01
Defined mountain locations
From ski areas to passes, trailheads and backcountry zones, each supported place is treated as its own forecast entity.
Built in Steamboat Springs, Colorado
The mountain forecast, resolved.
Low Pressure Labs turns atmospheric guidance, terrain behavior and observed conditions into a more rigorous forecast for the mountain in front of you.
Forecast → observe → verify → learn.
What we build
Every mountain has its own relationship with the atmosphere.
Generic forecasts see a grid point. We build a persistent profile for each mountain location — its terrain, elevation, exposure, storm behavior, nearby observations, and verified forecast history.
02
Mountain Truth
We reconcile imperfect observations — including snow reports, water, temperature and timing — instead of assuming any one report is exact.
03
Useful uncertainty
Expected snowfall, likely range, timing and confidence should help people decide, not create false precision.
The LPL Forecast Platform
Built for the places generic forecasts miss.
LPL is designed around user-selected mountain locations, beginning with skiing and mountain recreation — where a small change in terrain, wind, elevation or temperature can materially change the day.
Mountain-specific forecasting
A forecast system that stays accountable to the mountain.
Every forecast is connected to its outcome. LPL preserves forecast history, estimates the most defensible observed result, and uses verification to refine future guidance.
Truth estimationSources are interpreted by what they measure and how reliable they are.
Adaptive forecastingModel weighting can vary by location, lead time and storm regime.
Verified learningNew approaches earn promotion only when held-out tests show improvement.
Forecast workspace
See the storm move through the mountain.
Atmospheric signals, terrain context and verified observations come together in one mountain-specific forecast view — so the decision is clear without forcing you to decode raw model output.
Snowfallsource-aligned accumulation windows
Timingwhen meaningful precipitation is expected
Confidenceagreement and uncertainty, shown plainly
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MOUNTAIN PROFILE
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OBSERVATION
Low Pressure Labs forecast workspaceIllustrative weather layers · live-source connection in progress
precipitation active cell
Why we're different
Forecasts accountable to what actually happened.
No forecast source is best everywhere. Low Pressure Labs measures forecast skill by mountain, lead time and storm regime, then uses that evidence to make its guidance more useful over time.
The Low Pressure Labs model layer
Forecast data in. Verified mountain intelligence out.
This is not a static blend of models. It is a verification-led system designed to improve only when real-world evidence supports the change.
1
Preserve forecast signalsArchive weather-model guidance, timing, temperature, wind and precipitation for a common forecast window.
2
Estimate Mountain TruthReconcile observations by location, timing, method, elevation, provenance and uncertainty.
3
Verify and learnMeasure residuals by mountain, lead time and storm regime; keep long-term learning separate from within-storm updates.
4
Promote only if betterCandidate improvements are benchmarked against prior LPL versions and external baselines before becoming production guidance.
Core principle: make the forecast accountable to the mountain. We will describe performance with measured validation data, not unsupported accuracy claims.
Our approach
Built for decisions made outside.
We combine atmospheric science, measurement discipline and product design. The objective is not to add another weather dashboard — it is to make uncertainty and local conditions useful to real people.
01 / Be honest
Make uncertainty useful, not invisible.
Good product design should reduce the cognitive work required to understand a forecast without pretending that the atmosphere is certain.
02 / Localize
Build for actual mountains and actual users.
Generic weather products optimize for broad coverage. We start with mountain decisions, then work backward to the observations and interface required.
03 / Verify
Keep a record of what was forecast and what occurred.
We believe a forecast system should retain an empirical history of its performance and its improvement over time.
04 / Improve
Promote learning only when it proves itself.
New models are challengers first. They should earn their place by improving held-out results without degrading what already works.
Steamboat Springs, CO
Born where low pressure is good news.
Low Pressure Labs is based in Steamboat Springs, Colorado. The mountains are more than our backdrop — they are the source of the observations, testing environment and real-world feedback that shape our work.
Our identity is inspired by the weather map itself: tightly packed isobars, a low-pressure center, and the idea that better interpretation comes from connecting forecast data to what actually happens outside.
Follow the build →Stay in the loop
Mountain weather, made more useful.
Get product updates, field-validation notes and a closer look at how Low Pressure Labs makes mountain weather more accountable to reality.
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