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Extended T-index models for glacier surface melting: a case study from Chorabari Glacier, Central Himalaya, India

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An Erratum to this article was published on 30 March 2016

Abstract

Two enhanced temperature-index (T-index) models are proposed by incorporating meteorological parameters viz. relative humidity, wind speed and net radiation. The models are an attempt to explore different climatic variables other than temperature affecting glacier surface melting. Weather data were recorded at Chorabari Glacier using an automatic weather station during the summers of 2010 (July 10 to September 10) and 2012 (June 10 to October 25). The modelled surface melt is validated against the measured point surface melting at the snout. Performance of the developed models is evaluated by comparing with basic temperature-index model and is quantified through different efficiency criteria. The results suggest that proposed models yield considerable improvement in surface melt simulation. Consequently, the study reveals that glacier surface melt depends not only on temperature but also on weather parameters viz. relative humidity, wind speed and net radiation play a significant role in glacier surface melting. This approach provides a major improvement on basic temperature-index method and offers an alternative to energy balance model.

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Acknowledgments

The authors render their thanks to the Wadia Institute of Himalayan Geology (WIHG), Dehradun for providing the facilities to carry out the research work. We would like to appreciate Faram Bhandari, Dhanveer Panwar and Pratap Singh for their support in field work and data collection. The financial support from the Department of Science and Technology (DST), New Delhi is gratefully acknowledged.

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Correspondence to Indira Karakoti.

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An erratum to this article can be found at http://dx.doi.org/10.1007/s00704-016-1780-3.

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Karakoti, I., Kesarwani, K., Mehta, M. et al. Extended T-index models for glacier surface melting: a case study from Chorabari Glacier, Central Himalaya, India. Theor Appl Climatol 126, 401–410 (2016). https://doi.org/10.1007/s00704-016-1753-6

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