Advertisement

Climate Dynamics

, Volume 53, Issue 3–4, pp 1453–1476 | Cite as

Development and testing of a subgrid glacier mass balance model for nesting in the Canadian Regional Climate Model

  • Marjorie PerroudEmail author
  • Marc Fasel
  • Shawn J. Marshall
Article

Abstract

The aim of this study is to develop and test a methodology to explicitly resolve glacier energy and mass balance in regional climate models (RCMs). There is increasing interest in the ability to represent mountain glaciers in climate models, to enable either one-way forced or fully-coupled simulations of glacier response to climate change. However, mountain glaciers are generally subgrid features (areas of less than 10 km2) occupying high elevations in complex mountain terrain, and it is important to examine whether RCM-derived meteorological fields in mountain regions are accurate enough to model glacier mass balance. We use downscaled RCM data to force a glacier model at five different sites in western North America, where long-term glacier mass balance observations allow us to evaluate different glacier modelling and climate downscaling strategies. The model runs on a pre-processed, gridded database of 100-m resolution topographic characteristics. Our reference glacier simulations use this high resolution grid to explicitly simulate glacier surface and energy balance, but this is computationally demanding. We test different mosaic approaches for subgrid characterization of the glaciers, where glaciers in an RCM grid cell are distributed over different terrain classes, similar to hydrological response units. The subgrid mosaic approach drastically increases computational efficiency without affecting mass balance simulations for the five glaciers by more than a few percent. Elevation distribution within a grid cell is the most important element of the subgrid terrain characterization; subgrid elevation bands need to be resolved to 200 m or less in order to keep seasonal mass balance biases lower than 2%. Good simulations of glacier mass balance can be achieved with glacier-specific tuning, with correlation coefficients of ~ 0.8 between modelled and measured annual glacier mass balances over the period 1995–2014. However, there are large and regionally-variable biases in the modelled meteorological fields, and we cannot achieve good results without local bias correction.

Keywords

Glacier mass balance model RCM Subgrid modelling Mosaic approach 

Notes

Acknowledgements

We thank the Natural Sciences and Engineering Research Council (NSERC) of Canada for support of the Canadian Network for Regional Climate and Weather Processes (CNRCWP). We are grateful to Katja Winger and Laxmi Sushama for providing CRCM5 driving data and including this research in CNRCWP. Additional support has been provided by the Université de Genève, University of Calgary, and the Université de Québec à Montréal. Thank you to two anonymous reviewers, whose insights greatly improved this manuscript.

