Assimilation of HF radar-derived surface currents on tidal-timescales

A surface current observation system based on high-frequency (HF) radar has been developed for Raritan Bay and the coastal waters of New York and New Jersey. An HF radar network provides synoptic surface current maps in near-real-time that can be optimally combined with ocean circulation models using data assimilation (DA) framework to obtain the best possible estimate of a three-dimensional ocean state. A nudging or Newtonian damping scheme has been developed to assimilate HF radar data into an estuarine and coastal ocean circulation model. This model, with an extensive embedded real-time observational network, is called the New York Harbour Observing and Prediction System (NYHOPS). A nudging parameter is introduced into the equations of motion which affects the model dynamics. The data is imparted to neighbouring (three-dimensional) grid points via model dynamics. The impact of HF radar DA is analysed by computing the DA skill score (DAskill) based on the mean-square-error (mse). The DAskill is computed by comparing non-assimilated and assimilated model solutions with in-situ observations of three-dimensional currents, temperature and salinity, which have not been included in the assimilation. A positive DAskill (0∼1) represents an improvement in the model performance by assimilation. HF radar data covering Raritan Bay and the New York Bight (NYB) Apex were assimilated into the NYHOPS model in the model hindcast cycle (–24h to 0h) on a daily forecast basis for a period of 40 days. The DAskill is assessed with respect to the NYHOPS model hindcasts (daily model solutions from –24h to 0h) as well as the first day forecasts (daily model solutions from 0h to 24h). HF radar DA improved the NYHOPS model performance during both the hindcast and forecast periods. The model skill metrics for the near-surface layers in the inner-NJ shelf region shows a hindcast DAskill of 24% (14%) and forecast DAskill of 18% (7%) for horizontal velocities u: east-west component (v: north-south component), and a hindcast DAskill of 33% (38%) and forecast DAskill of 25% (30%) for temperature (salinity). The nudging scheme is robust and efficient for the HF radar DA into the NYHOPS operational forecast model. The NYHOPS-HF radar DA system is capable of importing in the observations and produce useful hindcasts/forecasts with minimum computational expense.

基于高频（HF）雷达的表面观察系统已为Raritan湾和纽约和新泽西州的沿海水域开发出来。使用数据同化（DA）框架的海洋循环模型，以获得三维海洋状态的最佳估计具有广泛的实时观察网络的模型称为纽约港观察和预测系统（NYHOPS）。通过模型动力学的网格点，通过基于平均值 - eRROR（MSE）计算DA技能得分（DASKILL）的影响。三维电流，温度和盐度的原位观测，这些溶液尚未包括在同化中。在每天的预测基础上，纽约野合（NYB）的顶点在模型后播（–24h至0h）中被纳入NYHOPS模型，为40天。型号从–24h到0H）以及第一天的森林（每日模型解决方案从0h到24h）。内部NJ货架区域中的层显示了后播Daskill的24％（​​14％），预测Daskill为18％（7％）的水平速度U：东西方组件（V：North-South组件）和后广播33％（38％）的Daskill（38％）的Daskill为25％（30％）（盐度）。能够在观测值中进口并产生最低计算费用的有用的后广播/预测。