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A modelling approach to reconstruct Little Ice Age climate from remote-sensing glacier observations in southeastern Tibet

Published online by Cambridge University Press:  03 March 2016

Eva Huintjes*
Affiliation:
Department of Geography, RWTH Aachen University, Aachen, Germany
David Loibl
Affiliation:
Department of Geography, RWTH Aachen University, Aachen, Germany
Frank Lehmkuhl
Affiliation:
Department of Geography, RWTH Aachen University, Aachen, Germany
Christoph Schneider
Affiliation:
Department of Geography, RWTH Aachen University, Aachen, Germany
*
Correspondence: Eva Huintjes <eva.huintjes@geo.rwth-aachen.de>
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Abstract

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We use numerical modelling of glacier mass balance combined with recent and past glacier extents to obtain information on Little Ice Age (LIA) climate in southeastern Tibet. We choose two glaciers that have been analysed in a previous study of equilibrium-line altitudes (ELA) and LIA glacier advances with remote-sensing approaches. We apply a physically based surface energy- and mass-balance model that is forced by dynamically downscaled global analysis data. The model is applied to two glacier stages mapped from satellite imagery, modern (1999) and LIA. Precipitation scaling factors (PSF) and air temperature offsets (ATO) are applied to reproduce recent ELA and glacier mass balance (MB) during the LIA. A sensitivity analysis is performed by applying seasonally varying gradients of precipitation and air temperature. The calculated glacier-wide MB estimate for the period 2000–12 is negative for both glaciers (–992±366 kgm–2 a–1 and –1053±258 kgm–2 a–1). Relating recent and LIA PSF/ATO sets suggests a LIA climate with ~8–25% increased precipitation and ~1–2.5°C lower mean air temperature than in the period 2000–12. The results only provide an order of magnitude because deviations in other input parameters are not considered.

Type
Paper
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s) 2016

Footnotes

*

Present address: Department of Geography, Humboldt Universität zu Berlin, Berlin, Germany.

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