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Tables of Limb and Gravity-darkening Coefficients for the Space Mission GAIA
<p><br> File Summary:<br> --------------------------------------------------------------------------------<br> FileName Lrecl Records Explanations<br> --------------------------------------------------------------------------------</p> <p><br> TABLE1 76 574 u linear LDCs <br> PHOENIX-COND models, all metallicities,<br> v.tu=2,0 km/s for GAIA (LSM, FCM)</p> <p> TABLE2 76 1148 a, b quadratic LDCs <br> PHOENIX-COND models, all metallicities,<br> v.tu=2 km/s for GAIA (LSM, FCM) </p> <p> TABLE3 76 1148 c,d square-root LDCs <br> PHOENIX-COND models, all metallicities,<br> v.tu=2 km/s for GAIA (LSM, FCM) <br> </p> <p> TABLE4 76 1148 e,f logarithmic LDCs<br> PHOENIX-COND models, all metallicities, <br> v.tu=2,0,1,4,8 km/s for GAIA (LSM, FCM)</p> <p> TABLE5 49 2296 a_1,a_2,a_3,a_4 LDCs<br> PHOENIX-COND models, all metallicities, <br> v.tu=2 km/s for GAIA (LSM)</p> <p> TABLE6 76 9586 u linear LDCs <br> ATLAS models, all metallicities,<br> v.tu=2,0,1,4,8 km/s for GAIA (LSM, FCM)</p> <p> TABLE7 76 19172 a, b quadratic LDCs <br> ATLAS models, all metallicities,<br> v.tu=2,0,1,4,8 km/s for GAIA (LSM, FCM) </p> <p> TABLE8 76 19172 c,d square-root LDCs <br> ATLAS models, all metallicities,<br> v.tu=2,0,1,4,8 km/s for GAIA (LSM, FCM) <br> </p> <p> TABLE9 76 19172 e,f logarithmic LDCs<br> ATLAS models, all metallicities, <br> v.tu=2,0,1,4,8 km/s for GAIA (LSM, FCM)</p> <p> TABLE10 49 38344 a_1,a_2,a_3,a_4 LDCs<br> ATLAS models, all metallicities, <br> v.tu=2,0,1,4,8 km/s for GAIA (LSM)<br> <br> TABLE11 55 9575 y GDCs <br> ATLAS models, all metallicities,<br> v.tu=0,1,2,4,8 km/s for GAIA(BP,G,RP) <br> --------------------------------------------------------------------------------</p> <p> Byte-by-byte Description of files: TABLE 1<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- u linear LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- u linear LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- u linear LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- u linear LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- u linear LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- u linear LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 2<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- a quadratic LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- a quadratic LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- a quadratic LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- a quadratic LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- a quadratic LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- a quadratic LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- b quadratic LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- b quadratic LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- b quadratic LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- b quadratic LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- b quadratic LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- b quadratic LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 3<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- c root-square LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- c root-square LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- c root-square LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- c root-square LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- c root-square LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- c root-square LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- d root-square LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- d root-square LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- d root-square LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- d root-square LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- d root-square LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- d root-square LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 4<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- e logar LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- e logar LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- e logar LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- e logar LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- e logar LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- e logar LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- f logar LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- f logar LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- f logar LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- f logar LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- f logar LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- f logar LDC (GAIA RP, FCM)<br> -------------------------------------------------------------------------------- <br> <br> Byte-by-byte Description of files: TABLE 5<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a1 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a1 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a1 4 TERMS LDC (GAIA RP,LSM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a2 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a2 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a2 4 TERMS LDC (GAIA RP,LSM)<br> THIRD LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a3 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a3 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a3 4 TERMS LDC (GAIA RP,LSM)<br> FOURTH LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a4 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a4 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a4 4 TERMS LDC (GAIA RP,LSM)<br> --------------------------------------------------------------------------------</p> <p> Byte-by-byte Description of files: TABLE 6<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- u linear LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- u linear LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- u linear LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- u linear LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- u linear LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- u linear LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 7<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- a