AndreaBozzo/ceres-open-data-index huggingface dataset:
Dataset for concurrent echosounder and ADCP measurements at a tidal energy candidate site in Australia

Interaction uncertainties between tidal energy devices and marine animals have the potential to disrupt the tidal energy industry as it advances. Best-practices for environmental impact assessments (EIAs) must be explored that are able to provide conclusive recommendations for mitigating environmental impact concerns of tidal energy developments. As the tidal energy industry is moving closer to commercial-scale array installations, the development of standardised EIAs would allow for potential impact concerns for the marine environment to be identified and minimised early in the site-development process. In an effort to help formulate a standardised EIA framework that addresses knowledge gaps in fish-current interactions at tidal energy candidate sites, this study investigated changes in fish aggregations in response to tidal currents at a tidal energy candidate site in Australia prior to turbine installation. Here, we present the dataset collected for this study that includes tidal current information from Acoustic Doppler Current Profiler (ADCP) measurements, volume backscattering strength from a four-frequency biological echosounder (Acoustic Zooplankton and Fish Profiler – AZFP) as an indicator for fish biomass, and fish aggregation metrics calculated from volume backscatter in post-processing. ADCP and AZFP were installed on a bottom-mounted mooring and engaged in a concurrent sampling plan for ~2.5 months from December 2018 to February 2019. The mooring was deployed in the Banks Strait, a tidal energy candidate site located in the northeast of Tasmania, Australia, at a location favourable for tidal turbine installations considering current speed, depth, substrate, sediment type and proximity to shore. The ADCP dataset includes current velocity and direction measurements at a 1 m vertical and 1-sec time intervals. The raw AZFP dataset includes volume backscattering strength collected at 4-sec time intervals with a vertical resolution of 0.072 m in raw, and 0.1 m in pre-processed form. Fish aggregation metrics were derived in post-processing and are presented by the minute along with corresponding environmental conditions for current speed, shear, temperature, diel stage, and tidal stage compiled from both AZFP and ADCP datasets.

Tags: ADCP, AZFP, Australian Tidal Energy, Concurrent measurements, Environmental monitoring, Fish aggregation, Hydroacoustics, Tidal resource assessment
Organization: Australian Ocean Data Network
AUSTEn Clarence Strait Casts

The AUStralian Tidal Energy (AUSTEn) project was a three year project (2018 - 2020) funded by the Australian Renewable Energy National Agency (agreement number G00902) led by the Australian Maritime College (University of Tasmania), in partnership with CSIRO and University of Queensland. The project had a strong industry support (Atlantis Resources Limited, MAKO Tidal Turbines Ltd, Spiral Energy Corporation Ltd). The aim of the project was to assess the technical and economic feasibility of tidal energy in Australia, based on the best understanding of resource achievable. For further information and output of the project, please visit the AUSTEn project website www.austen.org.au.

Organization: Australian Ocean Data Network
A pilot management program to maximise Tasmania's Sea Urchin (Heliocidaris erythrogramma) resource: Hope Island, urchin density manipulations

The main aim of this research program was to determine the potential for reducing the density of urchins to encourage the return of seaweeds and an improvement in urchin roe quality and quantity from remaining urchins. Tasmanian Sea Urchin Developments used two widely-separated sub-tidal experimental lease areas. One of these areas was at Meredith Point, on the east coast, and the other at Hope Island, on the south coast. Both sites had been subject to some overgrazing by urchins. At Meredith Point, the study area was divided into plots containing urchins at three densities: artificially enhanced, continually harvested and control (undisturbed). At Hope Island, controlled clearings of urchins and limpets from barrens areas were conducted. Recovery of vegetation was monitored as well as urchin roe quality and quantity. The data represented by this record was collected at Hope Island, and includes results from an inital survey collected at the site before the main study commenced.

