Ocean Modelling最新文献

The critical level instability mechanism for the generation of water waves by wind is re-examined for the situation when the atmosphere is density stratified. The density stratification is confined to the middle and upper atmosphere and then two cases are investigated. In case (A) no internal gravity waves are generated in the upper atmosphere and the effect of the density stratification is very small. In case (B) vertically propagating internal gravity waves form in the upper atmosphere and travel to infinity causing an energy loss, thus inhibiting the critical level instability in the lower atmosphere. Both cases are examined quantitatively for a logarithmic wind shear profile.

Correctly estimating the wind stress at the sea surface is of the utmost importance in models for climate studies, weather forecasting, and ocean–atmosphere interaction. The wind stress is mainly obtained by drag coefficient parameterizations, which always consider the wind stress to be aligned with the wind, but this is sometimes the case. Also, during moderate to weak wind conditions, these parameterizations may lead to high estimation errors due to the presence of swell. This study measured the wind stress with a high-rate (100 Hz) sonic anemometer mounted on a spar buoy. The sea state was also characterized by obtaining the directional spectrum of the waves by six wave-staff arrays sensing the free surface level at 10 Hz. Bouy’s movement was corrected by employing an inertial motion unit. The turbulent and wave-coherent wind stress components were also estimated and analyzed. It was observed that during swell conditions with wind traveling in the same direction, the wave-coherent wind stress component has an opposite direction to the wind and dampens the total wind stress magnitude. During counter-directional wind relative to swell events, the wave boundary layer is modified; swell produces a wave-coherent wind stress in the same direction as the wind, resulting in an enhanced total wind stress magnitude. The wave age, significant wave height, and the traveling direction of the swell relative to the wind are essential to correctly estimating the wind stress in swell-dominant conditions. A set of empirical parameterizations for each wind stress component is proposed.

We investigate the impact of ocean data assimilation using the Ensemble Adjustment Kalman Filter (EAKF) from the Data Assimilation Research Testbed (DART) on the oceanic and atmospheric states of the Red Sea. Our study extends the ocean data assimilation experiment performed by Sanikommu et al. (2020) by utilizing the SKRIPS model coupling the MITgcm ocean model and the Weather Research and Forecasting (WRF) atmosphere model. Using a 50-member ensemble, we assimilate satellite-derived sea surface temperature and height and in situ temperature and salinity profiles every three days for one year, starting January 01 2011. Atmospheric data are not assimilated in the experiments. To improve the ensemble realism, perturbations are added to the WRF model using several physics options and the stochastic kinetic energy backscatter (SKEB) scheme. Compared with the control experiments using uncoupled MITgcm with ECMWF ensemble forcing, the EAKF ensemble mean oceanic states from the coupled model are better or insignificantly worse (root-mean-square errors are 23% to −1.3% smaller), especially when the atmospheric model uncertainties are accounted for with stochastic perturbations. We hypothesize that the ensemble spreads of the air–sea fluxes are better represented in the downscaled WRF ensembles when uncertainties are well accounted for, leading to improved representation of the ensemble oceanic states from the new experiments with the coupled model. This indicates the ocean model assimilation will be improved with coupled models and may relax the need for operational centers to provide atmospheric ensembles to drive ocean forecasts. Although the feedback from ocean to atmosphere is included in this two-way regional coupled configuration, we find no significant effect of ocean data assimilation on the ensemble mean latent heat flux and 10-m wind speed over the Red Sea. This suggests that the improved skill using the coupled model is not from the two-way coupling, but from downscaling the ensemble atmospheric forcings (one-way coupled) to drive the ocean model.

The drag coefficient is a vital quantitative indicator within the field of wave attenuation by vegetation, thus receiving considerable critical attention. A systematic understanding of the drag coefficient under single flexible vegetation dynamic and emergent conditions is still insufficient. The present study aimed to quantitatively investigate the drag coefficient of emergent flexible vegetation based on a flume experiment and an emergent flexible vegetation dynamic model. Simulation results demonstrated the acceptability of constant skin friction coefficient and added mass coefficient in simulating the vegetation dynamics and determining the drag coefficient. Based on the calibration method, the obtained drag coefficients are more influenced by the Reynolds number, the Cauchy number, and the drag-to-stiffness ratio under the present investigation conditions. Vegetation flexibility can have evident influences on the drag coefficient of emergent flexible vegetation under waves. Then, a new empirical formula including the drag-to-stiffness ratio and relative vegetation length was proposed to estimate the drag coefficient. The effectiveness of the formula was demonstrated after evaluating the performance in both calculating the drag coefficient and simulating the emergent flexible vegetation dynamics. This study also provided evidence for the uncertainty in the formula establishment, and identified the uncertainty that different determination methods of characteristic wave velocity and utilizations of wave theory can lead to in the formula establishment. The findings can contribute to the understanding of the drag coefficient of emergent flexible vegetation, and highlight the potential usefulness of other parameters associated with vegetation flexibility in drag coefficient prediction.

