• Energy Research

Abstract A large number of urban surface energy balance models now exist with different assumptions about the important features of the surface and exchange processes that need to be incorporated. To date, no comparison of these models has been conducted; in contrast, models for natural surfaces have been compared extensively as part of the Project for Intercomparison of Land-surface Parameterization Schemes. Here, the methods and first results from an extensive international comparison of 33 models are presented. The aim of the comparison overall is to understand the complexity required to model energy and water exchanges in urban areas. The degree of complexity included in the models is outlined and impacts on model performance are discussed. During the comparison there have been significant developments in the models with resulting improvements in performance (root-mean-square error falling by up to two-thirds). Evaluation is based on a dataset containing net all-wave radiation, sensible heat, and latent heat flux observations for an industrial area in Vancouver, British Columbia, Canada. The aim of the comparison is twofold: to identify those modeling approaches that minimize the errors in the simulated fluxes of the urban energy balance and to determine the degree of model complexity required for accurate simulations. There is evidence that some classes of models perform better for individual fluxes but no model performs best or worst for all fluxes. In general, the simpler models perform as well as the more complex models based on all statistical measures. Generally the schemes have best overall capability to model net all-wave radiation and least capability to model latent heat flux.

City thermal discomfort conditions have been exacerbated by the rapid urbanization processes in China. High-resolution urban thermal climate simulations can help us to understand urban climate features and produce better urban designs. In this paper, a single-layer urban canopy model (UCM) combined with Landsat satellite data and high-resolution meteorological forcing data was used to simulate very-high-resolution characteristics of temperature and humidity at the urban canopy level, and the heat index at the pedestrian level was also estimated. The research shows that the National center of environmental forecasting, Oregon state university, Air force and Hydrological research lab (NOAH)-UCM model can simulate the distribution of meteorological elements for different land uses in a fine and effective manner, making it an effective approach to obtaining the fundamental data for urban climate analysis. The spatial distribution pattern of urban heat islands in Suzhou is highly consistent with urban land cover fraction. High-density and medium-density urban areas are centers of urban heat islands, and the annual number of high-temperature days and heat indices over the high-density and medium-density urban areas are markedly higher than those in low-density cities and suburbs, indicating that urban development has a significant impact on the urban thermal environment.

AbstractUrban land surface schemes have been developed to model the distinct features of the urban surface and the associated energy exchange processes. These models have been developed for a range of purposes and make different assumptions related to the inclusion and representation of the relevant processes. Here, the first results of Phase 2 from an international comparison project to evaluate 32 urban land surface schemes are presented. This is the first large‐scale systematic evaluation of these models. In four stages, participants were given increasingly detailed information about an urban site for which urban fluxes were directly observed. At each stage, each group returned their models' calculated surface energy balance fluxes. Wide variations are evident in the performance of the models for individual fluxes. No individual model performs best for all fluxes. Providing additional information about the surface generally results in better performance. However, there is clear evidence that poor choice of parameter values can cause a large drop in performance for models that otherwise perform well. As many models do not perform well across all fluxes, there is need for caution in their application, and users should be aware of the implications for applications and decision making. Copyright © 2010 Royal Meteorological Society