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15 results for “mesosphere”
Nitric oxide (NO) data set (60--160 km) from SCIAMACHY mesosphere--lower thermosphere limb scans
<p><strong>Overview</strong><br> Contains the nitric oxide (NO) number densities (in cm<sup>-3</sup>) from 60 km to 160 km retrieved from SCIAMACHY mesosphere--lower thermosphere (MLT, 50--150 km) limb scans.</p> <p>SCIAMACHY is a UV-visible-near-infrared spectrometer which flies on ESA's Envisat and was operational from 08/2002 to 04/2012 (see Burrows et al., 1995 and Bovensmann et al., 1999 and references therein). The Mesosphere--Lower Thermosphere (MLT) measurement mode was carried out from 07/2008 until the end of the mission for one day every 15 days. This data set comprises 84 days of SCIAMACHY MLT NO measurements, each<br> containing about 15 orbits.</p> <p>The NO retrieval was carried out at the Karlsruhe Institute of Technology (KIT), Karlsruhe, Germany, and is described in Bender et al., 2013. We used the SCIAMACHY geo-located atmospheric spectra (SCI_NL__1P) version 8.02 provided by ESA via their data browser at<br> https://earth.esa.int/web/guest/data-access/browse-data-products.<br> The spectra were calibrated with ESA's `SciaL1C` command line tool available for download at<br> https://earth.esa.int/web/guest/software-tools/content/-/article/scial1c-command-line-tool-4073.</p> <p>The SCIAMACHY NO data were compared to the results from ACE-FTS, MIPAS, and SMR in Bender et al., 2015, showing that all agree within the respective measurement uncertainties.</p> <p><strong>Acknowledgements</strong><br> The development of the retrieval was funded by the Helmholtz-society under the grant number VH-NG-624. The SCIAMACHY project, which was initiated by Professor Burrows in 1984, was funded by the German Aerospace Agency (DLR), the Netherlands Space Office NSO, formerly NIVR, and the Belgium ministry responsible for space. ESA funded the Envisat project. Professor Burrows of University of Bremen is the Principal Investigator. He and his research team comprising his colleagues in Bremen and international scientific collaborators led the scientific support and development of SCIAMACHY and the scientific exploitation of its data products.</p> <p>The SCIAMACHY instrument is developed by an industrial team headed by companies now known as Airbus SD on the German side and by Dutch Space on the Dutch side and included Belgium companies. The instrument and algorithm development is supported by the activities of the SCIAMACHY Science Advisory Group (SSAG), a team of scientists from various international institutions: University of Bremen (D), SRON (NL), SAO (USA), IASB (B), MPI Chemistry Mainz (D), KNMI (NL), University of Heidelberg (D), IMGA (I), CNRS-LPMA (F). Operational data processing is being performed by ESA and DLR-DFD within the ENVISAT ground segment. Support with respect to mission planning and operations is given by the SCIAMACHY Operations Support Team (SOST). The relevant work at the University of Bremen is funded by the University and State of Bremen.</p>
Polar mesospheric clouds from the Balloon Lidar Experiment (BOLIDE) during the PMC Turbo balloon mission
<p>This dataset contains BOLIDE lidar data obtained during the PMC Turbo balloon mission that was launched on 7 July 2018 from Esrange, Sweden and landed in Nunavut, Canada on 14 July 2018. The mission was designed to study small-scale atmospheric dynamics induced by breaking atmospheric gravity waves within the polar mesospheric cloud layer at ~82 km altitude. PMC Turbo floated at around 40 km altitude and carried seven digital cameras to image the polar mesospheric cloud layer and the first Rayleigh lidar to successfully operate from a balloon.</p> <p>The lidar data consists of volume backscatter coefficients of polar mesospheric clouds, available at 20 m vertical and 10 s temporal resolution, contained in a compressed netcdf file. The magnitude of volume backscatter coefficients scales with<br> the brightness of clouds imaged by the PMC Turbo cameras. The netcdf file further includes floating altitude, rotator angle (azimuth) as well as latitude and longitude of the lidar beam at 82 km altitude.</p> <p>Users are encouraged to contact us for discussion when using BOLIDE data.</p> <p>Data contact: natalie.kaifler@dlr.de</p> <p>References:</p> <p>PMC Turbo camera videos: https://svs.gsfc.nasa.gov/13073</p> <p>NASA Space Physics Data Facility: https://cdaweb.gsfc.nasa.gov/index.html/, select PMC Turbo</p> <p>DLR Institute mission database: https://halo-db.pa.op.dlr.de/mission/112</p> <p>Kaifler, N., Kaifler, B., Rapp, M., Fritts, D.C. The polar mesospheric cloud dataset of the Balloon Lidar Experiment BOLIDE. Earth System Science Data. In preparation.</p> <p>Kaifler, B., Rempel, D., Roßi, P., Büdenbender, C., Kaifler, N., and Baturkin, V.: A technical<br> description of the Balloon Lidar Experiment (BOLIDE), Atmos. Meas. Tech., 13, 5681–5695,<br> https://doi.org/10.5194/amt-13-5681-2020, 2020.</p> <p>Fritts, D. C., Miller, A. D., Kjellstrand, C. B., Geach, C., Williams, B. P., Kaifler, B.,<br> et al. (2019). PMC Turbo: Studying gravity wave and instability dynamics in the summer mesosphere<br> using polar mesospheric cloud imaging and profiling from a stratospheric balloon. Journal of<br> Geophysical Research: Atmospheres, 124, 6423– 6443. https://doi.org/10.1029/2019JD030298</p>
