@ The University of Oklahoma

Author: Chenghao Wang

New paper on urban thermal stress modeling published in Renewable and Sustainable Energy Reviews

Our new paper, “Realistic representation of city street-level human thermal stress via a new urban climate-human coupling system“, is published in Renewable and Sustainable Energy Reviews (IF: 16.799). This paper is from the collaboration with the Healthy Cities Laboratory at The University of Hong Kong.

The Share Link to download a copy of our paper is https://authors.elsevier.com/a/1flIY4s9Hw6370 (valid until Nov 03, 2022).

Authors: Xinjie Huang, Jiyun Song, Chenghao Wang, and Pak Wai Chan

Abstract: Urban overheating aggravated by climate change and rapid urbanization poses a severe threat to thermal health of urban residents. To more realistically represent street-level heat stress, we propose a new urban climate-human coupling system by integrating an advanced urban canopy model (UCM) with a new human-environment adaptive thermal stress (HEATS) module. The coupled UCM-HEATS system features a state-of-the-art solution to complicated human-street radiative exchanges and incorporates dynamic human thermoregulatory responses to microclimatic changes. The UCM-HEATS system was evaluated in a typical hot and humid city, Hong Kong, and then applied to investigate street-level thermal stress in various urban settings and under different personal conditions. By explicitly resolving shading effects of buildings and trees on human radiation budgets, our study emphasizes the marked effectiveness of active shade management using green and gray infrastructure on daytime heat mitigation, proposing a “right shade, right place, right time” paradigm for regulating important street canyon geometries (building height, road width, and tree crown width) and orientations. Additionally, human evaporative heat dissipation can be hindered by urban moisture islands and wind impediments; thus, a detailed urban ventilation strategy is suggested considering different temperature-humidity combinations. For personal heat protection, we identified an evident cooling effect of high-albedo clothing and a thermal-comfort-optimal walking speed. Special attention is paid to heat-vulnerable groups, especially older people who suffer from notably higher heat risks during pandemics with facemask-induced heat burden. Bridging urban climate and human ergonomics, this study aims to advance human-centric urban design toward future smart, resilient, and inclusive cities.

DOI: https://doi.org/10.1016/j.rser.2022.112919

Fig. 2. Schematic of the Urban Canopy Model-Human-Environment Adaptive Thermal Stress (UCM-HEATS) model.

We are seeking Ph.D. students to join our lab!

The Sustainable URban Futures (SURF) Lab in the School of Meteorology and the Department of Geography and Environmental Sustainability at the University of Oklahoma in Norman, Oklahoma, USA is seeking self-motivated doctoral students who are willing to pursue research in the areas of urban climate and urban meteorology. The successful candidate will enroll in the Ph.D. program in either Meteorology or Geography and Environmental Sustainability.

For prospective Ph.D. students, a master’s degree in meteorology, atmospheric science, geography, engineering, Earth science, or environmental science is preferred but not required. Candidates with experience in using programming languages, geographic information system, and/or remote sensing products are especially encouraged to apply. Successful candidates will work with Dr. Chenghao Wang and his collaborators at the University of Oklahoma and other research institutes. With the strong modeling and/or data analysis skills developed during the training, successful candidates will have the opportunity to study a wide range of urban issues and challenges as well as potential mitigation and adaptation measures on the path toward sustainable and resilient urban environments, and eventually to push the boundaries of our knowledge about past, present, and future cities.

If you are interested, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu) by Oct 15, 2022 and attach (1) a copy of your CV, (2) a brief statement that highlights your interest (and skills and previous research experience, if applicable) relevant to the Sustainable URban Futures (SURF) Lab, and (3) a copy of unofficial academic transcripts. Review of applications will begin immediately and continue until the position is filled.

Founded in 1890, the University of Oklahoma is a public research university located in Norman, Oklahoma just 20 mins. south of Oklahoma City, one of the top 50 metropolitan areas in the United States. The university is classified among “R1: Doctoral Universities – Very high research activity”. More information regarding the University of Oklahoma, the School of Meteorology, the Department of Geography and Environmental Sustainability, and available degree programs can be found https://sites.create.ou.edu/chenghaowang/about/.

For further information, please contact Dr. Chenghao Wang.

A PDF version of this post in English can be downloaded here

中文版招生简介可从此处下载

We are organizing a Special Issue “Using Remote Sensing and GIS Technique/Methods to Address Current Urbanization Issues” in Remote Sensing

We are running a Special Issue entitled “Using Remote Sensing and GIS Methods to Study Current Urbanization Issues” with the journal Remote Sensing (IF: 5.349, ISSN 2072-4292). This special issue belongs to the section “Urban Remote Sensing“. The guest editors for this issue are Dr. Zutao Ouyang from Stanford University, Dr. Chenghao Wang from the University of Oklahoma, and Dr. Peilei Fan from Michigan State University. The submission deadline is April 30, 2023.

