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University of Liverpool

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  • Seismic waveforms from an explosion catalogue from a seismic network at Santiaguito volcano between November 2014 and December 2018.

  • A new family of spherical harmonic geomagnetic field models spanning the past 9000 yr based on magnetic field directions and intensity stored in archaeological artefacts, igneous rocks and sediment records. The pfm9k geomagnetic field models and datafiles as well as the individual bootstraps of the pfm9k.1b geomagnetic field model presented in A. Nilsson, R. Holme, M. Korte, N. Suttie and M. Hill (2014): Reconstructing Holocene geomagnetic field variation: new methods, models and implications. Geophys. J. Int., doi: 10.1093/gji/ggu120 are included here.

  • Text files of physical parameters controlled or measured in rock heating and deformation experiments; jpg and tif files of optical and electron microscope images of experimental products; xome xlsx spreadsheets related to data interpretation.

  • All the raw experimental data obtained for the study reported in Hodgson, E., Grappone, J. M., Biggin, A. J., Hill, M. J., & Dekkers, M. J. (2018). Thermoremanent behavior in synthetic samples containing natural oxyexsolved titanomagnetite. Geochemistry, Geophysics, Geosystems, 19. https://doi.org/10.1029/2017GC007354

  • Data files have .dat extension and can be opened with Notepad or any basic text editor software. Each file contains details of sample name, dimensions (length and diameter). All deformed samples were pre-prepared cylinders of synthetic neighbourite. Each file contains 11 data column as follows: Time (hours); Time (secs); CP (V); Vol (V); Force(V); Temp (V); Disp(V); Euro disp (mm); Furn T (mV); PoreP (mV); Furnace Power where V= Volts, mV= millivolts. The Calibration sheet (specific to the apparatus used) uploaded together with the data files is required to convert V and mV raw data into values of stress, strain, strain rate, confining pressure and temperature.

  • P* data obtained through hydrostatic loading experiments, using triaxial experimental apparatus, as well as yield curve data obtained through differential loading tests, prior to the discovery of P* for different synthetic sandstones. The methodology used was taken from Bedford et al. (2018, 2019). Grain size analysis data obtained using a Beckman Coulter LS 13 320 laser diffraction particle size analyser. Particle analysis was conducted on five different synthetic sandstones with different grain size distributions. Secondary electron and backscatter electron SEM images for natural and synthetic sandstones. Secondary electron images were stitched together to form a whole core image. They were then binarised following the methodology of Rabbani and Ayatollahi. (2015). Hexagon grid size data used to obtain the correct grid size for performing porosity analysis across an mage using Fiji software (Brown, 2000). Bedford, J. D., Faulkner, D. R., Leclère, H., & Wheeler, J. (2018). High-Resolution Mapping of Yield Curve Shape and Evolution for Porous Rock: The Effect of Inelastic Compaction on 476 Porous Bassanite. Journal of Geophysical Research: Solid Earth, 123(2), 1217–1234. Bedford, J. D., Faulkner, D. R., Wheeler, J., & Leclère, H. (2019). High-resolution mapping of yield curve shape and evolution for high porosity sandstone. Journal of Geophysical Research: Solid Earth. Brown, G. O., Hsieh, H. T., & Lucero, D. A. (2000). Evaluation of laboratory dolomite core sample size using representative elementary volume concepts. Water Resources Research, 36(5), 484 1199–1207. Rabbani, A., & Ayatollahi, S. (2015). Comparing three image processing algorithms to estimate the grain-size distribution of porous rocks from binary 2D images and sensitivity analysis of the grain overlapping degree. Special Topics & Reviews in Porous Media: An International Journal, 6(1).

