An improved Terra–Aqua MODIS snow cover and Randolph Glacier Inventory 6.0 combined product (MOYDGL06*) for high-mountain Asia between 2002 and 2018

摘要

Snow is a significant component of the ecosystem andwater resources in high-mountain Asia (HMA). Therefore, accurate,continuous, and long-term snow monitoring is indispensable for the waterresources management and economic development. The present study improves theModerate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites8 d (“d” denotes “day”) composite snow cover Collection 6 (C6) products, named MOD10A2.006 (Terra) andMYD10A2.006 (Aqua), for HMA with a multistep approach. The primarypurpose of this study was to reduce uncertainty in the Terra–Aqua MODIS snow cover products and generate a combined snow cover product. For reducingunderestimation mainly caused by cloud cover, we used seasonal, temporal,and spatial filters. For reducing overestimation caused by MODIS sensors, wecombined Terra and Aqua MODIS snow cover products, considering snow only if apixel represents snow in both the products; otherwise it is classified as no snow, unlike some previousstudies which consider snow if any of the Terra or Aqua product identifies snow. Ourmethodology generates a new product which removes a significant amount ofuncertainty in Terra and Aqua MODIS 8 d composite C6 products comprising46 % overestimation and 3.66 % underestimation, mainly caused by sensorlimitations and cloud cover, respectively. The results were validated usingLandsat 8 data, both for winter and summer at 20well-distributed sites in the study area. Our validated adopted methodologyimproved accuracy by 10 % on average, compared to Landsat data. The final product covers the period from 2002 to 2018, comprising acombination of snow and glaciers created by merging Randolph GlacierInventory version 6.0 (RGI 6.0) separated as debris-coveredand debris-free with the final snow product MOYDGL06*. We haveprocessed approximately 746 images of both Terra andAqua MODIS snow containing approximately 100 000 satelliteindividual images. Furthermore, this product can serve as a valuableinput dataset for hydrological and glaciological modelling to assess the meltcontribution of snow-covered areas. The data, whichcan be used in various climatological and water-related studies, are available for end users at https://doi.org/10.1594/PANGAEA.901821 (Muhammadand Thapa,?2019).