WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid

Brousse, Oscar; Martilli, Alberto; Foley, Michael; Mills, Gerald; Bechtel, Benjamin

doi:10.1016/j.uclim.2016.04.001

Cited by 188 publications

(120 citation statements)

References 26 publications

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“…This feature is especially important for a high‐resolution study of such a city with many tall buildings as Singapore. The recent contributions by Salamanca and Martilli (), Brousse et al (), and Hammerberg et al () using MLCUM (BEP/BEM) in WRF have aided in‐depth evaluation of the UHI phenomenon in European cities.…”

Section: Introductionmentioning

confidence: 99%

“…A WUDAPT committee verifies the quality of the data and whether it accurately depicts the urban landscape (Ching et al, ). The WUDAPT methodology incorporating L0 data in WRF has introduced a standardized scientific way to describe the land cover and its thermal performance on the UHI in many studies (Brousse et al, ; Cai et al, ; Hammerberg et al, ; Ren et al, ; R. Wang et al, ).…”

Section: Introductionmentioning

confidence: 99%

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High‐Resolution, Multilayer Modeling of Singapore's Urban Climate Incorporating Local Climate Zones

Mughal

Yin

et al. 2019

JGR Atmospheres

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We applied Weather Research and Forecasting (WRF) model's Multilayer Urban Canopy Model (MLUCM) to simulate the urban climate of Singapore during a hot period in April 2016. The high‐resolution local climate zone (LCZ) map was used as urban land use/land cover data in order to study the intraurban variability in different LCZ classes. The LCZ map for Singapore was developed by adopting the World Urban Database and Access Portal Tools (WUDAPT) methodology based on satellite remote sensing imageries and building height data. The coupled WRF/MLUCM model was validated using meteorological data from stations across Singapore. Higher index of agreement compared to observations and lower root‐mean‐squared error of 2‐m temperature, relative humidity, and global horizontal irradiance showed satisfactory model performance. A sensitivity analysis of initial and boundary conditions helped in determining the model configuration with the least error for quantifying the urban heat island (UHI) effect. The diurnal cycle and the spatial pattern of UHI were investigated, and it was found that the mean UHI intensity peaked in the early morning at 2.2 °C, reaching 3.6 °C in the Compact High Rise (LCZ1) areas. The anthropogenic heat due to indoor air conditioning was found to play a major role in all the processes studied, while the effect of the different land use types was most pronounced during nighttime and least visible near noon. The UHI circulation developed near the central catchment is found to prevent sea breezes from further propagating inland.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

High‐Resolution, Multilayer Modeling of Singapore's Urban Climate Incorporating Local Climate Zones

Mughal

Yin

et al. 2019

JGR Atmospheres

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“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Hammerberg

Brousse

Martilli

et al. 2018

Intl Journal of Climatology

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ABSTRACT:One of the major obstacles to using numerical weather prediction models for guidance on mitigating urbanization's impact on local and regional climate is the lack of detailed and model ready morphological data at urban scale. The World Urban Database and Access Portal Tool (WUDAPT) is a recent project developed to extract climate relevant information on urban areas, in the form of local climate zones (LCZs), out of remote sensing imagery. This description of the urban landscape has been tested and used for parameterization of different urban canopy models (UCM) for mesoscale studies. As detailed information is usually bounded within cities' centres, crowdsourced and remote sensing data offer the possibility to move beyond the old barriers of urban climate investigations by studying the full range of variation from the urban core to the periphery and its related impacts on local climate. Thus, for this study we sought to compare the relative impact of using the WUDAPT methodology versus a simplified definition of the urban morphology extracted out of detailed GIS information to initialize a regional weather model and compare the output against official and crowdsourced weather station networks. A case study over Vienna, Austria was conducted using the weather research forecasting (WRF) model, coupled with the building effect parameterization and building energy models (BEP-BEM) in five distinct seasonal periods. Results demonstrated that using detailed GIS data to derive morphological descriptions of LCZs for mesoscale studies provided only a marginal overall improvement over using the default WUDAPT parameters based on the ranges proposed by Stewart and Oke (2012). The findings also highlighted the importance of developing techniques that are better at capturing the morphological heterogeneity across the entire urban landscape and thus improve our understandings of UCM performance over urban areas.

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“…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.…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2017

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Abstract:The World Urban Database and Access Portal Tools (WUDAPT) is a community initiative to collect worldwide data on urban form (i.e., morphology, materials) and function (i.e., use and metabolism). This is achieved through crowdsourcing, which we define here as the collection of data by a bounded crowd, composed of students. In this process, training data for the classification of urban structures into Local Climate Zones (LCZ) are obtained, which are, like most volunteered geographic information initiatives, of unknown quality. In this study, we investigated the quality of 94 crowdsourced training datasets for ten cities, generated by 119 students from six universities. The results showed large discrepancies and the resulting LCZ maps were mostly of poor to moderate quality. This was due to general difficulties in the human interpretation of the (urban) landscape and in the understanding of the LCZ scheme. However, the quality of the LCZ maps improved with the number of training data revisions. As evidence for the wisdom of the crowd, improvements of up to 20% in overall accuracy were found when multiple training datasets were used together to create a single LCZ map. This improvement was greatest for small training datasets, saturating at about ten to fifteen sets.

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WUDAPT, an efficient land use producing data tool for mesoscale models? Integration of urban LCZ in WRF over Madrid

Cited by 188 publications

References 26 publications

High‐Resolution, Multilayer Modeling of Singapore's Urban Climate Incorporating Local Climate Zones

High‐Resolution, Multilayer Modeling of Singapore's Urban Climate Incorporating Local Climate Zones

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

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

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