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496 results for “Volcanism”
Compositional Characterization of Glassy Volcanic Material From VNIR and MIR Spectra Using Partial Least Squares Regression Models
<p>This is supporting data for the paper titled "Compositional Characterization of Glassy Volcanic Material From VNIR and MIR Spectra Using Partial Least Squares Regression Models" by Leight et al. (submitted to JGR-P 11/23). Table S1 lists each spectrum used to train PLS models, its source, and which training datasets the spectrum was included in. Zip files contain the MIR and VNIR PLS model files. Model files are .asc, and can be run using the code at Ytsma, (2022), https://doi.org/10.5281/zenodo.7347345. </p>
Dataset: Very-small-aperture 3-D infrasonic array for volcanic jet observation at Stromboli Volcano, Geophysical Journal International, Volume 229, Issue 1, Pages 459–471, https://doi.org/10.1093/gji/ggab487
<p>This is the dataset of the infrasound observation of Yamakawa et al. (GJI, 2022).</p>
Understanding Zinc isotopic signatures in volcanic lakes
<p>Dataset for the publication entitled "Understanding Zinc isotopic signatures in volcanic lakes" published in GCA.</p>
Pollen data: Influences of sea level changes and volcanic eruptions on Holocene vegetation in Tonga
<p><strong>Aim</strong>:</p> <p>To investigate mid- to late-Holocene vegetation changes on low-lying coastal areas in Tonga and how changing sea level and recurrent volcanic eruptions have influenced vegetation dynamics on four islands of the Tongan Archipelago (South Pacific).</p> <p><strong>Methods: </strong></p> <p>To investigate past vegetation and environmental change at Ngofe Marsh ('Uta Vava'u) we examined palynomorphs (pollen and spores), charcoal (fire), and sediment characteristics (volcanic activity) from a 6.7-m long sediment core. Radiocarbon dating indicated the sediments were deposited over the last 7700 years. We integrated the Ngofe Marsh data with similar previously published data from Avai'o'vuna Swamp on Pangaimotu Island, Lotofoa Swamp on Foa Island, and Finemui Swamp on Ha'afeva Island. Plant taxa were categorised as littoral, mangrove, rainforest, successional/ disturbance, and wetland groups and linear models were used to examine relationships between vegetation, relative sea-level change, and volcanic eruptions (tephra).</p> <p><strong>Results</strong>:</p> <p>Relative sea-level change has impacted vegetation on three of the four islands investigated. Volcanic eruptions were not identified as a driver of vegetation change. Rainforest decline does not appear to be driven by sea-level changes or volcanic eruptions. From all sites analysed, vegetation at Finemui Swamp was most sensitive to changes in relative sea level.</p> <p><strong>Conclusions: </strong></p> <p>While vegetation on low-lying Pacific islands is sensitive to changing sea levels, island characteristics, such as size and elevation, are also likely to be important factors that mediate specific island responses to drivers of change.</p>
GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 4
<p>Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model. </p>
GEOSCCM Simulations for Thresholds for Volcanic Climate Warming 3
<p>Selected output in NetCDF format from simulations performed with the GEOSCCM global climate model. </p>
Data from: Past volcanic activity predisposes an endemic threatened seabird to negative anthropogenic impacts
<p>Humans are regularly cited as the main driver of current biodiversity extinction, but the impact of historic volcanic activity is often overlooked. Pre-human evidence of wildlife abundance and diversity are essential for disentangling anthropogenic impacts from natural events. Réunion Island, with its intense and well-documented volcanic activity, endemic biodiversity, long history of isolation and recent human colonization, provides an opportunity to disentangle these processes. We track past demographic changes of a critically endangered seabird, the Mascarene petrel <em>Pseudobulweria aterrima</em>, using genome-wide SNPs. Coalescent modeling suggested that a large ancestral population underwent a substantial population decline in two distinct phases, ca. 125,000 and 37,000 