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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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1st IAVCEI/GVM Workshop: "From Volcanic Hazard to Risk Assessment", Geneva, 27-29 June 2018
18 Dec 2018 | Contributor(s): Costanza Bonadonna, Sebastien Biass, Eliza S Calder, Corine Frischknecht, Chris Eric Gregg, Susanna Jenkins, Sue C Loughlin, Scira Menoni, Shinji Takarada, Tom Wilson
The complexity of volcanic risk analysis typically resides in the interaction of multiple hazard, vulnerability and exposure aspects dynamically acting over various spatial and temporal scales. Risk analyses provide an evidence-based approach to development and implementation of proactive...
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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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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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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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ECMapProb
18 Jul 2019 | *Tools | Contributor(s): Alvaro Aravena, Raffaello Cioni
Probability map of PDC by using a modifed approach of the energy cone model and topographic information derived from the SRTM 30 m elevation model.
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eject model
01 Feb 2011 | Offline Tools | Contributor(s): Larry Garver Mastin
Eject is a user-friendly model that calculates the trajectories of blocks that are ballistically ejected from volcanic craters. It has also been used to calculate ballistic trajectories of other objects in other other settings, including missiles and bullets.Details are at:The attached zip...
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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