Ocean Modelling最新文献

Oceanic mesoscale eddies play an important role in transports of heat, freshwater, mass in the ocean, therefore understanding three-dimensional structure of oceanic eddies is of significance to climate study and oceanic applications. However, detection of three-dimensional (3D) structures is a big challenge though many algorithms of sea surface 2D eddy detection are developed. In this study, we present a novel approach by using 3D U-Net residual architecture (3D-U-Res-Net) to identify 3D structure of oceanic eddies. The sensitivity tests to input variables are conducted to optimalize the input setting. Trained by 3D eddy data provided by a kinetic eddy detection method, the AI-based method can identify different kinds of eddy vertical structures and moreover can dig out more eddy information in deeper layers. This study has significant implications for the further application of the AI-based algorithm in oceanic study.

This paper proposes a new model to study future coastal maritime climate under climate change context. This new model combines statistical analysis, Monte Carlo simulations and Artificial Neural Networks (ANNs). Statistical analysis and Monte Carlo simulations are used to extrapolate future wave climate under climate change context at a regional level and ANNs are used to propagate these projected sea states obtained in deep water to the coast. The use of ANNs allows for the utilization of large amounts of data at a very low computational cost, and the use of Monte Carlo simulations enables the generation of future climate change projections at a regional level. The combination of the two methodologies results in a very accurate (MSE of 0.02 m and 1 s) and computationally inexpensive hybrid model that allows projections of coastal maritime climate considering climate change. This new methodology has been validated and applied in the Western Mediterranean for the long-term regime and for extreme events, obtaining increases in extreme events up to 1.5 m in wave height and up to 1.8 s in wave period by 2050.

Surface waves are extremely important in a large variety of oceanographic applications and thus, the study of their spatiotemporal characteristics remains crucial. This study analyzes waves in the Caribbean Sea (CS) and western Atlantic Ocean (AO) using a high-resolution (HR) Simulating WAves Nearshore model validated with buoy observations and paired with a HR bathymetric dataset from 2010 – 2019. Island sheltering effects are examined but special attention is given to these effects under Hurricane Dorian in The Bahamas using observations from the China-France Oceanographic Satellite. Results illustrate that wave heights within the CS fluctuated with Caribbean Low-Level Jet activity, but a different wave regime exists within the AO. While wind waves overwhelmingly dominate the wave field and this is true even in the AO, surprisingly, the contribution of swell in the central CS was equal to one site in the AO. Possibly, due to interaction with the shallow Nicaraguan Rise, wave heights were strongly (depth-induced) refracted nearly 45°, a feature unseen in previous research using coarse bathymetric datasets. Island sheltering effects were pervasive and were naturally most pronounced under hurricane conditions. Crucially, New Providence in The Bahamas is vulnerable to hurricane-forced waves funneled through the Grand Bahama and Northeastern Providence Channels.

The areas around estuaries are typically densely populated and economically developed. Therefore, robust flood risk assessment in these areas is critical. One of the key elements of flood risk assessment is the accurate prediction of estuarine water levels. However, the nonlinear interactions between riverine (i.e., upstream river discharge) and marine (i.e., tides) forces complicate the prediction of estuarine water levels. Traditional physics-based and data-driven models have made significant progress in predicting estuarine water levels, but they require upstream river discharge data as inputs. Considering the lack of such data, the development of new approaches is crucial. This study investigated a machine-learning-based light gradient boosting machine (LightGBM) framework for predicting estuarine water levels using historical water levels as the only inputs. Two prediction models based on the LightGBM framework, denoted as LightGBM1 and LightGBM2, are developed. The LightGBM1 model constructs only a single regression model and uses a recursive approach to generate multidimensional outputs. The LightGBM2 model constructs multiple regression models between the same inputs and outputs in each dimension. The LightGBM1 and LightGBM2 models were applied to the Yangtze estuary as a test case. The results demonstrate that both models are effective at predicting short-term (within 48 hours) estuarine water levels, but the statistical performance of LightGBM2 is better overall. For 24-hour prediction, the root-mean-squared errors of the LightGBM1 and LightGBM2 models are in the ranges of 0.14–0.17 m and 0.12–0.15 m, respectively.

Lake Erie has been negatively impacted by multiple stressors, including nutrient enrichment and climate change, that have exacerbated eutrophication and harmful algal blooms. Management of these long-term water quality problems requires numerical models that can be run over years to decades. The three-dimensional hydrodynamics and biogeochemistry models applied to date, however, have not been tested for continuous runs longer than one year and have not been shown to accurately reproduce seasonal variation in phytoplankton species composition (e.g., the development of harmful algal blooms) over decadal timescales. We simulated the three-dimensional nutrient and phytoplankton concentrations in western Lake Erie continuously from 2002 to 2014. Using a single parameter set, we were able to reproduce both seasonal and inter-annual variation in phytoplankton species composition. The model qualitatively reproduced the observed seasonal succession (i.e., variation in phytoplankton species composition), including the spring diatom bloom and late summer cyanobacterial growth. This study demonstrates that three-dimensional models can be applied for multi-year simulations of nutrients and phytoplankton to inform large lake research and management.

