Search Results (56)

Passive acoustic monitoring plays a critical role in the study of marine species, particularly in understanding the behavior of deep-diving endangered species like the Mediterranean sperm whale (Physeter macrocephalus). This paper presents an effective method for tracking sperm whales using synchronized acoustic data from four hydrophones. The tracking method estimates the location of sperm whales by measuring the time difference of arrival of detected clicks. The direction of arrival of the clicks and their reflections on the surface are then reconstructed to determine the position of the whale. The method was used to perform the first acoustic tracking study of sperm whale dives recorded in the Central Mediterranean Sea by the NEMO-O$\nu$DE cabled observatory, deployed at a depth of 2100 m in the Gulf of Catania. The data analyzed in this study were collected in August and October 2005 and include 49 five-minute recordings with the presence of sperm whale clicks. A Monte Carlo simulation revealed an estimated relative error of 2.7% in depth and 1.9% in the horizontal distance for the positioning of clicks. The algorithm successfully reconstructed 64 tracks of diving sperm whales and demonstrated its potential for monitoring within a 12 km radius. Moreover, a simultaneous tracking of a vessel and a sperm whale was performed, illustrating how the method can be used to study potential changes during dives in the presence of vessels. This method offers a reliable, non-invasive approach to studying sperm whale behavior, ecology, and interaction with anthropogenic activities. Full article

Hydrophones used in Passive Acoustic Monitoring generate vast amounts of data, with the storage requirements for raw signals dependent on the sampling frequency, which limits the range of frequencies that can be recorded. Since the installation of these observatories is costly, it is crucial to maximize the utility of high-sampling-rate recordings to expand the range of survey types. However, storing these large datasets for long-term trend analysis presents significant challenges. This paper proposes an approach that reduces the data storage requirements by up to 85% while preserving critical information about Power Spectral Density and Sound Pressure Level. The strategy involves generating these key metrics from spectrograms, enabling both short-term (micro) and long-term (macro) studies. A proposal for efficient data processing is presented, structured in three steps: the first focuses on generating key metrics to replace space-consuming raw signals, the second addresses the treatment of these metrics for long-term studies, and the third outlines the creation of event detectors from the processed metrics. A comprehensive overview of the essential features for analyzing acoustic signals is provided, along with considerations for the future design of marine observatories. The necessary calculations and processes are detailed, demonstrating the potential of these methods to address the current data storage and processing limitations in long-term acoustic monitoring. Full article

The coast is the most dynamic part of the Earth’s surface due to its strategic position at the interface of the land and the sea. It is, therefore, exposed to hazards and specific risks because of the geography as well as the geological and environmental characteristics of different countries. The coastal environment is essentially dynamic and evolving in time and space, marked by waves, tides, and seasons; moreover, it is subjected to many marine and continental processes (forcing). This succession of events significantly influences the frequency and severity of coastal hazards. The present paper aims at describing and characterizing the hazards and vulnerabilities on the Cameroonian coast. Cameroon possesses 400 km of coastline, which is exposed to various hazards. It is important to determine the probabilities of these hazards, the associated effects, and the related vulnerabilities. In this study, in this stable intraplate setting, the methodology used was diverse and combined techniques for the study of the shore and methods for the treatment of climatic data. Also, historical data were collected during field observations and from the CRED website for all the natural hazards recorded in Cameroon. In addition, documents on climate change were consulted. Remotely sensed data, combined with GIS tools, helped to determine and assess the associated risks. A critical grid combining a severity and frequency analysis was used to better understand these hazards and the coastal vulnerabilities of Cameroon. The results show that Cameroon’s coastal margins are subject to natural processes that cause shoreline changes, including inundation, erosion, and accretion. This study identified seven primary hazard types (earthquakes, volcanism, landslides, floods, erosion, sea level rise, and black tides) affecting the Cameroonian coastline, with the erosion rate exceeding 1.15 m/year at Cape Cameroon. Coastal populations are continuously threatened by these natural or man-induced hazards, and they are periodically subjected to catastrophic disasters such as floods and landslides, as experienced in Cameroon. In addition, despite the existence of the National Contingency Plan devised by the Directorate of Civil Protection, National Risk, and Climate Change Observatories, the implementation of disaster risk reduction and mitigation strategies is suboptimal. Full article

