990 resultados para Princeton Ocean Model


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A potential problem with Ensemble Kalman Filter is the implicit Gaussian assumption at analysis times. Here we explore the performance of a recently proposed fully nonlinear particle filter on a high-dimensional but simplified ocean model, in which the Gaussian assumption is not made. The model simulates the evolution of the vorticity field in time, described by the barotropic vorticity equation, in a highly nonlinear flow regime. While common knowledge is that particle filters are inefficient and need large numbers of model runs to avoid degeneracy, the newly developed particle filter needs only of the order of 10-100 particles on large scale problems. The crucial new ingredient is that the proposal density cannot only be used to ensure all particles end up in high-probability regions of state space as defined by the observations, but also to ensure that most of the particles have similar weights. Using identical twin experiments we found that the ensemble mean follows the truth reliably, and the difference from the truth is captured by the ensemble spread. A rank histogram is used to show that the truth run is indistinguishable from any of the particles, showing statistical consistency of the method.

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Considerable effort is presently being devoted to producing high-resolution sea surface temperature (SST) analyses with a goal of spatial grid resolutions as low as 1 km. Because grid resolution is not the same as feature resolution, a method is needed to objectively determine the resolution capability and accuracy of SST analysis products. Ocean model SST fields are used in this study as simulated “true” SST data and subsampled based on actual infrared and microwave satellite data coverage. The subsampled data are used to simulate sampling errors due to missing data. Two different SST analyses are considered and run using both the full and the subsampled model SST fields, with and without additional noise. The results are compared as a function of spatial scales of variability using wavenumber auto- and cross-spectral analysis. The spectral variance at high wavenumbers (smallest wavelengths) is shown to be attenuated relative to the true SST because of smoothing that is inherent to both analysis procedures. Comparisons of the two analyses (both having grid sizes of roughly ) show important differences. One analysis tends to reproduce small-scale features more accurately when the high-resolution data coverage is good but produces more spurious small-scale noise when the high-resolution data coverage is poor. Analysis procedures can thus generate small-scale features with and without data, but the small-scale features in an SST analysis may be just noise when high-resolution data are sparse. Users must therefore be skeptical of high-resolution SST products, especially in regions where high-resolution (~5 km) infrared satellite data are limited because of cloud cover.

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This study investigates the impact of a full interactive ocean on daily initialised 15 day hindcasts of the Madden-Julian oscillation (MJO), measured against a Met Office Unified Model (MetUM) atmosphere control simulation (AGCM) during a 3 month period of the Year of Tropical Convection (YOTC). Results indicated that the coupled configuration (CGCM) extends MJO predictability over that of the AGCM, by up to 3-5 days. Propagation is improved in the CGCM, which we partly attribute to a more realistic phase relationship between sea surface temperature (SST) and convection. In addition, the CGCM demonstrates skill in representing downwelling oceanic Kelvin and Rossby waves which warm SSTs along their trajectory, with the potential to feed back on the atmosphere. These results imply that an ocean model capable of simulating internal ocean waves may be required to capture the full effect of air-sea coupling for the MJO.

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A chemistry-climate model coupled to an ocean model is used to compare the climate impact of past (1960-2010) changes in concentrations of halocarbons with those of CO2 in the tropical upper troposphere and lower stratosphere. The halocarbon contribution to both upper troposphere warming and the associated increase in lower stratospheric upwelling is about 40% as large as that due to CO2. Trends in cold-point temperature and lower stratosphere water vapor are positive for both halocarbons and CO2, and are of about the same magnitude. Trends in lower stratosphere ozone are negative, due to the increased upwelling. These increases in water vapor and decreases in lower stratosphere ozone feed back on lower stratosphere temperature through radiative cooling. The radiative cooling from ozone is about a factor of two larger than that from water vapor in the vicinity of the cold-point tropopause, while water vapor dominates at heights above 50 hPa. For halocarbons this indirect radiative cooling more than offsets the direct radiative warming, and together with the adiabatic cooling accounts for the lack of a halocarbon-induced warming of the lower stratosphere. For CO2 the indirect cooling from increased water vapor and decreased ozone is of comparable magnitude to the direct warming from CO2 in the vicinity of the cold-point tropopause, and (together with the increased upwelling) lowers the height at which CO2 increases induce stratospheric cooling, thus explaining the relatively weak increase in cold-point temperature due to the CO2 increases.

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It is widely thought that changes in both the surface buoyancy fluxes and wind stress drive variability in the Atlantic meridional overturning circulation (AMOC), but that they drive variability on different time scales. For example, wind forcing dominates short-term variability through its effects on Ekman currents and coastal upwelling, whereas buoyancy forcing is important for longer time scales (multiannual and decadal). However, the role of the wind forcing on multiannual to decadal time scales is less clear. Here the authors present an analysis of simulations with the Nucleus for European Modelling of the Ocean (NEMO) ocean model with the aim of explaining the important drivers of the zonal density gradient at 26°N, which is directly related to the AMOC. In the experiments, only one of either the wind stress or the buoyancy forcing is allowed to vary in time, whereas the other remains at its seasonally varying climatology. On subannual time scales, variations in the density gradient, and in the AMOC minus Ekman, are driven largely by local wind-forced coastal upwelling at both the western and eastern boundaries. On decadal time scales, buoyancy forcing related to the North Atlantic Oscillation dominates variability in the AMOC. Interestingly, however, it is found that wind forcing also plays a role at longer time scales, primarily impacting the interannual variability through the excitation of Rossby waves in the central Atlantic, which propagate westward to interact with the western boundary, but also by modulating the decadal time-scale response to buoyancy forcing.

