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1,574 results for “atmospheres”
Oxidation of thin films at the air-water interface of atmospheric aerosol
<p>X-ray reflectivity data (reflectivity vs Q) for the oxidation of insoluble organic material at the air-water interface. The organic material was extracted from atmospheric aerosol and sea water samples. The organic material was reacted with gas-phase ozone and aqueous phase hydroxyl radicals. The reflectivity data was collected at the Diamond Light source on I07 in May 2013 (SI8744) and April 2014 (SI9632) funded by STFC and NERC. The data supports a publication in Atmospheric Environment entitled “Are organic films from atmospheric aerosol and sea water inert to oxidation by ozone at the air-water interface?"</p>
Causes and importance of new particle formation in the present-day and pre-industrial atmospheres: supporting data
<p>Data presented in the manuscript "Causes and importance of new particle formation in the present-day and pre-industrial atmospheres" currently in review.</p> <p>Particle number concentrations (files with initial word "CCN" or "N3") have units of particles per cubic centimetre, calculated at ambient temperature and pressure. Files with initial word "solar" have units of percent. Ion production rates have units ion pairs per cubic centimetre per second.</p> <p>The simulation data presented here was generated with the GLOMAP aerosol model, https://www.see.leeds.ac.uk/research/icas/research-themes/atmospheric-chemistry-and-aerosols/groups/aerosols-and-climate/the-glomap-model/ running on a T42 grid.</p> <p>The manuscript associated with this data was written using results from the CLOUD experiment at CERN, and the author list is a subset of the CLOUD collaboration.</p> <p> </p> <p> </p>
A dataset of atmospheric ozone above the Mexico City basin retrieved from FTIR remote sensing observations made at two different ground altitudes
<p>This dataset of atmospheric ozone (O<sub>3</sub>) has been generated from solar absorption spectra measured in central Mexico using ground-based Fourier-Transform Infrared (FTIR) spectrometers. The FTIR experiments have been operated by the “Spectroscopy and Remote Sensing” Research Group of the Centro de Ciencias de la Atmósfera of the Universidad Nacional Autónoma de México (http://www.atmosfera.unam.mx/espectroscopia/index.html).</p> <p>The dataset covers measurements made between November 2012 and February 2014 applying two different FTIR spectrometers. The first instrument offers very high resolution spectra and contributes to NDACC (Network for the Detection of Atmospheric Composition Change). It is located at the mountain observatory of Altzomoni (ALTZ) about 1700m above the Mexico City basin. The second instrument has a medium spectral resolution and is located inside of Mexico City at the Universidad Nacional Autónoma de México (UNAM) at a horizontal distance of about 60km to the mountain observatory.</p> <p>The here provided dataset consists of two NETCDF data-files for each station and a MATLAB script for reading the NETCDF files. The files “ALTZ_IFS125_O3.nc” and “UNAM_IFS125_O3.nc” contain the retrieved O<sub>3</sub> state vectors, the O<sub>3</sub> averaging kernels and the O<sub>3</sub> a priori profiles, together with auxiliary data: observation time, observation geometry, instrumental settings, atmospheric temperature and humidity profiles. The data as well as the method for combining the two different observations are presented in Plaza-Medina et al. (2017), which should be consulted for more details.</p> <p>The files “ALTZ_IFS125_O3_Jac+Gain.nc” and “UNAM_IFS125_O3_Jac+Gain.nc” contain the Jacobians (for O<sub>3</sub> as well as for error sources) and the Gain matrix, together with the auxiliary data. The MATLAB script “readNETCDF_and_combine2FTIR.m” reads the NETCDF files and performs the operations needed for the generation of a combined product, thereby exploiting the synergetic effects of two observations made in coincidence but at different ground altitudes.</p> <p>A related dataset with Altzomoni O<sub>3</sub> profiles obtained by applying slightly different retrieval settings is available at the NDACC database (ftp://ftp.cpc.ncep.noaa.gov/ndacc/station/altzomoni/hdf/ftir/). Further datasets of atmospheric parameters as measured by different techniques are available at the webpage of the Red Universitario de Observaciones Atmosfericas (www.ruoa.unam.mx).</p>
