DOI: 10.5285/aa34005e-42ac-4204-8cb0-98c15d63761e
title: Shapefiles of volcanoes and nearby glaciers in South America used to demonstrate the link between glacier equilibrium line altitude (ELA) and volcano thermal anomaly.

description: This dataset comprises four distinct shapefiles, which were used to demonstrate how glacier ELA is affected by volcanic thermal conditions. The shapefiles, with the exception of '139_Remapped_Glaciers.shp', are obtained from existing, open access data from the Randolph Glacier Inventory (RGI 6.0) and the Global Volcanism Program 2013. Additional information relevant to the study of the interaction between glaciers and volcanoes is included in the shapefile's attribute table, as obtained via the GIS analysis of these datasets. The '600_RGI_Glaciers.shp' shapefile comprises 600 (land-terminating, no debris-covered, superior to 0.1 km2) glacier polygons, which are located within 15 km from a Holocene (erupted in the past 10,000 years) volcano in South America. Crucially, the equilibrium line altitude (i.e., the elevation on the glacier where the surface mass balance, measured over 1 yr, is zero) and distance to the nearest volcano for each glacier is reported in the attribute table. The '37_GVP_Volacanoes.shp' shapefile contains points for 37 South America Holocene volcanoes which have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers). For each volcano, the difference in ELA between volcanic (inferior to 1km from volcano) and proximal (1-15 km) glaciers is reported in the attribute table, along with mean temperature and precipitation. The '139_Remapped_Glaciers.shp' shapefile provides detailed and updated (relative to RGI) mapping of glaciers (as polygons) that are located within 15 km from 13 South America Holocene volcanoes for which thermal anomaly is known. The ELA of these glaciers is calculated and reported in the attribute table. The '13_AVTOD_Volacanoes.shp' shapefile comprises the points for 13 Holocene volcanoes that have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers) from their centre, as well as recorded thermal anomaly. The glacier ELA and volcano thermal data provided in the attribute table allows us to establish the quantitative relationship between volcanoes and glaciers. A detailed description of the study based on this dataset is provided in Howcutt et al. (2023). This project and data were supported by the NERC Global Partnerships Seedcorn fund (NE/W003724/1).
description: * 37_GVP_Volacanoes.shp and 13_AVTOD_Volacanoes.shp Ice-clad volcano points Situated in the Andes mountain chain, South America. Coordinates provided by the Global Volcano Programme (GVP) in csv/kml format. Holocene Occurrences: volcanoes with eruptions within the last 10,000 years. The Global Volcanism Program (GVP) inventory was used for these shapefile, with kml points (and associated coordinates) downloaded from the Smithsonian Institution website and converted to shapefile format. The point feature classes were then reprojected from the WGS 1984 geographical coordinate system into the UTM zone 18S and imported into ArcGIS 10.8.1 for analyses. Volcanoes were filtered according to glacier local climatic and geomorphological properties of the corresponding nearby glacier outlines (see '600_RGI_Glacier.shp' entry). Thirty-seven volcanoes hosting glaciers within a radius of 1 km from the volcanic centre, and which were classified in GVP as Holocene (having been active within the last ~12,000 years), were classed as ice-clad volcanoes and used in this study. On each ice-clad volcano, a radius buffer was applied to differentiate volcanic-glaciers located less than 1 km from the volcanic centre and proximal glaciers located within 1-15 km of the volcanic centre. Glaciers are expected to be most strongly influenced by volcano thermal condition when located on or close to the volcanic centre (less than 1 km). Beyond this distance, the volcanic (i.e., heat) influence on basal melting is anticipated to reduce progressively, and thus glacier elevation and size be increasingly controlled by climate. We set the proximal glacier buffer to 15 km to facilitate the assumption that climate within this radius, and therefore its influence on glacier elevation and ELA, can be viewed