  • Seismic data and metadata. Grant abstract: More than 500 million people live close to active volcanoes. Evidence suggests that, throughout history, societies have been affected and destroyed by catastrophic eruptions. In the 1900s alone almost 100000 people were killed by volcanic explosions and their associated hazards. Explosive eruptions inject enormous columns of ash and debris into the atmosphere and discharge fast avalanches of hot gas and rocks on the slopes of volcanic edifices. Lava dome eruptions represent a style of volcanism of distinctive interest because of their potentially catastrophic effects. The hazards from this type of eruptions are well-known, due to the unpredictable transitions from slow effusion of viscous lava to violent explosive activity, and to the propensity of volcanic domes to suddenly collapse spawning devastating pyroclastic flows. Over the past few decades shifts in eruptive style were reported at several lava dome volcanoes worldwide. The underlying processes driving these transitions, however, remain poorly understood, and geophysical measurements documenting them are also very rare. The Santiaguito lava dome complex in Guatemala has been continuously erupting since 1922 and it has switched several times between effusive and explosive eruption regimes, even displaying the two types of activity simultaneously. At the time of this writing Santiaguito is undergoing a major transition from effusive to explosive behaviour marked by some the largest eruptive events ever recorded at this lava dome complex. The new activity started with a large explosion on 11 April, 2016, which produced an ash column that rose to a height in excess of 4.5 km above the vent and was clearly visible in satellite images. Preliminary estimates by local scientists suggest that this explosion was two orders of magnitude more energetic than anything recorded at Santiaguito over the past 5-6 years. The new activity offers a rare opportunity to document and investigate the geophysical fingerprint of a sudden switch in eruptive style at a lava dome volcano, and to decipher its underlying mechanisms. A geophysical deployment, including seismic, deformation and acoustic measurements is the ideal framework to seize an opportunity that is not frequently available. The proposed experiment will help addressing key scientific questions on activity at lava dome volcanoes, with impact on hazard assessment and risk mitigation in this and other eruption prone areas. The pool of target beneficiaries is broad and includes scientists within academia, civil defense authorities, policy makers and communities living nearby active volcanoes.

  • UKGEOS and Core Sample Analysis. Geomechanical testing was performed to determine triaxial compressional strength, tensile strength, frictional strength and permeability of sandstones, siltstones, mudstones and coals from eleven depth intervals within the GGC01 borehole, UK Geoenergy Observatories (UKGEOS), Glasgow, United Kingdom. Frictional strength tests were also performed on cuttings samples of sandstones, siltstones, mudstones and coals from the GGA08 borehole, Glasgow, United Kingdom. In total twenty-three tensile strength tests were performed on ten sampled intervals, and seven porosity measurements pre-and post-failure were taken. Nine triaxial compressive strength tests and twenty-one frictional strength tests were performed, with permeability measured both before and after failure or shear respectively. From compressive strength tests we also determined the Young’s modulus and Poisson’s ratio. Results of X-Ray Diffraction are also included in the dataset.

  • Infrasound Data collected at Volcan de Fuego (Guatemala) during three campaigns (May and November 2018, and June 2019). Associated article https://doi.org/10.3390/rs11111302

  • This dataset measures colour and estimates body size of ant species collected across four vertical strata: subterranean, ground, understory and canopy in lowland tropical rainforest. Ants were collected using different trapping techniques in each stratum; baited traps were used in the subterranean, understory and canopy strata and Winkler extractions were used to collect ground ants. The colour of each ant species was classified categorically by eye using a set pre-determined colours. A single dominant colour was assigned for each species, this was determined as the modal colour across all body parts and individuals for each species. Each colour was linked to a set of RGB (red, green and blue) values which were extracted from the original colour wheel using the image editing software paint.NET (v.4.0.3); RGB values for each colour were converted into HSV (hue, saturation and value) format. Body size of each species was estimated by measuring Weber’s length. Accompanying the ant species data set are four additional data files: 1) data set measuring intraspecific variation in colour, 2) data set measuring intraspecific variation in Weber’s length, 3) data set measuring soil temperature, and 4) data set measuring UVB radiation at 5 m vertical intervals from the ground to the canopy. This data is a contribution from the UK NERC-funded Biodiversity And Land-use Impacts on Tropical Ecosystem Function (BALI) consortium. Full details about this dataset can be found at https://doi.org/10.5285/c0f65bf5-3cb0-41ab-be3d-982490cecba9