North Sea Wave Database (NSWD)
The dataset contains each year of spectral metocean condition for Significant Wave Height (HSIGN) and wave energy period (TMM10), in meters and seconds.
Each variable has a year timestap which the data corresponds too i.e 1980. The latitudes and longitudes of the dataset have resolution of 0.025 degrees at each direction. Latitude starting coordinate is 50 degrees and Longitude 0.

For more information on the process that developed the dataset, the methodogies followed, calibration, valdiation and sensitivity analysis,
see:

Lavidas, G., & Polinder, H. (2019). North Sea Wave Database (NSWD) and the Need for Reliable Resource Data: A 38 Year Database for Metocean and Wave Energy Assessments. Atmosphere, 10(9), https://doi.org/10.3390/atmos10090551

Lavidas, G., & Polinder, H. (2019). Wind effects in the parametrisation of physical characteristics for a nearshore wave model. Proceedings of the 13th European Wave and Tidal Energy Conference 1-6 September 2019, Naples, Italy.

The dataset was produced by Dr George Lavidas during the WAVe Resource for Electrical Production (WAVREP, which received funding from the European Union's Horizon 2020 research & innovation programme under the Marie Sklodowska-Curie grant agreement No 787344.

The dataset is accompanied by two publication that (i) present the calibration-validation and production (ii) analysis of the dataset.

The official CORDIS website is https://cordis.europa.eu/project/id/787344
A list of outcomes for the NSWD and the WAVREP project is found at the researcher's page:
https://www.researchgate.net/project/WAVe-Resource-for-Electrical-Production-WAVREP

It can also be found at the official CORDIS website
https://cordis.europa.eu/project/id/787344

Sharing and Access information
Creative Commons Attribution (CC BY-SA).
The Creative Commons Attribution license allows others remix, tweak, and build upon your work, as long as they credit you and license their new creations under the identical terms.

The Pulse Wave Database

The Pulse Wave Database (PWDB) is a database of simulated arterial pulse waves designed to be representative of a sample of pulse waves measured from healthy adults. It contains pulse waves for 4,374 virtual subjects, aged from 25-75 years old (in 10 year increments). The database contains a baseline set of pulse waves for each of the six age groups, created using cardiovascular properties (such as heart rate and arterial stiffness) which are representative of healthy subjects at each age group. It also contains 728 further virtual subjects at each age group, in which each of the cardiovascular properties are varied within normal ranges. The entire database is available at DOI: 10.5281/zenodo.2633174 .

This dataset: baseline subjects aged 25 to 75

This dataset is a subset of the PWDB. It contains the pulse waves for the six baseline subjects aged 25 to 75 (in 10 year increments). It contains the following waves:

• arterial flow velocity (U),
• luminal area (A),
• pressure (P), and
• photoplethysmogram (PPG).

These pulse waves are provided at a range of measurement sites, including:

• aorta (ascending and descending)
• carotid artery
• brachial artery
• radial artery
• finger
• femoral artery

The data are available in three formats: Matlab, CSV and WaveForm Database (WFDB) format. Further details of the formatting and contents of each file are available at: https://github.com/peterhcharlton/pwdb/wiki/Using-the-Pulse-Wave-Database

Accompanying Publication

This is a subset of the PWDB database, which is described in the following publication:

Charlton P.H., Mariscal Harana, J., Vennin, S., Li, Y., Chowienczyk, P. & Alastruey, J., “Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices,” [under review]

Please cite this publication when using the database.

Further Information

Further information on the Pulse Wave Database project can be found at: https://peterhcharlton.github.io/pwdb/

Version History

Version 1.0 : provided for peer review of "Modelling arterial pulse waves in healthy ageing: a database for in silico evaluation of haemodynamics and pulse wave indices"

Provided here are the required input files to run a standalone wave model (Simulating Waves Nearshore [SWAN]; Booij and others, 1999) on eleven model domains from the Canada-U.S. border to Norton Sound, Alaska. The model runs create a downscaled wave database (DWDB) which, can be used to reconstruct hindcast, historical, or projected time series at each point in the model domains (see Engelstad and others, 2023 for further information on reconstruction of time-series). The model forcing files consist of reduced sets of binned wind and wave parameter combinations, hereafter termed ‘sea states’. The use of representative sea states allows for lower computational costs and follows modified methods outlined in for example Camus and others, 2011, Reguero and others, 2013, and Lucero and others, 2017. Wind and wave parameters were extracted from the ERA5 reanalysis (Hersbach and others, 2020; https://cds.climate.copernicus.eu/) for the hindcast period (1979–2019) and for the historical (1979-2014) and projected (2020-2050) time periods from WAVEWATCHIII wave model runs (Erikson and others, 2022) driven by winds and sea ice fields from the 6th generation Coupled Model Inter-comparison Projects (CMIP6 Haarsma and others, 2016 The extent of each model domain can be inferred from the browse graphic. Model input files are described in the Entity and Attribute Overview section.

