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1,574 results for “atmospheres”
Zonal mean of atmospheric water vapour and water vapour perturbation by emitted trace gases of hypersonic aircraft
<p>This short movie (no sound) shows two figures with time steps of five days over a period of fourteen years (2000-2014). On the left the atmospheric mixing ratio of water vapour is presented in parts per million. On the right the perturbation of stratospheric water vapour is depicted in parts per million. The perturbation is created by emitted water vapour of hypersonic aircraft flying at high altitudes (35 km). Over the years the accumulation of water vapour up to equilibrium is shown.</p>
Data from Potential source areas for atmospheric lead reaching Ny-Ålesund from 2010 to 2018
<p>date reports the sampling data in YYYY-MM-DD format and volume the sampling volume in m3.<br> pb_sign is = for Pb concentrarion data above limit of quantification (LoQ) and < for data below LoQ.<br> pb_val is numeric and it is the measured Pb concentration or LoQ in pg/m3.<br> pb is text and it is the measured Pb concentration or <LoQ in pg/m3.<br> al_ef is the enrichment factor (EF) EF(Pb/Al)c in comparison to the upper continental crust (UCC, Wedepohl 1995).<br> pb20x20y is the value measured for 20xPb / 20yPb isotope ratio.<br> u20x20y is the 95-confidence level uncertainty for the measured 20xPb / 20yPb isotope ratio value.<br> Missing values are reported as NA.<br> Wedepohl 1995: Wedepohl, K.H., 1995. The composition of the continental crust. Geochim. Cosmochim. Acta 58A, 959–960. https://doi.org/10.1180/minmag.1994.58A.2.234</p>
Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation
<p>Here is the surface mass balance calculated from a offline subsurface model, that is used in the paper Downscaled surface mass balance in Antarctica: impacts of subsurface processes and large-scale atmospheric circulation.<br> More data are available by contacting nichsen@space.dtu.dk</p>
Supplementary Material: A Large-Eddy Simulation Study of Vertical Axis Wind Turbine Wakes in the Atmospheric Boundary Layer
<p>Supplementary material for <em>Energies</em> <strong>2016</strong>, <em>9</em>, 366; doi:10.3390/en9050366:</p> <p><strong>Video S1:</strong> Normalized instantaneous streamwise velocity field both on a vertical plane (<em>x</em>-<em>z</em>) going through the center of the turbine and on a horizontal plane at the equator height of the turbine (Note: the physical time corresponding to this video is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p> <p><strong>Video S2:</strong> Normalized instantaneous streamwise velocity field on a horizontal plane at the equator height of the turbine for two cases: when the turbine starts to operate (top) and when the flow has reached statistically steady condition (bottom) (Note: the physical time corresponding to both videos is 1 minute and 17 seconds, and the size of the blades is magnified for illustration purposes).</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (T- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 575 to 1200 K (applicable for T- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 1300 to 2400 K (applicable for L- type objects) are available in the Zenodo DOI :- <a href="../records/10385987">https://zenodo.org/records/10385987</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020</a> HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> PH3 abundance is treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. Therefore in our v2 of this model grid we will further diminish the abundance.</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (L- type Models)
<ul> <li><strong>Overview of V2: "The Sonora Substellar Atmosphere Models. V: A Correction to the Disequilibrium Abundance of CO2 for Sonora Elf Owl"</strong></li> </ul> <p> Version 2 of the Sonora Elf Owl Models updates the CO2 and PH3 abundances and spectra. As described in the Wogan et al. (2024) research note (URL OF NOTE GOES HERE), Version 1 of the models did not apply the CO2 quench approximation properly resulting in predicted CO2 abundances that were too small by several orders of magintude in some cases. Version 2 fixes this mistake, updating CO2 abundances and the emission spectra to reflect the new CO2 abundances. Version 2 also removes all spectra contributions of PH3 because Version 1 consistently contained too much PH3 absorption when compared to JWST data (Veiler et al. 2024, <a href="http://doi.org/10.3847/1538-4357/ad6759" target="_blank" rel="noopener noreferrer">http://doi.org/10.3847/1538-4357/ad6759</a>).</p> <p> </p> <ul> <li><strong>Overview of V1</strong></li> </ul> <p> The Sonora Elf Owl Models is a successor to the <a href="../records/5063476#:~:text=This%20particular%20set%20of%20model,g%20are%200.25%20or%200.5.">Sonora Bobcat</a> and <a href="../records/4450269">Sonora Cholla</a> models. The Sonora Elf Owl model grid includes cloud-free radiative-convective equilibrium model atmospheres with vertical mixing induced disequilibrium chemistry with sub-solar to super-solar atmospheric metallicities and Carbon-to-Oxygen ratio. The atmospheric models have been computed using the open-source radiative-convective equilibrium model <a href="https://natashabatalha.github.io/picaso/">PICASO</a>. The parameters included within this grid are effective temperature (<strong><em>Teff</em></strong>), gravity (<strong><em>log(g)</em></strong>), vertical eddy diffusion coefficient (<strong><em>log(Kzz)</em></strong>), atmospheric metallicity (<strong><em>[M/H]</em></strong>), and Carbon-to-Oxygen ratio (<strong><em>C/O</em></strong>).