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70 results for “Caldera”
THD technique applied on Vp data of Long Valley Caldera
<p>We considered the V<sub>p</sub> tomographic model of Seccia et al. (2011) for Long Valley Caldera on which we applied the Horizontal Gradient technique for retrieving geometrical information about the deep structures characterizing the first 10 km of crust. Specifically, after the regularization through spatial based kriging interpolator, we compute the horizontal derivatives on single z-layers with sampling step of 500 m. The results are presented in Gola G., Barone A., Castaldo R., Chiodini G., D'Auria L., Garcia-Hernandez R., Pepe S., Solaro G. & Tizzani P. "A novel multidisciplinary approach for the thermo-rheological study of volcanic areas: The case study of Long Valley Caldera", which has been submitted for possible publication in Journal of Geophysical Research - Solid Earth.</p> <p>Coordinates: North America NAD27 UTM Zone 11N<br> Easting: 308000 - 353000 m.; Northing: 4155000 - 4185000 m; XY resolution: 500 m.</p>
Exploiting the Greenland volcanic ash repository to date caldera-forming eruptions and widespread isochrons during the Holocene
<p>Polar ice-cores have long been recognised as unrivalled repositories of past volcanic events. Although tephra products from local eruptions tend to dominate these records, improvements in micro-sampling and analytical techniques are uncovering a growing number of cryptotephras erupted from exceptionally distant volcanoes. We present a series of nine Middle Holocene cryptotephra deposits detected within the NGRIP ice-core that originate from five different volcanic regions across the Northern Hemisphere (Alaska, Cascades, Iceland, Japan, Kamchatka). Unique compositional signatures are employed to identify ash from three large caldera-forming events in Kamchatka (KS<sub>2 </sub>from Ksudach), the Cascades (Mazama) and North East Japan (Mashu), along with ash from the Hekla 4 eruption in Iceland. High-precision ice-core ages (adopting a 1950 datum for the GICC05 timescale assigned to the Greenland ice cores) are derived for each eruption: Hekla 4 (4325 ± 8 a b1.95k), KS<sub>2</sub> (7089 ± 26 a b1.95k), Mashu (i-f) (7473 ± 33 a b1.95k) and Mazama (7562 ± 35 a b1.95k), all of which can be employed as chronological fix-points in other proxy records where these deposits are also preserved. Four further cryptotephra deposits and one macro-deposit (in the GRIP ice core) are also identified and traced to sources in Iceland and Alaska. The cryptotephra originating from Alaska is correlated to a deposit identified in lake records from the Kenai Peninsula, thought to originate from Redoubt Volcano. The remaining four deposits are typical of the products of Katla, Grímsvötn and Veiðivötn in Iceland. This ensemble of mid-Holocene tephra deposits highlights the pivotal position of the Greenland ice-sheet and its ice-cores to capture deposition from the convergence of several far-travelled ash clouds. Precise age estimates derived from the annually resolved ice-core record greatly enhances the value of these tephra isochrons.</p> <p> </p>
Luigi Caldera (c1055)
<b>-- <a href="https://doi.org/10.5281/zenodo.11582199">Documentation</a> --</b><br><br><u>Name</u>: Luigi Caldera<br><u>musiXplora-ID</u>: c1055<br><u>musiXplora-URI</u>: <a href="https://musixplora.de/mxp/c1055">https://musixplora.de/mxp/c1055</a><br><u>Gender</u>: m<br><u>Date of Birth</u>: 1840<br><u>Place of Birth</u>: Cuneo<br><u>Date of Death</u>: 1905<br><u>Place of Death</u>: Turin<br><u>First Mentioned</u>: 1886<br><u>Sectors</u>: Instrumentenbau<br><u>Professions (Historical)</u>: Erfinder der Calderarpa, Patentinhaber<br><u>Professions (Non-Musical)</u>: Ingenieur<br><u>Other Places of Activity</u>: Turin<br><br><br><u>Tradition:</u><br><table><tbody><tr><th>Group</th><th>Role</th><th>Name</th><th>mXp-ID</th></tr><tr><td>Interessensbereich</td><td>Interessensbereich</td><td>Archiv Norbert Kottenstede</td><td><a href="https://musixplora.de/mxp/3080538">3080538</a></td></tr></tbody></table><br><u>Objekte/Werke:</u><br><table><tbody><tr></tr><tr><td>Hersteller</td><td></td><td>Klavierharfe</td><td>4010236</td></tr></tbody></table><br><br><u>Changelog</u>:<br> - v0.0.1: Initial Upload.<br>
Caldera resurgence during the 2018 eruption of Sierra Negra volcano, Galápagos Islands
<p>Key datasets associated with the 'Caldera resurgence during the 2018 eruption of Sierra Negra volcano, Galápagos Islands'. This are pre-eruption and co-eruption interferograms, IGUANA earthquake catalogue, list of earthquake times and magnitudes picked from station VCH1, and cGPS baseline timeseries.</p>
Fig. 1 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 1. Map of Lake Taal with the six sampling sites (NB – North Basin, SB – South Basin). The insert shows the location of Lake Taal and the other lakes mentioned in the text (P – Lake Paoay, Lb – Lake Laguna de Bay, N – Lake Naujan and Ln – Lake Lanao).
