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34 results for “Internal waves”
Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves_for JGR submission
<p>This folder contains preprocessed data, data processing scripts, Reynolds Averaged Navier Stokes (RANS) simulation scripts, and plotting scripts that produce the results in the manuscript entitled, "Observations of the Bottom Boundary Layer beneath the World's Largest Internal Solitary Waves," for submission to Journal of Geophysical Research Oceans by Trowbridge, Helfrich, Reeder, Medley, Chang, Jan, Ramp, and Yang.</p> <p> </p>
DATA SET: Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial
<p>This repository contains the data sets related to the publication:</p> <p>Cortese, L.; Zanoletti, M.; Karadeniz, U.; Pagliazzi, M.; Yaqub, M.A.; Busch, D.R.; Mesquida, J.; Durduran, T. Performance Assessment of a Commercial Continuous-Wave Near-Infrared Spectroscopy Tissue Oximeter for Suitability for Use in an International, Multi-Center Clinical Trial. <em>Sensors</em> <strong>2021</strong>, <em>21</em>, 6957. https://doi.org/10.3390/s21216957</p>
Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars
<p>Supporting data for peer-reviewed publication entitled: 'Photometric detection of internal gravity waves in upper main-sequence stars. IV. Comparable stochastic low-frequency variability in SMC, LMC, and Galactic massive stars', published in A&A. For the purpose of open access, the authors have applied a CC BY licence to the author accepted manuscript version and made it publicly available: <a href="https://arxiv.org/abs/2410.12726">https://arxiv.org/abs/2410.12726</a></p> <p>Evolutionary models and stability window calculations courtesy of Jermyn et al. 2022 (DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-4357/ac4e89">10.3847/1538-4357/ac4e89</a>) are publicly available via: <a href="https://github.com/adamjermyn/conv_trends">https://github.com/adamjermyn/conv_trends</a></p> <p>TESS full-frame image data are publicly available from the Mikulski Archive for Space Telescopes (MAST) at the Space Telescope Science Institute (STScI): <a href="https://archive.stsci.edu/missions-and-data/tess">https://archive.stsci.edu/missions-and-data/tess</a></p> <p>TESS light curves (provided in this repository) were extracted using the publicly available tglc (Han & Brandt 2023; DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-3881/acaaa7">10.3847/1538-3881/acaaa7</a>) software package: <a href="https://github.com/TeHanHunter/TESS_Gaia_Light_Curve">https://github.com/TeHanHunter/TESS_Gaia_Light_Curve </a></p> <p>SLF variability parameters (provided in this repository; cf. Tables 1 and 2 of the paper) were obtained using GP regression with the publicly available celerite2 (Foreman-Mackey et al. 2017; DOI: <a href="https://iopscience.iop.org/article/10.3847/1538-3881/aa9332">10.3847/1538-3881/aa9332</a>) software package: <a href="https://celerite2.readthedocs.io/en/latest/">https://celerite2.readthedocs.io/en/latest/</a> and confidence intervals were obtained using the publicly available pymc3 (Salvatier et al. 2016; <a href="https://doi.org/10.7717/peerj-cs.55">https://doi.org/10.7717/peerj-cs.55</a>) software package: <a href="https://github.com/pymc-devs/pymc">https://github.com/pymc-devs/pymc</a></p> <p>This research was supported in part by the National Science Foundation (NSF) under Grant Number NSF PHY-1748958; the Research Foundation Flanders (FWO) with grant agreement numbers 1286521N, 11F7120N, and V411621N; UK Research and Innovation (UKRI) in the form of a Frontier Research grant under the UK government's ERC Horizon Europe funding guarantee (SYMPHONY; grant number: EP/Y031059/1); a Royal Society University Research Fellowship (URF; grant number: URF\R1\231631); and the KU Leuven Research Council (grant number C16/18/005: PARADISE).</p>
Maintenance of Convectively Coupled Kelvin waves: Relative Importance of Internal Thermodynamic Feedback and External Momentum Forcing (Code and Data)
<p>This is the dataset and code for generating all figures for the journal article named "Maintenance of Convectively Coupled Kelvin Waves: Relative Importance of Internal Thermodynamic Feedback and External Momentum Forcing," The article was written by Mu-Ting Chien and Daehyun Kim and submitted to Geophysical Research Letters in 2024.</p>
Processed data supporting figures in Yang et al. 2023: Oceanic eddies induce a rapid formation of an internal wave continuum
