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1,880 results for “mars”
SuperDARN Grid data in netCDF format (2018-Mar)
<p>2018-Mar SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here: https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>
SuperDARN Grid data in netCDF format (2020-Mar)
<p>2020-Mar SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here: https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>
SAMI3 data in netCDF format (2019-Mar)
<p>This SAMI3 monthly record contains references to the daily records for March 2019.</p>
Mars thermal+non-thermal H Modeling
<p>This folder contains the RT model output for thermal H modeling and non-thermal H modeling. These values have been used to determine the line of sight modeled intensity for HST observations corresponding to campaign GO-15097. </p>
Stand de présentation de la SVE à Morges, 18 mars 2018. L'observation d'insectes sous la loupe et la dégustation d'insectes remportent un succès certain. (Photos Anne Freitag) in Société Vaudoise D'Entomologie (Sve)
Stand de présentation de la SVE à Morges, 18 mars 2018. L'observation d'insectes sous la loupe et la dégustation d'insectes remportent un succès certain. (Photos Anne Freitag)
A Spectroscopic Study of Mars-Analog Materials with Amorphous Sulfate and Chloride Phases: Implications for Detecting Amorphous Materials on the Martian Surface
<p>This repository contains the raw and baseline or continuum corrected data associated with the manuscript entitled:</p> <p> A Spectroscopic Study of Mars-Analog Materials with Amorphous Sulfate and Chloride Phases: Implications for Detecting Amorphous Materials on the Martian Surface</p> <p>This work is being submitted to The Planetary Science Journal</p> <p>ABSTRACT</p> <p>The Chemistry and Mineralogy X-ray diffraction (XRD) instrument aboard the Curiosity rover has consistently identified substantial amorphous material at Gale Crater. The amorphous component is compositionally variable, but often includes elevated sulfur and iron, suggesting that amorphous ferric sulfate (AFS) may be present. Understanding the spectral changes of common Martian materials exposed to ferric sulfate brines as they desiccate to AFS is a key step in bridging the gap between simple mixing studies and analyses of complex/realistic reaction assemblages. Visible and near-infrared reflectance (VNIR), mid-infrared attenuated total reflectance (MIR, FTIR-ATR), and Raman spectra, along with XRD data are presented for basaltic glass, hematite, gypsum, nontronite, and magnesite, each at three grain sizes (<25, 25-63, and 63-180 μm), mixed with ferric sulfate alone or also with NaCl, hydrated through deliquescence, and then rapidly desiccated in 11% relative humidity or via vacuum. All desiccated products are partially or completely XRD amorphous; crystalline phases include starting materials and trace precipitates, leaving the bulk of the ferric sulfate in the amorphous fraction. Due to considerable spectral masking, the detectability of AFS is highly dependent on spectroscopic technique and the observed mineral assemblage. This has strong implications for remote and in-situ observations of Martian samples which include an amorphous component. AFS is only identifiable in VNIR spectra for magnesite, nontronite, and gypsum samples; hematite and basaltic glass samples appear similar to pure materials. Sulfate features dominate Raman spectra for nontronite and basaltic glass samples; the analog material dominates Raman spectra of hematite and gypsum samples. MIR spectra reveal all end members most clearly except for basaltic glass samples, where the analog material is almost completely masked. NaCl leads to similar FTIR-ATR and Raman features, regardless of analog material.</p> <p>Associated photographs of samples in this project can be found at:</p> <p>https://www.lionsandlamms.com/</p> <p>This research was supported by NSF award #1819209.</p>
Mars Thermal + Non-Thermal Modeling Data from figures
<p>This folder contains all the values from all the figures present in the paper titled "Evidence of Non-thermal Hydrogen in the Exosphere of Mars Resulting in Enhanced Water Loss", by Bhattacharyya et al.</p>
Nicaragua: Jinotega, Santa Enriqueta, alt., 1250, m, Lat. 13.071944, Long. 85.92111, 29Mar03, col. JeanMichel Maes (MEL 446074 / 446075, 2 Hembras). in Cicadidae (Homoptera) de Nicaragua: Catalogo ilustrado, incluyendo especies exóticas del Museo Entomológico de Leon
Nicaragua: Jinotega, Santa Enriqueta, alt., 1250, m, Lat. 13.071944, Long. 85.92111, 29Mar03, col. JeanMichel Maes (MEL 446074 / 446075, 2 Hembras).