</p> <p>The ranges and increments of these parameters are described in the published paper.<br><br></p> <ul> <li><strong>Three grids available on three links</strong></li> </ul> <p><strong> The model grid has been presented using three Zenodo repositories. This repository has all the models between 1300 to 2400 K (applicable for L- type objects). The models for Teff between 275 to 550 K (applicable for Y- type objects) are available in the Zenodo DOI :- <a href="../records/10381250">https://zenodo.org/records/10381250</a>. The models for Teff between 575 to 1200 K (applicable for T- type objects) are available in the Zenodo DOI :- <a href="../records/10385821">https://zenodo.org/records/10385821</a>.</strong></p> <p> </p> <ul> <li><strong> File types and how to use them</strong></li> </ul> <p> The models have been presented in the Xarray format so that all the atmospheric properties including the T(P) profile, atmospheric chemistry, and thermal emission spectra can be accessed within the same files. A python based Jupyter notebook named "Reading and plotting Elf Owl Models.ipynb" has been also supplied which demonstrates how to open and use these files.</p> <ul> <li> <strong>Spectra</strong></li> </ul> <p> The emission spectra for each atmospheric model has been computed between 0.6 to 15 microns. The reported flux is in the units of erg/s/cm<sup>2</sup>/cm. Note that these fluxes need to be multiplied with R<sup>2</sup>/D<sup>2</sup> before comparing them with the typically observed flux of brown dwarfs/exoplanets. R is the radius of the object, and D is the distance here.</p> <div> </div> <div> <ul> <li><strong>Note on CH4</strong></li> </ul> </div> <p> As stated in <a href="https://ui.adsabs.harvard.edu/abs/2023ApJ...942...71M/abstract">Mukherjee et al. 2023 </a>our CH4 opacity is derived using the <a href="https://iopscience.iop.org/article/10.3847/1538-4365/ab7a1a">Hargreaves et al. 2020 </a>HITEMP line list and computed using the HAPI code (<a href="https://www.sciencedirect.com/science/article/abs/pii/S0022407315302466">Kochanov et al. 2016</a>). HAPI automatically pre-weights the isotopologues according to earth abundances that are listed on the HITRAN website (<a href="https://hitran.org/lbl/2?6=on" target="_blank" rel="noopener noreferrer">see here for CH4</a>). Therefore, users should note that there will be minor features of CH3D included in the models. Given the general absence of deuterated molecules in brown dwarfs (Teff>~300) we will include a second posting of models which includes the Elf Owl grid with <strong>only</strong> the major CH4 isotopologue (12C-H4).</p> <div> <ul> <li><strong>Note on PH3</strong></li> </ul> </div> <p> In v1, PH3 abundance was treated separately from the general disequilibrium scheme. This is because of the current non-detection of PH3 in many brown dwarf atmospheres (see citations in paper). The current PH3 treatment uses the chemical equilibrium treatment described in Visscher et al. However, after publishing this grid and using the model for analysis of high precision JWST data, we noticed that even the simple chemical equilibrium treatment which reduces the abundance, introduces a noticeable PH3 feature. In v2 we completely remove the contribution of PH3. </p>
sunset: A database of synthetic atmospheric-escape transmission spectra for nearly every transiting exoplanet
<div> <div> <p><strong>This sunset version belongs to the A&A paper. The sunset database belonging to the arXiv pre-print can be found as version 1 of this Zenodo repository.</strong></p> <p>This repository contains the sunset database of atmospheric-escape transmission spectra for most currently known transiting exoplanets. This database is described in Linssen et al. (2025). The complete zipped (unzipped) database is ~5GB (~28GB). To prevent a huge download just to access a specific single planet model, we have uploaded sunset in a few different batches. The "zip_dictionary.txt" file lists each planet and which zip batch it is in. </p> <p>For each planet, there are three files:<br>- The "info" file contains warnings that pertain to that planet specifically (for general warnings that apply to each planet, see Linssen et al. 2025). It also lists the used planetary parameters, and the transit depth, equivalent width, S/N prefactors and transmission spectroscopy metrics for a few spectral lines. Finally, it gives simple step-by-step instructions on how to reproduce the model results using sunbather.