Developing a GIS avalanche forecasting model using real-time weather telemetry information for the south side of MT. Hood

Cookler, L., & Orton, B. (2004). Developing a GIS avalanche forecasting model using real-time weather telemetry information for the south side of MT. Hood. In Proceedings of the 2004 International Snow Science Workshop, Jackson Hole, Wyoming (pp. 145-152). https://arc.lib.montana.edu/snow-science/objects/issw-2004-145-152.pdf

This study was done to see if GIS software is suitable for making accurate, local avalanche forecasts with real time weather telemetry data. This is important for individuals accessing the backcountry where point weather data is not as readily available as it is at ski resorts.

The geographic area covered for this research is the south quadrangle of Mount Hood, Oregon. The GIS avalanche forecasting model created by Cookler and Orton is based on two programs, the Swiss Nearest Neighbors Project (NXD-2000), and GeoWAX. As the authors describe, NXD-2000 functions by inputting "day x" (the desired forecast day) for which it identifies days of similar weather from a historical database using nearest neighbor calculations. Avalanche data that was reported for those historical weather nearest neighbors is displayed, enabling a forecaster to predict avalanche danger for the input "day x". GeoWax is a theoretical forecasting model that creates probability maps of avalanche slide paths using a similar nearest neighbors approach as NXD-2000, finding matches in a historical database based on the inputs of new snowfall, wind speed and wind direction.

Cookler and Orton hoped to build on those approaches because, while they have been proven to be very effective in avalanche danger assessment within ski resorts, they cannot be reliably used for avalanche forecasting in backcountry recreation areas where extensive weather and slide data is sparse or non-existent. Their approach tries to overcome this problem by using current remote telemetry weather data as inputs to predict local snow stability and assign an avalanche danger Index for specific locations. To assess the accuracy of this method, temperature, wind and snowfall data for the day are joined with point coverages of terrain on Mount Hood. The forecast formula is: (Windspeed Index + Snowfall Index + Aspect Index) X Critical Slope = Daily Forecast Value.

To assess the accuracy of this model, Cookler and Orton compared the forecasts it produced to the danger ratings provided by the Northwest Avalanche Center (NWAC). These comparisons were done on a daily basis for the '03-'04 winter season. On days when NWAC's danger forecast was High, the GIS model was always in agreement. However, for days of moderate or low danger, the GIS forecast showed some disagreement with NWAC forecasts.

I, like the researchers, feel that this approach has great potential for avalanche forecasting in maritime climates where the snowpack consolidates quickly after storms. This is due to the fact that it uses only the previous 24-hours of weather data. In continental mountain climates where weak layers of snow can remain buried for weeks or even months, this GIS based forecasting method would require many days or weeks of prior weather data. In general, their findings are in line with other studies that all acknowledge the necessity for a large amount of very localized weather data for a GIS to accurately predict daily avalanche danger for specific elevations and slope aspects.