concentrations were very low in the range of pg/L (femtomolar). All Hg species had higher concentration in western than in eastern basin. THg did not appear to be a useful geotracer. Elevated methylated Hg species were commonly associated with low-oxygen water masses and occasionally with peaks of chlorophyll a, both involved with carbon (re)cycling. The overall highest MeHg concentrations were observed in themixed layer (500m) and in the vicinity of the Gough Island. Conversely, DGM concentrations showed distinct layering and differed between the water masses in a nutrient-like manner. DGM was lowest at surface, indicating degassing to the atmosphere, and was highest in the Upper Circumpolar Deep Water, where the oxygen concentration was lowest. DGM increased also in Antarctic Bottom Water. At one station, dimethylmercury was determined and showed increase in region with lowest oxygen saturation. Altogether, our data indicate that the South Atlantic Ocean could be a source of Hg to the atmosphere and that its biogeochemical transformations depend primarily upon carbon cycling and are thereby additionally prone to global ocean change.

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Satellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field.

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Human health and well-being are tied to the vitality of the global ocean and coastal systems on which so many live and rely. We engage with these extraordinary environments to enhance both our health and our well-being. But, we need to recognize that introducing contaminants and otherwise altering these ocean systems can harm human health and well-being in significant and substantial ways. These are complex, challenging, and critically important themes. How the human relationship to the oceans evolves in coming decades may be one of the most important connections in understanding our personal and social well-being. Yet, our understanding of this relationship is far too limited. This remarkable volume brings experts from diverse disciplines and builds a workable understanding of breadth and depth of the processes – both social and environmental – that will help us to limit future costs and enhance the benefits of sustainable marine systems. In particular, the authors have developed a shared view that the global coastal environment is under threat through intensified natural resource utilization, as well as changes to global climate and other environmental systems. All these changes contribute individually, but more importantly cumulatively, to higher risks for public health and to the global burden of disease. This pioneering book will be of value to advanced undergraduate and postgraduate students taking courses in public health, environmental, economic, and policy fields. Additionally, the treatment of these complex systems is of essential value to the policy community responsible for these questions and to the broader audience for whom these issues are more directly connected to their own health and well-being.

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Field campaigns are instrumental in providing ground truth for understanding and modeling global ocean biogeochemical budgets. A survey however can only inspect a fraction of the global oceans, typically a region hundreds of kilometers wide for a temporal window of the order of (at most) several weeks. This spatiotemporal domain is also the one in which the mesoscale activity induces through horizontal stirring a strong variability in the biogeochemical tracers, with ephemeral, local contrasts which can easily mask the regional and seasonal gradients. Therefore, whenever local in situ measures are used to infer larger-scale budgets, one faces the challenge of identifying the mesoscale structuring effect, if not simply to filter it out. In the case of the KEOPS2 investigation of biogeochemical responses to natural iron fertilization, this problem was tackled by designing an adaptive sampling strategy based on regionally optimized multisatellite products analyzed in real time by specifically designed Lagrangian diagnostics. This strategy identified the different mesoscale and stirring structures present in the region and tracked the dynamical frontiers among them. It also enabled back trajectories for the ship-sampled stations to be estimated, providing important insights into the timing and pathways of iron supply, which were explored further using a model based on first-order iron removal. This context was essential for the interpretation of the field results. The mesoscale circulation-based strategy was also validated post-cruise by comparing the Lagrangian maps derived from satellites with the patterns of more than one hundred drifters, including some adaptively released during KEOPS2 and a subsequent research voyage. The KEOPS2 strategy was adapted to the specific biogeochemical characteristics of the region, but its principles are general and will be useful for future in situ biogeochemical surveys.

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The ERSEM model is one of the most established ecosystem models for the lower trophic levels of the marine food-web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North-Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic part of the marine ecosystem, including the microbial food-web, the carbonate system and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case-studies of mesocosm type simulations, water column implementations and a brief example of a full-scale application for the North-West European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.

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The European Regional Seas Ecosystem Model (ERSEM) is one of the most established ecosystem models for the lower trophic levels of the marine food web in the scientific literature. Since its original development in the early nineties it has evolved significantly from a coastal ecosystem model for the North Sea to a generic tool for ecosystem simulations from shelf seas to the global ocean. The current model release contains all essential elements for the pelagic and benthic parts of the marine ecosystem, including the microbial food web, the carbonate system, and calcification. Its distribution is accompanied by a testing framework enabling the analysis of individual parts of the model. Here we provide a detailed mathematical description of all ERSEM components along with case studies of mesocosm-type simulations, water column implementations, and a brief example of a full-scale application for the north-western European shelf. Validation against in situ data demonstrates the capability of the model to represent the marine ecosystem in contrasting environments.