References

  1. Abe-Ouchi A, Saito F, Kawamura K, Raymo ME, Okuno J, Takahashi K. Blatter H (2013) Insolation-driven 100,000-year glacial cycles and hysteresis of ice-sheet volume. Nature 500:190–193CrossRefGoogle Scholar
  2. Avissar R, Pielke RA (1989) A parameterization of heterogeneous land surfaces for atmospheric numerical models and its impact on regional meteorology. Mon Weather Rev 117:2113–2136CrossRefGoogle Scholar
  3. Bahr DB, Meier MF, Peckham SD (1997) The physical basis of glacier volume-area scaling. J Geophys Res 102:20355–20362CrossRefGoogle Scholar
  4. Brock BW, Willis IC, Sharp MJ (2000) Measurement and parameterization of albedo variations at Haut Glacier d’Arolla. Switz J Glaciol 155:675–688CrossRefGoogle Scholar
  5. Brock BW, Willis IC, Sharp MJ (2006) Measurement and parameterisation of surface roughness variations at Haut Glacier d’Arolla. J Glaciol 52:281–297.  https://doi.org/10.3189/172756506781828746 CrossRefGoogle Scholar
  6. Clarke GK, Jarosch AH, Anslow FS, Radić V. Menounos B (2015) Projected deglaciation of western Canada in 20 the twenty-first century. Nat Geosci 8(5):372–377CrossRefGoogle Scholar
  7. Collier E, Mölg T, Maussion F, Scherer D, Mayer C, Bush AGB (2013) High-resolution interactive modelling of the mountain glacier-atmosphere interface: an application over the Karakoram. Cryosphere 7(3):779–795.  https://doi.org/10.5194/tc-7-779-2013 CrossRefGoogle Scholar
  8. Crochet P, Jóhannesson T, Jónsson T, Sigurðsson O, Björnsson H, Pálsson F, Barstad I (2007) Estimating the spatial distribution of precipitation in Iceland using a linear model of orographic precipitation. J Hydrometeorol 8:1285–1306CrossRefGoogle Scholar
  9. Cuffey KM, Paterson WSB (2010) The physics of glaciers, 4th edn. Academic Press, AmsterdamGoogle Scholar
  10. Dee DP, Uppala SM, Simmons AJ et al (2011) The ERA-Interim reanalysis: configuration and performance of the data assimilation system. Q J R Meteorol Soc 137:553–597.  https://doi.org/10.1002/qj.828 CrossRefGoogle Scholar
  11. Ebrahimi S, Marshall SJ (2016) Surface energy balance sensitivity to meteorological variability on Haig Glacier, Canadian Rocky Mountains. Cryosphere 10:2799–2819CrossRefGoogle Scholar
  12. Gregory JM, Huybrechts P (2005) Ice sheet contributions to future sea-level change. Philos Trans R Soc Lond A 364(1844):1709–1732CrossRefGoogle Scholar
  13. Hernández-Díaz L, Laprise R, Sushama L, Martynov L, Winger K, Dugas B (2012) Climate simulation over CORDEX Africa domain using the fifth-generation Canadian Regional Climate Model (CRCM5). Clim Dyn 40:1415–1433.  https://doi.org/10.1007/s00382-012-1387-z CrossRefGoogle Scholar
  14. Hirose JMR, Marshall SJ (2013) Glacier meltwater contributions and glacio-meteorological regime of the Illecillewaet River Basin, British Columbia, Canada. Atmos Ocean 51:416–435.  https://doi.org/10.1080/07055900.2013.791614 CrossRefGoogle Scholar
  15. Horn BKP (1982) Hill shading and the reflectance map. Geo-Processing 2(1):65–147Google Scholar
  16. Houze RA Jr (2012) Orographic effects on precipitating clouds. Rev Geophys 50:RG1001.  https://doi.org/10.1029/2011RG000365 CrossRefGoogle Scholar
  17. Huisman O, de By RA (2009) Principles of geographic information systems. The International Institute for Geo-Information Science and Earth Observation (ITC), EnschedeGoogle Scholar
  18. Huss M, Hock R (2015) A new model for global glacier change and sea-level rise. Front Earth Sci 3:54.  https://doi.org/10.3389/feart.2015.00054 CrossRefGoogle Scholar
