Urban Energy Balance Model Research Articles

Dynamics of urban latent heat in response to climate change and urbanization: What would be a global threshold?

Urban latent heat is influenced by climate change-induced greening, CO2 fertilization, and the urban heat island effect (Effect 1), which offsets reductions in latent heat caused by urbanization’s expansion of impermeable surfaces (Effect 2). The interaction between these effects remains unclear. The Hong Kong-Shenzhen region, characterized by a stable Leaf Area Index, intense anthropogenic activities, and abundant water resources, amplifies Effect 1. This region serves as an experimental site to explore global thresholds where these impacts reach equilibrium. Using Landsat and ERA5-Land data, monthly latent heat fluxes were computed from 1990 to 2019 using a stomatal process-based urban energy balance model. Shenzhen experienced a decline in latent heat (slope: −0.02), whereas Hong Kong showed an increase (slope: 0.08), confirming the presence of such thresholds. The region was segmented into 129 units, establishing a global benchmark indicating that Effect 1 significantly influences regional latent heat when the vegetation-to-impermeable surface ratio exceeds 2.71. Climate change impacts on Shenzhen’s latent heat increased by 94 %, compared to Hong Kong’s 55 %. Hong Kong demonstrates greater resilience to climate change than Shenzhen. This study underscores the importance of assessing urban dynamics for developing climate mitigation and sustainability strategies.

Evaluation of surface urban energy and water balance scheme (SUEWS) using scaled 2D model experiments under various seasons and sky conditions

Urban energy balance models are essential for better understanding of urban climate processes and mitigating urban heat island intensity. In this study, the Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated using scaled outdoor experiments of idealized city models consisting of street canyons (aspect ratio H/W = 2, H = 0.5) and hollow concrete building models, under various seasonal and sky conditions in a humid subtropical climate in 2020, using three evaluation approaches. The results indicate that the model effectively simulates net all-wave radiation (Q∗), with the coefficient of determination (R2) exceeding 0.970. Storage heat flux (ΔQS) derived from the Objective Hysteresis Model (OHM) is compared to those obtained from the residual term method (RTM) and element surface temperature method (ESTM), revealing the RTM tend to overestimate ΔQS compared to the observation-based ESTM. Compared to using default OHM coefficients, applying fitted OHM coefficients obtained under seasons and sky conditions improves the simulations of ΔQS and sensible heat flux (QH), reducing statistical errors by approximately 50% for ΔQS and increasing R2 in rainy summer from 0.353 to 0.793 for QH, respectively. Additionally, the improved available energy simulation suggests the importance of accurately partitioning between QH and latent heat flux (QE) for the future development of SUEWS.

Evaluation of a single-layer urban energy balance model using measured energy fluxes by scaled outdoor experiments in humid subtropical climate

Urban energy balance models can simulate the localized climate and fluxes in urban areas. They are often evaluated using real urban site observations. However, uncertainties in anthropogenic emission, geometry and materials can hinder interpretation. These uncertainties can be eliminated by scaled outdoor models. We assess the performance of a single-layer urban canopy model (SLUCM) offline in predicting surface energy balance (SEB) fluxes within a street canyon-like urban configuration using field measurements from a scaled outdoor setup in Guangzhou, China. We utilize observations of SEB fluxes and surface temperature from a homogenous scaled urban site characterized by street canyons. The scaled observations in June–December 2020 in a dense urban environment with a height-to-width ratio (H/W) of 2 are employed to assess seasonal variations in model performance. Additionally, the December data from two distinct urban scenarios (H/W = 2(2020) and 0.5(2019)) are utilized to compare model performance in deep and shallow street canyon settings. Results show that QS(R2 = ∼0.47, RMSE = ∼46.0) is the most challenging to predict, followed by QH (R2 = ∼0.92, RMSE = ∼65.5), Q*(R2 = ∼0.99, RMSE = ∼39.5), L↑(R2 = ∼0.95, RMSE = ∼33.7), and K↑(R2 = ∼0.99, RMSE = ∼6.2). SLUCM faces difficulties simulating L↑ particularly during nighttime and cloudy conditions. It also tends to underestimate daytime net radiation (Q*), especially during hot, humid months. Moreover, H/W ratio slightly affects SLUCM's performance in simulating SEB fluxes under dry cool conditions denser urban settings (H/W = 2) show better model performance in K↑, QH, and QS but worse performance in L↑ and Q*.