quadratic LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- a quadratic LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- a quadratic LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- a quadratic LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- a quadratic LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- a quadratic LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- b quadratic LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- b quadratic LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- b quadratic LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- b quadratic LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- b quadratic LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- b quadratic LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 8<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- c root-square LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- c root-square LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- c root-square LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- c root-square LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- c root-square LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- c root-square LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- d root-square LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- d root-square LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- d root-square LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- d root-square LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- d root-square LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- d root-square LDC (GAIA RP, FCM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 9<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- e logar LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- e logar LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- e logar LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- e logar LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- e logar LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- e logar LDC (GAIA RP, FCM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 25- 31 F7.4 --- f logar LDC (GAIA BP, LSM)<br> 34- 40 F7.4 --- f logar LDC (GAIA G, LSM)<br> 43- 49 F7.4 --- f logar LDC (GAIA RP, LSM)<br> 52- 58 F7.4 --- f logar LDC (GAIA BP, FCM)<br> 61- 67 F7.4 --- f logar LDC (GAIA G, FCM)<br> 70- 76 F7.4 --- f logar LDC (GAIA RP, FCM)<br> -------------------------------------------------------------------------------- <br> <br> Byte-by-byte Description of files: TABLE 10<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> FIRST LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a1 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a1 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a1 4 TERMS LDC (GAIA RP,LSM)<br> SECOND LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a2 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a2 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a2 4 TERMS LDC (GAIA RP,LSM)<br> THIRD LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a3 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a3 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a3 4 TERMS LDC (GAIA RP,LSM)<br> FOURTH LINE<br> 1- 5 F5.2 cm/s+2 logg Surface gravity<br> 7- 12 F6.0 K Teff Effective temperature<br> 14- 17 F4.1 Z log [metal/H]<br> 19- 22 F4.1 km/s Vel microturbulent velocity<br> 24- 31 F8.4 --- a4 4 TERMS LDC (GAIA BP,LSM)<br> 34- 40 F7.4 --- a4 4 TERMS LDC (GAIA G,LSM)<br> 43- 49 F7.4 --- a4 4 TERMS LDC (GAIA RP,LSM)<br> --------------------------------------------------------------------------------</p> <p>Byte-by-byte Description of files: TABLE 11<br> --------------------------------------------------------------------------------<br> Bytes Format Units Label Explanations<br> --------------------------------------------------------------------------------<br> 2-6 F5.2 Z log [metal/H]<br> 8-13 F6.3 km/s Vel microturbulent velocity<br> 16-20 F5.2 cm/s+2 logg Surface gravity<br> 22-27 F6.3 K log Teff log Effective temperature<br> 31-37 F7.4 --- y GDC (GAIA, BP)<br> 40-46 F7.4 --- y GDC (GAIA, B)<br> 49-55 F7.4 --- y GDC (GAIA, RP)<br> --------------------------------------------------------------------------------</p>
QuasIncompact3D: Application to non-Boussinesq gravity currents
<p>Data used for manuscript introducing QuasIncompact3D with application to non-Boussinesq gravity currents.</p> <p>CHANGES</p> <p>v1.1.0 [2019-02-26] Updated with new mixing layer data for reviewed manuscript.</p> <p>v1.1.1 [2019-02-26] Correcting mistake in v1.1.0 - new mixing layer data did not attach.</p>
Forward Asteroseismic Modeling of Stars with a Convective Core from Gravity-mode Oscillations: Parameter Estimation and Stellar Model Selection
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/arXiv:1806.06869">Aerts et al. (2018)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.3847/1538-4365/aaccfb">10.3847/1538-4365/aaccfb</a></p>
Impact of binary interaction on the evolution of blue supergiants. The flux-weighted gravity luminosity relationship and extragalactic distance determinations
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2019A&A...621A..22F">Impact of binary interaction on the evolution of blue supergiants. The flux-weighted gravity luminosity relationship and extragalactic distance determinations</a></p>
The observational signatures of convectively excited gravity modes in main-sequence stars
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2013MNRAS.430.1736S">The observational signatures of convectively excited gravity modes in main-sequence stars</a></p>
Binary asteroseismic modelling: isochrone-cloud methodology and application to Kepler gravity mode pulsators
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018MNRAS.tmp.2555J/abstract">Johnston et al. (2019)</a>. MESA version 10108.</p> <p>Publication DOI: <a href="https://doi.org/10.1093/mnras/sty2671">10.1093/mnras/sty2671</a></p>
The shape of convective core overshooting from gravity-mode period spacings
<p>MESA inlists associated with <a href="https://ui.adsabs.harvard.edu/#abs/2018arXiv180202051P/abstract">The shape of convective core overshooting from gravity-mode period spacings</a></p>
Asteroseismology of the nearby SN II Progenitor Rigel. II. epsilon-mechanism Triggering Gravity-mode Pulsations?
