Variational interpolation of high-frequency radar surface currents using DIVAnd

Ocean Dynamics - DIVAnd (Data-Interpolating Variational Analysis, in n-dimensions) is a tool to interpolate observations on a regular grid using the variational inverse method. We have extended...     

Assessing the fidelity of surface currents from a coastal ocean model and HF radar using drifting buoys in the Middle Atlantic Bight

The rapid expansion of urbanization along the world’s coastal areas requires a more comprehensive and accurate understanding of the coastal ocean. Over the past several decades, numerical ocean circulation models have tried to provide such insight, based on our developing understanding of physical ocean processes. The systematic establishment of coastal ocean observation systems adopting cutting-edge technology, such as high frequency (HF) radar, satellite sensing, and gliders, has put such ocean model predictions to the test, by providing comprehensive observational datasets for the validation of numerical model forecasts. The New York Harbor Observing and Prediction System (NYHOPS) is a comprehensive system for understanding coastal ocean processes on the continental shelf waters of New York and New Jersey. To increase confidence in the system’s ocean circulation predictions in that area, a detailed validation exercise was carried out using HF radar and Lagrangian drifter-derived surface currents from three drifters obtained between March and October 2010. During that period, the root mean square (RMS) differences of both the east–west and north–south currents between NYHOPS and HF radar were approximately 15 cm s^?1. Harmonic analysis of NYHOPS and HF radar surface currents shows similar tidal ellipse parameters for the dominant M₂ tide, with a mean difference of 2.4 cm s^?1 in the semi-major axis and 1.4 cm s^?1 in the semi-minor axis and 3° in orientation and 10° in phase. Surface currents derived independently from drifters along their trajectories showed that NYHOPS and HF radar yielded similarly accurate results. RMS errors when compared to currents derived along the trajectory of the three drifters were approximately 10 cm s^?1. Overall, the analysis suggests that NYHOPS and HF radar had similar skill in estimating the currents over the continental shelf waters of the Middle Atlantic Bight during this time period. An ensemble-based set of particle tracking simulations using one drifter which was tracked for 11 days showed that the ensemble mean separation generally increases with time in a linear fashion. The separation distance is not dominated by high frequency or short spatial scale wavelengths suggesting that both the NYHOPS and HF radar currents are representing tidal and inertial time scales correctly and resolving some of the smaller scale eddies. The growing ensemble mean separation distance is dominated by errors in the mean flow causing the drifters to slowly diverge from their observed positions. The separation distance for both HF radar and NYHOPS stays below 30 km after 5 days, and the two technologies have similar tracking skill at the 95 % level. For comparison, the ensemble mean distance of a drifter from its initial release location (persistence assumption) is estimated to be greater than 70 km in 5 days.     

Correcting surface winds by assimilating high-frequency radar surface currents in the German Bight

Surface winds are crucial for accurately modeling the surface circulation in the coastal ocean. In the present work, high-frequency radar surface currents are assimilated using an ensemble scheme which aims to obtain improved surface winds taking into account European Centre for Medium-Range Weather Forecasts winds as a first guess and surface current measurements. The objective of this study is to show that wind forcing can be improved using an approach similar to parameter estimation in ensemble data assimilation. Like variational assimilation schemes, the method provides an improved wind field based on surface current measurements. However, the technique does not require an adjoint, and it is thus easier to implement. In addition, it does not rely on a linearization of the model dynamics. The method is validated directly by comparing the analyzed wind speed to independent in situ measurements and indirectly by assessing the impact of the corrected winds on model sea surface temperature (SST) relative to satellite SST.     

