Ocean Modelling最新文献

In this paper, we describe methods to verify the adequacy and accuracy of Lagrangian particles from a Lagrangian model to reproduce the concentrations of a passive tracer from an Eulerian-model in river plumes. The modelling simulates plumes from two major rivers discharging in the Great Barrier Reef (GBR), Australia, under real-world scenarios. The study has been a part of a major project to aid in the protection of the GBR system from the impacts of extreme events and climate change. We employ the Regional Ocean Modelling System (ROMS) activated with its built-in Lagrangian model, and forced with wind fields from global models and recorded river volume discharges. The ROMS-Lagrangian model tracks the Lagrangian particles using the spatially interpolated velocities computed on the Eulerian ROMS three-dimensional (3D) grid. The Lagrangian particles are released in the river in proportion to the measured river volume flux. We apply a novel technique that exploits Voronoi polygon areas to convert Lagrangian particle separation into a concentration field. This facilitates comparison with the passive tracer concentrations driven by the Eulerian velocities computed on the ROMS 3D grid. We evaluate the fate of Lagrangian particles activated on a 4-km grid resolution with those of equivalent Eulerian tracer concentrations. For validation, we compare the Lagrangian particles with the Eulerian passive tracer simulated using a higher model grid resolution of 500-m, and found that the computed Lagrangian particle concentrations showed similar overall patterns compared to the passive tracer concentrations from both the coarse 4-km, and high-resolution 500-m Eulerian models. The spatial extent of the particles was in better agreement with the coarse 4-km model than with the higher resolution 500-m model. The clustering of particles resulted in structures at finer scales than the Eulerian model, over the high particle density areas that compared well against observations. The Lagrangian particles are able to capture the general river plume patterns seen in the satellite MODIS images and the satellite derived Chlorophyll-a. We further compare the online ROMS model with an offline particle tracker, OceanPARCELS and determined the similarity of results from both online and offline methods. Overall, our study demonstrates the viability to use Lagrangian particles to reproduce the Eulerian tracer properties, which can be combined with particle properties include tracer age providing to enhance the guidance on the distribution and concentration of effluent from localised flooding river events.

A number of coastal tide gauges and offshore Deep-ocean Assessment and Reporting of Tsunamis (DART) buoys across the Pacific Basin recorded persistent oscillations excited by the 2011 Tohoku-Oki tsunami. The hazardous persistent oscillations prompted authorities to maintain a tsunami warning for dozens of hours. Tsunami waves reached the eastern China coast about five hours after the earthquake. The duration of detected prolonged oscillations was more than 80 h. In this study, we accurately reproduced tsunami generation and its evolution over the shallow and wide continental shelf of the East China Sea (ECS). For resonance analysis, we used an advanced numerical model that can consider simultaneously the effects of kinematic rupture process, horizontal displacement on tsunami generation, and Earth elasticity, seawater compressibility, and wave dispersion on tsunami propagation. The consistency of the simulated results was validated with both coastal and offshore tsunami records. In addition, we performed a combined spectral analysis of the observed tsunami records, background noise, and synthetic tsunami wave fields to identify tsunami oscillation modes and estimate their spatial distribution, including the spectral amplitude and phase angles. Eight main oscillation modes of the 2011 Tohoku tsunami were determined with periods of 24, 28, 37, 47, 57, 93, 136, and 157 min. They were all constrained within the 200-m isobaths for dozens of hours. The 57 min oscillations mode had the highest energy amplification across most of eastern China's coast. The spatial patterns of the resonance oscillations were used to propose hazard-prone areas. Based on the comprehensive spectral analysis results, the local and shelf topography properties played a key role in the dominant resonance modes of 136, 57, and 37 min. Identification of the shelf resonance oscillations coupled with the nearshore basin oscillations can provide valuable information for coastal tsunami hazard mitigation.

