@ The University of Oklahoma

Author: Chenghao Wang Page 5 of 6

New paper on urban land surface model intercomparison published in Quarterly Journal of the Royal Meteorological Society

Our new paper, “Evaluation of 30 urban land surface models in the Urban-PLUMBER project: Phase 1 results“, is published in Quarterly Journal of the Royal Meteorological Society (IF: 8.9).

This paper is one of the outcomes of the second international urban land surface model intercomparison project. The paper and its supporting information can be downloaded at https://rmets.onlinelibrary.wiley.com/doi/full/10.1002/qj.4589.

Authors: Lipson, M. J., Grimmond, S., Best, M., Abramowitz, G., Coutts, A., Tapper, N., Baik, J.-J., Beyers, M., Blunn, L., Boussetta, S., Bou-Zeid, E., De Kauwe, M. G., de Munck, C., Demuzere, M., Fatichi, S., Fortuniak, K., Han, B.-S., Hendry, M., Kikegawa, Y., Kondo, H., Lee, D.-I., Lee, S.-H., Lemonsu, A., Machado, T., Manoli, G., Martilli, A., Masson, V., McNorton, J., Meili, N., Meyer, D., Nice, K. A., Oleson, K. W., Park, S.-B., Roth, M., Schoetter, R., Simón-Moral, A., Steeneveld, G.-J., Sun, T., Takane, Y., Thatcher, M., Tsiringakis, A., Varentsov, M., Wang, C., Wang, Z.-H., & Pitman, A.

Abstract: Accurately predicting weather and climate in cities is critical for safeguarding human health and strengthening urban resilience. Multimodel evaluations can lead to model improvements; however, there have been no major intercomparisons of urban-focussed land surface models in over a decade. Here, in Phase 1 of the Urban-PLUMBER project, we evaluate the ability of 30 land surface models to simulate surface energy fluxes critical to atmospheric meteorological and air quality simulations. We establish minimum and upper performance expectations for participating models using simple information-limited models as benchmarks. Compared with the last major model intercomparison at the same site, we find broad improvement in the current cohort’s predictions of short-wave radiation, sensible and latent heat fluxes, but little or no improvement in long-wave radiation and momentum fluxes. Models with a simple urban representation (e.g., ‘slab’ schemes) generally perform well, particularly when combined with sophisticated hydrological/vegetation models. Some mid-complexity models (e.g., ‘canyon’ schemes) also perform well, indicating efforts to integrate vegetation and hydrology processes have paid dividends. The most complex models that resolve three-dimensional interactions between buildings in general did not perform as well as other categories. However, these models also tended to have the simplest representations of hydrology and vegetation. Models without any urban representation (i.e., vegetation-only land surface models) performed poorly for latent heat fluxes, and reasonably for other energy fluxes at this suburban site. Our analysis identified widespread human errors in initial submissions that substantially affected model performances. Although significant efforts are applied to correct these errors, we conclude that human factors are likely to influence results in this (or any) model intercomparison, particularly where participating scientists have varying experience and first languages. These initial results are for one suburban site, and future phases of Urban-PLUMBER will evaluate models across 20 sites in different urban and regional climate zones.

DOI: https://doi.org/10.1002/qj.4589

Fig. 1. Model schematics of the main built, hydrological and behavioural attributes for participating models. Here models are categorised into five cohorts (left column) based on the geometric representation of buildings, with built, hydrological and behavioural attributes used to refine a ‘total complexity’ (Figure 2). Block array, statistical distribution and building-resolved models are grouped together into a ‘complex’ cohort in later analysis.

New paper on urban building energy use published in Nature Communications

Our new paper, “Impacts of climate change, population growth, and power sector decarbonization on urban building energy use“, is published in Nature Communications (IF: 16.6).

The paper and its supplement can be downloaded at https://www.nature.com/articles/s41467-023-41458-5.

Authors: Chenghao Wang, Jiyun Song, Dachuan Shi, Janet L. Reyna, Henry Horsey, Sarah Feron, Yuyu Zhou, Zutao Ouyang, Ying Li, and Robert B. Jackson

