Abstract

Abstract. Seasonal snowpack is an essential component in the hydrological cycle and plays a significant role in supplying water resources to downstream users. Yet the snow water equivalent (SWE) in seasonal snowpacks, and its space–time variation, remains highly uncertain, especially over mountainous areas with complex terrain and sparse observations, such as in High Mountain Asia (HMA). In this work, we assessed the spatiotemporal distribution of seasonal SWE, obtained from a new 18-year HMA Snow Reanalysis (HMASR) dataset, as part of the recent NASA High Mountain Asia Team (HiMAT) effort. A Bayesian snow reanalysis scheme previously developed to assimilate satellite-derived fractional snow-covered area (fSCA) products from Landsat and MODIS platforms has been applied to develop the HMASR dataset (at a spatial resolution of 16 arcsec (∼500 m) and daily temporal resolution) over the joint Landsat–MODIS period covering water years (WYs) 2000–2017. Based on the results, the HMA-wide total SWE volume is found to be around 163 km3 on average and ranges from 114 km3 (WY2001) to 227 km3 (WY2005) when assessed over 18 WYs. The most abundant snowpacks are found in the northwestern basins (e.g., Indus, Syr Darya and Amu Darya) that are mainly affected by the westerlies, accounting for around 66 % of total seasonal SWE volume. Seasonal snowpack in HMA is depicted by snow accumulating through October to March and April, typically peaking around April and depleting in July–October, with variations across basins and WYs. When examining the elevational distribution over the HMA domain, seasonal SWE volume peaks at mid-elevations (around 3500 m), with over 50 % of the volume stored above 3500 m. Above-average amounts of precipitation causes significant overall increase in SWE volumes across all elevations, while an increase in air temperature (∼1.5 K) from cooler to normal conditions leads to an redistribution in snow storage from lower elevations to mid-elevations. This work brings new insight into understanding the climatology and variability of seasonal snowpack over HMA, with the regional snow reanalysis constrained by remote-sensing data, providing a new reference dataset for future studies of seasonal snow and how it contributes to the water cycle and climate over the HMA region.

Highlights

  • The High Mountain Asia (HMA) region consists of the major mountain ranges and headwaters of the largest rivers in Asia

  • The HMA Snow Reanalysis (HMASR) dataset is designed to provide a reliable and consistent snow water equivalent (SWE) product that can be used for assessing the spatiotemporal distribution of seasonal SWE over the recent remote-sensing record

  • The non-seasonal SWE values (Fig. 3b) are expected to be unreliable because the initial conditions for SWE at those locations at the beginning of the dataset are unknown and the lack of full melt-out makes the relationship between fractional snow-covered area (fSCA) depletion and peak SWE much less direct

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Summary

Introduction

The High Mountain Asia (HMA) region consists of the major mountain ranges and headwaters of the largest rivers in Asia. The HMASR aims to fill the spatiotemporal gaps in existing SWE datasets and allow for better characterization of the distribution and changes in seasonal snow storage, as well as provide insights into the hydrologic cycle and water availability over HMA Using this dataset, the spatial distribution of SWE climatology is examined at annual and seasonal scales over the HMA region, covering the highest mountain ranges and the Tibetan Plateau in Asia. How is the amount of snow distributed across elevation, and how does it vary under different climate conditions?

Data and method
HMA domain
Snow reanalysis scheme
Input data acquisition and processing
Non-seasonal snow and ice mask
Results and discussion
Spatial distribution of seasonal SWE climatology
Peak seasonal SWE climatology
Peak seasonal SWE timing
Seasonal SWE evolution
Temporal distribution of seasonal SWE
Climatology of seasonal SWE
Interannual variations in SWE and timing
Elevational distribution of seasonal SWE
Seasonal peak SWE climatology
Variations under different climate conditions
Conclusions
Full Text
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