as uniform for each ice-clad volcano and the corresponding proximal glaciers. For 37_GVP_Volacanoes.shp the study presents results from the 37 ice-clad volcanoes which host a total of 600; 526 proximal and 74 volcanic-glaciers. Fields include GVP volcano name; [Delta]ELAmean (m). They also include total annual precipitation (Mean_TAP) and mean annual air temperature (mean_AAT) between 1970 and 2000, obtained from WorldClimVersion 2. For 13_AVTOD_Volacanoes.shp, The initial 37 ice-clad volcanoes (hosting a total of 600; 526 proximal and 74 volcanic-glaciers) were reduced to 13 volcanoes - for those with valid temperature observations captured by the ASTER Terra satellite instrument as part of the ASTER Volcanic Thermal Output Database (AVTOD). Calculated mean values for the maximum temperature anomalies were recorded for each volcano, and this was compared with each glacier's [Delta]ELAmean. Fields include GVP volcano name; mean_Tmax; [Delta]ELAmean (m). Statistical attributes were used to analyse the effect of measured volcanic thermal anomalies for these 13 ice-clad volcanoes on the glacier elevation (i.e., [Delta]ELAmean - see '139_Remapped_Glaciers.shp' ELA descriptor and calculation). Volcanic thermal anomalies (mean_Tmax) captured from the AVTOD (ASTER Volcanic Thermal Output Database) Latin America archive. * 139_Remapped_Glaciers.shp Glacier outline polygons existing nearby ice-clad volcanoes, output using a combination of automated and manual GIS-based mapping techniques. Situated in the Andes mountain chain, South America. Mapped by Mr. Stephen Howcutt Date range: 2018 to 2019 (summer ablation seasons). Thirteen volcanoes of the 37 initially analysed have a record of measured temperature anomalies, obtained between 2000 and 2018. A total of 139 nearby glacier outlines were re-mapped by means of a semi-automated mapping approach. This involved the application of supervised pixel training and maximum likelihood classification techniques in ArcMap 10.8.1 for extraction of polygons, using shortwave infrared false colour imagery. Composite imagery was generated from a series of cloud-free Landsat 8 and Sentinel-2 satellite scenes acquired for the Andes during summer ablation seasons between 2018 and 2019. The ELAs for the 139 glaciers (28 volcanic- and 111 proximal) were calculated using a semi-automated GIS Toolbox. The RGI glacier outline polygons and DEMs of the glacier surfaces provide the required inputs. For the purpose of this investigation the AABR method was applied as it is the most robust technique for ELA calculation and accounts for glacier hypsometry (together with mass balance gradients). This method has a median absolute error of 65.5 m relative to field measurements. The first step in the AABR calculation involves the division of the glacier surface into contour elevation belts based on a user-specified contour interval. In this case, this parameter was set to 10 m and therefore each ELA reported in the paper has a computational accuracy of +/-5 m. The ELA of each glacier was determined with a user-defined AABR, which was here set to a globally representative median value of 1.56. Distance to volcano was simply calculated using the 'near' in the ArcGIS spatial analyst toolbox. For each of the 13 ice-clad volcanoes analysed, we determined the mean ELA of all proximal and volcanic- glaciers and calculated the difference to obtain the [Delta]ELAmean. * 600_RGI_Glaciers.shp Glacier outline polygons existing nearby ice-clad volcanoes. Situated in the Andes mountain chain, South America. Mapped by contributors to the Randolph Glacier Inventory (RGI) version 6.0. Date range: 2000 and 2004. Glaciers named in accordance with RGI ID and corresponding nearest volcano, and are situated in the Andes mountain chain in South America (countries: Colombia; Ecuador; Peru; Bolivia; Chile; Argentina) Andean glacier outline shapefiles mapped between 2000 and 2004 were downloaded from the Randolph Glacier Inventory (RGI) version 6.0 dataset. Data were reprojected from the WGS 1984 geographical coordinate system into the UTM zone 18S and imported into ArcGIS 10.8.1 for analyses. Due to the more complex dynamics of water (lake and marine) terminating glaciers, and the potential impact on glacier