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43 results for “Atmospheric waves”
Coupled atmosphere-wave-ocean simulation of Hurricane Dorian (2019)
<p><strong>Description</strong></p> <p>This dataset provides the output of the coupled atmosphere-wave-ocean simulation of Hurricane Dorian from August 29 to September 7, 2019. The simulation is a composite of two separate simulations:</p> <ol> <li>From 00 UTC August 29 to 00 UTC September 1, 2019</li> <li>From 00 UTC September 1 to 00 UTC September 7, 2019</li> </ol> <p>The first simulation serves as "spin-up" for the hurricane and its environment prior to landfall. The second simulation is initialized from the output of the first simulation, while relocating the Dorian vortex to its correct position on September 1. Due to the size of the dataset only the surface fields are made available.</p> <p><strong>Model configuration</strong></p> <ul> <li><strong>Atmosphere</strong>: Weather Research and Forecasting (WRF, https://github.com/wrf-model/WRF) model v4.2.2, with the Advanced Research WRF (ARW) dynamical core. The model has a 3-km resolution grid over the parent domain and a 1-km resolution nest over the Bahamas region (September 1-7 only), both with 45 vertical layers. Initial and boundary conditions are based on 6-hourly ERA-5 dataset.</li> <li><strong>Ocean Waves</strong>: University of Miami Wave Model (UMWM, https://umwm.org). The model is configured at the same 3-km as the atmosphere model, and has 36 directional bins and 37 frequency bins that are logarithmically spaced from 0.0313 to 2 Hz.</li> <li><strong>Ocean Circulation</strong>: HYbrid Coordinate Ocean Model (HYCOM, https://github.com/HYCOM) v2.3.01, configured at 0.01 degree resolution and 41 vertical layers. Initial and boundary conditions are based on daily GOFS 3.1 41-layer HYCOM + NCODA Global 1/12° Analysis, daily. K-Profile Parameterization for vertical mixing.</li> <li><strong>Coupling</strong>: Earth System Modeling Framework (ESMF, https://github.com/esmf-org/esmf) v8.0.1</li> </ul> <p><strong>File Description</strong></p> <ul> <li>blkdat.input - HYCOM (ocean circulation) configuration file</li> <li>dorian2019_atmosphere_1km_2019090100.nc - Atmosphere at 1-km resolution dataset</li> <li>dorian2019_atmosphere_waves_3km_2019082900.nc - Atmosphere and waves at 3-km resolution dataset, Aug 29 - Sep 1.</li> <li>dorian2019_atmosphere_waves_3km_2019090100.nc - Atmosphere and waves at 3-km resolution dataset, Sep 1-7</li> <li>dorian2019_ocean_1km_2019082900.nc - Ocean circulation at 1-km resolution dataset</li> <li>main.nml - UMWM (waves) configuration file</li> <li>namelist.input - WRF (atmosphere) configuration file</li> <li>regional.depth.[ab] - HYCOM (ocean circulation) bathymetry files</li> <li>regional.grid.[ab] - HYCOM (ocean circulation) grid files</li> <li>umwm.gridtopo - UMWM (waves) grid and bathymetry file</li> <li>wrfbdy_d01 - WRF (atmosphere) boundary conditions file</li> <li>wrfinput_d01.2019082900 - WRF (atmosphere) initial conditions file for parent domain on Aug 29</li> <li>wrfinput_d01.2019090100 - WRF (atmosphere) initial conditions file for parent domain on Sep 1</li> <li>wrfinput_d02.2019090100 - WRF (atmosphere) initial conditions file for inner nest on Sep 1</li> </ul> <p><strong>Coupled model source code</strong></p> <p>The model source code has not yet been released. We plan to open source it upon publication of the paper describing the simulation. When the source code is released, we will add the link to this repository.</p>
Waves Hindcast on the Senegalese Coast over the Last Four Decades (from 1980 to 2021). [A Dataset use in : SAMOU, M.S.; BERTIN, X.; SAKHO, I.; LAZAR, A.; SADIO, M.; DIOUF, M.B. Wave Climate Variability along the Coastlines of Senegal over the Last Four Decades. Atmosphere 2023]