Following the Dirichlet-type boundary condition that specifies value at boundary of a system in mathematics and physics, this study suggests applying satellite sea surface temperature (SST) as Dirichlet-type surface thermal boundary condition (STBC) in ocean models. Numerical experiments with Dirichlet-type and Combined-type STBC with different configurations of satellite SST, for the period of January to April 2019 in the Northwest Pacific Ocean, were carried out based on the Princeton Ocean Model. The experiments were assessed using satellite and in situ observations of temperature, GOFS3.1 analysis and GLORYS12v1 reanalysis. Results show that applying satellite SST as Dirichlet-type STBC could constrain the modeled SST and near-surface temperature in upper 50 m depth well, which is better than the scheme that uses satellite SST as the relaxation terms of Combined-type STBC. The temperature section along the 137°E resulted from the Dirichlet-type STBC is comparable with GOFS3.1 analysis and better than GLORYS12v1 reanalysis in upper 50 m depth. These results suggest that applying high-accuracy satellite SST as Dirichlet-type STBC in ocean models has a promising prospect in numerical simulation.

An atmosphere-ocean biogeochemistry coupled model is configured, customised and validated to decipher the role of atmospheric and oceanic processes in the north Indian Ocean (NIO, 3–30° N, 40–100° E), Arabian Sea (AS, 4–25° N, 50–75° E) and Bay of Bengal (BoB, 4–25° N, 76–100° E). The validation of model results with measurements shows that Sea Surface Temperature is better simulated by the coupled model than the standalone ocean model, with an average bias of ±0.2 °C in NIO. The simulated Sea Surface Salinity has a smaller bias with respect to reanalysis in AS (0.2 psu), but slightly higher in BoB (0.5 psu). The vertical distribution of temperature and salinity is also better represented in the coupled model. The atmospheric forcing, such as Long Wave Radiation, wind stress, and net surface heat and salt fluxes are better simulated by the coupled model with comparable variability and seasonality to the reanalysis data. The winter and summer Chlorophyll-a (Chl-a) blooms in AS are also well reproduced by the coupled model. The model also well simulates NO₃ within top 100 m in AS and BoB. The nitrate budget analysis indicates that vertical advection and entrainment play big roles in governing the overall budget in upwelling regions of NIO. Nitrate uptake by phytoplankton is the dominant biological process, except in the northern AS, where denitrification is dominant. New production contributes to Net Primary Productivity (NPP) in most upwelling regions in AS except in the northern AS, where regenerated production is higher than the new production. In BoB, the regenerated production dominates except in East Coast of India during monsoon season. Therefore, our study provides new insights on the capability of the coupled ocean-atmosphere models in simulating the physical and biogeochemical processes, and air-sea interactions in NIO.

Knowledge about statistics for water level variations along the coast due to storm surge is important for the utilization of the coastal zone. An open and freely available storm surge hindcast archive covering the coast of Norway and adjacent sea areas spanning the time period 1979–2022 is presented. The storm surge model is forced by wind stress and mean sea level pressure taken from the non-hydrostatic NORA3 atmospheric hindcast. A dataset consisting of observations of water level from more than 90 water level gauges along the coasts of the North Sea and the Norwegian Sea is compiled and quality controlled, and used to assess the performance of the hindcast. The observational dataset is distributed in both time and space, and when considering all the available quality controlled data, the comparison with modeled water levels yield a mean absolute error (MAE) of 9.7 cm and a root mean square error (RMSE) of 12.4 cm. Values for MAE and RMSE scaled by the standard deviation of the observed storm surge for each station are 0.42 and 0.54 standard deviations, respectively. When considering the geographical differences in characteristics of storm surge for different countries/regions, the values of MAE and RMSE are in the range $5.7$–$13.9$ cm and $7.6$–$17.8$ cm respectively, and $0.33$–$0.46$ and $0.42$–$0.59$ standard deviations for the scaled values. The minimum and maximum values for water level in the hindcast are $-2.60$ m and 3.92 m. In addition, 100-year return level estimates are calculated from the hindcast, with minimum and maximum values of, respectively, $-2.75$ m and 3.98 m. All minimum and maximum values are found in the southern North Sea area.

