ORCID Profile
0000-0001-9839-7234
Current Organisation
University of New South Wales
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Atmospheric Dynamics | Atmospheric Sciences | Physical Oceanography | Meteorology | Climate Change Processes
Atmospheric Processes and Dynamics | Climate Variability (excl. Social Impacts) | Climate Change Models |
Publisher: IOP Publishing
Date: 23-02-2021
Abstract: Global climate is changing as a result of anthropogenic warming, leading to higher daily excursions of temperature in cities. Such elevated temperatures have great implications on human thermal comfort and heat stress, which should be closely monitored. Current methods for heat exposure assessments (surveys, microclimate measurements, and laboratory experiments), however, present several limitations: measurements are scattered in time and space and data gathered on outdoor thermal stress and comfort often does not include physiological and behavioral parameters. To address these shortcomings, Project Coolbit aims to introduce a human-centric approach to thermal comfort assessments. In this study, we propose and evaluate the use of wrist-mounted wearable devices to monitor environmental and physiological responses that span a wide range of spatial and temporal distributions. We introduce an integrated wearable weather station that records (a) microclimate parameters (such as air temperature and humidity), (b) physiological parameters (heart rate, skin temperature and humidity), and (c) subjective feedback. The feasibility of this methodology to assess thermal comfort and heat stress is then evaluated using two sets of experiments: controlled-environment physiological data collection, and outdoor environmental data collection. We find that using the data obtained through the wrist-mounted wearables, core temperature can be predicted non-invasively with 95 percent of target attainment within ±0.27 °C. Additionally, a direct connection between the air temperature at the wrist ( T a , w ) and the perceived activity level (PAV) of in iduals was drawn. We observe that with increased T a , w , the desire for physical activity is significantly reduced, reaching ‘Transition only’ PAV level at 36 °C. These assessments reveal that the wearable methodology provides a comprehensive and accurate representation of human heat exposure, which can be extended in real-time to cover a large spatial distribution in a given city and quantify the impact of heat exposure on human life.
Publisher: IOP Publishing
Date: 26-02-2021
Abstract: To fully address the multi-faceted challenges of urban heat, it is paramount that humans are placed at the center of the agenda. This is manifested in a recent shift in urban heat studies that aim to achieve a ‘human-centric’ approach, i.e. focusing on personalized characteristics of comfort, well-being, performance, and health, as opposed to the one-size-fits-all solutions and guidelines. The proposed article is focused on systematically reviewing personalized urban heat studies and detailing the objectives posed, methodologies utilized, and limitations yet to be addressed. We further summarize current knowledge and challenges in addressing the impact of personal heat exposure on human life by discussing the literature linked with urban heat studies at the human, building, and city scales. Lastly, this systematic review reveals the need for future evaluations focused on accuracy and standardization of human-centric data collection and analytics, and more importantly, addressing critical geographic and socio-economic knowledge gaps identified in the field.
Publisher: Frontiers Media SA
Date: 13-09-2021
DOI: 10.3389/FENVS.2021.720323
Abstract: The spatial variability of land cover in cities results in a heterogeneous urban microclimate, which is often not represented with regulatory meteorological sensor networks. Crowdsourced sensor networks have the potential to address this shortcoming with real-time and fine-grained temperature measurements across cities. We use crowdsourced data from over 500 citizen weather stations during summer in Sydney, Australia, combined with 100-m land use and Local Climate Zone (LCZ) maps to explore intra-urban variabilities in air temperature. Sydney presents unique drivers for spatio-temporal variability, with its climate influenced by the ocean, mountainous topography, and erse urban land use. Here, we explore the interplay of geography with urban form and fabric on spatial variability in urban temperatures. The crowdsourced data consists of 2.3 million data points that were quality controlled and compared with reference data from five synoptic weather stations. Crowdsourced stations measured higher night-time temperatures, higher maximum temperatures on warm days, and cooler maximum temperatures on cool days compared to the reference stations. These differences are likely due to siting, with crowdsourced weather stations closer to anthropogenic heat emissions, urban materials with high thermal inertia, and in areas of reduced sky view factor. Distance from the coast was found to be the dominant factor impacting the spatial variability in urban temperatures, with diurnal temperature range greater for sensors located inland. Further differences in urban temperature could be explained by spatial variability in urban land-use and land-cover. Temperature varied both within and between LCZs across the city. Crowdsourced nocturnal temperatures were particularly sensitive to surrounding land cover, with lower temperatures in regions with higher vegetation cover, and higher temperatures in regions with more impervious surfaces. Crowdsourced weather stations provide highly relevant data for health monitoring and urban planning, however, there are several challenges to overcome to interpret this data including a lack of metadata and an uneven distribution of stations with a possible socio-economic bias. The sheer number of crowdsourced weather stations available can provide a high-resolution understanding of the variability of urban heat that is not possible to obtain via traditional networks.
