
Show HN: Open Avalanche Project – Using ML to Improve Avalanche Forecasting - scottcha
https://openavalancheproject.org
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scottcha
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.

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.

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.

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.

I'd love to answer any questions folks have about the approach taken or the
goals of the project.

~~~
thisjustinm
It might be worth reaching out to Joel at Open Snow
([http://opensnow.com/about/contact](http://opensnow.com/about/contact)) to
see if they'd be willing to share any of their historical weather data
(assuming it's what you need, I don't know the ins and outs of weather data
other than being an Open Snow user and knowing they have historical records
for snowfall for much of the US).

~~~
ryannevius
Open Snow pulls most of their SWE data from SNOTEL sites and NRCS reports.

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nicpottier
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
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.

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chasedehan
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:
[https://utahavalanchecenter.org/](https://utahavalanchecenter.org/) ?

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:
[https://utahavalanchecenter.org/avalanches/37960](https://utahavalanchecenter.org/avalanches/37960)

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.

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RHSman2
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.

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.

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starpilot
Browsed the repo a bit. From where do you get your surface-level forecast
data?

~~~
scottcha
The surface-level forecast data is the NAM model which I pull from NOAA.
Eventually I want to try the GFS (with a resolution tradeoff) or the EU models
(with a cost tradeoff).