The Sonora Substellar Atmosphere Models. IV. Elf Owl: Atmospheric Mixing and Chemical Disequilibrium with Varying Metallicity and C/O Ratios (Y- 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> <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 Teff of 275 to 550 K (applicable to Y-type objects). 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>. 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>
STEMMUS-SCOPE for PLUMBER2: A Physically Consistent Dataset Across the Soil-Plant-Atmosphere Continuum
<p>High-quality and long-term measurements of water, energy, and carbon fluxes between the land and atmosphere are critical for climate monitoring and land surface model (LSM) benchmarking. This dataset presents high-quality and long-term fluxes, and the corresponding above and below-ground hydrological, physiological, photosynthetic and radiative data derived from the STEMMUS-SCOPE model simulations for the PLUMBER2 project at 170 FLUXNET sites. The generated datasets by STEMMUS-SCOPE are in good agreement with quality in-situ measurements. Therefore, we recommend future applications of the datasets, for such as the detection and attribution of historical changes of fluxes and SM and associated extreme events, providing the initial and boundary conditions for atmospheric models, benchmarking various types of models, and monitoring drought risks. The published dataset can contribute to the development of earth system models in better representing land surface processes and land-atmosphere exchanges in forms of energy, water, and carbon.</p>
NCAR/ACOM FTIR Atmospheric Composition Dataset
<p>The NCAR/ACOM Optical Techniques Project operates three high spectral resolution, solar viewing FTIR instruments at Thule, Greenland (76.5ºN, 291.3ºE, 225 masl), Boulder Colorado (40.03ºN, 254.7ºE, 1612 masl) and Mauna Loa Observatory Hawaii (19.5ºN, 204.4ºE, 3396 masl). These instruments operate within the framework of the Network for the Detection of Atmospheric Composition change (NDACC). The raw data are recorded autonomously and downloaded to ACOM servers daily. They are processed at ACOM and produce vertical profiles of several trace atmospheric constituents: O3, HNO3, HCl, HF, CO, N2O, CH4, HCN, C2H6, OCS, H2CO, H2O and ClONO2. These data constitute a long-term reference dataset for tropospheric and stratospheric chemistry investigations.</p> <p>The data, along with metadata and full error analysis are saved to GEOMS conforming HDF files. Per our agreement with NDACC and our sponsor NASA, they are uploaded bi-yearly to the NDACC data handling facility (DHF) at www.ndacc.org. For select species, HDF files are uploaded on a near-real-time basis for the CAMS27 project which use the data for realtime air quality forecasting. Once these data are uploaded they are publicly available. The NDACC has implemented Creative Commons licensing designations for data at the DHF. These data maintain a CC0 license.</p>
dataset for: Carbonate content and stable isotopic composition of atmospheric aerosol carbon in the Canadian High Arctic
<p>Dataset related to publication of the same title in <a href="https://www.atmospheric-chemistry-and-physics.net/">Atmospheric Chemistry and Physics</a></p>
Global continuous 0.05 degree atmospheric carbon dioxide dataset (GCXCO2) based OCO-2 satellite, CAMS and CarbonTracker simulation data from 2000 to 2020
<p>This dataset provides global seamless 8-day XCO2 (column-averaged CO2 dry air mole fraction) with a spatial resolution of 0.05 degree from 2000 to 2020. The unit is ppm. The detailed process and product validation accuracy can be found in our paper at https://doi.org/10.1016/j.scitotenv.2024.177051</p>
Dynamically coupled kinetic chemistry in brown dwarf atmospheres - II. Cloud and chemistry connections in directly imaged sub-Jupiter exoplanets
<p>Gifs of GCM output from the paper, model is Teff = 1000 K, log g = 3, M/H = 1. </p><p>The atmos_daily_2980.nc file contains the GCM NETCDF output at 2080 days.</p>
Data & code for 'BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations'
<p>Code and data required to reproduce the manuscript ‘BoundaryLayerDynamics.jl v1.0: a modern codebase for atmospheric boundary-layer simulations’, submitted for publication in Geoscientific Model Development.</p>
Mount Holyoke College Laser Induced Breakdown Spectra; SuperLIBS 10K; Earth and vacuum atmospheres
