Enhancing Urban Climate-Energy Modeling in the Community Earth System Model (CESM) Through Explicit Representation of Urban Air-Conditioning Adoption

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 (BEM), 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 a new parameterization scheme in CESM that represents AC adoption explicitly through an AC adoption rate parameter in the BEM of CLMU, and build a present-day, global, survey-based, and spatially explicit AC adoption rate data set at country and sub-country level that is integrated within CESM. The new data set can be leveraged for other ESMs or global-scale models and analyses. The explicit AC adoption scheme and the AC adoption rate data set 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. Human activities in cities, such as building energy use, need to be better represented in models designed to simulate urban climate around the world. The Community Land Model Urban is one such model that has been continuously improved, but still cannot effectively model varying air conditioning (AC) adoption rate across countries or regions. This limitation hinders the model's ability in simulating urban climate and building energy use. Here, we improve the model by developing a new explicit-AC-adoption parameterization that represents the proportions of buildings with AC systems, and constructing a global AC adoption rate data set at present-day for all countries and regions in the world. These improvements help the model simulate the air-conditioning energy use more accurately, and provide opportunities to evaluate the combined effects of climate change, population growth, and economic development on building energy use and climates for cities around the world. An explicit air-conditioning adoption scheme is developed for the building energy model in the Community Land Model Urban A global air-conditioning adoption rate data set is built for Community Earth System Model, with potential for use in other global-scale models and analyses The new scheme and data set greatly improve model performance and enable more comprehensive climate and energy risk assessments