years ago, coinciding with periods of major eruptions of Piton des Neiges. Subsequently, the ancestral population was fragmented into the two known colonies, ca. 1,500 years ago, following eruptions of Piton de la Fournaise. In the last century, both colonies declined significantly due to anthropogenic activities, and although the species was initially considered extinct, it was rediscovered in the 1970s. Our findings suggest that the current conservation status of wildlife on volcanic islands should be firstly assessed as a legacy of historic volcanic activity, and thereafter by the increasing anthropogenic impacts, which may ultimately drive species towards extinction.</p>
Propagational Isotropy of Large Scale Traveling Ionospheric Disturbances Over Australia And New Zealand due to the 2022 Tonga Volcanic Eruption
<p>This data repository contains global TEC processed data from 14 - 16 January 2022. The original data were obtained from the GNSS-TEC database available at https://stdb2.isee.nagoya-u.ac.jp/GPS/GPS-TEC/ provided by the Institute for Space-Earth Environment Research, Nagoya University. The data is in .mat format (binary Matlab file) with the following data matrices:</p> <ol> <li>Coordinates (geographic coordinates - Latitude, Longitude)</li> <li>dTEC1 (detrended TEC)</li> <li>TimeTEC_combined (time series absolute TEC for each geographic coordinate)</li> </ol> <p>Data has a time resolution of 5 min in each column. </p>
Large ensemble simulations of Holocene temperature and volcanic forcing
<p>Simulations of the global monthly mean volcanic Stratospheric Aerosol Optical Depth (gmSAOD) for 6755 BCE - 1900 CE performed with EVA_H (code available from <span><a href="https://github.com/thomasaubry/EVA_H">https://github.com/thomasaubry/EVA_H</a></span>) and associated Effective Radiative Forcing (ERF).</p> <p>Simulations of the Holocene global annual mean temperature for 6755 BCE - 1900 CE performed with FaIR (code available from <span><a href="https://github.com/OMS-NetZero/FAIR/tree/v2.1.4">https://github.com/OMS-NetZero/FAIR/tree/v2.1.4</a></span>) using volcanic, greenhouse gases (CO2, CH4, N2O), solar, orbital, ice sheets, and anthropogenic land use forcings.</p>
Sentinel-5p/TROPOMI SO2 Layer Height dataset covering the Raikoke volcanic eruption 2019
<p>Sentinel-5p/TROPOMI SO2 Layer Height product generated by DLR as part of the INPULS project using the retrieval algorithm developed in the framework of the ESA Sentinel-5p Innovations: SO2 LH (S5P+I: SO2LH) project</p> <p>The dataset contains SO2LH results for the timeframe 2019-06-22 until 2019-07-30 covering the eruptive period of the Raikoke volcanic eruption. This dataset was used as input for the paper of Inness et al. "The CAMS volcanic forecasting system utilizing near-real time data assimilation of S5P/TROPOMI SO2 retrievals" (2021, submitted to GMD)</p> <p>The dataset contains modified Copernicus Sentinel data processed by DLR</p>
PyVOLCANS: A Python package to flexibly explore similarities and differences between volcanic systems
<p>Python tool to identify analogue volcanoes via <a href="https://doi.org/10.1007/s00445-019-1336-3">VOLCANS</a>.</p> <p>The main goal of PyVOLCANS is to help alleviate data-scarcity issues in volcanology, and contribute to developments in a range of topics, including (but not limited to): quantitative volcanic hazard assessment at local to global scales, investigation of magmatic and volcanic processes, and even teaching and scientific outreach. We hope that future users of PyVOLCANS will include any volcano scientist or enthusiast with an interest in exploring the similarities and differences between volcanic systems worldwide. Please visit our <a href="https://github.com/BritishGeologicalSurvey/pyvolcans/wiki">wiki pages</a> for more information.</p>
Data for the paper: "Nonlinear responses of droughts over China to volcanic eruptions at different drought phases"