A short-term predictive system for surface currents from a rapidly deployed coastal HF radar network

In order to address the need for surface trajectory forecasts following deployment of coastal HF radar systems during emergency-response situations (e.g., search and rescue, oil spill), a short-term predictive system (STPS) based on only a few hours data background is presented. First, open-modal analysis (OMA) coefficients are fitted to 1-D surface currents from all available radar stations at each time interval. OMA has the effect of applying a spatial low-pass filter to the data, fills gaps, and can extend coverage to areas where radial vectors are available from a single radar only. Then, a set of temporal modes is fitted to the time series of OMA coefficients, typically over a short 12-h trailing period. These modes include tidal and inertial harmonics, as well as constant and linear trends. This temporal model is the STPS basis for producing up to a 12-h current vector forecast from which a trajectory forecast can be derived. We show results of this method applied to data gathered during the September 2010 rapid-response demonstration in northern Norway. Forecasted coefficients, currents, and trajectories are compared with the same measured quantities, and statistics of skill are assessed employing 16 24-h data sets. Forecasted and measured kinetic variances of the OMA coefficients typically agreed to within 10–15%. In one case where errors were larger, strong wind changes are suspected and examined as the cause. Sudden wind variability is not included properly within the STPS attack we presently employ and will be a subject for future improvement.     

Use of surface currents measured by HF radar in planning coastal discharges

Surface currents measured by HF Radar (OSCR) are analysed to determine near-shore circulation in connection with planning optimum locations for sewage discharges. Dual radar units, each measuring a radial velocity component, were deployed at a total of five sites for three separate periods each of one week's duration (one site being common to two deployments). Observed data from 20 radial ‘bins’ each 1.2 km long were obtained for six beams each 6° wide at all five sites. These data were analysed separately to determine 1. the tidal constituents, 2. the wind driven component and 3. the steady residual component. In deriving the wind-driven response a relationship

was assumed where R(t) is the non-tidal velocity, W_E and W_N east and west components of wind speed, Δt a time lag and α and β empirical coefficients determined by least squares fitting techniques. At positions where beams from any two sites crossed, their separate current components were combined, producing the following spatial distributions of surface current vectors: 1. tidal ellipses, 2. separate responses to unit wind forcing from a. west and b. south and 3. steady residual drifts. The validity of these current distributions is examined by 1. comparison with other observational data, 2. by consideration of their self coherence and 3. in terms of simple theory.     

Multistatic estimation of high-frequency radar surface currents in the region of Toulon

Ocean Dynamics - The high-frequency radar coastal network in Toulon operates in multistatic mode for the monitoring of the ocean circulation in the Northwestern Mediterranean Sea. With 2...     

Simulation and detection of tsunami signatures in ocean surface currents measured by HF radar

High-frequency (HF) surface wave radars provide the unique capability to continuously monitor the coastal environment far beyond the range of conventional microwave radars. Bragg-resonant backscattering by ocean waves with half the electromagnetic radar wavelength allows ocean surface currents to be measured at distances up to 200 km. When a tsunami propagates from the deep ocean to shallow water, a specific ocean current signature is generated throughout the water column. Due to the long range of an HF radar, it is possible to detect this current signature at the shelf edge. When the shelf edge is about 100 km in front of the coastline, the radar can detect the tsunami about 45 min before it hits the coast, leaving enough time to issue an early warning. As up to now no HF radar measurements of an approaching tsunami exist, a simulation study has been done to fix parameters like the required spatial resolution or the maximum coherent integration time allowed. The simulation involves several steps, starting with the Hamburg Shelf Ocean Model (HAMSOM) which is used to estimate the tsunami-induced current velocity at 1 km spatial resolution and 1 s time step. This ocean current signal is then superimposed to modelled and measured HF radar backscatter signals using a new modulation technique. After applying conventional HF radar signal processing techniques, the surface current maps contain the rapidly changing tsunami-induced current features, which can be compared to the HAMSOM data. The specific radial tsunami current signatures can clearly be observed in these maps, if appropriate spatial and temporal resolution is used. Based on the entropy of the ocean current maps, a tsunami detection algorithm is described which can be used to issue an automated tsunami warning message.     