  19. Huss M, Hock R (2018) Global-scale hydrological response to future glacier mass loss. Nat Clim Change 8:135–140CrossRefGoogle Scholar
  20. Huss M, Bauder A, Funk M, Hock R (2008) Determination of the seasonal mass balance of four Alpine glaciers since 1865. J Geophys Res 113:F01015.  https://doi.org/10.1029/2007JF000803 CrossRefGoogle Scholar
  21. Jarosch AH, Anslow FS, Clarke GKC (2010) High-resolution precipitation and temperature downscaling for glacier models. Clim Dyn 38:391–409.  https://doi.org/10.1007/s00382-010-0949-1 CrossRefGoogle Scholar
  22. Jeong DI, Sushama L (2017) Projected changes to surface wind characteristics and extremes over North America in CRCM5. EGU General Assembly, ViennaGoogle Scholar
  23. Knight PG (1999) Glaciers. Cheltenham, Stanley ThornesGoogle Scholar
  24. Kotlarski S, Jacob D, Podzun R, Paul F (2010) Representing glaciers in a regional climate model. Clim Dyn 34:27–46.  https://doi.org/10.1007/s00382-009-0685-6 CrossRefGoogle Scholar
  25. Kumar P, Kotlarski W, Moseley C, Sieck K, Frey H, Stoffel M, Jacob D (2015) Response of Karakoram-Himalayan glaciers to climate variability and climatic change: a regional climate model assessment. Geophys Res Lett 42(6):1818–1825.  https://doi.org/10.1002/2015GL063392 CrossRefGoogle Scholar
  26. Machguth H, Paul F, Kotlarski S, Hoelzle M (2009) Calculating distributed glacier mass balance for the Swiss Alps from regional climate model output: a methodical description and interpretation of the results. J Geophys Res 114:D19106CrossRefGoogle Scholar
  27. Marshall SJ (2014) Meltwater runoff from Haig Glacier, Canadian Rocky Mountains, 2002–2013. Hydrol Earth Syst Sci 18:5181–5200.  https://doi.org/10.5194/hess-18-5181-2014 CrossRefGoogle Scholar
  28. Marzeion B, Cogley JG, Richter K, Parkes D (2014) Attribution of global glacier mass loss to anthropogenic and natural causes. Science 345:919–921.  https://doi.org/10.1126/science.1254702 CrossRefGoogle Scholar
  29. Marshall SJ, White EC, Demuth MN, Bolch T, Wheate R, Menounos B, Beedle M, Shea JM (2011) Glacier water resources on the eastern slopes of the Canadian Rocky Mountains. Can Water Resour J 36(2):109–134. ( https://doi.org/10.4296/cwrj3602823)CrossRefGoogle Scholar
  30. Maussion F, Butenko A, Eis J et al (2018) The Open Global Glacier Model (OGGM) v1.0. Geosci. Model Dev. Discuss.  https://doi.org/10.5194/gmd-2018-9
  31. Meier MF, Dyurgerov MB, Rick UK et al (2007) Glaciers dominate sea-level rise in the 21st century. Science 317(5841):1064–1067.  https://doi.org/10.1126/science.1143906 CrossRefGoogle Scholar
  32. Melton JR, Sospedra-Alfonso R, McCusker KE (2017) Tiling soil textures for terrestrial ecosystem modelling via clustering analysis: a case study with CLASS-CTEM (version 2.1). Geosci Model Dev 10:2761–2783.  https://doi.org/10.5194/gmd-10-2761-2017, 2017CrossRefGoogle Scholar
  33. Milewska EJ, Hopkinson RF, Niitsoo A (2005) Evaluation of geo-referenced grids of 1961–1990 Canadian temperature and precipitation normal. Atmos Ocean 43:49–75.  https://doi.org/10.3137/ao.430104 CrossRefGoogle Scholar
  34. Mölg T, Kaser G (2011) A new approach to resolving climate-cryosphere relations: downscaling climate dynamics to glacier-scale mass and energy balance without statistical scale linking. J Geophys Res Atmos 116:D16101.  https://doi.org/10.1029/2011JD015669 CrossRefGoogle Scholar
