990 resultados para Princeton Ocean Model
Resumo:
The climate over the Arctic has undergone changes in recent decades. In order to evaluate the coupled response of the Arctic system to external and internal forcing, our study focuses on the estimation of regional climate variability and its dependence on large-scale atmospheric and regional ocean circulations. A global ocean–sea ice model with regionally high horizontal resolution is coupled to an atmospheric regional model and global terrestrial hydrology model. This way of coupling divides the global ocean model setup into two different domains: one coupled, where the ocean and the atmosphere are interacting, and one uncoupled, where the ocean model is driven by prescribed atmospheric forcing and runs in a so-called stand-alone mode. Therefore, selecting a specific area for the regional atmosphere implies that the ocean–atmosphere system can develop ‘freely’ in that area, whereas for the rest of the global ocean, the circulation is driven by prescribed atmospheric forcing without any feedbacks. Five different coupled setups are chosen for ensemble simulations. The choice of the coupled domains was done to estimate the influences of the Subtropical Atlantic, Eurasian and North Pacific regions on northern North Atlantic and Arctic climate. Our simulations show that the regional coupled ocean–atmosphere model is sensitive to the choice of the modelled area. The different model configurations reproduce differently both the mean climate and its variability. Only two out of five model setups were able to reproduce the Arctic climate as observed under recent climate conditions (ERA-40 Reanalysis). Evidence is found that the main source of uncertainty for Arctic climate variability and its predictability is the North Pacific. The prescription of North Pacific conditions in the regional model leads to significant correlation with observations, even if the whole North Atlantic is within the coupled model domain. However, the inclusion of the North Pacific area into the coupled system drastically changes the Arctic climate variability to a point where the Arctic Oscillation becomes an ‘internal mode’ of variability and correlations of year-to-year variability with observational data vanish. In line with previous studies, our simulations provide evidence that Arctic sea ice export is mainly due to ‘internal variability’ within the Arctic region. We conclude that the choice of model domains should be based on physical knowledge of the atmospheric and oceanic processes and not on ‘geographic’ reasons. This is particularly the case for areas like the Arctic, which has very complex feedbacks between components of the regional climate system.
Resumo:
Current methods for initialising coupled atmosphere-ocean forecasts often rely on the use of separate atmosphere and ocean analyses, the combination of which can leave the coupled system imbalanced at the beginning of the forecast, potentially accelerating the development of errors. Using a series of experiments with the European Centre for Medium-range Weather Forecasts coupled system, the magnitude and extent of these so-called initialisation shocks is quantified, and their impact on forecast skill measured. It is found that forecasts initialised by separate ocean and atmospheric analyses do exhibit initialisation shocks in lower atmospheric temperature, when compared to forecasts initialised using a coupled data assimilation method. These shocks result in as much as a doubling of root-mean-square error on the first day of the forecast in some regions, and in increases that are sustained for the duration of the 10-day forecasts performed here. However, the impacts of this choice of initialisation on forecast skill, assessed using independent datasets, were found to be negligible, at least over the limited period studied. Larger initialisation shocks are found to follow a change in either the atmospheric or ocean model component between the analysis and forecast phases: changes in the ocean component can lead to sea surface temperature shocks of more than 0.5K in some equatorial regions during the first day of the forecast. Implications for the development of coupled forecast systems, particularly with respect to coupled data assimilation methods, are discussed.
Resumo:
We present ocean model sensitivity experiments aimed at separating the influence of the projected changes in the “thermal” (near-surface air temperature) and “wind” (near-surface winds) forcing on the patterns of sea level and ocean heat content. In the North Atlantic, the distribution of sea level change is more due to the “thermal” forcing, whereas it is more due to the “wind” forcing in the North Pacific; in the Southern Ocean, the “thermal” and “wind” forcing have a comparable influence. In the ocean adjacent to Antarctica the “thermal” forcing leads to an inflow of warmer waters on the continental shelves, which is somewhat attenuated by the “wind” forcing. The structure of the vertically integrated heat uptake is set by different processes at low and high latitudes: at low latitudes it is dominated by the heat transport convergence, whereas at high latitudes it represents a small residual of changes in the surface flux and advection of heat. The structure of the horizontally integrated heat content tendency is set by the increase of downward heat flux by the mean circulation and comparable decrease of upward heat flux by the subgrid-scale processes; the upward eddy heat flux decreases and increases by almost the same magnitude in response to, respectively, the “thermal” and “wind” forcing. Regionally, the surface heat loss and deep convection weaken in the Labrador Sea, but intensify in the Greenland Sea in the region of sea ice retreat. The enhanced heat flux anomaly in the subpolar Atlantic is mainly caused by the “thermal” forcing.