Nicaragua: Managua: Mateare, Lat. 12.236112, Long. 86.42972, 20/27Mar95, col. C. Grimm, (MEL 446014 + 446016 + 446018, 3 Hembras). in Cicadidae (Homoptera) de Nicaragua: Catalogo ilustrado, incluyendo especies exóticas del Museo Entomológico de Leon
Nicaragua: Managua: Mateare, Lat. 12.236112, Long. 86.42972, 20/27Mar95, col. C. Grimm, (MEL 446014 + 446016 + 446018, 3 Hembras).
SuperDARN Grid data in netCDF format (2017-Mar)
<p>2017-Mar SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here: https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>
SuperDARN Grid data in netCDF format (2016-Mar)
<p>2016-Mar SuperDARN radar data in netCDF format. These files were produced using versions 3.0 of the public FitACF and make_grid algorithms, using the AACGM v2 coordinate system. Cite this dataset if using our data in a publication.</p><p>The RST is available here: https://github.com/SuperDARN/rst</p><p>The research enabled by SuperDARN is due to the efforts of teams of scientists and engineers working in many countries to build and operate radars, process data and provide access, develop and improve data products, and assist users in interpretation. Users of SuperDARN data and data products are asked to acknowledge this support in presentations and publications. A brief statement on how to acknowledge use of SuperDARN data is provided below.</p><p>Users are also asked to consult with a SuperDARN PI prior to submission of work intended for publication. A listing of radars and PIs with contact information can be found here: (<a href="http://vt.superdarn.org/tiki-index.php?page=Radar+Overview">SuperDARN Radar Overview</a>)</p><p><strong>Recommended form of acknowledgement for the use of SuperDARN data:</strong></p><p>'The authors acknowledge the use of SuperDARN data. SuperDARN is a collection of radars funded by national scientific funding agencies of Australia, Canada, China, France, Italy, Japan, Norway, South Africa, United Kingdom and the United States of America.'</p>
Ceraunius Fossae and Tractus Fossae, Mars, Fault Catalogue
<p>Catalogue of all faults in Ceraunius Fossae and Tractus Fossae, Mars, in shapefile format. Faults are mapped on Context Camera (CTX) images, within the Tanaka et al. (2014) unit boundary outlines.</p>
Data from: Brine driven destruction of clay minerals in Gale crater, Mars
Open the record for dataset details and reuse information.
Mars Reconnaissance Orbiter (MRO) Mars Color Imager (MARCI) north seasonal cap original movies Mars years 28 to 35
Open the record for dataset details and reuse information.
Salt and Water Migration in Mars Duricrust Desiccation Experiments
<p>Dataset to supplement the manuscript. Includes raw data spetral files in .txt format and a spreadsheet containing measured salt concentrations.</p>
Dataset for Patent Landscape, update M36 (Mar 2020)
<p>Collection of .csv files with raw patent data, analysed to obtain landscaping information on technologies overlapping with the project. Used to produce the deliverable “Patent and scientific literature study M36” D7.7. The data where obtained on <a href="http://www.thelens.org">www.thelens.org</a></p>
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 "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>
Thermophysical properties and surface heterogeneity of landing sites on Mars from overlapping THEMIS observations-Data
<p>Files, scripts/functions, observed temperature data, and modeled results used in the Ahern et al. paper entitled: Thermophysical properties and surface heterogeneity of landing sites on Mars from overlapping THEMIS observations.</p>
The data generated or compiled in the study of "Diverse polygonal patterned grounds in the northern Eridania basin, Mars: Possible origins and implications"
<p>The data that we generated or compiled, that is used to make a figure (e.g. geologic maps (Figure 2), mapped ridges (included in Figure 2), tables of measurements underlying the histograms (Figures 10 and 18), crater counts (Figure 12)), are placed in a public data repository outside of the JGR paywall. They have been introduced in the following publication, where more details can be found:</p> <p> </p> <p>Y. Dang, F. Zhang, J. Zhao, J. Wang, Y. Xu, T. Huang, and L. Xiao</p> <p>Diverse Polygonal Patterned Grounds in the Northern Eridania Basin, Mars: Possible Origins and Implications.</p> <p>Journal of Geophysical Research: Planets, 2020,125, e2020JE006647. https://<br> doi.org/10.1029/2020JE006647</p> <p> </p> <p>The file format is "Shp" processed in the software ArcGIS 10.6. The detailed description and information can be found in the title of each file below, and also their corresponding figure caption in the paper after it is formally published.</p>
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OpenNeuro
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