挪威海和北海搜救业务模式
An Operational Search and Rescue Model for the Norwegian Sea and the North Sea
摘要：
介绍了一种新的适用于挪威海和北海的基于集合的搜索和救援模式。随机轨迹模型计算一系列搜索和救援对象的净运动。一个新的，强大的制定之间的关系的风和漂移对象的运动（称为对象的偏航）。由美国海岸警卫队编制的63类搜索对象的经验推导的系数被摄取，以估计漂流物体的回旋余地。一个蒙特卡洛技术是用来产生一个合奏，占强迫场（风和电流）的不确定性，偏航漂移特性，和搜索对象的初始位置。集合产生搜索对象的位置的时间演化概率密度函数的估计，并且其包络定义搜索区域。强迫场的业务海洋和大气预报系统的挪威气象研究所被用作输入的轨迹模型。这使得高分辨率的风场和海流场首次被用于预测未来60小时内的搜索区域。一组有限的现场演习显示模型轨迹，搜索区域，救生筏和其他搜索对象的观察轨迹之间的良好协议。与旧方法的比较表明，搜索区域扩展慢得多，使用新的集成方法与高分辨率的强迫场和新的leeway制定。结果发现，高阶随机轨道模型不会显着提高预测技能和搜索区域的扩展速度。
英文摘要：
A new operational, ensemble-based search and rescue model for the Norwegian Sea and the North Sea is presented. The stochastic trajectory model computes the net motion of a range of search and rescue objects. A new, robust formulation for the relation between the wind and the motion of the drifting object (termed the leeway of the object) is employed. Empirically derived coefficients for 63 categories of search objects compiled by the US Coast Guard are ingested to estimate the leeway of the drifting objects. A Monte Carlo technique is employed to generate an ensemble that accounts for the uncertainties in forcing fields (wind and current), leeway drift properties, and the initial position of the search object. The ensemble yields an estimate of the time-evolving probability density function of the location of the search object, and its envelope defines the search area. Forcing fields from the operational oceanic and atmospheric forecast system of The Norwegian Meteorological Institute are used as input to the trajectory model. This allows for the first time high-resolution wind and current fields to be used to forecast search areas up to 60 hours into the future. A limited set of field exercises show good agreement between model trajectories, search areas, and observed trajectories for liferafts and other search objects. Comparison with older methods shows that search areas expand much more slowly using the new ensemble method with high resolution forcing fields and the new leeway formulation. It is found that going to higher-order stochastic trajectory models will not significantly improve the forecast skill and the rate of expansion of search areas.
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