Uncertainty Estimates for SeaSonde HF Radar Ocean Current Observations
Uncertainty Estimates for SeaSonde HF Radar Ocean Current Observations
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DOI：
10.1175/jtech-d-18-0104.1
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发表时间：
2019-02
影响因子：
2.2
通讯作者：
B. Emery;L. Washburn
中科院分区：
文献类型：
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作者：
B. Emery;L. Washburn
高频雷达通常产生表面流速图，而不估计测量的不确定性。高频雷达数据的许多用户，包括溢漏反应和搜索救援行动，将这些观测结果纳入模型，因此将受益于量化的不确定性。使用两个操作SeaSonde HF雷达之间的基线的模拟和重合的观测，我们证明了多信号分类（MUSIC）算法获得的方向估计的不确定性的表达式的效用。利用区域海洋模拟系统的表面海流模拟雷达后向散射显示，波达方向误差与估计的不确定性之间有着密切的对应关系，10分贝时的平均值为15°，30分贝时则降至3°以下。来自两个运行中的海洋探空仪的观测结果的平均方位不确定度为2.7°和3.8°，其中一小部分观测结果（分别为10.5%和7.1%）的不确定度大于10°。使用DOA不确定性进行数据质量控制，改善了两个雷达之间的时间序列比较统计，r2=0.6增加到r2=0.75，RMS差从15 cm s-1减少到12 cm s-1。分析说明了海洋高频雷达误差的主要来源，并建议波达方向的不确定性是适合同化到数值模式。
HF radars typically produce maps of surface current velocities without estimates of the measurement uncertainties. Many users of HF radar data, including spill response and search and rescue operations, incorporate these observations into models and would thus benefit from quantified uncertainties. Using both simulations and coincident observations from the baseline between two operational SeaSonde HF radars, we demonstrate the utility of expressions for estimating the uncertainty in the direction obtained with the Multiple Signal Classification (MUSIC) algorithm. Simulations of radar backscatter using surface currents from the Regional Ocean Modeling System show a close correspondence between direction of arrival (DOA) errors and estimated uncertainties, with mean values of 15° at 10 dB, falling to less than 3° at 30 dB. Observations from two operational SeaSondes have average DOA uncertainties of 2.7° and 3.8°, with a fraction of the observations (10.5% and 7.1%, respectively) having uncertainties of >10°. Using DOA uncertainties for data quality control improves time series comparison statistics between the two radars, with r2=0.6 increasing to r2=0.75 and RMS difference decreasing from 15 to 12 cm s−1. The analysis illustrates the major sources of error in oceanographic HF radars and suggests that the DOA uncertainties are suitable for assimilation into numerical models.