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In general, particle filters need large numbers of model runs in order to avoid filter degeneracy in high-dimensional systems. The recently proposed, fully nonlinear equivalent-weights particle filter overcomes this requirement by replacing the standard model transition density with two different proposal transition densities. The first proposal density is used to relax all particles towards the high-probability regions of state space as defined by the observations. The crucial second proposal density is then used to ensure that the majority of particles have equivalent weights at observation time. Here, the performance of the scheme in a high, 65 500 dimensional, simplified ocean model is explored. The success of the equivalent-weights particle filter in matching the true model state is shown using the mean of just 32 particles in twin experiments. It is of particular significance that this remains true even as the number and spatial variability of the observations are changed. The results from rank histograms are less easy to interpret and can be influenced considerably by the parameter values used. This article also explores the sensitivity of the performance of the scheme to the chosen parameter values and the effect of using different model error parameters in the truth compared with the ensemble model runs.

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In a numerical, isopycnal, ocean model the mixing is investigated with the environment of two idealized Agulhas rings, one that splits, and one that remains coherent. The evolution of a passive tracer , initially contained within the rings, shows that tracer leakage is associated with the for mation of filaments in the early stage of ring evolution. These filaments reach down to the ther mocline. In the deepest layers leakage occurs on a larger scale. Self-advection of the rings is ver y irregular , and it is not possible to compute a Lagrangian boundar y i n order to estimate the transport of leakage from the rings. T o describe the processes that gover n tracer leakage, in a coordinate frame moving with the ring a kinematic separatrix is defined in the streamfunction field for the nondivergent flow . Initially , filaments arise because of the elongation of the ring, which is mainly gover ned by an m 5 2 instability that is collaborating with differential rotation. Because of beta, the symmetr y i s destroyed related to the separatrix associated with a stagnation point in the flow . The filament upstream of the stagnation point grows much faster and is associated with the bulk of tracer leakage. Mixing is enhanced by time dependence of the separatrix. As a result, there are no large differences between the leakage from a coherent ring, where the m 5 2 instability equilibrates, and from a splitting ring, where the m 5 2 instability keeps growing, which confir ms that the amount of leakage is mainly gover ned by the ring’ s initial defor mation combined with unsteady self-advection of the ring and not by the splitting of the ring. The decay of tracer content in the ther mocline shows that in the first months up to 40% of the ring water can be mixed with the environment. In deeper layers the decay of tracer content may reach up to 90%.

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The sea ice export from the Arctic is of global importance due to its fresh water which influences the oceanic stratification and, thus, the global thermohaline circulation. This study deals with the effect of cyclones on sea ice and sea ice transport in particular on the basis of observations from two field experiments FRAMZY 1999 and FRAMZY 2002 in April 1999 and March 2002 as well as on the basis of simulations with a numerical sea ice model. The simulations realised by a dynamic-thermodynamic sea ice model are forced with 6-hourly atmospheric ECMWF- analyses (European Centre for Medium-Range Weather Forecasts) and 6-hourly oceanic data of a MPI-OM-simulation (Max-Planck-Institute Ocean Model). Comparing the observed and simulated variability of the sea ice drift and of the position of the ice edge shows that the chosen configuration of the model is appropriate for the performed studies. The seven observed cyclones change the position of the ice edge up to 100 km and cause an extensive decrease of sea ice coverage by 2 % up to more than 10 %. The decrease is only simulated by the model if the ocean current is strongly divergent in the centre of the cyclone. The impact is remarkable of the ocean current on divergence and shear deformation of the ice drift. As shown by sensitivity studies the ocean current at a depth of 6 m – the sea ice model is forced with – is mainly responsible for the ascertained differences between simulation and observation. The simulated sea ice transport shows a strong variability on a time scale from hours to days. Local minima occur in the time series of the ice transport during periods with Fram Strait cyclones. These minima are not caused by the local effect of the cyclone’s wind field, but mainly by the large-scale pattern of surface pressure. A displacement of the areas of strongest cyclone activity in the Nordic Seas would considerably influence the ice transport.

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Whilst a range of animals have been shown to respond behaviourally to components of the Earth’s magnetic field, evidence of the value of this sensory perception for small animals advected by strong flows (wind/ocean currents) is equivocal. We added geomagnetic directional swimming behaviour for North Atlantic loggerhead turtle hatchlings (Caretta caretta) into a high-resolution (1/4°) global general circulation ocean model to simulate 2,925-year-long hatchling trajectories comprising 355,875 locations. A little directional swimming (1–3 h per day) had a major impact on trajectories; simulated hatchlings travelled further south into warmer water. As a result, thermal elevation of hatchling metabolic rates was estimated to be between 63.3 and 114.5% after 220 days. We show that even small animals in strong flows can benefit from geomagnetic orientation and thus the potential implications of directional swimming for other taxa may be broad.

