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

Abstract

Abstract. Snow is a significant component of the ecosystem and water resources in high-mountain Asia (HMA). Therefore, accurate, continuous, and long-term snow monitoring is indispensable for the water resources management and economic development. The present study improves the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites 8 d (“d” denotes “day”) composite snow cover Collection 6 (C6) products, named MOD10A2.006 (Terra) and MYD10A2.006 (Aqua), for HMA with a multistep approach. The primary purpose of this study was to reduce uncertainty in the Terra–Aqua MODIS snow cover products and generate a combined snow cover product. For reducing underestimation mainly caused by cloud cover, we used seasonal, temporal, and spatial filters. For reducing overestimation caused by MODIS sensors, we combined Terra and Aqua MODIS snow cover products, considering snow only if a pixel represents snow in both the products; otherwise it is classified as no snow, unlike some previous studies which consider snow if any of the Terra or Aqua product identifies snow. Our methodology generates a new product which removes a significant amount of uncertainty in Terra and Aqua MODIS 8 d composite C6 products comprising 46 % overestimation and 3.66 % underestimation, mainly caused by sensor limitations and cloud cover, respectively. The results were validated using Landsat 8 data, both for winter and summer at 20 well-distributed sites in the study area. Our validated adopted methodology improved accuracy by 10 % on average, compared to Landsat data. The final product covers the period from 2002 to 2018, comprising a combination of snow and glaciers created by merging Randolph Glacier Inventory version 6.0 (RGI 6.0) separated as debris-covered and debris-free with the final snow product MOYDGL06*. We have processed approximately 746 images of both Terra and Aqua MODIS snow containing approximately 100 000 satellite individual images. Furthermore, this product can serve as a valuable input dataset for hydrological and glaciological modelling to assess the melt contribution of snow-covered areas. The data, which can be used in various climatological and water-related studies, are available for end users at https://doi.org/10.1594/PANGAEA.901821 (Muhammad and Thapa, 2019).

Contemporary Snow Changes in the Karakoram Region Attributed to Improved MODIS Data between 2003 and 2018

“…This criterion may lead to some uncertainty in snowmelt simulations from the improved product, particularly in the peak ablation season. However, the uncertainty in glaciohydrological modeling is expected to be negligible because the snow underestimation (recovered in our improved product) is insignificant on average by 3.66% in the region [12]. In addition, only part of the 3.66% snow recovered in lower altitudes may cause some uncertainty as the high altitude areas are usually snow-covered until the late ablation season.…”

“…The MOD10A2 and MYD10A2 products were processed to remove clouds and reduced the average snow underestimation of 3.66% and merged to reduce the overestimation of 46% in the improved 8-day maximum snow cover product MOYDGL06* [12]. All these products were used in this paper to analyze snow cover trends and estimate snowline dynamics.…”

“…The improved cloud-free snow cover product is freely available from the Pangaea repository [17]. The detailed snow data improvement methodology and dataset are described in [12].…”

An improved Terra–Aqua MODIS daily cloud-free snow and Randolph Glacier Inventory 6.0 combined product (M*D10A1GL06) for high-mountain Asia between 2002 and 2019

“…The daily MODIS Terra and Aqua combined snow product in this paper cover HMA similar as in Muhammad and Thapa (2020) with the geographic extent of latitude 48 E. The 35 ten major river basins of the Hindukush Karakoram and Himalaya (HKH) region and Tibetan Plateau are covered in this study. The snow data in this study have a daily temporal resolution and 500 m spatial resolution.…”

“…The cloud contamination was somehow reduced in the eight-day composite MODIS snow cover products (Hall et al, 2002). To reduce the remaining clouds up to 99.98% in the original eight-day composite products M*D10A2, a new Terra and Aqua composite product, namely MOYDGL06* was developed for HMA 15 using a multi-step approach (Muhammad and Thapa, 2020). This product MOYDGL06* is a significant contribution to snow-related studies.…”