Publisher: Copernicus GmbH
Date: 27-08-2019
DOI: 10.5194/GMD-2019-176
Abstract: Abstract. The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to predict temporal and vertical variation of temperature, wind speed, and specific humidity. It is composed of various sub models: a rural model, an urban microclimate model, and a building energy model. In a nearby rural site, a rural model is forced with weather data to solve a vertical diffusion equation to calculate vertical potential temperature profiles using a novel parameterization. The rural model also calculates a horizontal pressure gradient. The rural model outputs are then forced on a vertical diffusion urban microclimate model that solves vertical transport equations for momentum, temperature, and specific humidity. The urban microclimate model is also coupled to a building energy model using feedback interaction. The aerodynamic and thermal effects of urban elements and vegetation are considered in VCWG. To evaluate the VCWG model, a microclimate field c aign was held in Guelph, Canada, from 15 July 2018 to 5 September 2018. The meteorological measurements were carried out under a comprehensive set of wind directions, wind speeds, and thermal stability conditions in both the rural and the nearby urban areas. The model evaluation indicated that the VCWG predicted vertical profiles of meteorological variables in reasonable agreement with field measurements for selected days. In comparison to measurements, the overall model biases for potential temperature, wind speed, and specific humidity were within 5 %, 11 %, and 7 %, respectively. The performance of the model was further explored to investigate the effects of urban configurations such as plan and frontal area densities, varying levels of vegetation, seasonal variations, different climate zones, and time series analysis on the model predictions. The results obtained from the explorations were reasonably consistent with previous studies in the literature, justifying the reliability and computational efficiency of VCWG for operational urban development projects.
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-3877
Abstract: Variability of building height induces flow heterogeneity and directly controls the depth of the roughness sub-layer, the strength of mutual sheltering, and the overlapping of urban canopy flow, which poses challenges for accurate modeling. Large-eddy simulations over 96 building arrays with varying density, height variability (standard deviation of building height), and horizontal arrangements were conducted to reveal the impact on the urban flow. Results demonstrate a strong non-local building effect on the flow due to height variability, where flow around high buildings possesses high wind speed, dispersive momentum flux, and other distinctive flow patterns, whereas around low buildings, the flow pattern is less unique. The complex flow behavior is beyond the capacity of the current multi-layer urban canopy model (MLUCM) where turbulent constants and drag effects were considered in a simplified way. The increased height variability and urban density also blur the interface of urban canopy, further making MLUCM estimates model constants heavily based on a clear urban canopy inappropriate. Based on the original model, we comprehensively tested potential contributing factors such as the estimation of displacement height, height-dependent drag coefficients, and the extended roughness sublayer. The modified model provides a better overall agreement with the LES results, especially above the mean building height where the prediction of the extended urban canopy layer is largely improved.&
Publisher: Elsevier BV
Date: 12-2018
Publisher: Frontiers Media SA
Date: 25-11-2021
DOI: 10.3389/FENVS.2021.725974
Abstract: Maintaining indoor environmental (IEQ) quality is a key priority in educational buildings. However, most studies rely on outdoor measurements or evaluate limited spatial coverage and time periods that focus on standard occupancy and environmental conditions which makes it hard to establish causality and resilience limits. To address this, a fine-grained, low-cost, multi-parameter IOT sensor network was deployed to fully depict the spatial heterogeneity and temporal variability of environmental quality in an educational building in Sydney. The building was particularly selected as it represents a multi-use university facility that relies on passive ventilation strategies, and therefore suitable for establishing a living lab for integrating innovative IoT sensing technologies. IEQ analyses focused on 15 months of measurements, spanning standard occupancy of the building as well as the Black Summer bushfires in 2019, and the COVID-19 lockdown. The role of room characteristics, room use, season, weather extremes, and occupancy levels were disclosed via statistical analysis including mutual information analysis of linear and non-linear correlations and used to generate site-specific re-design guidelines. Overall, we found that 1) passive ventilation systems based on manual interventions are most likely associated with sub-optimum environmental quality and extreme variability linked to occupancy patterns, 2) normally closed environments tend to get very unhealthy under periods of extreme pollution and intermittent rotracted disuse, 3) the elevation and floor level in addition to room use were found to be significant conditional variables in determining heat and pollutants accumulation, presumably due to the synergy between local sources and vertical transport mechanisms. Most IEQ inefficiencies and health threats could be likely mitigated by implementing automated controls and smart logics to maintain adequate cross ventilation, prioritizing building airtightness improvement, and appropriate filtration techniques. This study supports the need for continuous and capillary monitoring of different occupied spaces in educational buildings to compensate for less perceivable threats, identify the room for improvement, and move towards healthy and future-proof learning environments.
