Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data
<p>Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world'...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Copernicus Publications
2022-01-01
|
| Series: | Annales Geophysicae |
| Online Access: | https://angeo.copernicus.org/articles/40/67/2022/angeo-40-67-2022.pdf |
| _version_ | 1819242914479341568 |
|---|---|
| author | N. Desinayak A. K. Prasad H. El-Askary H. El-Askary M. Kafatos G. R. Asrar |
| author_facet | N. Desinayak A. K. Prasad H. El-Askary H. El-Askary M. Kafatos G. R. Asrar |
| author_sort | N. Desinayak |
| collection | DOAJ |
| description | <p>Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic
changes in the intra-annual (accumulating season and melting season) and
interannual variations in snow and glacial cover over the HKH region. The
zonal and altitudinal (hypsographic) analyses were carried out for the
melting season and accumulating season. The altitude-wise linear trend
analysis (Pearson's) of snow cover, shown as a hypsographic curve, clearly
indicates a major decline in snow cover (average of 5 % or more at 100 m interval aggregates) between 4000–4500 and 5500–6000 m altitudes, which is consistent with the median trend (Theil–Sen – TS) and the monotonic trend (Mann–Kendall – MK; statistics) analysis. This analysis also revealed the regions and altitudes where major and statistically significant increases (10 % to 30 %) or decreases (<span class="inline-formula">−</span>10 % to <span class="inline-formula">−</span>30 %) in snow cover are identified. The extrapolation of the altitude-wise linear trend shows that it may take between <span class="inline-formula">∼</span> 74 and 7900 years, for 3001–6000 and 6000–7000 m altitude zones respectively, for mean snow cover to decline approximately 25 % in the HKH. More detailed analysis based on longer observational records and model simulations is warranted to better understand the underlying factors, processes, and feedbacks that affect the dynamic of snow cover in HKH. These preliminary results suggest a need for continued monitoring of this highly sensitive region to climate variability and change that depends on snow as a major source of freshwater for all human activities.</p> |
| first_indexed | 2024-12-23T14:47:22Z |
| format | Article |
| id | doaj.art-33d3f704c82746e996575c7d5dec88cb |
| institution | Directory Open Access Journal |
| issn | 0992-7689 1432-0576 |
| language | English |
| last_indexed | 2024-12-23T14:47:22Z |
| publishDate | 2022-01-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Annales Geophysicae |
| spelling | doaj.art-33d3f704c82746e996575c7d5dec88cb2022-12-21T17:43:03ZengCopernicus PublicationsAnnales Geophysicae0992-76891432-05762022-01-0140678210.5194/angeo-40-67-2022Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM dataN. Desinayak0A. K. Prasad1H. El-Askary2H. El-Askary3M. Kafatos4G. R. Asrar5Photogeology and Image Processing Laboratory, Department of Applied Geology, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand 826004, IndiaPhotogeology and Image Processing Laboratory, Department of Applied Geology, Indian Institute of Technology (Indian School of Mines), Dhanbad, Jharkhand 826004, IndiaCenter of Excellence in Earth Systems, Modeling and Observations, Schmid College of Science and Technology, Chapman University, 452 N. Glassell, Orange, CA 92866, USADepartment of Environmental Sciences, Faculty of Science, Alexandria University, Moharem Bek, Alexandria 21522, EgyptCenter of Excellence in Earth Systems, Modeling and Observations, Schmid College of Science and Technology, Chapman University, 452 N. Glassell, Orange, CA 92866, USAUniversities Space Research Association, 7178 Columbia Gateway Drive, Columbia, MD 21046, USA<p>Snow cover changes have a direct bearing on the regional and global energy and water cycles and the change in the Earth's climate conditions. We studied the relatively long-term (2000–2017) altitudinal spatiotemporal changes in the coverage of snow and glaciers in one of the world's largest mountainous regions, the Hindu Kush Himalayan (HKH) region, including Tibet, using remote sensing data (5 km grid resolution) from the Moderate Resolution Imaging Spectroradiometer (MODIS) on board the Terra satellite. This dataset provided a unique opportunity to study zonal and hypsographic changes in the intra-annual (accumulating season and melting season) and interannual variations in snow and glacial cover over the HKH region. The zonal and altitudinal (hypsographic) analyses were carried out for the melting season and accumulating season. The altitude-wise linear trend analysis (Pearson's) of snow cover, shown as a hypsographic curve, clearly indicates a major decline in snow cover (average of 5 % or more at 100 m interval aggregates) between 4000–4500 and 5500–6000 m altitudes, which is consistent with the median trend (Theil–Sen – TS) and the monotonic trend (Mann–Kendall – MK; statistics) analysis. This analysis also revealed the regions and altitudes where major and statistically significant increases (10 % to 30 %) or decreases (<span class="inline-formula">−</span>10 % to <span class="inline-formula">−</span>30 %) in snow cover are identified. The extrapolation of the altitude-wise linear trend shows that it may take between <span class="inline-formula">∼</span> 74 and 7900 years, for 3001–6000 and 6000–7000 m altitude zones respectively, for mean snow cover to decline approximately 25 % in the HKH. More detailed analysis based on longer observational records and model simulations is warranted to better understand the underlying factors, processes, and feedbacks that affect the dynamic of snow cover in HKH. These preliminary results suggest a need for continued monitoring of this highly sensitive region to climate variability and change that depends on snow as a major source of freshwater for all human activities.</p>https://angeo.copernicus.org/articles/40/67/2022/angeo-40-67-2022.pdf |
| spellingShingle | N. Desinayak A. K. Prasad H. El-Askary H. El-Askary M. Kafatos G. R. Asrar Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data Annales Geophysicae |
| title | Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data |
| title_full | Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data |
| title_fullStr | Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data |
| title_full_unstemmed | Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data |
| title_short | Snow cover variability and trend over the Hindu Kush Himalayan region using MODIS and SRTM data |
| title_sort | snow cover variability and trend over the hindu kush himalayan region using modis and srtm data |
| url | https://angeo.copernicus.org/articles/40/67/2022/angeo-40-67-2022.pdf |
| work_keys_str_mv | AT ndesinayak snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata AT akprasad snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata AT helaskary snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata AT helaskary snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata AT mkafatos snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata AT grasrar snowcovervariabilityandtrendoverthehindukushhimalayanregionusingmodisandsrtmdata |