Abstract: Climate, technologies, and socio-economic changes will influence future building energy use in cities. However, current low-resolution regional and state-level analyses are insufficient to reliably assist city-level decision-making. Here we estimate mid-century hourly building energy consumption in 277 U.S. urban areas using a bottom-up approach. The projected future climate change results in heterogeneous changes in energy use intensity (EUI) among urban areas, particularly under higher warming scenarios, with on average 10.1–37.7% increases in the frequency of peak building electricity EUI but over 110% increases in some cities. For each 1 °C of warming, the mean city-scale space-conditioning EUI experiences an average increase/decrease of ~14%/ ~ 10% for space cooling/heating. Heterogeneous city-scale building source energy use changes are primarily driven by population and power sector changes, on average ranging from –9% to 40% with consistent south–north gradients under different scenarios. Across the scenarios considered here, the changes in city-scale building source energy use, when averaged over all urban areas, are as follows: –2.5% to –2.0% due to climate change, 7.3% to 52.2% due to population growth, and –17.1% to –8.9% due to power sector decarbonization. Our findings underscore the necessity of considering intercity heterogeneity when developing sustainable and resilient urban energy systems.

DOI: https://doi.org/10.1038/s41467-023-41458-5

Fig. 1. a SSP1-2.6 scenario. b SSP2-4.5 scenario. c SSP3-7.0 scenario. d SSP5-8.5 scenario. Each point represents the relative change (%) based on the ensemble mean of the simulations driven by 10 CMIP6 models under each SSPX-Y scenario.

Open Ph.D. positions at the SURF Lab (2024 Fall admission)

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 two doctoral students who are willing to pursue research in the following areas:

1. Urban Air Pollution Modeling Position

The SURF Lab is seeking a self-motivated PhD student to develop and apply an integrated high-resolution pollutant dispersion model over complex terrain (including urban environments), which will be evaluated with field observations. The PhD student will be supported through a project funded by the U.S. Department of Energy through the iM4 Technologies program (Innovative Methane Measurement, Monitoring, and Mitigation Technologies). The successful candidate will enroll in the Ph.D. program in Meteorology and will begin in Fall 2024 (starting in Aug 2024). For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, engineering, Earth science, or environmental science is preferred. Candidates with the following experience/expertise are especially encouraged to apply: (1) previous research experience in air pollution modeling, (2) proficiency in programming languages (Matlab, Fortran, R, and/or Python), and/or (3) familiar with geographic information systems.

2. Urban Climate Modeling and Analytics Position

The SURF Lab is seeking a self-motivated PhD student to work on multiscale urban climate models and data analytics. The PhD student will be supported through a mixture of GTA and GRA. The successful candidate will enroll in the Ph.D. program in Meteorology or Geography and Environmental Sustainability and will begin in Fall 2024 (starting in Aug 2024). For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, geography, engineering, Earth science, or environmental science is preferred but not required. Candidates with experience in using programming languages (e.g., Matlab, Python, R, and/or Fortran), reanalysis data, climate projections, and/or remotely sensed data are especially encouraged to apply.

Successful candidates will work with Dr. Chenghao Wang at the University of Oklahoma. With the strong modeling and/or data analysis skills developed during the training, successful candidates will have the opportunity to work in an interdisciplinary research team and 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.

If you are interested, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu) by Nov 10, 2023 (Fall 2024 admission), and attach (1) a copy of your CV, (2) a brief statement that highlights your interest (and skills and previous research experience when applicable) relevant to the position description, and (3) a copy of unofficial academic transcripts and TOEFL/IELTS/PET/DET transcripts (when applicable). Review of applications will begin immediately and continue until the position is filled.

Admission requirements:

About the SURF Lab:

The Sustainable URban Futures Lab at the University of Oklahoma examines the mechanisms of urban environments, their interactions with regional and global climates, and their impacts on building energy use, carbon emissions, and public health using numerical models and data analytics. Through our interdisciplinary research, we aim to advance the understanding of the urban environment and support more sustainable urban development under global environmental changes. Our research has been funded by multiple agencies including the U.S. Department of Energy (DOE), the National Science Foundation (NSF), and the National Oceanic and Atmospheric Administration (NOAA). Our work has been published in several leading journals such as Nature Aging, Nature Communications, Science Advances, Geophysical Research Letters, Remote Sensing of Environment, Earth’s Future, Building and Environment, and Renewable and Sustainable Energy Reviews. More information about ongoing research can be found here: https://sites.create.ou.edu/chenghaowang/.

About the University of Oklahoma:

Founded in 1890, the University of Oklahoma is a public research university located in Norman, Oklahoma just 20 minutes 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”. The School of Meteorology is the largest such program in the nation and is routinely ranked near the top of the nation. 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 here: https://sites.create.ou.edu/chenghaowang/about/.

For further information, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu).

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:

Dr. Wang presented at ICUC11 in Sydney

Dr. Wang recently presented the research conducted by the SURF Lab at the 11th International Conference on Urban Climate (ICUC11) in Sydney, Australia.

