986 resultados para Ocean modeling
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This report was developed to help establish National Ocean Service priorities and chart new directions for research and development of models for estuarine, coastal and ocean ecosystems based on user-driven requirements and supportive of sound coastal management, stewardship, and an ecosystem approach to management. (PDF contains 63 pages)
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Path planning and trajectory design for autonomous underwater vehicles (AUVs) is of great importance to the oceanographic research community because automated data collection is becoming more prevalent. Intelligent planning is required to maneuver a vehicle to high-valued locations to perform data collection. In this paper, we present algorithms that determine paths for AUVs to track evolving features of interest in the ocean by considering the output of predictive ocean models. While traversing the computed path, the vehicle provides near-real-time, in situ measurements back to the model, with the intent to increase the skill of future predictions in the local region. The results presented here extend prelim- inary developments of the path planning portion of an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. This extension is the incorporation of multiple vehicles to track the centroid and the boundary of the extent of a feature of interest. Similar algorithms to those presented here are under development to consider additional locations for multiple types of features. The primary focus here is on algorithm development utilizing model predictions to assist in solving the motion planning problem of steering an AUV to high-valued locations, with respect to the data desired. We discuss the design technique to generate the paths, present simulation results and provide experimental data from field deployments for tracking dynamic features by use of an AUV in the Southern California coastal ocean.
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Autonomous underwater gliders are robust and widely-used ocean sampling platforms that are characterized by their endurance, and are one of the best approaches to gather subsurface data at the appropriate spatial resolution to advance our knowledge of the ocean environment. Gliders generally do not employ sophisticated sensors for underwater localization, but instead dead-reckon between set waypoints. Thus, these vehicles are subject to large positional errors between prescribed and actual surfacing locations. Here, we investigate the implementation of a large-scale, regional ocean model into the trajectory design for autonomous gliders to improve their navigational accuracy. We compute the dead-reckoning error for our Slocum gliders, and compare this to the average positional error recorded from multiple deployments conducted over the past year. We then compare trajectory plans computed on-board the vehicle during recent deployments to our prediction-based trajectory plans for 140 surfacing occurrences.
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In recent years, ocean scientists have started to employ many new forms of technology as integral pieces in oceanographic data collection for the study and prediction of complex and dynamic ocean phenomena. One area of technological advancement in ocean sampling if the use of Autonomous Underwater Vehicles (AUVs) as mobile sensor plat- forms. Currently, most AUV deployments execute a lawnmower- type pattern or repeated transects for surveys and sampling missions. An advantage of these missions is that the regularity of the trajectory design generally makes it easier to extract the exact path of the vehicle via post-processing. However, if the deployment region for the pattern is poorly selected, the AUV can entirely miss collecting data during an event of specific interest. Here, we consider an innovative technology toolchain to assist in determining the deployment location and executed paths for AUVs to maximize scientific information gain about dynamically evolving ocean phenomena. In particular, we provide an assessment of computed paths based on ocean model predictions designed to put AUVs in the right place at the right time to gather data related to the understanding of algal and phytoplankton blooms.
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Data collection using Autonomous Underwater Vehicles (AUVs) is increasing in importance within the oceano- graphic research community. Contrary to traditional moored or static platforms, mobile sensors require intelligent planning strategies to manoeuvre through the ocean. However, the ability to navigate to high-value locations and collect data with specific scientific merit is worth the planning efforts. In this study, we examine the use of ocean model predictions to determine the locations to be visited by an AUV, and aid in planning the trajectory that the vehicle executes during the sampling mission. The objectives are: a) to provide near-real time, in situ measurements to a large-scale ocean model to increase the skill of future predictions, and b) to utilize ocean model predictions as a component in an end-to-end autonomous prediction and tasking system for aquatic, mobile sensor networks. We present an algorithm designed to generate paths for AUVs to track a dynamically evolving ocean feature utilizing ocean model predictions. This builds on previous work in this area by incorporating the predicted current velocities into the path planning to assist in solving the 3-D motion planning problem of steering an AUV between two selected locations. We present simulation results for tracking a fresh water plume by use of our algorithm. Additionally, we present experimental results from field trials that test the skill of the model used as well as the incorporation of the model predictions into an AUV trajectory planner. These results indicate a modest, but measurable, improvement in surfacing error when the model predictions are incorporated into the planner.
