Neural networks applied to estimating subglacial topography and glacier volume

Journal of Climate

Volumn 22, Issue 8, 2009, Pages 2146-2160

  Clarke, Garry K C ^a   Berthier, Etienne ^b,c   Schoof, Christian G ^a   Jarosch, Alexander H ^a  

^a UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^b UNIVERSITÉ DE TOULOUSE   (France)

^c CNRS   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ARTIFICIAL NEURAL NETWORK; DIGITAL ELEVATION MODEL; ESTIMATION SKILL; GLACIER ICE; ICE COVER; ICE DYNAMICS; ICE THICKNESS; ICE VOLUMES; ICE-CAPS; MOUNTAIN GLACIERS; REGIONS OF INTEREST; SCALE MODELS;

BACKPROPAGATION; ENGINEERING GEOLOGY; ESTIMATION; GEOMORPHOLOGY; GLACIAL GEOLOGY; GLACIERS; KNOWLEDGE BASED SYSTEMS; LANDFORMS; NEURAL NETWORKS; SURVEYING;

ICE;

ARTIFICIAL NEURAL NETWORK; DIGITAL ELEVATION MODEL; GLACIATION; ICE CAP; ICE COVER; ICE THICKNESS; NUMERICAL MODEL; SUBGLACIAL ENVIRONMENT;

EID: 66849095911     PISSN: 08948755     EISSN: None     Source Type: Journal    
DOI: 10.1175/2008JCLI2572.1     Document Type: Article

References (34)