<p>MESA inlist associated with <a href="https://ui.adsabs.harvard.edu/?#abs/2012ApJ...749...74M">Moravveji et al. (2012)</a>. MESA version 3723.</p> <p>Publication DOI: <a href="https://doi.org/10.1088/0004-637X/749/1/74">10.1088/0004-637X/749/1/74</a></p>
Simulation data and source code for Hausdorff dimension measurements in two-dimensional quantum gravity
<p>This entry contains the source code and simulation data used as basis for the paper</p> <p>J. Barkley, T. Budd, "Precision measurements of Hausdorff dimensions in two-dimensional quantum gravity." Preprint <a href="https://arxiv.org/abs/1908.09469">arXiv:1908.09469</a> (2019)</p> <p>Both the source code and the data consist of two parts:</p> <ul> <li>Measurements of (dual) graph distances in various models of random planar maps.</li> <li>Measurements of discrete Liouville first passage percolation distances on a regular lattice with periodic boundary conditions.</li> </ul> <p>Instructions on compiling and running the simulation software are included with the source code (see README files). Descriptions of the simulation data formats accompany the data files (see README files again). For background on the simulation and data analysis we refer to the publication mentioned above.</p>
Observation of very short period atmospheric gravity waves in the lower Ionosphere using Very Low Frequency waves
<p>This is the VLF frequency data recorded at PARI station owned by Prof Morris Cohen, at Georgia Institute of Technology, Atlanta, USA.</p> <p>Data is for six transmitter signals, DHO, NAA, NAU, NLK, NPM, NML with both amplitude and Phase</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>
Unconfined gravity current interactions with oblique slopes: deflection, reflection and combined-flow behaviours
<p><span>Video 1. Annotated video illustrating the behaviour of density currents upon incidence with an oblique topographic slope (Experiment S40°IN75°). </span></p> <p><span> </span><span>Video 2. Annotated video illustrating the behaviour of density currents upon incidence with an oblique topographic slope (S40°IN60°). </span></p> <p><span> </span><span>Video 3. Annotated video illustrating the behaviour of density currents upon incidence with an oblique topographic slope (Experiment S40°IN15°). </span></p> <p><span> </span><span>Video 4. Annotated video illustrating the behaviour of density currents upon incidence with an oblique topographic slope (Experiment S30°IN75°). </span></p> <p><span> </span><span>Video 5. Annotated video illustrating the behaviour of density currents upon incidence with a flow-parallel topographic slope of 10° slope gradient.</span></p>
Gravity and Heterogeneous Trade Cost Elasticities
<p>Replication package for "Gravity and Heterogeneous Trade Cost Elasticities," by Natalie Chen and Dennis Novy, Economic Journal.</p>
Gravity-Driven Grainflows on Barchan Slipfaces: Field Data
<p><strong>Introduction</strong></p> <p>Gravity-driven grainflows, or avalanches, occur in many environments on Earth, Mars, and elsewhere. Many aspects of their characteristic behavior have been revealed through laboratory and field studies. Some findings have been, however, inconclusive or contradictory. We present the results from the first comprehensive field study of 1609, gravity-driven grainflows, with measurements of their magnitude, frequency, area, speed, and related wind speeds and sand transport rates, made on the slipface of a 21 m high barchan dune. Key findings support previous research, with relatively small sample sizes from shorter slipfaces, indicating that grainflow frequency increases with sand transport rate and grainflow speed increases with its area. We also found that grainflow magnitude increases with transport rate, which contradicts a commonly made assertion that grainflow magnitude is independent of the sand transport rate. We found significant scaling differences between laboratory and field data concerning the relationship between grainflow area and speed, with laboratory speeds, per unit area, more than two orders of magnitude faster than speeds found in the field. The implications of this work point to the importance of additional field studies and the hazard of using laboratory data alone for modeling grainflow behavior on terrestrial and extraterrestrial dunes.