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Trajectory design for Autonomous Underwater Vehicles (AUVs) is of great importance to the oceanographic research community. Intelligent planning is required to maneuver a vehicle to high-valued locations for data collection. We consider the use of ocean model predictions to determine the locations to be visited by an AUV, which then provides near-real time, in situ measurements back to the model to increase the skill of future predictions. The motion planning problem of steering the vehicle between the computed waypoints is not considered here. Our focus is on the algorithm to determine relevant points of interest for a chosen oceanographic feature. This represents a first approach to an end to end autonomous prediction and tasking system for aquatic, mobile sensor networks. We design a sampling plan and present experimental results with AUV retasking in the Southern California Bight (SCB) off the coast of Los Angeles.
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In this paper, we examine the use of a Kalman filter to aid in the mission planning process for autonomous gliders. Given a set of waypoints defining the planned mission and a prediction of the ocean currents from a regional ocean model, we present an approach to determine the best, constant, time interval at which the glider should surface to maintain a prescribed tracking error, and minimizing time on the ocean surface. We assume basic parameters for the execution of a given mission, and provide the results of the Kalman filter mission planning approach. These results are compared with previous executions of the given mission scenario.
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Recent efforts in mission planning for underwater vehicles have utilised predictive models to aid in navigation, optimal path planning and drive opportunistic sampling. Although these models provide information at a unprecedented resolutions and have proven to increase accuracy and effectiveness in multiple campaigns, most are deterministic in nature. Thus, predictions cannot be incorporated into probabilistic planning frameworks, nor do they provide any metric on the variance or confidence of the output variables. In this paper, we provide an initial investigation into determining the confidence of ocean model predictions based on the results of multiple field deployments of two autonomous underwater vehicles. For multiple missions conducted over a two-month period in 2011, we compare actual vehicle executions to simulations of the same missions through the Regional Ocean Modeling System in an ocean region off the coast of southern California. This comparison provides a qualitative analysis of the current velocity predictions for areas within the selected deployment region. Ultimately, we present a spatial heat-map of the correlation between the ocean model predictions and the actual mission executions. Knowing where the model provides unreliable predictions can be incorporated into planners to increase the utility and application of the deterministic estimations.
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The purpose of this work is to carry out a comprehensive study on the Western Iberian Margin (WIM) circulation my means of numerical modeling, and to postulate what this circulation will be in the future. The adopted approach was the development of a regional ocean model configuration with high resolution, capable of reproducing the largeand small-scale dynamics of the coastal transition zone. Four numerical experiences were carried out according to these objectives: (1) a climatological run, in order to study the system’s seasonal behavior and its mean state; (2) a run forced with real winds and fluxes for period 2001-2011 in order to study the interannual variability of the system; (3) a run forced with mean fields from Global Climate Models (GCMs) for the present, in order to validate GCMs as adequate forcing for regional ocean modeling; (4) a similar run (3) for period 2071-2100, in order to assess possible consequences of a future climate scenario on the hydrography and dynamics of the WIM. Furthermore, two Lagrangian particle studies were carried out: one in order to trace the origin of the upwelled waters along the WIM; the other in order to portrait the patterns of larval dispersal, accumulation and connectivity. The numerical configuration proved to be adequate in the reproduction of the system’s mean state, seasonal characterization and an interannual variability study. There is prevalence of poleward flow at the slope, which coexists with the upwelling jet during summer, although there is evidence of its shifting offshore, and which is associated with the Mediterranean Water flow at deeper levels, suggesting a barotropic character. From the future climate scenario essay, the following conclusions were drawn: there is general warming and freshening of upper level waters; there is still poleward tendency, and despite the upwellingfavorable winds strengthening in summer the respective coastal band becomes more restricted in width and depth. In what concerns larval connectivity and dispersion along the WIM, diel vertical migration was observed to increase recruitment throughout the domain, and while smooth coastlines are better suppliers, there is higher accumulation where the topography is rougher.