<p>Computed from the WW3 Model, the last Four Decades Wave Hindcast is available on the Senegalese Coast through this present Dataset. Covering the period 1980 to 2021, this high resolution hindcast, both spatial (0.05x0.05) and temporal (1 h) provided all the wave parameters such as: the significant wave heights, the mean wave periods, the wave directions and the peak wave periods (to compute from wave frequencies) with an hourly interval.</p> <p>More details on this data (e.g., model implementation and validation) can be obtained in: SAMOU, M.S.; BERTIN, X.; SAKHO, I.; LAZAR, A.; SADIO, M.; DIOUF, M.B. Wave Climate Variability along the Coastlines of Senegal over the Last Four Decades. <em>Journal Atmosphere 2023</em>].</p>
Mountain waves in the upper atmosphere of Venus
<p>This dataset contains the GCM reduced variables of the outputs of the Venus PCM for the manuscript "Mountain waves in the upper atmosphere of Venus". It consists of NetCDF files showed in the following figures:</p> <p>Figure 1. Zonal wind and wave amplitude above the Beta Regio area [100◦W-40◦W ; 30◦S-30◦N] for three local times.</p> <p>Figure 2. Maps of downwards vertical wind speed (cm/s) above Beta Regio from the cloud top (70 km) to the thermosphere (135 km) for three local times. Positive (negative) values are downwards (upwards).</p> <p>Figure 3. Westward zonal wind (averaged for latitudes 40◦S-40◦N for data accumulated over one solar day) as a function of local time for altitudes 100 and 135 km. Continuous lines are averaged for one solar day, whereas the dashed line is averaged only for local times 16h-18h above Beta Regio (longitude 78◦ W). </p> <p>Figure 4. Vertical wind speed for local times 14h-16h and all latitudes, in m/s above the cloud top.</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>
Pressure data used in 'Surface-to-space atmospheric waves from Hunga Tonga-Hunga Ha'apai eruption' (Wright et al., 2022)
<p>Pressure data used in 'Surface-to-space atmospheric waves from Hunga Tonga-Hunga Ha’apai eruption' (Wright et al., 2022). </p> <p> </p> <p><strong>Phase speed estimates by station:</strong></p> <p>Author: <em>Fred Prata, AIRES Pty Ltd</em></p> <p>Description:<em> distances, locations, arrival times and phase speed estimates for the Hunga Tonga Lamb wave from pressure stations used in our study.</em></p> <p> </p> <p> </p> <p><strong>Pressure time series data (19 stations):</strong></p> <p><strong>Lauder (1 station):</strong></p> <p>Author: <em>Dan Smale/NIWA, State Highway 85, Omaku, New Zealand</em></p> <p>Description: <em>Data sourced from a CO2 eddy-covariance instrument operated and maintained by NIWA. Values were provided as an image file of pressure anomaly versus time (NZST) which was digitized at approximately 90 s time resolution and 0.1 hPa.</em></p> <p><strong>Mt Eliza / HRO (1 station):</strong></p> <p>Author: <em>Fred Prata/AIRES Pty Ltd, 116 Humphries Road, Mount Eliza, Vic 3930, Australia</em></p> <p>Description: <em>Data derived from an ecowitt weather station (Easyweather-WIFIA 19E) operated and maintained by AIRES Pty Ltd. The measurements are logged every 5 minutes with a pressure resolution of 0.1 hPa.</em></p> <p><strong>Tonga (1 station):</strong></p> <p>Author:<em> Malo e Leilei Taaniela/Fua'amotu Domestic Airport, Tonga and Shane Cronin/University of Auckland, School of Environment, New Zealand.</em></p> <p>Description: <em>Data derived from a barometer operated by the Tongan meteorological office located at Nukualofa port (met.gov.to). Sampling interval is 1 minute and the pressure resolution is 0.1 hPa</em></p> <p><strong>Weatherlink (3 stations):</strong></p> <p>Author: <em>Fred Prata/AIRES Pty Ltd, 116 Humphries Road, Mount Eliza, Vic 3930, Australia</em></p> <p>Description: <em>Data downloaded from http://weatherlink.com The time resolution is 5 minutes for Davis and Boston and 15 minutes for Travis. The pressure resolution is 0.01 in Hg.