Assessing Multi-Temporal Snow-Volume Trends in High Mountain Asia From 1987 to 2016 Using High-Resolution Passive Microwave Data

Taylor Smith,Bodo Bookhagen

doi:10.3389/feart.2020.559175

Abstract

High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987–2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987–1997, to much more positive trends across large regions of HMA during the periods 1997–2007 and 2007–2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.

Highlights

Rivers draining from High Mountain Asia (HMA) are relied upon by more than a billion people for agriculture, hydropower, and household use (Immerzeel et al, 2010; Bolch et al, 2012; Vaughan et al, 2013)
It is clear that snow-water equivalent (SWE) trends are spatially diverse—positive SWE trends are concentrated in the Karakoram, Pamir, Kunlun Shan, and the high Himalaya (Figures 3 and 4A–D)
We cannot rule out the impacts of both natural seasonality and regional temperature changes on snow densities, which could modify passive microwave SWE estimates over the course of our time series, and are part of the trends that we present as changes in SWE in this study (Judson and Doesken, 2000; Chen et al, 2011; Dai et al, 2012)

Summary

Introduction

Rivers draining from High Mountain Asia (HMA) are relied upon by more than a billion people for agriculture, hydropower, and household use (Immerzeel et al, 2010; Bolch et al, 2012; Vaughan et al, 2013). In-depth analyses of changes in HMA’s cryosphere are often limited by lack of insitu data and rugged terrain which hinders high-resolution data collection (Bookhagen and Burbank, 2010); estimates of climate trends from in-situ, satellite, and modeled data often result in heterogeneous and complex spatial patterns (Smith and Bookhagen, 2018). Passive microwave data have long provided the best global dataset for studying snow depth and snow-water storage (Chang et al, 1982). They are limited by spatial resolution—data are typically available as 0.25° × 0.25° (∼25 km × 25 km) grid cells which hinders many analyses. The enhanced resolution of this dataset allows us to more closely examine spatio-temporal trends in snow-water storage which have previously been shown to have strong impacts on climate and glacier dynamics in the region (Zhao and Moore, 2004; Fujita and Nuimura, 2011; Kapnick et al, 2014; Smith and Bookhagen, 2018)

Results

Discussion

Conclusion