The International Urban Energy Balance Models Comparison Project: First Results from Phase 1

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 com- parison 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 ap- proaches 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

An integrated wind risk warning model for urban rail transport in Shanghai, China

The integrated wind risk warning model for rail transport presented has four elements: Background wind data, a wind field model, a vulnerability model, and a risk model. Background wind data uses observations in this study. Using the wind field model with effective surface roughness lengths, the background wind data are interpolated to a 30-m resolution grid. In the vulnerability model, the aerodynamic characteristics of railway vehicles are analyzed with CFD (Computational Fluid Dynamics) modelling. In the risk model, the maximum value of three aerodynamic forces is used as the criteria to evaluate rail safety and to quantify the risk level under extremely windy weather. The full model is tested for the Shanghai Metro Line 16 using wind conditions during Typhoon Chan-hom. The proposed approach enables quick quantification of real- time safety risk levels during typhoon landfall, providing sophisticated warning information for rail vehicle operation safety

Evaluating single-sided natural ventilation models against full-scale idealised measurements: impact of wind direction and turbulence

Commonly single-sided natural ventilation is used in temperate climates to provide comfortable and healthy indoor environments. However, within built-up areas it is difficult to predict natural ventilation rates for buildings as they depend on many flow factors and opening type. Here, existing models are evaluated using the nine-month Refresh Cube Campaign (RCC). Pressure-based ventilation rates were determined for a small opening (1% porosity) in a cubical test building (side=6 m). The building was isolated and then sheltered in a limited staggered building array to simulate turbulent flows in dense urban areas. Internal and external flow, temperature and pressure measurements captured a wide range of scales of variability. Although the Warren and Parkins (1985, WP85) model performed best for 30-minute mean ventilation rates, all four models tested underestimated ventilation rates by a factor of 10. As wind dominated the stack effect, new coefficients were derived for the WP85 wind-driven model as a function of wind angle. Predictions were mostly improved, except for directions with complex flow patterns during the sheltered case. For the first time, the relation between ventilation rate and turbulence intensity (TI) around a full-scale building was tested. Results indicate that the wind-driven model for single-sided ventilation in highly turbulent flows (0.5<TI<4) can be improved by including TI as a multiplicative factor. Although small window openings with highly turbulent flows are common for sheltered buildings in urban areas, future model development should include a variety of configurations to assess the generality of these results

Urban warming in villages

Long term meteorological records (> 100 years) from stations associated with villages are generally classified as rural and assumed to have no urban influence. Using networks installed in two European villages, the local and microclimatic variations around two of these rural-village sites are examined. An annual average temperature difference ($\Delta{T}$) of 0.6 and 0.4 K was observed between the built-up village area and the current meteorological station in Geisenheim (Germany) and Haparanda (Sweden), respectively. Considerably larger values were recorded for the minimum temperatures and during summer. The spatial variations in temperature within the villages are of the same order as recorded over the past 100+ years in these villages (0.06 to 0.17 K/10 years). This suggests that the potential biases in the long records of rural-villages also warrant careful consideration like those of the more commonly studied large urban areas effects

Modelling the partitioning of turbulent fluxes at urban sites with varying vegetation cover

Inclusion of vegetation is critical for urban land surface models (ULSM) to represent reasonably the turbulent sensible and latent heat flux densities in an urban environment. Here the Joint UK Land Environment Simulator (JULES), an ULSM, is used to simulate the Bowen ratio at a number of urban and rural sites with vegetation cover varying between 1% and 98%. The results show that JULES is able to represent the observed Bowen ratios, but only when the additional anthropogenic water supplied into the urban ecosystem is considered. The impact of the external water use (irrigation, street cleaning), for example, on the surface energy flux partitioning can be as substantial as that of the anthropogenic heat flux on the sensible and latent heat fluxes. The Bowen ratio varies from 1-2 when the plan area vegetation fraction is between 30% and 70%. However, when the vegetation fraction is less than 20%, the Bowen ratios increase substantially (2-10) and have greater sensitivity to assumptions about external water use. As there are few long term observational sites with vegetation cover less than 30%, there is a clear need for more measurement studies in such environments

Investigation of the impact of anthropogenic heat flux within an urban land surface model and PILPS-urban

Results from the first international urban model comparison experiment (PILPS-Urban) suggested that models which neglected the anthropogenic heat flux within the surface energy balance performed at least as well as models that include the source term, but this could not be explained. The analyses undertaken show that the results from PILPS-Urban were masked by the signal from including vegetation, which was identified in PILPS-Urban as being important. Including the anthropogenic heat flux does give improved performance, but the benefit is small for the site studied given the relatively small magnitude of this flux relative to other terms in the surface energy balance. However, there is no further benefit from including temporal variations in the flux at this site. The importance is expected to increase at sites with a larger anthropogenic heat flux and greater temporal variations

