Xochitl Hidalgo recently joined the Sustainable URban Futures (SURF) Lab as an M.S. student. Welcome!
Xochitl completed her undergraduate studies at OU, receiving dual bachelor’s degrees in Meteorology and Environmental Sustainability. Her previous research endeavors include an assessment of non-profit organization response and adaptation post-Hurricane Harvey and an analysis of the agricultural response to increased vapor pressure deficit in Oklahoma. Xochitl also worked as the Climate Communications Assistant for the Southern Climate Impacts Planning Program. Xochitl’s research interests include applied climatology, climate variability, and precipitation extremes. She is particularly interested in how precipitation extremes will impact the agricultural industry, urban planning, and disaster management. Her M.S. research will focus on hurricane-induced precipitation modeling along the Houston coast.
Tianze Luo recently joined the Sustainable URban Futures (SURF) Lab as a Ph.D. student. Welcome!
Before coming to OU, Tianze received his Master’s degree (MLA) in landscape Architecture from the University of Edinburgh and Bachelor of Agriculture degree in Landscape gardening from Northwest A&F University. Tianze’s research interests include urban climate modeling, urban thermal comfort, and natural solutions based on urban trees. His doctoral research will focus on urban climate models, particularly numerical simulations of heat stress and air pollution. Additionally, he uses state of art technology modeling tools (such as machine learning) to combine observational data, remote sensing technology, and climate model output to deepen our understanding of the urban environment.
Our new paper, “Building resilient urban water systems: emerging opportunities for solving long-lasting challenges“, is published in Hydrological Sciences Journal (IF: 2.5).
Abstract: In this perspective paper, we analyse the challenges and opportunities of hydrology in the urban context and propose solutions for innovation and sustainability by leveraging advancements across technology, society, and governance for resilient cities. Technological breakthroughs, such as smart sensors and artificial intelligence, can enhance the efficiency and resilience of real-time water monitoring and predictions. Public awareness and community engagement can foster behavioural change and empower residents to actively participate in urban water governance through initiatives like rainwater harvesting and participatory planning. Additionally, big data and remote sensing provide cities with the insights needed for adaptive, data-driven decision-making. Together, these developments represent a paradigm shift from reactive problem-solving to proactive, integrated solutions that prioritise equity, environmental health, and urban resilience. Finally, the paper highlights the differences in progress between the Global North and the Global South and proposes research priorities for the future of urban hydrology.
Authors: Chenghao Wang, Xiao-Ming Hu, Sarah Feron, Jessica Leffel, & Raúl R. Cordero
Abstract: Ground-level ozone pollution and extreme heat are closely linked environmental stressors that often peak during similar warm-season conditions. Their co-occurrence as compound events can significantly amplify negative health impacts, particularly in densely populated urban areas. In this study, we systematically characterized the frequency, duration, and cumulative intensity of warm-season compound heat and ozone pollution events across all urban areas and their rural surroundings in the contiguous U.S. (CONUS), using long-term, high-resolution daily air temperature and pollution datasets. We found that urban heat waves, defined using daily maximum air temperature, were generally more frequent, more intense, and longer lasting than their rural counterparts, primarily due to the daytime urban heat island effect. In contrast, over half of the U.S. cities experienced fewer, less intense, and shorter ozone pollution episodes than nearby rural areas, largely reflecting differences in ozone chemical regimes. Despite these contrasting patterns, compound heat and ozone pollution events were more frequent in 88.8 % of urban areas, with higher cumulative heat and ozone pollution intensities in 91.1 % and 88.1 % of cities, respectively. However, compound event durations tended to be shorter in urban environments. These findings highlight the dependence of such compound events on local factors such as precursor emissions, as well as background conditions such as regional meteorological patterns, emphasizing the need for tailored mitigation strategies to simultaneously reduce heat stress and ozone pollution. This study also lays the foundation for detailed regional numerical simulations to elucidate the mechanisms that drive urban–rural disparities during these compound events.
Figure 1. Schematic of a compound heat and ozone pollution episode and potential key processes during daytime. Simplified urban surface energy exchanges are shown as an example driver of the urban heat island effect. SW: shortwave radiation; LW: longwave radiation; H: sensible heat flux; and LE: latent heat flux.
Our new paper, “Ultrafine-resolution urban climate modeling: Resolving processes across scales“, is published in Journal of Advances in Modeling Earth Systems (IF: 4.6).