<p>These files are data used in the paper "Nonlinear responses of droughts over China to volcanic eruptions at different drought phases", which is published on the Geophysical Research Letters (GRL). The uploaded data are simulations from volcanic sensitivity experiments, with volcanic eruptions added in the "late-" and "early-" phases of each of the 15 drought events, respectively. The sensitivity experiments are performed using the Community Earth System Model (CESM) version 1.0.3.</p> <p>The compressed file "data.zip" is comprised of 4 sub-files containing variables of precipitation (prect), 500hPa vertical speed (Omega), East Asia Summer Monsoon index (EASM index), and soil moisture, respectively.</p> <p>In each sub-file, there are 6 txt datasets. Among the 6 ".txt" files, three of them are precipitation(EASM/Omega/Soil Moisture) anomalies centered with volcanic eruptions taking place in the late-phase of the 15 drought events (late-) in the CTRLs (with suffix "ctrl.txt"), volcanic sensitivity experiments with respect to the climatology (with suffix "vol.txt"), and volcanic sensitivity experiments with respect to the CTRLs (with suffix "vol-ctrl.txt"). Another three ".txt" files are simulations with volcanic eruptions taking place in the early-phase of the 15 drought events (early-). Each ".txt" file contains 15 time series, and each time series is 21 years' long, with 10 years before and 10 years after the volcanic eruption.</p>
Gravity data collected during volcanic unrest period of the Svartsengi geothermal field in Iceland
<p>The file contains free-air corrected data collected during the one-year unrest at the Svartsengi geothermal field in Iceland as a precursor the Fagradalsfjall eruption in 2021.</p> <p>Column 1: Name of the measurement site</p> <p>Column 2 and 3: Geographical coordinates of measurement sites</p> <p>Column 4-6. Change in elevation, free-air correction and free air gravity change from January 28-29th to April 22-28th 2020</p> <p>Column 7-9. Change in elevation, free-air correction and free air gravity change from April 22-28th to October 5-6th 2020</p> <p>Column 10-12. Change in elevation, free-air correction and free air gravity change from October 5-6th 2020 to February 17-18th 2021</p>
Large Scale Volcanism and the heat-death of terrestrial worlds
<p>The files herein are used to generate the main and SI figures in the GRL paper:</p> <p>Title: Large Scale Volcanism and the heat-death of terrestrial worlds<br> Authors: M.J. Way, Richard E. Ernst, Jeffrey D. Scargle</p> <p>The data are derived from an Excel formatted table: WAY2021-TableS1.xlsx</p>
Gravity data used in the paper "Imaging the volcanic structures beneath Gran Canaria Island using new gravity data"
<p>This file includes the values of gravity and complete Bouguer gravity anomaly calculated for the land gravity stations in Gran Canaria Island (Canary Islands, Spain). Each station has the corresponding UTM coordinates (Zone 28N) in metres (Datum WGS84). </p> <p>This gravity data set has been used in the paper:</p> <p>Montesinos, F. G., Arnoso, J., Gómez-Ortiz, D., Benavent, M., Blanco-Montenegro, I., Vélez, E., et al. (2022). Imaging the volcanic structures beneath Gran Canaria Island using new gravity data. <em>Journal of Geophysical Research: Solid Earth</em>, 127, e2022JB024863. <a href="https://doi.org/10.1029/2022JB024863">https://doi.org/10.1029/2022JB024863</a></p> <p> </p> <p> </p> <p> </p>
Rock magnetic fingerprint of Mt. Etna volcanic ash: the dataset
<p>This dataset refers to the article: "Rock magnetic fingerprint of Mt. Etna volcanic ash" by the same authors, published in Geophysical Journal International, https://doi.org/10.1093/gji/ggac213.</p> <p>A detailed rock magnetic study was conducted on ash samples collected from different products erupted during explosive activity of Mount Etna, Italy, in order to test the use of magnetic properties as discriminating factors among them, and their explosive character in particular.<br> Samples include tephra emplaced during the last 18 ka: the benmoreitic Plinian eruptions of the Pleistocene Ellittico activity from marine core ET97-70 (Ionian Sea) and the basaltic Holocene FG eruption (122 BC), the Strombolian/Phreatomagmatic/sub-Plinian eruptions (namely, the Holocene TV, FS, FL, ETP products, and the 1990, 1998 eruptions) collected from the slope of the volcano, and the Recent explosive activity (lava fountains referred to as “Ash Rich Jets and Plumes”, or ARJP) that occurred in the 2001-2002 period, related to flank eruptions.