A novel approach to CFD analysis of the urban environment

The construction of cities, with their buildings and human activities, not only changes the landscape, but also influences the local climate in a manner that depends on many different factors and parameters: weather conditions, urban thermo-physical and geometrical characteristics, anthropogenic moisture and heat sources. Land-cover and canopy structure play an important role in urban climatology and every environmental assessment and city design face with them. Inside the previous frame, the objective of this study is both to identify both the key design variables that alter the environment surrounding the buildings, and to quantified the extension area of these phenomena. The tool used for this study is a 2D computational fluid dynamics (CFD) numerical simulation considering different heights for buildings, temperature gaps between undisturbed air and building’s walls, velocities of undisturbed air. Results obtained allowed to find a novel approach to study urban canopies, giving a qualitative assessment on the contribution and definition of the total energy of the area surrounding the buildings

The relationship between built-up areas and the spatial development of the mean maximum urban heat island in Debrecen, Hungary

The climate of built-up regions differs significantly from rural regions and the most important modifying effect of urbanization on local climate is the urban temperature excess, otherwise called the urban heat island (UHI). This study examines the influence of built-up areas on the near-surface air temperature field in the case of the medium-sized city of Debrecen, Hungary. Mobile measurements were used under different weather conditions between March 2002 and March 2003. Efforts concentrated on the determination of the spatial distribution of mean maximum UHI intensity with special regard to land-use features such as built-up ratio and its areal extensions. In both (heating and non-heating) seasons the spatial distribution of the UHI intensity field showed a basically concentric shape with local anomalies. The mean maximum UHI intensity reaches more than 2.0 degrees C (heating season) and 2.5 degrees C (non-heating season) in the centre of the city. We established the relationship between the above-mentioned land-use parameters and mean maximum UHI intensity by means of multiple linear regression analysis. As the measured and predicted mean maximum UHI intensity patterns show, there is an obvious connection between the spatial distribution of urban thermal excess and the land-use parameters examined, so these parameters play a significant role in the development of the strong, UHI intensity field over the city. Copyright (c) 2005 Royal Meteorological Society

Modelling and observing urban climate in the Netherlands

Volgens de klimaatscenario’s van het KNMI uit 2006 zal de gemiddelde temperatuur in Nederland in de komende decennia verder stijgen. Hittegolven zullen naar verwachting vaker voorkomen en de intensiteit van met name zomerse buien kan toenemen. In steden zijn de gevolgen van de opwarming extra voelbaar, omdat de temperaturen er door het zogenoemde Urban Heat Island (UHI) effect veel hoger kunnen zijn dan in het omliggende gebied. Zulke periodes met hoge temperaturen gaan veelal gepaard met verslechterde luchtkwaliteit en droogte. Dit alles kan grote gevolgen hebben voor de leefbaarheid en de gezondheid van de bevolking in stedelijke gebieden. Veranderingen in de buienintensiteit beïnvloeden de waterhuishouding van de stad

A WRF-UCM-SOLWEIG framework of 10m resolution to quantify the intra-day impact of urban features on thermal comfort

City-scale outdoor thermal comfort diagnostics are essential for understanding actual heat stress. However, previous research primarily focused on the street scale. Here, we present the WRF-UCM-SOLWEIG framework to achieve fine-grained thermal comfort mapping at the city scale. The background climate condition affecting thermal comfort is simulated by the Weather Research and Forecasting (WRF) model coupled with the urban canopy model (UCM) at a local-scale (500m). The most dominant factor, mean radiant temperature, is simulated using the Solar and Longwave Environmental Irradiance Geometry (SOLWEIG) model at the micro-scale (10m). The Universal Thermal Climate Index (UTCI) is calculated based on the mean radiant temperature and local climate parameters. The influence of different ground surface materials, buildings, and tree canopies is simulated in the SOLWEIG model using integrated urban morphological data. We applied this proposed framework to the city of Guangzhou, China, and investigated the intra-day variation in the impact of urban morphology during a heat wave period. Through statistical analysis, we found that the elevation in UTCI is primarily attributed to the increase in the fraction of impervious surface (ISF) during daytime, with a maximum correlation coefficient of 0.80. Tree canopy cover has a persistent cooling effect during the day. Implementing 40% of tree cover can reduce the daytime UTCI by 1.5 to 2.0 K. At nighttime, all urban features have a negligible contribution to outdoor thermal comfort. Overall, the established framework provides essential input data and references for studies and urban planners in the practice of urban (micro)climate diagnostics and planning