</em></p> <p><strong>PurpleAir (13 stations): </strong></p> <p>Author: <em>citizen science project - https://map.purpleair.com/ (free for non-commercial use)</em></p> <p>Description: <em>PNG images of pressure traces from each station: American Samoa, Anchorage, Auckland, Brisbane, Colorado Springs, Concepcion, Glenn Dale, Kahuko, Manhattan Beach, Papeete, Solvang, Sydney, Tokyo. See table, described above, for latitude/longitude of each site.</em></p> <p> </p> <p><strong>Other pressure data used in the paper already archived elsewhere, and associated licensing (11 stations):</strong></p> <p><strong>AIMS (10 stations)</strong>: https://apps.aims.gov.au/metadata/search?term=Weather%20Stations (CC BY 3.0 AU)</p> <p><strong>Wegenernet (1 station)</strong>: https://wegenernet.org/portal/v7.1/2021/1 ("openly available to all and free of charge except for commercial usage")</p> <p> </p> <p> </p> <p><strong>Not included (6 stations):</strong></p> <p>Due to licensing terms, we do not include 6 pressure time series obtained from the Australian Bureau of Meteorology in their raw form, specifically those at <em>Mt Isa Aero, Learmonth Airport, Broome Airport, Alice Springs Airport, Adelaide Airport and Perth Airport</em>. Derived products made from these data are permitted to be shared, and accordingly phase speed estimates from these stations are included in the table described above. A graphical representation of the data from <em>Broome</em> is also included in the scientific paper these data support as Extended Data Figure 1e.</p> <p> </p> <p> </p>
Processed data used for JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations"
<p>This is the processed dataset used in the JGR publication "Role of Midwater Mixed Waves in the Loop Current Separation Events from A Coupled Ocean-Atmosphere Regional Model and In-Situ Observations" by Xiao Ge.</p> <p>Please contact the author (gexiao@tamu.edu) for all the original/processed outputs of R-CESM, and use the following original papers as citations.</p> <p>The dataset used in this research includes:</p> <p>1. Loop Current Dynamics 2009-2011: LC_*.nc is the processed (reorganized) data for each in-situ station, * represents their station ID</p> <ul> <li>https://digital.library.unt.edu/ark:/67531/metadc955416/</li> <li>https://www.sciencedirect.com/science/article/pii/S0377026516301348?via%3Dihub</li> <li>https://search.dataone.org/view/%7BBD2513E6-3B34-4B7C-BCB9-3C4ED5E8D0FB%7D</li> </ul> <p>2. Regional Community Earth System Model, R-CESM: <a href="https://zenodo.org/api/records/13932074/draft/files/h.nc/content" target="_blank" rel="noopener noreferrer">h.nc</a> is the bathymetry data of R-CESM; cmpr_*.nc files are provided as examples of the original R-CESM outputs; pvsf_prho_*.nc are the processed (subsampled at the target region and interpolated on potential density layers, derived stream function, potential vorticity, and relative vorticity) R-CESM outputs used in this research; and <a href="https://zenodo.org/uploads/13932074" target="_blank" rel="noopener noreferrer">LC_pv_40hlp_2013.nc</a> is the example of organized processed R-CESM (pvsf_prho_*.nc files) containing potential vorticity and relative vorticity for figures plotting</p> <ul> <li>https://journals.ametsoc.org/view/journals/bams/102/9/BAMS-D-20-0024.1.xml?tab_body=fulltext-display</li> </ul> <p> </p> <p> </p> <p> </p> <p> </p>
Model data used for the paper: "Heat extremes driven by amplification of phase-locked circumglobal waves forced by topography in an idealized atmospheric model"