<br> A full set of rock magnetic experiments were carried out to determine the magnetic mineralogy and the magnetic grain size at the Institute for Rock Magnetism at the University of Minnesota, including First-Order Reversal Curves (FORCs), hysteresis loops and backfield DC demagnetization remanence curves (DCD or Backfield curves) at room temperature on Princeton Measurements Corporation (Princeton, NJ) Vibrating Sample Magnetometers (VSMs).<br> Low temperature (LT) experiments were conducted on Quantum Design (San Diego, CA) Magnetic Properties Measurement Systems (MPMS-XL and 5S). LT experiments were carried out by measuring the magnetic remanence on warming from 10 K to room temperature (300 K) after cooling in a 2.5 T field (field cooled remanence, FC), as well as after cooling in zero field and applying a saturation isothermal remanent magnetization (SIRM) of 2.5 T at 10 K (zero-field cooled remanence, ZFC). A room temperature (RT) 2.5 T SIRM was also applied at 300 K and the remanence was measured upon temperature cycling to 10 K and back (RTSIRM). AC susceptibility as a function of temperature and frequency (1, 10, 100 Hz or 1, 5, 32, 178, 1000 Hz) was also measured for selected specimens from the three groups of samples.<br> Room temperature susceptibility measurements as a function of field amplitude (10, 20, 40, 80, 120, 200, 400 A/m) were carried out on the Late Pleistocene samples using a Magnon susceptibility system. Saturation magnetization on warming between room temperature and 700°C (Ms-T) was measured on selected specimens using a horizontal Curie balance with Argon gas circulation to limit oxidation processes during heating. Likewise, magnetic susceptibility on warming between room temperature and 700°C (<em>X</em>-T) was measured on a Kappabridge KLY-2 (Brno, Czech Republic) using fields of 300 A/m and 920 Hz. Ms-T and <em>X</em>-T curves are collectively referred to as thermomagnetic curves.</p>
Data for figures of explosive volcanic tsunami generation, propagation and inundation around Lake Taupō
<p>Data for figures in a planned publication of scenario-based study of explosive volcanic tsunami generation, propagation and inundation around Lake Taupō.</p>
A successful short-term volcanic eruption forecasting using seismic features: datasets and Sotware
<p>Successful Short-Term Volcanic Eruption Forecasting Using Seismic Features, Suplementary Material</p> <p>by Rey-Devesa (1,2), Benítez (3), Prudencio, Ligdamis Gutiérrez (1,2), Cortés (1,2), Titos (3), Koulakov (4,5), Zuccarello (6) and Ibáñez (1,2).</p> <p><br> Institutions associated:</p> <p>(1) Department of Theoretical Physics and Cosmos. Science Faculty. Avd. Fuentenueva s/n. University of Granada. 18071. Granada. Spain.</p> <p>(2) Andalusian Institute of Geophysiscs. Campus de Cartuja. University of Granada. C/Profesor Clavera 12. 18071. Granada. Spain.</p> <p>(3) Department of Signal Theory, Telematics and Communication. University of Granada. Informatics and Telecommunication School. 18071. Granada. Spain.</p> <p>(4) Trofimuk Institute of Petroleum Geology and Geophysics SB RAS, Prospekt Koptyuga, 3, 630090 Novosibirsk, Russia</p> <p>(5) Institute of the Earth’s Crust SB RAS, Lermontova 128, Irkutsk, Russia</p> <p>(6) Istituto Nazionale di Geofisica e Vulcanologia, Sezione di Pisa (INGV-Pisa), via Cesare Battisti, 53, 56125, Pisa, Italy.</p> <p><br> Acknowledgment:</p> <p>This study was partially supported by the Spanish FEMALE project (PID2019-106260GB-I00).<br> P. Rey-Devesa was funded by the Ministerio de Ciencia e Innovación del Gobierno de España (MCIN),<br> Agencia Estatal de Investigación (AEI), Fondo Social Europeo (FSE),<br> and Programa Estatal de Promoción del Talento y su Empleabilidad en I+D+I Ayudas para contratos predoctorales para la formación de doctores 2020 (PRE2020-092719).<br> Ivan Koulakov was supported by the Russian Science Foundation (Grant No. 20-17-00075).<br> Luciano Zuccarello was supported by the INGV Pianeta Dinamico 2021 Tema 8 SOME project (grant no. CUP D53J1900017001)<br> funded by the Italian Ministry of University and Research<br> “Fondo finalizzato al rilancio degli investimenti delle amministrazioni centrali dello Stato e allo sviluppo del Paese, legge 145/2018”.