Long-term (${\sim}$40 years) mass balance appraisal and response of the Patsio glacier, in the Great Himalayan region towards climate change
ANANT KUMAR H S NEGI KAMAL KUMAR
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Comprehensive assessment of the long-term mass balance (40 years) has been performed for Patsio glacier located in Bhaga river basin in the Great Himalayan region. The temperature-index approach has been employed for generating the time-series of annual specific mass balance of 25 years (1993–2018) using Snow and Avalanche Study Establishment (SASE) field observatory data in Patsio region. Results based on observational data showed nearly balanced condition until the year 1999 (+0.03 m.w.e/yr), followed by an accelerated rate of mass loss during the period 2000–2007 (−0.17 m.w.e./yr). This was evident due to the annual rise (+0.7$^{\circ}$C) in the temperature and drop (−122 mm) in the amount of precipitation during 2000–2007. A slight drop in the mass balance (−0.14 m.w.e/yr) was observed during the past decade (2008–2018) which was well supported by in-situ climate observations and published geodetic results in the region. The altitudinal distribution of modelled mass balance was observed well in correlation with the glaciological measurements for the periods 2010–2011 and 2011–2012. Further, seasonal sensitivity characteristic (SSC) was developed for the glacier illustrating the dependence of specific mass balance on monthly anomalies in temperature and precipitation. The developed SSC was used with bias-corrected temperature and precipitation estimates from recently released ERA5 reanalysis to reconstruct annual specific mass balance during since 1979s.
$\bf{Highlights}$
$\bullet$ Field based temperature lapse rate, precipitation gradient and snow melt factor established for the Patsio glacier.
$\bullet$ Seasonal sensitivity of the glacier mass balance was studied.
$\bullet$ Past reconstruction of the glacier mass balance using bias corrected ERA5 reanalysis.
$\bullet$ Comparison of modeled mass balance with published geodetic and glaciological results.
ANANT KUMAR1 2 H S NEGI1 KAMAL KUMAR2
Volume 132, 2023
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