Resources (1-5 of 5)

1. Benchmarking probabilistic machine learning models for arctic sea ice forecasting

   23 Jul 2024 | Contributor(s):: Sahara Ali, Seraj Mostafa, Xingyan Li, Sara Khanjani, Jianwu Wang, James Foulds, Vandana Janeja

   The Arctic is a region with unique climate features, motivating new AI methodologies to study it. Unfortunately, Arctic sea ice has seen a continuous decline since 1979. This not only poses a significant threat to Arctic wildlife and surrounding coastal communities but is also adversely affecting...

2. Validation data for manuscript "Novel statistical emulator construction for volcanic ash transport model Ash3d with physically-motivated measures"

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   02 Sep 2020 | Contributor(s):: Qingyuan Yang, E Bruce Pitman, Elaine Spiller, Marcus I Bursik, Andrea Bevilacqua

   This database presents the testing and validation data used and presented in the manuscript titled "Novel statistical emulator construction for volcanic ash transport model Ash3d with physically-motivated measures". The manuscript is submitted to the Proceedings of the Royal...

3. Tephra inversion with Tephra2 and the Metropolis-Hastings algorithm

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   21 Jun 2020 | Contributor(s):: Qingyuan Yang, E Bruce Pitman, Marcus I Bursik, Susanna Jenkins

   We couple the Metropolis-Hastings algorithm (Hastings, 1970) with the volcanic ash transport model Tephra2 (Bonadonna et al, 2005; 2010), and present the coupled algorithm as a new method to estimate the Eruption Source Parameters (ESPs) of volcanic eruptions based on mass per unit area...

4. Supplementary material for Newhall and Pallister (2014) Using multiple data sets to populate probabilistic volcanic event trees

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   24 Nov 2014 | Contributor(s):: Chris Newhall, John S Pallister

   For probabilistic forecasting in volcanology, two widely used methods are the Cooke method (Aspinall and others) and BET-EF (Marzocchi and others).   The paper noted in the title, in Papale P (ed), Volcanic Hazards, Risks and Disasters. Academic Press, describes...

5. Cost/benefit Analysis: Guidelines for quantitative protocols for volcanic risk reduction

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   24 Aug 2015 | Contributor(s):: dmitri rouwet

   The goal of this deliverable is to provide guidelines that may allow scientists and decision makers tobridge the gap between volcanological knowledge and a rational decision making. Part of thecontent of this document has been published on the paper W. Marzocchi, C.G. Newhall, G. Woo(2012). The...