Analysis of precipitation climatology simulated by high resolution coupled global models over the South America

The results of coupled high resolution global models (CGCMs) over South America are discussed. HiGEM1.2 and HadGEM1.2 simulations, with horizontal resolution of ~90 and 135 km, respectively, are compared. Precipitation estimations from CMAP (Climate Prediction Center—Merged Analysis of Precipitation), CPC (Climate Prediction Center) and GPCP (Global Precipitation Climatology Project) are used for validation. HiGEM1.2 and HadGEM1.2 simulated seasonal mean precipitation spatial patterns similar to the CMAP. The positioning and migration of the Intertropical Convergence Zone and of the Pacific and Atlantic subtropical highs are correctly simulated by the models. In HiGEM1.2 and HadGEM1.2, the intensity and locations of the South Atlantic Convergence Zone are in agreement with the observed dataset. The simulated annual cycles are in phase with estimations of rainfall for most of the six regions considered. An important result is that HiGEM1.2 and HadGEM1.2 eliminate a common problem of coarse resolution CGCMs, which is the simulation of a semiannual cycle of precipitation due to the semiannual solar forcing. Comparatively, the use of high resolution in HiGEM1.2 reduces the dry biases in the central part of Brazil during austral winter and spring and in most part of the year over an oceanic box in eastern Uruguay.

Ranging characteristics of the domestic cat (Felis catus) in an urban environment

In many countries, high densities of domestic cats (Felis catus) are found in urban habitats where they have the potential to exert considerable predation pressure on their prey. However, little is known of the ranging behaviour of cats in the UK. Twenty cats in suburban Reading, UK, were fitted with GPS trackers to quantify movement patterns. Cats were monitored during the summer and winter for an average of 6.8 24 h periods per season. Mean daily area ranged (95 % MCP) was 1.94 ha. Including all fixes, mean maximum area ranged was 6.88 ha. These are broadly comparable to those observed in urban areas in other countries. Daily area ranged was not affected by the cat’s sex or the season, but was significantly larger at night than during the day. There was no relationship between area ranged and habitat availability. Taking available habitat into account, cat ranging area contained significantly more garden and other green space than urban habitats. If cats were shown to be negatively affecting prey populations, one mitigation option for consideration in housing developments proposed near important wildlife sites would be to incorporate a ‘buffer zone’ in which cat ownership was not permitted. Absolute maximum daily area ranged by a cat in this study was 33.78 ha. This would correspond to an exclusory limit of approximately 300–400 m to minimise the negative effects of cat predation, but this may need to be larger if cat ranging behaviour is negatively affected by population density

Natural ventilation assessment in typical open an semi-open urban environments under various wind directions

Semi-open street roofs protect pedestrians from intense sunshine and rains. Their effects on natural ventilation of urban canopy layers (UCL) are less understood. This paper investigates two idealized urban models consisting of 4(2×2) or 16(4×4) buildings under a neutral atmospheric condition with parallel (0°) or non-parallel (15°,30°,45°) approaching wind. The aspect ratio (building height (H) / street width (W)) is 1 and building width is B=3H. Computational fluid dynamic (CFD) simulations were first validated by experimental data, confirming that standard k-ε model predicted airflow velocity better than RNG k-ε model, realizable k–ε model and Reynolds stress model. Three ventilation indices were numerically analyzed for ventilation assessment, including flow rates across street roofs and openings to show the mechanisms of air exchange, age of air to display how long external air reaches a place after entering UCL, and purging flow rate to quantify the net UCL ventilation capacity induced by mean flows and turbulence. Five semi-open roof types are studied: Walls being hung above street roofs (coverage ratio λa=100%) at z=1.5H, 1.2H, 1.1H ('Hung1.5H', 'Hung1.2H', 'Hung1.1H' types); Walls partly covering street roofs (λa=80%) at z=H ('Partly-covered' type); Walls fully covering street roofs (λa=100%) at z=H ('Fully-covered' type).They basically obtain worse UCL ventilation than open street roof type due to the decreased roof ventilation. 'Hung1.1H', 'Hung1.2H', 'Hung1.5H' types are better designs than 'Fully-covered' and 'Partly-covered' types. Greater urban size contains larger UCL volume and requires longer time to ventilate. The methodologies and ventilation indices are confirmed effective to quantify UCL ventilation.