Resumo:
The ring-shedding process in the Agulhas Current is studied using the ensemble Kalman filter to assimilate geosat altimeter data into a two-layer quasigeostrophic ocean model. The properties of the ensemble Kalman filter are further explored with focus on the analysis scheme and the use of gridded data. The Geosat data consist of 10 fields of gridded sea-surface height anomalies separated 10 days apart that are added to a climatic mean field. This corresponds to a huge number of data values, and a data reduction scheme must be applied to increase the efficiency of the analysis procedure. Further, it is illustrated how one can resolve the rank problem occurring when a too large dataset or a small ensemble is used.
Resumo:
Sea-ice concentrations in the Laptev Sea simulated by the coupled North Atlantic-Arctic Ocean-Sea-Ice Model and Finite Element Sea-Ice Ocean Model are evaluated using sea-ice concentrations from Advanced Microwave Scanning Radiometer-Earth Observing System satellite data and a polynya classification method for winter 2007/08. While developed to simulate largescale sea-ice conditions, both models are analysed here in terms of polynya simulation. The main modification of both models in this study is the implementation of a landfast-ice mask. Simulated sea-ice fields from different model runs are compared with emphasis placed on the impact of this prescribed landfast-ice mask. We demonstrate that sea-ice models are not able to simulate flaw polynyas realistically when used without fast-ice description. Our investigations indicate that without landfast ice and with coarse horizontal resolution the models overestimate the fraction of open water in the polynya. This is not because a realistic polynya appears but due to a larger-scale reduction of ice concentrations and smoothed ice-concentration fields. After implementation of a landfast-ice mask, the polynya location is realistically simulated but the total open-water area is still overestimated in most cases. The study shows that the fast-ice parameterization is essential for model improvements. However, further improvements are necessary in order to progress from the simulation of large-scale features in the Arctic towards a more detailed simulation of smaller-scaled features (here polynyas) in an Arctic shelf sea.
Resumo:
In this paper we use a coupled ocean-atmosphere model to investigate the impact of the interruption of Agulhas leakage of Indian ocean water on the tropical Atlantic, a region where strong coupled ocean-atmosphere interactions occur. The effect of a shut down of leakage of Indian ocean water is isolated from the effect of a collapse of the MOC. In our experiments, the ocean model is forced with boundary conditions in the southeastern corner of the domain that correspond to no interocean exchange of Indian ocean water into the Atlantic. The southern boundary condition is taken from the Levitus data and ensures an MOC in the Atlantic. Within this configuration, instead of warm and salty Indian ocean water temperature (cold) and salinity (fresh) anomalies of southern ocean origin propagate into the South Atlantic and eventually reach the equatorial region, mainly in the thermocline. This set up mimics the closure of the ""warm water path"" in favor of the ""cold water path"". As part of the atmospheric response, there is a northward shift of the intertropical convergence zone (ITCZ). The changes in trade winds lead to reduced Ekman pumping in the equatorial region. This leads to a freshening and warming of the surface waters along the equator. Especially in the Cold Tongue region, the cold and fresh subsurface anomalies do not reach the surface due to the reduced upwelling. The anomaly signals are transported by the equatorial undercurrent and spread away from the equator within the thermocline. Part of the anomaly eventually reaches the Tropical North Atlantic, where it affects the Guinea Dome. Surprisingly, the main effect at the surface is small on the equator and relatively large at the Guinea Dome. In the atmosphere, the northward shift of the ITCZ is associated with a band of negative precipitation anomalies and higher salinities over the Tropical South Atlantic. An important implication of these results is that the modified water characteristics due to a shut down of the Agulhas leakage remain largely unaffected when crossing the equatorial Atlantic and therefore can affect the deepwater formation in the North Atlantic. This supports the hypothesis that the Agulhas leakage is an important source region for climate change and decadal variability of the Atlantic.