Climatology of Mesosphere and Lower Thermosphere Residual Circulations and Mesopause Height derived from SABER Observations
<p>SD-WACCM data used in "<strong>Climatology of Mesosphere and Lower Thermosphere Residual Circulations and Mesopause Height derived from SABER Observations"</strong></p>
The SPARC water vapour assessment II: Comparison of annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour observed from satellites
<p>Here we provide a NetCDF data set that contains the amplitudes and phases for the annual, semi-annual and quasi-biennial variations in stratospheric and lower mesospheric water vapour as observed by 30 satellite data sets. In addition, we combine the results from all data sets to provide average amplitudes and the corresponding standard deviations, among other.</p> <p>The content description of the NetCDF file looks as follows:</p> <p>netcdf results.amt-10-1111-2017 {<br> dimensions:<br> dataset = 30 ;<br> string_length = 60 ;<br> latitude = 37 ;<br> bands = 2 ;<br> altitude = 59 ;<br> variables:<br> char dataset_short(string_length, dataset) ;<br> dataset_short:standard_name = "data set" ;<br> dataset_short:long_name = "data set name" ;<br> dataset_short:description = "short label of data set" ;<br> char dataset_long(string_length, dataset) ;<br> dataset_long:standard_name = "data set" ;<br> dataset_long:long_name = "data set name" ;<br> dataset_long:description = "long label of data set" ;<br> double latitude(latitude) ;<br> latitude:standard_name = "latitude" ;<br> latitude:units = "degree_north" ;<br> latitude:minimum_value = "-90" ;<br> latitude:maximum_value = "90" ;<br> latitude:axis = "Y" ;<br> latitude:_CoordinateAxisType = "Lat" ;<br> double latitude_bands(bands, latitude) ;<br> latitude_bands:units = "degree_north" ;<br> double altitude(altitude) ;<br> altitude:standard_name = "altitude" ;<br> altitude:long_name = "pressure levels" ;<br> altitude:units = "hPa" ;<br> altitude:axis = "Z" ;<br> altitude:_CoordinateAxisType = "Alt" ;<br> double tropopause(latitude) ;<br> tropopause:standard_name = "tropopause" ;<br> tropopause:long_name = "tropopause pressure" ;<br> tropopause:description = "climatological tropopause pressure based on MERRA reanalysis data 2000 - 2014" ;<br> tropopause:units = "hPa" ;</p> <p>// global attributes:<br> :summary = "this file contains the results published in Lossow et al. (2017)" ;<br> :url = "https://www.atmos-meas-tech.net/10/1111/2017/amt-10-1111-2017.html" ;<br> :project = "second SPARC water vapour assessment (WAVAS-II)" ;<br> :creator_name = "Stefan Lossow & Farahnaz Khosrawi" ;<br> :creator_email = "stefan.lossow@kit.edu & farahnaz.khosrawi@kit.edu" ;<br> :creator_email_supplemental = "stefan.lossow@yahoo.se & f.khosrawi@gmail.com" ;<br> :value_for_nodata = "NaN" ;<br> :date_created = "20190105T112425Z" ;</p> <p>group: AO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the AO variation" ;<br> amplitude:description = "regression model is given by Eq. (1) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the AO variation" ;<br> phase:description = "regression model is given by Eq. (1) in the manuscript; phase calculation based on Eq. (3)" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (1) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-6,6] months interval by adding +/- 12 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group AO</p> <p>group: SAO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the SAO variation" ;<br> amplitude:description = "regression model is given by Eq. (4) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the SAO variation" ;<br> phase:description = "regression model is given by Eq. (4) in the manuscript; phase calculation based on Eq. (3)" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (4) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-3,3] months interval by adding +/- 6 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group SAO</p> <p>group: QBO {<br> dimensions:<br> latitude = 37 ;<br> altitude = 59 ;<br> dataset = 30 ;<br> variables:<br> double amplitude(dataset, altitude, latitude) ;<br> amplitude:standard_name = "amplitude" ;<br> amplitude:long_name = "amplitude of the QBO variation" ;<br> amplitude:description = "regression model is given by Eq. (5) in the manuscript; amplitude calculation based on Eq. (2)" ;<br> amplitude:units = "ppmv" ;<br> double phase(dataset, altitude, latitude) ;<br> phase:standard_name = "phase" ;<br> phase:long_name = "phase of the QBO variation" ;<br> phase:description = "regression model is given by Eq. (5) in the manuscript; phase is derived as the shift of the QBO regression fit for which the correlation with the Singapore (1N, 104E) winds at 50 hPa maximises" ;<br> phase:units = "month" ;<br> double offset(dataset, altitude, latitude) ;<br> offset:standard_name = "offset" ;<br> offset:long_name = "offset component of the regression model" ;<br> offset:description = "regression model is given by Eq. (5) in the manuscript; meant for calculation of relative amplitudes" ;<br> offset:units = "ppmv" ;<br> double screening(dataset, altitude, latitude) ;<br> screening:standard_name = "screening" ;<br> screening:long_name = "screening for the amplitude and phase data" ;<br> screening:description = "screening matrix for the amplitude and phase data to calculate the standard deviations described in Sect. 3.3; 1 means screening; 0 means no screening" ;<br> screening:units = "" ;<br> double phase_difference(dataset, altitude, latitude) ;<br> phase_difference:standard_name = "phase difference" ;<br> phase_difference:long_name = "phase difference with respect to the reference data set" ;<br> phase_difference:reference_data_set_short = "MLS" ;<br> phase_difference:reference_data_set_long = "Aura/MLS v4.2" ;<br> phase_difference:description = "phase difference has been adapted so that it not exceeds the [-14,14] months interval by adding +/- 28 months; has been calculated after the screening" ;<br> phase_difference:units = "month" ;<br> double amplitude_standard_deviation(altitude, latitude) ;<br> amplitude_standard_deviation:standard_name = "standard deviation of amplitude" ;<br> amplitude_standard_deviation:long_name = "standard deviation of amplitude over all data sets" ;<br> amplitude_standard_deviation:description = "standard deviation calculation based on Eq. (6)" ;<br> amplitude_standard_deviation:units = "ppmv" ;<br> double amplitude_mean(altitude, latitude) ;<br> amplitude_mean:standard_name = "mean amplitude" ;<br> amplitude_mean:long_name = "mean amplitude over all data sets" ;<br> amplitude_mean:description = "mean calculation based on Eq. (6)" ;<br> amplitude_mean:units = "ppmv" ;<br> double amplitude_relative_standard_deviation(altitude, latitude) ;<br> amplitude_relative_standard_deviation:standard_name = "relative standard deviation of amplitude" ;<br> amplitude_relative_standard_deviation:long_name = "relatuve standard deviation of amplitude " ;<br> amplitude_relative_standard_deviation:description = "relavtive standard deviation calculation based on Eq. (6); uses \"amplitude_mean\" as reference" ;<br> amplitude_relative_standard_deviation:units = "ppmv" ;<br> double phase_difference_standard_deviation(altitude, latitude) ;<br> phase_difference_standard_deviation:standard_name = "standard deviation of phase difference" ;<br> phase_difference_standard_deviation:long_name = "standard deviation of phase difference over all data sets" ;<br> phase_difference_standard_deviation:description = "standard deviation calculation based on Eq. (7)" ;<br> phase_difference_standard_deviation:units = "month" ;<br> double phase_difference_mean(altitude, latitude) ;<br> phase_difference_mean:standard_name = "mean of phase difference" ;<br> phase_difference_mean:long_name = "mean of phase difference over all data sets" ;<br> phase_difference_mean:description = "mean calculation based on Eq. (7)" ;<br> phase_difference_mean:units = "month" ;<br> } // group QBO<br> }</p> <p> </p>
Data files for A "Boreing" Night of Observations of the Upper Mesosphere and Lower Thermosphere Over the Andes Lidar Observatory
<p>The files in this set are data obtained from the ANI2 airglow imager located at the Andes Lidar Observatory.in Chile (30.23S, 70.73W, 2530 m). The files are named for a JGR paper by J. Hecht et al. entitled A "Boreing" Night of Observations of the UpperMesosphere and Lower Thermosphere Over the Andes Lidar Observatory. 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>
Meteor-ablated Aluminum in the Mesosphere-Lower Thermosphere
<p>Meteor-ablated Aluminum in the Mesosphere-Lower Thermosphere</p> <p>by John Plane, Shane Daly, Wuhu Feng, Michael Gerding and Juan Carlos Gómez Martín.</p> <p>The repository contains the data used in the above paper.</p>
Venus Mesosphere Constituents Brightness Temperatures Dataset
<p>This is a dataset corresponding to a simulation based study that has be performed using Atmospheric Radiative Transfer Simulator (ARTS) radiative transfer model. The ARTS model gives the facility to simulate the brightness temperature (measurements) at specific satellite altitude and for any given viewing geometry. The brightness temperatures are for water vapour, carbon monoxide, sulphur dioxide, hydrogen chloride.</p>
Data files for A "Boreing" Night of Observations of the Upper Mesosphere and Lower Thermosphere Over the Andes Lidar Observatory
