What’s in Your Snowpack?

The Value of Community Science Snow Observations

Article by David Hill, from the December 2020 Mazama

You don’t need to be a backcountry skier/rider or an alpinist to benefit from reliable information on the snowpack. Now, you probably are if you are reading this, so think about it for a minute…what do you typically want to know and where and when do you want to know it? You might be looking for an avalanche forecast right NOW, which requires site-specific information on the vertical structure and stability of the snowpack. You might be looking for less-detailed information on coverage in the near future– how long of a hike will you have from trailhead to snowline next weekend? Will the bergschrund at the base of the couloir you want to ski still be filled in two weeks from now? Will I have to wax for water again? And, could someone please tell me if the Pearly Gates will be in shape next month?

Well, even if the front country is more your style or (gasp!) you don’t even ski/ride/climb, you still benefit from information about the snow. Snowpack plays a huge role in regional water resources in the Pacific Northwest. Oregon and Washington each receive about 150 cubic kilometers of precipitation each year. In beer units, that’s 300 trillion pints of hoppy IPA, and a fair bit of that falls as snow. Water planners need regional-scale information on snow depth, density, and distribution in order to make accurate estimates of seasonal water yields months out into the future.

Meeting the information needs of these different user groups is a challenge because of these different spatial and temporal requirements. Fortunately, there are a lot of sources of snow data that can help, although they vary in terms of accuracy, coverage, and resolution. In-situ, or on the ground measurements have historically been the most common. These measurements include those made by personnel on the move in the field and also those at fixed, automated stations. An example of the former could be an avalanche forecaster, heli-ski guide, or ski patroller who records a measurement (pit profile, snow depth, snow density, etc.) in a database such as SnowPilot.

Fixed, automated snow telemetry (or SNOTEL) stations measure snow depth with an ultrasonic sensor and snow-water-equivalent (SWE) with a snow pillow, which is a fluid-filled bladder that measures pressure and therefore the weight of the overlying snowpack. In the western United States, we benefit from an incredible network of these stations, operated by the Natural Resources Conservation Service (NRCS). We have over 800 of these sites that are currently active, and many have periods of record of over 40 years. This is a gold mine of snow data that allows us to understand the current state of the snowpack and also how it has changed over the past several decades.

As if that was not good enough news, there are numerous remote sensing assets that are available to us. NASA has several missions that use airborne Light Detection and Ranging (LIDAR) to map snow depths in exquisite detail. At higher elevations still, there are many satellite missions (NASA, European Space Agency, etc.) that provide precise, high resolution images of snow cover and other snow-related information. The spatial coverage and the frequency of measurement vary among the different missions, and the measurements can be complicated by cloud cover and other environmental conditions.

Since no measurement campaign can measure everywhere, every time, computer modeling can be used to provide estimates on snowpack conditions at other places and times. At the national level, the National Operational Hydrologic Remote Sensing Center produces the Snow Data Assimilation System (SNODAS) data product, which has a 1 km spatial scale and a daily time step. SNODAS grids from 2003 up to today (it is an operational model) can be viewed at a number of websites including www.climateengine.org. The 1 km scale of SNODAS is fine for many applications such as water planning, but is too coarse to resolve local snow redistribution properties such as drifting and avalanching.

All of the data sources and modeling programs described above help snow scientists, snow safety professionals, and recreationists better understand the current state of the snowpack and also long-term (decadal scale) trends in snowpack characteristics. Opportunity still knocks, however. High-elevation regions of complex terrain are where most of the snow is found. However, that is not where the SNOTEL stations are. Due to the need for vehicular access for installation and maintenance, most SNOTEL sites are in areas of moderate elevation and gentle terrain.