Since the Industrial Revolution, underwater soundscapes have become more complex and contaminated due to increased cumulative human activities. Anthropogenic underwater sources have been growing in number, and shipping noise has become the primary source of chronic acoustic exposure. However, global data on current and historic noise levels is lacking. Here, using the Listening to the Deep-Ocean Environment network, we investigated the baseline shipping noise levels in thirteen observatories (eight stations from ONC Canada, four from the JAMSTEC network, and OBSEA in the Mediterranean Sea) and, in five of them, animal presence. Our main results show yearly noise variability in the studied locations that is not dominated by marine traffic but by natural and biological patterns. The halt in transportation due to COVID was insignificant when the data were recorded far from shipping routes. In order to better design a legislative framework for mitigating noise impacts, we highlight the importance of using tools that allow for long-term acoustic monitoring, automated detection of sounds, and big data handling and management. Full article

The Hong Kong Observatory has been using a parametric storm surge model to forecast the rise of sea level due to the passage of tropical cyclones. This model includes an offset parameter to account for the rise in sea level due to other meteorological factors. By adding the sea level rise forecast to the astronomical tide prediction using the harmonic analysis method, coastal sea level prediction can be produced for the sites with tidal observations, which supports the high water level forecast operation and alert service for risk assessment of sea flooding in Hong Kong. The Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modelling System, which comprises the Weather Research and Forecasting (WRF) Model and Regional Ocean Modelling System (ROMS), which in itself is coupled with wave model WaveWatch III and nearshore wave model SWAN, was tested with tropical cyclone cases where there was significant water level rise in Hong Kong. This case study includes two super typhoons, namely Hato in 2017 and Mangkhut in 2018, three cases of the combined effect of tropical cyclone and northeast monsoon, including Typhoon Kompasu in 2021, Typhoon Nesat and Severe Tropical Storm Nalgae in 2022, as well as two cases of monsoon-induced sea level anomalies in February 2022 and February 2023. This study aims to evaluate the ability of the WRF-ROMS-SWAN model to downscale the meteorological fields and the performance of the coupled models in capturing the maximum sea levels under the influence of significant weather events. The results suggested that both configurations could reproduce the sea level variations with a high coefficient of determination (R²) of around 0.9. However, the WRF-ROMS-SWAN model gave better results with a reduced RMSE in the surface wind and sea level anomaly predictions. Except for some cases where the atmospheric model has introduced errors during the downscaling of the ERA5 dataset, bias in the peak sea levels could be reduced by the WRF-ROMS-SWAN coupled model. The study result serves as one of the bases for the implementation of the three-way coupled atmosphere–ocean–wave modelling system for producing an integrated forecast of storm surge or sea level anomalies due to meteorological factors, as well as meteorological and oceanographic parameters as an upgrade to the two-way coupled Operational Marine Forecasting System in the Hong Kong Observatory. Full article

The rapid growth of marine industries has emphasized the focus on environmental impacts for all industries, as well as the influence of key environmental parameters on, for instance, offshore wind or aquaculture performance, animal welfare and structural integrity of different constructions. Development of automatized sensors together with efficient communication and information systems will enhance surveillance and monitoring of environmental processes and impact. We have developed a modular Smart Ocean observatory, in this case connected to a large-scale marine aquaculture research facility. The first sensor rigs have been operational since May 2022, transmitting environmental data in near real-time. Key components are Acoustic Doppler Current Profilers (ADCPs) for measuring directional wave and current parameters, and CTDs for redundant measurement of depth, temperature, conductivity and oxygen. Communication is through 4G network or cable. However, a key purpose of the observatory is also to facilitate experiments with acoustic wireless underwater communication, which are ongoing. The aim is to expand the system(s) with demersal independent sensor nodes communicating through an “Internet of Underwater Things (IoUT)”, covering larger areas in the coastal zone, as well as open waters, of benefit to all ocean industries. The observatory also hosts experiments for sensor development, biofouling control and strategies for sensor self-validation and diagnostics. The close interactions between the experiments and the infrastructure development allow a holistic approach towards environmental monitoring across sectors and industries, plus to reduce the carbon footprint of ocean observation. This work is intended to lay a basis for sophisticated use of smart sensors with communication systems in long-term autonomous operation in remote as well as nearshore locations. Full article

