Trends in Snow Cover Duration Across River Basins in High Mountain Asia From Daily Gap-Filled MODIS Fractional Snow Covered Area

Abstract

High Mountain Asia (HMA) has the largest expanse of snow outside of the polar regions and it plays a critical role in climate and hydrology. In situ monitoring is rare due to terrain complexity and inaccessibility, making remote sensing the most practical way to understand snow patterns in HMA despite relatively short periods of record. Here, trends in snow cover duration were assessed using MODIS between 2002 and 2017 across the headwaters of the region’s primary river basins (Amu Darya, Brahmaputra, Ganges, Indus, and Syr Darya). Data limitations, associated with traditional binary mapping and data gaps due to clouds, were addressed with a daily, spatially and temporally complete, snow cover product that maps the fraction of snow in each pixel using spectral mixture analysis. Trends in fractional snow cover duration (fSCD) were calculated at the annual and monthly scale, and across 1,000 m elevation bands, and compared to trends in binary snow cover duration (SCD). Snow cover is present, on average, for 102 days across all basin headwaters, with the longest duration in western basins and shortest in eastern basins. Broadly, snow cover is in decline, which is most pronounced in elevation bands where snow is most likely to be present and most needed to sustain glaciers. Some of the strongest negative trends in fSCD were in the Syr Darya, which has 13 fewer days between 4,000–5,000 m, and Brahmaputra, which has 31 fewer days between 5,000–6,000 m. The only increasing tendency was found in the Indus between 2,000 and 5,000 m. There were differences between fSCD and SCD trends, due to SCD overestimating snow cover area relative to fSCD.

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

“…The resulting significant negative trends at grid scale were most pronounced in the Ganges and Brahmaputra river basins during the monsoon and post-monsoon season. At basin scale, the general direction of previously reported trends and insignificant tendencies appeared to continue (Ackroyd et al, 2021;Gurung et al, 2017;Wang et al, 2017). However, ancillary trend analysis indicated that during the first part of the study period (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012), trends and tendencies in SCA were rather negative at annual scale, whereas the second period (2010-2020) resulted in positive tendencies (Table S4).…”

“…In this regard, seasonal trends of SCA were analyzed between December 2002 and November 2020 at grid scale, which remained understudied so far. Recent studies generally focused on annual trends and study periods until 2017 (Ackroyd et al, 2021;Desinayak et al, 2022) and 2018 (Notarnicola, 2020). In detail, the results of this study pointed towards partially significant decreasing and increasing trends at seasonal scale (Figure 5c), whereas trends at basin scale were mostly insignificant indicating that SCA remained stable (Table 2).…”

“…During the pre-monsoon season, the trends were significantly positive in both basins (Figure 4c). In comparison, Ackroyd et al (2021) analyzed trends in fractional snow cover duration in High Mountain Asia for elevation zones as well. They used MODIS data for the period 2002−2017.…”

Multi-faceted analyses of seasonal trends and drivers of land surface variables in Indo-Gangetic river basins

“…The identified significant decreasing trends at grid scale are most pronounced in the Ganges and Brahmaputra river basins during the monsoon and post-monsoon season. At basin scale, the general direction of previously reported trends and insignificant tendencies appear to continue (Ackroyd et al, 2021;Gurung et al, 2017;Wang et al, 2017). In fact, ancillary trend analysis indicates that during the first part of the study period (2002)(2003)(2004)(2005)(2006)(2007)(2008)(2009)(2010)(2011)(2012) trends and tendencies in SCA are rather negative at annual scale, whereas the second period (2010-2020) resulted in positive tendencies (Table S3).…”

Development of Global Snow Cover—Trends from 23 Years of Global SnowPack

“…The MODIS snow products [14] have a long history in analysis of snow cover dynamics worldwide. The areas of application range from spatially limited areas such as the Himalayas [15] or the Andes [16,17] to global investigations such as albedo analysis [18]. Sensor fusion methods are also used to increase time series by combining MODIS data with AVHRR [19].…”