<br>- The "spectrum_sparse" file contains the transmission spectrum. In principle, the spectrum runs from 911 to 11,000 angstroms in 1,000,000 bins (translating to R~400,000). However, in large portions of this wavelength grid, there are no spectral lines and the transit spectrum is simply equal to the continuum. To keep the file size to a minimum, we have removed those continuum regions from the spectrum, resulting in a "sparse" spectrum.<br>- The "structure" file contains the radial atmospheric structure profiles of the density, velocity, temperature and mean molecular weight.</p> <p>Additionally, this repository includes "included_lines_by_species.txt" and "included_lines_by_wavelength.txt", which list all the spectral lines that are present in the transmission spectra. Lines are labeled by the specific ion that they originate from, as well as the energy level. The energy level is expressed as a number, where 1 is the ground state, 2 is the first excited state, etc. Translating this energy level into the atomic configuration can be done by looking in the sunbather source code: in the /sunbather/src/sunbather/RT_tables/ folder, each ion has a file such as "Fe+_levels_processed.txt", which lists the energy levels and their atomic configurations.</p> <p>Finally, there is a large tabular file called "sunset_overview.csv". This file includes the NASA Exoplanet Archive parameters of each exoplanet. Additionally, there are some columns that we added, with calculated variables such as the atmospheric mass-loss rate, the Parker wind temperature, and line depths, equivalent widths, S/N prefactors and TSM metrics for various spectral lines. See the file header for explanation of each column. The file can easily be read in Python using pandas.read_csv("sunset_overview.csv", comments="#")</p> </div> </div>
CESM2 Atmospheric CO2 without agricultural management
This dataset was created to understand the impacts of agriculture on CO2 concentrations. Two 1-degree simulations were branched from the CMIP6 "CESM2-esm-hist" simulation in 1970. The first of these turned off the explicit representation of agriculture so that all crop areas are represented as "generic" C3 crops, where crop phenology is simulated as C3 grasses and do not include irrigation or fertilization (referred to as "generic crop"). The second uses the explicit representation of agriculture but removes industrial N fertilization (referred to as "no fertilization"). To ensure that changes in CO2 fluxes were minimally impacted by model drift, each simulation equilibrated carbon fluxes in 1970 by cycling over a single year of forcing for ten years. The CESM2 simulated these alternative representations of agriculture in a CO2 emissions-forced historical scenario following the "esm-hist" experimental protocol.
ECMWF ERA interim derived atmospheric mass, moisture and energy budget products
<p>As observations and atmospheric reanalyses have improved, the diagnostics that can be computed with confidence also increase. Accordingly, a new formulation of the energetics of the atmosphere is laid out, with a view to advancing diagnostic studies of Earth's energy budget and flows. It is utilized to produce assessments of the vertically integrated divergences in both the atmosphere and ocean. Careful conservation of mass is required, with special attention given to the hydrological cycle and redistribution of mass associated with precipitation and evaporation, and a new method for ensuring this is developed. It guarantees that the atmospheric divergence is associated with moisture and precipitation, unlike previous methods. A new term, identified as associated with the enthalpy of precipitation, is included in a preliminary way. It is sensitive to the formulation, and the use of temperature in degrees Celsius instead of Kelvin greatly reduces errors and produces the extra term with values up to about 65 W/m2. New results for 2000 to 2017 are presented for the vertical-mean and annual-mean diabatic atmospheric heating, atmospheric moistening, and total atmospheric energy divergence. Results for the atmospheric divergence are combined with top-of-atmosphere radiation observations to deduce total surface energy fluxes.</p> <p>These data files are monthly and span from 1979 to 2017, smoothed at T-106 resolution. The data format is NetCDF. A full dataset description is available at https://journals.ametsoc.org/view/journals/clim/31/16/jcli-d-17-0838.1.xml</p>
Final data used in JGR-Atmosphere manuscript 2023JD039605
<p>Final processed data used to generate all figures in the revised manuscript (2023JD039605) to Journal of Geophysical Research - Atmospheres.</p><p>All data are in self descriptive netCDF formats.</p><ul><li>codes.tar.gz contains Python scripts/notebooks used to process and visualize the data.</li><li>Feng2023JGR_rev1_data.tar.gz contains final processed data used to generate graphics in the manuscript.</li></ul>
Data Sets: Estimating scalar turbulent fluxes with slow-response sensors in the stable atmospheric boundary layer
