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Abstract In this study, we investigate the air temperature response to land-use and land-cover change (LULCC; cropland expansion and deforestation) using subgrid land model output generated by a set of CMIP6 model simulations. Our study is motivated by the fact that ongoing land-use activities are occurring at local scales, typically significantly smaller than the resolvable scale of a grid cell in Earth system models. It aims to explore the potential for a multimodel approach to better characterize LULCC local climatic effects. On an annual scale, the CMIP6 models are in general agreement that croplands are warmer than primary and secondary land (psl; mainly forests, grasslands, and bare ground) in the tropics and cooler in the mid–high latitudes, except for one model. The transition from warming to cooling occurs at approximately 40°N. Although the surface heating potential, which combines albedo and latent heat flux effects, can explain reasonably well the zonal mean latitudinal subgrid temperature variations between crop and psl tiles in the historical simulations, it does not provide a good prediction on subgrid temperature for other land tile configurations (crop vs forest; grass vs forest) under Shared Socioeconomic Pathway 5–8.5 (SSP5–8.5) forcing scenarios. A subset of simulations with the CESM2 model reveals that latitudinal subgrid temperature variation is positively related to variation in net surface shortwave radiation and negatively related to variation in the surface energy redistribution factor, with a dominant role from the latter south of 30°N. We suggest that this emergent relationship can be used to benchmark the performance of land surface parameterizations and for prediction of local temperature response to LULCC. 

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.

 

Subgrid data from earth system models are a powerful, yet underutilized, data resource for investigating the climatic impacts of land use and land cover change (LULCC). In this paper, we describe a global dataset on subgrid land surface climate variables produced by the Community Earth System Model in a fully coupled mode. The simulation was conducted at a 0.9° × 1.25° resolution under the Representative Concentration Pathway (RCP) 8.5 scenario from 2015 to 2100. Data are archived for eight subgrid tiles (urban, rural, tree, grass, shrub, bare soil, crop and lake) and include variables on the physical state, surface energy fluxes, runoff and atmospheric forcing conditions. Archival intervals are monthly, daily and hourly. Meta data on land surface parameters are also available. The data files are stored in NetCDF‐4 (Network Common Data Form, version 4) format and the meta data follow the latest Coupled Model Intercomparison Project phase 6 standards. We anticipate that this dataset will become a useful resource for characterizing local climate changes due to LULCC. This dataset can be downloaded from the Harvard Dataverse (https://doi.org/10.7910/DVN/HUXAH6).