Mesoscale oceanic eddies in the South China Sea from 1992 to 2012:evolution processes and statistical analysis

Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea（SCS）. However, very few studies attempt to examine eddies＇ internal evolution processes. In this study, we reported a hybrid method to trace eddies＇ propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies（DCEs） and the three long-lived anticyclonic eddies（ACEs） in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters.

Real-time dynamic system to path tracking and collision avoidance for redundant robotic arms

An dynamic system for real-time obstacle avoidance path planning of redundant robots is constructed in this paper. Firstly, the inter-frame difference method is used to identify the moving target and to calculate the target area, then on the basis of color features and gradient features extracted from the target area, the feature fusion Cam-Shift mean shift algorithm is used to track target, improving the robustness of the tracking algorithm. Secondly, a parallel two-channel target identification and location method based on binocular vision is proposed, updating the target＇s three-dimensional information in real time. Then, a dynamic collision-free path planning method is implemented： the safety rods are removed through the intersection test, and the minimum distance is derived directly by using the coordinate values of the target in the local coordinate system of the rod. On this basis, the obstacle avoidance gain and escape velocity related to the minimum distance is established, and obstacle avoidance path planning is implemented by using the zero space mapping matrix of redundant robot. Experiments are performed to Study the efficiency of the proposed system.

Oceanic mesoscale eddy in the Kuroshio extension:Comparison of four datasets

Some relatively mature mesoscale eddy products have been released for scientific purposes in recent decades.However,the metrics used to identify eddies,the tracking methods,and the definition of the physical parameters are all different across the different datasets,so intercomparisons and validation of these datasets are badly needed.Here,the authors intercompare the basic features of ocean mesoscale eddies in the Kuroshio extension region from four eddy datasets—namely,Chelton,GEM-M,Faghmous,and Dong.In the case study,eddy numbers and locations as well as the eddy tracks identified by the four datasets are compared for a specific date.The authors find that all the datasets have different eddy numbers,but more than 50%of identified eddies coincide.GEM-M,with the so-called"segmentation"algorithm,can identify considerably more eddies than others,while Chelton identifies fewer eddies due to tracking errors,which also lead to a long lifespan.From the analysis of the probability distribution function of eddy features,GEM-M eddies tend to have a larger amplitude and radius and Chelton tends to have long-life eddies.It is further found that the geographic distributions and temporal variation of normalized eddy features are highly similar among the four datasets—particularly among Chelton,Fahgmous,and Dong.In addition,the mean trajectories of the four datasets are generally overlapped initially,and then spread after 245 days.The findings help toward better understanding the uncertainties of eddy features in the Kuroshio extension region.

EXPERIMENTS TO TRACK STORMS USING MODERN OPTIMIZATION ALGORITHMS

Storm identification and tracking based on weather radar data are essential to nowcasting and severe weather warning. A new two-dimensional storm identification method simultaneously seeking in two directions is proposed, and identification results are used to discuss storm tracking algorithms. Three modern optimization algorithms （simulated annealing algorithm, genetic algorithm and ant colony algorithm） are tested to match storms in successive time intervals. Preliminary results indicate that the simulated annealing algorithm and ant colony algorithm are effective and have intuitionally adjustable parameters, whereas the genetic algorithm is unsatisfaetorily constrained by the mode of genetic operations Experiments provide not only the feasibility and characteristics of storm tracking with modern optimization algorithms, but also references for studies and applications in relevant fields.