<p>Atmospheric model output to reproduce the results of the study: "<strong>Heat Extremes Driven by Amplification of Phase-Locked Circumglobal Waves Forced by Topography in an Idealized Atmospheric Model" </strong>published in Geophysical Research letters.<br> <br> Authors: B. Jiménez-Esteve. K. Kornhuber and D. I.V. Domeisen <br> <br> DOI: <a href="https://doi.org/10.1029/2021GL096337">https://doi.org/10.1029/2021GL096337</a><br> <br> For more information about the model setup and the design of the experiments please refer to the above publication.</p>
Data for: The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0
<p class="MsoNormal"><span>The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0 is the first observation-based climatology dataset of Martian atmospheric waves.</span></p> <p class="MsoNormal"><span>It contains climatology-gridded temperature, gravity waves, and tides spanning the whole Martian year. MAWPD uses the Data INterpolating Empirical Orthogonal Functions method (DINEOF) reconstruction method for data assimilation with the observational data from the Mars Global Surveyor (MGS), Mars Reconnaissance Orbiter (MRO), Mars Atmosphere and Volatile EvolutioN (MAVEN), Mars Pathfinder (MP), Mars Phoenix Lander (MPL), Mars Exploration Rover (MER) and Mars Express (MEX) temperature retrievals. The dataset includes gridded fields of temperature (Level 1 data) as well as the physical quantities of GWs (Level 2 data, amplitude, and potential energies), SPWs and tides (Level 2 data, amplitude, and phase).</span></p> <p class="MsoNormal"><span>We found the MAWPD can well reflect the climatological variations of gravity and tidal waves in the Martian atmosphere. The dataset is useful for observation-based scientific studies concerning Martian atmospheric waves, e.g., circulation, dust storms, and the wave excitation mechanism on Mars, and their comparison with the reanalysis dataset.</span></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>
Data for: The Martian atmospheric waves perturbation Datasets (MAWPD) version 2.0
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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>
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>
Dataset of "Gravity Wave Activity in the Atmosphere of Mars During the 2018 Global Dust Storm: Simulations With a High-Resolution Model" (1/2)
<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 with the name starting 'data' contains two-dimensional (X: longitude, Y: latitude) data of surface pressure (Ps) (unit: hPa) and dust opacity in infrared wavelength (tau), and three-dimensional (X: longitude, Y: latitude, Z:sigma-level) data of temperature (T) (unit: K), zonal wind velocity (u) (unit: m/s), meridional wind velocity (v) (unit: m/s) and vertical wind velocity (w) (unit: m/s), in snapshots of every 1/6 Sol for the periods of 30 degrees in Ls per a file as described below. The dust scenario implemented for producing this dataset is taken from Montabone et al. (2020), which is based on the observed dust opacity in Mars Year 24 (MY34).</p> <p>data180rdc-my34.tar.xz: for Ls=180-210 (49 Sols)</p> <p>data210rdc-my34.tar.xz: for Ls=210-240 (47 Sols)</p> <p>data240rdc-my34.tar.xz: for Ls=240-270 (46 Sols)</p> <p>The .tar.xz files can be extracted in Linux with 'tar Jxvf' command, and .grd and .ctl files with the same stem are generated.</p> <p>The file 'flux61ls5-my34.tar.xz' contains the three-dimensional fluxes and physical parameters calculated from the model output with the MY34 dust scenario. The contents are (T')^2, (u')^2, (v')^2, u'v', u'w', v'w' T(bar), u(bar), v(bar), squared Brunt-Vaisala frequency, and geopotential height. (bar) denotes the sum of the total wavenumber s=0-60 components, and the dash denotes the deviation from (bar), i.e. sum of the total wavenumber s=61-106 components. There are 36 time grids between Ls=182.5 and Ls=357.5 with the step of Ls=5 degrees. Kinetic and potential energies can be derived from these values using the formulae in the paper.