Evaluation of the SPARTACUS-Urban Radiation Model for Vertically Resolved Shortwave Radiation in Urban Areas

The heterogenous structure of urban environments impacts interactions with radiation, and the intensity of urban–atmosphere exchanges. Numerical weather prediction (NWP) often characterizes the urban structure with an infinite street canyon, which does not capture the three-dimensional urban morphology realistically. Here, the SPARTACUS (Speedy Algorithm for Radiative Transfer through Cloud Sides) approach to urban radiation (SPARTACUS-Urban), a multi-layer radiative transfer model designed to capture three-dimensional urban geometry for NWP, is evaluated with respect to the explicit Discrete Anisotropic Radiative Transfer (DART) model. Vertical profiles of shortwave fluxes and absorptions are evaluated across domains spanning regular arrays of cubes, to real cities (London and Indianapolis). The SPARTACUS-Urban model agrees well with the DART model (normalized bias and mean absolute errors < 5.5%) when its building distribution assumptions are fulfilled (i.e., buildings randomly distributed in the horizontal). For realistic geometry, including real-world building distributions and pitched roofs, SPARTACUS-Urban underestimates the effective albedo (< 6%) and ground absorption (< 16%), and overestimates wall-plus-roof absorption (< 15%), with errors increasing with solar zenith angle. Replacing the single-exponential fit of the distribution of building separations with a two-exponential function improves flux predictions for real-world geometry by up to half. Overall, SPARTACUS-Urban predicts shortwave fluxes accurately for a range of geometries (cf. DART). Comparison with the commonly used single-layer infinite street canyon approach finds SPARTACUS-Urban has an improved performance for randomly distributed and real-world geometries. This suggests using SPARTACUS-Urban would benefit weather and climate models with multi-layer urban energy balance models, as it allows more realistic urban form and vertically resolved absorption rates, without large increases in computational cost or data inputs.

A microscale three-dimensional model of urban outdoor thermal exposure (TUF-Pedestrian).

Urban street design choices relating to tree planting, building height and spacing, ground cover, and building façade properties impact outdoor thermal exposure. However, existing tools to simulate heat exposure have limitations with regard to optimization of street design for pedestrian cooling. A microscale three-dimensional (3D) urban radiation and energy balance model, Temperatures of Urban Facets for Pedestrians (TUF-Pedestrian), was developed to simulate pedestrian radiation exposure and study heat-reducing interventions such as urban tree planting and modifications to building and paving materials. TUF-Pedestrian simulates the spatial distribution of radiation and surface temperature impacts of trees and buildings on their surroundings at the sub-facet scale. In addition, radiation absorption by a three-dimensional pedestrian is considered, permitting calculation of a summary metric of human radiation exposure: the mean radiant temperature (TMRT). TUF-Pedestrian is evaluated against a unique 24-h observational dataset acquired using a mobile human-biometeorological station, MaRTy, in an urban canyon with trees on the Arizona State University Tempe campus (USA). Model evaluation demonstrates that TUF-Pedestrian accurately simulates both incoming directional radiative fluxes and TMRT in an urban environment with and without tree cover. Model sensitivity simulations demonstrate how modelled TMRT and directional radiative fluxes respond to increased building height (ΔTMRT reaching -32°C when pedestrian becomes shaded), added tree cover (ΔTMRT approaching -20°C for 8m trees with leaf area density of 0.5 m2m-3), and increased street albedo (ΔTMRT reaching + 6°C for a 0.21 increase in pavement albedo). Sensitivity results agree with findings from previous studies and demonstrate the potential utility of TUF-Pedestrian as a tool to optimize street design for pedestrian heat exposure reduction.