High resolution simulation of the variability of surface energy balance fluxes across central London with urban zones for energy partitioning

The parameterization of surface heat-flux variability in urban areas relies on adequate representation of surface characteristics. Given the horizontal resolutions (e.g. ≈0.1–1km) currently used in numerical weather prediction (NWP) models, properties of the urban surface (e.g. vegetated/built surfaces, street-canyon geometries) often have large spatial variability. Here, a new approach based on Urban Zones to characterize Energy partitioning (UZE) is tested within a NWP model (Weather Research and Forecasting model;WRF v3.2.1) for Greater London. The urban land-surface scheme is the Noah/Single-Layer Urban Canopy Model (SLUCM). Detailed surface information (horizontal resolution 1 km)in central London shows that the UZE offers better characterization of surface properties and their variability compared to default WRF-SLUCM input parameters. In situ observations of the surface energy fluxes and near-surface meteorological variables are used to select the radiation and turbulence parameterization schemes and to evaluate the land-surface scheme

Sustainable urban metabolism as a link between bio-physical sciences and urban planning: the BRIDGE project

Urban metabolism considers a city as a system with flows of energy and material between it and the environment. Recent advances in bio-physical sciences provide methods and models to estimate local scale energy, water, carbon and pollutant fluxes. However, good communication is required to provide this new knowledge and its implications to endusers (such as urban planners, architects and engineers). The FP7 project BRIDGE (sustainaBle uRban plannIng Decision support accountinG for urban mEtabolism) aimed to address this gap by illustrating the advantages of considering these issues in urban planning. The BRIDGE Decision Support System (DSS) aids the evaluation of the sustainability of urban planning interventions. The Multi Criteria Analysis approach adopted provides a method to cope with the complexity of urban metabolism. In consultation with targeted end-users, objectives were defined in relation to the interactions between the environmental elements (fluxes of energy, water, carbon and pollutants) and socioeconomic components (investment costs, housing, employment, etc.) of urban sustainability. The tool was tested in five case study cities: Helsinki, Athens, London, Florence and Gliwice; and sub-models were evaluated using flux data selected. This overview of the BRIDGE project covers the methods and tools used to measure and model the physical flows, the selected set of sustainability indicators, the methodological framework for evaluating urban planning alternatives and the resulting DSS prototype.

Analysis of the seasonal cycle within the first international urban land-surface model comparison

A number of urban land-surface models have been developed in recent years to satisfy the growing requirements for urban weather and climate interactions and prediction. These models vary considerably in their complexity and the processes that they represent. Although the models have been evaluated, the observational datasets have typically been of short duration and so are not suitable to assess the performance over the seasonal cycle. The First International Urban Land-Surface Model comparison used an observational dataset that spanned a period greater than a year, which enables an analysis over the seasonal cycle, whilst the variety of models that took part in the comparison allows the analysis to include a full range of model complexity. The results show that, in general, urban models do capture the seasonal cycle for each of the surface fluxes, but have larger errors in the summer months than in the winter. The net all-wave radiation has the smallest errors at all times of the year but with a negative bias. The latent heat flux and the net storage heat flux are also underestimated, whereas the sensible heat flux generally has a positive bias throughout the seasonal cycle. A representation of vegetation is a necessary, but not sufficient, condition for modelling the latent heat flux and associated sensible heat flux at all times of the year. Models that include a temporal variation in anthropogenic heat flux show some increased skill in the sensible heat flux at night during the winter, although their daytime values are consistently overestimated at all times of the year. Models that use the net all-wave radiation to determine the net storage heat flux have the best agreement with observed values of this flux during the daytime in summer, but perform worse during the winter months. The latter could result from a bias of summer periods in the observational datasets used to derive the relations with net all-wave radiation. Apart from these models, all of the other model categories considered in the analysis result in a mean net storage heat flux that is close to zero throughout the seasonal cycle, which is not seen in the observations. Models with a simple treatment of the physical processes generally perform at least as well as models with greater complexity.