Yuqi Huang joined our group. Welcome!

Yuqi Huang recently joined the Sustainable URban Futures (SURF) Lab as a Ph.D. student majoring in Meteorology. Welcome!

Before coming to OU, Yuqi completed his master’s degree in civil engineering at Beijing Normal University, China. His previous research focused on understanding and modeling the physical, hydrological, and ecological processes of inland water bodies and the response of aquatic ecosystems to climate change.

Yuqi has an interest in interdisciplinary subjects across hydrology, meteorology, and statistics. His Ph.D. research will focus on understanding and improving the predictive capability of urban hydrometeorological and climate simulations across multiple spatial scales.

Open Ph.D. positions at the SURF Lab (2024 Spring or Fall admission)

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 two doctoral students who are willing to pursue research in the following areas:

1. Urban Air Pollution Modeling Position:

The SURF Lab is seeking a self-motivated Ph.D. student to develop and apply an integrated high-resolution pollutant dispersion model over complex terrain (including urban environments), which will be evaluated with field observations. The Ph.D. student will be supported through a project funded by the U.S. Department of Energy through the iM4 Technologies program (Innovative Methane Measurement, Monitoring, and Mitigation Technologies). The successful candidate will enroll in the Ph.D. program in Meteorology and will begin in Spring 2024 (starting in Jan 2024) or Fall 2024 (starting in Aug 2024). For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, engineering, Earth science, or environmental science is preferred. Candidates with the following experience/expertise are especially encouraged to apply: (1) previous research experience in air pollution modeling, (2) proficiency in programming languages (Matlab, Fortran, and/or Python), and/or (3) familiar with geographic information systems.

2. Urban Climate Position:

The SURF Lab is seeking a self-motivated Ph.D. student to work on multiscale urban climate models and/or urban climate data analytics. The Ph.D. student will be supported through a mixture of GTA and GRA. The successful candidate will enroll in the Ph.D. program in either Meteorology or Geography and Environmental Sustainability and will begin in Spring 2024 (starting in Jan 2024) or Fall 2024 (starting in Aug 2024). For prospective Ph.D. students, a master’s degree in atmospheric science, meteorology, geography, engineering, Earth science, or environmental science is preferred but not required. Candidates with experience in using programming languages (e.g., Matlab, Python, R, and/or Fortran), geographic information systems, climate projections, and/or remotely sensed data are especially encouraged to apply.

Successful candidates will work with Dr. Chenghao Wang at the University of Oklahoma. With the strong modeling and/or data analysis skills developed during the training, successful candidates will have the opportunity to work in an interdisciplinary research team and 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.

If you are interested, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu) by Sep 1, 2023 (Spring 2024 admission) or Nov 1, 2023 (Fall 2024 admission), and attach (1) a copy of your CV, (2) a brief statement that highlights your interest (and skills and previous research experience when applicable) relevant to the position description, and (3) a copy of unofficial academic transcripts and TOEFL/IELTS/PET/DET transcripts (when applicable). Review of applications will begin immediately and continue until the position is filled.

Admission requirements:

About the SURF Lab:

The Sustainable URban Futures Lab at the University of Oklahoma examines the mechanisms of urban environments, their interactions with regional and global climates, and their impacts on building energy use, carbon emissions, and public health using numerical models and data analytics. Through our interdisciplinary research, we aim to advance the understanding of the urban environment and support more sustainable urban development under global environmental changes. Our research has been funded by multiple agencies including the U.S. Department of Energy (DOE), the National Science Foundation (NSF), and the National Oceanic and Atmospheric Administration (NOAA). More information about ongoing research can be found here: https://sites.create.ou.edu/chenghaowang/.

About the University of Oklahoma:

Founded in 1890, the University of Oklahoma is a public research university located in Norman, Oklahoma just 20 minutes 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”. The School of Meteorology is the largest such program in the nation and is routinely ranked near the top of the nation. 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 here: https://sites.create.ou.edu/chenghaowang/about/.

For further information, please contact Dr. Chenghao Wang (chenghao.wang@ou.edu).

Sarah Henry successfully completed her REU project. Congratulations!

Sarah Henry has recently accomplished a successful National Weather Center REU project. Congratulations, Sarah!

Sarah delivering her work at the final presentation on Aug 21, 2023.