<p>Laser induced breakdown spectra of reference targets with known composition. Spectra were acquired on the SuperLIBS instrument at Mount Holyoke College under a ambient (Earth) and vacuum atmospheric conditions at laser energies of 2.4 mJ, 3.2 mJ, and 4.0 mJ (Earth) and 2.4 mJ, 4.0 mJ, 5.6 mJ, and 7.2 mJ (vacuum). Processing includes baseline removal (airPLS) and normalization within each spectral region (UV, VIS, and VIS-NIR). This is a subset of a larger LIBS reference database that will be available on the NASA PDS Geosciences node at: https://doi.org/10.17189/b2aj-cz96. This research was supported by NASA grant 80NSSC21K0888.</p>
CFS model monthly mean diurnal cycles of ocean and atmosphere variables at TAO mooring locations
<p>v0.1.3</p> <p>cfsm501_ocn_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly ocean variables: one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains water temperature with dimensions (time, depth, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v0.1.2</p> <p>cfsm501_atmo_2002_2006_TAOpoints_3D_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, plev, lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p> <p>-------------------------</p> <p>v0.1.1</p> <p>cfsm501_atmo_2002_2006_TAOpoints_hourly.tgz -- contains netCDF files of hourly atmosphere variables: one atmosphere file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, lat, lon) at TAO locations. If joining multiple files together, concatenate along the time axis.</p> <p>-------------------------</p> <p>v 0.1.0</p> <p>cfsm501_atmo_ocn_2002_2006_TAOpoints_monthlyMeanDiurnalCycle.tgz -- contains netCDF files of monthly mean diurnal cycle of ocean and atmosphere variables: one atmosphere and one ocean file per month over 4 years (2002-2006).</p> <p>Each file contains multiple variables with dimensions (time, hour, [depth,] lat, lon) at TAO locations. The dimension "time" is of length 1 in all files. If joining multiple files together, concatenate along the time axis. The "hour" dimension represents the 24 hours of the diurnal cycle.</p> <p>Note that this version of the data has NOT had the 3-day high pass filter applied before the diurnal cycle calculation.</p>
Supplementary Material: The Importance of Optical Wavelength Data on Atmospheric Retrievals of Exoplanet Transmission Spectra
<p>Supplementary material for "The Importance of Optical Wavelength Data on Atmospheric Retrievals of Exoplanet Transmission Spectra" DOI: <a href="https://ui.adsabs.harvard.edu/link_gateway/2024arXiv240307801F/doi:10.48550/arXiv.2403.07801" target="_blank" rel="noreferrer noopener">10.48550/arXiv.2403.07801</a></p> <p>Contents of this record:</p> <ul> <li>The retrieved atmospheric parameters for the population (see supplementary_material.pdf).</li> <li>The retrieval statistics per planet for the wavelength ranges 0.3-4.5, 0.6-4.5, and 1.1-4.5 microns (see supplementary_material.pdf).</li> <li>Planet specific retrieved spectra for the wavelength ranges 0.3-4.5, 0.6-4.5, and 1.1-4.5 microns.</li> <li>Retrieved parameter cornerplots per planet for the wavelength ranges 0.3-4.5, 0.6-4.5, and 1.1-4.5 microns.</li> </ul> <p>(NOTE: the retrieval model and priors for the results displayed in this record are specified in tables 2 and 3 of the paper.)</p>
Contents for: Influence of Ionization on the Polytropic Index of the Solar Atmosphere within Local Thermodynamic Equilibrium Approximation
<p>This is the data used for the creation of the manuscript figures. Explanation about the data is in the "README.txt" file. Version 2 includes compressed archive file containing Fortran module files with subroutines and input data files for the calculations of the study.</p>
COAMPS-TC atmospheric data subset for Hurricane Michael
<p>Hurricane Michael was a Category 5 hurricane when it made landfall on the Florida Panhandle on 10 October 2018. The data subset of the Hurricane Michael Coupled Ocean/Atmosphere Mesoscale Prediction System for Tropical Cyclones (COAMPS-TC) was utilized for the manuscript "In situ observations at the air-sea interface by expendable air-deployed drifters under Hurricane Michael (2018)". Zonal and meridional 10-m winds were subset for designated time steps and interpolated to the time and location of the drifter observations. The wind fields were used in calculations of wave age and to compare to drifter observed winds and European Centre for Medium-Range Weather Forecasts (ECMWF) Earth Reanalysis version 5 reanalysis (ERA5) wind.</p>