Tags: Algal coverage, Heliocidaris erythrogramma, Macrocystis pyrifera, Management, Substrate coverage, Temperate Reef, Urchin roe
Organization: Australian Ocean Data Network
Climate mode datasets and generating codes from CMIP6 pre-Industrial control simulations and observations

Internal climate variability encompasses processes ranging from daily weather fluctuations to multidecadal interactions within the climate system.  Understanding these processes is crucial for distinguishing natural variability from human-induced climate change.  A large component of internal variability on sub-seasonal to multi-decadal time scales are associated with recurring patterns or ‘climate modes’. 

Using pre-industrial control (piControl) simulations from the Coupled Model Intercomparison Project Phase 6 (CMIP6), we investigate eight critical climate modes: Eastern Pacific El Niño (EP-El Niño), Central Pacific El Niño (CP-El Niño), Interdecadal Pacific Oscillation (IPO), Indian Ocean Dipole (IOD), Subsurface Dipole Mode (SDM), Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), and Southern Annular Mode (SAM). These modes were derived from 23 CMIP6 models, each with over 500 years of simulation data, ensuring robust statistical insights into their spatial and temporal structures. The datasets were validated against observational data, revealing broad-scale consistency and highlighting biases in regional features and amplitudes. For example, the models effectively capture spatial patterns such as the tripolar SST anomaly of the IPO and the equatorial Pacific warming of EP-El Niño.  However, regional discrepancies, like exaggerated warming or cooling in specific areas, were observed. Despite these biases, the datasets provide critical tools for understanding climate variability, conducting detection and attribution studies, and improving climate projections. Details regarding the generated NetCDF files are provided in the accompanying README file.

All datasets are publicly accessible (https://doi.org/10.5281/zenodo.17274477, and additionally linked to this record), supporting future research and policy development to address climate variability and its implications for climate change adaptation and mitigation.

Tags: Atmospheric Dynamics, CMIP6 Pre Industrial Control simulation datasets, Climate Change Processes, Climate Mode Indices, Ocean and Atmospheric Climate Modes, Physical Oceanography, climate mode, internal variability
Organization: Australian Ocean Data Network
IMOS - Satellite Remote Sensing - Surface Waves Sub-Facility - SAR wind - Delayed mode data

Sentinel-1 A, B and C satellites are part of Europe's Copernicus Earth Observation program and carry identical C-band Synthetic Aperture Radar (SAR) instruments. This dataset contains 10m neutral stability wind speed and direction derived from Sentinel-1 A, B and C SARs in the wider Australian coastal regions. In these regions, the satellites normally operate in interferometric wide (IW) swath mode. The winds are derived using a consistent geophysical model function (gmf), CMOD5N, and variational Bayesian inversion approach as proposed in Portabella et al. (2002) and Sentinel-1 Ocean wind (owi) algorithm definition document. The input SAR and model (ECMWF) data used in the inversion are sourced from owi level-2 product, and the resulting derived winds are approximately at 1km horizontal spatial resolution as in the source product but derived using a consistent gmf over time (unlike the source product). Wind speeds are also calibrated against Metop-A and B scatterometer wind database of Ribal and Young, 2020 (JTECH).

This data has also been combined and interpolated to a nominal 0.01 x 0.01-degree regular grid (available as a separate gridded product: IMOS - Satellite Remote Sensing - Surface Waves Sub-Facility - Gridded SAR wind - Delayed mode data). 

The data represented by this record, are presented in delayed mode.

Tags: Global / Oceans | Indian Ocean, Global / Oceans | Pacific Ocean, Global / Oceans | Southern Ocean, Marine Features (Australia) | Great Australian Bight, SA/WA, Oceans | Ocean Winds | Surface Winds, Regional Seas | Andaman Sea, Regional Seas | Arafura Sea, Regional Seas | Banda Sea, Regional Seas | Celebes Sea, Regional Seas | Coral Sea, Regional Seas | Gulf of Thailand, Regional Seas | Philippine Sea, Regional Seas | Solomon Sea, Regional Seas | South China Sea, Regional Seas | Tasman Sea
Organization: Australian Ocean Data Network
ETAS (Eastern TASmania) Ocean Model Output - Eastward and Northward Currents

The ETAS (Eastern TASmania) model is a high-resolution (~2 km in the horizontal) ocean model for eastern Tasmania, providing three-dimensional estimates of daily temperature, salinity, and circulation over the 1993-2014 period. This dataset consists of eastward (u) and northward (v) currents organised into yearly files.

