Testing the Area-Altitude Balance Ratio (AABR) and Accumulation Area Ratio (AAR) methods of calculating glacier equilibrium-line altitudes

Rachel P. Oien* (Corresponding Author), Brice Rea, Matteo Spagnolo, Iestyn D. Barr, Robert G. Bingham

*Corresponding author for this work

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In this study, we compare equilibrium-line altitudes (ELAs) calculated using the Area-Altitude Balance Ratio (AABR) and the Accumulation-Area Ratio (AAR) methods, with measured ELAs derived from direct field observations. We utilise a GIS toolbox to calculate the ELA for 64 extant glaciers by applying the AABR and AAR methods to digital elevation models (DEMs) and polygons of their geometry. The calculated ELAs are then compared to measured zero-net balance ELAs obtained from mass balance time series held by the WGMS for the same glaciers. The correlation between zero-net balance ELAs and AABR (1.56)/AAR (0.58) calculated ELAs is very strong, with an R2 25 = 0.99. The smallest median difference between zero-net balance ELAs and calculated ELAs (i.e., 65.5 m) is obtained when a globally representative AABR of 1.56 is used. When applied to palaeoglacier-climate applications, this difference translates to ~0.42˚C, well within the uncertainty of palaeotemperature proxies used to determine mean summer temperature at the ELA. The more widely used mean AABR of 1.75 is shown to be statistically invalid due to skewness of the dataset. On this basis, when calculating glacier ELAs, we recommend the use of a global AABR value of 1.56.
Original languageEnglish
Pages (from-to)357-368
Number of pages12
JournalJournal of Glaciology
Issue number268
Early online date21 Sept 2021
Publication statusPublished - 1 Apr 2022

Bibliographical note


The Scottish Alliance for Geoscience Environment and Society (SAGES) and the University of Aberdeen are thanked for funding the PhD studentship awarded to Rachel P. Oien. The scientists who have over the years provided data to the WGMS and GLIMS are gratefully acknowledged, as are the USGS and NVE. Additionally, we would like to thank Dr. Dmitri Mauquoy for assistance regarding the statistical analyses used above. All data used in this publication publicly available.

Open access via CUP agreement.

Data Availability Statement

Data Availability
ASTER GDEM is a product of METI and NASA (ASTER GDEM Version 2: Accessed July 2019) (https://asterweb.jpl.nasa.gov/gdem.asp). GLIMS and NSIDC (2005, updated 2018): Global Land Ice Measurements from Space glacier database. Compiled and made available by the international GLIMS community and the National Snow and Ice Data Center, Boulder CO, USA. DOI: 10.7265/N5V98602 (http://www.glims.org/MapsAndDocs/ftp.html; https://www.glims.org/maps/glims). Farr, T. G. and others (2007), The Shuttle Radar Topography Mission, Rev. Geophys., 45, RG2004, doi:10.1029/2005RG000183 (https://www2.jpl.nasa.gov/srtm/). WGMS (2017): Global Glacier Change Bulletin No. 2 (2014–2015). Zemp, M., Nussbaumer, S.U., Gärtner-Roer, I., Huber, J., Machguth, H., Paul, F. and Hoelzle, M. (eds.), ICSU(WDS)/IUGG(IACS)/UNEP/UNESCO/WMO, World Glacier Monitoring Service, Zurich, Switzerland, 244 pp. Based on database version: doi: 10.5904/wgms-fog-2018-11 (https://wgms.ch/data_databaseversions/). WGMS, and National Snow and Ice Data Center (comps.). 1999, updated 2012. World Glacier Inventory, Version 1. [2018]. Boulder, Colorado USA. NSIDC: National Snow and Ice Data Center. doi: https://doi.org/10.7265/N5/NSIDC-WGI-2012-02 (January 2019) (https://nsidc.org/data/G01130/versions/1).


  • ELA
  • GIS tool
  • AABR
  • AAR
  • paleoclimate


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