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首页> 外文期刊>Journal of Geophysical Research, C. Oceans: JGR >Trajectory prediction using HF radar surface currents: Monte Carlo simulations of prediction uncertainties
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Trajectory prediction using HF radar surface currents: Monte Carlo simulations of prediction uncertainties

机译:使用HF雷达表面电流的轨迹预测:预测不确定性的蒙特卡洛模拟

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An important aspect of particle trajectory modeling in the ocean is the assessment of the uncertainty in the final particle position. Monte Carlo particle trajectory simulations using surface currents derived from standard-range and long-range CODAR HF radar systems were performed using random-walk and random-flight models of the unresolved velocities. Velocity statistics for these models were derived from the covariance functions of differences between CODAR and drifter estimates of surface currents. Comparison of predicted trajectories and drifter tracks demonstrate that these predictions are superior to assuming the drifters stay at their initial position. Vertical shear between the effective depth of long-range CODAR measurements (~2.4 m) and that of drifters (0.65 m) causes the drifters to move more rapidly downwind than predicted. This bias is absent when standard-range CODAR currents (effective depth ~0.5 m) are used, implying that drifter leeway is not the cause of the bias. Particle trajectories were computed using CODAR data and the random-flight model for 24-hour intervals using a Monte Carlo approach to determine the 95% confidence interval of position predictions. Between 80% and 90% of real drifters were located within the predicted confidence interval, in reasonable agreement with the expected 95% success rate. In contrast, predictions using the random-walk approach proved inconsistent with observations unless the diffusion coefficient was increased to approximately the random-flight value. The consistency of the random-flight uncertainty estimates and drifter data supports the use of our methodology for estimating model parameters from drifter-CODAR velocity differences.
机译:海洋中粒子轨迹建模的一个重要方面是评估最终粒子位置的不确定性。使用来自未解决速度的随机游走和随机飞行模型,执行了使用从标准范围和远程CODAR HF雷达系统获得的表面电流进行的蒙特卡洛粒子轨迹模拟。这些模型的速度统计数据是从CODAR和表面电流的漂移估计之间的协方差函数得出的。预测轨迹和漂移轨迹的比较表明,这些预测优于假设漂移停留在其初始位置。远程CODAR测量的有效深度(〜2.4 m)与浮子的有效深度(0.65 m)之间的垂直剪切力使浮子在下风处的移动速度比预期的快。当使用标准范围的CODAR电流(有效深度〜0.5 m)时,不存在这种偏差,这表明漂移并不是导致偏差的原因。使用CODAR数据和24小时间隔的随机飞行模型使用Monte Carlo方法计算粒子轨迹,以确定位置预测的95%置信区间。 80%至90%的真实流浪者位于预期的置信区间内,与95%的预期成功率在合理范围内一致。相反,除非扩散系数增加到近似随机飞行值,否则使用随机游走方法进行的预测与观察结果不一致。随机飞行不确定性估计值和漂移数据的一致性支持使用我们的方法从漂移器CODAR速度差异估计模型参数的方法。

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