Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia
Drifting snow is a significant factor in snow redistribution and cascading snow incidents. However, field observations of drifting snow are relatively difficult due to limitations in observation technology, and drifting snow observation data are scarce. The FlowCapt sensor is a relatively stable sen...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-03-01
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| Series: | Water |
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| Online Access: | https://www.mdpi.com/2073-4441/14/6/845 |
| _version_ | 1797440912687628288 |
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| author | Wei Zhang Jianqiao He An’an Chen Xuejiao Wu Yongping Shen |
| author_facet | Wei Zhang Jianqiao He An’an Chen Xuejiao Wu Yongping Shen |
| author_sort | Wei Zhang |
| collection | DOAJ |
| description | Drifting snow is a significant factor in snow redistribution and cascading snow incidents. However, field observations of drifting snow are relatively difficult due to limitations in observation technology, and drifting snow observation data are scarce. The FlowCapt sensor is a relatively stable sensor that has been widely used in recent years to obtain drifting snow observations. This study presents the results from two FlowCapt sensors that were employed to obtain field observations of drifting snow during the 2017–2018 snow season in the southern Altai Mountains, Central Asia, where the snow cover is widely distributed. The results demonstrate that the FlowCapt sensor can successfully acquire stable field observations of drifting snow. Drifting snow occurs mainly within the height range of 80-cm zone above the snow surface, which accounts for 97.73% of the total snow mass transport. There were three typical snowdrift events during the 2017–2018 observation period, and the total snowdrift flux caused during these key events accounted for 87.5% of the total snow mass transport. Wind speed controls the occurrence of drifting snow, and the threshold wind speed (friction velocity) for drifting snow is approximately 3.0 m/s (0.15 m/s); the potential for drifting snow increases rapidly above 3.0 m/s, with drifting snow essentially being inevitable for wind speeds above 7.0 m/s. Similarly, the snowdrift flux is also controlled by wind speed. The observed maximum snowdrift flux reaches 192.00 g/(m<sup>2</sup>·s) and the total snow transport is 584.9 kg/m during the snow season. Although drifting snow will lead to a redistribution of the snow mass, any accumulation or loss of the snow mass is also affected synergistically by other factors, such as topography and snow properties. This study provides a paradigm for establishing a field observation network for drifting snow monitoring in the southern Altai Mountains and bridges the gaps toward elucidating the mechanisms of drifting snow in the Altai Mountains of Central Asia. A broader network of drifting snow observations will provide key data for the prevention and control of drifting snow incidents, such as the design height of windbreak fences installed on both sides of highways. |
| first_indexed | 2024-03-09T12:15:18Z |
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| id | doaj.art-dea1708c9098484eb95c6cf0a0d8dc4e |
| institution | Directory Open Access Journal |
| issn | 2073-4441 |
| language | English |
| last_indexed | 2024-03-09T12:15:18Z |
| publishDate | 2022-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Water |
| spelling | doaj.art-dea1708c9098484eb95c6cf0a0d8dc4e2023-11-30T22:48:04ZengMDPI AGWater2073-44412022-03-0114684510.3390/w14060845Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central AsiaWei Zhang0Jianqiao He1An’an Chen2Xuejiao Wu3Yongping Shen4Koktokay Snow Station, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaKoktokay Snow Station, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaCollege of Urban and Environmental Sciences, Northwest University, Xi’an 710127, ChinaKoktokay Snow Station, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaKoktokay Snow Station, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, ChinaDrifting snow is a significant factor in snow redistribution and cascading snow incidents. However, field observations of drifting snow are relatively difficult due to limitations in observation technology, and drifting snow observation data are scarce. The FlowCapt sensor is a relatively stable sensor that has been widely used in recent years to obtain drifting snow observations. This study presents the results from two FlowCapt sensors that were employed to obtain field observations of drifting snow during the 2017–2018 snow season in the southern Altai Mountains, Central Asia, where the snow cover is widely distributed. The results demonstrate that the FlowCapt sensor can successfully acquire stable field observations of drifting snow. Drifting snow occurs mainly within the height range of 80-cm zone above the snow surface, which accounts for 97.73% of the total snow mass transport. There were three typical snowdrift events during the 2017–2018 observation period, and the total snowdrift flux caused during these key events accounted for 87.5% of the total snow mass transport. Wind speed controls the occurrence of drifting snow, and the threshold wind speed (friction velocity) for drifting snow is approximately 3.0 m/s (0.15 m/s); the potential for drifting snow increases rapidly above 3.0 m/s, with drifting snow essentially being inevitable for wind speeds above 7.0 m/s. Similarly, the snowdrift flux is also controlled by wind speed. The observed maximum snowdrift flux reaches 192.00 g/(m<sup>2</sup>·s) and the total snow transport is 584.9 kg/m during the snow season. Although drifting snow will lead to a redistribution of the snow mass, any accumulation or loss of the snow mass is also affected synergistically by other factors, such as topography and snow properties. This study provides a paradigm for establishing a field observation network for drifting snow monitoring in the southern Altai Mountains and bridges the gaps toward elucidating the mechanisms of drifting snow in the Altai Mountains of Central Asia. A broader network of drifting snow observations will provide key data for the prevention and control of drifting snow incidents, such as the design height of windbreak fences installed on both sides of highways.https://www.mdpi.com/2073-4441/14/6/845drifting snowsnow coverFlowCaptnorthern XinjiangAltai Mountains |
| spellingShingle | Wei Zhang Jianqiao He An’an Chen Xuejiao Wu Yongping Shen Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia Water drifting snow snow cover FlowCapt northern Xinjiang Altai Mountains |
| title | Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia |
| title_full | Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia |
| title_fullStr | Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia |
| title_full_unstemmed | Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia |
| title_short | Observations of Drifting Snow Using FlowCapt Sensors in the Southern Altai Mountains, Central Asia |
| title_sort | observations of drifting snow using flowcapt sensors in the southern altai mountains central asia |
| topic | drifting snow snow cover FlowCapt northern Xinjiang Altai Mountains |
| url | https://www.mdpi.com/2073-4441/14/6/845 |
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