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NWS Heat Index: Method and Humidity Adjustments

Calculate the NWS heat-index estimate with its simple method, Rothfusz regression and humidity adjustments, keeping model limits visible.

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Inputs that matter
Air temperature (selected unit), Temperature unit, Relative humidity (%), Sources and assumptions
Output to expect
NWS heat-index method
  • Check the units and required inputs before comparing results.
  • Keep the assumptions with a copied result so you can reproduce the calculation later.
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Reference & details

How it works

NWS heat-index method

Apply the WPC/NWS sequence: calculate and temperature-average the simple estimate, then use the adjusted Rothfusz regression when that screening value reaches 80°F. This apparent-temperature model assumes shade and light wind; extremes outside the source data can produce unreliable regression output.

Use the simple estimate below its 80°F screening threshold; otherwise apply the Rothfusz polynomial and the specified low/high humidity adjustments.

Updated: September 2026

Example Scenarios

Use the example to inspect the method and breakdown, then enter your own documented observations or equipment data.

→ 99.677718°F apparent-temperature estimate

FAQ

Apply the WPC/NWS sequence: calculate and temperature-average the simple estimate, then use the adjusted Rothfusz regression when that screening value reaches 80°F. This apparent-temperature model assumes shade and light wind; extremes outside the source data can produce unreliable regression output.

Retain the measurement time and location, equipment or source document, units and assumptions. Examples illustrate the calculation and must be replaced with your own actual data before saving a personal case.

Use Save planning case for an explicit local history entry. Copy MD includes inputs and notes; Download CSV exports the result breakdown. Keep portable copies and save a separate case after changing the assumptions.

About NWS Heat Index: Method and Humidity Adjustments

Apply the WPC/NWS sequence: calculate and temperature-average the simple estimate, then use the adjusted Rothfusz regression when that screening value reaches 80°F. This apparent-temperature model assumes shade and light wind; extremes outside the source data can produce unreliable regression output.