Remote sensing and energy balance modeling of urban climate variability across a semi-arid megacity

Local and regional urban surface heterogeneity produces diverse urban climates, significantly impacting water use, energy consumption, and human health. This study examines urban energy flux variability across landcover and climate gradients for 2123 km2 of urbanized Los Angeles County, USA, by using high resolution remote sensing combined with spatially distributed simulations with an urban energy balance model, covering the complete diurnal cycle of the remote sensing flights. Localized parameters, including landcover, plant type, albedo, building and tree height, and irrigation, were derived from hyperspectral and LiDAR imagery, and GIS. Modeled latent heat fluxes (LE) were linearly correlated with measured land surface temperature at the neighborhood scale (R2 = 0.51), and modeled Bowen ratio values closely agreed with previous values derived from eddy covariance observations. LE across the region displayed spatial and temporal responses to irrigation and regional climate. Peak LE occurred 3 h before solar noon, driven by early morning irrigation characteristic of the region. This suggests that schedule-based water conservation policies could reduce the cooling capacity of urban vegetation in late afternoon. Additionally, a negative effect of distance from the coast on LE was observed to strengthen through the day, reducing LE in interior areas relative to coastal areas.

Urban surface temperature observations from ground-based thermography: intra- and inter-facet variability

Ground based thermal cameras are used to observe urban surface temperatures (Ts) with an unprecedented combination of: temporal and spatial resolution (5 min and ~ 0.5 m → 2.5 m), spatial extent (3.9 ha), instrument number (6 static cameras) and surface heterogeneity (mixed high rise and vegetation). Unsupervised classification of images by geometry and material properties (surface orientation, albedo, solar irradiance, and shadow history) is facilitated by a detailed three-dimensional surface model (430 m × 430 m extent) and sensor view modelling. From detailed source area analysis, 9.5% of the area is observed by the cameras. Across all camera pixels, the 5th - 95th percentile Ts differences reach 37.5 K around midday. Roofs have the greatest diurnal Ts range (290.6 K → 329.0 K). Ts differences across sunlit sloped roofs reach 23.3 K. Walls of different cardinal orientations consistently differ by >10 K between 10:00 and 15:00. Shadow tracking within images is used to model cooling rates, where recently shaded (<30 min) ground can be 18.6 K warmer than equivalent unshaded Ts. West walls remain warm past sunset and are 1.2 K warmer than north walls at 23:00 (~4 h after sunset). Recently shaded walls cool exponentially to ambient Ts at a similar rate as the ground, but four times slower than roofs. The observed Ts characteristics are anticipated to have a wide range of applications (e.g. evaluation of urban surface energy balance models, ground-truthing of satellite thermal remote sensing).

Short and medium- to long-term impacts of nature-based solutions on urban heat

Many cities are growing and becoming more densely populated, resulting in land use changes, which promotes an increase in urban heating. Nature-based solutions (NBS) are considered sustainable, cost-effective and multi-purpose solutions for these problems. While various studies assess the effects of NBS on urban heat or urban sprawl/compaction, no studies assess their cumulative effect. The main objective of this study is to assess the short-term and medium- to long-term impacts of NBS on urban heat fluxes, taking as a case study the city of Eindhoven in The Netherlands. An integrated modelling approach, composed of a coupled meteorological and urban energy balance model (WRF-SUEWS) and an hedonic pricing simulation model (SULD), is used to assess urban heat fluxes and urban compaction effects, respectively. Results show that, in the short-term, NBS have a local cooling effect due to an increase in green/blue spaces and, in the medium to long-term, an urban compaction effect due to attraction of residents from peripheral areas to areas surrounding attractive NBS. This study provides evidence that NBS can be used to reduce the effects of urban heating and urban sprawl and that an integrated modelling approach allows to better understand its overalleffects.

Atmospheric and emissivity corrections for ground-based thermography using 3D radiative transfer modelling

