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This dataset contains meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains during water years 2019-2021. Data collection had an emphasis on paired open-forest sites and included three forested elevations. In total, we present 270 snow pit observations, 4,019 snow depth measurements, and three years of meteorological forcing from two weather stations (one in a meadow, the other in an adjacent forest). The dataset is described in a forthcoming publication of the same name: A meteorology and snow dataset from adjacent forested and meadow sites at Crested Butte, CO, USA</em> (Bonner et al., 2022).</p> All snow observation and meteorological forcing data are available as both .nc and .mat files. Additionally, original digitized copies of snow pit observations are provided as .gsheet/.xlxs files.</p> This dataset will continue to be updated, via this repository, as additional years of data are collected.</p>
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Snowfall Measurements at Wind-Exposed and Sheltered Sites in the Rocky Mountains of Southeastern Wyoming
Abstract Snowfall is an important driver of physical and biological processes in alpine systems. Previous work has shown that surface deposition of snow can vary for reasons not directly related to precipitation processes and that this variance has consequence for water budgets in snow-dominated terrestrial systems. In this work, measurements were made over several winter seasons in a forest–meadow ecotone in the Rocky Mountains of southeastern Wyoming. Two groups of measurements—both with wind-exposed and sheltered precipitation gauges—were analyzed. Reasonable agreement between snow deposition from a Hotplate gauge (exposed) and snow deposition from a SNOTEL pillow gauge (sheltered) is reported. The other result is that snow deposition is enhanced at an exposed gauge that was deployed on the leeward side of a forest–meadow edge. The enhancement is approximately a factor of 2 and varies with wind direction and speed and with upwind forest coverage. The enhancement is greater than was documented in an earlier investigation of Rocky Mountain snow deposition; however, in that study measurements were conducted above tree line.
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- Award ID(s):
- 1850809
- PAR ID:
- 10487693
- Publisher / Repository:
- American Meteorological Society
- Date Published:
- Journal Name:
- Journal of Applied Meteorology and Climatology
- Volume:
- 63
- Issue:
- 2
- ISSN:
- 1558-8424
- Format(s):
- Medium: X Size: p. 181-196
- Size(s):
- p. 181-196
- Sponsoring Org:
- National Science Foundation
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Abstract We present meteorology and snow observation data collected at sites in the southwestern Colorado Rocky Mountains (USA) over three consecutive water years with different amounts of snow water equivalent (SWE) accumulation: A year with above average SWE (2019), a year with average SWE (2020), and a year with below average SWE (2021). This data set is distinguished by its emphasis on paired open‐forest sites in a continental snow climate. Approximately once a month during February–May, we collected data from 15 to 20 snow pits and took 8 to 19 snow depth transects. Our sampling sites were in open and adjacent forested areas at 3,100 m and in a lower elevation aspen (3,035 m) and higher elevation conifer stand (3,395 m). In total, we recorded 270 individual snow pit density and temperature profiles and over 4,000 snow depth measurements. These data are complimented by continuous meteorological measurements from two weather stations: One in the open and one in the adjacent forest. Meteorology data—including incoming shortwave and longwave radiation, outgoing shortwave radiation, relative humidity, wind speed, snow depth, and air and infrared surface temperature—were quality controlled and the forcing data were gap‐filled. These data are available to download from Bonner, Smyth, et al. (2022) athttps://doi.org/10.5281/zenodo.6618553, at three levels of processing, including a level with downscaled, adjusted precipitation based on data assimilation using observed snow depth and a process‐based snow model. We demonstrate the utility of these data with a modeling experiment that explores open‐forest differences and identifies opportunities for improvements in model representation.more » « less
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