The development of this dataset was funded by the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, Water Power Technologies Office to improve our understanding of the U.S. wave energy resource and to provide critical information for wave energy project development and wave energy converter design. This high resolution publicly available long-term wave hindcast dataset will - when complete - cover the entire U.S. Exclusive Economic Zone (EEZ). Available data includes the Hawaiian Islands, West and Atlantic coasts, Atlantic coasts, and Gulf of Mexico/Puerto Rico with future additions including the Freely associated States. The data can be used to investigate the historical record of wave statistics at any U.S. site. As such, the dataset could also be of value to any entity with marine operations inside the U.S. EEZ. These data are available for download without login credentials through the free and publicly accessible Open Energy Data Initiative (OEDI) data viewer which allows users to browse and download individual or groups of files.

The database includes 477 subjects (54% male, 46% female). Data were collected from three hospitals: the First Affiliated Hospital of Hunan University of Traditional Chinese Medicine, Liuyang Hospital of Traditional Chinese Medicine, and the Affiliated Hospital of Hunan University of Traditional Chinese Medicine, between 2016 and 2017, from individuals undergoing physical examinations. The data primarily consisted of pulse waveform signals, age, gender, systolic blood pressure, diastolic blood pressure, and BMI. This study utilized a pulse data acquisition device developed by the Chinese Academy of Medical Sciences (CACMS) (Patent No. 200810225717.0), which employs pressure sensors. The device is capable of simultaneously collecting pulse data from three channels on a single wrist at a sampling frequency of 1000 Hz. Additionally, the device automatically saves the data collected by the sensors to the local disk. Prior to testing, all participants rested for at least 3 minutes. Pulse data from six channels were then sequentially recorded, with each recording lasting approximately 30 seconds. During the test, participants were instructed to sit upright with their arms relaxed, ensuring that the core and position remained nearly level throughout the data collection process. The device also allows for adjustment of the contact pressure on the skin to obtain clear pulse data. For the purposes of this database, only the pulse data from a single channel was selected.

Near real time wave and sea surface temperature data for selected sites along the Queensland coast.

For more information please refer to www.qld.gov.au/waves.

Field names are;
Hs - Significant wave height, an average of the highest third of the waves in a record (26.6 minute recording period).
Hmax - The maximum wave height in the record.
Tz - The zero upcrossing wave period.
Tp- The peak energy wave period.
Peak Direction- Direction (related to true north) from which the peak period waves are coming from.
SST - Approximation of sea surface temperature.

The shear-wave splitting (SWS) databases data product provides the geosciences community with an easy access to two published databases:

• "The Géosciences Montpellier SplitLab sShear-wave splitting database":http://ds.iris.edu/ds/products/sws-db/
• "The Missouri University of Science and Technology (Missouri S&T) shear-wave splitting database":http://ds.iris.edu/ds/products/sws-db-mst/ for western and central United States

✓ ☁️ The SWS files are also available from the "EarthScope Data Archive":https://data.earthscope.org/archive/seismology/products/swsdb/README.html.

https://ds.iris.edu/spud/resources/images/spud.png" style="width:30px;"/> A query for the Splitlab Shear-wave splitting database is available on "SPUD":https://ds.iris.edu/spud/swsmeasurement

The DeRisk database is an extensive database of long-crested (2D) nonlinear wave kinematics for computation of extreme loads on offshore structures.The database was produced by running the nonlinear potential flow model OceanWave3D [1] on a gently sloping domain. The performed computations spanned a large parameter space, defined by nondimensional water depth, significant wave height and spectral peak period. A work containing a thorough description and validation of the current computations and of the database concept is currently under preparation [2].The DataBase is openly accessible under the conditions of the present license.Routines for interacting with the database, and usage examples are located at:https://gitlab.windenergy.dtu.dk/fabpi/deriskdatabase.git[1] Engsig-Karup, Allan Peter, Harry B. Bingham, and Ole Lindberg.(2009) "An efficient flexible-order model for 3D nonlinear water waves." Journal of computational physics 228.6 : 2100-2118.[2] Pierella, F., Lindberg, O., Bredmose, H., Bingham, H. B., Read, R. W., & Engsig-Karup, A. P. (2021). The derisk database: Extreme design waves for offshore wind turbines. Marine Structures, 80, 103046.

