Item: RECENT DEVELOPMENTS WITH THE COMMUNITY SNOW OBSERVATIONS PROJECT - FROM CONCEPT TO OPERATIONAL MODELING
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Title: RECENT DEVELOPMENTS WITH THE COMMUNITY SNOW OBSERVATIONS PROJECT - FROM CONCEPT TO OPERATIONAL MODELING
Proceedings: International Snow Science Workshop Proceedings 2023, Bend, Oregon
Authors:
- David F. Hill [ Oregon State University, Corvallis, OR, USA ]
- Christina M. Aragon [ Oregon State University, Corvallis, OR, USA ]
- Gabriel Wolken [ Alaska Climate Adaptation Science Center; Alaska Division of Geological and Geophysical Surveys, Fairbanks, AK, USA ]
- Katreen Wikstrom Jones [ Alaska Division of Geological and Geophysical Surveys, Fairbanks/Anchorage, AK, USA ]
- Ryan L. Crumley [ Los Alamos National Laboratory, Los Alamos, NM, USA ]
- Anthony A. Arendt [ University of Washington, Seattle, WA, USA ]
- Emilio Mayorga [ Applied Physics Laboratory, Seattle, WA, USA ]
Date: 2023-10-08
Abstract: The Community Snow Observations (CSO) project crowd-sources snow depth information from backcountry recreationists and professionals in mountain environments. These individuals frequently traverse steep areas of complex terrain that are under-sampled by existing snow data networks such as the SNOTEL network in the USA. The CSO project then assimilates these data into high-resolution models of snowpack distribution and evolution in these areas, and returns model results to project participants in near-real time. Our modeling work has shown that assimilating crowd-sourced snow depth information improves our models beyond what can be achieved assimilating SNOTEL data alone. Here, we review aspects of model performance and review recent project developments, which include the use of forecast weather data and the production of new mobile apps for the visualization and exploration of the model results.
Object ID: ISSW2023_P2.06.pdf
Language of Article: English
Presenter(s):
Keywords: modeling, data assimilation, community science, snow distribution
Page Number(s): 687 - 694
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