Abstract: Recent advances in urban climate modeling resolution have improved the representation of complex urban environments, with large-eddy simulation (LES) as a key approach, capturing not only building effects but also urban vegetation and other critical urban processes. Coupling these ultrafine-resolution (hectometric and finer) approaches with larger-scale regional and global models provides a promising pathway for cross-scale urban climate simulations. However, several challenges remain, including the high computational cost that limits most urban LES applications to short-term, small-domain simulations, uncertainties in physical parameterizations, and gaps in representing additional urban processes. Addressing these limitations requires advances in computational techniques, numerical schemes, and the integration of diverse observational data. Machine learning presents new opportunities by emulating certain computationally expensive processes, enhancing data assimilation, and improving model accessibility for decision-making. Future ultrafine-resolution urban climate modeling should be more end-user oriented, ensuring that model advancements translate into effective strategies for heat mitigation, disaster risk reduction, and sustainable urban planning.
Figure 1. (a) Horizontal spatial and temporal scales of representative urban wind phenomena and (b)–(e) commonly used modeling approaches within the urban canopy layer: (b) the bulk approach, which neglects internal heterogeneity within the urban canopy layer; (c) the single-layer urban canopy model (UCM) that uses simplified street canyon geometry, with urban vegetation integrated; (d) the horizontal averaging approach, commonly used in multi-layer UCMs, which resolves vertical variations in atmospheric properties but neglect within-layer horizontal heterogeneity; and (e) the fully building-resolving approach, typically through computational fluid dynamics approaches such as large-eddy simulation. Arrows in blue represent wind.
Cathleen Simatupang recently joined the Sustainable URban Futures (SURF) Lab as a postdoctoral researcher. Welcome!
Before coming to OU, Cathleen completed her dual Ph.D. degrees in Environmental and Water Resources Engineering from Mahidol University, Thailand, and in Natural Sciences from Macquarie University, Australia. Her doctoral research focused on environmental pollution, particularly soil contamination, PM2.5 air pollution, and heavy metal exposure in both air and soil, with an emphasis on health risk assessments. She also examined how outdoor air pollution affects indoor air quality, especially in a semi-open learning environment such as a childcare center.
Her postdoctoral research will focus on the measurement and modeling of urban meteorology and air pollution.
Our new paper, “Enhancing climate-driven urban tree cooling with targeted nonclimatic interventions“, is published in Environmental Science & Technology (IF: 10.9).
Abstract: Urban trees play a pivotal role in mitigating heat, yet the global determinants and patterns of their cooling efficiency (CE) remain elusive. Here, we quantify the diel CE of 229 cities across four climatic zones and employ a machine-learning model to assess the influence of variables on CE. We found that for every 10% increase in tree cover, surface temperatures are reduced by 0.25 °C during the day and 0.04 °C at night. Trees in humid regions exhibit the highest daytime CE, while those in arid zones demonstrate the greatest cooling effect at night. This can be explained by the difference in canopy density between the humid and arid zones. During the day, the high canopy density in the humid zone converts more solar radiation into latent heat flux. At night, the low canopy density in the arid zone intercepts less longwave radiation, which favors surface cooling. While climatic factors contribute nearly twice as much to CE as nonclimatic ones, our findings suggest that optimizing CE is possible by managing variables within specific thresholds due to their nonlinear effects. For instance, we revealed that in arid regions, an impervious surface coverage of approximately 60% is optimal, whereas in humid areas, reducing it to around 40% maximizes cooling benefits. These insights underscore the need for targeted management of nonclimatic factors to sustain tree cooling benefits and offer practical guidance for designing climate-resilient, nature-based urban strategies.
Figure 1. Global patterns of daytime cooling efficiency (CE) of urban trees. (a) Spatial distribution of daytime CE for selected cities. Each point represents the mean CE value of all urban cells within a city. Inset histograms display the mean daytime CE values (means ± s.e.) for arid (n = 636), semiarid (n = 2784), subhumid (n = 772), and humid (n = 5438) climate zones. Statistical analysis was performed using Welch’s ANOVA, followed by the Games-Howell post hoc test for multiple comparisons. Asterisks indicate significant differences between two climate zones (*p < 0.05, **p < 0.01, ***p < 0.001). (b) Latitudinal variation of daytime CE across all urban cells. The graph shows mean CE values for two-degree latitude intervals, with the shaded area indicating 1 s.e., and the dotted line representing the global mean of all urban cells. (c) Latitudinal distribution of daytime CE across climate zones. Each bar represents mean CE values (means ± s.e.) within the specified latitude range for each climate zone.
Our new paper, “Satellite-driven evidence of forest-induced temperature variability and its biophysical and biogeochemical pathways across latitudes“, is published in Ecological Indicators (IF: 7.0).
