Cooling demand is projected to increase under climate change. However, most of the existing projections are based on rising air temperatures alone, ignoring that rising temperatures are associated with increased humidity; a lethal combination that could significantly increase morbidity and mortality rates during extreme heat events. We bridge this gap by identifying the key measures of heat stress, considering both air temperature and near-surface humidity, in characterizing the climate sensitivity of electricity demand at a national scale. Here we show that in many of the high energy consuming states, such as California and Texas, projections based on air temperature alone underestimates cooling demand by as much as 10-15% under both present and future climate scenarios. Our results establish that air temperature is a necessary but not sufficient variable for adequately characterizing the climate sensitivity of cooling load, and that near-surface humidity plays an equally important role.
Soaring temperatures and increased occurrence of heatwaves have drastically increased air‐conditioning demand, a trend that will likely continue into the future. Yet, the impact of anthropogenic warming on household air conditioning is largely unaccounted for in the operation and planning of energy grids. Here, by leveraging the state‐of‐the‐art in machine learning and climate model projections, we find substantial increases in future residential air conditioning demand across the U.S.—up to 8% with a range of 5%–8.5% (13% with a range of 11%–15%) after anthropogenic warming of 1.5°C (2.0°C) in global mean temperature. To offset this climate‐induced demand, an increase in the efficiency of air conditioners by as much as 8% (±4.5%) compared to current levels is needed; without this daunting technological effort, we estimate that some states will face supply inadequacies of up to 75 million “household‐days” (i.e., nearly half a month per average current household) without air conditioning in a 2.0°C warmer world. In the absence of effective climate mitigation and technological adaptation strategies, the U.S. will face substantial increases in air conditioning demand and, in the event of supply inadequacies, there is increased risk of leaving millions without access to space cooling during extreme temperatures.
Current projections of the climate-sensitive portion of residential electricity demand are based on estimating the temperature response of the mean of the demand distribution. In this work, we show that there is significant asymmetry in the summertime temperature response of electricity demand in the state of California, with high-intensity demand demonstrating a greater sensitivity to temperature increases. The greater climate sensitivity of high-intensity demand is found not only in the observed data, but also in the projections in the near future (2021-2040) and far future periods (2081-2099), and across all (three) utility service regions in California. We illustrate that disregarding the asymmetrical climate sensitivity of demand can lead to underestimating high-intensity demand in a given period by 37-43%. Moreover, the discrepancy in the projected increase in the climate-sensitive portion of demand based on the 50th versus 90th quantile estimates could range from 18 to 40% over the next 20 years. Electricity demand is influenced by many factors, including socio-demographic characteristics 4 , technology 5 , markets 6 , and climate 7-9. Here, we focus on understanding the climate sensitivity of residential electricity demand, which is a critical factor in ensuring the resilient operation of the grid under climate change 1-3. Recent work has isolated the effect of climate variability and change on both peak load (i.e., the highest load in a given time period) and total electricity consumption, indicating climate change will lead to greater electricity use, particularly in the residential sector 2,10-16. This has significant implications as unanticipated increases in cooling demand in the residential sector during heat waves (i.e., periods with sustained positive temperature anomalies) can lead to unexpected supply shortages 17 , distorted electricity market prices 18,19 , as well as increased morbidity and mortality 20 , particularly in vulnerable populations and disadvantaged communities 21. To minimize the economic and social costs of interrupted electricity service, researchers forecast the climatesensitive portion of residential electricity demand during extreme temperatures by harnessing methodologies from various fields, including econometrics 4,22,23 , engineering 23,24 , statistics and machine learning 13,15. However, the existing body of literature has primarily focused on modeling the temperature response of the central tendency (i.e., mean/median) of the demand distribution, as opposed to considering its entire distribution 2,25-27. We hypothesize that projections solely based on the mean/median values of the load distribution underestimate the climate sensitivity of high-intensity demand. Our central hypothesis is that while projections of the climate-demand nexus based on the mean/median values of demand distributions help to characterize the general trends in electricity use over time, they are likely inadequate in characterizing the climate sensitivity of the upper extremes of demand which are...
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