MFIX (Multiphase Flow with Interphase eXchanges) simulation input files and results of simulation of fragmentation-induced fluidization, and laboratory analyses of volcanic pyroclastic density current material. The data consists of: 1) the Fortran90 input files for the MFIX (Multiphase Flow with Interphase eXchanges) TFM simulation runs, 2) the postprocessed MFIX results from our simulations present within Excel sheets 3) laboratory results on the particle shape, size distribution and porosity of the volcanic granular mixtures, presented within Excel sheets. The dataset presented was gathered to investigate the role of compaction, resulting from particle fragmentation, within volcanic granular flows known as pyroclastic density currents. The presented results were obtained from a combination of laboratory analyses and numerical modelling, using Computational Fluid Dynamics. In the laboratory, characterization of the particle size distributions and shape of volcanic grains was undertaken to understand their packing properties. Using the Two-Fluid Model (TFM), an Eulerian-Eulerian method, I was able to simulate the effect of particle breakage on natural scale volcanic mixtures. This model supports a broad range of capabilities for dense multiphase flow. The code was used to investigate the role of particle breakage in pyroclastic density currents, which alters the maximum packing of the granular mixture and ultimately the concentration of the flow during transport. Because the solid phase is immersed in air, the code allowed me to simulate the self-fluidization of the volcanic mixture and the effect on its flowability. These simulations enable me to propose a new process that can play a large role in the occurrence of long runout deadly pyroclastic density currents: Fragmentation-Induced Fluidization. The laboratory work was conducted at the University of Oregon (USA) while the numerical work was completed by running the simulations on the UKRI ARCHER2 HPC and the Talapas Cluster from the University of Oregon (US). The data processing was ongoing from August 2021 to December 2021 (Lab analyses) and February 2022 to August 2022 (HPC work). The MFIX simulation results have been post-processed using ParaView open-source software but can be reproduced by the user using the MFIX custom-changed subroutines and input files contained within the dataset. The data was collected to test the hypothesis that compaction, and subsequent self-fluidization is key to the long-runout of pyroclastic density currents. Specialized audience that work on granular media and volcanic flows. The MFIX code that is modified from the core code from the Department of Energy (DOE) is all present. The missing core code can be downloaded from the DOE department https://mfix.netl.doe.gov/. All the experimental data from lab experiments are presented.

Glacier meltwater supplies a significant amount of silicon (Si) and iron (Fe) sourced from weathered bedrock to downstream ecosystems. However, the extent to which these essential nutrients reach the ocean is regulated by the nature of the benthic cycling of dissolved Si and Fe within fjord systems, given the rapid deposition of reactive particulate fractions at fjord heads. The dataset is used to examine the benthic cycling of the two nutrients at Patagonian fjord heads through geochemical analyses of sediment pore waters and reaction-transport modeling for Si. The dataset contains: (i) pore water redox-sensitive nitrate (NO3-) and dissolved manganese (DMn) concentration data, nutrient dissolved silicon (DSi) and iron (DFe) concentration and isotope data (delta30 Si, delta56 Fe); (ii) mild alkaline leachable (Si-Alk) and acid leachable (Si-HCl) sediment silica content and isotope data; and (iii) reaction transport model output for the benthic cycling of Si. The pore water and sediment samples were collected from four sites: SJ (48.228o S, 73.502o W, 106 m depth), SH (47.679 S, 73.715 W, 203 m depth), SP (48.179 S, 73.347 W, 248 m depth) and SB (47.787 S, 73.610 W, 151 m depth) in the Baker-Martinez Fjord Complex on the research vessel Sur-Austral in February 2017. Funded by NERC-CONICYT grant NE/P003133/1-PII20150106.