geometry, elevation and modelled ELA, glaciers nearby 26 volcanoes were excluded from the study. To avoid including potential erroneously mapped glaciers (i.e., perennial snow patches) and glaciers that are present in specific topoclimatic niches (e.g., highly shaded or sustained by snow avalanching), glaciers smaller than 0.1 km2 were excluded from the analysis. Glaciers classified as debris-covered in the RGI, are subject to more complex surface mass balance regimes, frequently leading to increased supraglacial insulation, reduced ablation rates and modified elevation ranges were also excluded. Thirty-seven volcanoes hosting glaciers within a radius of 1 km from the volcanic centre, and which were classified in GVP as Holocene (having been active within the last ~10,000 years), were classed as ice-clad volcanoes and used in this study. These 37 ice-clad volcanoes host a total of 600 glaciers which are presented and analysed in this study: 526 proximal and 74 volcanic-glaciers. The ELAs for each of the 74 volcanic- and 526 proximal glaciers were calculated using a semi-automated GIS Toolbox. The RGI glacier outline polygons and DEMs of the glacier surfaces provide the required inputs. For the purpose of this investigation the AABR method was applied as it is the most robust technique for ELA calculation and accounts for glacier hypsometry (together with mass balance gradients). This method has a median absolute error of 65.5 m relative to field measurements. The first step in the AABR calculation involves the division of the glacier surface into contour elevation belts based on a user-specified contour interval. In this case, this parameter was set to 10 m and therefore each ELA reported in the paper has a computational accuracy of +/-5 m. The ELA of each glacier was determined with a user-defined AABR, which was here set to a globally representative median value of 1.56. Distance to volcano was simply calculated using the 'near'' in the ArcGIS spatial analyst toolbox. For each of the 37 ice-clad volcanoes analysed, we determined the mean ELA of all proximal and volcanic- glaciers and calculated the difference to obtain the [Delta]ELAmean. Fields include nearest Global Volcano Programme (GVP) name, original RGI ID; calculated area (km2); calculated ELA (metres above sea level); and distance to nearest volcano (km). Polygons and associated statistical attributes were used to analyse the effect of distance from volcano (thus, volcanic heat) on the glacier elevation.
description: 13_AVTOD_Volacanoes.shp ASTER instrument, onboard the Terra satellite, detected and measured volcanic thermal features from space for 88 Central and South American volcanoes between 2000 and 2018, and maximum temperature anomalies ({delta}Tmax).
description: * 37_GVP_Volacanoes.shp and 13_AVTOD_Volacanoes.shp It is recognised that magma vent and tectonic structures could be complex for specific volcanoes (e.g., Nevado del Huila in Colombia) and hence GVP points can underestimate the extent and exact location of volcanic activity (thus, glacio-volcanic interactions). However, a volcano by volcano (field based) analysis of the magmatic geometry and geothermal heat flux each volcano was not feasible. * 600_RGI_Glaciers.shp and 139_Remapped_Glaciers.shp RGI/GLIMS have acknowledged that an ~5% gross geometry error was observed for the Southern Andes (region 17) for RGI 6.0 glacier outlines due to the inclusion of seasonal glacier-peripheral snow and transient ice, which was misclassified as glacial ice. Our exclusion of glaciers smaller than 0.1 km2 will have removed the likelihood of including at least some erroneously mapped snow patches and seasonal ice cover. While checking and potentially re-mapping all 74 volcanic- and 526 proximal glaciers would have been unfeasible within the scope of this particular study, we attempted to correct such factors for 13 volcanoes with a record of measured thermal anomalies (analysis central to this research), for which all glaciers outlines were re-mapped by applying a semi-automated mapping process. Using this technique, we could efficiently extract glacier polygons before carrying out manual adjustments to improve alignment with the glacier margins observed on short-wave false colour composite imagery.