Digital Twins of the Ocean (DTO) are a rapidly emerging topic that has attracted significant interest from scientists in recent years. The initiative, strongly driven by the EU, aims to create a digital replica of the ocean to better understand and manage marine environments. The Iliad project, funded under the EU Green Deal call, is developing a framework to support multiple interoperable DTO using a federated systems-of-systems approach across various fields of applications and ocean areas, called pilots. This paper presents the results of a Water Quality DTO pilot located in the Trondheim fjord in Norway. This paper details the building blocks of DTO, specific to this environmental monitoring pilot. A crucial aspect of any DTO is data, which can be sourced internally, externally, or through a hybrid approach utilizing both. To realistically twin ocean processes, the Water Quality pilot acquires data from both surface and benthic observatories, as well as from mobile sensor platforms for on-demand data collection. Data ingested into an InfluxDB are made available to users via an API or an interface for interacting with the DTO and setting up alerts or events to support ’what-if’ scenarios. Grafana, an interactive visualization application, is used to visualize and interact with not only time-series data but also more complex data such as video streams, maps, and embedded applications. An additional visualization approach leverages game technology based on Unity and Cesium, utilizing their advanced rendering capabilities and physical computations to integrate and dynamically render real-time data from the pilot and diverse sources. This paper includes two case studies that illustrate the use of particle sensors to detect microplastics and monitor algae blooms in the fjord. Numerical models for particle fate and transport, OpenDrift and DREAM, are used to forecast the evolution of these events, simulating the distribution of observed plankton and microplastics during the forecasting period. Full article

The forty-year-old Long-Term Ecological Research MareChiara (LTER-MC) program started on 26 January 1984, with fortnightly oceanographic sampling until 1991 and then, from 1995, with weekly sampling up to the present time. LTER-MC produced >150 publications that have been cited by thousands of other studies. In this scoping review, we analyzed this corpus using a semantic approach based on topic modeling, a machine-driven procedure to identify and map topics and their interactions. Understanding the causes behind the evolution of scientific topics, their emergence, splitting, hybridization, or merging within a scientific community is an important step in science policy in managing collaborative research and bringing it into the future. Across different topics, mainly represented by studies on Natural History, Biodiversity, Phenology, Life Cycles, and Community Ecology, the LTER-MC work expanded the knowledge on planktonic organisms, describing in detail their lifestyles and delineating their relationships with environmental conditions. In presenting these results, the potential strengths, weaknesses, opportunities, and threats connected to the overall scientific dimension of LTER-MC are discussed. Finally, the upcoming effort is envisioned in reinforcing internal collaboration to integrate basic and applied research around scientific investigations suitable for establishing a stronger interaction between science and policy, as indicated by the United Nations Decade of Ocean Science for Sustainable Development. Full article

Submarine volcanoes are more challenging to monitor than subaerial volcanoes. Yet, the large eruption of the Hunga Tonga-Hunga Ha’apai volcano in the Tonga archipelago in 2022 was a reminder of their hazardous nature and hence demonstrated the need to study them. In October 2020, four autonomous hydrophones were moored in the sound fixing and ranging channel 50 km offshore Mayotte Island, in the North Mozambique Channel, to monitor the Fani Maoré 2018–2020 submarine eruption. Between their deployment and July 2022, this network of hydrophones, named MAHY, recorded sounds generated by the recent volcanic activity, along with earthquakes, submarine landslides, marine mammals calls, and marine traffic. Among the sounds generated by the volcanic activity, impulsive signals have been evidenced and interpreted as proxy for lava flow emplacements. The characteristics and the spatio-temporal evolution of these hydroacoustic signals allowed the estimation of effusion and flow rates, key parameters for volcano monitoring. These sounds are related to the non-explosive quenching of pillow lavas due to the rapid heat transfer between hot lava and cold seawater, with this process releasing an energy equivalent to an airgun source as used for active seismic exploration. Volcano observatories could hence use autonomous hydrophones in the water column to detect and monitor active submarine eruptions in the absence of regular on-site seafloor survey. Full article

