A High-Resolution Numerical Model of the North Aegean Sea Aimed at Climatological Studies

A new, high-resolution model for the northern part of the Aegean Sea, aimed primarily at climatological research (relaxation and data assimilation-free climate simulations), is hereby presented, along with the results of a 28-year-long simulation covering the period from 1986 to 2013. The model applied is the Regional Ocean Modelling System (ROMS). A significant improvement over previous models of the Aegean introduced in this work is the replacement of parameterizations of the Dardanelles exchange by a fully three-dimensional simulation of the flow in the Strait. The incorporation of part of the Marmara Sea in the model domain enables the interaction with other regional climate simulations, thus allowing climatic variability of the exchange of the Mediterranean and Black Seas. An extensive validation is carried out comparing the model output with all the available observations from several different platforms, i.e., satellite sea surface temperature and height, T/S profiles from R/V ships, and HF radar surface currents velocity. We focus on the model’s ability to reproduce, to some extent, the distinct thermohaline features and circulation patterns that characterize this specific area of the Mediterranean Sea. Our findings, after comparing simulation results with all the available observations, revealed the model’s sufficiency to simulate very adequately the complex hydrology of the North Aegean Sea, and the model’s ability to reproduce incidents of deep-water formation that took place in the region in previous decades during the Eastern Mediterranean Transient (EMT).

Direction Finding and Likelihood Ratio Detection for Oceanographic HF Radars

Previous work with simulations of oceanographic HF radars has identified possible improvements when using Maximum Likelihood Estimation (MLE) for directional-of-arrival (DOA), however methods for determining the number of emitters (here defined as spatially distinct patches of the ocean surface) have not realized these improvements. Here we describe and evaluate the use of the Likelihood Ratio (LR) for emitter detection, demonstrating its application to oceanographic HF radar data. The combined detection-estimation methods MLE-LR are compared with MUSIC and MUSIC parameters for SeaSonde HF radars, along with a method developed for 8-channel systems known as MUSIC-Highest. Results show that the use of MLE-LR produces similar accuracy in terms of the RMS difference and correlation coefficients squared, as previous methods. We demonstrate that improved accuracy can be obtained for both methods, at the cost of fewer velocity observations and decreased spatial coverage. For SeaSondes, accuracy improvements are obtained with less commonly used parameter sets. The MLE-LR is shown to be able to resolve simultaneous closely spaced emitters, which has the potential to improve observations obtained by HF radars operating in complex current environments.

Estimating Coastal Winds by Assimilating High-Frequency Radar Spectrum Data in SWAN

Many activities require accurate wind and wave forecasts in the coastal ocean. The assimilation of fixed buoy observations into spectral wave models such as SWAN (Simulating Waves Nearshore) can provide improved estimates of wave forecasts fields. High-frequency (HF) radar observations provide a spatially expansive dataset in the coastal ocean for assimilation into wave models. A forward model for the HF Doppler spectrum based on first- and second-order Bragg scattering was developed to assimilate the HF radar wave observations into SWAN. This model uses the spatially varying wave spectra computed using the SWAN model, forecast currents from the Navy Coastal Ocean Model (NCOM), and system parameters from the HF radar sites to predict time-varying range-Doppler maps. Using an adjoint of the HF radar model, the error between these predictions and the corresponding HF Doppler spectrum observations can be translated into effective wave-spectrum errors for assimilation in the SWAN model for use in correcting the wind forcing in SWAN. The initial testing and validation of this system have been conducted using data from ten HF radar sites along the Southern California Bight during the CASPER-West experiment in October 2017. The improved winds compare positively to independent observation data, demonstrating that this algorithm can be utilized to fill an observational gap in the coastal ocean for winds and waves.

Derivation and Evaluation of Satellite-Based Surface Current

Observations of real-time ocean surface currents allow one to search and rescue at ocean disaster sites and investigate the surface transport and fate of ocean contaminants. Although real-time surface currents have been mapped by high-frequency (HF) radar, shipboard instruments, satellite altimetry, and surface drifters, geostationary satellites have proved their capability in satisfying both basin-scale coverage and high spatiotemporal resolutions not offered by other observational platforms. In this paper, we suggest a strategy for the production of operational surface currents using geostationary satellite data, the particle image velocimetry (PIV) method, and deep learning-based evaluation. We used the model scalar field and its gradient to calculate the corresponding surface current via PIV, and we estimated the error between the true velocity field and calculated velocity field by the combined magnitude and relevance index (CMRI) error. We used the model datasets to train a convolutional neural network, which can be used to filter out bad vectors in the surface current produced by arbitrary model scalar fields. We also applied the pretrained network to the surface current generated from real-time Himawari-8 skin sea surface temperature (SST) data. The results showed that the deep learning network successfully filtered out bad vectors in a surface current when it was applied to model SST and created stronger dynamic features when the network was applied to Himawari SST. This strategy can help to provide a quality flag in satellite data to inform data users about the reliability of PIV-derived surface currents.