<p>This data repository supports a manuscript by Luwei Yang, Roy Barkan, Kaushik Srinivasan, James C. McWilliams, Callum J. Shakespeare, and Angus H. Gibson, submitted to <em>Communications Earth & Environment</em>. This repository contains the processed data that support the figures in the manuscript. </p>
BUBS Pilbara internal waves and mixing study
<p>Repository for the data presented in the JGR 2018 article: "Quantifying diapycnal mixing in an energetic ocean". A second repository (DOI) was generated to upload additional parameters from the same observations submitted for publication elsewhere.</p>
Global characterization of the ocean's internal gravity wave vertical wavenumber spectrum from Argo float profiles
<p>Oceanic internal gravity wave energy levels E (m^2/s^2), vertical wavenumber spectral slopes s, and vertical wavenumber scale m* (1/m) estimated by fitting the Garrett Munk model vertical wavenumber shape function to strain spectra obtained from Argo float hydrographic profiles based on the finestructure method, as discussed in Pollmann (2020): "Global Characterization of the Ocean’s Internal Wave Spectrum" (<em>Journal of Physical Oceanography</em> 50.7: 1871-1891). The paper and hence this dataset are a contribution to the Collaborative Research Centre TRR181 ‘Energy Transfers in Atmosphere and Ocean’ funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation)—Projektnummer 274762653. The hydrographic profiles used in this study were collected and made freely available by the International Argo Program and the national programs that contribute to it (http://www.argo.ucsd.edu, http://argo.jcommops.org). The Argo Program is part of the Global Ocean Observing System.</p> <p>Please cite Pollmann (2020) when using this dataset.</p> <p>This dataset includes:</p> <p>a) energy density (m^2/s^2) binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>b) vertical wavenumber spectral slopes binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>c) vertical wavenumber scale m* (1/m) binned into 1°x1° horizontal bins and averaged into 3 depth bins (300-500 m, 500-1000 m, 1000-2000 m)</p> <p>d) latitude and longitude, defined such that, e.g., E(10,10) represents energy levels in the bin bounded by lat(10), lat(11) as well as lon(10), lon(11)</p>
Remote internal wave forcing of regional ocean simulations near the U.S. West Coast
<p>This dataset contains data from ROMS simulations near the U.S. West Coast with realistic atmospheric forcing, tidal forcing and remote internal wave forcing. FS800b has remote internal wave forcing while FS800a does not have remote internal wave forcing at the open boundaries. The ROMS simulations have 4-km horizontal resolution and 60 sigma-layers. All data is along the local x- and y- axis of the rotated C-grid. Data is stored in netcdf format. We also include the altimeter dataset (see Buijsman et al., 2020; doi: 10.1016/j.ocemod.2020.101656) used in validating the semidiurnal internal tides.</p> <p>More details and context of this data can be found in the article: https://doi.org/10.1016/j.ocemod.2022.102154 . Please cite this article along with any use of this data.</p> <p>Siyanbola, O.Q., Buijsman, M.C., Delpech, A., Renault, L., Barkan, R., Shriver, J.F., Arbic, B.K., & McWilliams, J.C. (2023). Remote internal wave forcing of regional ocean simulations near the U.S. West Coast, <strong><em>Journal of Ocean Modelling</em></strong>, <strong><em>181</em></strong>, 18 p.</p>
Data from: Effects of topography and Earth's rotation on the oblique interaction of internal solitary-like waves in the Andaman Sea
<p>This is a modeled data set from the paper:</p> <p>Shimizu, K., and K. Nakayama (2017), Effects of topography and Earth's rotation on the oblique interaction of internal solitary-like waves in the Andaman Sea, Journal of Geophysical Research - Oceans, 122, doi:10.1002/2017JC012888</p> <p>This data set includes results of MITgcm internal solitary-like wave (ISW) simulations in the Andaman Sea, and data derived from them. The model was run at two horizontal resolutions (0.005 and 0.0025 degree resolution) and three cases for the Coriolis effects (Full, Traditional, and No Coriolis). Please refer to the paper for the methods and data used to produce this data set.</p>
Internal gravity waves generated by subglacial discharge: Implications for tidewater glacier melt.