A novel convolutional neural network-long short-term memory (CNN-LSTM) model is proposed for wave height prediction. The model effectively extracts relevant features such as wind speed, wind direction, wave height, latitude, and longitude. The proposed model outperforms traditional machine learning algorithms such as multi-layer perceptron (MLP), support vector machine (SVM), random forest and LSTM, especially for extreme values and fluctuations. The model has a significantly lower average root mean square error (RMSE) of 71.1%, 72.8%, 71.9% and 72.2% for MLP, SVM, random forest and LSTM, respectively. Our model is computationally more efficient than traditional numerical simulations, making it suitable for real-time applications. Moreover, it has better long-term robustness compared to traditional models. The integration of CNN and LSTM techniques improves wave height prediction accuracy while enhancing its efficiency and robustness. The proposed CNN-LSTM model provides a promising tool for effective wave height prediction, making a valuable contribution to coastal disaster prevention and mitigation. Future research should aim to improve long-term prediction accuracy, and we believe that the CNN-LSTM model plays a crucial role in developing real-time coastal disaster prevention and mitigation measures. Overall, our study represents a significant step towards achieving more accurate and efficient wave height prediction using machine learning techniques.

Marine oxygen plays a fundamental role in regulating the transfer of organic carbon and nutrients to their dissolved inorganic forms, serving as the terminal electron acceptor for heterotrophic respiration. Oxygen can become limiting to these processes in coastal and open-ocean oxygen deficient zones (ODZs). The maintenance of ODZs depends on the balance between physical processes such as ventilation and biogeochemical processes such as remineralization. These two processes act in opposing directions on ODZs, with ventilation responsible for transporting oxygen from the surface, where it is near saturation with the partial pressure of O₂ in the atmosphere, to deeper oxygen-depleted layers, and remineralization acting to consume oxygen through biogeochemical processes such as microbial degradation throughout the water column. Remineralization is represented in all CMIP6 models, but the actual parameterizations, as well as their magnitude, are widely varying.

In this study, we examine the sensitivity to remineralization of the equatorial Pacific ODZ (O₂ $<60\mu m$ol/kg) in a model; the NASA GISS Ocean Biogeochemical Model (NOBM-G) embedded in the NASA-GISS coupled atmosphere-ocean model. We find that increasing the remineralization rate shoals the ODZ onset depth (i.e. the regionally averaged upper bound of the ODZ), and decreases ODZ volume and regional-averaged thickness. Changes in biological consumption and vertical convergence of oxygen are identified as the primary contributors to changes in ODZ onset depth. ODZ thickness is mainly influenced by the shoaling of the bottom boundary of the ODZ, which decreases with maximum remineralization rate due to decreasing oxygen consumption and increasing horizontal oxygen convergence in deep waters. On the other hand, vertically-averaged ODZ area has a more complex, non-monotonic relationship with maximum remineralization rate. While these findings suggest an important role for remineralization in determining the shape of the ODZ in our model, the relative importance of remineralization vs. other physical parameterizations remains to be established. While our results reflect the structure of our ocean biogeochemical model, the relationship of remineralization to ODZ characteristics in other models should be examined to better inform model inter-comparisons.

Coupled global numerical climate models (GCMs) typically underestimate mean Antarctic sea ice area and extent, particularly during the austral summer months, contributing to uncertainties in climate prediction. This study examines the climatological behaviour of Antarctic sea ice in a coupled GCM in the multivariate sea ice model parameter space. Individual parameters dominate the ice response in different seasons and regions, with a compensatory effect in some parameter combinations and an amplified effect in others; however, certain parameter combinations are found to improve aspects of Antarctic sea ice climatology well beyond the limitations of a univariate approach. For example, the disparity between observed and simulated summer sea ice extent and area is halved, and the tendency towards very low-concentration ice (<15 %) reduced in favour of a more compact summer and autumn ice pack. Regardless, clear limitations in the extent to which a coupled GCM can be calibrated with sea-ice model parameters also emerge. Relatively unconsolidated winter ice cover persists and, in some experiments, becomes looser still, exacerbating the already overestimated maximum sea ice extent. Furthermore, the seasonal evolution of sea ice and the exaggerated asymmetry of the seasonal cycle, with the onset of ice advance too slow and maximum sea ice reached too late, sees negligible improvements. We note that, even with the large gains under certain parameter combinations, bias and other deficiencies still remain. Using coupled data assimilation to optimise parameters in both sea-ice and ocean models will likely assist in contributing to further model improvements.