Publisher: Elsevier BV
Date: 06-2021
Publisher: Springer Science and Business Media LLC
Date: 07-03-2018
Publisher: Springer Science and Business Media LLC
Date: 09-04-2017
Publisher: Wiley
Date: 24-11-2021
Publisher: American Geophysical Union (AGU)
Date: 08-2022
DOI: 10.1029/2022EF002682
Abstract: Urban overheating, driven by global climate change and urban development, is a major contemporary challenge that substantially impacts urban livability and sustainability. Overheating represents a multifaceted threat to the well‐being, performance, and health of in iduals as well as the energy efficiency and economy of cities, and it is influenced by complex interactions between building, city, and global scale climates. In recent decades, extensive discipline‐specific research has characterized urban heat and assessed its implications on human life, including ongoing efforts to bridge neighboring disciplines. The research horizon now encompasses complex problems involving a wide range of disciplines, and therefore comprehensive and integrated assessments are needed that address such interdisciplinarity. Here, our objective is to go beyond a review of existing literature and instead provide a broad overview and integrated assessments of urban overheating, defining holistic pathways for addressing the impacts on human life. We (a) detail the characterization of heat hazards and exposure across different scales and in various disciplines, (b) identify in idual sensitivities to urban overheating that increase vulnerability and cause adverse impacts in different populations, (c) elaborate on adaptive capacities that in iduals and cities can adopt, (d) document the impacts of urban overheating on health and energy, and (e) discuss frontiers of theoretical and applied urban climatology, built environment design, and governance toward reduction of heat exposure and vulnerability at various scales. The most critical challenges in future research and application are identified, targeting both the gaps and the need for greater integration in overheating assessments.
Publisher: Wiley
Date: 29-11-2021
Publisher: Frontiers Media SA
Date: 02-05-2022
DOI: 10.3389/FENVS.2022.867434
Abstract: The scientific field of urban climatology has long investigated the two-way interactions between cities and their overlying atmosphere through in-situ observations and climate simulations at various scales. Novel research directions now emerge through recent advancements in sensing and communication technologies, algorithms, and data sources. Coupled with rapid growth in computing power, those advancements augment traditional urban climate methods and provide unprecedented insights into urban atmospheric states and dynamics. The emerging field introduced and discussed here as Urban Climate Informatics (UCI) takes on a multidisciplinary approach to urban climate analyses by synthesizing two established domains: urban climate and climate informatics. UCI is a rapidly evolving field that takes advantage of four technological trends to answer contemporary climate challenges in cities: advances in sensors, improved digital infrastructure (e.g., cloud computing), novel data sources (e.g., crowdsourced or big data), and leading-edge analytical algorithms and platforms (e.g., machine learning, deep learning). This paper outlines the history and development of UCI, reviews recent technological and methodological advances, and highlights various applications that benefit from novel UCI methods and datasets.
