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Importance of Spatially Continuous Urban Surface Properties in Urban-Resolving Earth System Modeling

  • University of Illinois at Urbana-Champaign
  • Pacific Northwest National Laboratory
  • Princeton University

Research output: Contribution to journal › Article › peer-review

1 Scopus citations

Abstract

Accurate representation of urban properties and processes at higher resolutions in global modeling systems is essential for advancing our ability to capture the complexities of urban systems and informing effective resilience strategies. However, the prescription of coarse global-scale urban properties in most state-of-the-art Earth system models (ESMs) is limiting their potential for capturing urban signals as they advance toward kilometer-scale simulation capabilities. To bridge this gap in inadequate urban property representation and to advance urban-resolving Earth system modeling, this work integrates the newly-developed global 1 km-resolution facet-level urban surface property data set, U-Surf, into the land component of Community Earth System Model (CESM)—Community Terrestrial System Model (CTSM). The land-only CTSM simulations are validated against satellite measurements, ground-based urban weather stations, flux tower observations, and reanalysis data. Results demonstrate that the enhanced urban properties allow improved simulations of urban meteorology and surface energy fluxes compared to the default coarse-resolution categorical urban canopy parameters. Spatial scaling analysis reveals regime-dependent information loss during resolution aggregation, as well as substantial scale-dependent variations in urban surface energy flux representation. These findings have critical implications for coupled Earth system modeling when including the effect of land-atmosphere interaction. This work establishes a foundation for future urban-resolving kilometer-scale ESM development, which will enable systematic intra- and inter-city comparisons that inform urban adaptation strategies across diverse global urban environments.

Original languageEnglish
Article numbere2025MS005573
JournalJournal of Advances in Modeling Earth Systems
Volume18
Issue number6
DOIs
StatePublished - Jun 2026

Funding

L.Z., Y.C. and J.Y. acknowledge the support by the U.S. National Science Foundation (CAREER Award Grant 2145362) and the Institute for Sustainability, Energy, and Environment at the University of Illinois Urbana-Champaign. L.Z. and Y.C. acknowledge the high-performance computing support from the Derecho system (https://doi.org/10.5065/qx9a-pg09) provided by the NSF National Center for Atmospheric Research (NCAR), sponsored by the National Science Foundation. L.Z. and T.C. also acknowledge the support by the U.S. National Aeronautics and Space Administration (NASA) through the AMT and LCLUC programs (Grant 80NSSC25K7322). T.C.'s contribution was also supported by the Earth and Environmental Systems Modeling program area of the U.S. Department of Energy (DOE) Office of Science's Biological and Environmental Research program through a DOE Early Career Award. The Pacific Northwest National Laboratory is operated for the DOE by the Battelle Memorial Institute under contract DE-AC05-76RL01830. K.O. acknowledges funding from the NSF National Center for Atmospheric Research, which is a major facility sponsored by the U.S. National Science Foundation under Cooperative Agreement No. 1852977. C.H. acknowledges the support by the NASA Land Cover Land Use Change (LCLUC) Grant 80NSSC25K7493 Subaward 2432603. K.Z. acknowledges support by the HMEI Environmental Fellows Program at Princeton University.

FundersFunder number
United States Department of EnergyDE-AC05-76RL01830
National Aeronautics and Space Administration80NSSC25K7322
National Science Foundation2145362, 1852977

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