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1. Regimes of Soil Moisture–Wet-Bulb Temperature Coupling with Relevance to Moist Heat Stress

   https://doi.org/10.1175/JCLI-D-23-0132.1  

   Kong, Qinqin ; Huber, Matthew ( November 2023 , Journal of Climate)

   Human heat stress depends jointly on atmospheric temperature and humidity. Wetter soils reduce temperature but also raise humidity, making the collective impact on heat stress unclear. To better understand these interactions, we use ERA5 to examine the coupling between daily average soil moisture and wet-bulb temperature (T_w) and its seasonal and diurnal cycle at global scale. We identify a global soil moisture–T_wcoupling pattern with both widespread negative and positive correlations in contrast to the well-established cooling effect of wet soil on dry-bulb temperature. Regions showing positive correlations closely resemble previously identified land–atmosphere coupling hotspots where soil moisture effectively controls surface energy partition. Soil moisture–T_wcoupling varies seasonally closely tied to monsoon development, and the positive coupling is slightly stronger and more widespread during nighttime. Local-scale analysis demonstrates a nonlinear structure of soil moisture–T_wcoupling with stronger coupling under relatively dry soils. Hot days with highT_wvalues show wetter-than-normal soil, anomalous high latent and low sensible heat flux from a cooler surface, and a shallower boundary layer. This supports the hypothesis that wetter soil increasesT_wby concentrating surface moist enthalpy flux within a shallower boundary layer and reducing free-troposphere-air entrainment. We identify areas of particular interest for future studies on the physical mechanisms of soil moisture–heat stress coupling. Our findings suggest that increasing soil moisture might amplify heat stress over large portions of the world including several densely populated areas. These results also raise questions about the effectiveness of evaporative cooling strategies in ameliorating urban heat stress.

   The purpose of this study is to provide a global picture of the relationship between soil moisture anomalies and a heat stress metric that includes the joint effects of temperature and humidity. This is important because a better understanding of this relationship will help improve the prediction of extreme heat stress events and inform strategies for ameliorating heat stress. We find a widespread positive correlation between soil moisture and heat stress, in contrast to studies relying on temperature alone. This raises the possibility that, over much of the world, and in the most populous regions, strategies like irrigation or “greening” that can reduce temperature might be ineffective or even harmful in reducing heat stress with humidity incorporated.

    

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2. Residential electricity demand on CAISO Flex Alert days: a case study of voluntary emergency demand response programs

   https://doi.org/10.1088/2753-3751/ad0fda  

   Peplinski, McKenna ; Sanders, Kelly T ( December 2023 , Environmental Research: Energy)

   The California Independent System Operator (CAISO) utilizes a system-wide, voluntary demand response (DR) tool, called the Flex Alert program, designed to reduce energy usage during peak hours, particularly on hot summer afternoons when surges in electricity demand threaten to exceed available generation resources. However, the few analyses on the efficacy of CAISO Flex Alerts have produced inconsistent results and do not investigate how participation varies across sectors, regions, population demographics, or time. Evaluating the efficacy of DR tools is difficult as there is no ground truth in terms of what demand would have been in the absence of the DR event. Thus, we first define two metrics that to evaluate how responsive customers were to Flex Alerts, including theFlex Period Response, which estimates how much demand was shifted away from the Flex Alert period, and theRamping Response, which estimates changes in demand during the first hour of the Flex Alert period. We then analyze the hourly load response of the residential sector, based on ∼200 000 unique homes, on 17 Flex Alert days during the period spanning 2015–2020 across the Southern California Edison (SCE) utility’s territory and compare it to total SCE load. We find that the Flex Period Response varied across Flex Alert days for both the residential (−18% to +3%) and total SCE load (−7% to +4%) and is more dependent on but less correlated with temperature for the residential load than total SCE load. We also find that responsiveness varied across subpopulations (e.g. high-income, high-demand customers are more responsive) and census tracts, implying that some households have more load flexibility during Flex Alerts than others. The variability in customer engagement suggests that customer participation in this type of program is not reliable, particularly on extreme heat days, highlighting a shortcoming in unincentivized, voluntary DR programs.

    

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3. A new method utilizing smart meter data for identifying the existence of air conditioning in residential homes

   https://doi.org/10.1088/1748-9326/ab35a8  

   Chen, Mo ; Sanders, Kelly T. ; Ban-Weiss, George A. ( August 2019 , Environmental Research Letters)

   Climate change, urbanization, and economic growth are expected to drive increases in the installation of new air conditioners, as well as increases in utilization of existing air conditioning (AC) units, in the coming decades. This growth will provide challenges for a diversity of stakeholders, from grid operators charged with maintaining a reliable and cost-effective power system, to low-income communities that may struggle to afford increased electricity costs. Despite the importance of building a quantitative understanding of trends in existing and future AC usage, methods to estimate AC penetration with high spatial and temporal resolution are lacking. In this study we develop a new classification method to characterize AC penetration patterns with unprecedented spatiotemporal resolution (i.e. at the census tract level), using the Greater Los Angeles Area as a case study. The method utilizes smart meter data records from 180 476 households over two years, along with local ambient temperature records. When spatially aggregated, the overall AC penetration rate of the Greater Los Angeles Area is 69%, which is similar to values reported by previous studies. We believe this method can be applied to other regions of the world where household smart meter data are available.

    

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4. Utilizing smart-meter data to project impacts of urban warming on residential electricity use for vulnerable populations in Southern California

   https://doi.org/10.1088/1748-9326/ab6fbe  

   Chen, Mo ; Ban-Weiss, George A. ; Sanders, Kelly T. ( May 2020 , Environmental Research Letters)

   Extreme heat events are increasing in frequency and intensity, challenging electricity infrastructure due to growing cooling demand and posing public health risks to urbanites. In order to minimize risks from increasing extreme heat, it is critical to (a) project increases in electricity use with urban warming, and (b) identify neighborhoods that are most vulnerable due in part to a lack of air conditioning (AC) and inability to afford increased energy. Here, we utilize smart meter data from 180 476 households in Southern California to quantify increases in residential electricity use per degree warming for each census tract. We also compute AC penetration rates, finding that air conditioners are less prevalent in poorer census tracts. Utilizing climate change projections for end of century, we show that 55% and 30% of the census tracts identified as most vulnerable are expected to experience more than 16 and 32 extreme heat days per year, respectively.

    

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5. The critical role of humidity in modeling summer electricity demand across the United States

   https://doi.org/10.1038/s41467-020-15393-8  

   Maia-Silva, Debora ; Kumar, Rohini ; Nateghi, Roshanak ( April 2020 , Nature Communications)

   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.

    

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