Methods to retrieve urban surface temperature (Ts) from remote sensing observations with sub-building scale resolution are developed using the Discrete Anisotropic Radiative Transfer (DART, Gastellu-Etchegorry et al., 2012) model. Corrections account for the emission and absorption of radiation by air between the surface and instrument (atmospheric correction), and for the reflected longwave infrared (LWIR) radiation from non-black-body surfaces (“emissivity” correction) within a single modelling framework. The atmospheric correction a) can use horizontally and vertically variable distributions of atmosphere properties at high resolution (<5 m); b) is applied here with vertically extrapolated weather observations and MODTRAN atmosphere profiles; and c) is a solution to ray tracing and cross section (e.g. absorption) conflicts (e.g. cross section needs the path length but it is typically unavailable during ray tracing). The emissivity correction resolves the reflection of LWIR radiation as a series of scattering events at high spatial (<1 m) and angular (ΔΩ ≈ 0.02 sr) resolution using a heterogeneous distribution of radiation leaving the urban surfaces. The method is applied to a novel network of seven ground-based cameras measuring LWIR radiation across a dense urban area (extent: 420 m × 420 m) where a detailed 3-dimensional representation of the surface and vegetation geometry is used. Our unique observation set allows the method to be tested over a range of realistic conditions as there are variations in: path lengths, view angles, brightness temperatures, atmospheric conditions and observed surface geometry. For pixels with 250 (±10) m path length the median (5th and 95th percentile) atmospheric correction magnitude is up to 4.5 (3.1 and 8.1) K at 10:10 on a mainly clear-sky day. The detailed surface geometry resolves camera pixel path lengths accurately, even with complex features such as sloped roofs.The atmospheric correction method evaluation, with simultaneous “near” (~15 m) and “far” (~155 m) observations, has a mean absolute error of 0.39 K. Using broadband approximations, the emissivity correction has clear diurnal variability, particularly when a cool and shaded surface (e.g. north facing) is irradiated by warmer (up to 17.0 K) surfaces (e.g. south facing). Varying the material emissivity with bulk values common for dark building materials (ε = 0.89 → 0.97) alters the corrected roof (south facing) surface temperatures by ~3 (1.5) K, and the corrected cooler north facing surfaces by less than 0.1 K. Corrected observations, assuming a homogeneous radiation distribution from surfaces (analogous to a sky view factor correction), differ from a heterogeneous distribution by up to 0.25 K. Our proposed correction provides more accurate Ts observations with improved uncertainty estimates. Potential applications include ground-truthing airborne or space-borne surface temperatures and evaluation of urban energy balance models.

Coupling of urban energy balance model with 3-D radiation model to derive human thermal (dis)comfort

While capabilities in urban climate modeling have substantially increased in recent decades, the interdependency of changes in environmental surface properties and human (dis)comfort have only recently received attention. The open-source solar long-wave environmental irradiance geometry (SOLWEIG) model is one of the state-of-the-art models frequently used for urban (micro-)climatic studies. Here, we present updated calculation schemes for SOLWEIG allowing the improved prediction of surface temperatures (wall and ground). We illustrate that parameterizations based on measurements of global radiation on a south-facing vertical plane obtain better results compared to those based on solar elevation. Due to the limited number of ground surface temperature parameterizations in SOLWEIG, we implement the two-layer force-restore method for calculating ground temperature for various soil conditions. To characterize changes in urban canyon air temperature (Tcan), we couple the calculation method as used in the Town Energy Balance (TEB) model. Comparison of model results and observations (obtained during field campaigns) indicates a good agreement between modeled and measured Tcan, with an explained variance of R2 = 0.99. Finally, we implement an energy balance model for vertically mounted PV modules to contrast different urban surface properties. Specifically, we consider (i) an environment comprising dark asphalt and a glass facade and (ii) an environment comprising bright concrete and a PV facade. The model results show a substantially decreased Tcan (by up to − 1.65°C) for the latter case, indicating the potential of partially reducing/mitigating urban heat island effects.

Development of the VTUF-3D v1.0 urban micro-climate model to support assessment of urban vegetation influences on human thermal comfort