Throughout a 10-week journey, she investigated the spatial and temporal patterns of compound heat wave and particle pollution episodes in the urban environment across the contiguous U.S. (CONUS). Based on geospatial analyses of nighttime air temperature and daily PM2.5 concentration data, she found that, compared to rural surroundings, the majority of urban areas in the CONUS experienced more frequent, more intense, and longer-lasting heat waves, PM2.5 pollution days, as well as the compound episodes. Regionally, the Northeast and Ohio Valley exhibited the highest frequency of compound heat and pollution events, while the Northeast, Ohio Valley, and Southeast showed the longest durations of these events. Furthermore, the West and Southwest regions had the highest heat intensity during compound events, while the Northeast, Ohio Valley, and Southeast experienced the highest pollution intensity. Sarah’s research offers a pioneering perspective on compound heat and pollution episodes in U.S. cities, providing valuable insights for future investigations in this field.

Fig. 6. Regional comparison of compound events (CEs) frequency, heat intensity, pollution intensity, and duration for UAs and RAs based on NOAA’s 9 climate regions: Northeast (NE), South (S), Ohio Valley (OV), Southeast (SE), Northwest (NW), Southwest (SW), Upper Midwest (UM), West (W), and Northern Rockies and Plains (NRP). Red dashed line indicates Rural Area (RA) average, and blue dashed line indicates Urban Area (UA) average. The center line of each box is the median, the box extends from lower to upper quartiles, vertical lines denote 1.5 times the interquartile range, and diamonds are outliers.

Her final paper titled “Compound Heat Wave and PM2.5 Pollution Episodes in U.S. Cities” has been posted on arXiv (https://doi.org/10.48550/arXiv.2307.15296) and is also available on REU’s website.

The REU program is funded by the National Science Foundation under Grant No. AGS-2050267. More information about REU and how to apply can be found here.

New paper on compound urban heat-ozone pollution published in Scientific Reports

Our new paper, “Compound climate-pollution extremes in Santiago de Chile“, is published in Scientific Reports (IF: 4.996).

The paper and its supplement can be downloaded at https://www.nature.com/articles/s41598-023-33890-w.

Authors: Sarah Feron, Raúl R. Cordero, Alessandro Damiani, Pedro Oyola, Tabish Ansari, Juan C. Pedemonte, Chenghao Wang, Zutao Ouyang, and Valentina Gallo

Abstract: Cities in the global south face dire climate impacts. It is in socioeconomically marginalized urban communities of the global south that the effects of climate change are felt most deeply. Santiago de Chile, a major mid-latitude Andean city of 7.7 million inhabitants, is already undergoing the so-called “climate penalty” as rising temperatures worsen the effects of endemic ground-level ozone pollution. As many cities in the global south, Santiago is highly segregated along socioeconomic lines, which offers an opportunity for studying the effects of concurrent heatwaves and ozone episodes on distinct zones of affluence and deprivation. Here, we combine existing datasets of social indicators and climate-sensitive health risks with weather and air quality observations to study the response to compound heat-ozone extremes of different socioeconomic strata. Attributable to spatial variations in the ground-level ozone burden (heavier for wealthy communities), we found that the mortality response to extreme heat (and the associated further ozone pollution) is stronger in affluent dwellers, regardless of comorbidities and lack of access to health care affecting disadvantaged population. These unexpected findings underline the need of a site-specific hazard assessment and a community-based risk management.

DOI: https://doi.org/10.1038/s41598-023-33890-w

Fig. 1. While socioeconomic inequalities generally drive disparities in the mortality rate, the gap between rich and poor considerably narrows during summer. (a) Annual mortality rate (number of annual deaths per 100,000 population) in individuals aged 65 and over across Santiago, averaged over the period 2010–2019. (b) Daily mortality rate in inhabitants (aged ≥ 65 years) of Santiago. (c) Daily mortality rate in inhabitants (aged ≥ 65 years) of Santiago, averaged over two periods: 1993–2002 (blue line) and 2010–2019 (red line). (d) Annual income per capita (2017 US$) across Santiago. (e) Progress of winter mortality rate in inhabitants (aged ≥ 65 years) of affluent (blue line) and deprived (red line) municipalities over the period 1992–2019. (f) Progress of summer mortality rate in inhabitants (aged ≥ 65 years) of affluent (blue line) and deprived (red line) municipalities over the period 1992–2019.

New paper on causal networks of precipitation published in Geophysical Research Letters

Our new paper, “Finding causal gateways of precipitation over the contiguous United States“, is published in Geophysical Research Letters (IF: 5.576). This paper is from the collaboration with the Urban Environment Research Group at Arizona State University (ASU).

The paper and its supplement can be downloaded at https://agupubs.onlinelibrary.wiley.com/doi/10.1029/2022GL101942.

