Contrasting glacier responses to recent climate change in high-mountain Asia

Abstract

Recent studies of Asian glaciers have shown that glaciers in eastern Karakoram and West Kunlun have been slightly gaining mass while those in nearby Jammu Kashmir and Himalayas are losing mass, at rates of more than 0.5 m w.e.yr^-1 and about 0.3 m w.e.yr^-1, respectively. Two possible explanations have been proposed for this difference in glacier behaviour: spatial heterogeneity in climate change (climatic forcing) or differing glacier responses to climate change (glacier response). However, neither explanation has strong supporting evidence. Here, we examine the glacial response by calculating the mass-balance sensitivity to temperature change in high-mountain Asia. In support of the glacier-response explanation, we find a strong correlation between observed glacier surface-elevation changes and mass-balance sensitivity of glaciers. The high coefficient of determination (R² = 0.61) suggests that spatially heterogeneous mass-balance sensitivity has more explanatory power than regionally different climate change for the recent contrasting glacier fluctuations in the high mountain Asia.

Figure 1

Trends in elevation change (TECs) and mass-balance sensitivity to air temperature change over high-mountain Asia (HMA). (a) TECs for glaciers along the Pamir-Karakoram-Himalaya for 2003–2008 modified from Kääb et al.. Ref. is licensed under a Creative Commons Attribution 3.0 Unported License (https://creativecommons.org/licenses/by/3.0/). (b) TECs for glaciers in HMA for 2003–2009 modified from Gardner et al., Science 340: 6134 (2013). Reprinted with permission from AAAS. Black square indicates data with high overlapping ratios (>0.8, see Methods). (c) Calculated mass-balance sensitivity (MBS) to temperature change. TEC values were calculated from ICESat and SRTM data. Original TEC data from ref. is the spatial average of a minimum of 50 TEC observations within a 50-km radius. All data are on a 1° grid, each point is the average over 2° cells (see Methods). These figures were created using The Generic Mapping Tools (http://gmt.soest.hawaii.edu/), Version 5.1.0. and were edited using Adobe Illustrator CS6 Version 16.0.0.

Figure 2

Relationship between the sensitivity of mass balance to temperature change and changes in TECs for glaciers^,. Vertical error bars indicate the standard error calculated in ref., horizontal error bars indicate the standard deviation calculated from averaging each 0.5° grid point in the MBS calculation over a 2° area. There are three different TECs: Kääb et al., Gardner et al. with high overlapping ratios (>0.8), and Gardner et al. for all of HMA. Equations for regression lines and statistics are summarized in Table S1.

Figure 3

Distributions and boundaries of explanatory variables for multi-regression analysis and area boundaries for each explanatory variable with a weaker MBS. (a) The area with summer temperatures <0 °C is encompassed with a light blue line. (b) The areas with an annual range in monthly temperature >20 °C is encompassed with an orange line. (c) The area with a summer precipitation ratio of <50% is encompassed with a purple line. (d) MBS distribution showing overlapping areas of lower summer temperature (<0 °C), higher temperature ranges (>20 °C) and lower summer precipitation ratio (<50%) with a black dashed line. a-c are depicted based on a 0.5° grid cell. Each threshold for explanatory variables is provided in Fig. S6, which indicates that each threshold divides the MBS values such that half are less negative (weaker) and half are more negative (stronger). These figures were created using The Generic Mapping Tools (http://gmt.soest.hawaii.edu/), Version 5.1.0. and were edited using Adobe Illustrator CS6 Version 16.0.0.