Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data
Abstract. Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mix...
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ftcdlib:oai:escholarship.org:ark:/13030/qt43q3q5g4 2024-01-07T09:47:01+01:00 Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data Zheng, Z Kirchner, PB Bales, RC 257 - 269 2016-01-01 application/pdf https://escholarship.org/uc/item/43q3q5g4 unknown eScholarship, University of California qt43q3q5g4 https://escholarship.org/uc/item/43q3q5g4 public The Cryosphere, vol 10, iss 1 Earth Sciences Atmospheric Sciences Oceanography Physical Geography and Environmental Geoscience Meteorology & Atmospheric Sciences article 2016 ftcdlib 2023-12-11T19:05:32Z Abstract. Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mixed-conifer forest sites covering the main snow-accumulation zone, with a total surveyed area of over 106 km2. The percentage of pixels with at least one snow-depth measurement was observed to increase from 65–90 to 99 % as the sampling resolution of the lidar point cloud was increased from 1 to 5 m. However, a coarser resolution risks undersampling the under-canopy snow relative to snow in open areas and was estimated to result in at least a 10 cm overestimate of snow depth over the main snow-accumulation region between 2000 and 3000 m, where 28 % of the area had no measurements. Analysis of the 1 m gridded data showed consistent patterns across the four sites, dominated by orographic effects on precipitation. Elevation explained 43 % of snow-depth variability, with slope, aspect and canopy penetration fraction explaining another 14 % over the elevation range of 1500–3300 m. The relative importance of the four variables varied with elevation and canopy cover, but all were statistically significant over the area studied. The difference between mean snow depth in open versus under-canopy areas increased with elevation in the rain–snow transition zone (1500–1800 m) and was about 35 ± 10 cm above 1800 m. Lidar has the potential to transform estimation of snow depth across mountain basins, and including local canopy effects is both feasible and important for accurate assessments. Article in Journal/Newspaper The Cryosphere University of California: eScholarship |
institution |
Open Polar |
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University of California: eScholarship |
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topic |
Earth Sciences Atmospheric Sciences Oceanography Physical Geography and Environmental Geoscience Meteorology & Atmospheric Sciences |
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Earth Sciences Atmospheric Sciences Oceanography Physical Geography and Environmental Geoscience Meteorology & Atmospheric Sciences Zheng, Z Kirchner, PB Bales, RC Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
topic_facet |
Earth Sciences Atmospheric Sciences Oceanography Physical Geography and Environmental Geoscience Meteorology & Atmospheric Sciences |
description |
Abstract. Airborne light detection and ranging (lidar) measurements carried out in the southern Sierra Nevada in 2010 in the snow-free and peak-snow-accumulation periods were analyzed for topographic and vegetation effects on snow accumulation. Point-cloud data were processed from four primarily mixed-conifer forest sites covering the main snow-accumulation zone, with a total surveyed area of over 106 km2. The percentage of pixels with at least one snow-depth measurement was observed to increase from 65–90 to 99 % as the sampling resolution of the lidar point cloud was increased from 1 to 5 m. However, a coarser resolution risks undersampling the under-canopy snow relative to snow in open areas and was estimated to result in at least a 10 cm overestimate of snow depth over the main snow-accumulation region between 2000 and 3000 m, where 28 % of the area had no measurements. Analysis of the 1 m gridded data showed consistent patterns across the four sites, dominated by orographic effects on precipitation. Elevation explained 43 % of snow-depth variability, with slope, aspect and canopy penetration fraction explaining another 14 % over the elevation range of 1500–3300 m. The relative importance of the four variables varied with elevation and canopy cover, but all were statistically significant over the area studied. The difference between mean snow depth in open versus under-canopy areas increased with elevation in the rain–snow transition zone (1500–1800 m) and was about 35 ± 10 cm above 1800 m. Lidar has the potential to transform estimation of snow depth across mountain basins, and including local canopy effects is both feasible and important for accurate assessments. |
format |
Article in Journal/Newspaper |
author |
Zheng, Z Kirchner, PB Bales, RC |
author_facet |
Zheng, Z Kirchner, PB Bales, RC |
author_sort |
Zheng, Z |
title |
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
title_short |
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
title_full |
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
title_fullStr |
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
title_full_unstemmed |
Topographic and vegetation effects on snow accumulation in the southern Sierra Nevada: a statistical summary from lidar data |
title_sort |
topographic and vegetation effects on snow accumulation in the southern sierra nevada: a statistical summary from lidar data |
publisher |
eScholarship, University of California |
publishDate |
2016 |
url |
https://escholarship.org/uc/item/43q3q5g4 |
op_coverage |
257 - 269 |
genre |
The Cryosphere |
genre_facet |
The Cryosphere |
op_source |
The Cryosphere, vol 10, iss 1 |
op_relation |
qt43q3q5g4 https://escholarship.org/uc/item/43q3q5g4 |
op_rights |
public |
_version_ |
1787428972466798592 |