Surface Urban Energy And Water Balance Scheme Research Articles

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.

CO2 uptake of urban vegetation in a warming Nordic city

Many cities are committed to reducing greenhouse gas emissions, improving air quality, and reducing air temperatures through climate actions. Maintaining or increasing carbon sinks in urban green areas is relevant, as the sinks compensate a part of the emissions in addition to reducing emissions themselves. This research assesses the magnitude of carbon dioxide (CO2) net uptake (i.e. respiration and CO2 uptake by photosynthesis) and local 2-m air temperature in Helsinki, Finland, using an urban ecosystem model SUEWS (The Surface Urban Energy and Water Balance Scheme), and examines their potential future changes due to climate change. The model was run at an hourly resolution within the entire city at a spatial resolution of 250 × 250 m2. Two separate simulations were considered: the present climate by simulating years 2014–2019 and the future climate in the 2050s following the climate scenario RCP8.5. Each modelled grid was further divided into natural and built surfaces using Local Climate Zones (LCZs) to determine how vegetation in forests and various urban vegetation types contributes to cooling and carbon sequestration. According to our simulations, the urban green space in Helsinki annually sequestered 36.3 ± 7.7 kt C in 2015–2019, offsetting circa 7% of the city’s anthropogenic emissions. The mean annual temperatures varied by 2.1∘C between natural and built areas within the city. Although urban forests were the strongest sinks (0.3 kg C m−2 year−1), urban neighbourhoods contributed 47% of Helsinki’s net carbon sinks. Local temperatures were expected to increase with the RCP8.5 climate scenario on average by 1.3∘C within the simulated area and CO2 net uptake by 11%, without altering existing green spaces. Overall, this research highlights the significance of urban green as carbon sinks and how climate change may influence their role in mitigating greenhouse gas emissions and local climate conditions in urban environments.

A study of the impact of landscape heterogeneity on surface energy fluxes in a tropical climate using SUEWS

This study employs an evaluated Surface Urban Energy and Water Balance Scheme (SUEWS) model driven by Local Climate Zone (LCZ)-derived urban canopy parameters to explore landscape heterogeneity's impacts on the partitioning of surface energy fluxes and heat stress variations in Lagos, Nigeria. The results reveal that LCZ-based SUEWS effectively replicates the diurnal patterns of air temperature (Tair), relative humidity (RH), and land surface temperature (LST). The root mean square error (RMSE) for simulated Tair and RH ranges from 0.4 °C to 1.2 °C and 1.8% to 8.0%, respectively. While a nighttime warm bias in LST is observed, it reduces during the daytime. Significant spatial variability in turbulent heat fluxes and LST among LCZs is noted, with core urban LCZs experiencing notable increases in sensible heat flux and LST, while suburban LCZs exhibit higher latent heat flux values. Anthropogenic heat flux peaks in high compact low-rise LCZ 3, reaching a maximum of 95 W/m2. Remarkably, no significant difference is found in the diurnal heat stress cycle among LCZs, despite consistently elevated heat stress levels in high compact LCZs. These findings offer valuable insights into quantifying surface energy flux variabilities and spatio-temporal heat stress patterns in a densely populated tropical city- Lagos Nigeria.

Simulating heat and CO2 fluxes in Beijing using SUEWS V2020b: sensitivity to vegetation phenology and maximum conductance

