Heating and Cooling Degree Days

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Caption: <p><b>Key Points: </b><br> Degree days reflect changes in climate and are used as an indicator for the energy demand for heating or cooling buildings (generally, fossil fuel demand for heating and electricity demand for cooling).<br> Since around 1980, the number of heating degree days has decreased and the number of cooling degree days has increased relative to the 20th century average. The recent increase in cooling degree days is driven by more frequent days above 65°F and more frequent extreme high temperatures. </p> <p></p><b>About the Indicator: </b> <br> Heating and cooling degree days are calculated by the National Oceanic and Atmospheric Administration (NOAA). Daily temperature values for each region of the United States are used to calculate departures from the 65°F baseline. These values are population-weighted using United States Census Bureau data, such that, for example, the same temperature produces more degree days in New York City than in rural Nebraska. </a> </p> <p><b>Why It's Important:</b> <ul><li> This indicator is used in utility planning and can support construction decisions. It provides information on the relationship between climate and energy use that can inform mitigation strategies. <li>As temperatures continue to rise, combined changes in heating and cooling degree days are projected to change patterns of energy use and increase net electricity demand nationwide. <br> </li><br> </p>

This panel, "Heating and Cooling Degree Days" is an original panel.

Analysis Methods and Tools

This figure panel was created using the following analysis methods:

1. NCEI calculated a monthly average heating degree day (HDD) and cooling degree day (CDD) for each climate division (each state within the contiguous 48 has up to 10 climate divisions; see: https://www.ncei.noaa.gov/access/monitoring/reference-maps/conus-climate-divisions) using climatologically aided interpolation to address topographic and network variability. This step is part of NCEI’s nClimDiv analysis, in which NCEI uses station data and interpolation between stations to create a 5-km grid across the contiguous 48 states for each variable in the dataset. Divisional averages are derived by averaging the grid cells within each climate division. This approach ensures that divisional SPI values are not biased towards areas that happen to have more stations clustered close together.
2. NCEI calculated monthly averages for each state by weighting the climate divisions by their population. With this approach, state HDD and CDD values more closely reflect the conditions that the average resident of the state would experience.
3. NCEI calculated monthly averages for the contiguous 48 states by weighting the divisions or states according to their population using the population data from the 2020 U.S. Census.
4. NCEI added each year’s monthly averages together to arrive at annual totals for the contiguous 48 states as a whole.

They used Microsoft Excel to analyze the data. The operating system macOS Ventura , Microsoft Windows 10 Enterprise was used to perform the analysis.

The data was visualized using the following methods:

1. The total number of nationally-averaged annual heating degree days (HDD) and cooling degree days (CDD) were plotted as a time series. CDD values were plotted in red and HDD values in blue. Note: Versions of this indicator prior to 2019 showed the change in heating and cooling degree days calculated relative to the 20th century (1901-2000) average. This updated presentation matches that used in the Fourth National Climate Assessment.
2. A legend and axes labels were added.

and with the following software:

Adobe Illustrator

These methods are not published. For more information please contact the analysis methods authoritative source(s) .

For full details, please download the full metadata record available on the “Full Record” tab.