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  1. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science

    23 Apr 2024 | Contributor(s): Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, Don Engel

    Naomi Tack, Nicholas Holschuh, Sharad Sharma, Rebecca Williams, and Don Engel. 2023. Development and Initial Testing of XR-Based Fence Diagrams for Polar Science. In IGARSS 2023 – 2023 IEEE International Geoscience and Remote Sensing Symposium, July 16, 2023, Pasadena, CA, USA. IEEE,...

  2. Direct sampling of volcanic clouds

    08 Feb 2011 | Contributor(s): William I Rose

    Volcanic clouds have only sporadically been directly sampled. Sampling is advantageous to validate remote sensing. Direct sampling was more common in the 1978-1984 period before the hazards to jet aircraft were understood and when piston aircraft sampling was more prevalent. This sampling...

  3. Documentation for "Effect of particle entrainment on the runout of pyroclastic density currents"

    08 Sep 2016 | Contributor(s): Kristen Fauria, Michael Manga, Michael Chamberlain

    This is a repository for the data and script used in, "Effect of particle entrainment on the runout of pyroclastic density currents."Here you will find:1. A compilation of splash function experimental data from this study and data that was extracted from seven other studies:...

  4. Dome rock densification parameters

    20 Oct 2014 | Contributor(s): Fabian Ben Wadsworth, Betty Scheu

  5. dWind

    27 Jul 2010 | Contributor(s): Seb Biass, Costanza Bonadonna

    UPDATE: A new version of dWind is now available as part of the TephraProb package here: https://vhub.org/resources/4094It allows to download wind data from both the NOAA NCEP Reanalysis 1 and the ECMWF Era-Interim datasets and provides a variety of functions to plot and analyse wind...

  6. Eruption data for ash-cloud model validation

    04 Apr 2013 | Contributor(s): Larry Garver Mastin, Costanza Bonadonna, Arnau Folch, peter webley, barbara stunder, Michael Pavolonis

    This is a collection of data, references, and links to data on well-documented eruptions whose observations can be used to validate ash-cloud transport models. Data include, among other things, plume height, duration, erupted volume, satellite observations, numerical wind fields, and grain-size...

  7. Evaluating Machine Learning and Statistical Models for Greenland Bed Topography

    15 May 2024 | Contributor(s): Homayra Alam, Katherine Yi, Angelina Dewar, Tartela Tabassum, Jason Lu, Ray Chen, Jianwu Wang, Sikan Li, Mathieu Morlighem, Omar Faruque

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bed topography in Greenland using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for understanding ice sheet...

  8. Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography

    15 May 2024 | Contributor(s): Homayra Alam, Jianwu Wang, Tartela Tabassum, Katherine Yi, Angelina Dewar, Jason Lu, Ray Chen, Omar Faruque, Mathieu Morlighem, Sikan LI

    Abstract:The purpose of this research is to study how different machine learning and statistical models can be used to predict bedrock topography under the Greenland ice sheet using ice-penetrating radar and satellite imagery data. Accurate bed topography representations are crucial for...

  9. Eyjafjallajokull WMO meeting, Geneva, Bursik presentation

    19 Oct 2010 | Contributor(s): Marcus I Bursik

    Presentation given at WMO, Geneva, Switzerland by M. Bursik, attempting to summarize work of this group to date (18 Oct 2010).LaTeXNSF-RAPID grant EAR-1041775, Icelandic Meteorological Office

  10. Eyjafjallajökull, volcanic clouds and aviation - one year on

    05 Aug 2011 | Contributor(s): Simon Carn

    A workshop at the 2011 IUGG General Assembly in Melbourne, Australia, lead by Andrew Tupper (Australian Bureau of Meteorology), Fred Prata (Norwegian Institute for Air Research), and Arnau Folch (Barcelona Supercomputing Center).The Eyjafjallajokull eruption, resulting in ground and air...

  11. GIS layer of Greenland Ice Sheet bed available for sub-ice drilling

    15 Sep 2022 | Contributor(s): jason briner

    This dataset includes several geographical-information-system (GIS, ArcGIS) shapefiles relating to this study:Briner, J.P., Walcott, C.K., Schaefer, J.M., Young, N.E., MacGregor, J.A., Poinar, K., Keisling, B.A., Anandakrishnan, S., Albert, M.R., Kuhl, T., Boeckmann, G. (submitted). Where to...

  12. GIS layers of North America ice sheet history

    03 Oct 2022 | Contributor(s): jason briner

    Included are ArcGIS shapefiles of North American ice sheet extent in 36 time slices spanning from 18,000 to 1,000 years ago.

  13. Greenland ice sheet data explorer

    15 Dec 2018 | Contributor(s): Prashant Shekhar, Renette Jones-Ivey

    Greenland icesheet time series data explorer

  14. Greenland Ice Sheet Model Jupyter Notebook

    12 Dec 2018 | Contributor(s): Erika Simon

    Example for Plotting a Greenland Ice Sheet Model

  15. Greenland Ice Surface Temperature, Surface Albedo, and Water Vapor from MODIS Comparison Tool

    26 Jan 2021 | *Tools | Contributor(s): Denis Felikson, Erika Simon, Dorothy K. Hall, Nicolo DiGirolamo, Elliot Snitzer

    Compare observations of Greenland Ice Surface Temperature, Surface Albedo, and Water Vapor from MODIS against MERRA-2 reanalysis model output.

  16. Greenland Surface Strain Rates & Stresses

    15 Sep 2021 | *Data Sets/Collections | Contributor(s): Kristin Poinar

    These datasets are 2D principal strain rates and principal stresses across the surface of the Greenland Ice Sheet.We started with representative surface velocities over a 20-year period (Joughin et al., 2016). We smoothed the velocities with a 1 km × 1 km boxcar filter, which carries...

  17. GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation

    16 Oct 2023 | *Tools | Contributor(s): Emma MacKie

    GStatSim is a Python package specifically designed for geostatistical interpolation and simulation. These tools are part of our ongoing effort to develop and adapt open-access geostatistical functions.

  18. Hazards of volcanic ash

    29 Nov 2011 | Presentations | Contributor(s): William I Rose

    Claire Horwell

  19. Ice Sheet Simulation Compliance Checker

    19 Jan 2024 | *Tools | Contributor(s): Renette Jones-Ivey, sophie nowicki, Sophie Goliber

    Checks the compliance of a simulation dataset according criteria for ISMIP6

  20. IceBridge ATM L2 Icessn Elevation, Slope, and Roughness

    23 Sep 2021 | *Data Sets/Collections | Contributor(s): Ash Narkevic, Ivan Parmuzin, Beata Maria Csatho, Greg Babonis

    This data set contains  IceBridge ATM L2 Icessn Elevation, Slope, and Roughness data  (Studinger, M. 2014, updated 2020) organized into individual flight lines, both in ascii and ArcGIS shape file formats.  The data were collected as part of NASA's Operation...