<br> English language editing was performed by Tornillo Scientific, UK.</p> <p><br> Data availability statement:</p> <p>1.- Seismic data from Kilauea, Augustine, Bezymianny (2007), and Mount St. Helens are available from the IRIS data repository (http://ds.iris.edu/seismon/index.phtml).<br> (An example of the Python code to access the data is described below.)<br> 2.- Seismic data from Bezymianny (2017-2018) are available from Ivan Koulakov (ivan.science@gmail.com) upon request.<br> 3.- Seismic data from Mt. Etna are available from INGV-Italy upon request (http://terremoti.ingv.it/en/help),<br> also available from the Zenodo data repository (https://doi.org/10.5281/zenodo.6849621).</p> <p> </p> <p>Access code in Python to download the records of Kilauea, Augustine and Mount St. Helens volcanoes, from the IRIS data repository.</p> <p>'''To access the raw signals please first install ObsPy and then execute following commands in a python console: '''</p> <p>Example:</p> <p>from obspy.core import UTCDateTime<br> from obspy.clients.fdsn import Client<br> import obspy.io.mseed<br> client = Client('IRIS')<br> t1 = UTCDateTime('2006-01-10T00:00:00')<br> t2 = UTCDateTime('2006-01-12T00:00:00')<br> raw_data = client.get_waveforms(<br> network='AV',<br> station='AUH',<br> location='',<br> channel='HHZ',<br> starttime=t1,<br> endtime=t2)</p> <p>'''To further download station information execute: '''</p> <p>xml = client.get_stations(network='AV',station='AUH', <br> channel='HHZ',starttime=t1,endtime=t2,level='response')</p> <p>''' 'To scale the data using the station’s meta-data: '''</p> <p>data = raw_data.remove_response(inventory=xml)</p> <p>''' To filter, trim and plot the data execute: '''</p> <p>data.write("Augustine.mseed", format="MSEED")</p> <p>data.filter('bandpass',freqmin=1.0,freqmax=20)<br> data.trim(t1+60,t2-60)<br> data.plot()</p> <p>Contents:</p> <p>6 different Matlab codes. The principal code is called FeatureExtraction.<br> The codes rsac.m and ReadMSEEDFast.m are for reading different format of data. (Not developed by the group)<br> Seismic Data from Mt. Etna for using as an example.</p> <p> </p>
ModelE simulation output used in the study "Severe Global Cooling After Volcanic Supereruptions? The Answer Hinges on Unknown Aerosol Size" in Journal of Climate (2024)
<p>The included files are the GISS ModelE output needed to replicate the figures in McGraw et al 2023, "Severe Global Cooling After Volcanic Supereruptions? The Answer Hinges on Unknown Aerosol Size"</p> <p>Most of the data herein is output from GISS ModelE2.2 simulations that did not include interactive aerosol microphysics and chemistry. Instead, aerosol extinction and effective radius were input into the model from scaled Easy Volcanic Aerosol [Toohey et al, GMD 2016] output, as described in this study's Methods section. To calculate volcanic temperature impacts and forcings at combinations of injected sulfur mass and peak effective radius (Reff) that were not simulated, we used 2D linear interpolation with the scipy function 'Rbf'.</p> <p>Separately included is output from GISS ModelE2.1 with MATRIX interactive aerosol microphysics and chemistry [Bauer et al, ACP 2008]. Note that the injections were scaled to match that a 6.5 Tg sulfur (S) injection in ModelE2.1/MATRIX best replicated the aerosol optical depth (AOD) and effective radius observations of the 1991 Pinatubo event despite this injection being most commonly considered an 9 Tg S injection. Hence, to produce the 1000 Tg S eruption, a 722 Tg S injected was simulated. Such a mismatch has been found in other GCMs (eg Mills et al, JGRA 2016) and may be due to aerosol quick-removal processes not represented in these models.</p> <p>Please note that simulated eruption masses are in this dataset listed in units of Tg S, but in the publication are in Tg SO2 (Tg S x 2).</p> <p>Data from other modeling studies included in Fig. 1 and tree ring estimates in Figs. S2 & S4 can be found within the cited studies.</p> <p>For additional information, please contact zachary.mcgraw@columbia.edu</p>
Volcanic Revolver
I'm back sorry, it's Red Dead 2's fault! he kept me modeling :) btw have you seen Lenny around? Source: Objaverse 1.0 / Sketchfab
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