<p>The files in this set are data obtained from the ANI2 airglow imager located at the Andes Lidar Observatory.in Chile (30.23S, 70.73W, 2530 m). The files are named for a JGR paper by J. Hecht et al. entitled A "Boreing" Night of Observations of the Uppe rMesosphere and Lower Thermosphere Over the Andes Lidar Observatory. 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>
Spectral data used in the paper "Intense Zonal Wind in the Martian Mesosphere During the 2018 Planet-Encircling Dust Event Observed by Ground-based IR Heterodyne Spectroscopy"
<p>This data contains the spectral data used in the paper "Intense Zonal Wind in the Martian Mesosphere During the 2018 Planet-Encircling Dust Event Observed by Ground-based IR Heterodyne Spectroscopy". </p> <p>"MILAHI_2018PEDE_Spectral_Data" is the spectral data and you can find the detailed information of the data in "README".</p> <p> </p> <p> </p>
Simulation data of 'Effects of Nonmigrating Diurnal Tides on the Na Layer in the Mesosphere and Lower Thermosphere'
<p>The simulation data of the manuscript 'Effects of Nonmigrating Diurnal Tides on the Na Layer in the Mesosphere and Lower Thermosphere'.</p>
Meteor-ablated Aluminum in the Mesosphere-Lower Thermosphere
<p>Meteor-ablated Aluminum in the Mesosphere-Lower Thermosphere</p> <p>by John Plane, Shane Daly, Wuhu Feng, Michael Gerding and Juan Carlos Gómez Martín.</p> <p>The repository contains the data used in the above paper.</p>
Transport between stratosphere and mesosphere datasets
<p>Time series of transport (both downwelling and upwelling) and its decomposition into individual terms for the 1960-2098 period. Density term is further decomposed here as p (pressure) a T (tempererature) term. </p>
UARS Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AL V010 (UARIS3AL) at GES DISC
The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AL data product consists of daily, 4 degree increment latitude-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients. The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns. ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AL data were processed with the version 10 algorithm, except H2O which is version 9. The ISAMS level 3AL product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day. Data are on the UARS standard pressure levels (in mbars) given by: P(i) = 1000 * 10**(-i/6) for i = 0, 1, 2, ... Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3LP. The parameter file, contains the additional ancillary and quality information not found in the 3AL file. The data files are available in a binary record oriented format.
UARS Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AT V010 (UARIS3AT) at GES DISC
The Improved Stratospheric and Mesospheric Sounder (ISAMS) Level 3AT data product consists of daily, 65.536 second interval time-ordered vertical profiles of temperature and concentrations of O3, H2O, CH4, CO, N2O, N2O5, NO2, and aerosol absorption coefficients. The insrument measured infrared molecular emmissions in the spectral region from 4.6 to 16.6 microns. ISAMS was flown on NASA's Upper Atmosphere Research Satellite (UARS) and designed to measure the global temperature and composition profiles in the stratosphere and mesosphere. Limb measurements were made in the altitude range between 15 and 60 km at about 2.5 km resolution. Data were collected between latitude 34S and 80N and 80S and 34N, alternating each satellite yaw cycle of about 36 days. The ISAMS Level 3AT data were processed with the version 10 algorithm, except H2O which is version 9. The ISAMS level 3AT product consists of 10 granules per day. A data granule is one ISAMS species or subtype per day. Data are on the UARS standard pressure levels (in mbars) given by: P(i) = 1000 * 10**(-i/6) for i = 0, 1, 2, ... Each of the 10 ISAMS granules is accompanied by its own additional parameter file, designated as level 3TP. The parameter file, contains the additional ancillary and quality information not found in the 3AT file. The data files are available in a binary record oriented format.
Dataset for generating figures 3 and 4 in paper titled "Spectroscopy of a mesospheric ghost", and figure 1 in supplementary information of the same paper.
<p>Dataset for figures 3 and 4 in Passas-Varo et al. (2023): "Spectroscopy of a mesospheric ghost" and figure 1 in the related "Supplementary Information".</p> <p>AllSpectra_20190921_214514.csv contains the dataset of the sequence of spectra for the reported event. </p> <p>Flux_Ratio_20190921_214514.csv contains the dataset of the line flux to generate figure 4 in the main paper and figure 1 in the supplementary information. </p> <p>More information on the data of this study is given in the main paper.</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
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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