Abstract. The Surface Urban Energy and Water Balance Scheme (SUEWS) has recently been introduced to include a bottom-up approach to modeling carbon dioxide (CO2) emissions and uptake in urban areas. In this study, SUEWS is evaluated against the measured eddy covariance (EC) turbulent fluxes of sensible heat (QH), latent heat (QE), and CO2 (FC) in a densely built neighborhood in Beijing. The model sensitivity to maximum conductance (gmax) and leaf area index (LAI) is examined. Site-specific gmax is obtained from observations over local vegetation species, and LAI parameters are extracted by optimization with remotely sensed LAI obtained from a Landsat 7 data product. For the simulation of anthropogenic CO2 components, local traffic and population data are collected. In the model evaluation, the mismatch between the measurement source area and simulation domain is also considered. Using the optimized gmax and LAI, the modeling of heat fluxes is noticeably improved, showing higher correlation with observations, lower bias, and more realistic seasonal dynamics of QE and QH. The effect of the gmax adjustment is more significant than the LAI adjustment. Compared to heat fluxes, the FC module shows lower sensitivity to the choices of gmax and LAI. This can be explained by the low relative contribution of vegetation to the net FC in the modeled area. SUEWS successfully reproduces the average diurnal cycle of FC and annual cumulative sums. Depending on the size of the simulation domain, the modeled annual accumulated FC ranges from 7.4 to 8.7 kgCm-2yr-1, compared to 7.5 kgCm-2yr-1 observed by EC. Traffic is the dominant CO2 source, contributing 59 %–70 % to the annual total CO2 emissions, followed by human metabolism (14 %–18 %), buildings (11 %–14 %), and CO2 release by vegetation and soil respiration (6 %–10 %). Vegetation photosynthesis offsets only 5 %–10 % of the total CO2 emissions. We highlight the importance of choosing the optimal LAI parameters and gmax when SUEWS is used to model surface fluxes. The FC module of SUEWS is a promising tool in quantifying urban CO2 emissions at the local scale and therefore assisting in mitigating urban CO2 emissions.

Impact of building density on natural ventilation potential and cooling energy saving across Chinese climate zones

Natural ventilation is an energy-efficient approach to reduce the need for mechanical ventilation and air conditioning in buildings. However, traditionally weather data for building energy simulation are obtained from rural areas, which do not reflect the urban micrometeorological conditions. This study combines the Surface Urban Energy and Water Balance Scheme (SUEWS) and EnergyPlus to predict natural ventilation potential (NVP) and cooling energy saving in three idealised urban neighbourhoods with different urban densities in five Chinese cities of different climate zones. SUEWS downscales the meteorological inputs required by EnergyPlus, including air temperature, relative humidity, and wind speed profiles. The findings indicate that NVP and cooling energy saving differences between urban and rural areas are climate- and season-dependent. During summer, the urban-rural differences in natural ventilation hours are −43% to 10% (cf. rural) across all climates, while in spring/autumn, they range from −7% to 36%. The study also suggests that single-sided ventilation can be as effective as cross ventilation for buildings in dense urban areas. Our findings highlight the importance of considering local or neighbourhood-scale climate when evaluating NVP. We demonstrate a method to enhance NVP prediction accuracy in urban regions using EnergyPlus, which can contribute to achieving low-carbon building design.

Carbon sequestration potential of street tree plantings in Helsinki

Abstract. Cities have become increasingly interested in reducing their greenhouse gas emissions and increasing carbon sequestration and storage in urban vegetation and soil as part of their climate mitigation actions. However, most of our knowledge of the biogenic carbon cycle is based on data and models from forested ecosystems, despite urban nature and microclimates differing greatly from those in natural or forested ecosystems. There is a need for modelling tools that can correctly consider temporal variations in the urban carbon cycle and take specific urban conditions into account. The main aims of our study were to (1) examine the carbon sequestration potential of two commonly used street tree species (Tilia × vulgaris and Alnus glutinosa) growing in three different growing media by taking into account the complexity of urban conditions and (2) evaluate the urban land surface model SUEWS (Surface Urban Energy and Water Balance Scheme) and the soil carbon model Yasso15 in simulating the carbon sequestration of these street tree plantings at temporal scales (diurnal, monthly, and annual). SUEWS provides data on the urban microclimate and on street tree photosynthesis and respiration, whereas soil carbon storage is estimated with Yasso. These models were used to study the urban carbon cycle throughout the expected lifespan of street trees (2002–2031). Within this period, model performances were evaluated against transpiration estimated from sap flow, soil carbon content, and soil moisture measurements from two street tree sites located in Helsinki, Finland. The models were able to capture the variability in the urban carbon cycle and transpiration due to changes in environmental conditions, soil type, and tree species. Carbon sequestration potential was estimated for an average street tree and for the average of the diverse soils present in the study area. Over the study period, soil respiration dominated carbon exchange over carbon sequestration due to the high initial carbon loss from the soil after street construction. However, the street tree plantings turned into a modest sink of carbon from the atmosphere on an annual scale, as tree and soil respiration approximately balanced the photosynthesis. The compensation point when street tree plantings turned from an annual source into a sink was reached more rapidly – after 12 years – by Alnus trees, while this point was reached by Tilia trees after 14 years. However, these moments naturally vary from site to site depending on the growing media, planting density, tree species, and climate. Overall, the results indicate the importance of soil in urban carbon sequestration estimations.

