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(Poster) Ghub: A new community-driven data-model resource for ice-sheet scientists
19 Apr 2023 | Contributor(s): Sophie Goliber, jason briner, sophie nowicki
PDF of the poster for "Ghub: A new community-driven data-model resource for ice-sheet scientists".
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2018 NSF Large Scale Experiment Workshop on Volcanic Blasts
01 Sep 2021 | Contributor(s): Ingo Sonder, Alison Graettinger, Tracianne B. Neilsen, Robin Matoza, Jacopo Taddeucci, Julie Oppenheimer, Einat Lev, Kae Tsunematsu, Gregory Waite, Greg A Valentine
We moved the whole dataset to zenodo, all of its parts. the dataset is available under the doi 10.5281/zenodo.5842607.
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A Survey on Causal Discovery Methods for IID and Time Series Data
16 Jul 2024 | Contributor(s): Uzma Hasan, Emam Hossain, Md Osman Gani
Abstract: The ability to understand causality from data is one of the major milestones of human-level intelligence. Causal Discovery (CD) algorithms can identify the cause-effect relationships among the variables of a system from related observational data with certain assumptions. Over the...
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AGU Poster: Results of the Tephra 2014 Workshop on Maximizing the Potential of Tephra for Multidisciplinary Science
11 Dec 2014 | Contributor(s): Stephen C Kuehn, Solene Pouget, Kristi L Wallace, Marcus I Bursik
Poster presentation from the 2014 AGU Fall Meeting reporting on results and conclusions of the Tephra 2014 workshop
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An Open Source Tool for Visualizing ISM Intercomparisons
14 Dec 2021 | Contributor(s): Alex Becerra, sophie nowicki, Erika Simon
This tool produces visualizations from Seroussi et al. (2020).
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Announcement: Coupling Uncertain Geophysical Hazards Workshop
30 Nov 2018 | Contributor(s): Marcus I Bursik
Coupling Uncertain Geophysical Hazards WorkshopMarch 24-26, 2019James B. Hunt Library, North Carolina State University, Raleigh, NCDescription: Scientists are beginning to understand the propagation of uncertainty through mathematical models, to enable predictions of the likely...
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Approximation by Localized Penalized Splines (ALPS)
22 Sep 2021 | *Tools | Contributor(s): Prashant Shekhar, Abani Patra
Approximation by Localized Penalized Splines (ALPS)
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ATM-Based Crevasse Detection & Extraction workflow
29 Jul 2020 | *Tools | Contributor(s): Renette Jones-Ivey, Jeanette Sperhac, Kristin Poinar
ABCDE Tool
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bent: A model of plumes in crossflow
11 Nov 2010 | Presentations | Contributor(s): Marcus I Bursik
Bent is an integral trajectory model for calculation of plume parameters in the presence of a crossflow (wind). It has been validated against data for eruptions from Kliuchevskoi and Avachinskiy volcanoes, Russia.
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CESM ISMIP6 Forcing Data
20 Oct 2021 | *Data Sets/Collections | Contributor(s): Kate Thayer-Calder, Gunter Leguy, William Lipscomb
The Community Earth System Model (CESM) version 2.1 is a world-class coupled climate system model that includes components for the atmosphere, ocean, terrestrial system, river run-off, and fully active glaciers (Danabasoglu et al. 2020). This version of CESM was used in many experiments as part...
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CmCt GRACE MASCON Tool
16 Nov 2020 | *Tools | Contributor(s): Erika Simon, sophie nowicki
The Cryosphere model Comparison tool (CmCt) GRACE Mascon Module compares user uploaded ice sheet models to the GRACE Mascon product derived by NASA GSFC.
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CmCt Histogram Tool
21 May 2019 | *Tools | Contributor(s): Erika Simon, sophie nowicki
This Jupyter notebook based tool can be used to plot the comparison results from the Cryosphere model Comparison tool (CmCt).
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Code Demos for "Regression on Ice" Lecture Notes
10 Oct 2023 | *Tools | Contributor(s): Noah J Bergam
Notebooks with visualizations of some basic regression / machine learning concepts for glaciology
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Confort 15 (Conflow improvement)
22 Apr 2016 | Offline Tools | Contributor(s): Silvia Campagnola, Claudia Romano, Larry G Mastin, Alessandro Vona
We present an updated version of the Conflow model, an open-source numerical model for flow in eruptive conduits during steady-state pyroclastic eruptions (Mastin and Ghiorso, 2000). In the Confort 15 program, several updates were considered:The rheological parameters of the model are...
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Development and Initial Testing of XR-Based Fence Diagrams for Polar Science
23 Apr 2024 | Publications | 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,...
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Documentation for "Effect of particle entrainment on the runout of pyroclastic density currents"
08 Sep 2016 | *Data Sets/Collections | 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:...
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dWind
27 Jul 2010 | Offline Tools | 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...
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Evaluating Machine Learning and Statistical Models for Greenland Bed Topography
15 May 2024 | Publications | 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...
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Evaluating Machine Learning and Statistical Models for Greenland Subglacial Bed Topography
15 May 2024 | Publications | 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...
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Eyjafjallajokull WMO meeting, Geneva, Bursik presentation
19 Oct 2010 | Presentations | 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