With urban areas facing longer duration heat-waves and temperature extremes from climate change and growing urban development, adaptation strategies are needed to protect city residents. Examining the role that increased tree cover and water availability can have on human thermal comfort (HTC) is needed to help guide the development of thermally comfortable cities. To inform planning, modelling tools are needed that provide sufficient resolution to resolve urban influences on HTC and the ability to model important physiological processes of vegetation. To achieve this, a new micro-scale model, VTUF-3D (Vegetated Temperatures of Urban Facets) has been developed. In it, offline modelling of individual items of vegetation is performed using the MAESPA process-based tree model (Duursma and Medlyn, 2012) (a model that can model individual trees, vegetation, and soil components), and integrated into the TUF-3D (Krayenhoff and Voogt, 2007) urban micro-climate surface energy balance (SEB) model. This innovative approach allows the new model to account for important vegetative physiological processes and shading effects, using configurable templates to allow representation of any type of vegetation or water sensitive design feature. This work enables detailed calculations of surface temperatures (Tsfc), mean radiant temperature (Tmrt), and a HTC index, the universal thermal climate index (UTCI), across urban canyons. This study presents an overview of VTUF-3D. Also presented are two evaluations of VTUF-3D. The first evaluation compares modelled surface energy balance fluxes to observations in Preston, Australia (Coutts et al., 2007). The second evaluation compares spatial and temporal predictions of Tmrt and UTCI to two observed street canyons in the City of Melbourne (Coutts et al., 2015b). The VTUF-3D model is shown to perform well and is suitable for use to examine critical questions relating to the role of vegetation and water in the urban environment in support of HTC.

Impacts of Realistic Urban Heating, Part I: Spatial Variability of Mean Flow, Turbulent Exchange and Pollutant Dispersion

As urbanization progresses, more realistic methods are required to analyze the urban microclimate. However, given the complexity and computational cost of numerical models, the effects of realistic representations should be evaluated to identify the level of detail required for an accurate analysis. We consider the realistic representation of surface heating in an idealized three-dimensional urban configuration, and evaluate the spatial variability of flow statistics (mean flow and turbulent fluxes) in urban streets. Large-eddy simulations coupled with an urban energy balance model are employed, and the heating distribution of urban surfaces is parametrized using sets of horizontal and vertical Richardson numbers, characterizing thermal stratification and heating orientation with respect to the wind direction. For all studied conditions, the thermal field is strongly affected by the orientation of heating with respect to the airflow. The modification of airflow by the horizontal heating is also pronounced for strongly unstable conditions. The formation of the canyon vortices is affected by the three-dimensional heating distribution in both spanwise and streamwise street canyons, such that the secondary vortex is seen adjacent to the windward wall. For the dispersion field, however, the overall heating of urban surfaces, and more importantly, the vertical temperature gradient, dominate the distribution of concentration and the removal of pollutants from the building canyon. Accordingly, the spatial variability of concentration is not significantly affected by the detailed heating distribution. The analysis is extended to assess the effects of three-dimensional surface heating on turbulent transfer. Quadrant analysis reveals that the differential heating also affects the dominance of ejection and sweep events and the efficiency of turbulent transfer (exuberance) within the street canyon and at the roof level, while the vertical variation of these parameters is less dependent on the detailed heating of urban facets.

Effects of Roof-Edge Roughness on Air Temperature and Pollutant Concentration in Urban Canyons

The influence of roof-edge roughness elements on airflow, heat transfer, and street-level pollutant transport inside and above a two-dimensional urban canyon is analyzed using an urban energy balance model coupled to a large-eddy simulation model. Simulations are performed for cold (early morning) and hot (mid afternoon) periods during the hottest month of the year (August) for the climate of Abu Dhabi, United Arab Emirates. The analysis suggests that early in the morning, and when the tallest roughness elements are implemented, the temperature above the street level increases on average by 0.5 K, while the pollutant concentration decreases by 2% of the street-level concentration. For the same conditions in mid afternoon, the temperature decreases conservatively by 1 K, while the pollutant concentration increases by 7% of the street-level concentration. As a passive or active architectural solution, the roof roughness element shows promise for improving thermal comfort and air quality in the canyon for specific times, but this should be further verified experimentally. The results also warrant a closer look at the effects of mid-range roughness elements in the urban morphology on atmospheric dynamics so as to improve parametrizations in mesoscale modelling.