Surface Urban Energy and Water Balance Scheme (v2020a) in vegetated areas: parameter derivation and performance evaluation using FLUXNET2015 dataset

Abstract. To compare the impact of surface–atmosphere exchanges from rural and urban areas, fully vegetated areas (e.g. deciduous trees, evergreen trees and grass) commonly found adjacent to cities need to be modelled. Here we provide a general workflow to derive parameters for SUEWS (Surface Urban Energy and Water Balance Scheme), including those associated with vegetation phenology (via leaf area index, LAI), heat storage and surface conductance. As expected, attribution analysis of bias in SUEWS-modelled QE finds that surface conductance (gs) plays the dominant role; hence there is a need for more estimates of surface conductance parameters. The workflow is applied at 38 FLUXNET sites. The derived parameters vary between sites with the same plant functional type (PFT), demonstrating the challenge of using a single set of parameters for a PFT. SUEWS skill at simulating monthly and hourly latent heat flux (QE) is examined using the site-specific derived parameters, with the default NOAH surface conductance parameters (Chen et al., 1996). Overall evaluation for 2 years has similar metrics for both configurations: median hit rate between 0.6 and 0.7, median mean absolute error less than 25 W m−2, and median mean bias error ∼ 5 W m−2. Performance differences are more evident at monthly and hourly scales, with larger mean bias error (monthly: ∼ 40 W m−2; hourly ∼ 30 W m−2) results using the NOAH-surface conductance parameters, suggesting that they should be used with caution. Assessment of sites with contrasting QE performance demonstrates how critical capturing the LAI dynamics is to the SUEWS prediction skills of gs and QE. Generally gs is poorest in cooler periods (more pronounced at night, when underestimated by ∼ 3 mm s−1). Given the global LAI data availability and the workflow provided in this study, any site to be simulated should benefit.

Earth Observation Data Exploitation in Urban Surface Modelling: The Urban Energy Balance Response to a Suburban Park Development

Cities are developing rapidly as an increasing percentage of the global population resides in urban areas. In the face of climate change, the sustainable development of cities is crucial for the well-being and safety of urban populations. The potential of planning interventions towards improving of urban resilience can be evaluated based on methodological approaches used in the domain of urban climate. In this study, we present how Earth Observation (EO) can be systematically used to evaluate urban planning interventions, based on Urban Surface Models (USM) simulations. More specifically, the impact of a suburban park development in Heraklion, Crete, was assessed based on simulations of the USM SUEWS (Surface Urban Energy and Water Balance Scheme), which was forced by EO data. Multi-source satellite data were analyzed to provide information on urban form, highlighting the importance of EO data in evaluating the environmental sustainability potential of urban planning interventions. The modifications caused by this planning intervention to surface energy fluxes were simulated. The scale (102 m) and the type (no-use vegetated area changed to recreational vegetated) of the intervention triggered minor responses in the Urban Energy Balance (UEB) at neighborhood scale, since the change of the relevant surface fluxes was not greater than 10 W m−2, on average, assuming no irrigation and no important changes in soil moisture. However, the planned substitution of grass and bare soil with paved surfaces and trees was found to increase the overall net change in heat storage, therefore contributing to the urban heat island development.

Evaluation of nature-based solutions implementation scenarios, using urban surface modelling

The present paper aims to study the impact of Nature Based Solutions (NBS) on the urban environment. The Surface Urban Energy and Water balance Scheme (SUEWS) is used to quantify the impact of NBS in the city of Heraklion, Crete, Greece, a densely built urban area. Local meteorological data and data from an Eddy Covariance flux tower installed in the city center are used for the model simulation and evaluation. Five different scenarios are tested by replacing the city’s roofs and pavements with green infrastructure, i.e., trees and grass, and water bodies. The NBS impact evaluation is based on the changes of air temperature above 2m from the ground, relative humidity and energy fluxes. A decrease of the air temperature is revealed with the highest reduction (2.3%) occurring when the pavements are replaced with grass for all scenarios. The reduction of the air temperature is followed by a decrease in turbulent sensible heat flux. For almost all cases, an increase of the relative humidity is noticed, accompanied by a considerable increase of the turbulent latent heat flux. Therefore, NBS in cities change the energy balance significantly and modify the urban environment for the citizens' benefit.

