Hi, this is a side project I've been working on for the better part of the last year. Unfortunately we've also had 5 avalanche deaths in Washington (my home state) in the last week alone. Preventing these deaths is my primary goal.<p>I originally came up with this idea when I was working on another project to help the Ski Guides of Hokkaido Japan share snow and avalanche information as there is no avalanche forecasts there.<p>In the US (as opposed to Canada and Europe) our avalanche forecasting is generally only lightly funded. I wanted to find a way to increase the capability of our forecasting while also building a platform which allowed us to improve the forecast products themselves. The Open Avalanche Project is meant to both be a data and experimentation platform for this. Operationalizing the data and using ML to predict the aspects of an avalanche forecast seemed like a good way to begin to move towards that goal.<p>This goes beyond what existing avalanche forecasts do in that it has a gridded resolution as opposed to a regional estimate. It also has been built to operate at scale as I would like to cover every avalanche hazard area in the world with a forecast.<p>I'd love to answer any questions folks have about the approach taken or the goals of the project.
As someone who has backcountry skied in Washington for the past 15 years color me interested!<p>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?<p>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.<p>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.
This is cool! I have been looking into building something similar along these lines for a while (I'm a data scientist and avid backcountry skier in the Wasatch). Have you seen: <a href="https://utahavalanchecenter.org/" rel="nofollow">https://utahavalanchecenter.org/</a> ?<p>I would potentially be interested in contributing to this. One of the approaches I have thought would be beneficial is to generate probabilities of a slide occuring on a given slope using snow profiles as features in the model. Here we have the Utah Avalanche Center who go visit slides and generate snowpack reports like this: <a href="https://utahavalanchecenter.org/avalanches/37960" rel="nofollow">https://utahavalanchecenter.org/avalanches/37960</a><p>There are also a bunch of other snow pits dug with reports on slopes where a slide didn't occur. I would be neat to be able to plug in a slope (aspect, pitch, elevation, wind loading, etc) and have a red/yellow/green generated. The problem I ran into was obtaining the data - it all looks to be stored in random places.
Great stuff!
Super interested for a European version. Its been close to my heart for a long time.
I'd like to see a change in the risk scale.
1-5 just doesn't work.
If its 4-5 you don't ski.
1 is basically bomber.
2 is where all the safe skiing happens
3 is where all the deaths occur.<p>Seems like 3 could be a whole system of grading or simply 3- or 3+. I know that there is huge risk with adding that indicator as people then take it for 'gospel' but informed is better than ignorance.