A neighbourhood-scale estimate for the cooling potential of green roofs

Green roofs offer the possibility to mitigate multiple environmental issues in an urban environment. A common benefit attributed to green roofs is the temperature reduction through evaporation. This study focuses on evaluating the effect that evaporative cooling has on outdoor air temperatures in an urban environment. An established urban energy balance model was modified to quantify the cooling potential of green roofs and study the scalability of this mitigation strategy. Simulations were performed for different climates and urban geometries, with varying soil moisture content, green roof fraction and urban surface layer thickness. All simulations show a linear relationship between surface layer temperature reduction ΔTs and domain averaged evaporation rates from vegetation mmW, i.e. ΔTs=eW ⋅ mmW, where eW is the evaporative cooling potential with a value of ∼−0.35 Kdaymm−1. This relationship is independent of the method by which water is supplied. We also derive a simple algebraic relation for eW using a Taylor series expansion.

The urban energy balance of a lightweight low-rise neighborhood in Andacollo, Chile

Worldwide, the majority of rapidly growing neighborhoods are found in the Global South. They often exhibit different building construction and development patterns than the Global North, and urban climate research in many such neighborhoods has to date been sparse. This study presents local-scale observations of net radiation (Q*) and sensible heat flux (QH) from a lightweight low-rise neighborhood in the desert climate of Andacollo, Chile, and compares observations with results from a process-based urban energy-balance model (TUF3D) and a local-scale empirical model (LUMPS) for a 14-day period in autumn 2009. This is a unique neighborhood-climate combination in the urban energy-balance literature, and results show good agreement between observations and models for Q* and QH. The unmeasured latent heat flux (QE) is modeled with an updated version of TUF3D and two versions of LUMPS (a forward and inverse application). Both LUMPS implementations predict slightly higher QE than TUF3D, which may indicate a bias in LUMPS parameters towards mid-latitude, non-desert climates. Overall, the energy balance is dominated by sensible and storage heat fluxes with mean daytime Bowen ratios of 2.57 (observed QH/LUMPS QE)–3.46 (TUF3D). Storage heat flux (ΔQS) is modeled with TUF3D, the empirical objective hysteresis model (OHM), and the inverse LUMPS implementation. Agreement between models is generally good; the OHM-predicted diurnal cycle deviates somewhat relative to the other two models, likely because OHM coefficients are not specified for the roof and wall construction materials found in this neighborhood. New facet-scale and local-scale OHM coefficients are developed based on modeled ΔQS and observed Q*. Coefficients in the empirical models OHM and LUMPS are derived from observations in primarily non-desert climates in European/North American neighborhoods and must be updated as measurements in lightweight low-rise (and other) neighborhoods in various climates become available.

Dynamic Spatial-temporal Evaluations of Urban Heat Islands and Thermal Comfort of a Complex Urban District Using an Urban Canopy Model

This study conducted hourly dynamic simulations of the thermal climate and thermal comfort of 120 blocks within the complex district of the International Low Carbon City (ILCC) by applying an urban energy balance model (UDC), during the summertime in Shenzhen. Two parameters, including the local urban heat island (LUHI) and SET*, were adopted as evaluation indices, and the temporal-spatial distributions of these parameters were discussed. The results show that the northeast blocks of the ILCC always presented higher values of LUHI and SET* compared with the lower values of the middle blocks. The LUHI values varied between different blocks at the same time, ranging between -4°C and 4°C, whereas the SET* values varied from 27.5°C to 33.5°C. The large differences in the LUHI and SET* values between these blocks may be caused by their different urban spatial patterns and the varied underlying surface compositions. Additionally, the average diurnal variation of LUHI showed more fluctuations compared with the continuous conic variation manner of SET*. The average maximum values of LUHI and SET* both occurred in the afternoon, whereas the average minimum values occurred in the early morning.

Simulating the impact of urban development pathways on the local climate: A scenario-based analysis in the greater Dublin region, Ireland