Ambient noise from the atmosphere within the seismic hum period band: A case study of hurricane landfall
<p>Spectral analysis results, synthetic Green's functions, and seismic modeling results of this study.</p> <p>This work can be found at GitHub: <a href="https://github.com/NickJi98/Atm_Noise_2024_EPSL.git">https://github.com/NickJi98/Atm_Noise_2024_EPSL.git</a></p>
Data for: Evolution of avian heat tolerance: The role of atmospheric humidity
<p>The role of atmospheric humidity in the evolution of endotherms' thermoregulatory performance remains largely unexplored, despite elevated atmospheric humidity being known to impede evaporative cooling capacity. Using a phylogenetically informed comparative framework, we tested the hypothesis that pronounced hyperthermia tolerance among birds occupying humid lowlands evolved to reduce the impact of humidity-impeded scope for evaporative heat dissipation by comparing heat tolerance limits (HTL; maximum tolerable air temperature), maximum body temperatures (<em>T</em><sub>b</sub><em>max</em>) and associated thermoregulatory variables in humid (19.2 g H<sub>2</sub>O m<sup>− 3</sup>) <em>versus</em> dry (1.1 g H<sub>2</sub>O m<sup>− 3</sup>) air among 30 species from three climatically distinct sites (arid, mesic montane and humid lowland). Humidity-associated decreases in evaporative water loss and resting metabolic rate were 27 - 38% and 21 - 27%, respectively, and did not differ significantly between climatic sites. Decreases in heat tolerance limits were significantly larger among arid-zone (mean ± SD = 3.13 ± 1.12 °C) and montane species (2.44 ± 1.0 °C) compared to lowland species (1.23 ± 1.34 °C), with more pronounced hyperthermia among lowland (<em>T</em><sub>b</sub><em>max</em> = 46.26 ± 0.48°C) and montane birds (<em>T</em><sub>b</sub><em>max</em> = 46.19 ± 0.92°C) compared to arid-zone species (45.23 ± 0.24°C). Our findings reveal a functional link between facultative hyperthermia and humidity-related constraints on evaporative cooling, providing novel insights into how hygric and thermal environments interact to constrain avian performance during hot weather. Moreover, the macrophysiological patterns we report provide further support for the concept of a continuum from thermal specialization to thermal generalization among endotherms, with adaptive variation in body temperature correlated with prevailing climatic conditions.</p>
Models (atmospheric and atomic) for the P-CORONA code together with some sample runs.
<p>The dataset comprises some sample example runs with all necessary input parameters and corresponding outputs expected from P-CORONA, along with a few atomic and atmospheric models. Description of the files included is given in the README.txt file.</p> <p>The P-CORONA code can be obtained at <a href="https://gitlab.com/polmag/P-CORONA">https://gitlab.com/polmag/P-CORONA</a> and its documentation at <a href="https://polmag.gitlab.io/P-CORONA/">https://polmag.gitlab.io/P-CORONA/</a></p> <p>The version of P-CORONA used to generate this dataset (which corresponds to the commit #85d7552 in <a href="https://gitlab.com/polmag/P-CORONA">https://gitlab.com/polmag/P-CORONA</a>) can be found at: <a href="https://doi.org/10.5281/zenodo.15195460">https://doi.org/10.5281/zenodo.15195460</a></p>
Coupled Ocean-atmospheric forcing on Indian Summer Monsoon variability during the middle Holocene: Insights from the Core Monsoon Zone speleothem record.
<p>Stable oxygen and carbon isotope data of stalagmite sample during middle Holocene time from Mahadev cave of Jagdalpur region in Central India.</p>
Spring tropical cyclones modulate near-surface isotopic compositions of atmospheric water vapour at Kathmandu, Nepal
<p>All these data have been published in a ACP paper. If you use these data in any conditions, please cite the following publicaiton: Adhikari, N., Gao, J., Zhao, A., Xu, T., Chen, M., Niu, X., and Yao, T.: Spring tropical cyclones modulate near-surface isotopic compositions of atmospheric water vapour at Kathmandu, Nepal, EGUsphere, https://doi.org/10.5194/egusphere-2023-2186, 2023.</p>
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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.
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DANDI Archive for NWB datasets
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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.