Research priorities in observing and modeling urban weather and climate

In 2007, the world reached the unprecedented milestone of half of its people living in cities, and that proportion is projected to be 60% in 2030. The combined effect of global climate change and rapid urban growth, accompanied by economic and industrial development, will likely make city residents more vulnerable to a number of urban environmental problems, including extreme weather and climate conditions, sea-level rise, poor public health and air quality, atmospheric transport of accidental or intentional releases of toxic material, and limited water resources. One fundamental aspect of predicting the future risks and defining mitigation strategies is to understand the weather and regional climate affected by cities. For this reason, dozens of researchers from many disciplines and nations attended the Urban Weather and Climate Workshop.1 Twenty-five students from Chinese universities and institutes also took part. The presentations by the workshop's participants span a wide range of topics, from the interaction between the urban climate and energy consumption in climate-change environments to the impact of urban areas on storms and local circulations, and from the impact of urbanization on the hydrological cycle to air quality and weather prediction.

Estimating the potential yield of small wind turbines in urban areas: a case study for Greater London, UK

To optimise the placement of small wind turbines in urban areas a detailed understanding of the spatial variability of the wind resource is required. At present, due to a lack of observations, the NOABL wind speed database is frequently used to estimate the wind resource at a potential site. However, recent work has shown that this tends to overestimate the wind speed in urban areas. This paper suggests a method for adjusting the predictions of the NOABL in urban areas by considering the impact of the underlying surface on a neighbourhood scale. In which, the nature of the surface is characterised on a 1 km2 resolution using an urban morphology database. The model was then used to estimate the variability of the annual mean wind speed across Greater London at a height typical of current small wind turbine installations. Initial validation of the results suggests that the predicted wind speeds are considerably more accurate than the NOABL values. The derived wind map therefore currently provides the best opportunity to identify the neighbourhoods in Greater London at which small wind turbines yield their highest energy production. The model does not consider street scale processes, however previously derived scaling factors can be applied to relate the neighbourhood wind speed to a value at a specific rooftop site. The results showed that the wind speed predicted across London is relatively low, exceeding 4 ms-1 at only 27% of the neighbourhoods in the city. Of these sites less than 10% are within 10 km of the city centre, with the majority over 20 km from the city centre. Consequently, it is predicted that small wind turbines tend to perform better towards the outskirts of the city, therefore for cities which fit the Burgess concentric ring model, such as Greater London, ‘distance from city centre’ is a useful parameter for siting small wind turbines. However, there are a number of neighbourhoods close to the city centre at which the wind speed is relatively high and these sites can only been identified with a detailed representation of the urban surface, such as that developed in this study.

Multi-site evaluation of an urban land-surface model: intra-urban heterogeneity, seasonality and parameter complexity requirements

An extensive off-line evaluation of the Noah/Single Layer Urban Canopy Model (Noah/SLUCM) urban land-surface model is presented using data from 15 sites to assess (1) the ability of the scheme to reproduce the surface energy balance observed in a range of urban environments, including seasonal changes, and (2) the impact of increasing complexity of input parameter information. Model performance is found to be most dependent on representation of vegetated surface area cover; refinement of other parameter values leads to smaller improvements. Model biases in net all-wave radiation and trade-offs between turbulent heat fluxes are highlighted using an optimization algorithm. Here we use the Urban Zones to characterize Energy partitioning (UZE) as the basis to assign default SLUCM parameter values. A methodology (FRAISE) to assign sites (or areas) to one of these categories based on surface characteristics is evaluated. Using three urban sites from the Basel Urban Boundary Layer Experiment (BUBBLE) dataset, an independent evaluation of the model performance with the parameter values representative of each class is performed. The scheme copes well with both seasonal changes in the surface characteristics and intra-urban heterogeneities in energy flux partitioning, with RMSE performance comparable to similar state-of-the-art models for all fluxes, sites and seasons. The potential of the methodology for high-resolution atmospheric modelling application using the Weather Research and Forecasting (WRF) model is highlighted. This analysis supports the recommendations that (1) three classes are appropriate to characterize the urban environment, and (2) that the parameter values identified should be adopted as default values in WRF.