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

Participatory Roles of Urban Trees in Regulating Environmental Quality

abstract: The world has been continuously urbanized and is currently accommodating more than half of the human population. Despite that cities cover only less than 3% of the Earth’s land surface area, they emerged as hotspots of anthropogenic activities. The drastic land use changes, complex three-dimensional urban terrain, and anthropogenic heat emissions alter the transport of mass, heat, and momentum, especially within the urban canopy layer. As a result, cities are confronting numerous environmental challenges such as exacerbated heat stress, frequent air pollution episodes, degraded water quality, increased energy consumption and water use, etc. Green infrastructure, in particular, the use of trees, has been proved as an effective means to improve urban environmental quality in existing research. However, quantitative evaluations of the efficacy of urban trees in regulating air quality and thermal environment are impeded by the limited temporal and spatial scales in field measurements and the deficiency in numerical models. This dissertation aims to advance the simulation of realistic functions of urban trees in both microscale and mesoscale numerical models, and to systematically evaluate the cooling capacity of urban trees under thermal extremes. A coupled large-eddy simulation–Lagrangian stochastic modeling framework is developed for the complex urban environment and is used to evaluate the impact of urban trees on traffic-emitted pollutants. Results show that the model is robust for capturing the dispersion of urban air pollutants and how strategically implemented urban trees can reduce vehicle-emitted pollution. To evaluate the impact of urban trees on the thermal environment, the radiative shading effect of trees are incorporated into the integrated Weather Research and Forecasting model. The mesoscale model is used to simulate shade trees over the contiguous United States, suggesting how the efficacy of urban trees depends on geographical and climatic conditions. The cooling capacity of urban trees and its response to thermal extremes are then quantified for major metropolitans in the United States based on remotely sensed data. It is found the nonlinear temperature dependence of the cooling capacity remarkably resembles the thermodynamic liquid-water–vapor equilibrium. The findings in this dissertation are informative to evaluating and implementing urban trees, and green infrastructure in large, as an important urban planning strategy to cope with emergent global environmental changes.Dissertation/ThesisDoctoral Dissertation Civil, Environmental and Sustainable Engineering 201

Climate and more sustainable cities: climate information for improved planning and management of cities (producers/capabilities perspective)

In the last two decades substantial advances have been made in the understanding of the scientific basis of urban climates. These are reviewed here with attention to sustainability of cities, applications that use climate information, and scientific understanding in relation to measurements and modelling. Consideration is given from street (micro) scale to neighbourhood (local) to city and region (meso) scale. Those areas where improvements are needed in the next decade to ensure more sustainable cities are identified. High-priority recommendations are made in the following six strategic areas: observations, data, understanding, modelling, tools and education. These include the need for more operational urban measurement stations and networks; for an international data archive to aid translation of research findings into design tools, along with guidelines for different climate zones and land uses; to develop methods to analyse atmospheric data measured above complex urban surfaces; to improve short-range, high-resolution numerical prediction of weather, air quality and chemical dispersion through improved modelling of the biogeophysical features of the urban land surface; to improve education about urban meteorology; and to encourage communication across scientific disciplines at a range of spatial and temporal scales

Climate Impacts of Land Cover and Land Use Changes in Coastal Tropical Regions Under Conditions of Global Climate Change

The work presented in this document is an investigation of the climate impacts of land cover and land use (LCLU) changes in coastal tropical regions under conditions of global climate change (global warming, GW) using the Regional Atmospheric Modeling System (RAMS) as the main research tool, and taking the northeastern region of the Caribbean island of Puerto Rico as the test case. To achieve this goal an ensemble of climate simulations were performed, combining two LCLU and two GW scenarios. Reconstructed agricultural maps combined with reconstructed sea surface temperatures (SST) form the Past (1951-1956) climate scenario, while the Present (2000-2004) scenario was supported with high-resolution remote sensing data. The climate reconstruction approach is validated with observational data from surface weather stations for both timeframes. Results indicate that LCLU changes produced the largest air temperature differences over heavily urbanized regions and that these changes occur near the surface. The influence of the global warming signal is to induce a positive inland gradient for maximum temperature, possibly due to increased trade winds in the present climatology. In terms of minimum temperatures, the global warming signal induces temperature increases along the coastal plains and inland lowlands. The global warming signal also produced stronger trade winds with an easterly-southeasterly direction. These changes cause a shift in the location of a convergence zone north of the Central Mountains, where without orographic lifting clouds have higher bases and the total column liquid water content is decreased above higher elevations. This combination of factors translates into a dramatic decrease in surface accumulated precipitation in the highlands of the region of interest due to global climate change. Regarding the combined effects of LCLU changes and global warming, results indicate that the impact of LCLU changes on temperatures, total column liquid water content, and surface accumulated precipitation are relatively independent of the large-scale climate conditions, and vice versa