Resumo:
Analysis of the NCAR/NCEP Reanalysis show changes in the atmospheric circulation in the Southern hemisphere, with a strengthening and poleward displacement of the westerlies. Because the wind is one of the main sources of the ocean's kinetic energy, a numerical experiment with the Hybrid Coordinate Ocean Model (HYCOM) was forced with monthly means of the NCAR/NCEP Reanalysis products to investigate the effects of the changes in the wind on the ocean circulation in a geographical domain defined by 98W – 114E; 65S – 60N. The results show good agreement with other models and with available satellite data. In the western sector of the South Atlantic there are several indications of changes such as a poleward displacement of the Brazil-Malvinas Confluence and positive trends in temperature and salinity of the southwestern region of the subtropical gyre
Resumo:
Analysis of the NCAR/NCEP Reanalysis show changes in the atmospheric circulation in the Southern hemisphere, with a strengthening and poleward displacement of the westerlies. Because the wind is one of the main sources of the ocean's kinetic energy, a numerical experiment with the Hybrid Coordinate Ocean Model (HYCOM) was forced with monthly means of the NCAR/NCEP Reanalysis products to investigate the effects of the changes in the wind on the ocean circulation in a geographical domain defined by 98W – 114E; 65S – 60N. The results show good agreement with other models and with available satellite data. In the western sector of the South Atlantic there are several indications of changes such as a poleward displacement of the Brazil-Malvinas Confluence and positive trends in temperature and salinity of the southwestern region of the subtropical gyre.
Resumo:
[EN] The General Curvilinear Environmental Model is a high-resolution system composed of the General Curvilinear Coastal Ocean Model (GCCOM) and the General Curvilinear Atmospheric Model (GCAM). Both modules are capable of reading a general curvilinear grid, orthogonal as well as non-orthogonal in all three directions. These two modules are weakly coupled using the distributed coupling toolkit (DCT). The model can also be nested within larger models and users are able to interact with the model and run it using a web based computational environment.
Resumo:
This research activity studied how the uncertainties are concerned and interrelated through the multi-model approach, since it seems to be the bigger challenge of ocean and weather forecasting. Moreover, we tried to reduce model error throughout the superensemble approach. In order to provide this aim, we created different dataset and by means of proper algorithms we obtained the superensamble estimate. We studied the sensitivity of this algorithm in function of its characteristics parameters. Clearly, it is not possible to evaluate a reasonable estimation of the error neglecting the importance of the grid size of ocean model, for the large amount of all the sub grid-phenomena embedded in space discretizations that can be only roughly parametrized instead of an explicit evaluation. For this reason we also developed a high resolution model, in order to calculate for the first time the impact of grid resolution on model error.
Resumo:
The exchange of chemical constituents between ocean and atmosphere provides potentially important feedback mechanisms in the climate system. The aim of this study is to develop and evaluate a chemically coupled global atmosphere-ocean model. For this, an atmosphere-ocean general circulation model with atmospheric chemistry has been expanded to include oceanic biogeochemistry and the process of air-sea gas exchange. The calculation of seawater concentrations in the oceanic biogeochemistry submodel has been expanded from DMS, CO₂
Resumo:
Geostrophic surface velocities can be derived from the gradients of the mean dynamic topography-the difference between the mean sea surface and the geoid. Therefore, independently observed mean dynamic topography data are valuable input parameters and constraints for ocean circulation models. For a successful fit to observational dynamic topography data, not only the mean dynamic topography on the particular ocean model grid is required, but also information about its inverse covariance matrix. The calculation of the mean dynamic topography from satellite-based gravity field models and altimetric sea surface height measurements, however, is not straightforward. For this purpose, we previously developed an integrated approach to combining these two different observation groups in a consistent way without using the common filter approaches (Becker et al. in J Geodyn 59(60):99-110, 2012, doi:10.1016/j.jog.2011.07.0069; Becker in Konsistente Kombination von Schwerefeld, Altimetrie und hydrographischen Daten zur Modellierung der dynamischen Ozeantopographie, 2012, http://nbn-resolving.de/nbn:de:hbz:5n-29199). Within this combination method, the full spectral range of the observations is considered. Further, it allows the direct determination of the normal equations (i.e., the inverse of the error covariance matrix) of the mean dynamic topography on arbitrary grids, which is one of the requirements for ocean data assimilation. In this paper, we report progress through selection and improved processing of altimetric data sets. We focus on the preprocessing steps of along-track altimetry data from Jason-1 and Envisat to obtain a mean sea surface profile. During this procedure, a rigorous variance propagation is accomplished, so that, for the first time, the full covariance matrix of the mean sea surface is available. The combination of the mean profile and a combined GRACE/GOCE gravity field model yields a mean dynamic topography model for the North Atlantic Ocean that is characterized by a defined set of assumptions. We show that including the geodetically derived mean dynamic topography with the full error structure in a 3D stationary inverse ocean model improves modeled oceanographic features over previous estimates.
