The model of tracing drift targets and its application in the South China Sea

A Leeway-Trace model was established for the traceability analysis of drifting objects at sea.The model was based on the Leeway model which is a Monte Carlo-based ensemble trajectory model,and a method of realistic traceability analysis was proposed in this study by using virtual spatiotemporal drift trajectory prediction.Here,measured data from a drifting buoy observation experiment in the northern South China Sea in April 2019,combined with surface current data obtained from the finite volume community ocean model(FVCOM),were used for the traceability analysis of humanoid buoys.The results were basically consistent with the observations,and the assimilation of measured current data can significantly improve the accuracy of the traceability analysis.Several sensitive experiments were designed to discuss the effects of wind and tide on the traceability analysis,and their results showed that the wind-driven current and the wind-induced leeway drift are both important to the traceability analysis.The effect of tidal currents on traceability could not be ignored even though they were much weaker than the residual currents in the experimental area of the northern South China Sea.

High-resolution simulation of upper-ocean submesoscale variability in the South China Sea:Spatial and seasonal dynamical regimes

Submesoscale processes in marginal seas usually have complex generating mechanisms,highly dependent on the local background flow and forcing.This numerical study investigates the spatial and seasonal differences of submesoscale activities in the upper ocean of the South China Sea(SCS)and the different dynamical regimes for sub-regions.The spatial and seasonal variations of vertical vorticity,horizontal convergence,lateral buoyancy gradient,and strain rate are analyzed to compare the submesoscale phenomenon within four sub-regions,the northern region near the Luzon Strait(R1),the middle ocean basin(R2),the western SCS(R3),and the southern SCS(R4).The results suggest that the SCS submesoscale processes are highly heterogeneous in space,with different seasonalities in each sub-region.The submesoscale activities in the northern sub-regions(R1,R2)are active in winter but weak in summer,while there appears an almost seasonal anti-phase in the western region(R3)compared to R1 and R2.Interestingly,no clear seasonality of submesoscale features is shown in the southern region(R4).Further analysis of Ertel potential vorticity reveals different generating mechanisms of submesoscale processes in different sub-regions.Correlation analyses also show the vertical extent of vertical velocity and the role of monsoon in generating submesoscale activities in the upper ocean of sub-regions.All these results suggest that the sub-regions have different regimes for submesoscale processes,e.g.,Kuroshio intrusion(R1),monsoon modulation(R2),frontal effects(R3),topography wakes(R4).

Assessment of theoretical approaches to derivation of internal solitary wave parameters from multi-satellite images near the Dongsha Atoll of the South China Sea

This study assesses the accuracy and the applicability of the Korteweg-de Vries(KdV)and the nonlinear Schr?dinger(NLS)equation solutions to derivation of dynamic parameters of internal solitary waves(ISWs)from satellite images.Visible band images taken by five satellite sensors with spatial resolutions from 5 m to 250 m near the Dongsha Atoll of the northern South China Sea(NSCS)are used as a baseline.From the baseline,the amplitudes of ISWs occurring from July 10 to 13,2017 are estimated by the two approaches and compared with concurrent mooring observations for assessments.Using the ratio of the dimensionless dispersive parameter to the square of dimensionless nonlinear parameter as a criterion,the best appliable ranges of the two approaches are clearly separated.The statistics of total 18 cases indicate that in each 50%of cases,the KdV and the NLS approaches give more accurate estimates of ISW amplitudes.It is found that the relative errors of ISW amplitudes derived from two theoretical approaches are closely associated with the logarithmic bottom slopes.This may be attributed to the nonlinear growth of ISW amplitudes as propagating along a shoaling thermocline or topography.The test results using three consecutive satellite images to retrieve the ISW propagation speeds indicate that the use of multiple satellite images(>2)may improve the accuracy of retrieved phase speeds.Meanwhile,repeated multi-satellite images of ISWs can help to determine the types of ISWs if mooring data are available nearby.

A two-stage inflation method in parameter estimation to compensate for constant parameter evolution in Community Earth System Model

Parameter estimation is defined as the process to adjust or optimize the model parameter using observations.A long-term problem in ensemble-based parameter estimation methods is that the parameters are assumed to be constant during model integration.This assumption will cause underestimation of parameter ensemble spread,such that the parameter ensemble tends to collapse before an optimal solution is found.In this work,a two-stage inflation method is developed for parameter estimation,which can address the collapse of parameter ensemble due to the constant evolution of parameters.In the first stage,adaptive inflation is applied to the augmented states,in which the global scalar parameter is transformed to fields with spatial dependence.In the second stage,extra multiplicative inflation is used to inflate the scalar parameter ensemble to compensate for constant parameter evolution,where the inflation factor is determined according to the spread growth ratio of model states.The observation system simulation experiment with Community Earth System Model(CESM)shows that the second stage of the inflation scheme plays a crucial role in successful parameter estimation.With proper multiplicative inflation factors,the parameter estimation can effectively reduce the parameter biases,providing more accurate analyses.

Identifying the sensitive areas in targeted observation for predicting the Kuroshio large meander path in a regional ocean model

With the Regional Ocean Modeling System(ROMS),this paper investigates the sensitive areas in targeted observation for predicting the Kuroshio large meander(LM)path using the conditional nonlinear optimal perturbation approach.To identify the sensitive areas,the optimal initial errors(OIEs)featuring the largest nonlinear evolution in the LM prediction are first calculated;the resulting OIEs are localized mainly in the upper 2500 m over the LM upstream region,and their spatial structure has certain similarities with that of the optimal triggering perturbation.Based on this spatial structure,the sensitive areas are successfully identified,located southeast of Kyushu in the region(29°–32°N,131°–134°E).A series of sensitivity experiments indicate that both the positions and the spatial structure of initial errors have important effects on the LM prediction,verifying the validity of the sensitive areas.Then,the effect of targeted observation in the sensitive areas is evaluated through observing system simulation experiments.When targeted observation is implemented in the identified sensitive areas,the prediction errors are effectively reduced,and the prediction skill of the LM event is improved significantly.This provides scientific guidance for ocean observations related to enhancing the prediction skill of the LM event.