Supplementary material to "Brief Communication: Updated GAMDAM Glacier Inventory over the High Mountain Asia"

AbstractContemporary glaciers of southeast Siberia are located on three high-mountain ridges (east Sayan, Baikalsky and Kodar). In this study, we present an updated glacier inventory based on high- to middle-resolution satellite imagery and field investigations. The inventory includes 51 glaciers with a total area of - 15 km2. Areas of individual glaciers vary from 0.06 to 1.33 km2, lengths from 130 to 2010 m and elevations from 1796 to 3490 m. The recent ice maximum extents (Little Ice Age) have been delineated from terminal moraines. On average, debris-free surface area shrunk by 59% between 1850 and 2006/11 (0.37% a–1), by 44% between 1850 and 2001/02 (0.29% a–1) and by 27% between 2001/02 and 2006/11 (3.39% a–1). The Kodar glaciers have experienced the largest area shrinkage, while the area loss on Baikalsky ridge was more moderate. Glacier changes are mainly related to regional summer temperature increase (by 1.7-2.6C from 1970 to 2010). There are some differences in glacier response due to different spatial patterns of snow accumulation, local topography (e.g. glacier elevation, slope) and geological activity. The studied glaciers (especially of Kodar ridge) are the most sensitive in Siberia to climate change since the late 20th century.

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Brief Communication: Updated GAMDAM Glacier Inventory over the High Mountain Asia

10.5194/tc-2018-139 ◽

2018 ◽

Cited By ~ 1

Author(s):

Akiko Sakai

Keyword(s):

Snow Cover ◽

Cloud Cover ◽

High Mountain ◽

Glacier Area ◽

Landsat Images ◽

Glacier Inventory ◽

Final Version ◽

Seasonal Snow ◽

Steep Slopes ◽

Seasonal Snow Cover

Abstract. The first version of the Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) glacier inventory was the first methodologically consistent glacier inventory covering High Mountain Asia, and it underestimated glacier area because it did not include steep slopes covered with ice or snow and shadowed areas. During the process of revising the GAMDAM glacier inventory, source Landsat images were carefully selected to find images free of shadows, cloud cover, and seasonal snow cover taken from 1990 to 2010. Then, more than 90 % of the glacier area in the final version of the GAMDAM glacier inventory was delineated based on summer Landsat images. The total glacier area was 100,693±15,103 km2 and included 134,770 glaciers using 453 Landsat image scenes.

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

Earth System Science Data ◽

10.5194/essd-12-345-2020 ◽

2020 ◽

Vol 12 (1) ◽

pp. 345-356 ◽

Cited By ~ 2

Author(s):

Sher Muhammad ◽

Amrit Thapa

Keyword(s):

Water Resources ◽

Snow Cover ◽

Cloud Cover ◽

High Mountain ◽

Landsat 8 ◽

Spatial Filters ◽

Glacier Inventory ◽

Input Dataset ◽

Moderate Resolution Imaging Spectroradiometer ◽

Improved Accuracy

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).

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Brief communication: Updated GAMDAM glacier inventory over high-mountain Asia

The Cryosphere ◽

10.5194/tc-13-2043-2019 ◽

2019 ◽

Vol 13 (7) ◽

pp. 2043-2049 ◽

Cited By ~ 3

Author(s):

Akiko Sakai

Keyword(s):

Snow Cover ◽

Landsat Imagery ◽

High Mountain ◽

Glacier Area ◽

Landsat Images ◽

Glacier Inventory ◽

Seasonal Snow ◽

Seasonal Snow Cover

Abstract. The original Glacier Area Mapping for Discharge from the Asian Mountains (GAMDAM) glacier inventory was the first methodologically consistent dataset for high-mountain Asia. Nonetheless, the GAMDAM inventory underestimated glacier area, as it did not include steep ice- and snow-covered slopes or shaded components. During revision of the inventory, Landsat imagery free of shadow, cloud, and seasonal snow cover was selected for the period 1990–2010, after which >90 % of the glacier area was delineated. The updated GAMDAM inventory, comprised of 453 Landsat images, includes 134 770 glaciers with a total area of 100 693±11 790 km2.

