Home heat explorer · Daily indoor heat estimator
How many days could
your home feel too hot?
Explore estimated hot days using real weather history, published climate projections and adjustable building assumptions. Move the year and emissions sliders to see how the result changes.
How often could indoors feel too hot?
Choose a temperature, then explore the climate and your building assumptions.
Example: Bristol weather, terraced-house assumptions. No postcode has been selected.
Illustrative starting points. Adjust them below to explore a different building.
Edit the building assumptions
These inputs describe a simplified whole-home thermal zone. They are assumptions, not facts inferred from your postcode.
Heat loss describes how readily heat passes through the building fabric. Thermal mass describes stored heat. Effective solar aperture combines glazing, orientation and transmission into one simplified input; it is not the measured window area.
Bristol example · Around 2050 · SSP2-4.5
per year
with indoor temperature above 26°C
A day counts once if the model exceeds your threshold in at least one hourly step. It does not mean the whole day is hot.
An illustrative building estimate using real weather and climate data. Not a measured result or a validated prediction for your property.
When could those days happen?
Average days per month above your temperature threshold.
How could that change over time?
Same emissions pathway and building assumptions.
Real climate data. A clearly defined building model.
What goes into the estimate?
We use 20 complete years of daily minimum and maximum outdoor temperature and solar radiation from NASA POWER (1995–2014). The postcode selects a coarse weather grid: roughly 0.5° × 0.625° for meteorology, with coarser solar data. This cannot resolve your street’s shade or urban heat island.
Future temperature changes come from the World Bank Climate Change Knowledge Portal: monthly UK-average CMIP6 ensemble-median changes in daily minimum and maximum temperature, relative to 1995–2014. Four published SSP pathways are available. UK-wide changes are applied to local weather; they are not local climate projections.
How do the sliders work?
The year represents climate around that date. Published periods are 2020–2039, 2040–2059, 2060–2079 and 2080–2099, shown as 2030, 2050, 2070 and 2090. We linearly interpolate monthly changes between them. The emissions slider selects a published pathway; we do not blend different pathways.
The model reconstructs an illustrative hourly temperature cycle from each day’s minimum and maximum. A single-zone heat balance then accounts for heat loss, thermal storage, solar and internal gains and ventilation. Days are counted from these simulated hourly temperatures, not converted from an overheating percentage.
Model assumptions, limitations and reproducibility
Model version 1.0. The whole home is represented by one temperature, with a 2.4m ceiling height and heating floor of 18°C; active cooling is off. Internal gains are 2 W/m² at night, 3 W/m² by day and 4 W/m² in the evening. Background ventilation is 0.5 air changes/hour. Selected night ventilation applies 22:00–07:00 only when indoors is above 22°C and the outdoor air is cooler.
Daily outdoor minima and maxima are reconstructed at 06:00 and 15:00 using smooth curves. Solar radiation is spread across calculated daylight hours and multiplied by the effective solar aperture and shading factor. The thermal balance uses an exact exponential step for constant hourly forcing. Building presets are illustrative assumptions, not calibrated archetypes. Rooms, humidity, orientation, occupant behaviour and future changes in solar radiation and weather variability are not individually modelled.
The headline is the mean annual count across 20 adjusted historical weather sequences, including leap years. The displayed range is their minimum and maximum. It excludes climate-model spread and building uncertainty, so it is not a prediction interval. Real homes may differ substantially. Use this for exploring sensitivities, not equipment sizing or regulatory compliance.
Inputs, monthly results, annual results, model version and source links are included in the downloadable estimate. Missing weather values cause an error rather than being filled with invented values.
Climate data: World Bank Climate Change Knowledge Portal / CMIP6, adapted under CC BY 4.0, retrieved 2026-10-23. Weather: NASA POWER, MERRA-2 and solar data products. NASA and the World Bank do not endorse this estimator.
Government reference: nighttime overheating in England & Wales
These published Environment Agency / DESNZ statistics measure nighttime hours above 26°C. They are separate from the experimental daily estimator above and cannot be converted into a count of hot days.
Bristol · All homes
Modelled median share of April–September nighttime hours above 26°C, without adaptations. These are area-level projections, not a forecast for a particular home.
What changes with adaptations?
Same area, home type and climate scenario
Chart scale: 0–20%. Lower values mean fewer modelled overheating hours.
The shading packages also include insulation and assumed air-conditioning uptake. Their results do not isolate the effect of blinds or shutters.
How do the future scenarios compare?
No adaptations · Your selected home type
Lower emissions · RCP2.6
Starting comparisonLower emissions · RCP2.6
1.7 percentage points higherHigh emissions · RCP8.5
A different emissions pathway2030 and 2050 share the same lower-emissions pathway. The 2080 scenario changes both the year and the pathway.
Compare home types in this area
2030 · Lower emissions · No adaptations
| Home type | This area | England & Wales | Area vs England & Wales |
|---|---|---|---|
| Detached house | 6.9% | 6.9% | No change to 1 decimal place |
| Semi-detached house | 13.8% | 13.7% | No change to 1 decimal place |
| Mid-terrace house | 16.3% | 14.1% | 2.2 percentage points higher |
| End-terrace house | 12.6% | 10.9% | 1.7 percentage points higher |
| Bungalow | 5.5% | 5.5% | No change to 1 decimal place |
| Low-rise flat | 16.5% | 15.5% | 1.0 percentage points higher |
| High-rise flat | 13.6% | 13.5% | 0.1 percentage points higher |
| Converted flat | 13.8% | 13.7% | 0.1 percentage points higher |
England & Wales uses the source’s national aggregation, compared with the same home type and climate scenario locally.
What the numbers mean
A result of 10% means that, for the modelled median home in that group, one tenth of nighttime hours in April–September exceeded 26°C. It does not mean 10% of homes overheat.
Changing the home type shows the model’s separate estimates for that category. Your glazing, shading, orientation, ventilation and construction can make your own home behave differently.
Compare scenarios carefully
2030 and 2050 use the lower-emissions RCP2.6 pathway. The 2080 result uses the high-emissions RCP8.5 pathway. Differences between 2050 and 2080 therefore reflect both time and emissions assumptions.
An empty category means the source has no figure for that selection. We keep it empty rather than substitute a nearby area or another type of home.
Sources, coverage and reuse
Source: Environment Agency / DESNZ: Overheating in Homes. This tool uses the published local-authority and home-type tables. It covers England and Wales; Scotland and Northern Ireland are not in this dataset.
We retrieved this edition on 20 October 2026. These are modelled future scenarios using a housing-stock model, not temperature readings, an assessment of your address or a prediction of which equipment you need.
Download the full data used here (CSV) · Government data catalogue · Research report
Contains Environment Agency information © Environment Agency copyright and/or database right 2024. Licensed under the Open Government Licence v3.0. Read the licence. Domestic Aircon’s presentation is independent of the government publisher.
Domestic Aircon Home Heat Explorer, using Environment Agency / DESNZ Overheating in Homes data, retrieved 20 October 2026. https://domestic-aircon.co.uk/tools/home-heat/