Linking urban climate classification with an urban energy and water budget model: Multi-site and multi-seasonal evaluation

Abstract

There are a number of models available for examining the interaction between cities and the atmosphere over a range of scales, from small scales -such as individual facades, buildings, neighbourhoods -to the effect of the entire conurbation itself. Many of these models require detailed morphological characteristics and material properties along with relevant meteorological data to be initialised. However, these data are difficult to obtain given the heterogeneity of built forms, particularly in newly emerging cities. Yet, the need for models which can be applied to urban areas (for instance to address planning problems) is increasingly urgent as the global population becomes more urban. In this paper, a modeling approach which derives the required land cover parameters for a mid-complex urban energy budget and water budget model (SUEWS) in a consistent manner is evaluated in four cities (Dublin, Hamburg, Melbourne and Phoenix). The required parameters for the SUEWS model are derived using local climate zones (LCZs) for land cover, and meteorological observations from off-site synoptic stations. More detailed land cover and meteorological data are then added to the model in stages to examine the impact on model performance with respect to observations of turbulent fluxes of sensible (Q H ) and latent (Q E ) heat. Replacing LCZ land cover with detailed fractional coverages was shown to marginally improve model performance, however the performance of model coupled with 'coarse' LCZ data was within

Implications of employing detailed urban canopy parameters for mesoscale climate modelling: a comparison between WUDAPT and GIS databases over Vienna, Austria

“…() demonstrated over Berlin, Germany, increasing complexity in UCMs might actually be a source of error more than a source of precision. However, it has been shown in previous studies (Alexander et al ., ; Brousse et al ., , ) and in this study that the models are sensible to the LCZs disparities.…”

“…Those classes describe the climate relevant aspects of the urban environment with ranges of values, which are implementable in UCMs (Table ). Although mean values of those ranges already give a good approximation of the climate impact of heterogeneous urban landscapes (Alexander et al ., ; Brousse et al ., ; Wouters et al ., ), the use of more detailed data sets to improve the definition of those typologies might provide more accurate results.…”

Impact of urban canopy models and external parameters on the modelled urban energy balance in a tropical city

“…Herein, consistent data are collected at various stages, with level 0 being the Local Climate Zones (LCZs; Stewart and Oke, 2012) and higher level products providing more specific parameters about urban form (canyon height‐to‐width ratio, building/canyon height), built materials and function. Since the LCZ classifier uses Landsat 8 red, near‐infrared and thermal bands, available at 30 m horizontal resolution, the resulting products can be expected to provide a detailed, globally available consistent and comprehensive dataset on the urban landscape with respect to its canopy layer climate (Bechtel et al , 2015; Alexander et al , 2016a).…”

Quality of Crowdsourced Data on Urban Morphology—The Human Influence Experiment (HUMINEX)

“…The LCZ scheme was designed primarily for assessing local climate impacts [15][16][17][18][19]; but as it describes the urban landscape generally (e.g., vegetative and building fractions), a map of LCZ types across a city also encodes its internal structure. As such, WUDAPT data can be used to assess current and project urban impacts on the local atmosphere and hydrosphere and can be used to map exposure to existing and projected hazards [20][21][22]. Moreover, these maps can provide a spatial framework for gathering related information on ecosystems, carbon emissions, public health, etc.…”