Characteristics of Sea Surface Current in the Bali Strait, Indonesia using HF Radar and Its Utilization in Safety Navigation

This paper was done by using the HF Radar data from 2018-2019 to study the characteristics of Sea Surface Current (SSC) in the Bali Strait. The data processing method was done by calculating the speed and SSC direction of the zonal and meridional components. Furthermore, SSC analysis was performed every hour and month by calculating the average of all data at the same hour and month. It was found that the unique SSC pattern in the Bali Strait occurred on the western side of Bali Island and the eastern side of Java Island. On the west side of the Bali Island, there was a decrease in SSC speed at 0.00-7.00 and 13.00-18.00, as well as a two-fold increase at 8.00-12.00 and 19.00-2.00, both of which were in a fluctuating speed range from 0-140 cm s-1 in the direction of dominant towards the south. On the eastern side of Java Island, SSC speed ranges from 0 to 40 cm s-1 all the time with the dominant direction heading from east to southeast. The monthly SSC pattern was also seen more clearly in this study, meanwhile during December-March the SSC rate was lower than during June-September, ranging from 0 to 20 cm s-1 and from 40 to 140 cm s-1, respectively. Furthermore, the two SSC patterns above can be simplified into two periods, namely periods of relaxation and agitation. This study also applies the device to ship accidents that occurred in the Bali Strait as case studies.

Measurement and Analysis of Ocean Current using High- Frequency (HF) Radar Observation in the Bali Strait

High-Frequency (HF) Radar is an instrument using radio waves to measure ocean currents and waves remotely. This technology has many advantages, including has unprecedented spatial and temporal resolution, can operate in any weather condition, and is not dangerous for the environment. However, HF Radar's research is still limited in Indonesia. This research aimed to analyze the tidal and residual current in the Bali Strait in July 2020. Radial velocity from two HF Radar sites is combined to obtain the total currents. Current data from HF Radar were compared with Acoustic Doppler Current Profiler (ADCP) data to investigate its accuracy. Surface current data were analyzed using harmonic analysis to separate tidal and residual currents. Comparison between HF Radar and ADCP data are in good agreement for meridional current with a very high correlation of 0.813 and a small RMSE value of 0.22 m/s. Harmonic analysis shows that the dominant currents are tidal currents. The current direction was northward (southward) at flood (ebb), with maximum northward (southward) velocities are 2.17 m/s (2.97 m/s), respectively. The residual current has a random pattern, slightly faster northward than southward, and has similar spectral with the wind.

Remote Sensing of the Polar Ice Zones with HF Radar

Radars operating in the HF band are widely used for over-the-horizon remote sensing of ocean surface conditions, ionospheric studies and the monitoring of ship and aircraft traffic. Several hundreds of such radars are in operation, yet only a handful of experiments have been conducted to assess the prospect of utilizing this technology for the remote sensing of sea ice. Even then, the measurements carried out have addressed only the most basic questions: is there ice present, and can we measure its drift? Recently the theory that describes HF scattering from the dynamic sea surface was extended to handle situations where an ice cover is present. With this new tool, it becomes feasible to interpret the corresponding radar echoes in terms of the structural, mechanical, and electrical properties of the ice field. In this paper we look briefly at ice sensing from space-borne sensors before showing how the persistent and synoptic wide area surveillance capabilities of HF radar offer an alternative. The dispersion relations of different forms of sea ice are examined and used in a modified implementation of the electromagnetic scattering theory employed in HF radar oceanography to compute the corresponding radar signatures. Previous and present-day HF radar deployments at high latitudes are reviewed, noting the physical and technical challenges that confront the implementation of an operational HF radar in its ice monitoring capability.

Detection and Warning of Tsunamis Generated by Marine Landslides

Seismic signals provide an effective early detection of tsunamis that are generated by earthquakes, and for epicentres in the hard-rock subduction zones there is a robust analysis procedure that uses a global network of seismometers. For earthquakes with epicentres in soft layers in the upper subduction zones the processes are slower and the seismic signals have lower frequencies. For these soft-rock earthquakes a given earthquake magnitude can produce a bigger tsunami amplitude than the same earthquake magnitude in a hard rock rupture. Numerical modelling for the propagation from earthquake-generated tsunamis can predict time of arrivals at distant coastal impact zones. A global network of deep-water pressure sensors is used to detect and confirm tsunamis in the open ocean. Submarine landslide and coastal collapse tsunamis, meteo-tsunamis, and other disturbances with no significant seismicity must rely on the deep-water pressure sensors and HF radar for detection and warning. Local observations by HF radar at key impact sites detect and confirm tsunami time and amplitude in the order of 20–60 minutes before impact. HF radar systems that were developed for mapping the dynamics of coastal currents have demonstrated a capability to detect tsunamis within about 80 km of the coast and where the water depth is less than 200 m. These systems have now been optimised for tsunami detection and some installations are operating continuously to provide real-time data into tsunami warning centres. The value of a system to warn of hazards is realised only when coastal communities are informed and aware of the dangers.