The Community Snow Observations (CSO; communitysnowobs.org;
@communitysnowobs) project began in 2017 to test the idea that backcountry users could help to fill the data gaps that exist in high-elevation mountain areas. In concept, it’s a perfect match. Backcountry skiers, riders, and climbers cover long distances, thrive in high elevations and in complex terrain, and go far away from roads! The CSO vision was that data crowd-sourced by the backcountry community would then be assimilated into high-resolution snowpack models, and these model products could be returned to the public to be obsessed over while planning shenanigans for the coming weekend. In addition, the data would be used in collaborations with other NASA programs that focus on snow processes. So, if you’ve ever dreamed of being a rocket scientist and working with NASA, here’s your chance!

The idea of creating a large network of community scientists is not a new one. In the context of weather and snow observations, the Community Collaborative Rain, Hail and Snow Network (CoCoRaHS) has observers distributed throughout the United States who measure rainfall, snowfall, and hail. However, the CoCoRaHS project is largely a ‘backyard observer’ type program and does not sample high alpine environments. And, community science does have some challenges. The measurements are opportunistic and depend upon decisions made by the participants themselves. CSO can offer some suggestions and guidance, but ultimately must rely on the decisions made by its participants about where and when data come from. Another challenge has to do with data quality control. Tutorials are provided but, in the end, CSO recognizes that measurements are coming from a diverse body of contributors with differing levels of experience with data collection.

Participating in CSO is quick and easy. Depth measurements are made with an avalanche probe or other measuring device. Protocols on making measurements and selecting representative sites are provided on the CSO website. Your smartphone is the second piece of gear you need. Even if you’re out of cell range, the GPS on your phone knows where you are and what time it is, critical pieces of information for the project. Third, you need to have the Mountain Hub app on your phone. Mountain Hub was founded in 2015 with a vision of a crowd-sourced information network for the outdoors. Mountain Hub was acquired by Mammut in 2017 and then just this summer, the CSO project acquired it. Easy-to-follow tutorials on using the app are also found at our website. With just a bit of practice, you can stop, assemble your probe, log a measurement and be on your way in a few minutes. So, stopping to shed a layer? Pull out your probe and send in the data. Ripping skins at the start of a descent? The snow needs a few more minutes to corn up…pull out your probe, check the depth, and tell us all about it. Cooling your heels waiting for your out-of-shape partner to catch up? Might as well do some snow science while you wait…and wait.

Participation in CSO has grown steadily since the project started. We have had about 15,000 submissions from about 3000 unique users around the globe. Measurements to date have been dominated by North America, but we are starting to make inroads in other areas around the globe.

So, what’s in it for us? Well, CSO gets unique, high-elevation data that we get to study and share with NASA, and, as noted above, NASA gets to use these data points to validate many of their other snow measurements. But, community science should not be a one-way street. Successful community science projects are collaborative exchanges and CSO is invested in listening to our participants about ways to improve our project and also in delivering to our participants useful, timely information about snow in their region. The CSO project started up in Alaska and our model simulations there have demonstrated that data contributions from community scientists dramatically reduce errors in our snowpack models. Since then, as our project has grown, we have rolled out modeling efforts in many other areas in the western United States. The goal we are working toward is real-time, high-resolution snowpack information in all high elevation areas.

We named the project Community Snow Observations for a reason…community. Backcountry users who see the value in community science and who see the value in trading a bit of their time for the best available information on snow and water resources are the true core of CSO. There is no crowd-sourcing without the crowd and we sincerely hope you will participate this winter. Be sure to visit communitysnowobs.org, sign up for our email list, and follow us at @communitysnowobs on Twitter and Instagram for the latest project results and information. Have a great and safe season.

David Hill is a professor at Oregon State University and a National Geographic Explorer. For over 25 years, he has studied how water behaves from snowy mountain headwaters to coastal environments. He collaborates with other scientists interested in water’s response to climate drivers and works with stakeholders to provide information on water resources. He currently co-leads the Community Snow Observations project, a citizen science project funded by NASA to improve our understanding of our physical environment. Hill has also recently been an Erskine Fellow at the University of Canterbury, New Zealand. No matter the hemisphere, if it is springtime, you’ll find him out on skis sampling the snow between mountain summit and trailhead.