</p> <p>The file 'flux61ls5-lowdust.tar.xz' is the same as 'flux61ls5-my34.tar.xz', except the model output with the 'low-dust' scenario (Kuroda et al., 2019; Kuroda, 2019a, 2019b).</p> <p>The file 'scripts.zip' contains the FORTRAN scripts to derive the fluxes and physical parameters equivalent to the file 'flux61ls5-my34.tar.xz' from the model outputs in this dataset and Kuroda (2020), i.e. data180rdc-my34.tar.xz, data210rdc-my34.tar.xz, data240rdc-my34.tar.xz, data270rdc-my34.tar.xz, data300rdc-my34.tar.xz and data330rdc-my34.tar.xz. Also, the fluxes and physical parameters equivalent to the file 'flux61ls5-lowdust.tar.xz' can be derived with those scripts from the model outputs data180rdc.tar.xz, data210rdc.tar.xz, data240rdc.tar.xz, data270rdc.tar.xz, data300rdc.tar.xz and data330rdc.tar.xz which are available in Kuroda (2019a, 2019b).</p>
Data from: Upper atmosphere heating from ocean-generated acoustic wave energy
Colliding sea surface waves generate the ocean microbarom, an acoustic signal that may transmit significant energy to the upper atmosphere. Previous estimates of acoustic energy flux from the ocean microbarom and mountain/wind interactions are on the order of 0.01 to 1 mW/m2, heating the thermosphere by tens of degrees Kelvin per day. We captured up going ocean microbarom waves with a balloon borne infrasound microphone; the maximum acoustic energy flux was approximately 0.05 mW/m2. This is about half the average value reported in previous ground-based microbarom observations spanning eight years. The acoustic flux from the microbarom episode described here may have heated the thermosphere by several degrees Kelvin per day while the source persisted. We suggest that ocean wave models could be used to parameterize acoustically-generated heating of the upper atmosphere based on sea state.
Tropical Cyclone Characteristics Represented by the Ocean Wave Coupled Atmospheric Global Climate Model Incorporating Wave-Dependent Momentum Flux
<p>This is dataset of global climate model simulation used in the paper "Tropical Cyclone Characteristics Represented by the Ocean Wave Coupled Atmospheric Global Climate Model Incorporating Wave-Dependent Momentum Flux" by Shimura et al. (2021)</p> <p>Followings are the explanation of data file.</p> <p>*** File naming rule ***<br> {data_group_name}_Exp{experiment_name}_TCnumber{tropical_cyclone_case_number}.nc</p> <p> data_group_name<br> - atm<br> - track</p> <p> experiment_name<br> - Wind<br> - Wave<br> - SlabO</p> <p> tropical_cyclone_case_number<br> - 001<br> - 002<br> ...<br> - 099<br> - 100</p> <p>*** Description on each data group ***<br> <br> atm: three dimentional atmospheric velocity data<br> - level: pressure levels for vertical atmospheric data<br> - longitude: Longitude<br> - latitude: Latitude<br> - velocity_u_component: averaged atmospheric eastward velocity</p> <p> track: data around tropical cyclone track<br> - time: UTC time (YYYYMMDDHH)<br> - longitude_center: Longitude of typhoon center<br> - latitude_center: Latitude of typhoon center<br> - central_pressure: typhoon central pressure<br> - maximum_surface_wind: typhoon maximum surface wind speed<br> - longitude_sfc: Longitude for surface data around typhoon center<br> - latitude_sfc: Latitude for surface data around typhoon center<br> - surface_wind_u_component: surface eastward wind around typhoon<br> - surface_wind_v_component: surface northward wind around typhoon<br> - sea_level_pressure: sea level pressure around typhoon<br> - latent_heat_flux: surface upward latent heat flux<br> - sensible_heat_flux: surface upward sensible heat flux<br> - time_atm: UTC time (YYYYMMDDHH) for atmospheric data<br> - level: pressure levels for atmospheric data<br> - longitude_atm: Longitude for atmospheric data around typhoon center<br> - latitude_atm: Latitude for atmospheric data around typhoon center<br> - velocity_u_component: 3d eastward velocity around typhoon<br> - velocity_v_component: 3d northward velocity around typhoon</p> <p> </p>