<p>Additional data used in the paper titled "Internal gravity waves generated by subglacial discharge: implications for tidewater glacier melt", submitted to Geophysical Research Letters, that is not already contained in the GitHub repository.</p>
Data files for Atmospheric Gravity Wave and Instability Observations from the International Space Station using the Near InfraRed Airglow Camera (NIRAC)
<p>The files in this set are data obtained from the NIRAC airglow imager on the International Space Station. The files are named for a JGR paper by J. Hecht et al. entitled Atmospheric Gravity Wave and Instability Observations from the International Space Station using the Near InfraRed Airglow Camera (NIRAC). These files are for plots in Figures 5,7,10,11,17,18, and 19 in the submitted paper. The files are published here so as to be available for review. This paper should appear in JGR Atmospheres sometime in late 2023 or early 2024. The files that are text files are meant to be read with IDL as discussed in the readme file. </p>
Internal gravity waves in a three solar mass star
<p>The movie shows the horizontal velocity (left) and horizontal temperature fluctuations (right) for the 2D hydrodynamical simulation of a three solar mass star at the zero-age main sequence. Both quantities are scaled by their respective horizontal mean value to account for the different amplitudes in the inner (lower amplitudes) and outer (higher amplitudes) parts of the model. The magnified regions show the convective core. The simulation has been performed with the fully compressible, time-implicit <a href="http://slh-code.org">Seven-League Hydro (SLH)</a> code.</p>
Insights into Internal Solitary Waves East of Dongsha Atoll from Integrating Geostationary Satellite and Mooring Observations
<p>The dataset used to produce the figures in the manuscript. All the data are in MATLAB file format. </p>
Data from: Fundamental properties of adjoint model and adjoint sensitivity under fully-nonlinear hydrostatic internal gravity waves
<p>This folder contains data from</p> <p>Shimizu, K. (2024), Fundamental properties of adjoint model and adjoint sensitivity under fully-nonlinear hydrostatic internal gravity waves, Journal of Geophysical Research: Oceans, 129, e2023JC020577. https://doi.org/10.1029/2023JC020577</p> <p>Its contents are briefly described in ReadMe.txt.</p>
Data from: A method of separating linear internal wave and vortical mode energies using shipboard ADCP velocity measurements
Open the record for dataset details and reuse information.
Temperature timeseries and idealized simulations of internal solitary waves colliding with the Grande-Anse wharf, Saguenay Fjord, Canada
Open the record for dataset details and reuse information.
Internal Wave Bolus Data Set
<p>Image files for experiments of internal wave boluses. Stratification data for the experiments is also included.</p>
S1-IW-2023 Dataset(Ocean Internal Wave Dataset)
<p>The data for manuscript submitted to Ocean Land Atmosphere Research. Manuscript title:" A Transformer-based Hierarchical Multiscale Feature Fusion Internal Wave Detector and Dataset "; by (Zetai Ma, Longyu Huang, Jingsong Yang, Lin Ren, Xiaohui Li, Shuangyan He, Bingqing Liu, and Antony K. Liu)</p> <p>This data set (S1-IW-2023 Dataset) includes 742 marine internal wave SAR sub images and their tag files from June, 2014 to February, 2023 (from the earliest available data time to the time of data set production). The data is from ESA Sentinel-1 satellite, and is produced by Jinsong Yang's team of the State Key Laboratory of Satellite Ocean Environment Dynamics (SOED) of the Second Institute of Oceanography (SIO) of the Ministry of Natural Resources (to be updated later as appropriate). Please annotate the DOI of the manuscript and dataset for use. Welcome to download and use.</p>
Effects of Horizontal Resolution on Long-Range Equatorward Radiation of Near-inertial Internal Waves in Ocean General Circulation Models
<p>Effects of Horizontal Resolution on Long-Range Equatorward Radiation of Near-inertial Internal Waves in Ocean General Circulation Models</p>
Wave Simulation Results Using XBeach and Application Results at Kansai International Airport (KIX)
<p>The dataset includes input files for the numerical simulations (grids, topography, boundary conditions, and parameter settings), XBeach simulation results for a wind speed of 30 m/s, and the application results for Kansai International Airport (KIX).</p>
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International Brain Laboratory public data
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OpenNeuro
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