• Energy Research

Abstract Many urban climates are characterized by increased temperature and decreased relative humidity, under climate change and compared to surrounding rural landscapes. The two trends have contrasting effects on human-perceived heat stress. However, their combined impact on urban humid heat and adaptation has remained largely unclear. Here, we use simulations from an earth system model to investigate how urbanization coupled with climate change affects urban humid heat stress, exposure, and adaptation. Our results show that urban humid heat will increase substantially across the globe by 3.1 °C by the end of the century under a high emission scenario. This projected trend is largely attributed to climate change-driven increases in specific humidity (1.8 °C), followed by air temperature (1.4 °C)—with urbanization impacts varying by location and of a smaller magnitude. Urban humid heat stress is projected to be concentrated in coastal, equatorial areas. At least 44% of the projected urban population in 2100, the equivalent of over 3 billion people worldwide, is projected to be living in an urban area with high humid heat stress. We show a critical, climate-driven dilemma between cooling efficacy and water limitation of urban greenery-based heat adaptation. Insights from our study emphasize the importance of using urban-explicit humid heat measures for more accurate assessments of urban heat exposure and invite careful evaluation of the feasibility of green infrastructure as a long-term cooling strategy.

AbstractAccurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban‐focussed land surface models in over a decade. Here, in Phase 1 of the Urban‐PLUMBER project, we evaluate the ability of 30 land surface models to simulate surface energy fluxes critical to atmospheric meteorological and air quality simulations. We establish minimum and upper performance expectations for participating models using simple information‐limited models as benchmarks. Compared with the last major model intercomparison at the same site, we find broad improvement in the current cohort's predictions of short‐wave radiation, sensible and latent heat fluxes, but little or no improvement in long‐wave radiation and momentum fluxes. Models with a simple urban representation (e.g., ‘slab’ schemes) generally perform well, particularly when combined with sophisticated hydrological/vegetation models. Some mid‐complexity models (e.g., ‘canyon’ schemes) also perform well, indicating efforts to integrate vegetation and hydrology processes have paid dividends. The most complex models that resolve three‐dimensional interactions between buildings in general did not perform as well as other categories. However, these models also tended to have the simplest representations of hydrology and vegetation. Models without any urban representation (i.e., vegetation‐only land surface models) performed poorly for latent heat fluxes, and reasonably for other energy fluxes at this suburban site. Our analysis identified widespread human errors in initial submissions that substantially affected model performances. Although significant efforts are applied to correct these errors, we conclude that human factors are likely to influence results in this (or any) model intercomparison, particularly where participating scientists have varying experience and first languages. These initial results are for one suburban site, and future phases of Urban‐PLUMBER will evaluate models across 20 sites in different urban and regional climate zones.

AbstractUrban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban‐PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators expecting better scoring models to capture the latent heat flux more accurately. We find that the water budget is only closed in 57% of the model‐site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all water balance indicators for any site. Models passing more indicators do not capture the latent heat flux more accurately refuting our hypothesis. While output reporting inconsistencies may have negatively affected model performance, our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest.

Improved representation of urban processes in Earth System Models (ESMs) is a pressing need for climate modeling and climate-driven urban energy studies. Despite recent improvements to its fully coupled building energy model, the current Community Land Model Urban (CLMU) in the Community Earth System Model (CESM) lacks the infrastructure to model air-conditioning (AC) adoption explicitly. This undermines CESM’s fidelity in modeling urban climate and energy use, and limits its use in climate and energy risk assessments. Here, we establish an explicit-AC-adoption parameterization scheme in CESM that represents AC adoption explicitly through an AC adoption rate parameter in the Building Energy Model of CLMU, and build a present-day, global, survey-based, and spatially explicit AC adoption rate dataset at country and sub-country level that is integrated within CESM. The new dataset can be leveraged for other ESMs or global-scale models and analyses. The explicit AC adoption scheme and the AC adoption rate dataset significantly improve the accuracy of anthropogenic heat modeling due to AC in CESM. The new parameterization scheme makes it possible to evaluate the effects of changing AC adoption on global urban energy and climate using CESM. These developments enhance CESM in its use for climate impact assessments under future climate and socioeconomic development scenarios, and represent continued efforts in better representing urban processes and coupled human-urban-Earth dynamics in ESMs.

This dataset contains the historical and future (SSP3 and RCP7.0) CESM climate simulations used in the article "Large humidity effects on urban heat exposure and cooling challenges under climate change" (upcoming). Further details about these simulations can be found in the article. This dataset documents the monthly mean projections of air temperature, wet-bulb temperature, precipitation, relative humidity, and numerous other climatic variables for 2000-2009 (for the historical run) and for 2015-2100 (for the future projection under SSP3-RCP7). This dataset may be useful for urban planners, climate scientists, and decision-makers interested in changes in urban and rural climate under climate change.