  35. Möller M, Obleitner F, Reijmer CH, Pohjola VA, Głowacki P, Kohler J (2016) Adjustment of regional climate model output for modeling the climatic mass balance of all glaciers on Svalbard. J Geophys Res Atmos 121(10):5411–5429.  https://doi.org/10.1002/2015JD024380 CrossRefGoogle Scholar
  36. Molod A, Salmun H (2002) A global assessment of the mosaic approach to modeling land surface heterogeneity. J Geophys Res 107:4217.  https://doi.org/10.1029/2001jd000588, 2002CrossRefGoogle Scholar
  37. Munro DS (1989) Surface roughness and bulk heat transfer on a glacier: comparison with eddy correlation. J Glaciol 35(121):343–348CrossRefGoogle Scholar
  38. National Snow and Ice Data Centre (NSIDC) (2017) Facts about glaciers. https://nsidc.org/cryosphere/glaciers/quickfacts.html. Accessed 11 Dec 2017
  39. Natural Resources Canada (2016a) Canadian Digital Elevation Model (CDEM). http://ftp.geogratis.gc.ca/pub/nrcan_rncan/elevation/cdem_mnec. Accessed 11 Dec 2017
  40. Natural Resources Canada (2016b) Canadian Digital Elevation Model Product Specifications. http://ftp.geogratis.gc.ca/pub/nrcan_rncan/elevation/cdem_mnec/doc/CDEM_product_specs.pdf. Accessed 11 Dec 2017
  41. Oksanen J, Sarjakoski T (2005) Error propagation of DEM-based surface derivatives. Comput Geosci 31(8):1015–1027.  https://doi.org/10.1016/j.cageo.2005.02.014 CrossRefGoogle Scholar
  42. Otto-Bliesner B, Marshall SJ, Overpeck JT, Miller GH, Hu G, CAPE Last Interglacial Project Members (2006) Simulating Arctic climate warmth and ice sheet retreat in the last interglaciation. Science 311: 1751–1753CrossRefGoogle Scholar
  43. Pacific Climate Impacts Consortium (2014) High-resolution PRISM climatology for British Columbia. Pacific Climate Impacts Consortium, University of Victoria, and PRISM Climate Group, Oregon State University. https://www.pacificclimate.org/data/high-resolution-prism-climatology. Accessed 11 Dec 2017
  44. Paul F, Kotlarski S (2010) Forcing a distributed glacier mass balance model with the regional climate model REMO. Part II. Downscaling strategy and results for two Swiss Glaciers. J Clim 23:1607–1620CrossRefGoogle Scholar
  45. Pfeffer WT, Arendt AA, Bliss A, Bolch T, Cogley JG, Gardner AS, Randolph C (2014) The Randolph Glacier Inventory: a globally complete inventory of glaciers. J Glaciol 60(221):537–552.  https://doi.org/10.3189/2014JoG13J176 CrossRefGoogle Scholar
  46. Pritchard MS, Bush AB, Marshall SJ (2008) Neglecting ice-atmosphere interactions underestimates ice sheet melt in millennial-scale deglaciation simulations. Geophys Res Lett 35:L01503.  https://doi.org/10.1029/2007GL031738 Google Scholar
  47. Raaflaub LD, Collins MJ (2006) The effect of error in gridded digital elevation models on the estimation of topographic parameters. Environ Model Softw 21(5):710–732.  https://doi.org/10.1016/j.envsoft.2005.02.003 CrossRefGoogle Scholar
  48. Raup B, Racoviteanu A, Khalsa SJS, Helm C, Armstrong R, Arnaud Y (2007) The GLIMS geospatial glacier database: a new tool for studying glacier change. Glob Planet Change 56(1–2):101–110.  https://doi.org/10.1016/j.gloplacha.2006.07.018 CrossRefGoogle Scholar
  49. Rogozhina I, Rau D (2014) Vital role of daily temperature variability in surface mass balance parameterizations of the Greenland ice sheet. Cryosphere 8:575–585CrossRefGoogle Scholar
  50. Samimi S, Marshall SJ (2017) Diurnal cycles of meltwater percolation, refreezing, and drainage in the supraglacial snowpack of Haig Glacier, Canadian Rocky Mountains. Front Earth Sci 5:6.  https://doi.org/10.3389/feart.2017.00006 CrossRefGoogle Scholar
