Understanding Snow Depth Variability with Respect to the Canopy in Multiple Climates Using Airborne LiDAR
Abstract
Snow depth within a typical hydrologic model grid cell (150 m or 1 km) can vary from 0.5 meters to 6 meters, or more. This variability is driven by the meteorological conditions throughout the winter as well as the forest architecture. To better understand this variability, we used airborne LiDAR from Olympic National Park, WA, Yosemite National Park, CA, Jemez Caldera, NM, and Niwot Ridge, CO to determine unique spatial patterns of snow depth in forested regions. Specifically, we compared snow depth distributions along north facing forest edges and south facing forest edges to those in the open or directly under the canopy. When categorizing the north facing and south facing edges based on distance from the canopy, distances relative to tree height, and distances relative to the fraction of the sky that is visible (sky view factor) we found unique snow depth patterns for each of these regions. In all regions besides Olympic National Park, WA, north facing edges contained more snow than open areas, forested areas, or along the south facing edges. These snow distributions were relatively consistent regardless of the metric used to define the forest edge and the size of the domain (150 m through 1 km). The absence of the forest edge effect in Olympic National Park was attributed to the meteorological data and climate conditions, which showed significantly less incoming shortwave radiation and more incoming longwave radiation. Furthermore, this study evaluated the effect that wind speed and direction have on the spatial distribution of snow depth.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2017
- Bibcode:
- 2017AGUFM.C51E..07C
- Keywords:
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- 0736 Snow;
- CRYOSPHERE;
- 0740 Snowmelt;
- CRYOSPHERE;
- 0758 Remote sensing;
- CRYOSPHERE;
- 1863 Snow and ice;
- HYDROLOGY