Utah Avalanche Center asks for $750,000 to scale machine‑learning forecasts statewide

Representatives of the Utah Avalanche Center described a multiyear project to apply machine‑learning tools, additional weather stations and public data to expand forecasting and create detailed avalanche danger maps across more mountain ranges in Utah. The presenters said the project would give forecasters automated preprocessing, allow finer‑scale forecasts and make hazard information available for rural ranges that lack dense instrumentation.

The presenters estimated the project (excluding a later predictive‑analysis phase) at about $1 million and requested roughly $750,000 from the commission, with the remainder coming from partners such as the university, UDOT, the National Weather Service and international partners (Avalanche Canada, SLF) that already use similar models.

They argued the proposal advances public safety by enabling preventive search‑and‑rescue and dispersing recreation away from overcrowded trailheads. "If we can prevent one or two accidents... it saves search and rescue effort and lives," a presenter said. The proposal also envisions collecting data from resorts, weather stations and crowd‑sourced public observations to train models and produce state‑wide danger maps.

Commissioners and stakeholders praised the education and SAR benefits and asked about previous state allocations for avalanche infrastructure. Staff clarified certain capital allocations are earmarked for broader mobility investments but not yet committed to specific avalanche sheds. The Avalanche Center committed to follow up on partners' funding commitments and implementation timelines.

Next steps: UAC will provide a more detailed budget and partner match commitments; commissioners signaled support but did not vote on funding at the meeting.