  51. Sauter T, Galos SP (2016) Effects of local advection on the spatial sensible heat flux variation on a mountain glacier. Cryosphere 10:2887–2905.  https://doi.org/10.5194/tc-10-2887-2016 CrossRefGoogle Scholar
  52. Separovic L, Alexandru A, Laprise R, Martynov A, Sushama L, Winger K, Tete K, Valin M (2013) Present climate and climate change over North America as simulated by the fifth-generation Canadian regional climate model. Clim Dyn 41:3167–3201.  https://doi.org/10.1007/s00382-013-1737-5 CrossRefGoogle Scholar
  53. Shulski M, Wendler G (2007) The climate of Alaska. University of Alaska Press, FairbanksGoogle Scholar
  54. Smith RB (2003) A linear upslope-time-delay model of orographic precipitation, mountain hydrology and water resources. J Hydrol 282:2–9CrossRefGoogle Scholar
  55. Smith CD (2007) The relationship between monthly precipitation and elevation in the Alberta foothills during the foothills orographic precipitation experiment. In: Woo M (ed) Cold Region Atmospheric and Hydrologic Studies. The Mackenzie GEWEX Experience. Springer, Berlin, pp 167–185Google Scholar
  56. Smith RB, Barstad I (2004) A linear theory of orographic precipitation. J Atmos Sci 61:1377–1391CrossRefGoogle Scholar
  57. Snyder JP (1987) Map projections: a working manual. U.S. Government Printing Office. https://pubs.er.usgs.gov/publication/pp1395. Accessed 11 Dec 2017
  58. Szeto KK (2008) On the extreme variability and change of cold-season temperatures in northwest Canada. J Clim 21(2):94–113CrossRefGoogle Scholar
  59. U.S. Geological Survey (2016) 3D Elevation Program (3DEP). https://nationalmap.gov/3DEP. Accessed 11 Dec 2017
  60. Verseghy DL (1991) CLASS—a Canadian land surface scheme for GCMS. I. Soil model. Int J Climatol 11:111–113CrossRefGoogle Scholar
  61. Verseghy DL (2009) CLASS—the Canadian Land Surface Scheme (Version 3.4). Tech. Rep. Climate Research Division, Science and Technology Branch, Environment Canada, QuebecGoogle Scholar
  62. Verseghy DL, McFarlane NA, Lazare M (1993) A Canadian Land Surface Scheme for GCMs: II. Vegetation model and coupled runs. Int J Climatol 13:347–370CrossRefGoogle Scholar
  63. Vizcaino M, Lipscomb WH, Sacks WJ, Van den Broeke MR (2014) Greenland surface mass balance as simulated by the community earth system model. Part II: twenty-first-century changes. J Clim 27:215–226CrossRefGoogle Scholar
  64. Vizcaino M, Mikolajewicz U, Ziemen F, Rodehacke CB, Greve R, van den Broeke MR (2015) Coupled simulations of Greenland ice sheet and climate change up to AD 2300. Geophys Res Lett 42(10):3927–3935.  https://doi.org/10.1002/2014GL061142 CrossRefGoogle Scholar
  65. WGMS (2011) Glacier Mass Balance Bulletin No. 11 (2008–2009). Zemp M, Nussbaumer SU, Gärtner-Roer I, Hoelzle M, Paul F, Haeberli W (eds) ICSU (WDS)/IUGG (IACS)/UNEP/SCO/WMO. World Glacier Monitoring Service, ZurichGoogle Scholar
  66. WGMS (2016) Fluctuations of Glaciers Database. World Glacier Monitoring Service, Zurich (online access).  https://doi.org/10.5904/wgms-fog-2016-08
  67. Whiteman CD (2000) Mountain meteorology: fundamentals and applications. Oxford University Press, New YorkGoogle Scholar
  68. Ziemen F, Rodehacke C, Mikolajewicz U (2014) Coupled ice sheet–climate modeling under glacial and pre-industrial boundary conditions. Clim Past 10:1817–1836.  https://doi.org/10.5194/cp-10-1817-2014 CrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of GeographyUniversity of CalgaryCalgaryCanada
  2. 2.Institute for Environmental SciencesUniversity of GenevaGenevaSwitzerland

Personalised recommendations