High Mountain Asia Overview

The NSIDC DAAC High Mountain Asia (HMA) collection includes data related to snow and ice in a region that stretches across five mountain ranges, including the Himalaya and Hindu Kush. The region covers parts of China, Afghanistan, Nepal, India, Pakistan, Bhutan, Kazakhstan, Uzbekistan, Kyrgyzstan, and Tajikistan. These mountains funnel fresh water into major river basins that support about 1.5 billion people, providing drinking water, irrigation, and hydropower.

HMA has one of the highest concentrations of snow and glacier ice outside of the polar regions. Changes in snow and ice influence glacial advances and retreats, changing the capacity for life-sustaining water while posing hazards such as glacial-lake outburst floods and landslides. To monitor these changes, NASA funded the High Mountain Asia Team (HiMAT), consisting of 13 research groups, to integrate historical data with newer data-collecting techniques that include:

  • Optical imagery to map the extent of glaciers and seasonal snow
  • Photogrammetry, or the assembly of disparate satellite images to create a topographical map
  • Measurements of Earth’s surface height using lasers
  • Satellite gravimetry to measure changes in Earth’s mass caused by variations in the water cycle

The High Mountain Asia effort includes two projects: HMA-1 lasting from 2016 to 2020, and HMA-2 which started in late 2020 and will continue into 2023.

The data and tools produced by the High Mountain Asia team are called the Glacier and Snow Melt Toolbox (GMELT). GMELT consists of remote sensing products such as digital elevation and snow cover maps; precipitation, dust, and water models; and other tools to assess and project change in the water, ice, snow, hazards, and related phenomena in HMA.

HMA open-science software

The following software was developed by scientists to produce High Mountain Asia products from satellite data or reanalysis (climate model) data. These software products are not designed for non-specialist users in general, but may be useful to other scientists, and may facilitate learning the details of the algorithms behind some of the High Mountain Asia data products.

Atmospheric variable downscaling framework
Author(s): Yiwen Mei
Mei et al. 2020 at https://doi.org/10.1002/essoar.10502607.1
Rouf et al. 2020 at https://doi.org/10.1175/JHM-D-19-0109.1

MODIS processing for emissivity, land cover type, normalized-difference snow index, other parameters
Author(s): Yiwen Mei

Land information system framework
Author(s): Sujay Kumar
Reference(s)/documentation: lis.gsfc.nasa.gov/

Landslide hazard analysis for situational awareness
Author(s): Thomas Stanley, Dalia Kirschbaum

Radiative transfer in turbid water to examine heat transfer in glacial lakes
Author(s): Enrico Schiassi, Robert Furfaro, Jeffrey S. Kargel
Reference(s)/documentation: Schiassi et al. 2019 at https://doi.org/10.3389/feart.2019.00267

Glacier evolution model
Author(s): David Rounce
Reference(s)/documentation: Rounce et al. 2020 at https://doi.org/10.3389/feart.2019.00331


Glacier, ice sheet, snow, and precipitation changes; and ice- and water-related hazards over high mountain Asia

Geographic coverage

Tian Shan / Hindu Kush to eastern Himalaya

Related collection(s)


Explore images from High Mountain Asia

High Mountain Asia Data