Urban meteorological forcing data for building energy simulations

Despite building energy use being one of the largest global energy consumers, building energy simulations rarely take the actual local neighbourhood scale climate into account. A new globally applicable approach is proposed to support buildings energy design. ERA5 (European Centre Reanalysis version 5) data are used with SUEWS (Surface Urban Energy and Water balance Scheme) to obtain (in this example case) an urban typical meteorological year (uTMY) that is usable in building energy modelling. The predicted annual energy demand (heating and cooling) for a representative four-storey London residential apartment using uTMY is 6.9% less (cf. conventional TMY). New vertical profile coefficients for wind speed and air temperature in EnergyPlus are derived using SUEWS. EneryPlus simulations with these neighbourhood scale coefficients and uTMY data, predict the top two floors have ~10% larger energy demand (cf. the open terrain coefficients with uTMY data). Vertical variations in wind speed have a greater impact on the simulated building energy than equivalent variations in temperature. This globally appliable approach can provide local meteorological data for building energy modelling, improving design for the local context through characterising the surrounding neighbourhood.

Application of SUEWS model forced with WRF: Energy fluxes validation in urban and suburban Portuguese areas

Urban areas, home to over half of the world's population, are at the forefront of climate change impacts and adaptation issues. Planning sustainable cities for the future requires not only a clear understanding of how climate change will influence urban areas but also how urban areas influence the local climate. This paper validates the Surface Urban Energy and Water Balance Scheme (SUEWS) model at an urban and a suburban site in Portugal, through five months of simulations, with forcing data from the Weather Research and Forecasting Model (WRF). SUEWS is tested against direct flux measurements carried out at the two study areas. The surface energy fluxes are also analysed in terms of the land cover characteristics of each study area, to understand the influence of the surface on the energy balance. At both sites SUEWS is able to simulate the turbulent sensible and latent heat fluxes and reproduces the diurnal cycle of the turbulent fluxes, but shows a consistent overestimation of the sensible heat flux. In terms of the latent heat flux, underestimation at the urban site and overestimation at the suburban site are evident. These results enable the use of WRF-SUEWS for emerging applications, such as, assessment of urban planning measures or assessment of urban climate under climate change scenarios.

Simulation of the radiative effect of haze on the urban hydrological cycle using reanalysis data in Beijing

Abstract. Although increased aerosol concentration modifies local air temperatures and boundary layer structure in urban areas, little is known about its effects on the urban hydrological cycle. Changes in the hydrological cycle modify surface runoff and flooding. Furthermore, as runoff commonly transports pollutants to soil and water, any changes impact urban soil and aquatic environments. To explore the radiative effect of haze on changes in the urban surface water balance in Beijing, different haze levels are modelled using the Surface Urban Energy and Water Balance Scheme (SUEWS), forced by reanalysis data. The pollution levels are classified using aerosol optical depth observations. The secondary aims are to examine the usability of a global reanalysis dataset in a highly polluted environment and the SUEWS model performance. We show that the reanalysis data do not include the attenuating effect of haze on incoming solar radiation and develop a correction method. Using these corrected data, SUEWS simulates measured eddy covariance heat fluxes well. Both surface runoff and drainage increase with severe haze levels, particularly with low precipitation rates: runoff from 0.06 to 0.18 mm d−1 and drainage from 0.43 to 0.62 mm d−1 during fairly clean to extremely polluted conditions, respectively. Considering all precipitation events, runoff rates are higher during extremely polluted conditions than cleaner conditions, but as the cleanest conditions have high precipitation rates, they induce the largest runoff. Thus, the haze radiative effect is unlikely to modify flash flooding likelihood. However, flushing pollutants from surfaces may increase pollutant loads in urban water bodies.