Atmospheric visibility inferred from continuous-wave Doppler wind lidar, data set
<p>Visibility data from Pershore, UK, between 2018 and 2020</p>
Different behavior of density perturbations between dayside and nightside in the Martian thermosphere and the ionosphere associated with atmospheric gravity waves
<div>---------------------</div> <div>GENERAL INFORMATION</div> <div>---------------------</div> <div> </div> <div>1. Title of Dataset: Different behavior of density perturbations between dayside and nightside in the Martian thermosphere and the ionosphere associated with atmospheric gravity waves</div> <div> </div> <div>2. Authors: Nakagawa, England, et al.</div> <div> </div> <div>3. Contact information: hiromu.nakagawa.c1@tohoku.ac.jp</div> <div> </div> <div>4. Date of data collection: April 2024</div> <div> </div> <div> </div> <div>---------------------</div> <div>DATA & FILE OVERVIEW</div> <div>---------------------</div> <div> </div> <div>1. Original MAVEN data access:</div> <div> </div> <div>The MAVEN/NGIMS (level-2, version-8, revision-1) are publicly available in ASCII format on the NASA Planetary Data System (PDS) at https://atmos.nmsu.edu/data_and_services/atmospheres_data/MAVEN/ngims.html.</div> <div> </div> <div>As for references in Figures 2-4, the MAVEN/MAG Calibrated data are publicly available in ASCII format on the NASA Planetary Data System (PDS) at https://pds-ppi.igpp.ucla.edu/search/view/?id=pds://PPI/maven.mag.calibrated.</div> <div> </div> <div> </div> <div>2. File List:</div> <div> </div> <div>[1] correlate_coefficients.txt</div> <div>[2] rmse_170-190_coupling_case.txt</div> <div>[3] rmse_190-210_coupling_case.txt</div> <div>[4] rmse_170-190_ion_specific_case.txt</div> <div>[5] rmse_190_210_ion_specific_case.txt</div> <div> </div> <div>---------------------</div> <div>DATA-SPECIFIC INFORMATION</div> <div>---------------------</div> <div> </div> <div>[1] correlate_coefficients.txt</div> <div>This includes the geometric information and the calculated correlate coefficient between neutrals and ions in all profiles applied in this study. The first header provides the information in the file: Orbit, Year, Month, Day, Hour, Minute, Unix time, SZA(deg), Lon(deg), Lat(deg), LST(hr), CC(CO2-N2), CC(CO2-CO2+). The geometric information corresponds to those at altitude around 190 km. The last two columns represents the correlate coefficients between CO2 and N2 and between CO2 and CO2+. </div> <div> </div> <div>[2] rmse_170-190_coupling_case.txt</div> <div>This includes RMSE (the unit is percentage) between the observed perturbations and the model fit. The first header provides the information in the file: unix_time, orbit number, sza, lon, lat, lst, rmse_neu_gw_%, rmse_neu_aw_%, rmse_ion_gw_%, rmse_ion_aw_%. The geometric information corresponds to those at altitude around 190 km. The last four RMSEs represents those with the model to fit with the gravity waves (gw) parameters and with the acoustic waves (aw) for the neutral (neu) perturbations (N2) and for the ion (ion) perturbations (CO2+) at altitude range between 170 km and 190 km for the case of ion-neutral coupling case. </div> <div> </div> <div>[3] rmse_190-210_coupling_case.txt</div> <div>This includes RMSE (the unit is percentage) between the observed perturbations and the model fit. The first header provides the information in the file: unix_time, orbit number, sza, lon, lat, lst, rmse_neu_gw_%, rmse_neu_aw_%, rmse_ion_gw_%, rmse_ion_aw_%. The