Tags: Climatology (excl. Climate Change Processes), Eastward component of bottom current deviation, Eastward component of current, Latitude at cell centre, Longitude at cell centre, Northward component of bottom current deviation, Northward component of current, Physical Oceanography, Time, Z coordinate at grid layer faces
Organization: Australian Ocean Data Network
NESP TWQ Project 4.1 - Crown-of-thorns starfish: surveillance and life history, 2018-2019 (CSIRO)

This project supports the implementation of the NESP Crown-of-Thorns Starfish Integrated Pest Management Project’s management and research strategy by;

i) describing ecological parameters key to parameterizing the tools underpinning the management strategy;
ii) analysing existing data sets to assess management performance and describe the interaction between CoTS and bleaching; and
iii) scoping new technologies and surveillance strategies for detecting and monitoring primary and secondary outbreaks. 

The work will involve a combination of field ecological research, statistical analysis of existing data, technology and strategy development (the latter through workshops) and inform decision making through incorporation into decision support tools and recommendations.

Tags: National Environmental Science Programme Tropical Water Quality (NESP TWQ) hub, marine
Organization: Australian Ocean Data Network
Wet Tropics of Queensland World Heritage Area Zoning Scheme 1998 (WTMA)

This dataset contains polygon features that represent the zoning classification of lands within the Wet Tropics World Heritage Area. This dataset is a working depiction only.

For legal confirmation, refer to signed maps held at WTMA. The official zoning maps for the Wet Tropics of Queensland World Heritage Area can be downloaded from http://www.wettropics.gov.au/zoning-maps

The zoning maps are an essential element of the Wet Tropics Management Plan 1998. The zoning maps depict four zones (A, B, C and D), based on distance from disturbance model and catering for community services infrastructure and developed visitor facilities. The zones have different degrees of integrity, different physical and social settings and different management purposes. The zoning scheme allows different types of activities in each zone, in accordance with the management intent and integrity of the zone.



Zone A: Land included in zone A has a high degree of integrity and is remote from the disturbances associated with modern technological society.

Zone B: High degree of ecological integrity and it is in a natural state but is not necessarily remote from disturbance.

Zone C: Land in zone C already contains disturbances, which are often associated with existing community infrastructure.

Zone D: Zone D contains lands where there are, or may be, visitor facilities of a well-developed type.


For information about zoning see http://www.wettropics.gov.au/wha-zoning

The Wet Tropics Management Plan 1998, including the zoning is currently under review http://www.wettropics.gov.au/wet-tropics-plan-review

This metadata was prepared for the eAtlas and is not authoritative. Please contact the Wet Tropics Management Authority for an authoritative record.

Organization: Australian Ocean Data Network
NSW Nearshore Wave Buoy Data (2016 - 2023)

Wind wave observations in shallow coastal waters are essential for calibrating, validating, and improving numerical wave models to predict sediment transport, shoreline change, and coastal hazards such as beach erosion and oceanic inundation. Nearshore wave conditions may vary considerably alongshore, for the same offshore wave condition, due to coastline orientation and shape, bathymetry and islands. 

This data descriptor includes a snapshot of an ongoing dataset of in-situ wave buoy observations from shallow waters (&lt; 35 m) in New South Wales, Australia. By the end of 2023 that dataset comprised over 7,000 days of wave measurements at 20 locations. Temporarily moored GPS/GNSS wave buoys have been used to measure wave conditions continuously for several months to multiple years at each location, capturing ambient and storm conditions in diverse settings, including coastal hazard risk sites. The dataset includes time series of standard spectral and time-domain parameters describing wave height, period and direction at half-hourly temporal resolution. Buoy displacement data and wave spectra data are also provided for advanced applications. The nearshore wave data will interest coastal oceanography and processes researchers and practitioners. The data have been collected and processed by the NSW Government Environment Coastal and Marine Science team.

