Abstract
Climate change is expected to decrease heating demand and increase cooling demand for buildings and affect outdoor thermal comfort. Here, we project changes in residential heating degree-days (HDD) and cooling degree-days (CDD) for the historical (1981–2010) and future (2080–2099) periods in the United States using median results from the Climate Model Intercomparison Project phase 5 (CMIP5) simulations under the Representation Concentration Pathway 8.5 (RCP8.5) scenario. We project future HDD and CDD values by adding CMIP5 projected changes to values based on historical observations of US climate. The sum HDD + CDD is an indicator of locations that are thermally comfortable, with low heating and cooling demand. By the end of the century, station median HDD + CDD will be reduced in the contiguous US, decreasing in the North and increasing in the South. Under the unmitigated RCP8.5 scenario, by the end of this century, in terms of HDD and CDD values considered separately, future New York, NY, is anticipated to become more like present Oklahoma City, OK; Denver, CO, becomes more like Raleigh, NC, and Seattle, WA, becomes more like San Jose, CA. These results serve as an indicator of projected climate change and can help inform decision-making.
Highlights
If the standard US base temperature[8,9,10,11] of 65 °F (18.3 °C) is used
We suggest that heating degree-days (HDD) and cooling degree-days (CDD) values are useful in helping to understand the magnitude[8] of climate change projected for the United States
In this work, using the latest US Climate Normals developed by the National Oceanic and Atmospheric Administration (NOAA)[31,32], along with state-of-the-art CMIP5 multi-model ensemble simulations[33], we find areas with the maximum and minimum combined degree-day sum for the historical (1981–2010) and future (2080–2099) periods under the unmitigated RCP8.5 climate scenario
Summary
If the standard US base temperature[8,9,10,11] of 65 °F (18.3 °C) is used. The most precise way to determine degree-days is to use the mean degree-hours method[9]; yet, if the weather data is limited to maximum and minimum daily temperatures, either the mean daily temperature approach[9] or the Meteorological Office equations[9] could be used, which give a lower per cent error[9] (see Methods). Even though the degree-day technique is associated with some limitations[9,12], it accurately captures the duration and severity of weather events[9,13], becoming a useful tool for evaluating residential heating and cooling demand, as well as outdoor thermal comfort. We focus only on heating and cooling degree-days, and do not evaluate the associated energy requirements or costs Assuming that they are mathematically defined in an internally consistent way, metrics such as HDD and CDD cannot be right or wrong; they can be more or less useful. The unweighted sum of HDD and CDD has previously been applied as an easy-to-understand indication of differences in heating and cooling demand[10,19] to provide an approximate comparative measure of outdoor thermal comfort at various locations in the US. In this work, using the latest US Climate Normals developed by the National Oceanic and Atmospheric Administration (NOAA)[31,32], along with state-of-the-art CMIP5 multi-model ensemble simulations[33], we find areas with the maximum and minimum combined degree-day sum for the historical (1981–2010) and future (2080–2099) periods under the unmitigated RCP8.5 climate scenario
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