Urban climates and global climate change

Cities and global climate change are closely linked: cities are where the bulk of greenhouse gas emissions take place through the consumption of fossil fuels; they are where an increasing proportion of the world’s people live; and they also generate their own climate – commonly characterized by the urban heat island. In this way, understanding the way cities affect the cycling of energy, water, and carbon to create an urban climate is a key element of climate mitigation and adaptation strategies, especially in the context of rising global temperatures and deteriorating air quality in many cities. As climate models resolve finer spatial-scales, they will need to represent those areas in which more than 50% of the world’s population already live to provide climate projections that are of greater use to planning and decision-making. Finally, many of the processes that are instrumental in determining urban climate are the same factors leading to global anthropogenic climate change, namely regional-scale land-use changes; increased energy use; and increased emissions of climatically-relevant atmospheric constituents. Cities are therefore both a case study for understanding, and an agent in mitigating, anthropogenic climate change. This chapter reviews and summarizes the current state of understanding of the physical basis of urban climates, as well as our ability to represent these in models. We argue that addressing the challenges of managing urban environments in a changing climate requires understanding the energy, water, and carbon balances for an urban landscape and, importantly, their interactions and feedbacks, together with their links to human behaviour and controls. We conclude with some suggestions for where further research is needed.

How to parametrize urban-canopy drag to reproduce wind-direction effects within the canopy

The mean wind direction within an urban canopy changes with height when the incoming flow is not orthogonal to obstacle faces. This wind-turning effect is induced by complex processes and its modelling in urban-canopy (UC) parametrizations is difficult. Here we focus on the analysis of the spatially-averaged flow properties over an aligned array of cubes and their variation with incoming wind direction. For this purpose, Reynolds-averaged Navier–Stokes simulations previously compared, for a reduced number of incident wind directions, against direct numerical simulation results are used. The drag formulation of a UCparametrization ismodified and different drag coefficients are tested in order to reproduce the wind-turning effect within the canopy for oblique wind directions. The simulations carried out for a UC parametrization in one-dimensional mode indicate that a height-dependent drag coefficient is needed to capture this effect.

Thr54 allele carriers of the Ala54Thr variant of FABP2 gene have associations with metabolic syndrome and hypertriglyceridemia in urban South Indians

The intestinal fatty acid-binding protein gene is proposed as a candidate gene for diabetes because the protein it codes is involved in fatty acid absorption and metabolism. This study investigates the association of the Ala54Thr variant of the intestinal fatty acid-binding protein gene on type 2 diabetes mellitus and other related metabolic traits in Asian Indians. Ala54Thr polymorphism was genotyped by using polymerase chain reaction-restriction fragment length polymorphism in unrelated 773 type 2 diabetic and 899 normal glucose-tolerant (NGT) subjects, randomly chosen from the Chennai Urban Rural Epidemiology Study, an ongoing population-based study in South India. The Ala54Thr polymorphism was not associated with type 2 diabetes mellitus or obesity. However, genotype-phenotype study revealed that the NGT subjects carrying the Thr54 allele had significantly higher 2-hour plasma glucose (P = .007), glycated hemoglobin (P = .004), 2-hour insulin (P = .027), and fasting low-density lipoprotein cholesterol (P = .032) levels compared with those with the Ala54 allele. Normal glucose-tolerant subjects with Ala54Thr and Thr54Thr genotypes had significantly higher fasting serum triglyceride levels (P = .003) compared with those with Ala54Ala. The subjects were stratified into those with hypertriglyceridemia (serum triglyceride levels >or=150 mg/dL) and those without. The odds ratio for hypertriglyceridemia for the individuals carrying the Ala54Thr genotype was 1.491 (95% confidence interval [CI], 1.22-1.83, P < .0001), and for those carrying the Thr54Thr genotype, it was 1.888 (95% CI, 1.34-2.67; P < .0001). Subjects were also stratified into those with metabolic syndrome (MS) and those without, according to modified Adult Treatment Panel III guidelines. The odds ratio (adjusted for age and sex) for MS for the individuals carrying the Ala54Thr genotype was 1.240 (95% CI, 1.02-1.51; P = .03), whereas for those carrying the Thr54Thr genotype, it was 1.812 (95% CI, 1.28-2.57; P = .001). Carriers of the Thr54 allele have associations with MS and hypertriglyceridemia in this urban South Indian population.

