How Solar Irradiance Correlates with Payback Years Across US States
PlainSolarData measures the statistical correlation between average solar irradiance and modeled residential solar payback period across 51 US states, computed live from the current dataset.
Research period:
Research question
Across the 51 US states with a modeled payback period on record, how strongly does average solar irradiance predict how fast a representative residential solar system breaks even, and what other factors explain the gap?
Methodology
The correlation coefficient below is computed fresh from the current dataset every time this page loads (a standard Pearson correlation between each state's average solar irradiance and its modeled payback period), not a fixed figure typed in once and forgotten. When the underlying data refreshes, the coefficient and every chart on this page recompute automatically.
States missing either an irradiance figure or a payback figure are excluded from the correlation rather than shown with a placeholder value.
Every number on this page traces back to a specific state record, so you can verify it yourself against the state-by-state data. See the methodology page for the full data pipeline and how often we refresh.
Irradiance vs. modeled payback, all reporting states
Each dot is a state (n=51). Pearson r = -0.36 - a weak-to-moderate correlation.
Hawaii (highlighted) leads on payback at 5 years, not necessarily the sunniest state, since electricity rates and incentives move the outcome too.
Top 10 US States by Average Solar Irradiance
Live data, current as of the most recent source-data refresh
The fastest-payback 10
Every row below reflects the current dataset and updates automatically the next time we refresh it.
| # | State | Payback (yrs) | Irradiance (kWh/m²/day) | Electricity rate (¢/kWh) |
|---|---|---|---|---|
| 1 | Hawaii | 5 | 6 | 38 |
| 2 | California | 6 | 6 | 30 |
| 3 | Connecticut | 9 | 4 | 29 |
| 4 | Massachusetts | 9 | 4 | 28 |
| 5 | Maine | 9 | 4 | 26 |
| 6 | Rhode Island | 10 | 4 | 26 |
| 7 | New Hampshire | 10 | 4 | 26 |
| 8 | Arizona | 10 | 7 | 14 |
| 9 | New Mexico | 10 | 6 | 14 |
| 10 | New York | 11 | 4 | 22 |
Source: National Renewable Energy Laboratory, NREL Solar Resource Maps, joined against the site's modeled state payback dataset (51 states with both figures on record). Values are current as of our most recent data refresh. National Renewable Energy Laboratory, NREL Solar Resource Maps, joined against the site's modeled state payback dataset (51 states with both figures on record). Values are current as of our most recent data refresh.
Findings
The correlation is real but weak-to-moderate
Across the 51 states with both an irradiance figure and a modeled payback figure on record, the Pearson correlation coefficient between average solar irradiance and payback period is -0.36 - a weak-to-moderate relationship. Irradiance alone statistically accounts for roughly 13% of the state-to-state variation in payback; the remaining variation comes from factors this simple pairwise comparison does not hold constant. Directionally, more sunshine tends to associate with a shorter modeled payback, but the relationship is far from a straight line, the scatter chart above shows meaningful spread at every irradiance level.
Electricity rates are the visible confound
The fastest-payback state on record is Hawaii at 5 years, with an average irradiance of 6 kWh/m²/day, not necessarily the highest irradiance figure in the dataset. A high retail electricity rate raises the value of every kWh a rooftop system offsets, which can shorten payback even in a state with middling sunshine, while a low-rate state with strong sunshine can still show a longer payback because each offset kWh is worth less. The table above lists the electricity-rate column alongside irradiance and payback for each of the top 10 fastest-payback states.
What a weak-to-moderate correlation means for a household decision
A correlation coefficient this size is a population-level statistical description, not a household-level prediction. It says that irradiance is one real input among several, alongside electricity rates, installed cost per watt, and state/utility incentive stacking (see the incentive-count ranking) - and that no single factor dominates the outcome enough to predict payback from irradiance alone. The solar savings calculator models a specific state's full input set rather than irradiance in isolation.
Source provenance
Irradiance figures originate from the National Renewable Energy Laboratory's solar resource data. Payback figures are PlainSolarData's own modeled output (see the residential payback ranking for the full input set and its own limitations). PlainSolarData recomputes this correlation from the current dataset on every page load, so this page always reflects the current data rather than a fixed snapshot. The methodology page documents the source URLs, vintage, and transformation steps applied during ETL.
What this analysis cannot tell us
A correlation coefficient describes the strength and direction of a linear relationship between two variables across 51 states; it does not establish that irradiance causes a given payback period, and a coefficient this size leaves most of the state-to-state variation unexplained by irradiance alone. Retail electricity rates, state and utility incentive stacking, net-metering rules, and average installed cost per watt all vary independently of irradiance and are not held constant in this simple pairwise comparison, see the state-by-state table and the Solar Score ranking for a fuller comparison across those factors. State-level averages also mask real intra-state variation (a coastal fog belt vs. a high desert within the same state can differ by more than a full point of irradiance). Payback figures are modeled outputs for a representative 6 kW rooftop system, not a specific household's bill; see the residential payback ranking's own limitations for the full modeling assumptions.
Sources
- National Renewable Energy Laboratory, Solar Resource Maps and Data - https://www.nrel.gov/gis/solar.html
- U.S. Energy Information Administration, Average Retail Price of Electricity - https://www.eia.gov/electricity/monthly/epm_table_grapher.php