Impact of Air Conditioning Systems on the Outdoor Thermal Environment during Summer in Berlin, Germany

Multicriteria Spatial Modeling: Methodological Contribution to the Analysis of Atmospheric and Surface Heat Islands in Presidente Prudente, Brazil

Several studies demonstrate the potential of models for the representation of phenomena such as urban heat islands. This article aimed to analyze atmospheric heat islands (UHIucl) by integrating primary air temperature data with spatial information such as land use and relief from a multicriteria model based on multiple linear regression. Furthermore, we compared the measured and estimated air temperature at 11 p.m. with the surface temperature at 10:51 p.m. (local time). These temperatures were obtained through the thermal band of the Landsat 8 satellite considering extraction points of interest in Presidente Prudente city, Brazil. The multicriteria model showed reliability in UHIucl spatialization, reaching the confidence interval (p-value ≤ 0.05). The model proves that urban surface materials are the main energy sources modulating heat transfer to the atmosphere, while vegetation has a temperature-reducing effect. Precise mappings such as the one proposed here are relevant for the formulation of measures that support decision-making by public authorities. These mappings aim at urban planning that is resilient to the effects of urban climate and can be replicated in other realities.

Climate change projections for sustainable and healthy cities

The ambition to develop sustainable and healthy cities requires city-specific policy and practice founded on a multidisciplinary evidence base, including projections of human-induced climate change. A cascade of climate models of increasing complexity and resolution is reviewed, which provides the basis for constructing climate projections-from global climate models with a typical horizontal resolution of a few hundred kilometres, through regional climate models at 12-50 km to convection-permitting models at 1 km resolution that permit the representation of urban induced climates. Different approaches to modelling the urban heat island (UHI) are also reviewed-focusing on how climate model outputs can be adjusted and coupled with urban canopy models to better represent UHI intensity, its impacts and variability. The latter can be due to changes induced by urbanisation or to climate change itself. City interventions such as greater use of green infrastructure also have an effect on the UHI and can help to reduce adverse health impacts such as heat stress and the mortality associated with increasing heat. Examples for the Complex Urban Systems for Sustainability and Health (CUSSH) partner cities of London, Rennes, Kisumu, Nairobi, Beijing and Ningbo illustrate how cities could potentially make use of more detailed models and projections to develop and evaluate policies and practices targeted at their specific environmental and health priorities.

PRACTICE RELEVANCE

Large-scale climate projections for the coming decades show robust trends in rising air temperatures, including more warm days and nights, and longer/more intense warm spells and heatwaves. This paper describes how more complex and higher resolution regional climate and urban canopy models can be combined with the aim of better understanding and quantifying how these larger scale patterns of change may be modified at the city or finer scale. These modifications may arise due to urbanisation and effects such as the UHI, as well as city interventions such as the greater use of grey and green infrastructures.There is potential danger in generalising from one city to another-under certain conditions some cities may experience an urban cool island, or little future intensification of the UHI, for example. City-specific, tailored climate projections combined with tailored health impact models contribute to an evidence base that supports built environment professionals, urban planners and policymakers to ensure designs for buildings and urban areas are fit for future climates.

Comparison of Urban Heat Island Intensity Estimation Methods Using Urbanized WRF in Berlin, Germany

In this study, we present a meso-scale simulation of the urban microclimate in Berlin, Germany, using the Weather Research and Forecasting (WRF) numerical weather prediction platform. The objective of the study is to derive an accurate estimate of the near-surface urban heat island (UHI) intensity. The simulation is conducted over a two-week summer period. We compare different physical schemes, different urban canopy schemes and different methods for estimating the UHI intensity. The urban fraction of each urban category is derived using the Copernicus Impervious Density data and the Corine Land Cover data. High-resolution City Geography Markup Language (CityGML) data is used to estimate the building height densities required by the multi-layer urban canopy model (UCM). Within the single-layer UCM, we implement an anthropogenic heat profile based on the large scale urban consumption of energy (LUCY) model. The optimal model configuration combines the WRF Single Moment Five-Class (WSM5) microphysics scheme, the Bougeault–Lacarrère planetary boundary layer scheme, the eta similarity (Mellor–Yamada–Janjic) surface layer scheme, the Noah Multi-Parameterization land surface model, the Dudhia and Rapid Radiative Transfer Model (RRTM) radiation schemes, and the multi-layer UCM (including the building energy model). Our simulated UHI intensity results agree well with measurements with a root mean squared error of 0.86K and a mean bias error of 0.20K. After model validation, we proceed to compare several UHI intensity calculation methods, including the ‘ring rural reference’ (RRR) method and the ‘virtual rural reference’ (VRR) method. The VRR mthod is also known as the ‘urban increment’ method. We suggest and argument that the VRR approach is superior.