The hours matter: comparing indicators of US residential cooling from hourly versus daily climate variables

Gesangyangji, G., Holloway, T., Vimont, D.J., Mastrucci, A. ORCID: https://orcid.org/0000-0002-5611-7780, Byers, E. ORCID: https://orcid.org/0000-0003-0349-5742, & Acker, S.J. (2025). The hours matter: comparing indicators of US residential cooling from hourly versus daily climate variables. Environmental Research Letters 20 (4) e044024. 10.1088/1748-9326/adbd54.

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Abstract

Cooling energy demand in buildings is rapidly increasing as climate warms. Current methods of estimating and predicting residential cooling demand are primarily based on daily temperature, which neglects intraday temperature variations. To determine whether large-scale cooling demand is substantially affected by intraday temperature variations, we conduct a thorough comparison between variable degree days (VDDs) derived from daily temperature data with variable degree hours (VDHs) derived from hourly temperature data during the summer seasons in the United States. The results imply that incorporating intraday variations in temperature will have substantial impacts on cooling estimation and prediction. A comparison of the historical (1990–2014) VDD and VDH calculated from ERA5 temperature data reveals that US summer cooling demand estimated from hourly temperature is 29%–45% higher than those estimated from daily temperature, with differences exceeding 60% when hourly solar radiation is considered. This occurs because the hourly calculations captures the ‘hot hours’ of the mild days. Future scenario analysis, using the NASA Earth Exchange Global Daily Downscaled Projections, indicates that under the medium greenhouse gas emissions pathway (SSP2-45), US summer VDH and VDD are expected to increase by approximately 45% and 100% by the late century (2081–2100). This suggests that, daily-based predictions generally project cooling demand growth at twice the rate of hourly-based predictions, as the daily method accounts for increases in both high and low temperatures regardless of whether they exceed the baseline, while the hourly method, with its finer temporal resolution, includes only temperatures that surpass the baseline. Such effects are seen across most areas of the US. Our analysis underscores the significance of incorporating temperature data at higher temporal resolution in estimating and predicting cooling demand, which is essential for effectively implementing various measures to achieve energy conservation and climate goals.

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