With increasing air and sea temperatures, the thermodynamic environments over the oceans are becoming more favourable for the development of intense tropical cyclones (TCs) with rapid intensification (RI). The South China coastal region consists of highly densely populated cities, especially over the Pearl River Delta (PRD) region. Intense TCs maintaining their strength or the RI of TCs close to the coastal region can present substantial forecasting challenges and have significant potential impacts on the coastal population. This study investigates the effect of sea-surface and sub-surface temperatures and salinity on the intensification of five TCs, namely Super Typhoon Hato in 2017, Super Typhoon Mangkhut in 2018, and Typhoon Talim, Super Typhoon Saola, and Severe Typhoon Koinu in 2023, which have significantly affected the South China coastal region and triggered high TC warning signals in Hong Kong in the past few years. This analysis utilised the Hong Kong Observatory’s TC best-track and intensity data, along with sea temperature and salinity profiles generated using the China Ocean ReAnalysis version 2 (CORA2) product from the National Marine Data and Information Service of China. It was found that high sea-surface temperatures (SST) of 30 °C or above for a depth of about 20 m, low sea-surface salinity (SSS) levels of 33.8 psu or below for a depth of at least 20 m, and strong salinity stratification of at least 0.6 psu per 100 m depth might offer useful hints for predicting the RI of TCs over the western North Pacific and the South China Sea (SCS) in operational forecasting, while noting other contributing environmental factors and synoptic flow patterns conducive to RI. This study represents the first documentation of sub-surface salinity’s impact on some intense TCs traversing the SCS during 2017–2023 based on an observational study. Our aim is to supplement operational techniques for forecasting RI with some quantitative guidance based on upper-level ocean observations of temperatures and salinity, on top of well-known but more rapidly changing dynamical factors like low-level convergence, weak vertical wind shear, and upper-level divergent outflow, as forecasted with numerical weather prediction models. This study will also encourage further research to refine the analysis of quantitative contributions from different RI factors and the identification of essential features for developing AI models as one way to improve the forecasting of TC RI before the TC makes landfall near the PRD, with due consideration given to the effect of freshwater river discharge from the Pearl River. Full article

In order to address the requirements of scientific multidisciplinary observation in diverse small-scale regions, we have introduced the Buoy-based Cable Seafloor Observatory System (BCSOS). This system offers a distinct advantage in contexts where the use of shorter cables is feasible, contrasting with the lengthy cables typically necessary for conventional observatories. The BCSOS consists of three primary components: the Real-Time Electric Communication (RTEC) Buoy, the Power Information Transmission System (PITS), and the Seafloor Observation Subsystem (SOS). The RTEC Buoy is equipped with instruments for measuring sea surface parameters and serves as a data and power hub. The PITS, comprising a robust EM cable, connects the buoy to the SOS, which houses instruments for seafloor observations. The system is designed for a maximum water depth of 100 m and has an expected lifespan of about 5 years. The BCSOS prototypes were deployed at the Huangqi Peninsula, Fujian Province, and successfully documented the process during Typhoon Doksuri (international code 2305) at the end of July 2023. The recorded data from the BCSOS revealed a significant increase in wave height and period as the storm approached the Huangqi Peninsula. Additionally, the RTEC buoy exhibited a notable response to the large waves. The data analysis revealed a distinct pattern between the buoy response and the direction of wave propagation across various sea conditions, that the buoy’s angular movement in pitch and roll directions follows a regular elliptical distribution corresponding to different wave propagation directions. Upon thorough evaluation, future enhancements to the system are slated to concentrate on refining its design, with a particular emphasis on bolstering stability and enhancing corrosion resistance. These improvements are aimed at cementing the system’s long-term viability and performance within the challenging marine environment. Full article

