About the training
Permafrost remains poorly addressed in the Hindu Kush Himalaya (HKH) region although it contributes significantly to catchment hydrology and hazards in the region. Building on previous training workshops on snow and glacier monitoring, this training will introduce permafrost – as the third pillar of the cryosphere.
The training will introduce participants to field monitoring and sensor technology and using the data obtained for modelling. Participants will also learn how to access and process freely-accessible data.
Training content
Participants will be introduced to the theory of permafrost and relevant data products used to estimate permafrost. They will also receive training on field monitoring and data analysis. While focusing on permafrost, we will also provide basic training on coding languages (python, R, GEE) and guide them on how to make codes traceable and reproducible via GitHub.
The training will follow a hybrid modality. Participants who are unable to travel to Kathmandu, Nepal will be able to participate online.
Objectives
- Theoretical understanding of permafrost modelling, data collection, and data analysis
- Theoretical understanding of the climatic drivers of permafrost change
- Introduce best practices in coding and sharing research insights
- Foster networks and collaboration between researchers in the region
Expected participants
The training is aimed at organisations, students, and early career scientists working on cryosphere in the HKH region. We are seeking nominations from our partners institutions in the regional member countries (RMCs), and from Kathmandu University and Tribhuvan University, who are co-organising this training.
We are also inviting interested applicants through an open call.
Application process
Graduate students, government employees, and full-time early career scientists from research institutes in the following countries can apply: Afghanistan, Bangladesh, Bhutan, China, India, Myanmar, Nepal, or Pakistan. Priority will be given to research scientists and students who are focusing on permafrost and snow studies.
Applicants will be considered on a first-come-first-served basis, considering they meet the required qualifications.
Nominated participants and those applying through the open call must have the following qualifications:
- An interest in cryosphere science and a basic understanding of earth science or environmental science.
- Previous basic knowledge of the R software or similar programming language (Python, Matlab)
- Knowledge of at last one of the following areas: permafrost, glacier mass balance, glacier dynamics, snow cover analysis, GLOFS (glacier lake outburst floods), hydrology, remote sensing
- Preferably at least an MSc in a relevant subject
We strongly encourage women to apply.
Important dates
26 May 2022: Application deadline
3 June 2022: Announcement of selected participants
Please note that only successful candidate will be notified.
Expected outcomes
The trainees are expected to use the acquired skills in this training for permafrost monitoring in the HKH region, and to develop their own monitoring programmes and/or understand the results and implications of such programmes.
This training responds to the 6th HKH Call to Action on regional data and information sharing and science and knowledge co-operation, which emphasises fostering co-operation and capacity building on data generation methodologies for consistent, disaggregated, timely, and quality data on a range of issues.
Planned follow-up
We will be following up with the participants for further support in permafrost monitoring and research in the region, through the CryoHub and other channels. The training will also work as a networking event and will contribute to building a network of permafrost researchers in the region. Participants will be asked to fill out a post-training survey that is critical to improving similar capacity building training in the future. Bi-annual follow up meeting may be arranged.
Contact: Miriam Jackson, Dibas Shrestha & Rijan Bhakta Kayastha
Cover image by Bishes Gurung.
