Additional
Solar in snowy and cold climates
What measured data say about cold, snow loss and panel wear, where production models fall short, and what to change if you live where it snows.
Written by HyreSolar Research team Research and analysis
Audited by HyreSolar Research team Data audit and fact check
The short answer
Cold is good for solar panels, and the evidence on that is stronger than you might expect. A study of silicon systems in cold climate zones found degradation at a median of 0.33% a year, against warm and temperate rates the same paper characterizes as running around 0.75 to 1.2% a year.
The authors suspect lower operating temperatures and reduced ultraviolet exposure outweigh the mechanical stresses of freeze-thaw and snow load, though they are careful to say suspect rather than demonstrate.
Snow is the real cost, and it is worse than the models say. Laboratory work states that snow-related losses "can exceed 30% of annual production" at northern latitudes and that winter-month losses reach "90% to 100% for some systems", while noting that snow models "tend to significantly underpredict snow losses".
The tool behind many residential estimates defaults snow loss to zero.
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The counterintuitive finding: cold is good for panels
The intuition is that a harsh climate is hard on equipment. Freeze-thaw cycling, snow load, wind, temperatures reaching minus forty. All of that sounds like it should shorten a system’s life.
The measurement points the other way. A study of 27 unique silicon photovoltaic systems in cold climate zones found degradation at a median of 0.33% a year and an average of 0.45%. The distribution "peaks at 0.1% to 0.2% per year but has a large tail with rates above 0.5%".
Set that against the comparison class the same paper cites: warm, hot and temperate climate degradation rates "ranging around 0.75 to 1.2% per year". Cold-climate systems in this sample degraded at roughly a third to a half the rate.
The paper also reports a separate US study with the same direction: the coolest temperature zone degraded at a median of 0.48% a year against 0.78% and 0.88% in two hotter zones, with the coolest zone corresponding roughly to the northern third of the continental United States.
The mechanism the authors propose, in their own hedged words: "the benefits of lower PV system operating temperatures and reduced UV-light exposure are suspected to outweigh these mechanical stresses". They say suspected. They do not claim to have demonstrated it, and we are not going to upgrade their language.
One reason this matters more than it sounds: a difference between 0.33% and 1.0% a year compounds. Over twenty-five years the first leaves a module at roughly 92% of its original output and the second at roughly 78%.
That is a large gap in the back half of a system’s life, and it lands in exactly the years a payback calculation is most sensitive to and least confident about.
We are not going to turn it into a savings figure, because the sample is small and the comparison class is drawn from other literature, but the direction is worth carrying.
Two limits belong with the finding. The sample is 27 systems, and the paper notes that systems with reported degradation rates in cold climates "are typically small rooftop deployments with less than 10 years of field exposure".
Three new subarctic sites in the same work varied between 0.4% and 1.5% a year, which is a wide spread on a small sample.
Snow is the real cost, and it is larger than assumed
If the panels last better, the offsetting problem is that they spend part of the year under snow, and the numbers here are substantial.
The bounding statement, verbatim: "Snow is a significant challenge for PV plants at northern latitudes, and snow-related power losses can exceed 30% of annual production."
That is a bound rather than a typical value and we are careful to present it that way, because the same sentence is frequently quoted as though it were an average.
Winter concentrates it. The same work summarizes the literature as showing "losses as high as 90% to 100% during winter months for some systems", and notes that this falls in "a period of high demand in snowy regions".
And the models are known to be optimistic. Snow cover models "can reduce error in generation predictions to as little as 7% during winter months, but reviews have demonstrated that these models tend to significantly underpredict snow losses if they do not reference current snow cover conditions".
Even detecting snow is hard. One algorithm developed to identify snow from inverter and temperature data "failed to detect a third of snow events" when compared against field data.
The field site behind that study is worth picturing. A northeastern US installation observed over 196 days, chosen because of the heavy snow losses its owners had seen. Over the observation period it experienced more than 100 inches of snowfall, and "persistent snow cover on panels was observed to last for weeks on end."
The model behind your quote assumes none of it
The tool many residential estimates are built on assigns a default snow loss of 0%.
Set that beside a laboratory statement that snow losses can exceed 30% of annual production at northern latitudes, and it becomes the single largest silent assumption in any northern quote.
This is not a flaw in the tool, which documents its defaults openly and is explicitly the simplified option. It is a problem with using its output as a promise.
If you are in a snowy region, the question to ask your installer is whether snow was modeled at all, and if so, on what basis. "The default" is an answer that means zero.
What actually changes snow loss, measured rather than assumed
Sandia runs a test facility in Michigan specifically to measure this, with side-by-side arrays differing in one variable at a time. Three of its findings are directly useful and one contradicts common advice.
Portrait against landscape barely matters. From a year of data: "Snow losses for a year show that both orientations perform equally well", and "orientation is not a large factor in snow losses" for the module types tested. If someone tells you to mount portrait for snow shedding, that is not what the measurement found.
Cell technology matters a little. Interdigitated back contact modules showed "4% lower snow losses than PERC", attributed to a lower cell breakdown voltage, three volts against twenty, and confirmed by circuit simulation. A real difference and a small one.
Frames matter most. Two side-by-side arrays identical except for the aluminum frame, over two winters: "When actual snow sliding rates differed between the framed and frameless PV modules, the snow shed more quickly from frameless PV modules 75% of the time."
