Quantcast

CRYOSPHERE INITIATIVE

The HKH CryoHub

The collaborative HKH CryoHub platform supports knowledge generation and exchange, learning, and networking, to create better connected practitioners and decision makers to enhance work and policies relevant to the cryosphere in the region.

Red panda
Fire-tailed sunbird (Aethopyga ignicauda
Laccaria-amethystina

Our focus

Networking

The CryoHub links regional institutions conducting cryosphere-related research and provides a platform through which a common approach to data sharing is being promoted to improve our understanding of water resources and their management in the HKH.

The regional CryoHub is a collaborative effort through which we share and disseminate data and information using a network of national partners from and beyond our RMCs. It serves as a clearing house for cryosphere-related data and information for relevant operational services and research activities. As a knowledge hub, it integrates geospatial data to support knowledge development and decision making, and builds on capacity building efforts in the HKH for future generations of scientists.

Our activities under the regional CryoHub include:

  • Building a web-based interactive portal for the dissemination and visualization of cryosphere data that includes science applications and story maps
  • Regular publication of quarterly e-bulletins on our cryosphere-related activities
  • Organizing and facilitating conferences, seminars, and workshops
  • Organizing events for regional knowledge sharing

In the spotlight

Qiao Liu

For this month’s HKH CryoHub: In the spotlight, we speak with Qiao Liu, who is a professor at the Institute of Mountain Hazards and Environment (IMHE), Chinese Academy of Sciences.

Learn more
Qiao Liu

HKH Data

Debris cover glacier melt in the Karakoram during 2018-2019

The assessment of meltwater sourcing from the clean and debris-covered glaciers is scarce in High Mountain Asia (HMA). The melting rate varies with the debris cover thickness and glacier orientation. The present study quantifies glacier melting rate attributed to varying thickness of debris cover in the Karakoram. We observed daily melting rates by installing ablation stakes over debris-free and debris-covered ice during a field expedition. The stakes were installed on glacier surface with debris cover thickness ranges between 0.5 and 40 cm at selected experimental sites during the ablation period (September to October 2018) and (July to August 2019). We selected three glaciers including Ghulkin, Hinarchi, and Hoper facing east, south, and north, respectively to assess the role of glacier orientation on melting rates. We observed that the debris-free ice melts faster than the debris-covered ice. Intriguingly, a thin debris layer of 0.5 cm does not enhance melting compared to the clean ice which is inconsistent with the earlier studies. The melting rate decreases as the thickness of debris cover increases at all the three selected glaciers. Furthermore, south-facing glacier featured the highest melting (on average ~ 25% more). However, the north and east-facing glaciers revealed almost same melting rates. For further information, please read the paper associated with this data: Muhammad, S., Tian, L., Ali, S., Latif, Y., Wazir, M.A., Goheer, M.A., Saifullah, M., Hussain, I. and Shiyin, L., 2020. Thin debris layers do not enhance melting of the Karakoram glaciers. Science of the Total Environment, 746, p.141119.

Snow Water Equivalent Station at Yala Basecamp

Gamma Ray Station close to Yala Basecamp measuring Snow Water Equivalent as well as radiation (shortwave and longwave radiation) and distance to surface/snow depth

Improved daily MODIS TERRA/AQUA Snow and Randolph Glacier Inventory (RGI6.0) data for High Mountain Asia (2002-2019)

The data contains improved daily MODIS Terra/Aqua combined snow-cover merged with Randolph Glacier Inventory (RGI6.0) product. This product is generated using MODIS Terra and Aqua daily snow cover products MOD10A1 and MYD10A1 collection 6 (C6), respectively. The data covers High Mountain Asia (HMA) covering latitude 24.32− 49.19 N and Longitude 58.22 - 122.48 E with temporal coverage between 2002 and 2019. The data has daily temporal resolution and 500 m spatial resolution. The product is named as M*D10A1GL06 derived from MODIS Terra (MOD) MODIS Aqua (MYD), original product number (10A1) and Glacier (GL), Version 6 (06). The product is described in ordinal date available in GeoTIFF file format as described in the associated Dataset README. For more details about the data, please read the paper associated with this data titled "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" in Earth System Science Data Journal.

Improved MODIS TERRA/AQUA composite Snow and glacier (RGI6.0) data for High Mountain Asia (2002-2018)

The data contains an enhanced MODIS 8-day Terra (MOD10A2) and Aqua (MYD10A2) collection 6 snow-cover composite product merged with Randolph Glacier Inventory (RGI6.0). The data is specifically developed for the High Mountain Asia (HMA) with the geographic coverage between latitude 24.32 − 49.19 N and Longitude 58.22 − 122.48 E. The data is available with eight-day temporal resolution and 500 m spatial resolution covering the period between 2002 and 2018. The name of the product is derived from MODIS Terra (MOD) MODIS Aqua (MYD), and Glacier (GL), Version 6 (06) as MOYDGL06*. The product is described in Julian day and each year has 46 eight-day composite images in GeoTIFF file format as described in the associated readme.TXT. The data can be accessed alternatively from https://doi.org/10.1594/PANGAEA.901821. The R code developed for this product is available at https://doi.org/10.5281/zenodo.3610735. For more details about the data, please read the paper associated with this data titled lease read the paper associated with this data titled "An improved Terra/Aqua MODIS snow-cover and RGI6.0 glacier combined product (MOYDGL06*) for the High Mountain Asia between 2002 and 2018" published in Earth System Science Data Journal.

GST (Ground surface temperature) loggers Langtang Valley

Collection of ground surface temperaure loggers (39) placed on the Yala Plateau on different surface types.

Eddy Covariance Station Lirung Glacier

Eddy Covariance Station measuring turbulent fluxes on Lirung Glacier over approximately 16 days in October 2016.

Discussion forum

Community of practice

Register Login View all Invite

NEWS AND FEATURES

Around the HKH

Resources

Publications

Glacial Lake Outburst Flood (Glofs)
The melting Himalayas: Regional challenges and local impacts of climate change on mountain ecosystems and livelihoods

This policy summary looks at reported and possible future consequences of climate change in the greater Himalayan region.

Read More
Glofs
Inventory of glaciers, glacial lakes, and Glacial Lake Outburst Floods: Monitoring and Early Warning Systems in the Hindu Kush Himalayan Region – Bhutan

Himalayan glaciers are retreating; the resultant long-term loss of natural fresh water storage will have as yet uncalculated effects.

Read More
Snow-cover mapping and monitoring in the Hindu Kush Himalaya

Snow is an important component of the cryosphere, and the study of snow trends is essential for understanding regional climate change and for managing water resources.

Read more
The status of glacial lakes in the Hindu Kush Himalaya

This is the first comprehensive report on the distribution of glacial lakes for the HKH providing baseline data for further investigation of glacial lakes, GLOF hazards and risk assessments, and mitigation measures.

Read more

Partners

The HKH CryoHub profile

comstat
COMSATS University
Read more
imhe
Institute of Mountain Hazards and Environment
Read more
kabul university
Kabul University
Read more
Wadia Institute of Himalayan Geology
Wadia Institute of Himalayan Geology
Read more

Resources and information for the media

Press releases

Landmark study: Two-degree temperature rise could melt half of glaciers in Hindu Kush Himalaya region, destabilizing Asia’s rivers

Read more
explore