Fig. 4 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 4. Monthly variations in Shannon-Wiener Diversity (H') Index values of rotifers and cladocerans in the north and south basins of Lake Taal.
Fig. 3 in The Composition, Diversity And Community Dynamics Of Limnetic Zooplankton In A Tropical Caldera Lake (Lake Taal, Philippines)
Fig. 3. Mean monthly biomass (μg / l) of common zooplankton species from the north and south basins of Lake Taal for the year 2008.
Geodetic anomaly detection and analysis in the Campi Flegrei caldera (Italy) deformation pattern of the 2021-2023 escalating unrest phase
<p>Data used within the manuscript: "<strong><span>First evidence of a geodetic anomaly in the Campi Flegrei caldera (Italy) ground deformation pattern revealed by DInSAR and GNSS measurements during the 2021-2023 escalating unrest phase</span>"</strong></p> <p> </p> <p>Archive content:</p> <ul> <li><code>DTSLOS_CNRIREA_20150325_20231021_FB9K</code>: Line of Sight displacement time series retrieved by applying the P-SBAS algorithm to Sentinel-1 data set acquired from ascending orbits (Track 44) over Campi Flegrei caldera in the 20150325 - 20231021 interval. Data format is according to the <a href="https://gitlab.com/epos-tcs-satdata/doc/-/blob/main/TCS_SATD_Product_Description.md#los-displacement-time-series-dtslos" target="_blank" rel="noopener noreferrer">EPOS specification</a>.</li> <li><code>DTSLOS_CNRIREA_20150324_20231020_UJBI</code>: Line of Sight displacement time series retrieved by applying the P-SBAS algorithm to Sentinel-1 data set acquired from descending orbits (Track 22) over Campi Flegrei caldera in the 20150324 - 20231020 interval. Data format is according to the <a href="https://gitlab.com/epos-tcs-satdata/doc/-/blob/main/TCS_SATD_Product_Description.md#los-displacement-time-series-dtslos" target="_blank" rel="noopener noreferrer">EPOS specification</a>.</li> <li><code>Campi_Flegrei_GNSS_Weekly_Timeseries</code>: Weekly displacement time series of Campi Flegrei caldera GNSS network from 2016 to 2023.</li> </ul>
Dataset for the paper "Accelerating Seafloor Uplift of Submarine Caldera near Sofugan Volcano, Japan, Resolved by Distant Tsunami Recordings"
<p>The results of the analysis in the paper "Accelerating Seafloor Uplift of Submarine Caldera near Sofugan Volcano, Japan, Resolved by Distant Tsunami Recordings" published in Geophysical Research Letters are available here. For the details of the file, please see Readme.pdf.</p>
Numerical simulations of the latest caldera-forming eruption of Okmok volcano, Alaska
<p>Raw outputs of the numerical simulations of an explosive volcanic eruption.</p> <p>The file "source.zip" includes all the source files modified compared to the default<br>MFIX 2016-1 files (www.mfix.netl.doe.gov, v.2016). It also includes an example of the input file mfix.dat (run 3). These<br>are raw file intended for enabling result reproductibility. They contain unused <br>optional variables and are not intented (and commented) to serve as tutorials. The<br>subfolder "postmfix" includes the source file for option 6 of the post processing<br>program. Some options are user-defined, and others are hard coded.</p> <p>The file "AllRuns.zip" inculde all the Okmok runs. All runs were generated with <br>MFIX 2016-1 in TFM mode. They are organized in folders corresponding to the naming<br>convention of Table 1. Some runs were generated in several sequences (e.g., 0-300 s,<br>then 300-700 s) that were stitched into a single output bundle. Other sequences were<br>kept separated.</p> <p>The files OK.RES can be openend with Paraview >5.6 and selecting the MFIXReader.</p> <p>The variables are:</p> <p>EP_g = Gas volume fraction<br>Gas Velocity = Gas velocity vector (m/s)<br>P_g = Pressure (Pa)<br>P_star = Solid pressure (Pa)<br>ROP_s_m = Solid density times particle volume fraction of solid phase m (kg/m3)<br>RRates_1 = Gas density (kg/m3)<br>RRates_2 = Gas viscosity (Pa s)<br>Solids_Velocity_x = Velocity vector of solid phase x (m/s)<br>T_g = Gas temperature (K)<br>T_s_x = Temperature of solid phase x (K)<br>Theta_m_x = Granular temperature of solid phase x (m2/s2)<br>U_g = Horizontal component of gas velocity (m/s)<br>V_g = Vertical component of gas velocity (m/s)<br>W_g = Z component of gas velocity (0 because axisymmetric domain)<br>U_s_x = Horizontal component of velocity of solid phase x (m/s)<br>V_s_x = Vertical component of velocity of solid phase x (m/s)<br>W_s_x = Z component of velocity of solid phase x (0 because axisymmetric domain)<br>X_g_x, X_s_x = unused<br>k_turb_g (not always recorded) = Turbulent kinetic energy (J/kg)<br>e_turb_g = duplicate of k_turb_g</p> <p><br>Refer to the MFIX documentation for more details on the format and on the model itself.</p> <p> </p>