Key conclusions of the first international urban land surface model comparison project

he first international urban land surface model comparison was designed to identify three aspects of the urban surface-atmosphere interactions: (1) the dominant physical processes, (2) the level of complexity required to model these, and 3) the parameter requirements for such a model. Offline simulations from 32 land surface schemes, with varying complexity, contributed to the comparison. Model results were analysed within a framework of physical classifications and over four stages. The results show that the following are important urban processes; (i) multiple reflections of shortwave radiation within street canyons, (ii) reduction in the amount of visible sky from within the canyon, which impacts on the net long-wave radiation, iii) the contrast in surface temperatures between building roofs and street canyons, and (iv) evaporation from vegetation. Models that use an appropriate bulk albedo based on multiple solar reflections, represent building roof surfaces separately from street canyons and include a representation of vegetation demonstrate more skill, but require parameter information on the albedo, height of the buildings relative to the width of the streets (height to width ratio), the fraction of building roofs compared to street canyons from a plan view (plan area fraction) and the fraction of the surface that is vegetated. These results, whilst based on a single site and less than 18 months of data, have implications for the future design of urban land surface models, the data that need to be measured in urban observational campaigns, and what needs to be included in initiatives for regional and global parameter databases

An urban parameterization for a global climate model. Part I: Formulation and evaluation for two cities

Urbanization, the expansion of built-up areas, is an important yet less-studied aspect of land use/land cover change in climate science. To date, most global climate models used to evaluate effects of land use/land cover change on climate do not include an urban parameterization. Here, the authors describe the formulation and evaluation of a parameterization of urban areas that is incorporated into the Community Land Model, the land surface component of the Community Climate System Model. The model is designed to be simple enough to be compatible with structural and computational constraints of a land surface model coupled to a global climate model yet complex enough to explore physically based processes known to be important in determining urban climatology. The city representation is based upon the “urban canyon” concept, which consists of roofs, sunlit and shaded walls, and canyon floor. The canyon floor is divided into pervious (e.g., residential lawns, parks) and impervious (e.g., roads, parking lots, sidewalks) fractions. Trapping of longwave radiation by canyon surfaces and solar radiation absorption and reflection is determined by accounting for multiple reflections. Separate energy balances and surface temperatures are determined for each canyon facet. A one-dimensional heat conduction equation is solved numerically for a 10-layer column to determine conduction fluxes into and out of canyon surfaces. Model performance is evaluated against measured fluxes and temperatures from two urban sites. Results indicate the model does a reasonable job of simulating the energy balance of cities

Evaluation of the urban tile in MOSES using surface energy balance observations

The UK Met Office has introduced a new scheme for its urban tile in MOSES 2.2 (Met Office Surface Exchange Scheme version 2.2), which is currently implemented within the operational Met Office weather forecasting model. Here, the performance of the urban tile is evaluated in two urban areas: the historic core of downtown Mexico City and a light industrial site in Vancouver, Canada. The sites differ in terms of building structures and mean building heights. In both cases vegetation cover is less than 5%. The evaluation is based on surface energy balance flux measurements conducted at approximately the blend- ing height, which is the location where the surface scheme passes flux data into the atmo- spheric model. At both sites, MOSES 2.2 correctly simulates the net radiation, but there are discrepancies in the partitioning of turbulent and storage heat fluxes between predicted and observed values. Of the turbulent fluxes, latent heat fluxes were underpredicted by about one order of magnitude. Multiple model runs revealed MOSES 2.2 to be sensitive to changes in the canopy heat storage and in the ratio between the aerodynamic roughness length and that for heat transfer (temperature). Model performance was optimum with heat capacity values smaller than those generally considered for these sites. The results suggest that the current scheme is probably too simple, and that improvements may be obtained by increasing the complexity of the model

Surface and atmospheric driven variability of the single‐layer urban canopy model under clear‐sky conditions over London

Urban canopy models (UCMs) are parametrization schemes that are used to improve weather forecasts in urban areas. The performance of UCMs depends on understanding potential uncertainty sources that can generally originate from the (a) urban surface parameters, (b) atmospheric forcing, and (c) physical description. Here, we investigate the relative importance of surface and atmospheric driven model sensitivities of the single‐layer urban canopy model when fully interactive with a 1‐D configuration of the Weather Research and Forecasting model (WRF). The impact of different physical descriptions in UCMs and other key parameterization schemes of WRF is considered. As a case study, we use a 54‐h period with clear‐sky conditions over London. Our analysis is focused on the surface radiation and energy flux partitioning and the intensity of turbulent mixing. The impact of changes in atmospheric forcing and surface parameter values on model performance appears to be comparable in magnitude. The advection of potential temperature, aerosol optical depth, exchange coefficient and roughness length for heat, surface albedo, and the anthropogenic heat flux are the most influential. Some atmospheric forcing variations have similar impact on the key physical processes as changes in surface parameters. Hence, error compensation may occur if one optimizes model performance using a single variable or combinations that have potential for carryover effects (e.g., temperature). Process diagrams help differences to be understood in the physical description of different UCMs, boundary layer, and radiation schemes and between the model and the observations