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

Abstract

h i g h l i g h t s• The impact of different future development pathways on local climate are simulated.• Sprawling scenarios increased sensible/stored heat across 7.7-14.9% of the domain.• Greening rooftops resulted in the lowering the impact on local scale climate. a r t i c l e i n f o b s t r a c tIn 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.

Mapping Local Climate Zones Using ArcGIS-Based Method and Exploring Land Surface Temperature Characteristics in Chenzhou, China

“…Chen concluded that both the spatial configuration of tree canopies and the vertical structure of tree canopies are important predictors for reducing land surface temperature (LST) during daytime and nighttime [13]. Also, specific urban structures and morphologies produce distinct microclimates [14][15][16][17][18], which means that in order to achieve effective urban heat island mitigation, it is necessary to understand and apply urban climatic information in urban planning. However, investigating the impacts of urban physical characteristics on microclimate is a difficult task because of the complexity and variety of land cover, surface structures, construction materials and human activities [19].…”

The Human Influence Experiment (Part 2): Guidelines for Improved Mapping of Local Climate Zones Using a Supervised Classification

“…At the 10th International Conference on Urban Climate in 2018, it became clear that LCZ maps are now regarded as a global reference for urban land cover descriptions [10]. Since LCZ maps are intended for and already used in a range of different applications, such as climate models at various scales [11][12][13][14][15][16][17][18][19][20], land use change investigations [6], or the characterization of several hundreds of crowd-sourced citizen-weather stations in terms of their local-scale surroundings [21], there is a clear need for highly accurate classification results [22]. However, it is unclear what determines the final quality of a LCZ map derived with the WUDAPT level-0 methodology.…”

A Review of Urban Planning Research for Climate Change

“…A climate-based classification of the city was developed as a method for urban heat island investigation [37,38]. Recent studies have combined the LCZs partition method, and a certain number of climate correlation analyses and scenario simulation prediction analyses have been carried out at the city macro level [39]. On the urban microscale level, research has focused on the effects influenced by building layouts and spatial structures.…”