<p>Date of data analysis: Statistical analyses conducted throughout the 2023 year </p><p>Information about funding sources that supported the collection of the data:</p><p>The research was supported by the Cooperative Institute for Modeling the Earth System at Princeton University under Award NA18OAR4320123 from the National Oceanic and Atmospheric Administration, and by the US National Science Foundation under award number AGS 2128345. Also, it was supported by the National Defense Science and Engineering Graduate Fellowship from the U.S. Department of Defense and Army Research Office. Similarly, the National Science Foundation provided support to complete the PHOXMELT field studies (Grant PLR- 1417914) to collect the data. Also, the study was supported by the U.S. National Science Foundation (NSF-AGS-2028633) and the Department of Energy (DE-SC0022072).</p><p>The statements, findings, conclusions, and recommendations are those of the authors and do not necessarily reflect the views of the National Oceanic and Atmospheric Administration.</p><p>This dataset contains the observational data for the two field experiments (Barrow and Wendell) in .nc file format.</p>
Reconstruction of atmospheric H2 from Greenland and Antarctic firn air
<p>This data set contains:</p> <ol> <li>firn air depth profiles of H<sub>2</sub> from 4 polar sites (South Pole and Megadunes in Antarctica) and NEEM and Summit in Greenland used to by Patterson et al., in press to reconstruct the history of atmospheric H<sub>2</sub> </li> <li>Matlab code for the UCI firn air model and data used in the reconstructions </li> </ol> <p>Reference: Patterson, J. D., Aydin, M., Crotwell, A. M., Pétron, G., Severinghaus, J. P., Krummel, P. B., Langenfelds, R. L., Petrenko, V. V., and Saltzman, E. S.: Reconstructing atmospheric H<sub>2</sub> over the past century from bi-polar firn air records, Clim. Past, https://doi.org/10.5194/cp-2023-27, in press.</p> <p>Note: The firn air depth profiles archived here are processed to remove outliers and average replicates. For raw data, please contact the laboratories at which the measurements were made (G. Petron, GML/NOAA; P. Krummel; CSIRO). </p>
Dataset for illustrative examples using the Lagrangian Atmospheric moisTure and heaT trackINg (LATTIN) tool
<p>This dataset provides the FLEXPART outputs for the illustrative examples of LATTIN usage. See the LATTIN GitHub repository (https://github.com/apalarcon/LATTIN) for details.</p><p>It was generated using FLEXPART model v9 fed by ERA-Interim reanalysis at the Environmental Physics Laboratory (EPhysLab) at the University of Vigo. See the list of publications of the EPhysLab research group for details on these simulations (https://ephyslab.uvigo.es/moisturetransport/index.php/Publications). </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>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the Max Forest scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the base scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
CESM2 atmosphere output data for study on hydrological impacts of large-scale forest expansion
<p>This repository contains the atmosphere output data from CESM2 which was generated in the study investigating the hydrological impacts of global-scale forestation, for the No LULCC scenario. The datasets cover the period 2015-2100. Output fields are as follows:</p> <p>CCN3: concentration of cloud condensation nuclei at 0.1% supersaturation, units cm^-3</p> <p>CLDLOW: cloud fraction integrated between 1200-700 hPa, units fraction of grid cell</p> <p>CONCLD: convective cloud cover, units fraction of grid cell</p> <p>GCLDLWP: grid cell cloud water path, units kg m^-2</p> <p>LWCF_d1: clean longwave cloud forcing, units W m^-2</p> <p>OMEGA: vertical velocity, units Pa s^-1</p> <p>PRECT: total precipitation, units m s^-1</p> <p>SWCF_d1: clean shortwave cloud forcing, units W m^-2</p> <p>V: meridional wind, units m s^-1</p> <p> </p> <p>All data were generated and processed by James A. King.</p>
Potential Ozone Depletion from Satellite Demise during Atmospheric Reentry in the Era of Mega-Constellations
<p>Dataset support to "Potential Ozone Depletion from Satellite Demise during Atmospheric Reentry in the Era of Mega-Constellations"</p>
Hourly time series of soil and atmosphere variables at the experimental site of El Cautivo, Tabernas Desert, Almeria, Spain (February 2018 to December 2019)
<p>Measurements were performed along a hypothetical succession of biological soil crusts. Main studied variables were the soil-atmosphere CO2 and water vapor fluxes. This dataset was used by Lopez-Canfin et al. (2022) and Kim and al. (2024) at the time of publication.</p>
Simulation dataset and plotting scripts used for journal article "Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments" by Sengupta and Prisle (2024)
<p>Simulation data underlying all figures presented in "Surface modulated dissociation of organic aerosol acids and bases in different atmospheric environments" by Sengupta and Prisle (2024) <a href="http://dx.doi.org/10.1080/02786826.2024.2323641" target="_blank" rel="noopener noreferrer">http://dx.doi.org/10.1080/02786826.2024.2323641</a>. </p> <p>The data for each figure and the plotting scripts are included in a zip file labelled by the figure number as presented in the paper and accompanying supplement.</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.