• Energy Research

AbstractAccurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban‐focussed land surface models in over a decade. Here, in Phase 1 of the Urban‐PLUMBER project, we evaluate the ability of 30 land surface models to simulate surface energy fluxes critical to atmospheric meteorological and air quality simulations. We establish minimum and upper performance expectations for participating models using simple information‐limited models as benchmarks. Compared with the last major model intercomparison at the same site, we find broad improvement in the current cohort's predictions of short‐wave radiation, sensible and latent heat fluxes, but little or no improvement in long‐wave radiation and momentum fluxes. Models with a simple urban representation (e.g., ‘slab’ schemes) generally perform well, particularly when combined with sophisticated hydrological/vegetation models. Some mid‐complexity models (e.g., ‘canyon’ schemes) also perform well, indicating efforts to integrate vegetation and hydrology processes have paid dividends. The most complex models that resolve three‐dimensional interactions between buildings in general did not perform as well as other categories. However, these models also tended to have the simplest representations of hydrology and vegetation. Models without any urban representation (i.e., vegetation‐only land surface models) performed poorly for latent heat fluxes, and reasonably for other energy fluxes at this suburban site. Our analysis identified widespread human errors in initial submissions that substantially affected model performances. Although significant efforts are applied to correct these errors, we conclude that human factors are likely to influence results in this (or any) model intercomparison, particularly where participating scientists have varying experience and first languages. These initial results are for one suburban site, and future phases of Urban‐PLUMBER will evaluate models across 20 sites in different urban and regional climate zones.

Differences in land surface characteristics across a city produce great spatial and temporal variability in air temperature. This fact is particularly pronounced between urban and surrounding rural areas giving rise to the canopy-layer urban heat island (CL-UHI) phenomenon. In the present study, we apply the dimensional analysis technique to develop a simple semi-empirical equation to map daily maximum CL-UHI (UHImax) intensities during nighttime over the city of Singapore for specific weather conditions. By adopting the methodology proposed by Theeuwes et al., but selecting meteorological and morphological parameters that affect UHImax intensity most for Singapore, evaluation of the developed equation shows good agreement with observations (RMSE = 1.13 K and IOA = 0.76). Model performance depends strongly on wind conditions and is best during weak winds when ‘ideal’ conditions for UHI development are approached (RMSE = 0.65 K and IOA = 0.85). Results using the simple equation developed to map UHImax intensities in Singapore under dry weather conditions are comparable to those obtained from more sophisticated numerical models, which demand significant computational resources, and the complex parameterizations involved require expertise to carry out the simulations. The resulting maps of the present study can be used to investigate less favorable thermal conditions and assess population vulnerability to a certain temperature excess, as well as provide insights for urban planning strategies of mitigation measures according to the land cover and morphology of a location.