</p> <p>Here we present the data (the four spreadsheets in Natural grainflow dataset.xlsx) and metadata used to support a manuscript reporting our results and conclusions. The study site was on the slipface of a 20+m high barchan dune near Jericoacoara, Ceará, Brazil, and measurements made on November 7 and 9, 2013. The slipface was scanned repetitively with a Leica C10 terrestrial Laser scanner (TLS) on those two days. Details of TLS data processing and limitations are reported in Pelletier et al. (2015). Wind speeds were measured with Gill-type, DC-generating, cup anemometers. Sand transport rates were measured with sets of mesh-type traps described in Sherman et al. (2014). Grainflows that occurred near the apex of the slipface were video-recorded. More detail is provided for each of the individual spreadsheets to describe the measurement or derivation of data types.</p> <p><strong>Spreadsheet 1: Grainflow Area and Speed</strong></p> <p>Columns A and B report the date and time of each observation. Column C reports grainflow area (m<sup>2</sup>) as derived from Difference of Digital Elevation Models using the methods described in Zhang (2021). Column D reports grainflow speeds (ms<sup>-1</sup>) derived from DEM data (grainflow length) and video recordings (grainflow duration).</p> <p><strong>Spreadsheet 2: Grainflow Frequency and Magnitude</strong></p> <p>Columns A and B report the date and time of each observation. Column C reports the duration of a particular scan. Most scans required 7 minutes to complete and then a new scan began. Column D reports number of grainflows detected in an individual scan. Grainflow frequency, Column E, is normalized to one-minute equivalents. Average grainflow magnitude (m<sup>3</sup>) in Column F is derived from measurements of the volumes of the accretionary tails of all grainflows divided by the number of grainflows occurring during a scan.</p> <p><strong>Spreadsheet 3: Wind Speeds</strong></p> <p>Wind speed was measured with a set of three anemometers installed at 20 m spacing at the center of the top of the barchan slipface. Measurements at each anemometer were made at 1 Hz frequency. Columns A and B report the date and time of each observation. Column C reports average wind speeds (ms<sup>-1</sup>) obtained by block-averaging the 1 Hz data to one minute equivalent, and then averaging those data from the three anemometers.</p> <p><strong>Spreadsheet 4: Sand Transport Rates</strong></p> <p>Columns A and B report the date and time of each observation and Column C reports the duration of deployments of pairs of traps. Average transport rates in Column D were obtained by first averaging the trapped sand masses of the trap pair and then converting that value to an equivalent transport rate (gm<sup>-1</sup>s<sup>-1</sup>) for each sample period. The irregularly spaced point data were linearly interpolated to produce a time series with one-minute increments.</p> <p>References:</p> <p>Pelletier, J. D., Sherman, D. J., Ellis, J. T., Farrell, E. J., Jackson, N. L., Li, B., et al. (2015). Dynamics of sediment storage and release on aeolian dune slip faces: A field study in Jericoacoara, Brazil. <em>Journal of Geophysical Research: Earth Surface</em>, <em>120</em>(9), 1911–1934.</p> <p>Sherman, D. J., Swann, C., & Barron, J. D. (2014). A high-efficiency, low-cost aeolian sand trap. <em>Aeolian Research</em>, <em>13</em>, 31–34.</p> <p>Zhang, P. (2021). An algorithm for objective analysis of grainflow morphology, <em>Aeolian Research, 50, </em>100686.</p>
Attenuating surface gravity waves with mechanical metamaterials
