Journal article

Global glacier volume projections under high-end climate change scenarios

  • Shannon, Sarah School of Geography, University of Exeter, The Queen's Drive, Exeter, UK - Bristol Glaciology Centre, Department of Geographical Science, University Road, University of Bristol, UK
  • Smith, Robin NCAS-Climate, Department of Meteorology, University of Reading, Reading, UK
  • Wiltshire, Andy Met Office, Exeter, Devon, UK
  • Payne, Tony Bristol Glaciology Centre, Department of Geographical Science, University Road, University of Bristol, UK
  • Huss, Matthias Department of Geosciences, University of Fribourg, Switzerland - Laboratory of Hydraulics, Hydrology and Glaciology, ETH Zurich, Switzerland
  • Betts, Richard School of Geography, University of Exeter, The Queen's Drive, Exeter, UK - Met Office, Exeter, Devon, UK
  • Caesar, John Met Office, Exeter, Devon, UK
  • Koutroulis, Aris School of Environmental Engineering, Technical University of Crete, Chania, Greece
  • Jones, Darren University of Exeter, Penryn Campus, Penryn, Cornwall, UK
  • Harrison, Stephan University of Exeter, Penryn Campus, Penryn, Cornwall, UK
Show more…
    01.02.2019
Published in:
  • The Cryosphere. - 2019, vol. 13, no. 1, p. 325–350
English The Paris agreement aims to hold global warming to well below 2 ∘C and to pursue efforts to limit it to 1.5 ∘C relative to the pre-industrial period. Recent estimates based on population growth and intended carbon emissions from participant countries suggest global warming may exceed this ambitious target. Here we present glacier volume projections for the end of this century, under a range of high-end climate change scenarios, defined as exceeding +2 ∘C global average warming relative to the pre-industrial period. Glacier volume is modelled by developing an elevation- dependent mass balance model for the Joint UK Land Environment Simulator (JULES). To do this, we modify JULES to include glaciated and unglaciated surfaces that can exist at multiple heights within a single grid box. Present-day mass balance is calibrated by tuning albedo, wind speed, precipitation, and temperature lapse rates to obtain the best agreement with observed mass balance profiles. JULES is forced with an ensemble of six Coupled Model Intercomparison Project Phase 5 (CMIP5) models, which were downscaled using the high-resolution HadGEM3-A atmosphere-only global climate model. The CMIP5 models use the RCP8.5 climate change scenario and were selected on the criteria of passing 2 ∘C global average warming during this century. The ensemble mean volume loss at the end of the century plus or minus 1 standard deviation is −64±5 % for all glaciers excluding those on the peripheral of the Antarctic ice sheet. The uncertainty in the multi-model mean is rather small and caused by the sensitivity of HadGEM3-A to the boundary conditions supplied by the CMIP5 models. The regions which lose more than 75 % of their initial volume by the end of the century are Alaska, western Canada and the US, Iceland, Scandinavia, the Russian Arctic, central Europe, Caucasus, high-mountain Asia, low latitudes, southern Andes, and New Zealand. The ensemble mean ice loss expressed in sea level equivalent contribution is 215.2±21.3 mm. The largest contributors to sea level rise are Alaska (44.6±1.1 mm), Arctic Canada north and south (34.9±3.0 mm), the Russian Arctic (33.3±4.8 mm), Greenland (20.1±4.4), high-mountain Asia (combined central Asia, South Asia east and west), (18.0±0.8 mm), southern Andes (14.4±0.1 mm), and Svalbard (17.0±4.6 mm). Including parametric uncertainty in the calibrated mass balance parameters gives an upper bound global volume loss of 281.1 mm of sea level equivalent by the end of the century. Such large ice losses will have inevitable consequences for sea level rise and for water supply in glacier-fed river systems.
Faculty
Faculté des sciences et de médecine
Department
Département de Géosciences
Language
  • English
Classification
Hydrology
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/307551
Statistics

Document views: 9 File downloads:
  • hus_ggv.pdf: 1