Data Set for Sandanbata et al. (2023: GRL) entitled "Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc"
<p><strong>Descriptions</strong></p> <p>This dataset contains supplementary materials for the manuscript under revision for Geophysical Research Letters; the preprint has been uploaded to ESS Open Archive:</p> <ul> <li>Sandanbata, O., Watada, S., Satake, K., Kanamori, H., & Rivera, L. (2023). Two volcanic tsunami events caused by trapdoor faulting at a submerged caldera near Curtis and Cheeseman Islands in the Kermadec Arc. <em>Geophysical Research Letters</em>, 50, e2022GL101086. <a href="https://doi.org/10.1029/2022GL101086">https://doi.org/10.1029/2022GL101086</a></li> </ul> <p>We constructed a source model for the 2017 earthquake at Curtis caldera in the Kermadec Arc. The dislocation distributions and source geometries of this source model, presented in Figure 3, are contained in this dataset.</p>
Analogue models of caldera resurgence: database of models and elaborations
<p>This dataset presents the results of an experimental series of analogue models performed to investigate caldera resurgence processes, particularly the setting of the Los Potreros caldera that belongs to the Los Humeros Volcanic Complex (Puebla State, Mexico). Our experimental series was designed adopting a parametric approach, which consisted in the systematic variation of controlling parameters, such as: depth of intrusion, overburden thickness above the analogue magma chamber, presence of inherited discontinuities. Structures of models have been analysed quantitatively by means of (i) photogrammetric Digital Elevation Model reconstruction, (ii) semi-automatic fault pattern quantification and (iii) Digital Particle Image Velocimetry techniques. In this dataset, we show the row data and specific elaborations supporting the interpretation of modelling results.</p>
Supplementary material for the article "The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani"
<p>This repository contains the data and supplementary material associated with the manuscript: Ágreda-López M., Musu A., Jorgenson C., Sǎla M., Giordano G., Caricchi L., Stremtan C., Petrelli M. "<strong>The Crystal Cargo Provides a Chronicle of Pre-Caldera Dynamics in Mafic Volcanic Systems: Insights from Colli Albani</strong>".<em> S</em>ubmitted to the Journal<em> Bulletin of Volcanology.</em></p> <div> </div> <p> </p>
Supporting Information for "Data analysis of the unsteadily accelerating GPS and seismic records at Campi Flegrei caldera from 2000 to 2021". Data Set S1. Extended dataset of all the analyses
<p>This compressed folder contains supporting information related to the Figures in the manuscript: "Data analysis of the unsteadily accelerating GPS and seismic records at Campi Flegrei caldera from 2000 to 2021".</p> <p>Files and folders labeled with G1…n are related to the GPS data, those labeled with H1…n are related to the seismic data.</p> <p>In particular: <br> Subfolder 1_DATA supports Figure 3 – the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; the logarithmic plots of all seismic events and of their energy. It also shows the complete plot leveling data from 1905 to 2010 (modified from del Gaudio et al., 2010). It also includes Figure 2 and Figure 6a-c.</p> <p>Subfolder 2_AnnualRate supports Figure 4 - the annual rate of the vertical and horizontal moduli of ground displacement at all analyzed GPS stations; the annual rate of all seismic events and of their energy. These detail the 2-year, the 6-month, and the 30-day average results. It also supports Figure 5 with similar data concerning 2018-2020.