Application of HF radar currents to oil spill modelling

In this work, the benefits of high-frequency (HF) radar currents for oil spill modeling and trajectory analysis of floating objects are analyzed. The HF radar performance is evaluated by means of comparison between a drifter buoy trajectory and the one simulated using a Lagrangian trajectory model. A methodology to optimize the transport model performance and to calculate the search area of the predicted positions is proposed. This method is applied to data collected during the Galicia HF Radar Experience. This experiment was carried out to explore the capabilities of this technology for operational monitoring along the Spanish coast. Two long-range HF radar stations were installed and operated between November 2005 and February 2006 on the Galician coast. In addition, a drifter buoy was released inside the coverage area of the radar. The HF radar currents, as well as numerical wind data were used to simulate the buoy trajectory using the TESEO oil spill transport model. In order to evaluate the contribution of HF radar currents to trajectory analysis, two simulation alternatives were carried out. In the first one, wind data were used to simulate the motion of the buoy. In the second alternative, surface currents from the HF radar were also taken into account. For each alternative, the model was calibrated by means of the global optimization algorithm SCEM-UA (Shuffled Complex Evolution Metropolis) in order to obtain the probability density function of the model parameters. The buoy trajectory was computed for 24 h intervals using a Monte Carlo approach based on the results provided in the calibration process. A bivariate kernel estimator was applied to determine the 95% confidence areas. The analysis performed showed that simulated trajectories integrating HF radar currents are more accurate than those obtained considering only wind numerical data. After a 24 h period, the error in the final simulated position improves using HF radar currents. Averaging the information from all the simulated daily periods, the mean search and rescue area calculated using HF radar currents, is reduced by approximately a 62% in comparison with the search area calculated without these data. These results show the positive contribution of HF radar currents for trajectory analysis, and demonstrate that these data combined with atmospheric forecast models, are of value for trajectory analysis of oil spills or floating objects.     

Characterization of ocean surface current properties from single site HF/VHF radar

Surface current mapping from HF/VHF coastal radars traditionally requires at least two distant sites. Vector velocities are estimated by combining the radial velocity components measured by the radars. In many circumstances (e.g., failures, interferences, logistics constraints), such a combination is not possible by lack of data from one station. Two methods are evaluated to get information on surface circulation from a single site radar: the Vectorial Reconstruction Method (VRM) for current vector mapping and the Vortex Identification Method (VIM) for detecting eddy-like structures. The VRM assumes a non-divergent horizontal surface current, and the VIM analyzes radial velocities and their radial and orthoradial gradients. These two methods are tested on modeled and measured data sets in the Northwestern Mediterranean Sea where both high-resolution ocean circulation model and radar campaigns are available. The VRM performance is strongly limited by the divergence-free hypothesis which was not satisfied in our real data. The VIM succeeded in detection of vortex in the Gulf of Lions and from an operating single site radar located on the Provence coasts in summer.     

探地雷达地面以上物体反射干扰特征模拟和分析

地面以上物体产生的反射是探地雷达探测工作面临的主要干扰之一.地面以上物体干扰源的空间位置分布具有随机性,识别和去除这些干扰首先需要了解干扰波的传播特征.为达到这一目的,进而为干扰压制研究提供理论依据,本文首先通过对地面以上物体建立抽象模型并进行正演模拟,求解出电磁波在不同观测系统中受点、线、面干扰源影响的波场分布特征;其次,根据射线理论推导出点、线、面干扰源产生的干扰波时距曲线的一般表达式,并对时距曲线特征进行分析和归纳.     

