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Large underestimation of urban surface emissivities in an Earth system model

Presentation Date
Wednesday, December 13, 2023 at 8:30am - Wednesday, December 13, 2023 at 12:50pm
MC - Poster Hall A-C - South



Urbanization induces local warming and other climatic effects through modification of the biophysical properties of the surface, which are usually associated with severe socioeconomic implications. Numerical simulation serves as a valuable tool to study UHI and inform mitigation and adaptation policy, and is widely applied at local to regional scales. At the global scale, however, explicit representation of urban areas in Earth System Models (ESMs) is scarce. The Community Earth System Model (CESM) is one of the few ESMs with a physically based urban parameterization (Community Land Model Urban, CLMU) which adopts an urban canyon scheme and includes a building energy model to simulate the physical processes within cities, enabling the examination of urban climate under the context of global climate change. However, we find that the urban surface emissivity parameterized in CESM is considerably lower than observed by Moderate Resolution Imaging Spectroradiometer (MODIS), causing a substantial high bias in CESM’s simulated urban land surface temperature. This high bias will likely incur other bias errors in the simulated urban surface energy balance. Here we bias-correct the urban surface emissivity in the CESM globally against the MODIS emissivity observation. Simulation results using the new urban emissivity dataset shows significant improvement of accuracy in modeling the urban surface temperature globally. The simulated urban surface energy balance is further evaluated against 20 urban flux tower measurement sites. Our results suggest that the observation-based emissivity of urban surface may better represent urban landscapes’ effective emissivity than material-based emissivities from a surface energy balance perspective. Adopting these more realistic urban parameters in models will help improve the overall precision of urban climate modeling with ESMs.

Funding Program Area(s)