Association of low adiponectin levels with the metabolic syndrome--the Chennai Urban Rural Epidemiology Study (CURES-4)

The aim of the study was to assess the relation of adiponectin levels with the metabolic syndrome in Asian Indians, a high-risk group for diabetes and premature coronary artery disease. The study was conducted on 100 (50 men and 50 women) type 2 diabetic subjects and 100 age and sex matched subjects with normal glucose tolerance selected from the Chennai Urban Rural Epidemiology Study, an ongoing population study in Chennai in southern India. Metabolic syndrome was defined using modified Adult Treatment Panel III (ATPIII) guidelines. Adiponectin values were significantly lower in diabetic subjects (men: 5.2 vs 8.3 microg/mL, P=.00l; women: 7.6 vs 11.1 microg/mL, P<.00l) and those with the metabolic syndrome (men: 5.0 vs 6.8 microg/mL, P=.01; women: 6.5 vs 9.9 microg/mL, P=.001) compared with those without. Linear regression analysis revealed adiponectin to be associated with body mass index (P<.05), waist circumference (P<.01), fasting plasma glucose (P=.001), glycated hemoglobin (P<.001), triglycerides (P<.00l), high-density lipoprotein (HDL) cholesterol (P<.001), cholesterol/HDL ratio (P<.00l), and insulin resistance measured by homeostasis assessment model (P<.00l). Factor analysis identified 2 factors: factor 1, negatively loaded with adiponectin and HDL cholesterol and positively loaded with triglycerides, waist circumference, and insulin resistance measured by homeostasis assessment model; and factor 2, with a positive loading of waist circumference and systolic and diastolic blood pressure. Logistic regression analysis revealed adiponectin to be negatively associated with metabolic syndrome (odds ratio [OR], 0.365; P<.001) even after adjusting for age (OR, 0.344; P<.00l), sex (OR, 0.293; P<.001), and body mass index (OR, 0.292; P<.00l). Lower adiponectin levels are associated with the metabolic syndrome per se and several of its components, particularly, diabetes, insulin resistance, and dyslipidemia in this urban south Indian population.

Continuous sky view factor maps from high resolution urban digital elevation models

This paper presents a new method to calculate sky view factors (SVFs) from high resolution urban digital elevation models using a shadow casting algorithm. By utilizing weighted annuli to derive SVF from hemispherical images, the distance light source positions can be predefined and uniformly spread over the whole hemisphere, whereas another method applies a random set of light source positions with a cosine-weighted distribution of sun altitude angles. The 2 methods have similar results based on a large number of SVF images. However, when comparing variations at pixel level between an image generated using the new method presented in this paper with the image from the random method, anisotropic patterns occur. The absolute mean difference between the 2 methods is 0.002 ranging up to 0.040. The maximum difference can be as much as 0.122. Since SVF is a geometrically derived parameter, the anisotropic errors created by the random method must be considered as significant.

Contribution of land use changes to near-surface air temperatures during recent summer extreme heat events in the Phoenix Metropolitan Area

The impact of 1973–2005 land use–land cover (LULC) changes on near-surface air temperatures during four recent summer extreme heat events (EHEs) are investigated for the arid Phoenix, Arizona, metropolitan area using the Weather Research and Forecasting Model (WRF) in conjunction with the Noah Urban Canopy Model. WRF simulations were carried out for each EHE using LULC for the years 1973, 1985, 1998, and 2005. Comparison of measured near-surface air temperatures and wind speeds for 18 surface stations in the region show a good agreement between observed and simulated data for all simulation periods. The results indicate consistent significant contributions of urban development and accompanying LULC changes to extreme temperatures for the four EHEs. Simulations suggest new urban developments caused an intensification and expansion of the area experiencing extreme temperatures but mainly influenced nighttime temperatures with an increase of up to 10 K. Nighttime temperatures in the existing urban core showed changes of up to 2 K with the ongoing LULC changes. Daytime temperatures were not significantly affected where urban development replaced desert land (increase by 1 K); however, maximum temperatures increased by 2–4 K when irrigated agricultural land was converted to suburban development. According to the model simulations, urban landscaping irrigation contributed to cooling by 0.5–1 K in maximum daytime as well as minimum nighttime 2-m air temperatures in most parts of the urban region. Furthermore, urban development led to a reduction of the already relatively weak nighttime winds and therefore a reduction in advection of cooler air into the city.