A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations

Zhang, Hengyue; Mao, Jin; Leach, Martin J.

doi:10.3390/cli5030072

Cited by 15 publications

(5 citation statements)

References 33 publications

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“…Jin et al (2005) (JI) thoroughly inspected the influence of the urban system on climate change [27]. In other previous studies [28][29][30][31] which analyzed the UHI effect extensively, the dependence of the UHI effect on the surface temperatures, albedos, and emissivity was demonstrated.…”

Section: Introductionmentioning

confidence: 99%

Validation and Improvement of the WRF Building Environment Parametrization (BEP) Urban Scheme

Gohil

Mao

2019

Climate

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The building environment parameterization scheme (BEP) is a built-in “urban physics” scheme in the weather research and forecasting (WRF) model. The urbanized College Park (CP) in Maryland state (MD) in the United States (US) covers an approximate land area of 14.8 km2 and has a population of 32,000 (reported by The United States Census Bureau, as of 2017). This study was an effort to validate and improve the BEP urban physics scheme for a small urban setting, College Park, MD. Comparing the WRF/BEP-simulated two-meter air temperatures with the local rooftop WeatherBug® observations and with the airport observations, systemic deficiencies in BEP for urban heat island effect simulation are evident. Specifically, WRF/BEP overestimates the two-meter air temperature by about 10 °F during clear summer nights and slightly underestimates it during noon of the same days by about 1–3 °F. Similar deficiencies in skin temperature simulations are also evident in WRF/BEP. Modification by adding an anthropogenic heat flux term resulted in better estimates for both skin and two-meter air temperatures on diurnal and seasonal scales.

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Section: Introductionmentioning

confidence: 99%

Validation and Improvement of the WRF Building Environment Parametrization (BEP) Urban Scheme

Gohil

Mao

2019

Climate

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“…(A-C) are summer, winter and Annual respectively. (Zhang H. Y. et al, 2017;Jiang et al, 2020). The fact that the data used in this study were collected for the inner city may explain why WIN was found to have a negative impact on precipitation in summer.…”

Section: Figurementioning

confidence: 97%

Spatial heterogeneity and impact scales of driving factors of precipitation changes in the Beijing-Tianjin-Hebei region, China

Wei

Liu

Liang

et al. 2023

Front. Environ. Sci.

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Changes in land surface properties during urbanization have a significant impact on variations in precipitation. Little research has been carried out on spatial heterogeneity and influence strength of the driving factors of precipitation changes at different urbanization scales. Using a trend analysis and multi-scale geographically weighted regression, this study analysed the spatial heterogeneity and impact scale of driving factors of precipitation changes in 156 urban units in the Beijing-Tianjin-Hebei urban agglomeration region (Jing-Jin-Ji). In summer, RAD (radiation), RHU (relative humidity), WIN (wind speed), and POP (urban population density) were found to act on a small regional scale, AOD (aerosol optical depth) on a medium regional scale, and NDVI (normalized difference vegetation index), NLI (night time light intensity), UHI (urban heat island intensity), and AREA (urban area size) on a global scale. In winter, AREA and WIN acted on a medium regional scale, UHI on a large regional scale, and AOD, NDVI and NLI on a global scale. Across the whole year, NDVI and AREA had a medium regional impact and NLI a large regional one. Variations in natural factors, such as RAD and RHU, had a great influence on the spatial heterogeneity of precipitation changes, whereas human factors, such as NLI and UHI, had a small influence. In summer, AOD mainly affected Tangshan and Qinhuangdao in the northeast and Cangzhou in the southeast of the Jing-Jin-Ji. RHU and AREA primarily affected the cities of Handan and Xingtai. In winter, NLI, AREA, WIN, and UHI had significant effects in the cities of Handan and Xingtai, with AREA being the most important factor. In the Shijiazhuang-Hengshui area, RAD and NLI played a significant role; in the Beijing-Zhangjiakou-Chengde area, the most important factor affecting precipitation changes was the variation in POP. These results provide a scientific basis for flood disaster risk management in the Jing-Jin-Ji and the establishment of differentiated climate policies in different cities.

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“…Recent advances in climate science and climate models such as the Weather Research and Forecasting (WRF) model allows researchers to downscale data to a resolution of 1km with relative accuracy, accounting for urban parameterizations and land use. As such, different urban parameterization schemes and local land cover data and their effects on the local UHI effect can be analysed [48,49]. Additionally, the effects of climate change and further development in urban areas can be studied through dynamic modelling, where global climate models following a climate change scenario can be dynamically downscaled to estimate what fraction of the increase in UHI intensity can be attributed to global warming or to urbanization [50].…”

Section: At Regional Scalesmentioning

confidence: 99%

Nature-Based Solutions (NBSs) to Mitigate Urban Heat Island (UHI) Effects in Canadian Cities

et al. 2022

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Canada is warming at double the rate of the global average caused in part to a fast-growing population and large land transformations, where urban surfaces contribute significantly to the urban heat island (UHI) phenomenon. The federal government released the strengthened climate plan in 2020, which emphasizes using nature-based solutions (NBSs) to combat the effects of UHI phenomenon. Here, the effects of two NBSs techniques are reviewed and analysed: increasing surface greenery/vegetation (ISG) and increasing surface reflectivity (ISR). Policymakers have the challenge of selecting appropriate NBSs to meet a wide range of objectives within the urban environment and Canadian-specific knowledge of how NBSs can perform at various scales is lacking. As such, this state-of-the-art review intends to provide a snapshot of the current understanding of the benefits and risks associated with the implantation of NBSs in urban spaces as well as a review of the current techniques used to model, and evaluate the potential effectiveness of UHI under evolving climate conditions. Thus, if NBSs are to be adopted to mitigate UHI effects and extreme summertime temperatures in Canadian municipalities, an integrated, comprehensive analysis of their contributions is needed. As such, developing methods to quantify and evaluate NBSs’ performance and tools for the effective implementation of NBSs are required.

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A Study of the Oklahoma City Urban Heat Island Effect Using a WRF/Single-Layer Urban Canopy Model, a Joint Urban 2003 Field Campaign, and MODIS Satellite Observations

Cited by 15 publications

References 33 publications

Validation and Improvement of the WRF Building Environment Parametrization (BEP) Urban Scheme

Validation and Improvement of the WRF Building Environment Parametrization (BEP) Urban Scheme

Spatial heterogeneity and impact scales of driving factors of precipitation changes in the Beijing-Tianjin-Hebei region, China

Nature-Based Solutions (NBSs) to Mitigate Urban Heat Island (UHI) Effects in Canadian Cities

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