How is my Heat Factor calculated?

Have more questions? Submit a request

Learn how property-specific heat risk is determined.

The expected change in average high temperature is influenced by the changing environment. A changing environment means higher average temperatures and increased humidity, which has a compounding effect on heat indexes, or “feels like” temperatures, that make risky health impacts more likely. As the global temperature rises at a faster rate than ever recorded, it's important to understand what factors contribute to heat risk.

A property's Heat Factor is an indicator of its risk to extreme heat exposure over the next thirty years.  The model assigns each property a Heat Factor, ranging from 1 (minimal risk) to 10 (extreme risk). Heat Factors are based on the current average daily high temperature and humidity of a property’s specific location during the hottest month of the year, and considers how it’s expected to grow over the next 30 years. Properties with higher Heat Factors have higher current, and/or future “feels like” temperatures.


The impact of the changing environment 

Climate change influences average high temperatures and increases humidity, causing heat risks to change. As average high temperatures increase around the globe, hot days increase in both frequency and intensity. Conservative estimates show that temperatures across the United States are projected to increase by at least 2.5 °F over the next 30 years. An increase in temperature can also lead to an increase in humidity in some areas. The First Street Foundation Extreme Heat Model (the model used by Heat Factor) uses the RCP 4.5 carbon emissions scenario to forecast how temperatures will change 30 years from now. This allows the model to predict temperatures 30 years from now in a way that meets the rigorous standard of scientific peer review.

Local variability

The amount of change in heat risk is influenced by local factors such as an area's landscape, vegetation, elevation, urbanization, and distance to water bodies and coastlines. These factors explain why some places will experience large changes in heat risk while others will experience more mild changes. For example, the urban heat island effect is a common example of how temperatures vary significantly. This effect describes how temperatures tend to be warmer in urban areas, compared to the more leafy, and less dense, suburban areas of a given city. 

Neighboring towns and cities can have very different temperatures due to local characteristics. It's easiest to identify local differences when temperatures are the warmest. For this reason, the model looks at temperatures and humidity during the hottest months of the year, which is July for most areas and in some areas August. Historic temperature records are used to create a map of average high temperatures across the U.S and compare how temperatures vary from property to property within a community. 

The calculation of property-specific Heat Factors 

Scoring system for properties 

Temperatures during the hottest month of the year are reviewed for each property’s specific location. For the majority of areas, the hottest month of the year is July and in some areas is August. The daily high “feels like” temperatures during this month are then averaged to determine the average high daily temperature for a property’s specific location this year, and 30 years into the future. Heat index, also known as a “feels like” temperature, is a measure used to indicate the level of discomfort the average person is thought to experience as a result of the combined effects of the temperature and humidity in the air.

This 30 year average high temperature represents how hot the specific location of a property is and how much the temperature is expected to change at that given location. Properties with higher Heat Factors have higher current, and/or future “feels like” temperatures during the summer months.

These temperatures are then compared to the safety thresholds for heat index informed by the National Weather Service. “Health caution” days are considered to be temperatures around 80°F and associated with relatively minor consequences, such as fatigue. Days above 125°F are considered “Extreme Danger” as they’re associated with life threatening effects such as heat stroke.

Heat Factor Scores

How hot a specific location is today and how much that temperature is expected to grow is used to determine the boundaries for each level of heat risk. These boundaries produce a set of rules that can be used to understand why one property may have a Heat Factor of 4 while another has a Heat Factor of 7. If the current average high temperature and the average high temperature in 30 years is:

Heat Factor

Temperature Boundaries


 Less than 80 °F


 80°F - 83°F


 83°F - 86°F


 86°F - 89°F


 89°F - 92°F


 92°F - 95°F


 95°F - 98°F


 98°F - 104°F


 104°F - 110°F


 Greater than 110°F

Ensuring scientific accuracy

The peer-reviewed First Street Foundation Extreme Heat Model is a first of its kind, nationwide, spatial temperature model that shows a specific location’s exposure to extreme heat events based on the temperature, topography, land cover, and humidity in the surrounding area. It builds off of decades of peer-reviewed research and forecasts how heat effects will change over time due to changes in the environment.

The development of the model required an unprecedented partnership with top climate scientists and modelers from leading organizations along with top data scientists and technologists to ensure the data is accessible, accurate and actionable. Where possible, data has been validated against historic temperature data and government records. All methods used by the First Street Foundation Extreme Heat Model have been submitted to scientific peer-review journals. Use Risk Factor to find property-specific heat risk assessments for any U.S. address.


Learn more

The methodology behind the model used by Heat Factor

Data sources used to determine Heat Factors

Heat Factor - Frequently asked questions (FAQ)

Articles in this section

Was this article helpful?
0 out of 0 found this helpful