DOI: 10.5281/zenodo.14695837
title: U-Surf: a global 1km spatially continuous urban surface property dataset for kilometer-scale urban-resolving Earth system modeling

description: High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth System Models (ESMs) and ultra-high-resolution urban climate modeling, particularly at large scales. Here, we present a first-of-its-kind 1km-resolution present-day (circa-2020) global continuous urban surface parameter dataset – U-Surf. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for developing dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet- and canopy-level. Our high-resolution U-Surf dataset significantly improves the representation of the urban land heterogeneity both within and across cities globally. U-Surf provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs, enables detailed city-to-city comparisons across the globe, and supports the next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf are also relevant as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to promote the research frontier on urban systems science, climate-sensitive urban design, and coupled human-Earth systems in the future.

The complete list of parameters is presented in the table below.




Category
Parameter
Notes


Radiative
Roof | Impervious | Pervious canyon floor | Wall emissivity
 


 
Roof | Impervious | Pervious canyon floor | Wall albedo
 


Morphological
Roof | Pervious fraction
Roof fraction is w.r.t. urban horizontal surface, and pervious fraction is w.r.t. canyon floor (i.e. pervious and impervious canyon floor).


 
Building height
Unit: m; Height of wind in the canyon is simply set as half of the building height in CLMU.


 
Canyon height-to-width ratio
 


 
Urban percentage
 


Thermal
Roof | Wall thickness
Unit: m


 
Roof | Impervious canyon floor | Wall thermal conductivity
Unit: W/m*K


 
Roof | Impervious canyon floor | Wall volumetric heat capacity
Unit: J/m^3*K


 
Number of impervious canyon floor layer
 


 
Minimum | Maximum interior building temperature
Unit: K


 
Air conditioning adoption rate
 




 

Radiative and morphological parameters are presented in the format of both .tif and .nc to accommodate different needs for the urban climate modeling community. Thermal parameters adapted from CLMU are available in a single .nc file. A CESM-compatiable surface dataset and a time-variant urban dataset (including P_AC and T_BUILDING_MAX; Li et al., 2024) at standard resolution (0.9375°x1.25°) are included for direct simulation use. Note that the urban percentage used to create the surface dataset comes from the PCT_URBAN parameter calculated in U-Surf, but users can input their own urban extent data to generate a customized surface dataset. The raw 1-km data can be easily aggregated/regridded to other resolution as needed.

 

Version 1.1 updates:

1. Fill part of the data gaps in Asia. 

2. Change the aggregation method of some parameters to be facet-area weighted in the 1deg surfdata.