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As someone who has backcountry skied in Washington for the past 15 years color me interested! What are the weather inputs into the models and do you think that

As someone who has backcountry skied in Washington for the past 15 years color me interested! What are the weather inputs into the models and do you think that will capture enough? Wind transportation seems easy enough to think about but stuff like hoar frost seems harder to predict using available weather data, but maybe that's just clear cold days? I do wonder as well whether the models should actually be regionally specific. Sure avy patterns are different but that likely falls out if you are basing it all on weather. IE, WA can act like CO when we have many weeks in a row of cold and vice versa during warm spells there. Anyways, will be keeping an eye on this. Enabling places with no current forecast to have something at all is a noble goal, though I am skeptical that the recent WA deaths would have been prevented, that's just education and group dynamics sadly.

scottcha 9y ago
The current model captures data from three separate inputs: The NAM weather forecast model--primarily wind, air temperature and precipitation values SNOTEL data--on the ground snow values include snowpack depth and SWE SNODAS-which has things like snowpack temperature and sublimation rates The input combines these and has a lookback of ~21 days to allow for things like buried hoar frost. I do think there is work to be done to validate that buried weak layers are well represented in the model but currently the model is a pretty good representation of the human forecasts which do account for those. I do agree that regional variation is a factor. One example is that I feature engineered a Long Term Cold feature which we know is a primary cause of snowpack faceting leading to buried deep layers. This is more of a continental feature of avalanches as opposed to a coastal. My model doesn't consider this feature important. I currently attribute this to being only trained on costal forecasts. I have reached out to both to the Colorado Avalanche and Utah avalanche centers to work on how to best incorporate their historical forecast data in to the modeling to assess this further.

scottcha 9y ago

The current model captures data from three separate inputs: The NAM weather forecast model--primarily wind, air temperature and precipitation values SNOTEL data--on the ground snow values include snowpack depth and SWE SNODAS-which has things like snowpack temperature and sublimation rates The input combines these and has a lookback of ~21 days to allow for things like buried hoar frost. I do think there is work to be done to validate that buried weak layers are well represented in the model but currently the model is a pretty good representation of the human forecasts which do account for those. I do agree that regional variation is a factor. One example is that I feature engineered a Long Term Cold feature which we know is a primary cause of snowpack faceting leading to buried deep layers. This is more of a continental feature of avalanches as opposed to a coastal. My model doesn't consider this feature important. I currently attribute this to being only trained on costal forecasts. I have reached out to both to the Colorado Avalanche and Utah avalanche centers to work on how to best incorporate their historical forecast data in to the modeling to assess this further.