Thermal comfort combines air temperature, radiation, wind and humidity into one felt temperature, the UTCI. A standard run uses the wind of the weather file for the whole site. The level with local wind gives each 1 m cell its own wind from our AI wind model, so sheltered courtyards and windy streets differ (how the physics levels work). Use Thermal Comfort Index to inspect UTCI over a selected window. Use Thermal Comfort Statistics to inspect how often a selected comfort condition occurs.
Step 1: Check the inputs
Open your project and select Data layers. Check buildings, trees, ground materials and the weather station or uploaded EPW file. Our example uses the same Vienna site as the first simulation guide.
Step 2: Set the weather and period
Select Add analysis, then Thermal Comfort Index or Thermal Comfort Statistics. Open the configure control in Selected. Review Weather & period and select Customize period.
Choose a weather preset or use Advanced for custom months and hours. Check the window on the cart row before you run. Auto is the app default window; do not assume that it means the full year.
Step 3: Read the UTCI result
Check the cart price, press Run, and open the completed card in Results. Read the run window first. The findings give the mean, highest map value, comfort zone and heat-stress share. The histogram shows the distribution across the site.
A map value can be an average over the selected hours. It is not necessarily the hottest hour. Keep the weather-file summary separate from the saved UTCI result. They can cover different periods.
Step 4: Read comfort frequency
Open the completed Thermal Comfort Statistics result. Read the selected mode and period. A comfortable-hours result shows the share of time within the comfort range. A heat-stress result answers a different question. Check the result label before you interpret its percentages.
Step 5: Compare the same conditions
Keep the weather, period and analysis settings the same across design options. Open Compare and choose Across scenarios. Total shows the result value; the difference and percentage modes compare it with the baseline.
Our Hong Kong example below illustrates the dashboard. It is a separate study, not a comparison with Vienna. Use the same colour scale and inspect the maps before you judge a difference. A smaller value is not better for every measure: read its purpose and units.