Wind-speed inversion from HF radar first-order backscatter signal

Land-based high-frequency (HF) radars have the unique capability of continuously monitoring ocean surface environments at ranges up to 200 km off the coast. They provide reliable data on ocean surface currents and under slightly stricter conditions can also give information on ocean waves. Although extraction of wind direction is possible, estimation of wind speed poses a challenge. Existing methods estimate wind speed indirectly from the radar derived ocean wave spectrum, which is estimated from the second-order sidebands of the radar Doppler spectrum. The latter is extracted at shorter ranges compared with the first-order signal, thus limiting the method to short distances. Given this limitation, we explore the possibility of deriving wind speed from radar first-order backscatter signal. Two new methods are developed and presented that explore the relationship between wind speed and wave generation at the Bragg frequency matching that of the radar. One of the methods utilizes the absolute energy level of the radar first-order peaks while the second method uses the directional spreading of the wind generated waves at the Bragg frequency. For both methods, artificial neural network analysis is performed to derive the interdependence of the relevant parameters with wind speed. The first method is suitable for application only at single locations where in situ data are available and the network has been trained for while the second method can also be used outside of the training location on any point within the radar coverage area. Both methods require two or more radar sites and information on the radio beam direction. The methods are verified with data collected in Fedje, Norway, and the Ligurian Sea, Italy using beam forming HF WEllen RAdar (WERA) systems operated at 27.68 and 12.5 MHz, respectively. The results show that application of either method requires wind speeds above a minimum value (lower limit). This limit is radar frequency dependent and is 2.5 and 4.0 m/s for 27.68 and 12.5 MHz, respectively. In addition, an upper limit is identified which is caused by wave energy saturation at the Bragg wave frequency. Estimation of this limit took place through an evaluation of a year long database of ocean spectra generated by a numerical model (third generation WAM). It was found to be at 9.0 and 11.0 m/s for 27.68 and 12.5 MHz, respectively. Above this saturation limit, conventional second-order methods have to be applied, which at this range of wind speed no longer suffer from low signal-to-noise ratios. For use in operational systems, a hybrid of first- and second-order methods is recommended.     

The synthesis of travelling ionospheric disturbance (TID) signatures in HF radar observations using ray tracing

Characteristic signatures are often observed in HF radar range-time-intensity plots when travelling ionospheric disturbances (TIDs) are present. These signatures, in particular the variation of the F-region skip distance, have been synthesised using a ray tracing model. The magnitude of the skip variation is found to be a function of the peak electron density perturbation associated with the TID and radar frequency. Examination of experimental observations leads to an estimate of the peak electron density perturbation amplitude of around 25% for those TIDs observed by the CUTLASS radar system. The advantage of using the skip variation over the radar return amplitude as an indicator of density perturbation is also discussed. An example of a dual radar frequency experiment has been given. The investigation of the effect of radar frequency on the observations will aid the optimisation of future experiments.     

Inversion of swell frequency from a 1-year HF radar dataset collected in Brittany (France)

This article presents long period ocean wave (swell) frequencies inverted from a 13-month dataset of high-frequency (HF) phased array radars and an assessment of these estimates by comparison with WAVEWATCH III model data. The method of swell frequency inversion from high-frequency radar sea echo Doppler spectra is described. Radar data were collected from a two-site HF Wellen Radar (WERA) radar system on the west coast of Brittany (France) operating at 12 MHz. A standard beam-forming processing technique has been used to obtain Doppler spectra of processed radar cells. Swell frequencies are obtained from the frequencies of particular spectral peaks of the second-order continuum in hourly averaged Doppler spectra. The data coverage of effective Doppler spectra considered for swell frequency estimates shows the influence of islands and shallow water effects. Swell estimates from both radar stations are in good agreement. The comparison of radar-derived results to WAVEWATCH III (WW3) estimates shows that radar measurements agree quite well with model results. The bias and standard deviation between two estimates are very small for swells with frequency less than 0.09 Hz (period >11 s), whereas radar estimates are generally lower than model estimates for shorter swells, along with higher standard deviation. Statistical analysis suggests that radar measurement uncertainty explains most of the difference between radar and model estimates. For each swell event, time series of frequency exhibits a quasi-linear frequency increase which is associated with the dispersive property of wave phase velocity. The use of swell frequency estimates from both radars on common radar cells only slightly increases the accuracy of swell frequency measurement.     