Publisher: Elsevier BV
Date: 05-2019
Publisher: Elsevier BV
Date: 2016
Publisher: Routledge
Date: 08-09-2021
Publisher: Copernicus GmbH
Date: 15-05-2023
DOI: 10.5194/EGUSPHERE-EGU23-10461
Abstract: Urban heat is a local scale warming effect associated with urban areas where most of the world's population live. Due to the scarcity of air temperature (Ta) data, urban heat studies have been mostly focused on Land Surface Temperature (LST) extracted from satellite imagery and a quantitative understanding of how LST interacts with Ta within a city is still lacking. Using crowdsourced weather station data in Sydney, Australia, combined with high resolution satellite images and urban datasets (such as Local Climate Zone (LCZ) and building-level urban data), we explore the interaction between Ta and LST, and their intra-urban variabilities during different seasons. We found that LST and Ta have different characteristics and their dependency varies by season and LCZ. When exploring the relationship between Ta, LST, and variables describing the urban structure, such as building fraction, the correlation between LST and urban structure was stronger and more seasonal dependent than the Ta-urban form relationship. Moreover, stronger correlations between LST and Ta were observed in the less built-up areas within the city. We also found that the determinants of LST variability are different from the contributing factors of Ta. These findings provide new insights for quantitatively investigating surface and canopy urban heat and their relationship with land cover, providing fit-for-purpose information to mitigate the adverse effects of urban overheating at local and global scales.&
Publisher: Springer Science and Business Media LLC
Date: 24-08-2021
DOI: 10.1007/S10546-021-00658-6
Abstract: Good representation of turbulence in urban canopy models is necessary for accurate prediction of momentum and scalar distribution in and above urban canopies. To develop and improve turbulence closure schemes for one-dimensional multi-layer urban canopy models, turbulence characteristics are investigated here by analyzing existing large-eddy simulation and direct numerical simulation data. A range of geometries and flow regimes are analyzed that span packing densities of 0.0625 to 0.44, different building array configurations (cubes and cuboids, aligned and staggered arrays, and variable building height), and different incident wind directions ( $$0^\\circ $$ 0 ∘ and $$45^\\circ $$ 45 ∘ with regards to the building face). Momentum mixing-length profiles share similar characteristics across the range of geometries, making a first-order momentum mixing-length turbulence closure a promising approach. In vegetation canopies turbulence is dominated by mixing-layer eddies of a scale determined by the canopy-top shear length scale. No relationship was found between the depth-averaged momentum mixing length within the canopy and the canopy-top shear length scale in the present study. By careful specification of the intrinsic averaging operator in the canopy, an often-overlooked term that accounts for changes in plan area density with height is included in a first-order momentum mixing-length turbulence closure model. For an array of variable-height buildings, its omission leads to velocity overestimation of up to $$17\\%$$ 17 % . Additionally, we observe that the von Kármán coefficient varies between 0.20 and 0.51 across simulations, which is the first time such a range of values has been documented. When driving flow is oblique to the building faces, the ratio of dispersive to turbulent momentum flux is larger than unity in the lower half of the canopy, and wake production becomes significant compared to shear production of turbulent momentum flux. It is probable that dispersive momentum fluxes are more significant than previously thought in real urban settings, where the wind direction is almost always oblique.
Publisher: Elsevier BV
Date: 03-2020
Publisher: Springer Science and Business Media LLC
Date: 14-09-2022
DOI: 10.1038/S41598-022-19431-X
Abstract: Cities with different background climates experience different thermal environments. Many studies have investigated land cover effects on surface urban heat in in idual cities. However, a quantitative understanding of how background climates modify the thermal impact of urban land covers remains elusive. Here, we characterise land cover and their impacts on land surface temperature (LST) for 54 highly populated cities using Landsat-8 imagery. Results show that urban surface characteristics and their thermal response are distinctly different across various climate regimes, with the largest difference for cities in arid climates. Cold cities show the largest seasonal variability, with the least seasonality in tropical and arid cities. In tropical, temperate, and cold climates, normalised difference built-up index (NDBI) is the strongest contributor to LST variability during warm months followed by normalised difference vegetation index (NDVI), while normalised difference bareness index (NDBaI) is the most important factor in arid climates. These findings provide a climate-sensitive basis for future land cover planning oriented at mitigating local surface warming.