</p> <p>Subfolder 3_InverseRate supports Figure S3 - the inverse rate of the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; the inverse rate of all seismic events and of their energy. These detail the 2-year, 6-month, and 30-day average results, including detailed plots of 2018-2020.</p> <p>Subfolder 4_RateChange supports Figure S2 - the daily rate change of the vertical and horizontal moduli of ground displacement at all analyzed GPS stations; the daily rate change of all seismic events and of their energy. These detail the 2-year, the 6-month, and the 30-day average results, including detailed plots of 2018-2020.</p> <p>Subfolder 5_FourierCoef supports Figure 6 - the Fourier spectrum of the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations. These detail the 2-year, 6-month, and 30-day average results obtained in 2000-2020, 2011-2020, 2018-2020. Also, additional plots that detail other combinations of time domain and part of the Fourier spectrum, thus testing the sensitivity of the main harmonics on the time domain selected.</p> <p>Subfolder 6_ FFM_WaitTime supports Figure 11 – waiting time examples based on vertical and horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events, and their energy. These detail the 2-year, 6-month, and 30-day average rate results, and the 10-year, 5-year and 3-year regressions.</p> <p>Subfolder 7_FFM_FailTime also supports Figure 11 – all the results expressed in terms of the failure time t<sub>f</sub> instead of in terms of the waiting time [t<sub>f</sub>(t) - t].</p> <p>Subfolder 8_pFFM_Regression supports Figure 9 - the pFFM examples based on the vertical and the horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events and of their energy. These detail the 2-year, 6-month, and 30-day average rate results, and the 10-year, 5-year and 3-year regression.</p> <p>Subfolder 9_pFFM_Probability supports Figure S4 - pFFM examples based on vertical and horizontal moduli of ground displacement at all analyzed GPS stations; all seismic events, and their energy. These detail the 2-year, 6-month, and 30-day average rates, and the 10-year, 5-year and 3-year regressions.</p> <p>Subfolder 10_BarplotProb supports Figure S5 - results expressed in terms of the mean failure time probability at 2, 5, 10, and 25 years.It also supports Figure S6 - examples based on 6-month, and 30-day average rate results.</p> <p>Subfolder 11_BarplotWaitTime supports Figure S6 - all the results expressed in terms of the waiting time (t<sub>f</sub> – t) barplot. It also includes Figure S5.</p>
Simualtion results of T wave proapgation from regions near the Sofu seamount and the Sumisu Caldera
<p>The simulation results used in the submitted manuscript</p> <p>Simulation results of high-frequency T-wave propagation from regions near the Sofug seamount and the Sumisu Caldera</p> <ul> <li>sac.tar: envelopes of simulation results</li> <li>green_sofugan: source grids and index information for simulation results in the region near the Sofugan Volcano</li> <li>green_sumisu: source grids and index information for simulation results in the region around the Sumisu Caldera</li> </ul> <p>The characteristics of simulated envelopes were listed in 231009GF_M.KMB06_???.dat (near the Sofu seamount) and 180506GF_M.KMB06_???.dat (Sumisu Caldera).</p> <ul> <li>longitude, latitude, depth, epicental distance, theoretical P traveltime, peak arrival time of body wave, theoretical T traveltime, peak arrival time of T wave, half-value starting, half-value ending, mximuma body wave amplitude, maximum T wave amplitude, envelope file name</li> </ul> <p>Details are described in "<span>Takemura, S.</span>, <span>Kubota, T.</span>, & <span>Sandanbata, O.</span> (<span>2024</span>). <span>Successive tsunamigenic events near Sofu Seamount inferred from high-frequency teleseismic <em>P</em> and regional <em>T</em> waves</span>. <em>Journal of Geophysical Research: Solid Earth</em>, <span>129</span>, e2024JB029746. <a href="https://doi.org/10.1029/2024JB029746">https://doi.org/10.1029/2024JB029746</a>"</p>
Askja caldera 1945-2023 geospatial dataset