Evaluation of the Surface Urban Energy and Water Balance Scheme (SUEWS) at a Dense Urban Site in Shanghai: Sensitivity to Anthropogenic Heat and Irrigation

Abstract The Surface Urban Energy and Water Balance Scheme (SUEWS) is used to investigate the impact of anthropogenic heat flux QF and irrigation on surface energy balance partitioning in a central business district of Shanghai. Diurnal profiles of QF are carefully derived based on city-specific hourly electricity consumption data, hourly traffic data, and dynamic population density. The QF is estimated to be largest in summer (mean daily peak 236 W m−2). When QF is omitted, the SUEWS sensible heat flux QH reproduces the observed diurnal pattern generally well, but the magnitude is underestimated compared to observations for all seasons. When QF is included, the QH estimates are improved in spring, summer, and autumn but are poorer in winter, indicating winter QF is overestimated. Inclusion of QF has little influence on the simulated latent heat flux QE but improves the storage heat flux estimates except in winter. Irrigation, both amount and frequency, has a large impact on QE. When irrigation is not considered, the simulated QE is underestimated for all seasons. The mean summer daytime QE is largely overestimated compared to observations under continuous irrigation conditions. Model results are improved when irrigation occurs with a 3-day frequency, especially in summer. Results are consistent with observed monthly outdoor water use. This study highlights the importance of appropriately including QF and irrigation in urban land surface models—terms not generally considered in many previous studies.

Impact of temporal resolution of precipitation forcing data on modelled urban‐atmosphere exchanges and surface conditions

ABSTRACTRepresentative precipitation data sets are very difficult to obtain due to the inherent spatial and temporal variability of rainfall. Gridded rainfall products exist at various scales, but temporal resolution is coarse (daily or, at best, a few hours). This study demonstrates the impact of low temporal resolution precipitation forcing data (PFD) on modelled energy fluxes, runoff and surface conditions, which could have implications for a range of applications including flood forecasting, irrigation scheduling and epidemiology. An evaporation‐interception model originally developed for forests is applied here within the framework of the Surface Urban Energy and Water balance Scheme (SUEWS). The model is forced with rainfall data representative of a range of temporal resolutions (from 5 min to 3 h). Taking the highest resolution case as a reference, differences in model output are found as the temporal resolution of PFD decreases, depending on the timing of rainfall occurrence, intensity and duration. Modelled evaporation, runoff and surface wetness deviate from the reference case, which affect other variables such as the turbulent sensible heat flux. The largest impacts are seen on days with greatest daily total rainfall and, even on days with no rain, differences in antecedent conditions (soil moisture or surface wetness) can cause deviations from the reference case. Errors can be reduced by applying a disaggregation scheme that provides a more realistic distribution of rainfall, importantly, one that allows for intermittent rainfall.

Sensitivity of Surface Urban Energy and Water Balance Scheme (SUEWS) to downscaling of reanalysis forcing data

Often the meteorological forcing data required for urban hydrological models are unavailable at the required temporal resolution or for the desired period. Although reanalysis data can provide this information, the spatial resolution is often coarse relative to cities, so downscaling is required prior to use as realistic forcing. In this study, WATCH WFDEI reanalysis data are used to force the Surface Urban Energy and Water Balance Scheme (SUEWS). From sensitivity tests in two cities, Vancouver and London with different orography, we conclude precipitation is the most important meteorological variable to be properly downscaled to obtain reliable surface hydrology results, with relative humidity being the second most important. Overestimation of precipitation in reanalysis data at the three sites gives 6–21% higher annual modelled evaporation, 26–39% higher runoff at one site and 4% lower value at one site when compared to modelled values using observed forcing data. Application of a bias correction method to the reanalysis precipitation reduces the model bias compared to using observed forcing data, when evaluated using eddy covariance evaporation measurements.

Quantification and mapping of urban fluxes under climate change: Application of WRF-SUEWS model to Greater Porto area (Portugal)

Climate change and the growth of urban populations are two of the main challenges facing Europe today. These issues are linked as climate change results in serious challenges for cities. Recent attention has focused on how urban surface-atmosphere exchanges of heat and water will be affected by climate change and the implications for urban planning and sustainability.In this study energy fluxes for Greater Porto area, Portugal, were estimated and the influence of the projected climate change evaluated. To accomplish this, the Weather Research and Forecasting Model (WRF) and the Surface Urban Energy and Water Balance Scheme (SUEWS) were applied for two climatological scenarios: a present (or reference, 1986–2005) scenario and a future scenario (2046–2065), in this case the Representative Concentration Pathway RCP8.5, which reflects the worst set of expectations (with the most onerous impacts). The results show that for the future climate conditions, the incoming shortwave radiation will increase by around 10%, the sensible heat flux around 40% and the net storage heat flux around 35%. In contrast, the latent heat flux will decrease about 20%. The changes in the magnitude of the different fluxes result in an increase of the net all-wave radiation by 15%. The implications of the changes of the energy balance on the meteorological variables are discussed, particularly in terms of temperature and precipitation.