A snapshot of this data (up to 18/01/2024) has been assigned a DOI and will be maintained in perpetuity by the Australian Ocean Data Network (AODN). The ongoing version of this dataset is freely available through the National Wave Archive on the AODN Portal (https://catalogue-imos.aodn.org.au:443/geonetwork/srv/api/records/2807f3aa-4db0-4924-b64b-354ae8c10b58) – follow the link and access the ‘NetCDF files via THREDDS catalog (NSW-DPE)’ dataset.

Tags: Coastal Cities / Towns (Australia) | Byron Bay, NSW, Coastal Cities / Towns (Australia) | Coffs Harbour, NSW, Coastal Cities / Towns (Australia) | Eden, NSW, Coastal Cities / Towns (Australia) | Port Kembla, NSW, Coastal Cities / Towns (Australia) | Sydney, NSW, Coastal Waters (Australia) | New South Wales Coast, NSW, Global / Oceans | Pacific Ocean, Global / Oceans | South West Pacific Ocean, Marine Features (Australia) | Batemans Bay, NSW, Oceans | Ocean Waves | Significant Wave Height, Oceans | Ocean Waves | Wave Period, Oceans | Ocean Waves | Wave Spectra, Oceans | Ocean Waves | Wave Speed/direction, Regional Seas | Coral Sea, Regional Seas | Tasman Sea
Organization: Australian Ocean Data Network
Oceanic Shoals Commonwealth Marine Reserve - Predicted pelagic diversity

This dataset provides predictions of pelagic vertebrate species richness and relative abundance throughout sub-areas of the Oceanic Shoals Australian Marine Park (AMP). Predictive models were constructed from in situ observations made using mid-water stereo-BRUVS (baited remote underwater video systems) deployed at 116 sites within three sampling areas in the western half of the AMP. Sampling took place in September and October 2012 aboard the RV Solander (survey GA0339/SOL5650), as part of an expedition supported by the National Environmental Research Programme's Marine Biodiversity Hub (Theme 3). Expedition partners included the Australian Institute of Marine Science (AIMS), Geoscience Australia (GA), The Centre for Marine Futures at the University of Western Australia (UWA), and the Northern Territory Museum. Full methodological details can be found in the following peer-reviewed publication: Bouchet, P.J., Letessier, T.B., Caley, M.J., Nichol, S.L., Hemmi, J.M., Meeuwig, J. (2020). Submerged carbonate banks aggregate pelagic megafauna in offshore tropical Australia. Front. Mar. Sci. doi: 10.3389/fmars.2020.00530

Tags: ABUNDANCE, BIOGEOGRAPHY, HOTSPOTS, KILLER WHALES, PELAGIC FISHES, RAYS, SHARKS, SPECIES RICHNESS, TURTLES, WILDLIFE DISTRIBUTION
Organization: Australian Ocean Data Network
D6 Socio-economic benchmark nationally modelled recreational fishing effort

The data represents the results of a national model of boat-based recreational fishing effort (number of trips) around Australia. The model reflects boat-based line fishing trips in marine waters and is reported on a 5x5 nautical mile grid to a distance of 100 km from the Australian coastline. The model includes two parts: (i) allocation of fishing trips from a reporting region to individual boat ramps and (ii) allocation of fishing trips from boat ramps to adjacent marine waters.

Raw fishing effort data could not be made available. Aggregated effort data is supplied as summary plots in the final report: https://www.nespmarine.edu.au/document/social-and-economic-benchmarks-australian-marine-parks

Organization: Australian Ocean Data Network
IMOS - Satellite Remote Sensing - NOAA20 - 01 day - Optical Water Type (Moore et al 2009 algorithm)

The NOAA20 satellite platform carries a VIIRS sensor that observes sunlight reflected from within the ocean surface layer at multiple wavelengths. These measurements at discrete wavelengths represent the spectrum of light leaving the water surface, and the shape of the spectrum is characteristic of the water optical properties. 