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The aim of this study is to clarify the role of the Southern Ocean storms on interior mixing and meridional overturning circulation. A periodic and idealized numerical model has been designed to represent the key physical processes of a zonal portion of the Southern Ocean located between 70 and 40° S. It incorporates physical ingredients deemed essential for Southern Ocean functioning: rough topography, seasonally varying air–sea fluxes, and high-latitude storms with analytical form. The forcing strategy ensures that the time mean wind stress is the same between the different simulations, so the effect of the storms on the mean wind stress and resulting impacts on the Southern Ocean dynamics are not considered in this study. Level and distribution of mixing attributable to high-frequency winds are quantified and compared to those generated by eddy–topography interactions and dissipation of the balanced flow. Results suggest that (1) the synoptic atmospheric variability alone can generate the levels of mid-depth dissipation frequently observed in the Southern Ocean (10−10–10−9 W kg−1) and (2) the storms strengthen the overturning, primarily through enhanced mixing in the upper 300 m, whereas deeper mixing has a minor effect. The sensitivity of the results to horizontal resolution (20, 5, 2 and 1 km), vertical resolution and numerical choices is evaluated. Challenging issues concerning how numerical models are able to represent interior mixing forced by high-frequency winds are exposed and discussed, particularly in the context of the overturning circulation. Overall, submesoscale-permitting ocean modeling exhibits important delicacies owing to a lack of convergence of key components of its energetics even when reaching Δx = 1 km.
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In this paper, we explore a novel idea of using high dynamic range (HDR) technology for uncertainty visualization. We focus on scalar volumetric data sets where every data point is associated with scalar uncertainty. We design a transfer function that maps each data point to a color in HDR space. The luminance component of the color is exploited to capture uncertainty. We modify existing tone mapping techniques and suitably integrate them with volume ray casting to obtain a low dynamic range (LDR) image. The resulting image is displayed on a conventional 8-bits-per-channel display device. The usage of HDR mapping reveals fine details in uncertainty distribution and enables the users to interactively study the data in the context of corresponding uncertainty information. We demonstrate the utility of our method and evaluate the results using data sets from ocean modeling.
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Based on the Estuarine, Coastal and Ocean Modeling System with Sediments (ECOMSED) model, a 3-D hydrodynamic-transport numerical model was established for the offshore area near the Yangtze Estuary in the East China Sea. The hydrodynamic module was driven by tide and wind. Sediment module included sediment resuspension, transport and deposition of cohesive and non-cohesive sediment. The settling of cohesive sediment in the water column was modeled as a function of aggregation (flocculation) and deposition. The numerical results were compared with observation data for August, 2006. It shows that the sediment concentration reduces gradually from the seashore to the offshore area. Numerical results of concentration time series in the observation stations show two peaks and two valleys, according with the observation data. It is mainly affected by tidal current. The suspended sediment concentration is related to the tidal current during a tidal cycle, and the maximum concentration appears 1 h-4 h after the current maximum velocity has reached.
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Este trabalho combina esforços de simulação numérica e de análise de dados para investigar a dinâmica em diversos compartimentos (oceano aberto, plataforma continental e zona costeira-estuarina) e, em multiplas escalas, na Margem Continental Leste Brasileira (MCLB). A circulação de largo e mesoescala espacial e a propagação da maré barotrópica são investigadas através de uma configuração aninhada do modelo numérico ROMS. O estudo da dinâmica regional da Baía de Camamu (CMB) baseia-se na análise de dados locais. A MCLB, localizada a SW do Atlântico Sul entre 8±S e 20±S, possui plataforma estreita, batimetria complexa, e baixa produtividade primária. A sua dinâmica é influenciada pela divergência da Corrente Sul Equatorial (CSE). As simulações refletem as conexões sazonais e espaciais entre a Corrente do Brasil e a Contra Corrente Norte do Brasil , em conexão com a dinâmica da CSE. As simulações revelam atividades vorticais nas proximidades da costa e interações com a dinâmica costeira, cujos padrões são descritos. A validação do modelo em mesoescala é baseada em cálculos de energia cinética turbulenta e em dados históricos de transporte. A CMB, localizada a 13±400S, abriga uma comunidade piscatória tradicional e extenso de manguezal. Situa-se porém sobre uma bacia sedimentar com grande reservas de óleo e gás, estando em tensão permanente de impacto ambiental. Neste trabalho sumarizamos as condições físicas regionais e investigamos sua dinâmica interna, focando sua variabilidade em amostragens realizadas sob condições de seca (Setembro de 2004) e de chuva (Julho de 2005). Finalmente, o modelo numérico ROMS é forçado com o sinal de maré, empregando-se uma configuração simples (com coeficientes de atrito de fundo constantes e condições hidrográficas homogéneas), com o intuito de avaliar sua resposta e investigar a natureza da propagação da maré barotrópica na MCLB, convergindo na CMB. A análise da resposta do modelo à maré basea-se em séries históricas do nível do mar para a MCLB e dados recentes da CMB.