Detecting surface geostrophic currents using wavelet filter from satellite geodesy

According to the features of spatial spectrum of the dynamic ocean topography (DOT),wavelet filter is proposed to reduce short-wavelength and noise signals in DOT. The surface geostrophic currents calculated from the DOT models filtered by wavelet filter in global and Kuroshio regions show more detailed information than those from the DOT models filtered by Gaussian filter. Based on a satellite gravity field model (CG01C) and a gravity field model (EGM96),combining an altimetry-derived mean sea surface height model (KMSS04),two mean DOT models are estimated. The short-wavelength and noise signals of these two DOT models are removed by using wavelet filter,and the DOT models asso-ciated global mean surface geostrophic current fields are calculated separately. Comparison of the surface geostrophic currents from CG01C and EGM96 model in global,Kuroshio and equatorial Pacific regions with that from oceanography,and comparison of influences of the two gravity models errors on the precision of the surface geostrophic currents velocity show that the accuracy of CG01C model has been greatly improved over pre-existing models at long wavelengths. At large and middle scale,the surface geostrophic current from satellite gravity and satellite altimetry agrees well with that from oceanography,which indicates that ocean currents detected by satellite measurement have reached relatively high precision.     

BAKTRAK: backtracking drifting objects using an iterative algorithm with a forward trajectory model

The task of determining the origin of a drifting object after it has been located is highly complex due to the uncertainties in drift properties and environmental forcing (wind, waves, and surface currents). Usually, the origin is inferred by running a trajectory model (stochastic or deterministic) in reverse. However, this approach has some severe drawbacks, most notably the fact that many drifting objects go through nonlinear state changes underway (e.g., evaporating oil or a capsizing lifeboat). This makes it difficult to naively construct a reverse-time trajectory model which realistically predicts the earliest possible time the object may have started drifting. We propose instead a different approach where the original (forward) trajectory model is kept unaltered while an iterative seeding and selection process allows us to retain only those particles that end up within a certain time–space radius of the observation. An iterative refinement process named BAKTRAK is employed where those trajectories that do not make it to the goal are rejected, and new trajectories are spawned from successful trajectories. This allows the model to be run in the forward direction to determine the point of origin of a drifting object. The method is demonstrated using the leeway stochastic trajectory model for drifting objects due to its relative simplicity and the practical importance of being able to identify the origin of drifting objects. However, the methodology is general and even more applicable to oil drift trajectories, drifting ships, and hazardous material that exhibit nonlinear state changes such as evaporation, chemical weathering, capsizing, or swamping. The backtracking method is tested against the drift trajectory of a life raft and is shown to predict closely the initial release position of the raft and its subsequent trajectory.     

CUTLASS HF radar observations of high-latitude azimuthally propagating vortical currents in the nightside ionosphere during magnetospheric substorms

High-time resolution CUTLASS observations and ground-based magnetometers have been employed to study the occurrence of vortical flow structures propagating through the high-latitude ionosphere during magnetospheric substorms. Fast-moving flow vortices (800 m s^–1) associated with Hall currents flowing around upward directed field-aligned currents are frequently observed propagating at high speed (1 km s^–1) azimuthally away from the region of the ionosphere associated with the location of the substorm expansion phase onset. Furthermore, a statistical analysis drawn from over 1000 h of high-time resolution, nightside radar data has enabled the characterisation of the bulk properties of these vortical flow systems. Their occurrence with respect to substorm phase has been investigated and a possible generation mechanism has been suggested.     

Multi-scale variability of circulation in the Gulf of Tonkin from remote sensing of surface currents by high-frequency radars

Ocean Dynamics - The sea surface velocity measurements obtained during the period of 2014–2016 using two high-frequency radars (HFR), which were installed on the northern coast of Vietnam,...