<p>Videos showing simulations of one or more submerged oscillators attenuating surface gravity waves, related to the publication </p> <p><a href="https://aip.scitation.org/author/de+Vita%2C+F">F. De Vita</a><em>, </em><a href="https://aip.scitation.org/author/de+Lillo%2C+F">F. De Lillo</a><em>, </em><a href="https://aip.scitation.org/author/Bosia%2C+F">F. Bosia</a><em>, and </em><a href="https://aip.scitation.org/author/Onorato%2C+M">M. Onorato</a>, "Attenuating surface gravity waves with mechanical metamaterials", Physics of Fluids 33, 047113 (2021) <a href="https://doi.org/10.1063/5.0048613">https://doi.org/10.1063/5.0048613</a></p> <p>Also included are Data relative to Figs. 3, 5, 6, 8 and gnuplot scripts to generate the figures.</p>
Datasets from the RecSys 2021 article "Cold Start Similar Artists Ranking with Gravity-Inspired Graph Autoencoders"
<p>We publicly release :</p> <ol> <li>the anonymized deezer_graph<em>.csv</em> and deezer_features<em>.csv</em> datasets</li> <li>the pre-trained node embedding vectors from all pre-trained models</li> </ol> <p>described in the <a href="https://github.com/deezer/similar_artists_ranking/">deezer/similar_artists_ranking/</a> GitHub repository.</p>
Corresponding Dataset of Advanced Water Vapor Radiometer Data for Juno Gravity Science
<p><br> Corresponding Dataset of Advanced Water Vapor<br> Radiometer Data for Juno Gravity Science<br> Troposphere Calibrations<br> README FILE<br> Dustin Buccino<br> August 24, 2021<br> Jet Propulsion Laboratory<br> California Institute of Technology</p> <p>=============================================================================<br> INTRODUCTION<br> =============================================================================</p> <p> This dataset contains high rate data collected by the Advanced Water<br> Vapor Radiometer (AWVR) at the Deep Space Network's Goldstone Complex in <br> California. This dataset is provided in order to supplement the submitted<br> article to the "Radio Science" journal</p> <p> Buccino, D.R., et al (2021), Performance of Earth Troposphere <br> Calibration Measurements with the Advanced Water Vapor Radiometer <br> for the Juno Gravity Science Investigation, Radio Science, submitted<br> October 2021.</p> <p> ******************************************************************<br> * ANY USERS OF JUNO GRAVITY SCIENCE DATA ARE HIGHLY ENCOURAGED *<br> * TO INSTEAD REFER TO THE OFFICIAL ARCHIVE ON THE NASA PLANETARY *<br> * DATA SYSTEM. THIS SUPPLEMENTAL DATA SET DOES NOT CONTAIN ANY *<br> * GRAVITY SCIENCE DATA; IT ONLY CONTAINS HIGHER RATE AWVR DATA *<br> ******************************************************************</p> <p> Additional Juno Gravity Science Data may be found at the Planetary Data<br> System:</p> <p> Buccino, D. R. (2016). Juno jupiter gravity science raw data set <br> V1.0, JUNO-J-RSS-1 JUGR-V1.0, NASA planetary data system (PDS). <br> Retrieved from https://atmos.nmsu.edu/PDS/data/jnogrv_1001/<br> </p> <p>=============================================================================<br> ARCHIVE INFORMATION<br> =============================================================================</p> <p> This archive contains several data types, located within subdirectories.<br> <br> ROOT<br> `- PJ03/<br> <br> This directory contains all PJ-03 related data, including<br> path delay, path delay rate, calibration values, and frequency<br> residuals.<br> <br> `- PJ06/<br> <br> This directory contains all PJ-06 related data, including<br> path delay, path delay rate, and calibration values.<br> <br> `- PJ08/<br> <br> This directory contains all PJ-08 related data, including<br> path delay, path delay rate, and calibration values.<br> <br> `- ADEV/<br> <br> This directory contains troposphere scintillation Allan deviations<br> from each perijove. Files are named using the start time of the file,<br> in YYYYMMDDHHMM format, where YYYY is the year, MM is the month,<br> DD is the day of month, HH is the hour, and MM is the minute.<br> <br> `- STATS/<br> <br> This directory contains the Juno perijove frequency residual <br> statistics. Only one file is present in this directory.</p> <p>=============================================================================<br> FILE FORMAT<br> =============================================================================</p> <p> This dataset contains two separate file formats as described below.