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Supplementary material to "Ice loss in High Mountain Asia and the Gulf of Alaska observed by CryoSat-2 swath altimetry between 2010 and 2019"

10.5194/tc-2020-176-supplement ◽

2020 ◽

Author(s):

Livia Jakob ◽

Noel Gourmelen ◽

Martin Ewart ◽

Stephen Plummer

Keyword(s):

Gulf Of Alaska ◽

High Mountain ◽

Supplementary Material

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LO STATO ATTUALE DEI GHIACCIAI ITALIANI E LA LORO RECENTE EVOLUZIONE

Istituto Lombardo - Accademia di Scienze e Lettere - Rendiconti di Scienze ◽

10.4081/scie.2016.539 ◽

2020 ◽

Author(s):

Claudio Smiraglia ◽

Guglielmina Adele Diolaiuti

Keyword(s):

High Mountain ◽

Glacier Area ◽

Glacier Surface ◽

Mountain Glacier ◽

Glacier Inventory ◽

Mountain Glaciers ◽

Proglacial Lakes ◽

The World ◽

Mountain Landscapes ◽

Recent Project

Mountain glaciers represent an important hydrological and touristic resource, and their recent evolution provides a dramatic evidence of climate change for the general public. Glacier inventories, quantifying glacier characteristics and evolution, are an important tool to describe and manage high mountain glacier environments and Italy has developed a long tradition in this sector. Our country was the first to provide itself with a glacier inventory, compiled by Comitato Glaciologico Italiano and CNR, showing a glacier surface of 530 km2. A recent project, coordinated by Università Statale di Milano with the support of private bodies and the cooperation of Comitato EvK2CNR and Comitato Glaciologico Italiano, led to the development of the new Italian Glacier Inventory, a national atlas produced from the analysis of color orthophotos at high resolution acquired between 2005 and 2011. The New Italian Glacier Inventory lists 903 glaciers, covering an area of 370 km2. The largest part of glacier area is located in Val d’Aosta (36.15% of the total), followed by Lombardia and South Tyrol. 84% of glaciers (considering the number of glaciers) have an area lower than 0.5 km2 and jointly account for 21% of the total glacier surface. Glaciers larger than 1 Km2 make up 9.4% of the total number, but cover 67.8% of the total glacier area. The comparison between data from the New Italian Glacier Inventory and the CGI-CNR inventory (1959-1962) shows a 30% reduction in glacier area in Italy; considering instead the World Glacier Inventory or WGI, published at the end of the ‘80s, which reported 1381 glaciers and an area of 609 km2, glacier loss sums up to 478 glaciers and an area of 239 km2 (-39%). This shrinkage has led to rapid and significant changes to high mountain landscapes, notably glacier fragmentation, an increase in deglaciated areas, the formation of proglacial lakes and the development of pioneer vegetation.

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The GAMDAM glacier inventory: a quality-controlled inventory of Asian glaciers

The Cryosphere ◽

10.5194/tc-9-849-2015 ◽

2015 ◽

Vol 9 (3) ◽

pp. 849-864 ◽

Cited By ~ 86

Author(s):

T. Nuimura ◽

A. Sakai ◽

K. Taniguchi ◽

H. Nagai ◽

D. Lamsal ◽

...

Keyword(s):

Peer Review ◽

Landsat Imagery ◽

The United States ◽

United States Geological Survey ◽

High Mountain ◽

Data Sets ◽

Glacier Area ◽

Glacier Inventory ◽

Elevation Model

Abstract. We present a new glacier inventory for high-mountain Asia named "Glacier Area Mapping for Discharge from the Asian Mountains" (GAMDAM). Glacier outlines were delineated manually using 356 Landsat ETM+ scenes in 226 path-row sets from the period 1999–2003, in conjunction with a digital elevation model (DEM) and high-resolution Google EarthTM imagery. Geolocations are largely consistent between the Landsat imagery and DEM due to systematic radiometric and geometric corrections made by the United States Geological Survey. We performed repeated delineation tests and peer review of glacier outlines in order to maintain the consistency and quality of the inventory. Our GAMDAM glacier inventory (GGI) includes 87 084 glaciers covering a total area of 91 263 ± 13 689 km2 throughout high-mountain Asia. In the Hindu Kush–Himalaya range, the total glacier area in our inventory is 93% that of the ICIMOD (International Centre for Integrated Mountain Development) inventory. Discrepancies between the two regional data sets are due mainly to the effects of glacier shading. In contrast, our inventory represents significantly less surface area (−24%) than the recent global Randolph Glacier Inventory, version 4.0 (RGI), which includes 119 863 ± 9201 km2 for the entirety of high Asian mountains. Likely causes of this disparity include headwall definition, effects of exclusion of shaded glacier areas, glacier recession since the 1970s, and inclusion of seasonal snow cover in the source data of the RGI, although it is difficult to evaluate such effects quantitatively. Further rigorous peer review of GGI will both improve the quality of glacier inventory in high-mountain Asia and provide new opportunities to study Asian glaciers.

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