Publisher: Wiley
Date: 06-07-2022
Publisher: Wiley
Date: 27-04-2022
Publisher: Elsevier BV
Date: 03-2019
Publisher: American Geophysical Union (AGU)
Date: 07-2023
DOI: 10.1029/2022MS003287
Abstract: Urban heterogeneity, such as the variation of street layouts, building shapes, and building heights, cannot be fully represented by density parameters commonly used in idealized urban environmental analyses. To address this shortcoming and better model flow fields over complex urban neighborhoods, we propose two novel descriptive geometric parameters, alignedness and building facet entropy, which quantify the connectivity of inter‐building spaces along the prevailing wind direction and the variation of building facet orientations, respectively. We then conducted large eddy simulations over 101 urban layouts, including realistic urban configurations with uniform building height as well as idealized building arrays with variable heights, and evaluated the resulting bulk flow properties. Urban canopy flow over realistic neighborhoods resembles staggered building arrays for low urban densities but becomes similar to aligned configurations beyond λ p ∼ 0.25 where the realistic flow is less sensitive to changes in density. We further show that compared to traditional density parameters (such as plan and frontal area densities), the mean alignedness, a measure of connectivity of flow paths in street canyons, better predicts canopy‐averaged flow properties. Furthermore, for realistic urban flow, the dispersive momentum flux shows a clear increasing trend with building density, and a decreasing trend with alignedness, which is in contrast with idealized cases that exhibit no clear trend. This distinct behavior further highlights the necessity of evaluating flow over realistic urban layouts for flow parameterization. This study provides an improved method of describing urban layouts for flow characterization that can be applied in neighborhood‐scale urban canopy parameterization.
Publisher: Elsevier BV
Date: 06-2017
Publisher: Springer Science and Business Media LLC
Date: 14-10-2018
Publisher: Copernicus GmbH
Date: 18-02-2021
Abstract: Abstract. The Vertical City Weather Generator (VCWG) is a computationally efficient urban microclimate model developed to predict temporal and vertical variation of potential temperature, wind speed, specific humidity, and turbulent kinetic energy. It is composed of various sub-models: a rural model, an urban vertical diffusion model, a radiation model, and a building energy model. Forced with weather data from a nearby rural site, the rural model is used to solve for the vertical profiles of potential temperature, specific humidity, and friction velocity at 10 m a.g.l. The rural model also calculates a horizontal pressure gradient. The rural model outputs are applied to a vertical diffusion urban microclimate model that solves vertical transport equations for potential temperature, momentum, specific humidity, and turbulent kinetic energy. The urban vertical diffusion model is also coupled to the radiation and building energy models using two-way interaction. The aerodynamic and thermal effects of urban elements, surface vegetation, and trees are considered. The predictions of the VCWG model are compared to observations of the Basel UrBan Boundary Layer Experiment (BUBBLE) microclimate field c aign for 8 months from December 2001 to July 2002. The model evaluation indicates that the VCWG predicts vertical profiles of meteorological variables in reasonable agreement with the field measurements. The average bias, root mean square error (RMSE), and R2 for potential temperature are 0.25 K, 1.41 K, and 0.82, respectively. The average bias, RMSE, and R2 for wind speed are 0.67 m s−1, 1.06 m s−1, and 0.41, respectively. The average bias, RMSE, and R2 for specific humidity are 0.00057 kg kg−1, 0.0010 kg kg−1, and 0.85, respectively. In addition, the average bias, RMSE, and R2 for the urban heat island (UHI) are 0.36 K, 1.2 K, and 0.35, respectively. Based on the evaluation, the model performance is comparable to the performance of similar models. The performance of the model is further explored to investigate the effects of urban configurations such as plan and frontal area densities, varying levels of vegetation, building energy configuration, radiation configuration, seasonal variations, and different climate zones on the model predictions. The results obtained from the explorations are reasonably consistent with previous studies in the literature, justifying the reliability and computational efficiency of VCWG for operational urban development projects.