In this study, the impact of different urban development scenarios on neighbourhood climate are examined. The investigation considers the relative impact differing policy/planning choices will have on the local-scale climate across a city during a typical climatological year (TCY). The aim is to demonstrate a modelling approach which couples a climate-based land classification and simple urban climate model and how this can be used to examine the impact differing urban forms and design strategies have on neighbourhood scale partitioning of energy and resulting consequences. Utilising the Surface Urban Energy and Water Balance (SUEWS) model (Järvi et al., 2011) hourly fluxes of sensible, latent and stored heat are simulated for an entire year under four different urban development scenarios. The land cover scenarios are based on those obtained by the MOLAND model for 2026 (Brennan et al., 2009) in our case study city Dublin (Ireland). MOLAND LULC are translated into local climate zones (Stewart and Oke, 2012) for examination. Subsequently, the types of building forms, vegetation type and coverage are modified based on realistic examples currently found across Dublin city. Our results focused on 2 principle aspects: the seasonality of energy partitioning with respect to vegetation and average diurnal partitioning of energy. Our analysis illustrates that compact scenarios are suitable form of future urban development in terms of reducing the spatial impact on the existing surface energy budget in Dublin. Design interventions which maintain the level of vegetation at a ratio≥9:16 to artificial surfaces reduces the impact.

Development of an urban canopy model for the evaluation of urban thermal climate with snow cover in severe cold regions

Snow plays an important role in determining heat and moisture exchanges between the underlying surface and atmosphere in winter. However, the effect of snow cover is not considered or assumed to be negligible in existing urban canopy energy balance models. In this paper, a one-dimensional snow model that accounts for heat transfer within snow cover is developed, and the model is implemented into an urban canopy energy balance model to simulate energy and moisture exchanges in cold urban areas with stable snow cover. The numerical methods of the snow model and the urban canopy model are demonstrated first, and the urban canopy model is subsequently used to simulate the thermal climate of a residential area dynamically in Yichun, China during winter. The results indicate that the existence of snow cover decreases the outdoor air temperature by 0.15 °C on average and 1.16 °C at maximum. In addition, the outdoor mean SET* increases 0.43 °C with the removal of snow cover, indicating that the thermal comfort of people outside decreases due to the presence of snow cover.

A GIS-based Energy Balance Modeling System for Urban Solar Buildings

Solar buildings as one type of decentralized renewable energy systems have been widely adopted to reduce carbon emissions. Related policy making faces two questions: how much total solar energy can be produced in a city and what proportion of building energy use can be supplied by the solar power? These questions remain hard to answer because of the lack of appropriate modeling systems, due to the data inconsistency and the limitation of current building energy and solar potential modeling methods in accounting for the urban context influences. This study tries to fill this gap by developing a GIS-based energy balance modeling system for urban solar buildings. This modeling system extends the system boundary from a single building to the urban building system, uses urban-scale data instead of costly survey, adopts widely used GIS-platform, and makes reasonable trade-offs between speed and accuracy. It consists of four major models: the Data Integration model, Urban Building Energy model, Urban Roof Solar Energy model and Energy Balance model. This modeling system is applied to Manhattan as a case study. The results show the spatial and temporal variations of building energy uses, the solar power potentials in the usable roof areas, and the self-supply and surplus ratio of buildings in Manhattan in 2012.

Using LCZ data to run an urban energy balance model

In recent years a number of models have been developed that describe the urban surface and simulate its climatic effects. Their great advantage is that they can be applied in environments outside the cities in which they have been developed and evaluated. Thus, they may be applied to cities in the economically developing world, which are growing rapidly, and where the results of such models may have greatest impact with respect to informing planning decisions. However, data requirements, particularly for the more complex urban models, represent a major obstacle to their employment. Here, we examine the potential for running the Surface Urban Energy and Water Balance model (SUEWS) using readily obtained data. SUEWS was designed to simulate energy and water balance terms at a neighbourhood scale (⩾1km2) and requires site-specific meteorological data and a detailed description of the surface. Here, its simulations are evaluated by comparison with measurements made over a seven month (approximately 3 seasons) period (April–October) at two flux tower sites (representing urban and suburban landscapes) in Dublin, Ireland. However, the main purpose of this work is to test the performance of the model under ‘ideal’ and ‘imperfect’ circumstances in relation to the input data required to run SUEWS. The ideal case uses detailed urban land cover data and meteorological data from the tower sites. The imperfect cases use parameters derived from the Local Climate Zone (LCZ) classification scheme and meteorological data from a standard weather station located beyond the urban area. For the period of record examined, the simulations show good agreement with the observations in both ideal and imperfect cases, suggesting that the model can be used with data that is more easily derived. The comparison also shows the importance of including vegetative cover and of the initial moisture state in simulating the urban energy budget.