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75 results for “gravity wave”
Dataset for Observations of gravity wave refraction and its causes and consequences
<p>Dataset for the publication submitted to Journal of Geophysical Research: Atmospheres. The title of the publication is:</p> <p>Observations of gravity wave refraction and its causes and consequences</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>
The propagation of gravity waves in Titan's stratosphere
<p>The model code and figure data of our article "The propagation of gravity waves in Titan's stratosphere". <a href="https://zenodo.org/api/files/a647c3b7-0796-4a3a-96bc-779957496aad/GW-simulation-program.txt">GW-simulation-program.txt</a> is the Mathematica code used to simulate gravity wave propagation. <a href="https://zenodo.org/api/files/a647c3b7-0796-4a3a-96bc-779957496aad/simulations-nowind.rar">simulations-nowind.rar</a> and <a href="https://zenodo.org/api/files/a647c3b7-0796-4a3a-96bc-779957496aad/simulations-wind.rar">simulations-wind.rar</a> are the simulation results for gravity wave with its horizontal propagation direction perpendicular or not perpendicular to the background wind, respectively. <a href="https://zenodo.org/api/files/a647c3b7-0796-4a3a-96bc-779957496aad/FigureData.rar">FigureData.rar</a> contains several data files for figures in our article.</p>
Pertubation Profiles Dataset used for "Convection-generated gravity waves in the tropical lower stratosphere from Aeolus wind profiling and ERA5 reanalysis"
<p>These are the perturbation profiles, from 5km to 29.5km, with a 500m grid. In the study, we picked up the data between tropopause-1km to 22km, which was then squared, smoothed, and averaged into one value. We used a 14 points moving average for the smoothing.</p> <p>The data is from 2018-09 to 2022-09, based on the Aeolus L2B Rayleigh clear wind, using only quality flag 1 data.</p> <p>Please email me at mathieu.ratynski@estaca.eu if you're interested in the 100m resolution version, used in the final version of the manuscript.</p>
Vertical Wind and Temperature Gravity Wave Perturbations Derived from Na Lidar Observations
<p>The gravity wave perturbations associated with vertical wind and temperature in the mesopause region for heat flux calculations. </p>
ERA5 overviews complementing temperature measurements of ground-based Rayleigh lidars for the investigation of gravity waves generated by moving sources
<p>ERA5 overviews to associate stratospheric gravity waves in temperature measurements from vertically staring (zenith-pointing) ground-based Rayleigh lidars with atmospheric processes. Animations are for a virtual lidar location over the Southern Ocean during research flight RF25 of the DEEPWAVE campaign (July 17 to 19, 2014) and for the location of the COmpact Rayleigh Autonomous Lidar (CORAL) in the lee of the southern Andes. Here, the first overview is for the CORAL measurement from June 22 to 23, 2018. The second one is for the nightly measurements between August 7 and 9, 2020.</p> <p>(a) and (b) emulate the measurement of a vertically staring ground-based lidar and show temperature perturbations after subtracting a temporal running mean of 12h (a) and the mean absolute temperature profile (b). Panels (c) and (d) are vertical sections of stratospheric 𝑇′ along sectors of the latitude circle (c) and meridian (d) of the virtual lidar location. (e) and (f) are corresponding vertical sections of thermal stability 𝑁2 (10−4 s−2, color-coded), potential temperature (K, thin grey lines), and potential vorticity (1, 2, 4 PVU: black, 2 PVU: green). Thin black lines in the vertical sections are zonal (d, f) and meridional (c, e) wind components (solid: positive, dashed: negative). Panel (g) is a horizontal section of the height of the 2 PVU surface (km, color-coded), geopotential height (m, solid lines) and wind barbs at the 850 hPa level. The black vertical line in (a) marks the time for (c)-(g) and dashed lines in (c)-(g) highlight the location of the virtual lidar and profiles in (a) and (b).</p> <p>The provided NETCDF files contain the corresponding CORAL temperature measurements for the two periods with CORAL measurements in 2018 and 2020.</p>
Gravity waves in Titan's atmosphere: A comparison between linearized wave model calculations and HASI observations
