Degree Days
Explore projected changes in Heating Degree Days and Cooling Degree Days, which are a common proxy for energy needed to heat and cool buildings, respectively.
Cooling Degree Days
Grid Cell near Sacramento, CA, USA
Emissions peak around 2040, then decline (RCP 4.5)
- This chart shows number of Cooling Degree Days in a year for the selected location and time period under the RCP 4.5 scenario.
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Four models have been selected by California’s Climate Action Team as priority models for research contributing to California’s Fourth Climate Change Assessment (Pierce et al., 2018). Projected future climate from these four models can be described as producing:
- A warm/dry simulation (HadGEM2-ES)
- A cooler/wetter simulation (CNRM-CM5)
- An average simulation (CanESM2)
- The model simulation that is most unlike the first three for the best coverage of different possibilities (MIROC5)
- The gray line (1950–2005) is observed data. The colored lines (2006–2100) are projections from 10 LOCA downscaled climate models selected for California. Use year sliders to get means for different time periods. The projected mean is calculated for all models with a ☑. Use slider below the chart to zoom and pan different time periods in the chart.
About the Tool
With this tool, you can explore how Cooling Degree Days (CDD) and Heating Degree Days (HDD), which are proxies for energy used to cool and heat buildings, are expected to change under different emissions scenarios and climate models. You can customize the metric for CDDs and HDDs by adjusting the baseline temperature as well as selecting the entire year or a specific portion of the year for inquiry.
The underlying data are derived from daily climate projections that have been downscaled from global climate models from CMIP5 archive, using the Localized Constructed Analogs (LOCA) statistical technique developed by Scripps Institution Of Oceanography. LOCA is a statistical downscaling technique that uses past history to add improved fine-scale detail to global climate models.
CDDs and HDDs are often used by utilities and other energy sector planners to understand energy demand for cooling and heating. As California’s climate changes, historical observed climate is becoming an increasingly poor proxy for future energy demand for cooling and heating. For example, an increase in the number and magnitude of hot days is expected to increase demand for air conditioning.
What is a Cooling Degree Day?
A Cooling Degree Day (CDD) is defined as the number of degrees by which a daily average temperature exceeds a reference temperature. The reference temperature is typically 65 degrees Fahrenheit, although different utilities and planning entities sometimes use different reference temperatures. The reference temperature loosely represents an average daily temperature below which space cooling (e.g., air conditioning) is not needed. The average temperature is represented by the average of the maximum and minimum daily temperature. CDDs can be summed over the entire year or over a portion of the year (e.g., the month of July) as a rough indicator of cooling energy over that period.
What is a Heating Degree Day?
A Heating Degree Day (HDD) is defined as the number of degrees by which a daily average temperature is below a reference temperature. The reference temperature is typically 65 degrees Fahrenheit, although different utilities and planning entities sometimes use different reference temperatures. The reference temperature loosely represents an average daily temperature above which space heating is not needed. The average temperature is represented by the average of the maximum and minimum daily temperature. HDDs can be summed over the entire year or over a portion of the year (e.g., the month of February) as a rough indicator of heating energy over that period.
Data Sources
LOCA Downscaled CMIP5 Projections
Scripps Institution Of Oceanography - University of California, San Diego
Daily climate projections for California at a resolution of 1/16° (about 6 km, or 3.7 miles) generated to support climate change impact studies for California’s Fourth Climate Change Assessment. The data, derived from 32 coarse-resolution (~100 km) global climate models from the CMIP5 archive, were bias corrected and downscaled using the Localized Constructed Analogues (LOCA) statistical method. The data cover 1950-2005 for the historical period and 2006-2100 (some models stop in 2099) for two future climate projections. Details are described in Pierce et al., 2018.
Gridded Observed Meteorological Data
University of Colorado, Boulder
Historical observed daily temperature data from approximately 20,000 NOAA Cooperative Observer (COOP) stations form the basis of this gridded dataset from 1950–2013 at a spatial resolution of 1/16º (approximately 6 km). Observation-based meteorological data sets offer insights into changes to the hydro-climatic system by diagnosing spatio-temporal characteristics and providing a historical baseline for future projections. Details are described in Livneh et al., 2015.
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