How Much Snow Are We Going To Get? Snowfall Estimator

This calculator estimates likely snow accumulation by combining the expected liquid precipitation with a snow-to-liquid ratio (SLR) that depends on temperature, moisture, and elevation. A typical winter storm produces about 10 inches of snow per 1 inch of liquid water, but cold dry air can push that ratio above 20:1 while warm wet snow can fall closer to 6:1. For example, 0.4 inches of liquid precipitation at 25°F and moderate humidity often yields roughly 4 to 5 inches of accumulation in flat open areas.

You can also estimate the probability that snow will stick using surface temperature, dew point, and ground conditions. If the ground is above 35°F, early flakes may melt on contact even while air temperatures sit near freezing. The default numbers shown here are starting points, not hard limits — enter the values from your local forecast, and the tool will scale all outputs accordingly. A change from 28°F to 18°F, for instance, can lift the SLR from about 10:1 to 15:1 and raise total accumulation by 50%.

How it works: Enter expected liquid precipitation, air temperature, humidity, elevation, storm intensity, and ground surface conditions. The calculator picks a snow-to-liquid ratio based on temperature and moisture, multiplies it by your liquid precip, then adjusts for elevation and ground temperature to estimate accumulation and the probability of sticking.

Forecasting Snowfall in 2026: How to Estimate Accumulation Before the Storm

Snow totals depend on much more than just how much precipitation is in the forecast. The same 0.5 inches of liquid water can produce anywhere from 3 to 15 inches of snow depending on temperature, moisture, elevation, and ground conditions. This guide explains how meteorologists combine those factors and how you can do a quick mental estimate at home.

Typical snow-to-liquid ratio (SLR) by air temperature

How ground surface temperature affects sticking

Why liquid equivalent matters more than 'inches of snow'

Professional forecasters work in liquid equivalent — the melted water content of expected precipitation — because it is a far more stable physical quantity than snow depth. A storm carrying 0.6 inches of liquid water might fall as 4 inches of wet snow in coastal North Carolina but 12 inches of dry powder in the Colorado Rockies. Rule of thumb: take your forecast liquid precipitation and multiply by the expected SLR, which is usually between 8 and 20. If you only know snow depth, you can divide by the expected SLR to back out liquid.

How temperature sets the snow-to-liquid ratio

Temperature is the single biggest driver of snow density. Near 32°F, crystals partially melt and clump into heavy aggregates, giving ratios near 5:1 to 8:1. Between 15°F and 25°F, classic dendritic snowflakes form efficiently, producing the 'textbook' 10:1 to 13:1 ratio. Below 10°F, ice crystals are small and irregular and pack loosely, pushing ratios above 17:1. A common rule: every 10°F drop below freezing adds roughly 3 to 4 units to the SLR, until extreme cold dries the air so much that snowfall efficiency starts to fall.

The role of humidity and dew point

Moist storms with relative humidity above 90% often produce slightly denser snow because crystals collide and aggregate during their fall, squeezing out air. Drier mid-level air, common in upslope and lake-effect setups, tends to favor pristine, low-density crystals and higher SLRs. As a rule of thumb, reduce your expected SLR by about 10% if humidity is near saturation and the column is warm, and increase it 10–15% in genuinely dry, cold environments. Dew point also matters: a dew point well below freezing is a strong signal that any precipitation will fall and remain as snow.

Elevation and upslope enhancement

Elevation affects both temperature and moisture. As an air parcel rises about 1,000 feet, it cools roughly 3 to 5°F, which can shift a borderline rain event into all snow and push SLR upward. Mountains also force air to rise mechanically, wringing out more liquid precipitation than nearby valleys. A practical guideline: in upslope-favored terrain, expect 1.5 to 3 times the valley snow total for every 2,000 feet of elevation gain. Use the elevation input to nudge SLR up by 10–15% above 1,500 meters and even more in true alpine zones.

Ground temperature and the 'sticking' question

Whether snow sticks depends mostly on ground surface temperature, not air temperature. Pavement that has been baking in late-autumn sun can sit above 50°F even when air is 32°F, melting the first inch or two of snow until the surface cools. Grass loses heat faster and whitens first. Rule of thumb: if the ground is above 40°F, expect the first 1 to 1.5 inches of forecast snow to disappear into melt before any visible accumulation. Heavy snowfall rates above 1 inch per hour can overwhelm warm ground and stick anyway.

Storm intensity, duration, and drift

Two storms with identical totals can feel completely different. A 6-inch storm spread over 18 hours might leave roads passable; the same 6 inches in 3 hours overwhelms plows and pile-up rates exceed snow removal. Intensity also overwhelms warm ground: rates above 1 inch per hour suppress melt because incoming snow insulates the surface. Wind multiplies the impact through drifting — sustained winds above 25 mph can pile snow into drifts 3 to 5 times the storm average on the lee side of buildings, fences, and ridges, while scouring exposed areas down to bare ground.

How to sanity-check a forecast number

Before trusting any snow total, run three quick checks. First, divide the snow forecast by the liquid forecast and see if the implied SLR matches the expected temperature regime. Second, look at the ground temperature — totals near 35°F should usually be discounted 20–40% for melt. Third, compare the forecast to climatology: if your region averages 3 inches per storm in February, a forecast of 18 inches needs extraordinary support from moisture, dynamics, or upslope. The calculator above formalizes this same logic so you can stress-test any forecast in seconds.

How This Calculator Works: Methodology & Parameter Explanations

Core formula: snowfall = liquid_precip_mm × SLR(temperature, humidity, elevation, region) − ground_melt_loss; output_unit ∈ {in, cm}; conversions: in→mm ×25.4, ft→m ×0.3048, °F→°C (F−32)×5/9.

Parameter explanations

Assumptions

The numbers shown in the keyword (e.g. specific accumulation examples) are defaults for illustration only — the model recomputes from your actual inputs and is not hard-coded to any particular total.

Snow-to-liquid ratio is approximated from a single near-surface temperature; real storms can have multiple cloud layers with different crystal habits.

Ground melt loss is modeled as a fixed equivalent depth per ground band, modulated by storm intensity; this simplifies complex heat-flux physics.

Probability of sticking is a heuristic combining temperature, ground condition, and intensity, not a calibrated meteorological probability.

Wind, drifting, and compaction over time are not modeled — observed snow depth in drifts or after settling may differ substantially from the estimate.

Parameter meanings