<p>The data for the article "Gravity waves in Titan's atmosphere: A comparison between linearized wave model calculations and HASI observations" (GWTA). </p> <p> </p> <ol> <li>"Titan_CJP_std_chem.dat" is the background atmosphere data of Titan's atmosphere from Strobel's model. It is used in Figure 1 of the article.</li> <li>"HASI_T_p_rho_vsZ_2008.dat" is the data for Cassini-Huygens observations in Titan's atmosphere. It is used in Figure 1 of the article.</li> <li>"Mma-Program-for-GW-on-Titan.txt" is the main Mathematica program to simulate the gravity waves on Titan.</li> <li>"solutions-fun.rar" is the simulation result. This RAR file includes 174 gravity wave samples simulated with different periods and horizontal wavelengths (can be read from the subfile names after uncompressing). These gravity wave solutions are stored as InterpolatingFunction of Mathematica. The solution describes the gravity wave temperature, velocity, and density perturbations profiles from altitude 300km to 2000km. However, they are plain texts and can easily be read by any software. Figures from 2-10 are based on these data.</li> </ol> <p> </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>
Surface Gravity Waves in the Gulf of Mexico
<p>This dataset includes the results of a coupled SWAN-ROMS simulation over the Gulf of Mexico between 2001 and 2010. Published at https://doi.org/10.1029/2018JC014820 (JGR: Oceans)</p>
Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice with waves component is 564 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</p>
Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates
<p>This data corresponds to the runs analysed in the manscript: Role of Surface Gravity Waves in Aquaplanet Ocean Climates (JAMES, 2021).</p> <p>In this work, we present a set of idealised numerical experiments that demonstrate the thermodynamic and dynamic implications of surface gravity waves for the oceanic climate of an aquaplanet. We study the impact of accounting for modulations by such waves upon air-sea momentum fluxes, Langmuir circulation and the Stokes-Coriolis force.</p> <p>This dataset is made up of atmospheric, oceanic and surface gravity wave simulations. When uncompressed the total dataset is 1.6 TB, the ocean and ice without waves component is 484 GB. See below for further details.</p> <p>See the related works section for the corresponding datasets.</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>
Ocean and ice without waves data for role of surface gravity waves in aquaplanet ocean climates
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Ocean and ice with waves data for role of surface gravity waves in aquaplanet ocean climates
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Ocean and ice spin-up data for role of surface gravity waves in aquaplanet ocean climates
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Atmospheric and surface gravity wave data for role of surface gravity waves in aquaplanet ocean climates
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Dataset of "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" (2/2)
<p>This dataset contains the GrADS data of high-resolution Mars GCM results used for figures in the paper "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" by T. Kuroda, A.S. Medvedev and E. Yiğit.</p> <p>Each file contains two-dimensional (X: longitude, Y: latitude) data of surface pressure (Ps) and dust opacity in infrared wavelength (tau), and three-dimensional (X: longitude, Y: latitude, Z:sigma-level) data of temperature (T), zonal wind velocity (u), meridional wind velocity (v) and vertical wind velocity (w). Each tar.xz file contains snapshots of those data in every 1/6 Sol for Ls of 30 degrees. The dust scenario implemented for producing this dataset is taken from Montabone et al. (2020).</p> <p>data270rdc-my34.tar.xz: for Ls=270-300 (48 Sols)</p> <p>data300rdc-my34.tar.xz: for Ls=300-330 (51 Sols)</p> <p>data330rdc-my34.tar.xz: for Ls=330-360 (56 Sols)</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>
Dataset of "Effects of latitude-dependent gravity wave source variations on the middle and upper atmosphere"
<p>This is a dataset for three 60-day simulations with the CMAT2-GCM for June-July 2010 conditions, using the Whole atmosphere gravity wave parameterization by Yiğit et al. (2008).</p> <p>Dimensions: 66 vertical levels, 24 longitudes, and 91 latitudes. The bottom level is at 100 mb. </p> <p>Variables: There are seven physical variables. Daily-averaged zonal wind, temperature, geopotential height, zonal drag, gravity wave total heating/cooling rate, gravity wave-induced temperature fluctuations, and gravity wave absolute momentum flux. </p> <p>Simulations: A benchmark run "00n", a run with latitude-dependent gravity wave source spectrum with 50% increased flux at the lower boundary in both hemispheres "51n"; same as "52n" but 100% increased flux in the Southern Hemisphere only. </p>
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