Publisher: Center for Open Science
Date: 20-06-2020
Abstract: This is a comment to the paper "Magnitude of urban heat islands largely explained by climate and population" by Manoli et al. (2019, Nature 573 p. 55-60 0.1038/s41586-019-1512-9)
Publisher: MDPI AG
Date: 25-08-2017
DOI: 10.3390/ATMOS8090159
Abstract: Dense urban areas restrict air movement, causing airflow in urban street canyons to be much lower than the flow above buildings. Boosting near-ground wind speed can enhance thermal comfort in warm climates by increasing skin convective heat transfer. We explored the potential of a wind catcher to direct atmospheric wind into urban street canyons. We arranged scaled-down models of buildings with a wind catcher prototype in a water channel to simulate flow across two-dimensional urban street canyons. Velocity profiles were measured with Acoustic Doppler Velocimeters. Experiments showed that a wind catcher enhances pedestrian-level wind speed in the target canyon by 2.5 times. The flow enhancement is local to the target canyon with little effect in other canyons. With reversed flow direction, a “reversed wind catcher” has no effect in the target canyon but reduces the flow in the immediate downstream canyon. The reversed wind catcher exhibits a similar blockage effect of a tall building amid an array of lower buildings. Next, we validated Computational Fluid Dynamics (CFD) simulations of all cases with experiments and extended the study to reveal impacts on three-dimensional ensembles of buildings. A wind catcher with closed sidewalls enhances maximum pedestrian-level wind speed in three-dimensional canyons by four times. Our results encourage better designs of wind catchers to increase wind speed in targeted areas.
Publisher: Elsevier BV
Date: 06-2015
Publisher: Frontiers Media SA
Date: 06-07-2022
DOI: 10.3389/FENVS.2022.866398
Abstract: In urban climate studies, datasets used to describe urban characteristics have traditionally taken a class-based approach, whereby urban areas are classified into a limited number of typologies with a resulting loss of fidelity. New datasets are becoming increasingly available that describe the three-dimensional structure of cities at sub-metre micro-scale resolutions, resolving in idual buildings and trees across entire continents. These datasets can be used to accurately determine local characteristics without relying on classes, but their direct use in numerical weather and climate modelling has been limited by their availability, and because they require processing to conform to the required inputs of climate models. Here, we process building-resolving datasets across large geographical extents to derive city-descriptive parameters suitable as common model inputs at resolutions more appropriate for local or meso-scale modelling. These parameter values are then compared with the ranges obtained through the class-based Local Climate Zone framework. Results are presented for two case studies, Sydney and Melbourne, Australia, as open access data tables for integration into urban climate models, as well as codes for processing high-resolution and three-dimensional urban datasets. We also provide an open access 300 m resolution building morphology and surface cover dataset for the Sydney metropolitan region (approximately 5,000 square kilometres). The use of building resolving data to derive model inputs at the grid scale better captures the distinct heterogenetic characteristics of urban form and fabric compared with class-based approaches, leading to a more accurate representation of cities in climate models. As consistent building-resolving datasets become available over larger geographical extents, we expect bottom-up approaches to replace top-down class-based frameworks.
Publisher: IOP Publishing
Date: 11-2019
DOI: 10.1088/1742-6596/1343/1/012145
Abstract: Labelled human comfort data can be a valuable resource in optimising the built environment, and improving the wellbeing of in idual occupants. The acquisition of labelled data however remains a challenge. This paper presents a methodology for the collection of in-situ occupant feedback data using a Fitbit smartwatch. The clock-face application cozie can be downloaded free-of-charge on the Fitbit store and tailored to fit a range of occupant comfort related experiments. In the initial trial of the app, fifteen users were given a smartwatch for one month and were prompted to give feedback on their thermal preferences. In one month, with minimal administrative overhead, 1460 labelled responses were collected. This paper demonstrates how these large data sets of human feedback can be analysed to reveal a range of results from building anomalies, occupant behaviour, occupant personality clustering, and general feedback related to the building. The paper also discusses limitations in the approach and the next phase of design of the platform.
Publisher: Routledge
Date: 08-09-2021
Publisher: Elsevier BV
Date: 09-2020
Publisher: Copernicus GmbH
Date: 19-09-2023
Publisher: Elsevier BV
Date: 06-2020
Publisher: Elsevier
Date: 2023
Location: Spain
Location: Singapore
Location: United States of America
Start Date: 08-2017
End Date: 12-2024
Amount: $30,050,000.00
Funder: Australian Research Council
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