Abstract

Abstract. High Mountain Asia (HMA) – encompassing the Tibetan Plateau and surrounding mountain ranges – is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications – such as agriculture, drinking-water generation, and hydropower – rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season – defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3–5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade−1 over the 29-year study period (5–25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002–2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers – such as the Karakoram and Kunlun Shan – see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.

Highlights

  • More than a billion people across Asia rely directly or indirectly on water sourced from melting snow in High Mountain Asia (HMA) (Bookhagen and Burbank, 2010; Bolch et al, 2012; Kääb et al, 2012; Kang et al, 2010; Immerzeel et al, 2010; Gardner et al, 2013; Hewitt, 2005; Malik et al, 2016).Published by Copernicus Publications on behalf of the European Geosciences Union.T

  • We find the lowest SD for the end of melt, which is to be expected given that the end of snowmelt is determined by both snow clearance and the Tb37V signal and is more tightly constrained than the MXPGR date

  • The last year of data shows a mismatch between the algorithm and control datasets, where it is difficult to determine the best candidate for the MXPGR

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Summary

Introduction

T. Smith et al.: Spatiotemporal patterns of High Mountain Asia’s snowmelt season. Many catchments receive the majority of their yearly water budget in the form of snow – at high elevations (Barnett et al, 2005). Both the volume of snowfall and the timing of snowmelt play crucial roles in the efficacy of water provision for downstream users, as many applications – such as agriculture and hydropower – rely on consistent and predictable water availability. Any changes in the onset, length, or intensity of the snowmelt season will impact the water security of both high-elevation and downstream communities

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