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Data generated at UCL on a conventional triaxial apparatus. The data includes the 'raw' data, as well as semi-processed data used to plot figures and draw main conclusions. This dataset is used and fully described/interpreted in the paper: M. Jefferd, N. Brantut, P.G. Meredith and T.M. Mitchell, Compactive Deformation of Sandstone under Crustal Pressure and Temperature Conditionsserpentinite, submitted to J. Geophys. Res. And in the UCL PhD Thesis M.Jefferd, Sandstone under Crustal Pressure and Temperature
Electronic Supplementary Material: "Event trees and epistemic uncertainty in long-term volcanic hazard assessment of rift volcanoes: the example of Aluto (Central Ethiopia)", by Tierz, P., Clarke, B., Calder, E. S., Dessalegn, F., Lewi, E., Yirgu, G., Fontijn, K., Crummy, J. M., and Loughlin, S. C., submitted to Geochemistry, Geophysics, Geosystems. The datasets contain volcanological data on analogue (i.e. similar) volcanoes of Aluto volcano (Ethiopia), including conditional probabilities of eruption size, number of eruptions with specific volcanic phenomena reported and values of volcano analogy calculated using the VOLCano ANalogues Search tool (VOLCANS, Tierz et al., 2019, https://doi.org/10.1007/s00445-019-1336-3). These type of data can be used to parameterise event tree models (e.g. Newhall and Hoblitt, 2002, https://doi.org/10.1007/s004450100173; Marzocchi et al., 2010, https://doi.org/10.1007/s00445-010-0357-8) and, thus, quantify volcanic hazard at a particular volcano of interest, including the relevant sources of uncertainty. The production of the datasets was supported by the UK Natural Environment Research Council project: Rift Volcanism: Past, Present and Future (RiftVolc). Grant NE/L013460/1.
Data are distances (in cm) to water measured by an experimental near-infrared lidar sensor in six different setups (2017–9). Laboratory tests conducted at Imperial College London include quantifying the effect of (i) distance, (ii) sensor inclination, (iii) turbidity/clarity of the water, and (iv) ambient temperature on measurement bias. Outdoor tests at three locations in London interrogated the effect of varying water surface roughness on the measurements. A dataset of high-frequency measurements is also included, from which the effects of sample autocorrelation were interrogated.
Seismic waveforms from an explosion catalogue from a seismic network at Santiaguito volcano between November 2014 and December 2018. A network of 6 broadband and 6 short-period stations was used to record explosive volcanic activity. Waveforms from 18,895 explosions have been automatically been detected and extracted.
This data set characterises the seismicity occurring within 30 km of the Bora - Tullu-Moye volcanic field between 2016 and 2017. It also provides a description of key geologic features in this region. See the README file for a full explanation of the data set. These data were originally published as supplementary material in g-cubed article: Seismicity of the Bora – Tullu-Moye Volcanic field 2016-2017: Greenfield et al (2018), https://doi.org/10.1029/2018GC007648