首页> 外文期刊>Journal of Marine Environmental Engineering >A Hierarchy of Stochastic Particle Models for Search and Rescue (SAR): Application to Predict Surface Drifter Trajectories Using HF Radar Current Forcing
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A Hierarchy of Stochastic Particle Models for Search and Rescue (SAR): Application to Predict Surface Drifter Trajectories Using HF Radar Current Forcing

机译:搜索和救援(SAR)随机粒子模型的层次结构:在使用HF雷达电流强迫预测表面漂移轨迹的应用

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A hierarchy of stochastic particle models, where the object's position, velocity, and acceleration are progressively represented as Markovian processes, is summarized. Numerical implementation and testing of the first and second order models (random walk and random flight) against an analytic solution to the diffusion equation show very good agreement provided that 2000 or more independent simulations are ensemble averaged. The random flight model is shown to predict smaller search areas than the random walk model, with a long term reduction in the area proportional to the dispersion coefficient times the velocity autocorrelation time scale. This offset ramps in immediately after the release, and occurs over the velocity autocorrelation time scale. The particle models were applied to predict the trajectories of seven US Coast Guard, Self Locating Datum Marker Buoys (SLDMB) Argos tracked drifters (Davis like) deployed in three clusters: one located in western Block Island Sound and the other two, near the coast and shelf break in the New York Bight. The buoys were deployed for a 35-day period starting on July 27, 2004. High frequency coastal radar (CODAR) measurements were collected during the same time period by a short range system (50 km range and 5 km resolution) operated by the Universities of Rl and Connecticut for the Block Island Sound and adjacent shelf area and by the long range system (150 km range, 6 km resolution) operated by Rutgers University for the Mid Atlantic Bight. The motion of the buoys was dominated by a mean southwesterly shelf transport and inertial and semi-diurnal tidal oscillations. A cluster analysis of the very limited number of SLDMBs gives dispersion coefficients in the range of 40 to 80 m~2/sec. Analysis of the CODAR velocity errors and variances gives values in the range of 40 to 700 mVsec, with velocity autocorrelation time scales in the range of 4 to 7 hours, depending on the velocity component, the location, and whether the current record used to determine the autocorrelation time scale is de-tided. Comparison of the velocities derived from the drifters and the radar system show differences comparable to the observed speeds. Scatter plots for the Block Island Sound (Mid Atlantic Bight) show a correlation of less than 0.1 (greater than 0.75) for the east-west component and greater than 0.6 (less than 0.4) for the north-south component. Correlation coefficients were observed to be much lower in areas where the percent data return was below 50%. Statistically independent simulations were performed using SARMAP, a search and rescue model, to predict the daylong trajectories at successive (non-overlapping) locations along the paths of the seven SLDMBs in the Mid Atlantic Bight.
机译:总结了随机粒子模型的层次结构,其中对象的位置,速度和加速度逐渐表示为马尔可夫过程。一阶和二阶模型(随机游走和随机飞行)的数值实现和针对扩散方程的解析解的测试显示出很好的一致性,只要对2000个或更多独立模拟进行综合平均即可。与随机游走模型相比,随机飞行模型可预测更小的搜索区域,并且与色散系数乘以速度自相关时标成比例的区域会长期减少。该偏移在释放后立即增加,并在速度自相关时间范围内发生。粒子模型被用于预测七个美国海岸警卫队,自定位基准标记浮标(SLDMB)的Argos追踪漂流者(像戴维斯一样)分布在三个集群中的轨迹:一个位于Block Island Sound西部,另外两个位于海岸附近和纽约货架上的货架中断。从2004年7月27日开始,浮标部署了35天。在同一时期,大学使用的短距离系统(50 km范围和5 km分辨率)收集了高频沿海雷达(CODAR)测量值。 Rl和康涅狄格州针对Block Island Sound和邻近的陆架区域,并采用罗格斯大学中大西洋大西洋分校的远程系统(150公里范围,分辨率为6 km)。浮标的运动主要由西南向平均陆架运移以及惯性和半日潮汐振荡决定。对数量非常有限的SLDMB进行聚类分析得出的分散系数在40至80 m〜2 / sec的范围内。对CODAR速度误差和方差的分析得出的值在40到700 mVsec的范围内,速度自相关时间标度在4到7小时的范围内,具体取决于速度分量,位置以及当前记录是否用于确定自相关时间刻度被取消。从漂移器和雷达系统得出的速度的比较显示出与观察到的速度相当的差异。布洛克岛声音(中大西洋大西洋)的散点图显示,东西方向的相关性小于0.1(大于0.75),而南北方向的相关性大于0.6(小于0.4)。在数据返回百分比低于50%的区域中,观察到相关系数要低得多。使用搜寻和救援模型SARMAP进行统计上独立的模拟,以预测沿大西洋中部大西洋中7个SLDMB路径的连续(不重叠)位置的整日轨迹。

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