The dataset includes results from laboratory experiments aiming to explore the reduction and polymerization potential of phosphorus under metamorphic conditions. Table 1 shows the initial composition of the starting materials, as well as the conditions under which those materials were heated to metamorphic temperatures. Table 2 shows the analytical results, including mineralogy and phosphorus speciation. The results show that phosphate polymerization occurs at moderate temperatures of a <100 to ca. 300 degrees whereas phosphate reduction increases with increasing temperature. The presence of metallic catalysts impacts both processes. The results imply that a diverse suite of phosphorus species can be created during metamorphism, which may explain previous reports of reduced phosphorus in high-grade metamorphic rocks. This is relevant for the origin of life, where such species may have been important precursors for phosphorylated biomolecules.

The data provided here are model iteration objects and rasters needed to run the multi-scale modelling process and predict how the host condition affects probability of Hendra virus shedding. The dataset contains predictions of three proxies for host conditions (including food shortage, rehabilitation admissions and formation of a new roost) across eastern Australia in 2008-2019. The Roost Species Distribution Model (SDM) has predictions of roost suitability. These are monthly, spatially explicit predictions of particular conditions or probability of roost occupations. The model objects are iterations of models that were initially trained on data held in figshare (https://figshare.com/s/ddb5a1584609b20f6596). These data objects are linked with code provided at https://github.com/hanlab-ecol/BatOneHealth to be able to run the models and analyses. This includes comparisons of virus predictions of seven different multiscale model structures to observed Hendra virus shedding in field surveys. The purpose of this study was to determine if quantifying and incorporating host condition into epidemiological models improves predictions of virus shedding in space and time. The data objects relate to the 1,000 iterations run of this process to better able to account for uncertainty. Full details about this dataset can be found at https://doi.org/10.5285/93bb37c6-ef86-4386-945d-c1a3d1e2683c

A database of pyroclastic density current deposit characteristics. The database includes both quantitative datasets (e.g., grain size, density, bedform dimensions, thickness) and qualitative descriptors (e.g., sedimentary structures, lithofacies). PDCD-DAT includes data from 85 source publications, covering 97 eruptions or eruptive phases, and 214 individual depositional units from 55 globally distributed volcanoes. Eruptions recorded in the database range from VEI 1-8. A website is currently being built which will host the searchable database, https://flowdat.org/pdcd-dat

This dataset consists of the time series of mass change of the Greenland Ice Sheet and its contribution to global sea level between 1980 and 2018 derived from satellite measurements. The dataset presented here is a reconciled estimate of mass balance estimates from three independent satellite-based techniques - gravimetry, altimetry and input-output method - and its associated uncertainty. This dataset is part of the Ice Sheet Mass Balance Inter-comparison Exercise (IMBIE). The total mass change as well as the partition between surface and dynamics mass balance are provided in this dataset. This work is an outcome of the Ice Sheet Mass Balance Inter-Comparison Exercise (IMBIE) supported by the ESA Climate Change Initiative and the NASA Cryosphere Program. Andrew Shepherd was additionally supported by a Royal Society Wolfson Research Merit Award and the UK Natural Environment Research Council Centre for Polar Observation and Modelling (cpom30001). ***** PLEASE BE ADVISED TO USE UPDATED DATA ***** The expanded data set (see 'Related Data Set Metadata' link below) has an additional 24 months of measurements, and also includes data for Antarctica.

This dataset contains rates of mass change and cumulative mass change and their associated uncertainty for the Antarctic Ice Sheet (in its entirety and split into West Antarctica, East Antarctica and the Antarctic Peninsula), the Greenland Ice Sheet, and their sum between 1992 and 2020. The data are reconciled estimates of mass balance from three independent satellite-based techniques: altimetry, gravimetry and input-output method. This dataset is part of the Ice Sheet Mass Balance Intercomparison Exercise (IMBIE). This work is an outcome of the Ice Sheet Mass Balance Inter-Comparison Exercise IMBIE) supported by the ESA Climate Change Initiative and the NASA Cryosphere Program. Andrew Shepherd was additionally supported by a Royal Society Wolfson Research Merit Award and the UK Natural Environment Research Council Centre for Polar Observation and Modelling (cpom30001).