<p>Here, we present a geospatial dataset covering the 1945-2023 period of morphodynamics at Askja caldera, Iceland. The dataset consists of three parts: (1) digital elevation models (DEMs) generated from the 1945 and 1987 archive aerial photographs, 2013 and 2022 Pléiades satellite imagery, and 2019, 2022, and 2023 drone images; (2) orthophotographs generated from the same source data; and (3) set of shapefiles, which represents the identified morphological features at the SE wall of Askja caldera.</p> <p>The initial data was processed using Agisoft Metashape Professional v. 1.8.3 photogrammetric software. In addition, the 2022 and 2023 drone datasets contained infrared images that were pre-processed in ThermoViewer v. 3.0.4 and DJI Thermal Analysis Tool v. 3.1.0. The features in the shapefiles were extracted based on the DEMs and orthophotos using ArcGIS desktop v. 10.8.2 tools.</p> <p>Data was used to perform 2D and 3D analysis of the long-term geomorphological processes and slope instability at the caldera wall, to reveal precursors of preparing hazardous events, and to calculate volumes of the 2014 landslide. Repeated morphological analysis and feature tracking starting from 1945 revealed that changes are persistent over the observation period, locally accumulating in the area, which was later affected by the 2014 landslide. The results are relevant for understanding the factors of slope instability at Askja caldera and for possible hazard assessment.</p> <p>We acknowledge the National Land Survey of Iceland (LMI) for providing the 1987 and 1945 aerial photographs, the National Center for Space Studies (CNES) for providing Plèiades data at a preferential (institutional) price, the German Research Center for Geosciences (GFZ) for financing the fieldwork.</p> <p>This dataset corresponds to an article: Shevchenko, A.V., Walter, T.R., Gudmundsson, M.T. et al. Morphological changes of the south-eastern wall of Askja caldera, Iceland over the past 80 years. Commun Earth Environ 5, 441 (2024). https://doi.org/10.1038/s43247-024-01616-z</p>
Toba Caldera geochronological and modelling dataset
<p>Bayesian statistical analysis and inverse thermal history modeling of feldspar <sup>40</sup>Ar/<sup>39</sup>Ar and zircon (U-Th)/He ages reveal that post-caldera dome eruptions at Toba Caldera, Sumatra occurred up to ca. 13.6 kyr later than indicated by <sup>40</sup>Ar/<sup>39</sup>Ar feldspar ages. This discordance implies cold storage of feldspar antecrysts prior to eruption for a maximum duration of ca. 5 and 13 kyr at between 280°C and 500°C. These findings connote that the solidified carapace of remnant magma after the Youngest Toba Tuff (YTT) eruption ~74 ka erupted in a subsolidus state, without being thermally remobilized or rejuvenated. Our data mean that resurgent uplift and volcanism initiated approximately 5 kyrs after the climactic YTT eruption, thus providing rare constraints on resurgence after a cataclysmic supereruption. Our approach has the potential to reveal complexities in pre-eruptive storage and eruption at unprecedented temporal resolution with implications for active restless calderas and young silicic volcanoes worldwide.</p>
Datasets for "Trapdoor fault activation: a step towards caldera collapse at Sierra Negra, Galápagos, Ecuador", Journal of Geophysical Research: Solid Earth
<p>The following files were used in the analysis from "Trapdoor fault activation: a step towards caldera collapse at Sierra Negra, Galápagos, Ecuador", <em>Journal of Geophysical Research: Solid Earth</em>:</p> <p><strong>alos2_csk/alos2_sm1_dsc_20180504_20180713/:</strong> Includes DEM used in processing of the ALOS-2 SM1 descending interferogram spanning 4 May 2018–13 July 2018 (dem.2alks_2rlks.crop.*); geocoded SAR offsets in pixels (range resolution=1.43 m/pixel; azimuth resolution=2.01 m/pixel; denseOffsets.bil.2alks_2rlks.geo*); geocoded SNR of SAR offsets (denseOffsets_snr.bil.2alks_2rlks.geo.*); geocoded, unwrapped interferometric phase (filt_topophase.unw.2alks_2rlks.geo.*); geocoded incidence and heading angle for the interferogram (los.rdr.2alks_2rlks.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/alos2_sm3_asc_20180114_20180701/:</strong> Includes DEM used in processing of the ALOS-2 SM3 ascending interferogram spanning 14 January 2018–1 July 2018 (dem.crop.*); geocoded, unwrapped interferometric phase (filt_topophase.unw.geo.*); geocoded incidence and heading angle for the interferogram (los.rdr.