The wave-generated turbulence dissipation term together with the improved post-breaking spectrum term proposed in this paper are incorporated in the MASNUM wave model as new dissipation terms. To compare the performance of these terms with the previous dissipation term in wave simulation, comprehensive validations of the simulated results were conducted against satellite data and NDBC buoy data on the significant wave heights. The results show that the incorporation of the wave-generated turbulence dissipation term with the improved post-breaking spectrum term significantly improves the model performance, the deviations are significantly reduced, and the correlation coefficients are effectively improved. In particular, there is a noticeable improvement in the simulation of significant wave heights exceeding 4 m or 6 m. In addition, a preliminary ideal experiment was conducted to compare the effect of the swell dissipation term proposed by Zieger et al. (2015) and the wave-generated turbulence dissipation term, and the results show that the dissipation magnitudes of the two terms are consistent to some extent.

The β-effect and mesoscale vorticity are considered the two important mechanisms guiding the downward propagation of near-inertial energy (NIE), while the influence of stratification is often neglected. In this study, the “heat pumping” and “cold suction” effects of Typhoon Kalmaegi on ocean stratification were analyzed. Enhanced stratification accelerated the vertical propagation of near-inertial waves (NIWs) from the mixed layer into the ocean interior along the left side of the typhoon track. To illustrate the impact of stratification changes on both sides of typhoon tracks, the Regional Ocean Modeling System was used to simulate the NIWs generated by Typhoon Kalmaegi in 2014. The results show that, despite higher wind energy input along the right side of the typhoon track, the NIE injection into the deep ocean along the left side was stronger owing to reduced dissipation and enhanced stratification. This study improves our understanding of the generation, propagation, and dissipation mechanisms of wind-induced NIWs during typhoons.

Ocean waves and sea ice properties are intimately linked in the marginal ice zone (MIZ), nevertheless a definitive modelling paradigm for the wave attenuation in the MIZ is missing. The evolution of wave directional properties in the MIZ is a proxy for the main attenuation mechanism but paucity of measurements and disagreement between them contributed to current uncertainty. Here we provide an analytical evidence that viscous attenuation tilts the mean wave direction orthogonal to the sea ice edge and the narrows directionality. Departure from this behaviour are attributed to bimodality of the spectrum. We also highlight the need for high quality directional measurements to reduce uncertainty in the definition of the attenuation rate.

To improve Arctic sea ice simulations by the First Institute of Oceanography–Earth System Model (FIO–ESM), the model version has been updated from FIO–ESM v2.0 to FIO–ESM v2.1 by upgrading its sea ice component from Los Alamos Sea–Ice Model (CICE) version 4.0 (CICE4.0) to CICE6.0, and improving the ice–ocean heat exchange process from a two–equation boundary condition parameterization to a more realistic three–equation boundary condition parameterization. Numerical experiments show that the underestimation of Arctic summer sea ice extent (SIE) in FIO–ESM v2.0 is significantly improved by the model enhancements. The root mean square error of the simulated Arctic September SIE during 1979–2014 is reduced from 2.9 million to 0.7 million km². Nevertheless, the biases of Antarctic SIE increase following the model version update. FIO–ESM v2.1 performs well for the simulations of surface air temperature, sea surface temperature, Atlantic Meridional Overturning Circulation, and Arctic SIE; however, it overestimates summer SIE in the Antarctic. Furthermore, future projections based on FIO–ESM v2.1 indicate that the first ice–free Arctic summer will occur in the 2050s and the 2040s under SSP2–4.5 and SSP5–8.5, respectively.