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

Abstract: Identifying regions that mediate regional propagation of atmospheric perturbations is important to assessing the susceptibility and resilience of complex hydroclimate systems. Detecting the regional gateways through causal inference, can help unravel the interplay of physical processes and inform projections of future changes. In this study, we characterize the causal interactions among nine climate regions in the contiguous United States using long-term (1901–2018) precipitation data. The constructed causal networks reveal the cross-regional propagation of precipitation perturbations. Results show that the Ohio Valley region acts as an atmospheric gateway for precipitation and moisture transport in the U.S., which is largely regulated by the regional convective uplift. The findings have implications for improving predicative capacity of hydroclimate modeling of regional precipitation.

Plain Language Summary: Successful detection of causality in complex systems is important to unraveling the underlying mechanisms of system dynamics. The dynamic interactions in Earth’s climate system are often nonlinear, weakly or moderately coupled, and essentially non-separable, which renders conventional approaches of causal inference, such as statistical correlation or Granger causality, infeasible or ineffective. Here we applied the convergent cross mapping method to detect causal influence among different climate regions in the contiguous U.S. in response to precipitation perturbations. The results of our study show that the Ohio Valley region, as an atmospheric convergence zone, acts as a regional gateway and mediator for the long-term precipitation perturbations in the U.S. The temporal evolution of causal effect and susceptibility exhibits superposition of climate variability at various time scales, highlighting the impact of prominent climate variabilities such as El Niño–Southern Oscillation on the dynamics of causality.

DOI: https://doi.org/10.1029/2022GL101942

Fig. 3. Measuring causal effect in the dynamical network of precipitation in the CONUS. (a) and (b) Long-term averaged causal effect (ACE) and averaged causal susceptibility (ACS) for each climate region. (c) Evolution of the strength of the CCM causality over time (with a 15-year sliding window) between two adjacent regions: NRP (Northern Rockies and Plains) and UM (Upper Midwest). (d) Time evolution of the CCM causality strength between the South and Ohio Valley. The horizontal dashed lines in red or blue in (c) and (d) represent the mean values of CCM causality strength. (e) ACE versus ACS over all 15-year sliding windows for each climate region.

New paper on moisture sources of precipitation in the Tibetan Plateau published in Hydrology and Earth System Sciences

Our new paper, “Spatial distribution of oceanic moisture contributions to precipitation over the Tibetan Plateau“, is published in Hydrology and Earth System Sciences (IF: 6.617).

The paper and its supplement can be downloaded at https://hess.copernicus.org/articles/26/6413/2022/.

Authors: Ying Li, Chenghao Wang, Ru Huang, Denghua Yan, Hui Peng, and Shangbin Xiao

Abstract: Evaporation from global oceans is an important moisture source for glaciers and headwaters of major Asian rivers in the Tibetan Plateau (TP). Although the accelerated global hydrological cycle, the altered sea–land thermal contrast and the amplified warming rate over the TP during the past several decades are known to have profound effects on the regional water balance, the spatial distribution of oceanic moisture contributions to the vast TP remains unclear. This hinders the accurate quantification of regional water budgets and the reasonable interpretation of water isotope records from observations and paleo archives. Based on historical data and moisture tracking, this study systematically quantifies the absolute and relative contributions of oceanic moisture to long-term precipitation in the TP. Results show that the seasonal absolute and relative oceanic contributions are generally out of phase, revealing the previously underestimated oceanic moisture contributions brought by the westerlies in winter and the overestimated moisture contributions from the Indian Ocean in summer. Quantitatively, the relative contribution of moisture from the Indian Ocean is only ∼30 % in the south TP and further decreases to below 10 % in the northernmost TP. The absolute oceanic contribution exhibits a spatial pattern consistent with the dipole pattern of long-term precipitation trends across the Brahmaputra Canyon region and the central-northern TP. In comparison, relative oceanic contributions show strong seasonal patterns associated with the seasonality of precipitation isotopes across the TP.

DOI: https://doi.org/10.5194/hess-26-6413-2022

Fig. 8. Locations of the precipitation isotope monitoring stations and the relationship between the monthly relative IO moisture contributions (blue lines) and the precipitation isotope observations (dotted lines). Sites 1–13, 14–17 and 18–19 represent stations located within the monsoon domain, transition domain and westerlies domain, respectively. Blue lines show the mean IO moisture contributions based on three simulations, while the shadings show the range (detailed seasonal variations of three simulations are shown in Fig. S14). Note that for consistency, oceanic contributions below 10% and above 50% are not shown for sites 12 and 18.

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