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The movements of some long-distance migrants are driven by innate compass headings that they follow on their first migrations (e.g., some birds and insects), while the movements of other first-time migrants are learned by following more experienced conspecifics (e.g., baleen whales). However, the overall roles of innate, learned, and social behaviors in driving migration goals in many taxa are poorly understood. To look for evidence of whether migration routes are innate or learned for sea turtles, here for 42 sites around the world we compare the migration routes of >400 satellite-tracked adults of multiple species of sea turtle with ∼45 000 Lagrangian hatchling turtle drift scenarios. In so doing, we show that the migration routes of adult turtles are strongly related to hatchling drift patterns, implying that adult migration goals are learned through their past experiences dispersing with ocean currents. The diverse migration destinations of adults consistently reflected the diversity in sites they would have encountered as drifting hatchlings. Our findings reveal how a simple mechanism, juvenile passive drift, can explain the ontogeny of some of the longest migrations in the animal kingdom and ensure that adults find suitable foraging sites.

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Water quality monitoring and prediction are critical for ensuring the sustainability of water resources which are essential for social security, especially for countries with limited land like Singapore. For example, the Singapore government identified water as a new growth sector and committed in 2006 to invest S$ 330 million over the following five years for water research and development [1]. To investigate the water quality evolution numerically, some key water quality parameters at several discrete locations in the reservoir (e.g., dissolved oxygen, chlorophyll, and temperature) and some environmental parameters (e.g., the wind distribution above water surface, air temperature and precipitation) are used as inputs to a three-dimensional hydrodynamics-ecological model, Estuary Lake and Coastal Ocean Model - Computational Aquatic Ecosystem Dynamics Model (ELCOM-CAEDYM) [2]. Based on the calculation in the model, we can obtain the distribution of water quality in the whole reservoir. We can also study the effect of different environmental parameters on the water quality evolution, and finally predict the water quality of the reservoir with a time step of 30 seconds. In this demo, we introduce our data collection system which enables water quality studies with real-time sensor data.

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In the Tropics, continental shelves governed by western boundary currents are considered to be among the least productive ocean margins in the world, unless eddy-induced shelf-edge upwelling becomes significant. The eastern Brazilian shelf in the Southwest Atlantic is one of these, and since the slight nutrient input from continental sources is extremely oligotrophic. It is characterized by complex bathymetry with the presence of shallow banks and seamounts. In this work, a full three-dimensional nonlinear primitive equation ocean model is used to demonstrate that the interaction of tidal currents and the bottom topography of the east Brazil continental shelf is capable of producing local upwelling of South Atlantic Central Water, bringing nutrients up from deep waters to the surface layer. Such upper layer enrichment is found to be of significance in increasing local primary productivity. (c) 2005 Elsevier Ltd. All rights reserved.

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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It has been shown that the vertical structure of the Brazil Current (BC)-Intermediate Western Boundary Current (IWBC) System is dominated by the first baroclinic mode at 22 degrees S-23 degrees S. In this work, we employed the Miami Isopycnic Coordinate Ocean Model to investigate whether the rich mesoscale activity of this current system, between 20 degrees S and 28 degrees S, is reproduced by a two-layer approximation of its vertical structure. The model results showed cyclonic and anticyclonic meanders propagating southwestward along the current axis, resembling the dynamical pattern of Rossby waves superposed on a mean flow. Analysis of the upper layer zonal velocity component, using a space-time diagram, revealed a dominant wavelength of about 450 km and phase velocity of about 0.20 ms(-1) southwestward. The results also showed that the eddy-like structures slowly grew in amplitude as they moved downstream. Despite the simplified design of the numerical experiments conducted here, these results compared favorably with observations and seem to indicate that weakly unstable long baroclinic waves are responsible for most of the variability observed in the BC-IWBC system. (C) 2009 Elsevier Ltd. All rights reserved.

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Last Glacial Maximum simulated sea surface temperature from the Paleo-Climate version of the National Center for Atmospheric Research Coupled Climate Model (NCAR-CCSM) are compared with available reconstructions and data-based products in the tropical and south Atlantic region. Model results are compared to data proxies based on the Multiproxy Approach for the Reconstruction of the Glacial Ocean surface product (MARGO). Results show that the model sea surface temperature is not consistent with the proxy-data in all of the region of interest. Discrepancies are found in the eastern, equatorial and in the high-latitude South Atlantic. The model overestimates the cooling in the southern South Atlantic (near 50 degrees S) shown by the proxy-data. Near the equator, model and proxies are in better agreement. In the eastern part of the equatorial basin the model underestimates the cooling shown by all proxies. A northward shift in the position of the subtropical convergence zone in the simulation suggests a compression or/and an equatorward shift of the subtropical gyre at the surface, consistent with what is observed in the proxy reconstruction. (C) 2008 Elsevier B.V. All rights reserved