<br> ASCII plain-text files are given with the "*.txt" extension and the<br> comma-separated text files are given with the "*.csv" extension.</p> <p><br> TXT FILES<br> -------------------------------------------------------------------------</p> <p> The ASCII plain-text files are human-readable, space-delimited<br> text files. Each column is defined by a header row which provides<br> a description of each column. Additional comments may be optionally<br> specified by starting a row with the character "#".</p> <p> CSV FILES<br> -------------------------------------------------------------------------</p> <p> The Comma-Separated Value (CSV) files are plain-text files. Values in<br> each data file are separated using a comma ",". Each column is defined <br> by a header row which provides a description of each column.</p> <p><br> =============================================================================<br> FIGURE REPRODUCTION<br> =============================================================================</p> <p> This section will describe the data that are used to produce the figures<br> in the article that describes this dataset.</p> <p> FIGURE 1<br> -------------------------------------------------------------------------</p> <p> Figure 1 is a photograph and is not included in this dataset.</p> <p> FIGURE 2<br> -------------------------------------------------------------------------</p> <p> Figure 2 is produced using files within the "PJ03", "PJ06", and "PJ08"<br> directories.<br> <br> The first row of subfigures are produced by plotting the final three <br> columns of "pjXX_bt_zenith.txt" as a function of time.<br> <br> The second row of subfigures are produced by plotting the path delay<br> componets as a function of time from the "pjXX_pd_awvr.txt" and <br> "pjXX_pd_tsac.txt" data files.</p> <p><br> FIGURE 3<br> -------------------------------------------------------------------------</p> <p> Figure 3 is produced using files within the "PJ03", "PJ06", and "PJ08"<br> directories.<br> <br> The first row of subfigures are produced by plotting the last column<br> of "pjXX_freq_awvr.txt" and "pjXX_freq_tsac.txt".<br> <br> The second row of subfigures are produced by differencing the values.<br> <br> FIGURE 4<br> -------------------------------------------------------------------------</p> <p> Figure 4 is produced using files within the "ADEV" directory.<br> <br> Each individual file within the "ADEV" directory contains the Allan <br> deviation. Each Allan deviation is plotted on a log-log scale and is<br> color-mapped to the calendar date. The file naming convention gives<br> the calendar date of data collection, with the filenames starting with<br> YYYYMMDD, where YYYY is 4-digit year, MM is 2-digit month, and DD is<br> 2-digit day of month in UTC time.</p> <p> FIGURE 5<br> -------------------------------------------------------------------------</p> <p> Figure 5 is produced using files within the "PJ03" directory. The<br> frequency residual from the "pj03_resid_awvr.csv" and<br> "pj03_resid_tsac.csv" is simply plotted as a function of time.<br> <br> FIGURE 6<br> -------------------------------------------------------------------------</p> <p> Figure 6 is produced using files within the "STATS" directory. This <br> directory contains a single file, "AWVR_stats_jul2021_v3.csv" and<br> contains the root-mean-square of the frequency residuals from Juno <br> perijove passes. The root-mean-square of the frequency residuals<br> are plotted using a bar plot and the percent improvement is plotted <br> with a scatterplot.<br> </p> <p>=============================================================================<br> ACKNOWLEDGMENTS<br> =============================================================================</p> <p>This work was carried out at the Jet Propulsion Laboratory, <br> California Institute of Technology, under contract with the National <br> Aeronautics and Space Administration. Government sponsorship acknowledged.