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

Gohil, Kanishk; Mao, Jin

doi:10.3390/cli7090109

Cited by 10 publications

(5 citation statements)

References 39 publications

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“…Negative differences are systematically much larger during the night hours (−1.5 and −3.4 • C, respectively), resulting in a clear underestimation of the intensity of the typical nocturnal UHI effect over the city. The underestimation does not agree with the finding in [34]: anyway, in that case, a much smaller town is considered. During the sunlit hours, absolute values of the differences are smaller, and their sign can be even positive (−1.0 and +0.9 • C, respectively, in 2014 and 2015).…”

Section: Comparison Results: Wrfcontrasting

confidence: 71%

“…With suitable extensions, it can also be applied for the urban environment [31]. For the city of Milan, the WRF was used for several applications [32,33] with the building environment parameterization (BEP) urban scheme [34] and at a resolution of 1 km or even less. We made use of some outputs (in default configuration: BEPd) for a direct comparison with measurements in the UCL by the 7 FOMD Network weather stations located in Milan downtown.…”

Section: Comparison With the Weather Research And Forecasting Modelmentioning

confidence: 99%

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High-Resolution Gridded Air Temperature Data for the Urban Environment: The Milan Data Set

Frustaci¹,

Pilati²,

Lavecchia³

et al. 2022

Forecasting

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Temperature is the most used meteorological variable for a large number of applications in urban resilience planning, but direct measurements using traditional sensors are not affordable at the usually required spatial density. On the other hand, spaceborne remote sensing provides surface temperatures at medium to high spatial resolutions, almost compatible with the needed requirements. However, in this case, limitations are represented by cloud conditions and passing times together with the fact that surface temperature is not directly comparable to air temperature. Various methodologies are possible to take benefits from both measurements and analysis methods, such as direct assimilation in numerical models, multivariate analysis, or statistical interpolation. High-resolution thermal fields in the urban environment are also obtained by numerical modelling. Several codes have been developed to resolve at some level or to parameterize the complex urban boundary layer and are used for research and applications. Downscaling techniques from global or regional models offer another possibility. In the Milan metropolitan area, given the availability of both a high-quality urban meteorological network and spaceborne land surface temperatures, and also modelling and downscaling products, these methods can be directly compared. In this paper, the comparison is performed using: the ClimaMi Project high-quality data set with the accurately selected measurements in the Milan urban canopy layer, interpolated by a cokriging technique with remote-sensed land surface temperatures to enhance spatial resolution; the UrbClim downscaled data from the reanalysis data set ERA5; a set of near-surface temperatures produced by some WRF outputs with the building environment parameterization urban scheme. The comparison with UrbClim and WRF of the cokriging interpolated data set, mainly based on the urban canopy layer measurements and covering several years, is presented and discussed in this article. This comparison emphasizes the primary relevance of surface urban measurements and highlights discrepancies with the urban modelling data sets.

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Section: Comparison Results: Wrfcontrasting

confidence: 71%

Section: Comparison With the Weather Research And Forecasting Modelmentioning

confidence: 99%

High-Resolution Gridded Air Temperature Data for the Urban Environment: The Milan Data Set

Frustaci¹,

Pilati²,

Lavecchia³

et al. 2022

Forecasting

View full text Add to dashboard Cite

show abstract

“…The BEP scheme allows the WRF model to represent the direct interaction of the buildings with the atmosphere (wind speed, potential temperature, and turbulent kinetic energy) through geometric, thermal, and aerodynamic properties of different urban land uses [61,[73][74][75]. Each class of urban canopy is characterized by the homogenous grouping of urban structures considering the same width, separated at the same distance (canyon wide), and with different building heights (see characteristics of LCZ urban classes in Table S1) [61].…”

Section: Modeling Systemmentioning

confidence: 99%

Meteorological Effects of Green Infrastructure on a Developing Medium Latin American City: A Numerical Modeling Assessment

et al. 2023

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Urban areas concentrate more than 50% of the world’s population and are highly impacted by human activities, mainly due to high population density, directly affecting the micro-climate. In this sense, green infrastructures (GIs) have been pointed out to be helpful in mitigating these effects in large urban areas, where most of the studies were conducted. Therefore, this study evaluates the impacts on meteorological variables in a medium-sized city through the Weather Research and Forecasting model by implementing urban classes of Local Climate Zones (LCZ). Five urban parks and an urban lake were identified and expanded in the inner model grid to analyze the effects of GIs on meteorological variables in the urban environment. Results show that the 10 m wind speed can present an improvement for all statistical indices due to the better vertical representation of urban structures in the central urban area by the LCZ urban classes. In addition, green areas contributed locally to reducing the urban heat island (UHI) effects, resulting in cooling rates around these infrastructures. Compared to the lake, the use of the urban LCZ classes has proven to be an effective way to improve the representation of meteorological variables by a mesoscale weather model. Regarding GIs, this practice performs environmental services capable of mitigating the effects of UHI, sustaining the importance of these systems in urban projects, even for medium-sized cities. Finally, these findings provide support for public decision-makers in creating Master Plans for medium-sized cities regarding the implementation of GIs.

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“…They found a deeper UHI effect at both daytime and night-time, rather than at night, as suggested from surface air temperature measurements, using the skin temperature. Gohil and Jin (2019) modelled the UHI in the small city of College Park (Maryland, USA) using the BEP scheme for various seasons and clear and cloudy days. They compared the simulated and observed 2-m-temperature trend showing systematic errors at night, with overestimations and underestimations up to 5 °C both in urban and rural areas.…”

Section: Introductionmentioning

confidence: 99%

Interaction of the Sea Breeze with the Urban Area of Rome: WRF Mesoscale and WRF Large-Eddy Simulations Compared to Ground-Based Observations

Bernardino

Mazzarella

Pecci

et al. 2022

Boundary-Layer Meteorol

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The Weather Research and Forecast (WRF) model is used to simulate atmospheric circulation during the summer season in a coastal region of central Italy, including the city of Rome. The time series of surface air temperature, wind speed, and direction are compared with in situ observations in urban Rome and its rural surroundings. Moreover, the vertical wind profiles are compared to sodar urban measurements. To improve the WRF model’s ability to reproduce the local circulation, and the onset and propagation of the sea breeze, several simulations are carried out modifying the land use and the thermal and physical properties of the surfaces. Based on the results of the correlation coefficient and the RMSE, the heat capacity and albedo are the parameters mostly influencing the daily temperature cycle. Particularly, the temperature in the urban area is reproduced more realistically when the heat capacity is increased. Hence, the best simulations are used to initialize a large-eddy simulation at high spatial resolution to analyze the interaction between the sea breeze and the urban heat island and to investigate the interaction of the sea breeze front with orography and surface roughness. As confirmed by observations collected by in situ weather stations in the surroundings of Rome, the front, entering the city, splits into three branches: (i) a west component in the western flank of the city, closer to the sea; (ii) a north-west component in the northern, inland side, and (iii) a south-west component in the south area of the city.

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

Cited by 10 publications

References 39 publications

High-Resolution Gridded Air Temperature Data for the Urban Environment: The Milan Data Set

High-Resolution Gridded Air Temperature Data for the Urban Environment: The Milan Data Set

Meteorological Effects of Green Infrastructure on a Developing Medium Latin American City: A Numerical Modeling Assessment

Interaction of the Sea Breeze with the Urban Area of Rome: WRF Mesoscale and WRF Large-Eddy Simulations Compared to Ground-Based Observations

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