An earlier single-winter study by the same team found the lack of a frame caused snow to shed roughly 50% more quickly.
The researchers are candid about the other quarter. In the 25% of cases where framed modules shed faster, "the cause of differences in shedding rate is not fully understood", and they conclude that "snow sliding remains to be somewhat difficult to predict".
There is a design lever the measurements do not cover and it is worth naming. Snow slides off a steeper pitch more readily than a shallow one, which bears on the ground mount or roof mount choice, and the shedding models take tilt angle as an input alongside temperature, irradiance and mounting configuration.
On a roof you do not get to choose the pitch, which is precisely why the ground-mounted literature is a poor guide here: a utility array at low fixed tilt and a residential roof at a steep pitch are different problems, and the residential one may well be the easier of the two.
The steer this supports is modest and real: if you are choosing between comparable modules in a snowy climate, the frame is the variable with the largest measured effect on shedding, and orientation is not worth arguing about.
What the measurements found, and how confident to be
| Variable | Measured effect | How firm |
|---|---|---|
| Frame | Frameless shed faster in 75% of cases where rates differed; an earlier study found roughly 50% faster | The largest measured effect, with the authors noting the remaining 25% is not understood |
| Cell technology | IBC showed 4% lower snow losses than PERC | Real and small, with a proposed mechanism confirmed by simulation |
| Portrait or landscape | Both orientations performed equally well | Directly contradicts common advice |
| Tilt, temperature, irradiance, mounting | All inputs to the shedding models | Modeled rather than isolated in these tests |
| Snow modeling generally | Models tend to significantly underpredict without current snow cover data | Stated as a review finding |
From Sandia National Laboratories snow program papers at its Michigan test facility. Read 3 September 2026.
Every row here is ground-mounted utility-scale or test-facility data. See the limitation below before applying any of it to a roof.
The limitation that governs this whole page
All of the snow measurement above is utility-scale or test-facility data on ground-mounted arrays. None of it measures a residential rooftop.
That matters because roofs differ in ways that cut both directions. A steeper residential pitch may shed snow better than a low-tilt utility array. A roof is higher, more exposed and less accessible. And critically, a homeowner cannot safely clear a roof, which removes an option a utility operator has.
So treat the direction as transferable and the numbers as not. Snow costs real production in northern climates, models underpredict it, frames slow shedding, and orientation does not matter much. What a specific roof loses in a specific winter is not something this literature can tell you.
What to do if you are in a snowy region
If the estimate used the default, it assumed zero snow loss. In a climate where losses can exceed 30% of annual production, that is the assumption most likely to make a projection wrong, and it is a one-sentence question.
An annual figure hides the shape. Winter losses reaching 90% to 100% for some systems means several months contributing almost nothing, which matters if you were counting on them.
It is the variable with the largest measured effect on shedding, and the effect was consistent in three quarters of cases where rates differed. It is a tiebreaker rather than a decisive factor.
The measurement found both orientations performed equally well. There may be other reasons to prefer one, and snow shedding is not among them on the evidence we read.
This is the one piece of advice on this page that is not about economics. A snow-covered pitched roof is among the most dangerous places a homeowner can stand, the array is energized whenever light reaches it, and the production you would recover is worth a fraction of the risk.
An annual figure averages away the season that concerns you. If the estimate cannot produce a December and January number, it has not modeled the thing you are asking about, and the difference between a light dusting that slides and cover lasting weeks is the difference between a nuisance and a real loss.
Cold-climate systems in the study degraded at roughly a third to a half the rate of warm-climate ones. Over twenty-five years that is a meaningful offset against winter losses, and it is the part of this that almost nobody mentions.
Method and limitations
What was read
A 2025 national laboratory paper on long-term photovoltaic system performance in cold, snowy climates, for the degradation findings, the comparison class, the proposed mechanism and the sample limitations.
Sandia National Laboratories papers from its snow program, for the annual and winter loss statements, the model underprediction finding, the detection algorithm result, the field site description, and the measured effects of orientation, cell technology and framing.
The PVWatts Version 5 manual for the zero snow default.
Two things to keep separate
The degradation finding and the snow finding come from different literatures and answer different questions. The cold-climate paper is about how fast panels lose capability over years, and it filters snow out by design.
The snow papers are about energy lost while panels are covered. Neither contradicts the other, and conflating them produces nonsense in both directions.
Cold climates being good for panel longevity is not the same as cold climates being good for annual output. Both things are true and they point opposite ways.
What we do not claim
No typical annual snow loss figure for a residential roof. The 30% statement is an explicit upper bound at utility scale, and no source we read gives a residential typical value.
No recommendation on snow removal equipment or services. We found no primary source evaluating any of it, and the safety consideration dominates the economics.
And no claim that the degradation mechanism is established. The authors wrote "suspected to outweigh" and we have kept their word.
Questions
Do solar panels work in cold climates?
How much production does snow cost?
Does my estimate account for snow?
Should I mount panels portrait for better snow shedding?
Do frameless panels shed snow better?
Should I clear snow off my panels?
Are snow loss models reliable?
Does the longevity benefit outweigh the snow losses?
Written and audited by
HyreSolar Research
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Data as of national laboratory papers read on 3 September 2026. Authorship on this site is organizational: the analysis belongs to the desk rather than to a named individual, and we do not publish credentials we do not hold. Our editorial policy sets out how we source, date and correct what we publish.
Sources & retrieval dates
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