</p> <p>=============================================================================<br> PRIMARY POINT OF CONTACT<br> =============================================================================</p> <p>Dustin Buccino<br> Jet Propulsion Laboratory<br> Planetary Radar and Radio Sciences<br> (818) 393 - 1072<br> Dustin.R.Buccino@jpl.nasa.gov</p> <p>=============================================================================<br> ACRONYMS AND ABBREVIATIONS<br> =============================================================================</p> <p> ASCII American Standard Code for Information Interchange<br> DOY Day of year<br> DSN Deep Space Network<br> JPL Jet Propulsion Laboratory<br> NAIF Navigation Ancillary Information Facility<br> NASA National Aeronautics and Space Administration<br> PDS Planetary Data System<br> RS Radio Science<br> RSS Radio Science Subsystem<br> SIS Software Interface Specification<br> TXT Text file<br> UTC Universal Time, Coordinated<br> </p>
Primary Versus Secondary Gravity Wave Responses at F-region Heights Generated by a Convective Source
<p>Simulation outputs for the paper "Primary Versus Secondary Gravity Wave Responses at F-region Heights Generated by a Convective Source" by Heale et al.</p> <p>The .mat file consist of 3D (t,x,z) arrays of the temperature perturbation (K) for the full amplitude (T_fullamp), 1/4 amplitude (T_quarteramp), and 1/100th amplitude (T_hundrethamp) simulations. The time resolution is 60 seconds and the spatial resolution is 1km. The .mat file also included an x array and height array (km)</p>
Model and the related code for gravity field determination from the third invariant of the GOCE gravity gradient tensors: I3GG V1.0th
<p>The model and the related code for gravity field determination from the third invariant of the GOCE gravity gradient tensors: I3GG V1.0th</p>
Simulation datasets for: Intense surface winds from gravity wave breaking in simulations of a destructive macroburst
<p>Shortly after 0600 UTC (midnight local time) 9 June 2020, a convective line produced severe winds across parts of northeast Colorado that caused extensive damage, especially in the town of Akron. High-resolution observations showed gusts exceeding 50 m s<sup>−1</sup>, accompanied by extremely large pressure fluctuations, including a 5-hPa pressure surge in 19 s immediately following the strongest winds and a 15-hPa pressure drop in the following 3 min. Numerical simulations of this event (using the WRF Model) and with horizontally homogeneous initial conditions (using Cloud Model 1) reveal that the severe winds in this event were associated with gravity wave dynamics. In a very stable postfrontal environment, elevated convection initiated and led to a long-lived gravity wave. Strong low-level vertical wind shear supported the amplification and eventual breaking of this wave, resulting in at least two sequential strong downbursts. This wave-breaking mechanism is different from the usual downburst mechanism associated with negative buoyancy resulting from latent cooling. The model output reproduces key features of the high-resolution observations, including similar convective structures, large temperature and pressure fluctuations, and intense near-surface wind speeds. The findings of this study reveal a series of previously unexplored mesoscale and storm-scale processes that can result in destructive winds.</p> <p><strong>Significance Statement </strong></p> <p>Downbursts of intense wind can produce significant damage, as was the case on 9 June 2020 in Akron, Colorado. Past research on downbursts has shown that they occur when raindrops, graupel, and hail in thunderstorms evaporate and melt, cooling the air and causing it to sink rapidly. In this research, we used numerical models of the atmosphere, along with high-resolution observations, to show that the Akron downburst was different. Unlike typical lines of thunderstorms, those responsible for the Akron macroburst produced a wave in the atmosphere, which broke, resulting in rapidly sinking air and severe surface winds.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.