This provides a brief overview of the database. Further details are provided at: https://peterhcharlton.github.io/pwdb/ppwdb.html

Background: The shape of the arterial pulse wave (PW) is a rich source of information on cardiovascular (CV) health, since it is influenced by both the heart and the vasculature. Consequently, many algorithms have been proposed to estimate clinical parameters from PWs. However, it is difficult and costly to acquire comprehensive datasets with which to assess their performance. We are aiming to address this difficulty by creating a database of simulated PWs under a range of CV conditions, representative of a healthy population. The database provided here is an initial version which has already been used to gain some novel insights into haemodynamics.

Methods: Baseline PWs were simulated using 1D computational modelling. CV model parameters were varied across normal healthy ranges to simulate a sample of subjects for each age decade from 25 to 75 years. The model was extended to simulate photoplethysmographic (PPG) PWs at common measurement sites, in addition to the pressure (ABP), flow rate (Q), flow velocity (U) and diameter (D) PWs produced by the model.

Validation: The database was verified by comparing simulated PWs with in vivo PWs. Good agreement was observed, with age-related changes in blood pressure and wave morphology well reproduced.

Conclusion: This database is a valuable resource for development and pre-clinical assessment of PW analysis algorithms. It is particularly useful because it contains several types of PWs at multiple measurement sites, and the exact CV conditions which generated each PW are known.

Future work: However, there are two limitations: (i) the database does not exhibit the wide variation in cardiovascular properties observed across a population sample; and (ii) the methods used to model changes with age have been improved since creating this initial version. Therefore, we are currently creating a more comprehensive database which addresses these limitations.

Accompanying Presentation: This database was originally presented at the BioMedEng18 Conference. The presentation describing the methods for creating the database, and providing an introduction to the database, is available at: https://www.youtube.com/watch?v=X8aPZFs8c08 . The accompanying abstract is available here.

Accompanying Manual: Further information on how to use the PWDB datasets, including this preliminary dataset, are provided in the user manual. Further details on the contents of the dataset files are available here.

Citation: When using this dataset please cite this publication:

Charlton P.H. et al. Modelling arterial pulse wave propagation during healthy ageing, In World Congress of Biomechanics 2018, Dublin, Ireland, 2018.

Version History:

• v.1.0: Originally uploaded to PhysioNet. This is the version which was used in the accompanying presentation.

• v.2.0: The initial upload to this DOI. The database was curated using the PWDB Algorithms v.0.1.1. It differs slightly from the originally reported version in that: (i) the augmentation pressure and index were calculated at the aortic root rather than the carotid artery.

Text adapted from: Charlton P.H. et al., 'A database for the development of pulse wave analysis algorithms', BioMedEng18, London, 2018.

Wave statistics computed using output from the NOAA WWIII hindcast simulations, spanning thirty years from 1980 to 2009. The statistics are computed based on frequency-directional variance density spectra every three hours for 1951 locations in US waters.

Modeled wave time series data from a downscaled wave database (DWDB)are presented for the hindcast period of 1979 to 2023 from the U.S. Canada border to Norton Sound close to the 5 and 10 m isobaths. Outputs include three-hourly nearshore significant wave heights (Hs), mean wave periods (Tm) and mean wave directions (Dm) for 8485 (5 m isobath) and 8232 (10 m isobath) locations. Data are available as netCDF files and are packaged for the Beaufort Sea region from the U.S. Canada border to Nuwuk (Point Barrow), for the Chukchi Sea region from Nuwuk to Kotzebue Sound and from Kotzebue Sound to the Bering Strait, and from the Bering Strait to the southern boundary of Norton Sound. The methods used to create this dataset are described in detail in Engelstad and others, 2024

This provides a link to the version of the Pulse Wave Database which was made available through PhysioNet for the purposes of peer review.This database of simulated arterial pulse waves is designed to be representative of a sample of pulse waves measured from healthy adults. It will contain pulse waves for 4,374 virtual subjects, aged from 25-75 years old (in 10 year increments). The database will contain a baseline set of pulse waves for each of the six age groups, which was created using cardiovascular properties (such as heart rate and arterial stiffness) which are representative of healthy subjects at each age group. It will also contain 728 further virtual subjects at each age group, in which each of the cardiovascular properties are varied within normal ranges. This allows for extensive in silico analyses of the performance of pulse wave analysis algorithms.

