Item: MOUNTAIN RAIN OR SNOW: ENHANCING AVALANCHE FORECASTING WITH REAL-TIME PRECIPITATION PHASE DATA
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Title: MOUNTAIN RAIN OR SNOW: ENHANCING AVALANCHE FORECASTING WITH REAL-TIME PRECIPITATION PHASE DATA
Proceedings: International Snow Science Workshop 2024, Tromsø, Norway
Authors:
- Anne Heggli [ Desert Research Institute ]
- David Reichel [ Sierra Avalanche Center ]
- Brian Brong [ National Weather Service, Reno ]
- Benjamin Hatchett [ Cooperative Institute for Research in the Atmosphere, Colorado State University, ]
- Nayoung Hur [ Lynker ]
- Meghan Collins [ Desert Research Institute ]
- Keith Jennings [ Lynker ]
- Monica Arienzo [ Desert Research Institute ]
Date: 2024-09-23
Abstract: Both minor and major rain-on-snow events can create a weak layer in the snowpack or reduce snowpack stability, increasing the potential for avalanche conditions. Understanding and monitoring rain-on-snow events is crucial for avalanche forecasters to assess the stability of the snowpack. But for mountainous regions, forecasting rain vs. snow (precipitation phase) is not as simple as knowing whether the air temperature is above or below freezing. The atmospheric temperature profile, humidity, surface pressure, warm air advection, cold air damming, and other microclimate phenomena are some of the reasons that precipitation phase forecasting remains a challenge. These challenges are amplified in mountainous regions where terrain shapes local and regional weather patterns. To address these challenges, we developed the Mountain Rain or Snow participatory science project and recruited over 1,300 observers across the US to build a precipitation phase validation dataset focused on eight regions. Across these eight regions of the continental US, we have collected over 78,000 observations to-date. These observations show real-time changes in precipitation phase, which can help forecasters validate the occurrence of both minor rain-on-snow events and high-impact rain-on-snow events that can rapidly change snowpack conditions, increase snow load, and lead to snowpack instability. By providing real-time precipitation phase observations, the Mountain Rain or Snow dataset can help forecasters better understand and predict these critical changes in snowpack conditions, ultimately improving avalanche forecasting and safety. In this pilot study, we explore the application of Mountain Rain or Snow data for avalanche forecasting by comparing probabilistic forecast snow levels to observed precipitation phase, analyzing the correlation between precipitation phase observations and subsequent avalanche activity, and studying the effectiveness of using real-time precipitation phase data from the Mountain Rain or Snow application in the decision-making process.
Object ID: ISSW2024_P1.13.pdf
Language of Article: English
Presenter(s): Anne Heggli
Keywords: snow level, probabilistic forecast, precipitation phase, Sierra Nevada
Page Number(s): 153 - 159
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