Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks
To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-...
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| Vydáno v: | Journal of hydrometeorology Ročník 21; číslo 9; s. 2061 - 2081 |
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| Médium: | Journal Article |
| Jazyk: | angličtina |
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American Meteorological Society
01.09.2020
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| ISSN: | 1525-755X, 1525-7541 |
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| Abstract | To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T
wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T
wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T
wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins. |
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| AbstractList | To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T
wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T
wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T
wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins. To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature T wet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A T wet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using T wet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins. Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation methods using ground measurements from basin-scale wireless sensor networks: one based on wet-bulb temperature Twet and the other based on snow-depth measurements of accumulation and ablation. With data from 17 spatially distributed clusters (178 nodes) from two networks, in the American and Feather River basins of California’s Sierra Nevada, we analyzed transition elevation during 76 storm events in 2014–18. A Twet threshold of 0.5°C best matched the transition elevation defined by snow depth. Transition elevations using Twet in upper elevations of the basins generally agreed with atmospheric snow level from radars located at lower elevations, while radar snow level was ~100 m higher due to snow-level lowering on windward mountainsides during orographic lifting. Diurnal patterns of the difference between transition elevation and radar snow level were observed in the American basin, related to diurnal ground-temperature variations. However, these patterns were not found in the Feather basin due to complex terrain and higher uncertainties in transition-elevation estimates. The American basin tends to exhibit 100-m-higher transition elevations than does the Feather basin, consistent with the Feather basin being about 1° latitude farther north. Transition elevation averaged 155 m higher in intense atmospheric river events than in other events; meanwhile, snow-level lowering was enhanced with a 90-m-larger difference between radar snow level and transition elevation. On-the-ground continuous observations from distributed sensor networks can complement radar data and provide important ground truth and spatially resolved information on transition elevations in mountain basins. |
| Author | Rice, Robert Hartsough, Peter Bales, Roger Avanzi, Francesco Conklin, Martha Cui, Guotao Anderson, Michael |
| Author_xml | – sequence: 1 givenname: Guotao surname: Cui fullname: Cui, Guotao – sequence: 2 givenname: Roger surname: Bales fullname: Bales, Roger – sequence: 3 givenname: Robert surname: Rice fullname: Rice, Robert – sequence: 4 givenname: Michael surname: Anderson fullname: Anderson, Michael – sequence: 5 givenname: Francesco surname: Avanzi fullname: Avanzi, Francesco – sequence: 6 givenname: Peter surname: Hartsough fullname: Hartsough, Peter – sequence: 7 givenname: Martha surname: Conklin fullname: Conklin, Martha |
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| CitedBy_id | crossref_primary_10_1002_hyp_14796 crossref_primary_10_1029_2021WR029954 crossref_primary_10_1016_j_rse_2024_114000 crossref_primary_10_3389_feart_2022_875795 crossref_primary_10_1016_j_envsoft_2021_105076 crossref_primary_10_3390_atmos11111259 crossref_primary_10_1002_hyp_14519 crossref_primary_10_1016_j_jhydrol_2022_128835 crossref_primary_10_5194_essd_15_639_2023 crossref_primary_10_3390_w13162260 |
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| Snippet | To provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two estimation... Here, to provide complementary information on the hydrologically important rain–snow-transition elevation in mountain basins, this study provides two... |
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| SubjectTerms | ENVIRONMENTAL SCIENCES Hydrology Instrumentation/sensors Measurements Mountain meteorology Operational forecasting Radar observations Radars |
| Title | Detecting Rain–Snow-Transition Elevations in Mountain Basins Using Wireless Sensor Networks |
| URI | https://www.jstor.org/stable/26967463 https://www.osti.gov/servlets/purl/2251501 |
| Volume | 21 |
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