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/alos2_wd1_dsc_147_180518_180629/</strong>: Includes DEM used in processing of the ALOS-2 WD1 descending interferogram spanning 18 May 2018–29 June 2018 (crop.dem.*); geocoded, unwrapped interferometric phase (filt_180629-180518_2rlks_14alks.unw.geo.*) ; geocoded incidence and heading angle for the interferogram (180629-180518_2rlks_14alks.los.geo.*); geocoded coherence for the interferogram (180629-180518_2rlks_14alks.cor.geo.*); geocoded mask for the interferogram (filt_topophase.unw.masked.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/csk_asc_20180617_20180703/:</strong> Includes DEM used in processing of the COSMO-SkyMed ascending interferogram spanning 17 June 2018–3 July 2018 (dem.crop.*); geocoded SAR offsets in pixels (range resolution=1.54 m/pixel; azimuth resolution=2.48 m/pixel; denseOffsets.bil.geo.*); geocoded SNR of SAR offsets (denseOffsets_snr.bil.geo); geocoded incidence and heading angle for the interferogram (los.rdr.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/csk_asc_20180703_20180719/</strong>: Includes DEM used in processing of the COSMO-SkyMed ascending interferogram spanning 3 July 2018–19 July 2018 (dem.crop.*); geocoded SAR offsets in pixels (range resolution=1.54 m/pixel; azimuth resolution=2.48 m/pixel; denseOffsets.bil.geo.*); geocoded SNR of SAR offsets (denseOffsets_snr.bil.geo); geocoded incidence and heading angle for the interferogram (los.rdr.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/csk_dsc_20180618_20180704/:</strong> Includes DEM used in processing of the COSMO-SkyMed descending interferogram spanning 18 June 2018–4 July 2018 (dem.crop.*); geocoded SAR offsets in pixels (range resolution=1.70 m/pixel; azimuth resolution=2.45 m/pixel; denseOffsets.bil.geo.*); geocoded SNR of SAR offsets (denseOffsets_snr.bil.geo); geocoded incidence and heading angle for the interferogram (los.rdr.geo.*); all in ISCE format.</p> <p><strong>alos2_csk/csk_dsc_20180704_20180720/: </strong>Includes DEM used in processing of the COSMO-SkyMed descending interferogram spanning 4 July 2018–20 July 2018 (dem.crop.*); geocoded SAR offsets in pixels (range resolution=1.70 m/pixel; azimuth resolution=2.45 m/pixel; denseOffsets.bil.geo.*); geocoded SNR of SAR offsets (denseOffsets_snr.bil.geo); geocoded incidence and heading angle for the interferogram (los.rdr.geo.*); all in ISCE format.</p> <p><strong>S1.zip</strong>: Unwrapped, geocoded interferometric phase in meters for Sentinel-1 ascending and descending interferograms, spanning time periods of interest. </p> <p><strong>S1_20180630_20180706_asc_mask_nan_ref.grd: </strong>Unwrapped, geocoded, and masked interferometric phase for Sentinel-1 ascending interferogram spanning 30 June 2018–6 July 2018.</p> <p><strong>S1_20180701_20180707_desc_mask_nan_ref.grd: </strong>Unwrapped, geocoded, and masked interferometric phase for Sentinel-1 descending interferogram spanning 1 July 2018–7 July 2018.</p> <p><strong>tandemx12m_crop.grd</strong>: TanDEM-X 12 meter DEM in meters.</p> <p><strong>pleaides_tandemx12m_diff.grd</strong>: Difference between the TanDEM-X 12 meter DEM and the Pléiades-derived DEM, computed from images on 29 October 2018 and 6 December 2019.</p> <p><strong>trapdoorFaultSlip.zip</strong>: Discretized trapdoor fault patch dip-slip modeled to fit deformation from Sentinel-1 ascending interferograms, estimated using the Classic Slip Inversion software.</p> <p><strong>trapdoorFaultTraces.zip</strong>: Caldera and trapdoor fault traces, derived from <em>Bell et al. 2021</em>.</p> <p><strong>SN14_tilt_10s_2018-19.txt</strong>: Text filt containing date-time (sampled at 10 s, in matplotlib date-time number format), N-S tilt and E-W tilt. Tilt values can be converted to microradians by multiplying by a factor of 0.00129. Tilt data obtained from authors of <em>Bell et al. 2021</em>. For use of this dataset, please cite <a href="https://doi.org/10.1038/s41467-021-21596-4">https://doi.org/10.1038/s41467-021-21596-4</a>.</p>
Toba Caldera geochronological and modelling dataset
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3D attenuation model of Long Valley Caldera (CA)
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