Measured and derived wave parameters from data collected by a wave monitoring buoy anchored at Palm Beach. For more information, please refer to www.qld.gov.au/waves.

Field names are; Hs - Significant wave height, an average of the highest third of the waves in a record (26.6 minute recording period). Hmax - The maximum wave height in the record. Tz - The zero upcrossing wave period. Tp - The peak energy wave period. Peak Direction - Direction (related to true north) from which the peak period waves are coming from. SST - Sea Surface Temperature as measured by a sensor embedded in the hull of the buoy.

Historically measured/calculated wave parameters. Measured and derived wave data from data collected by oceanographic wave measuring buoys anchored at locations on the Queensland coastline.
For more information please refer to www.qld.gov.au/waves.

Field names are;
Hs - Significant wave height, an average of the highest third of the waves in a record (26.6 minute recording period).
Hmax - The maximum wave height in the record.
Tz - The zero upcrossing wave period.
Tp - The peak energy wave period.
Dir_Tp TRUE - Direction (related to true north) from which the peak period waves are coming from.
SST - Approximation of sea surface temperature.

this data set is the result of calculating the anomalies of the ocean wave parameters from the waverys product (global_multiyear_wav_001_032), which makes it easier for researchers to carry out studies related to climate change, cold fronts, hurricanes and other physical processes. in the caribbean sea. various existing sources were used, such as model output data, analysis, reanalysis, and satellite observed data, as well as the dataset with combined data sources.

Measured and derived wave parameters from data collected by a wave monitoring buoy anchored at Albatross Bay. This site is jointly operated by the Department of Environment and Science, and the North Queensland Bulk Ports (NQBP).
For more information please refer to www.qld.gov.au/waves.

Field names;
Hs - Significant wave height, an average of the highest third of the waves in a record (26.6 minute recording period).
Hmax - The maximum wave height in the record.
Tz - The zero upcrossing wave period.
Tp - The peak energy wave period.
Peak Direction - Direction (related to true north) from which the peak period waves are coming from.
SST - Sea Surface Temperature as measured by a sensor embedded in the bottom of the hull of the buoy.

The database of costs is a list of costs related to the commercialisation of a wave energy farm. The costs are collected in an Excel sheet divided into categories. This collection of costs is intended to be used in LCoE calculations. The data has been gathered through a thorough literature review.

Wave recorders have been operated on 11 positions along the west coast of Denmark. At present recorders are operated on 7 positions. On three of these positions the recorders are only operated in the winter period.

The purpose of collecting these data is to provide a basis for forecasting, mathematical modelling, statistics, and planning.

This dataset presents projected hourly time-series of wave heights, wave periods, incident wave directions, and directional spreading at distinct points along the U.S. Atlantic, Gulf of Mexico, and Puerto Rico coasts for the years 2020 through 2050. The projections were developed by running the National Oceanic and Atmospheric Administration’s (NOAA’s) WAVEWATCHIII model. Wind and sea ice fields from seven different Global Climate or General Circulation Models from the CMIP6 High-Resolution Model Intercomparison Project were used to simulate waves across the globe at a 0.5-degree resolution (approximately 50 kms, depending on latitude) and further downscaled to 10- (approximately 18 km) and 4-arc-minute (approximately 7 km) model grids. Point model output data extracted from NOAA’s 4-arc-minute grid for the Gulf of Mexico and NW Atlantic (at_4m) are provided herein.

This database is a deliverable of the FLOATECH project, funded under the European Union's Horizon 2020 research and innovation program under grant agreement No 101007142. The aim of the accompanying document is to describe the experimental testing campaign C2 at the LHEEA wave-tank facility. The campaign took place between May and June 2023. The objective of the campaign is to test several FOWT control strategy, including a feed forward wave-based control, using the software-in-the-loop SOFTWIND system. The accompanying report on the E.U. portal describes the database created from these experiments and aimed to be shared for model validation.