1. Bahr, D. B., 1997: Global distributions of glacier properties: A stochastic scaling paradigm. Water Resour. Res., 33, 1669-1679.
2. Bahr, D. B., M. F. Meier, and S. D. Peckham, 1997: The physical basis of glacier volume-area scaling. J. Geophys. Res., 102, 20 355-20 362.
3. Bishop, C. M., 1995: Neural Networks for Pattern Recognition. Oxford University Press, 482 pp.
4. Björnsson, H., 1986: Surface and bedrock topography of ice caps in Iceland mapped by radio echo soundings. Ann. Glaciol., 8, 11-18.
5. Cavazos, T., 2000: Using self-organizing maps to investigate extreme climate events: An application to wintertime precipitation in the Balkans. J. Climate, 13, 1718-1732.
6. Chen, J., and A. Ohmura, 1990: Estimation of Alpine glacier water resources and their change since 1870s. Hydrology in Mountainous Regions I, IAHS Publication 193, 127-135.
7. Demuth, H., M. Beale, and M. Hagan, 2006: Neural network toolbox user's guide. The Math Works, Inc., 452 pp.
8. Driedger, C., and P. Kennard, 1986: Glacier volume estimation on Cascade volcanoes - An analysis and comparison with other methods. Ann. Glaciol., 8, 59-64.
9. 2-Induced Climatic Change, National Academy Press, 216-231.
10. Haeberli, W., and M. Hoelzle, 1995: Application of inventory data for estimating characteristics of and regional climate-change effects on mountain glaciers: A pilot study with the European Alps. Ann. Glaciol., 21, 206-212.
11. Hewitson, B. C., and R. G. Crane, 2002: Self-organizing maps: Application to synoptic climatology. Climate Res., 22, 13-26.
12. Hsieh, W. W., 2001: Nonlinear canonical correlation analysis of the tropical Pacific climate variability using a neural network approach. J. Climate, 14, 2528-2539.
13. Huss, M., D. Farinotti, A. Bauder, and M. Funk, 2008: Modelling runoff from highly glacierized alpine drainage basins in a changing climate. Hydrol. Proc., 22, 3888-3902.
14. Hutter, K., 1983: Theoretical Glaciology. D. Reidel Publishing Company, 510 pp.
15. Kessler, M. A., R. S. Anderson, and G. M. Stock, 2006: Modeling topographic and climatic control of east-west asymmetry in Sierra Nevada glacier length during the Last Glacial Maximum. J. Geophys. Res., 111, F02002, doi:10.1029/2005JF000365.
16. Kohonen, T., 2001: Self-Organizing Maps. 3rd ed. Springer-Verlag, 501 pp.
17. Lemke, P., and Coauthors, 2007: Observations: Changes in snow, ice and frozen ground. Climate Change 2007: The Physical Basis, S. Solomon et al., Eds., Cambridge University Press, 337-383.
18. Levenberg, K., 1944: A method for the solution of certain nonlinear problems in least squares. Quart Appl. Math., 2, 164-168.
19. Marquardt, D. W., 1963: An algorithm for least squares estimation of nonlinear parameters. SIAM J. Appl. Math., 11, 431-441.
20. Meier, M. F., M. B. Dyurgerov, U. K. Rick, S. O'Neel, W. T. Pfeffer, R. S. Anderson, S. P. Anderson, and A. F. Glazovsky, 2007: Glaciers dominate eustatic sea-level rise in the 21st century. Science, 317, 1064-1067.
21. Monahan, A. H., 2000: Nonlinear principal component analysis of neural networks: Theory and application to the Lorenz system. J. Climate, 13, 821-835.
22. Nye, J. F., 1952: A comparison between the theoretical and measured long profile of the Unteraar Glacier. J. Glaciol., 2, 103-107.
23. Ohmura, A., 2004: Cryosphere during the twentieth century. The State of the Planet: Frontiers and Challenges in Geophysics, Geophys.Monogr., Vol. 150, Amer. Geophys. Union, 239-257.
24. Paterson, W. S. B., 1999: The Physics of Glaciers. 3rd ed. Butterworth-Heinemann, 496 pp.
25. Plummer, M. A., and F. M. Phillips, 2003: A 2-D numerical model of snow/ ice energy balance and ice flow for paleoclimatic interpretation of glacial geomorphic features. Quat. Sci. Rev., 22, 1389-1406.
26. Reed, R. D., and R. J. Marks II, 1999: Neural Smithing: Supervised Learning in Feedforward Artificial Neural Networks. MIT Press, 358 pp.
27. Reusch, D. B., and R. B. Alley, 2007: Antarctic sea ice: A self-organizing map-based perspective. Ann. Glaciol., 46, 391-396.
28. Reusch, D. B., B. C. Hewitson, and R. B. Alley, 2005: Towards ice-core-based synoptic reconstructions of West Antarctic climate with artificial neural networks. Int. J. Climatol., 25, 581-610.
29. Steiner, D., A. Walter, and H. J. Zumbühl, 2005: The application of a non-linear back-propagation neural network to study the mass balance of Grosse Aletschgletscher, Switzerland. J. Glaciol., 51, 313-323.
30. Steiner, D., A. Pauling, S. U. Nussbaumer, A. Nesje, J. Luterbacher, H. Wanner, and H. J. Zumbühl, 2008: Sensitivity of European glaciers to precipitation and temperature - Two case studies. Climatic Change, 90, 413-441, doi:10.1007/s10584-008-9393-1.
31. Tang, Y., and W. W. Hsieh, 2001: Coupling neural networks to incomplete dynamical systems via variational data assimilation. Mon. Wea. Rev., 129, 818-834.
32. Tangang, F. T., W. W. Hsieh, and B. Tang, 1998a: Forecasting regional sea surface temperatures in the tropical Pacific by neural network models, with wind stress and sea level pressure as predictors. J. Geophys. Res., 103, 7511-7522.
33. Tangang, F. T., B. Tang, A. H. Monahan, and W. W. Hsieh, 1998b: Forecasting ENSO events: A neural network-extended EOF approach. J. Climate, 11, 29-41.
34. Zumbühl, H. J., D. Steiner, and S. U. Nussbaumer, 2008: 19th century glacier representations and fluctuations in the central and western European Alps: An interdisciplinary approach. Global Planet. Change, 60, 42-57.