Abstract: Forests significantly influence local temperature dynamics, although the specifics of their impacts and mechanisms exhibit global variability. This study investigates the cooling or warming effects of global forests from 2001 to 2021 using multi-satellite data. The results indicate that (1) boreal forests exhibit a significant warming effect of +1.99 °C. Temperate forests exhibit nighttime warming but notable daytime cooling effect, resulting in a net daily cooling effect (−0.48 °C in the northern hemisphere, −0.91 °C in the southern hemisphere). The daily cooling effects peak in summer and gradually rise from spring to autumn, with winter exhibiting a warming inclination. Tropical forests consistently provide a cooling effect year-round (−2.11 °C). (2) Over the study period, tropical forests consistently revealed robust and stable cooling effects. Temperate forests displayed modest fluctuations in cooling effects, while the warming effect of boreal forest showed a slow trend upwards at a rate of +0.03 °C per year. (3) The warming effect of boreal forests is primarily due to NEE (net ecosystem exchange) and ET pathways (indirect effect: +0.253 and +0.392), while tropical forest cooling is driven by increased evapotranspiration (indirect effect: −0.938). As for temperate zones, annual cooling is primarily led by the NEE pathway (NH: −0.055 and SH: −0.415). (4) A robust annual coherence emerges between forests’ temperature regulation effects and ΔNEE, ΔET, and Δalbedo, where augmented ET and albedo significantly amplify cooling effects synchronously. The decrease in NEE exhibits a positive but non-synchronous impact on cooling at the local scale, while showing a strong and synchronous relationship with ΔLST at the global scale. These findings highlight the crucial role of forests in local temperature regulation, necessitating targeted management strategies.
Fig. 3. Global distribution and latitudinal trend of ΔLST. It showcases the spatial distribution (a, c, e) and latitudinal patterns (b, d, f) of ΔLST (°C) for the entire year during the daily average (a, b), daytime (c, d), and nighttime (e, f). The histograms located at the lower left corner of figures a, c, and e illustrate the concentrated distribution of ΔLST values across all sample windows.
Our new paper, “Observation and simulation of methane plumes during the morning boundary layer transition“, is published in Journal of Geophysical Research: Atmospheres (IF: 3.8).
Abstract: Methane (CH4) contributes significantly to global warming. However, accurate identification of CH4 sources for reducing CH4 emissions is often hampered by inadequate accuracy and spatiotemporal coverage of CH4 detection, and lack of accurate CH4 forward modeling used in top-down inversion systems. In this study, a field experiment was conducted in Pampa, Texas using two CH4 sensors (LI-COR and OGI camera) to detect CH4 releases. We investigated whether high-resolution simulations using the Weather Research and Forecasting (WRF) model with greenhouse gases (WRF-GHG) could accurately simulate the CH4 plumes in the presence of evolving atmospheric boundary layer from sunrise to noon. CH4 plumes showed substantial variation in time. At a release rate of ∼17.5 kg hr−1, the maximum enhancement of CH4 measured by LI-COR was 2.6 ppm at sunrise (7:36 a.m.), 250 m from the release location. Within half an hour after sunrise, this enhancement decreased to 0.3–0.4 ppm. The enhancement was 0.2 ppm by 10:00 a.m. and further dropped to less than 0.1 ppm after 11:30 a.m. Due to the low temperature at sunrise, the OGI camera failed to detect the CH4 plume. The WRF-GHG large-eddy simulation (LES) with 32 m grid spacing successfully reproduced these CH4 enhancements. In situ measurements together with numerical simulations illustrate the impact of the transition from a stable boundary layer in the early morning to a convective boundary layer at noon on the dispersion of CH4 plumes. Additionally, CH4 plumes from a cattle farm in Oklahoma are briefly examined using the same modeling approach.
Fig. 3. Simulated CH4 mixing ratios and wind vectors (reference vector of 4 m s−1 marked in top‐right corners) in domain (a), (b) 4 and (c), (d) 3 overlaid with observed mixing ratios along the driving routes during (left) sunrise and (right) noon time. The numbers are the observed maximum mixing ratios at the time period.
Liam Thompson was recently selected as the 2025 Goldwater Scholar. His essay was based on the continental-scale model evaluation work recently published in Urban Climate.
The Goldwater Foundation is a federally endowed agency established by Public Law 99-661 on November 14, 1986. The Scholarship Program honoring Senator Barry Goldwater was designed to identify, encourage, and financially support outstanding undergraduates interested in pursuing research careers in the sciences, engineering, and mathematics. The Goldwater Scholarship is the preeminent undergraduate award of its type in these fields.
From an estimated pool of over 5,000 college sophomores and juniors, 1,350 science, engineering, and mathematics students were nominated by 445 academic institutions to compete for the 2025 Goldwater scholarships. The Trustees of the Goldwater Board awarded 441 Goldwater scholarships to college students from across the United States for the 2025-2026 academic year. With the 2025 awards, the Goldwater Foundation has awarded 11,162 scholarships since 1989, the first year the scholarship was bestowed.