Resumo:
The CMCC Global Ocean Physical Reanalysis System (C-GLORS) is used to simulate the state of the ocean in the last decades. It consists of a variational data assimilation system (OceanVar), capable of assimilating all in-situ observations along with altimetry data, and a forecast step performed by the ocean model NEMO coupled with the LIM2 sea-ice model. KEY STRENGTHS: - Data are available for a large number of ocean parameters - An extensive validation has been conducted and is freely available - The reanalysis is performed at high resolution (1/4 degree) and spans the last 30 years KEY LIMITATIONS: - Quality may be discontinuos and depend on observation coverage - Uncertainty estimates are simply derived through verification skill scores
Resumo:
Northern Hemisphere sea ice from a Finite-Element Sea-Ice Ocean Model (FESOM) 4.5 km resolution simulation carried out by researchers from Alfred Wegener Institute (AWI), Germany. Concentration is shown with color; thickness is shown with shading. A global 1 degree mesh is used, with the "Arctic Ocean" locally refined to 4.5 km. South of CAA and Fram Strait the resolution is not refined in this simulation. The animation indicates that the 4.5 km model resolution helps to represent the small scale sea ice features, although much higher resolution is required to fully resolve the ice leads. The animation is created by Michael Böttinger from DKRZ (https://www.dkrz.de).
Resumo:
The marine cycle of calcium carbonate (CaCO3) is an important element of the carbon cycle and co-governs the distribution of carbon and alkalinity within the ocean. However, CaCO3 export fluxes and mechanisms governing CaCO3 dissolution are highly uncertain. We present an observationally constrained, probabilistic assessment of the global and regional CaCO3 budgets. Parameters governing pelagic CaCO3 export fluxes and dissolution rates are sampled using a Monte Carlo scheme to construct a 1000-member ensemble with the Bern3D ocean model. Ensemble results are constrained by comparing simulated and observation-based fields of excess dissolved calcium carbonate (TA*). The minerals calcite and aragonite are modelled explicitly and ocean–sediment fluxes are considered. For local dissolution rates, either a strong or a weak dependency on CaCO3 saturation is assumed. In addition, there is the option to have saturation-independent dissolution above the saturation horizon. The median (and 68 % confidence interval) of the constrained model ensemble for global biogenic CaCO3 export is 0.90 (0.72–1.05) Gt C yr−1, that is within the lower half of previously published estimates (0.4–1.8 Gt C yr−1). The spatial pattern of CaCO3 export is broadly consistent with earlier assessments. Export is large in the Southern Ocean, the tropical Indo–Pacific, the northern Pacific and relatively small in the Atlantic. The constrained results are robust across a range of diapycnal mixing coefficients and, thus, ocean circulation strengths. Modelled ocean circulation and transport timescales for the different set-ups were further evaluated with CFC11 and radiocarbon observations. Parameters and mechanisms governing dissolution are hardly constrained by either the TA* data or the current compilation of CaCO3 flux measurements such that model realisations with and without saturation-dependent dissolution achieve skill. We suggest applying saturation-independent dissolution rates in Earth system models to minimise computational costs.