Transport assessments near the coast are often related to particles drifting near the surface. Such “particles” may be salmon lice, cod eggs, macro plastics or ship debris. Their drift depends on the Eulerian currents and the Stokes drift associated with the wind-generated surface wave field. The Stokes drift must be parameterized, and in doing so, one will inevitably make bulk estimates of the direction and speed of the drift for the wave spectrum. This paper implements a recently proposed parameterization of the Stokes drift vertical profile, which accounts for the effect of swell and windsea that propagate in different directions, to the open-source Lagrangian particle tracking model OpenDrift. We investigate how particles drifting in the Lofoten archipelago in Northern Norway depend on the Stokes drift and how we parameterize it. The parameterization accounting for crossing windsea and swell leads to lower residence time near the coastline than other popular parameterizations in the domain we studied.

Islands, acting as transitional areas between land and sea, significantly influence their surrounding environments. Studying the changes in vortex structure resulting from the interaction between islands and mesoscale vortices is crucial for understanding the dynamic characteristics and ecological processes of the marine environment. Previous theoretical studies have shown that in a domain without boundaries, due to the conservation of angular momentum, a vortex cannot split by itself. This paper establishes the conditions for the splitting of an anticyclonic vortex when it collides with two square islands. By linking the initial and final states of islands effect on the vortex and utilizing conserved quantities such as angular momentum and mass, along with the slow variation approximation, a nonlinear theoretical solution is constructed. The analysis shows that when the interaction between the vortex and the two islands leads to vortex splitting, the length of the islands, the vortex radius, and the distance between the islands must satisfy a certain condition $O\left(\frac{L}{R}\right)$∼$O\left(\frac{w}{R}\right)$∼$O\left(1\right)$. These results provide support for subsequent analyses of the impact of various parameters on vortex structure when the North Brazil Current (NBC) ring encounters the Lesser Antilles in the tropical western Atlantic.

The seasonal variation of intermediate meridional overturning circulation (IMOC) in the South China Sea (SCS) is investigated using the Simple Ocean Data Assimilation version 2.2.4 (SODA2.2.4) product for the period of 1950–2010. The SCS IMOC displays distinct seasonal features, with a counterclockwise cell dominating the interior SCS (12∼18°N, 200∼700 m) in winter and a broader clockwise cell occupying the region for (7∼20°N, 50∼900 m) in summer. By removing the 12-month average, the main characteristics of the seasonal IMOC is captured deeply. There is a counterclockwise anomaly in winter and a clockwise anomaly in summer occurring in the region for (8∼20°N, 100∼1000 m). And the strongest anomalies of the overturning stream functions are mainly located in (12∼17°N, 200∼400 m) that is taken as the representative region to study the seasonal IMOC. A dynamical decomposition of the IMOC seasonal anomaly allows a further look into the seasonal variation of the SCS IMOC. The IMOC seasonal anomaly is decomposed into three components: the Ekman component, the vertical shear component, and the external component. The Ekman component exhibits a full cell clockwise in winter and counterclockwise in summer with a negative contribution to the IMOC anomaly. The vertical shear component has a strong cell counterclockwise in winter and clockwise in summer occupying most of the areas above 1000 m with a positive contribution to the IMOC anomaly. The external component has a relatively complex structure, and its positive and negative contributions to the IMOC anomaly alternate with increasing latitude at 200∼1000 m. According to the seasonal fractional covariance of these three components on the IMOC anomaly in the representative region, the vertical shear component and the Ekman component have the main contributions to the IMOC seasonal anomaly, and the external component has a limited impact. The vertical shear and its meridional difference can lead to a downward motion at around 12°N and an upward motion at around 17°N in winter, and reverse motions in summer. The seasonal vertical motions will cause an overturning counterclockwise in winter and clockwise in summer. The Ekman component is mainly driven by the monsoon over the SCS that generates the Ekman transport northward in winter and southward in summer. The seasonal Ekman transport and its return flow together form an overturning clockwise in winter and counterclockwise in summer. And the external component counterclockwise in winter and clockwise in summer between 14°N and 17°N is associated with the horizontal flow northeastward in winter and southwestward in summer zonally going over shallower or greater depths, which can induce seasonal reverse upwelling and downwelling at different latitudes.