Through the use of Underwater Smart Sensor Networks (USSNs), Marine Observatories (MOs) provide continuous ocean monitoring. Deployed sensors may not perform as intended due to the heterogeneity of USSN devices’ hardware and software when combined with the Internet. Hence, USSNs are regarded as complex distributed systems. As such, USSN designers will encounter challenges throughout the design phase related to time, complexity, sharing diverse domain experiences (viewpoints), and ensuring optimal performance for the deployed USSNs. Accordingly, during the USSN development and deployment phases, a few Underwater Environmental Constraints (UECs) should be taken into account. These constraints may include the salinity level and the operational depth of every physical component (sensor, server, etc.) that will be utilized throughout the duration of the USSN information systems’ development and implementation. To this end, in this article we present how we integrated an Artificial Intelligence (AI) Database, an extended ArchiMO meta-model, and a design tool into our previously proposed Enterprise Architecture Framework. This addition proposes adding new Underwater Environmental Constraints (UECs) to the AI Database, which is accessed by USSN designers when they define models, with the goal of simplifying the USSN design activity. This serves as the basis for generating a new version of our ArchiMO design tool that includes the UECs. To illustrate our proposal, we use the newly generated ArchiMO to create a model in the MO domain. Furthermore, we use our self-developed domain-specific model compiler to produce the relevant simulation code. Throughout the design phase, our approach contributes to the handling and controling of the uncertainties and variances of the provided quality of service that may occur during the performance of the USSNs, as well as reducing the design activity’s complexity and time. It provides a way to share the different viewpoints of the designers in the domain of USSNs. Full article

Time series prediction is an effective tool for marine scientific research. The Hierarchical Temporal Memory (HTM) model has advantages over traditional recurrent neural network (RNN)-based models due to its online learning and prediction capabilities. Given that the neuronal structure of HTM is ill-equipped for the complexity of long-term marine time series applications, this study proposes a new, improved HTM model, incorporating Gated Recurrent Units (GRUs) neurons into the temporal memory algorithm to overcome this limitation. The capacities and advantages of the proposed model were tested and evaluated on time series data collected from the Xiaoqushan Seafloor Observatory in the East China Sea. The improved HTM model both outperforms the original one in short-term and long-term predictions and presents results with lower errors and better model stability than the GRU model, which is proficient in long-term predictions. The findings allow for the conclusion that the mechanism of online learning has certain advantages in predicting ocean observation data. Full article

The analysis of the 2002 Prestige tanker accident showed how public misinformation can worsen marine pollution incidents, rendering their management suboptimal as these evolve, thus raising the issue of appropriately informing and educating coastal and island populations who are at risk. Two decades later, developments in electronic platforms, including Geographic Information Systems (GIS), the Automatic Identification System (AIS) for ship signal transmission, and social media, provide a set of means for public monitoring of such incidents, creating the possibility to antagonise effectively erroneous or malevolent information, which can hinder efficient actions for containing marine pollution risks even without active training of the populations concerned. The authors, in the framework of the development of the Marine Coastal Observatory and Risk Management project “AEGIS+”, have developed E-S.A.V.E., an online innovative platform that (a) meets the needs of different users as revealed by a survey run across groups of them, (b) uses a suitable Geographic Information System (GIS) environment, (c) cooperates with public authorities, for the reliable update of automated systems, and (d) employs an artificial intelligence (AI)-supported tool for social media monitoring; the platform also provides educational resources and information on national and international resources on marine environmental protection and sustainable maritime logistics. Full article

In this work, we utilize space-based radar products from CloudSat mission and provide statistics on the properties of the clouds observed above the PANGEA (PANhellenic GEophysical observatory of Antikythera) observatory, located in the Eastern Mediterranean. We found that the variable atmospheric conditions that prevailed above the region in 2007–2017 resulted in complex cloud structures. From the clouds observed, 39.8% were low-level clouds formed at the top of the marine boundary layer (≤2 km), 34.2% were mid-level clouds (between 2–7 km), and 25.9% were high-level or deep convective clouds (between 7–15 km). Thin clouds (<1 km depth) are observed in 33% of the cases, while thick clouds (>6 km) in 15% of the cases. The results of this study can be used from regional and climate models to evaluate their cloud predictions and investigate the performance of different cloud microphysics schemes. Full article