This research evaluates the performance of CAS-LICOM3 (Chinese Academy of Science, State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics/Institute of Atmospheric Physics (LASG/IAP) Climate system Ocean Model, version 3) in simulating global coherent mesoscale eddies by comparison to satellite altimeter observations. The simulations of westward and eastward propagating eddies (WPEs and EPEs) and cyclonic and anticyclonic eddies (CEs and AEs) are separately analyzed. The results demonstrate that the simulated spatial-temporal variabilities in global mesoscale eddies agree roughly with the satellite observations. CAS-LICOM3 also reproduces the distinctive features between WPEs and EPEs or between CEs and AEs. However, some systematic biases are found. Globally, CAS-LICOM3 simulates a less frequent and weaker mesoscale eddy field than is observed. WPEs contribute more to these global biases than do EPEs. EPEs are relatively better reproduced than WPEs, exhibiting smaller underestimations and even overestimations in the energetic western boundary current and Antarctic circumpolar current regions. The simulation results for CEs resemble those of AEs, but AEs are comparatively less biased than CEs. These findings provide a basis for improving low-resolution and eddy-resolving ocean general circulation models (OGCMs) and developing submesoscale-resolving OGCMs.

The Yellow Sea Cold Water Mass (YSCWM), surrounded by thermocline and fronts, is one of the most notable hydrological characteristics of the Yellow Sea (YS) in the summer. Temperature structure at the boundary of the YSCWM drives the Yellow Sea Cold Water Mass Circulation (YSCWMC). However, the 3D structure of YSCWMC remains unclear. The position, seasonal evolution, and dynamical mechanisms of the YSCWMC were examined by observations and high-resolution numerical model. It was found that the core of the YSCWMC is located at the junction of the fronts and the thermocline during the summer. Furthermore, the YSCWMC exhibits remarkable seasonal variations characterized by a progressive shrinking and deepening dependence on the position and strength of the fronts and thermocline. The YSCWMC is geostrophic at the basin scale, with the barotropic pressure term determining the direction of the circulation and the baroclinic pressure term controlling the vertical structure of the circulation. Fronts yield a baroclinic effect in the thermal field and affect the sea surface elevation in the barotropic process. Therefore, fronts are crucial to the formation of the YSCWMC. Nevertheless, under conditions of steep topography, tidal rectification is comparable to the frontal contribution to the circulation.

To fully resolve eight major tides from short-term records, classical harmonic analysis model usually infers unresolved constituents with the help of inference relationships from nearby long-term tide gauges. Our previous study developed a modified harmonic analysis model using the credo of smoothness (i.e., MHACS) which can achieve this without inference relationships. Via introducing the inherent natural links between major tides, MHACS breaks the restrictions of the Rayleigh criterion and requires only ∼9-day hourly records to resolve eight major tides. However, when data length is shorter than 9 days, the results of MHACS become problematic due to over-fitting. In this study, we introduce ridge regression to replace ordinary least squares (OLS) in the MHACS. Practical experiments on short-term hourly tide gauge records and satellite altimeter observations indicate that ridge regression can effectively eliminate meaningless mathematical artifacts obtained by OLS. The minimum length of records for MHACS to resolve eight major tides dramatically decreases from ∼210 h to ∼75 h as a result of using ridge regression. It is also found that ridge regression can notably reduce the uncertainties of tidal estimates from MHACS. Moreover, other modified harmonic analysis models such as NS_TIDE designed for river tides also suffer from over-fitting which can be solved by ridge regression in a similar way.

Here we address the problem of coherent interference that arises in double-sum wavemakers of wave-resolving models. Identified as a key problem for experimental and numerical simulations since the late 1970s, this problem induces spurious persistent longshore variability and affects nearshore dynamics. To overcome this problem, we present the implementation of a single-sum wavemaker in the 3D wave-resolving model CROCO. The new wavemaker, which assigns only one pair of direction and frequency values to each component of the wave spectrum, definitively prevents coherent interference, unlike a conventional double-sum wavemaker that allows waves of different direction to share the same frequency. Each wave component must also strictly comply with the periodicity rules, to avoid any spurious boundary dynamics. We validate the single-sum wavemaker with experimental data collected in a wave basin with longshore-uniform bathymetry and compare results with the double-sum wavemaker simulations. We show that the new wavemaker produces transient rips devoid of any coherent interference effect and that, consequently, the model statistics closely match the experimental data. The new wavemaker therefore guarantees statistical integrity while reducing computational costs, a necessary step for realistic wave-resolving studies of nearshore dynamics.

Thirteen laboratory and field tests were carried out with vibrating sea ice beams to study the dependence of the elastic modulus of sea ice in the spectral range from 1 Hz to 500 Hz. Six full-scale tests with floating fixed ends beams were carried out on the land fast ice of the Spitsbergen fjords. For laboratory testing, smaller ice beams were made sea ice of the same fjords. Three tests with columnar fresh lake ice S2 were conducted to validate the method for calculating of the added mass of a floating beam with fixed ends. A 60% increase in the elastic modulus of columnar sea ice S2 was found due to an increase in the frequency of flexural deformations in the range from 10 Hz to 500 Hz. The paper also discusses the influence of ice structure on the elastic modulus.