Further details on this Special Issue and how to submit can be found here: https://www.mdpi.com/journal/remotesensing/special_issues/Y602B3CNT6.

The increase in the number of people living in urban areas, the proliferation of megacities, and the pervasive expansion of per-urban areas are some of the most challenging transformations in the 21st century. The complexity of urbanization imposes intertwined social, economic, and environmental impacts. While urbanization can achieve social and economic benefits, such as improved education, job opportunities, and healthcare, it also brings numerous negative ecological and social consequences, such as increasing the cost of living and social and economic inequality, deforestation, loss of natural habitat and biodiversity, soil, air, and water pollution, increased emission of greenhouse gases, heat island effect, and increased risk of disease. Therefore, it is imperative to create a sustainable urban environment that reconciles the conflicts between human and natural systems and reduces the negative impacts of the urbanization process. Remote sensing techniques could provide a “unique view” of the urban landscape. When combined with GIS-based spatial analysis, it can serve as a powerful tool to study processes and patterns of urbanization, drivers and impacts of urbanization, and the coupled human and natural systems embedded in urban ecosystems.

The main objective of this Special Issue shall be to provide a scientific forum for advancing the successful implementation of remote sensing (RS) technologies and geographic information system (GIS)-based methods towards urbanization issues and the peri-urban environment and to foster informed debates among scientists and stakeholders on the environmental issues prevalent therein, relating these to city growth dynamics.

This Special Issue will provide readers in the fields of GIS, remote sensing, Earth science, environmental science, and computer science with theoretical and practical advances in urbanization-related research. Topics of research articles, or reviews, submitted to this Special Issue include, but are not limited to:

  • Integration of remote sensing data for urban environmental analysis.
  • Novel remote sensing applications (new sensors, new methodology, etc.) in urban ecology and sustainability.
  • Tracking urban growth and land use change with remote sensing technologies and GIS tools.
  • Remote sensing and GIS analysis informing/supporting urban and peri-urban governance and planning.
  • Landscape ecological analysis.
  • Urban growth and fringe development.
  • Water, river, and lake monitoring in and surrounding urban areas.
  • Relations between urban growth and climate change.
  • Social and environmental justice issues relevant to urban residents.
  • Impacts and mitigation of urban heat.

New paper on causal urban climate network published in Journal of Environmental Management

Our new paper, “Detecting the causal influence of thermal environments among climate regions in the United States“, is published in Journal of Environmental Management (IF: 8.910). This paper is from the collaboration with the Urban Environment Research Group at Arizona State University (ASU). The first author, Xueli Yang, is a Ph.D. candidate at ASU. Congratulations to Xueli!

The Share Link to download a copy of our paper is https://authors.elsevier.com/c/1fepj14Z6tlDl~ (valid until Oct 15, 2022).

Authors: Xueli Yang, Zhi-Hua Wang, Chenghao Wang, and Ying-Cheng Lai

Abstract: The quantification of cross-regional interactions for the atmospheric transport processes is of crucial importance to improve the predictive capacity of climatic and environmental system modeling. The dynamic interactions in these complex systems are often nonlinear and non-separable, making conventional approaches of causal inference, such as statistical correlation or Granger causality, infeasible or ineffective. In this study, we applied an advanced approach, based on the convergent cross mapping algorithm, to detect and quantify the causal influence among different climate regions in the contiguous U.S. in response to temperature perturbations using the long-term (1901–2018) climatology of near surface air temperature record. Our results show that the directed causal network constructed by convergent cross mapping algorithm, enables us to distinguish the causal links from spurious ones rendered by statistical correlation. We also find that the Ohio Valley region, as an atmospheric convergent zone, acts as the regional gateway and mediator to the long-term thermal environments in the U.S. In addition, the temporal evolution of dynamic causality of temperature exhibits superposition of periodicities at various time scales, highlighting the impact of prominent low frequency climate variabilities such as El Niño–Southern Oscillation. The proposed method in this work will help to promote novel system-based and data-driven framework in studying the integrated environmental system dynamics.

DOI: https://doi.org/10.1016/j.jenvman.2022.116001

Fig. 3. Comparison of the correlation and causality networks for the nine CONUS climate regions: (a) the matrix of connectivity determined by undirected statistical correlation, (b) the matrix of connectivity determined by directed causality, and (c) graphic representation of causal and spurious links resulted from (a) and (b), with a threshold strength of 0.5. Cells with dashed boxes in (a) and (b) represent causally (above the threshold) connected pairs. The gray dashed lines represent the spurious link between different regions, and lines with an arrow the directed causal influence with strength denoted by different colors (the same scale as in (b)).

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