geometric information corresponds to those at altitude around 190 km. The last four RMSEs represents those with the model to fit with the gravity waves (gw) parameters and with the acoustic waves (aw) for the neutral (neu) perturbations (N2) and for the ion (ion) perturbations (CO2+) at altitude range between 190 km and 210 km for the case of ion-neutral coupling case. </div> <div> </div> <div>[4] rmse_170-190_ion_specific_case.txt</div> <div>This includes RMSE (the unit is percentage) between the observed perturbations and the model fit. The first header provides the information in the file: unix_time, orbit number, sza, lon, lat, lst, rmse_neu_gw_%, rmse_neu_aw_%, rmse_ion_gw_%, rmse_ion_aw_%. The geometric information corresponds to those at altitude around 190 km. The last four RMSEs represents those with the model to fit with the gravity waves (gw) parameters and with the acoustic waves (aw) for the neutral (neu) perturbations (N2) and for the ion (ion) perturbations (CO2+) at altitude range between 170 km and 190 km for the case of ion-specific case. </div> <div> </div> <div>[5] rmse_190_210_ion_specific_case.txt</div> <div>This includes RMSE (the unit is percentage) between the observed perturbations and the model fit. The first header provides the information in the file: unix_time, orbit number, sza, lon, lat, lst, rmse_neu_gw_%, rmse_neu_aw_%, rmse_ion_gw_%, rmse_ion_aw_%. The geometric information corresponds to those at altitude around 190 km. The last four RMSEs represents those with the model to fit with the gravity waves (gw) parameters and with the acoustic waves (aw) for the neutral (neu) perturbations (N2) and for the ion (ion) perturbations (CO2+) at altitude range between 190 km and 210 km for the case of ion-specific case. </div> <div> </div> <div>---------------------</div> <div>METHODOLOGICAL INFORMATION</div> <div>---------------------</div> <div> </div> <div>Period to analysis: from March 2015 to August 2020 (orbit number from 713 to 11881)</div> <div> </div> <div>Number of files (CO2): 8,911</div> <div> </div> <div>Number of files (N2): 8,913</div> <div> </div> <div>Number of files (CO2+): 7,053(?)</div> <div> </div> <div>Data selection:</div> <div> </div> <div>1. Neutral species with inbound valid (IV)</div> <div> </div> <div>2. Ion species with SCP (quality flag=0)</div> <div> </div> <div>3. Simultaneous observations of CO2, N2, and CO2+ at altitudes 170-210 km</div> <div> </div> <div>4. All three species CO2, N2, and CO2+ are valid with data sample >10 points in a single orbit.</div> <div> </div> <div>Total number of files after data selection = 3,018</div> <div> </div> <div>Fitting:</div> <div> </div> <div>4th-order polynomial fit to extract the perturbation components of density in the range between 160 and 220 km.</div> <div> </div> <div> </div> <div>Correlation coefficient:</div> <div> </div> <div>The correlation coefficients between perturbations are calculated in the range between 170 and 210 km.</div> <div> </div> <div>Ion-neutral coupling cases whose correlation coefficient between CO2 and CO2+ larger than 0.7: Total number = 839</div> <div> </div> <div>Ion-specific case whose correlation coefficient between CO2 and CO2+ smaller than 0.2: Total number = 823</div> <div> </div> <div>#We also define CME cases based on Lee et al. (2017): Total number = 31 cases</div> <div> </div>
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>
Atmospheric Wavenumber-4 driven South Pacific Marine Heat Waves and Marine Cool Spells
<p>Data and code files for</p> <p>Atmospheric Wavenumber-4 driven South Pacific Marine Heat Waves and Marine Cool Spells, Stephen M. Chiswell, Nature Communications ***** **** </p>
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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.