Moore et al. (2009, RSE, 113, pp2424-2430, doi:10.1016/j.rse.2009.07.016) applied a clustering technique to spectra to identify 8 sets of discrete optical water types for data from the MODIS sensor. This product "owtd_csiro" is produced using a CSIRO implementation of the Moore et al. algorithm, and testing shows that it closely reproduces the results of the original Moore et al implementation in the NASA SeaDAS package.  The CSIRO implementation was created because the implementation in SeaDAS has not been kept up to date, and to extend the product to the VIIRS sensor.

Tags: Countries | Australia, Countries | Fiji, Countries | Indonesia, Countries | Malaysia, Countries | New Caledonia, Countries | New Zealand, Countries | Papua New Guinea, Countries | Philippines, Countries | Timor-Leste, Countries | Vanuatu, Global / Oceans | Indian Ocean, Global / Oceans | Pacific Ocean, Global / Oceans | Southern Ocean, Marine Features (Australia) | Bass Strait, TAS/VIC, Marine Features (Australia) | Great Australian Bight, SA/WA, Oceans | Ocean Optics | Ocean Color, Regional Seas | Arafura Sea, Regional Seas | Banda Sea, Regional Seas | Celebes Sea, Regional Seas | Coral Sea, Regional Seas | Java Sea, Regional Seas | Philippine Sea, Regional Seas | Solomon Sea, Regional Seas | Tasman Sea, Regional Seas | Timor Sea, States, Territories (Australia) | New South Wales, States, Territories (Australia) | Northern Territory, States, Territories (Australia) | Queensland, States, Territories (Australia) | South Australia, States, Territories (Australia) | Tasmania, States, Territories (Australia) | Victoria, States, Territories (Australia) | Western Australia
Organization: Australian Ocean Data Network
Satellite Relay Tagging Program - Southern Ocean - MEOP Quality Controlled CTD Profiles

CTD (Conductivity-Temperature_Depth)-Satellite Relay Data Loggers (CTD-SRDLs) are used to explore how marine animal behaviour relates to their oceanic environment. Loggers developed at the University of St Andrews Sea Mammal Research Unit transmit data in near real-time via the Argo satellite system. Data represented here was collected in the Southern Ocean, from elephant, fur and Weddell Seals. In 2024 data was added from flatback and olive ridley turtles, from a pilot study co-funded by the Royal Australian Navy in collaboration with the Australian Institute of Marine Science and Indigenous Ranger groups.

Data parameters measured by the instruments include time, conductivity (salinity), temperature, pressure and depth. The data represented by this record have been Qc'd and are the Australian subset of the MEOP-CTD database (MEOP: Marine Mammals Exploring the Oceans Pole to Pole), complemented with the most recent Southern Ocean deployment data. This Australian subset of the Southern Ocean database represents about one quarter of the entire MEOP-CTD database, which currently is about 52,000 profiles obtained from 275 CTD-SRDL tag deployments. The Australian dataset originated in 2004, and was initially collected by Mark Hindell's team based at the University of Tasmania, and in later years his data has formed part of the Animal Tracking Facility of Integrated Marine Observing System (IMOS).

Tags: Agency | SMRU | Sea Mammal Research Unit, CTD Satellite Relay Data Logger, Continents | Antarctica, Countries | Australia, Countries | Australia (including external territories), Countries | Indonesia, Countries | New Zealand, Global / Oceans | Atlantic Ocean, Global / Oceans | Indian Ocean, Global / Oceans | Pacific Ocean, Global / Oceans | Southern Ocean, Marine Features (Australia) | Bass Strait, TAS/VIC, Oceans | Marine Biology | Marine Mammals, Oceans | Marine Biology | Marine Reptiles, Oceans | Ocean Temperature | Water Temperature, Oceans | Salinity/density | Conductivity, Offshore Islands (Australia) | Heard & McDonald Islands, Offshore Islands (Australia) | Macquarie Island, Regional Seas | Arafura Sea, Regional Seas | Tasman Sea, Regional Seas | Timor Sea, States, Territories (Australia) | New South Wales, States, Territories (Australia) | Northern Territory, States, Territories (Australia) | Queensland, States, Territories (Australia) | Tasmania, States, Territories (Australia) | Victoria, Tags and Tracking Devices
Organization: Australian Ocean Data Network