Surface Urban Energy and Water Balance Scheme (SUEWS): Development and evaluation at two UK sites

The Surface Urban Energy and Water Balance Scheme (SUEWS) is evaluated at two locations in the UK: a dense urban site in the centre of London and a residential suburban site in Swindon. Eddy covariance observations of the turbulent fluxes are used to assess model performance over a two-year period (2011−2013). The distinct characteristics of the sites mean their surface energy exchanges differ considerably. The model suggests the largest differences can be attributed to surface cover (notably the proportion of vegetated versus impervious area) and the additional energy supplied by human activities. SUEWS performs better in summer than winter, and better at the suburban site than the dense urban site. One reason for this is the bias towards suburban summer field campaigns in observational data used to parameterise this (and other) model(s). The suitability of model parameters (such as albedo, energy use and water use) for the UK sites is considered and, where appropriate, alternative values are suggested. An alternative parameterisation for the surface conductance is implemented, which permits greater soil moisture deficits before evaporation is restricted at non-irrigated sites. Accounting for seasonal variation in the estimation of storage heat flux is necessary to obtain realistic wintertime fluxes.

Development of the Surface Urban Energy and Water Balance Scheme (SUEWS) for cold climate cities

Abstract. The Surface Urban Energy and Water Balance Scheme (SUEWS) is developed to include snow. The processes addressed include accumulation of snow on the different urban surface types: snow albedo and density aging, snow melting and re-freezing of meltwater. Individual model parameters are assessed and independently evaluated using long-term observations in the two cold climate cities of Helsinki and Montreal. Eddy covariance sensible and latent heat fluxes and snow depth observations are available for two sites in Montreal and one in Helsinki. Surface runoff from two catchments (24 and 45 ha) in Helsinki and snow properties (albedo and density) from two sites in Montreal are also analysed. As multiple observation sites with different land-cover characteristics are available in both cities, model development is conducted independent of evaluation. The developed model simulates snowmelt related runoff well (within 19% and 3% for the two catchments in Helsinki when there is snow on the ground), with the springtime peak estimated correctly. However, the observed runoff peaks tend to be smoother than the simulated ones, likely due to the water holding capacity of the catchments and the missing time lag between the catchment and the observation point in the model. For all three sites the model simulates the timing of the snow accumulation and melt events well, but underestimates the total snow depth by 18–20% in Helsinki and 29–33% in Montreal. The model is able to reproduce the diurnal pattern of net radiation and turbulent fluxes of sensible and latent heat during cold snow, melting snow and snow-free periods. The largest model uncertainties are related to the timing of the melting period and the parameterization of the snowmelt. The results show that the enhanced model can simulate correctly the exchange of energy and water in cold climate cities at sites with varying surface cover.

The Surface Urban Energy and Water Balance Scheme (SUEWS): Evaluation in Los Angeles and Vancouver

Summary An urban energy and water balance model is presented which uses a small number of commonly measured meteorological variables and information about the surface cover. Rates of evaporation-interception for a single layer with multiple surface types (paved, buildings, coniferous trees and/or shrubs, deciduous trees and/or shrubs, irrigated grass, non-irrigated grass and water) are calculated. Below each surface type, except water, there is a single soil layer. At each time step the moisture state of each surface is calculated. Horizontal water movements at the surface and in the soil are incorporated. Particular attention is given to the surface conductance used to model evaporation and its parameters. The model is tested against direct flux measurements carried out over a number of years in Vancouver, Canada and Los Angeles, USA. At all measurement sites the model is able to simulate the net all-wave radiation and turbulent sensible and latent heat well (RMSE = 25–47 W m−2, 30–64 and 20–56 W m−2, respectively). The model reproduces the diurnal cycle of the turbulent fluxes but typically underestimates latent heat flux and overestimates sensible heat flux in the day time. The model tracks measured surface wetness and simulates the variations in soil moisture content. It is able to respond correctly to short-term events as well as annual changes. The largest uncertainty relates to the determination of surface conductance. The model has the potential be used for multiple applications; for example, to predict effects of regulation on urban water use, landscaping and planning scenarios, or to assess climate mitigation strategies.