A Mechanical Drag Coefficient Formulation and Urban Canopy Parameter Assimilation Technique for Complex Urban Environments

Gutiérrez, Estatio; Martilli, Alberto; Santiago, José Luis; González, Jorge E.

doi:10.1007/s10546-015-0051-7

Cited by 38 publications

(26 citation statements)

References 26 publications

(29 reference statements)

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“…BEP and BEM have also been modified to account for latent heat fluxes from air conditioning, based on the work of Gutierrez et al () as well as effects of varying building packing density on drag coefficient (Gutiérrez et al , ). Cooling towers use evaporative cooling processes to remove heat from water used in air conditioning systems.…”

Section: Methodsmentioning

confidence: 99%

“…This evaporative cooling effectively partitions urban heat fluxes into sensible and latent, adding a hydrological component to BEM. Gutiérrez et al , implemented impacts of building packing density into the BEP code following results from Reynolds averaged numerical simulations (RANS) of Santiago et al (), who related buildings' drag coefficient to their packing density through a series of experiments, as follows:

C_{eq} ((), λ_{p}) = false{\begin{matrix} true \\ 3.32 λ_{p}^{0.47} for λ_{p} \leq 0.29 \\ 1.85 for λ_{p} > 0.29 \end{matrix} .

…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

High‐resolution projections of extreme heat in New York City

Ortiz

González

Horton

et al. 2019

Intl Journal of Climatology

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Heat waves impact a wide array of human activities, including health, cooling energy demand, and infrastructure. Cities amplify many of these impacts by concentrating large populations and critical infrastructure in relatively small areas. In addition, heat waves are expected to become longer, more intense, and more frequent in North America. Here, we evaluate combined climate and urban surface impacts on localized heat wave metrics throughout the 21st century across two emissions scenarios (RCP4.5 and RCP8.5) for New York City (NYC), which houses the largest urban population in the United States. We account for local biases due to urban surfaces via bias correcting with observed records and urbanized 1‐km resolution dynamical downscaling simulations across selected time periods (2045–2049 and 2095–2099). Analysis of statistically downscaled global model output shows underestimation of uncorrected summer daily maximum temperatures, leading to lower heat wave intensity and duration projections. High‐resolution dynamical downscaling simulations reveal strong dependency of changes in event duration and intensity on geographical location and urban density. Event intensity changes are expected to be highest closer to the coast, where afternoon sea‐breezes have traditionally mitigated summer high temperatures. Meanwhile, event duration anomaly is largest over Manhattan, where the urban canopy is denser and taller.

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Section: Methodsmentioning

confidence: 99%

C_{eq} ((), λ_{p}) = false{\begin{matrix} true \\ 3.32 λ_{p}^{0.47} for λ_{p} \leq 0.29 \\ 1.85 for λ_{p} > 0.29 \end{matrix} .

…”

Section: Methodsmentioning

confidence: 99%

High‐resolution projections of extreme heat in New York City

Ortiz

González

Horton

et al. 2019

Intl Journal of Climatology

View full text Add to dashboard Cite

show abstract

“…Thus, the drag coefficient becomes a function of the plan area per unit ground area, λ P . The new implementation of the drag coefficient term in equation , which is discussed in section 4, is as follows [ Santiago and Martilli , ; Gutiérrez et al , ]:

C_{{drag}_{new}} = ({,, \begin{matrix} 3.32 {λ_{P}}^{0.47}, when λ_{P} \leq 0.29 \\ 1.85, when λ_{P} > 0.29 \end{matrix})

where λ P is the plan area per unit ground area.…”

Section: Methodsmentioning

confidence: 99%

“…Table shows the New‐drag Case evaluation results for 10 m wind speed, 2 m air temperature, and relative humidity for the stations in Table . The implementation of the new BEP‐BEM urban parameterization drag coefficient significantly reduces the mean value from 3.15 m/s to 2.63 m/s (also investigated for New York city by Gutiérrez et al []), and the mean bias error of 10 m wind speed from 0.70 m/s to 0.17 m/s. Meanwhile, the increase in drag force and TKE within the urban canopy layer increases the mean surface air temperature of the 25 stations by 0.20°C.…”

