TY - JOUR
T1 - Using climate reanalysis data in conjunction with multi-temporal satellite thermal imagery to derive supraglacial debris thickness changes from energy balance modelling
AU - Stewart, Rebecca
AU - Westoby, Matt
AU - Pellicciotti, Francesca
AU - Rowan, Ann V.
AU - Swift, Darrel
AU - Brock, Benjamin
AU - Woodward, John
N1 - Funding information: We thank NASA's LP DAAC for ASTER G-DEM-2 imagery, and USGS for Landsat 7 surface brightness products. The meteorological dataset for Khumbu Glacier used in this study was collected within the framework of the Ev-K2-CNR Project in collaboration with the Nepal Academy of Science and Technology as foreseen by the Memorandum of Understanding between Nepal and Italy, and thanks to the contributions from the Italian National Research Council, the Italian Ministry of Education, University and Research and the Italian Ministry of Foreign Affairs. FP acknowledges funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme grant agreement No 772751. F.P. and M.W. additionally acknowledge funding from the Natural Environment Research Council (NERC) via Research Grant NE/S013296/1. Finally, we thank Associate Chief Editor Hester Jiskoot, Scientific Editor Nicolas Cullen and two anonymous reviewers whose insightful comments and suggestions vastly improved the manuscript.
PY - 2021/4/1
Y1 - 2021/4/1
N2 - Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.
AB - Surface energy-balance models are commonly used in conjunction with satellite thermal imagery to estimate supraglacial debris thickness. Removing the need for local meteorological data in the debris thickness estimation workflow could improve the versatility and spatiotemporal application of debris thickness estimation. We evaluate the use of regional reanalysis data to derive debris thickness for two mountain glaciers using a surface energy-balance model. Results forced using ERA-5 agree with AWS-derived estimates to within 0.01 ± 0.05 m for Miage Glacier, Italy, and 0.01 ± 0.02 m for Khumbu Glacier, Nepal. ERA-5 data were then used to estimate spatiotemporal changes in debris thickness over a ~20-year period for Miage Glacier, Khumbu Glacier and Haut Glacier d'Arolla, Switzerland. We observe significant increases in debris thickness at the terminus for Haut Glacier d'Arolla and at the margins of the expanding debris cover at all glaciers. While simulated debris thickness was underestimated compared to point measurements in areas of thick debris, our approach can reconstruct glacier-scale debris thickness distribution and its temporal evolution over multiple decades. We find significant changes in debris thickness over areas of thin debris, areas susceptible to high ablation rates, where current knowledge of debris evolution is limited.
KW - Debris-covered glaciers
KW - energy balance
KW - supraglacial debris
UR - http://www.scopus.com/inward/record.url?scp=85099974751&partnerID=8YFLogxK
U2 - 10.1017/jog.2020.111
DO - 10.1017/jog.2020.111
M3 - Article
AN - SCOPUS:85099974751
SN - 0022-1430
VL - 67
SP - 366
EP - 384
JO - Journal of Glaciology
JF - Journal of Glaciology
IS - 262
ER -