Section: Effect Of Urban Morphology On Uhic and Slbc Developmentmentioning

confidence: 99%

Impact of land surface heterogeneity on urban heat island circulation and sea‐land breeze circulation in Hong Kong

et al. 2017

Self Cite

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Hong Kong is one of the most high‐rise and highly compact cities in the world. The urban land surface is highly heterogeneous, which creates low‐level convergence zones in urban areas, particularly the Kowloon Peninsula. The low‐level convergence zone is due to the combined effect of urban heat island circulation (UHIC) and sea‐land breeze circulation (SLBC) under weak northeasterly synoptic flow. To study the impacts of anthropogenic fluxes and built‐up areas on the local circulation, the Weather Research and Forecasting (WRF) mesoscale model is combined with the multilayer urban canopy building effect parameterization/building energy model (BEP/BEM) parameterization to produce a 3 day simulation of an air pollution episode in Hong Kong in September 2012. To better represent the city land surface features, building information is assimilated in the central part of the Kowloon Peninsula. The WRF‐BEP‐BEM model captures the 2 m temperature distribution and local wind rotation reasonably well but overestimates the 10 m wind speed with a mean bias error of 0.70 m/s. A dome‐shaped feature with a high level of moisture is captured in the convergence zones due to intensified UHIC and inflowing SLBC. The anthropogenic heat increases the air temperature by around 0.3°C up to 250 m, which in turn modifies the SLBC. A new drag coefficient based on λP, plan area per unit ground area, is tested. Besides the basic physical characteristics captured by the WRF‐BEP‐BEM model, the stagnation of wind in the lower level convergence zone is better captured by this approach than by the traditional constant value coefficient.

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“…Figure 1 shows a map of the region being analyzed. According to Stewart and Oke (2012), the airport locations (LGA, JFK, and EWR sites) can be categorized as a Local Climate Zone 8, and the CCNY site as a Local Climate Zone 1, which is mostly high-rise residential buildings with an average height of 25-65 m. Additional information on the land-use categories for New York City can be found in Gutiérrez et al (2015a), where high-resolution, land-cover information was used for mapping the urban morphology (e.g., the building height and landuse category according to Fry et al 2011). The land-use characteristics around each airport are as follows: around the JFK site are low-rise residential units, around the LGA site are high-rise residential and commercial units, while the EWR site is surrounded by a commercial district, with average building heights adjacent to each airport of 8.5-10, 15-25, and 8-10 m, respectively.…”

Section: Measurements and Data Analysismentioning

confidence: 99%

Thermal Structure of a Coastal–Urban Boundary Layer

Melecio-Vázquez

Ramamurthy

Arend

et al. 2018

Boundary-Layer Meteorol

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We use various temperature profilers located in and around New York City to observe the structure and evolution of the thermal boundary layer. The primary focus is to highlight the spatial variability of potential-temperature profiles due to heterogeneous surface forcing in an urban environment during different flow conditions. Overall, the observations during the summer period reveal the presence of thermal internal boundary layers due to the interaction between the marine atmospheric boundary layer and the convective urban environment. The summer daytime potential-temperature profiles within the city indicate a superadiabatic layer is present near the surface beneath a mildly stable layer. Large spatial variability in the near-surface (0-300 m) potential temperature is detected, with the thermal profile in the lower atmosphere uniquely determined by the underlying surface forcing and the distance from the coast. The summer and winter average night-time potential-temperature profiles show that the atmosphere is still convective near the surface. The seasonal averages of mixing ratio show large variability in the vertical direction.Keywords Coastal boundary layer · Microwave radiometer · Moisture boundary layer · Thermal boundary layer · Urban boundary layer

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A Mechanical Drag Coefficient Formulation and Urban Canopy Parameter Assimilation Technique for Complex Urban Environments

Cited by 38 publications

References 26 publications

High‐resolution projections of extreme heat in New York City

High‐resolution projections of extreme heat in New York City

Impact of land surface heterogeneity on urban heat island circulation and sea‐land breeze circulation in Hong Kong

Thermal Structure of a Coastal–Urban Boundary Layer

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