Title: Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment
Abstract
This paper examines summer- and wintertime variations of the surface and near-surface urban heat island (UHI) for the Phoenix metropolitan area using the Moderate Resolution Imaging Spectroradiometer (MODIS), near-surface meteorological observations, and the Weather Research and Forecasting (WRF) Model during a 31-day summer- and a 31-day wintertime period. The surface UHI (defined based on the urban–rural land surface temperature difference) is found to be higher at night and during the warm season. On the other hand, the morning surface UHI is low and frequently exhibits an urban cool island that increases during the summertime period. Similarly, the near-surface UHI (defined based on the urban–rural 2-m air temperature difference) is higher at night and during summertime. On the other hand, the daytime near-surface UHI is low but rarely exhibits an urban cool island. To evaluate the WRF Model’s ability to reproduce the diurnal cycle of near-surface meteorology and surface skin temperature, two WRF Model experiments (one using the Bougeault and Lacarrere turbulent scheme and one with the Mellor–Yamada–Janjić turbulent parameterization) at high spatial resolution (1-km horizontal grid spacing) are conducted for each 31-day period. Modeled results show that the WRF Model (coupled to the Noah-MP land surface model) tends to underestimate to some extent surface skin temperature during daytime and overestimate nighttime values during the wintertime period. In the same way, the WRF Model tends to accurately reproduce the diurnal cycle of near-surface air temperature, including maximum and minimum temperatures, and wind speed during summertime, but notably overestimates nighttime near-surface air temperature during wintertime. This nighttime overestimation is especially remarkable with the Bougeault and Lacarrere turbulent scheme for both urban and rural areas.
Wang, Liang; Li, Dan(
, Journal of Applied Meteorology and Climatology)
null
(Ed.)
Abstract In this study, we simulate the magnitude of urban heat islands (UHIs) during heat wave (HWs) in two cities with contrasting climates (Boston, Massachusetts, and Phoenix, Arizona) using the Weather Research and Forecasting (WRF) Model and quantify their drivers with a newly developed attribution method. During the daytime, a surface UHI (SUHI) is found in Boston, which is mainly caused by the higher urban surface resistance that reduces the latent heat flux and the higher urban aerodynamic resistance r a that inhibits convective heat transfer between the urban surface and the lower atmosphere. In contrast, a daytime surface urban cool island is found in Phoenix, which is mainly due to the lower urban r a that facilitates convective heat transfer. In terms of near-surface air UHI (AUHI), there is almost no daytime AUHI in either city. At night, an SUHI and an AUHI are identified in Boston that are due to the stronger release of heat storage in urban areas. In comparison, the lower urban r a in Phoenix enhances convective heat transfer from the atmosphere to the urban surface at night, leading to a positive SUHI but no AUHI. Our study highlights that the magnitude of UHIs or urban cool islands is strongly controlled by urban–rural differences in terms of aerodynamic features, vegetation and moisture conditions, and heat storage, which show contrasting characteristics in different regions.
Han, S.; Jang, M.(
, Atmospheric chemistry and physics discussion)
The daytime oxidation of biogenic hydrocarbons is attributed to both OH radicals and O3, while nighttime chemistry is dominated by the reaction with O3 and NO3 radicals. Here, the diurnal pattern of Secondary Organic Aerosol (SOA) originating from biogenic hydrocarbons was intensively evaluated under varying environmental conditions (temperature, humidity, sunlight intensity, NOx levels, and seed conditions) by using the UNIfied Partitioning Aerosol phase Reaction (UNIPAR) model, which comprises multiphase gas-particle partitioning and in-particle chemistry. The oxidized products of three different hydrocarbons (isoprene, α-pinene, and β-caryophyllene) were predicted by using near explicit gas mechanisms for four different oxidation paths (OH, O3, NO3, and O(3P)) during day and night. The gas mechanisms implemented the Master Chemical Mechanism (MCM v3.3.1), the reactions that formed low volatility products via peroxy radical (RO2) autoxidation, and self- and cross-reactions of nitrate-origin RO2. In the model, oxygenated products were then classified into volatility-reactivity base lumping species, which were dynamically constructed under varying NOx levels and aging scales. To increase feasibility, the UNIPAR model that equipped mathematical equations for stoichiometric coefficients and physicochemical parameters of lumping species was integrated with the SAPRC gas mechanism. The predictability of the UNIPAR model was demonstrated by simulating chamber-generated SOA data under varying environments day and night. Overall, the SOA simulation decoupled to each oxidation path indicated that the nighttime isoprene SOA formation was dominated by the NO3-driven oxidation, regardless of NOx levels. However, the oxidation path to produce the nighttime α-pinene SOA gradually transited from the NO3-initiated reaction to ozonolysis as NOx levels decreased. For daytime SOA formation, both isoprene and α-pinene were dominated by the OH-radical initiated oxidation. The contribution of the O(3P) path to all biogenic SOA formation was negligible in daytime. Sunlight during daytime promotes the decomposition of oxidized products via photolysis and thus, reduces SOA yields. Nighttime α-pinene SOA yields were significantly higher than daytime SOA yields, although the nighttime α-pinene SOA yields gradually decreased with decreasing NOx levels. For isoprene, nighttime chemistry yielded higher SOA mass than daytime at the higher NOx level (isoprene/NOx > 5 ppbC/ppb). The daytime isoprene oxidation at the low NOx level formed epoxy-diols that significantly contributed SOA formation via heterogeneous chemistry. For isoprene and α-pinene, daytime SOA yields gradually increased with decreasing NOx levels. The daytime SOA produced more highly oxidized multifunctional products and thus, it was generally more sensitive to the aqueous reactions than the nighttime SOA. β-Caryophyllene, which rapidly oxidized and produced SOA with high yields, showed a relatively small variation in SOA yields from changes in environmental conditions (i.e., NOx levels, seed conditions, and diurnal pattern), and its SOA formation was mainly attributed to ozonolysis day and night. To mimic the nighttime α-pinene SOA formation under the polluted urban atmosphere, α-pinene SOA formation was simulated in the presence of gasoline fuel. The simulation suggested the growth of α-pinene SOA in the presence of gasoline fuel gas by the enhancement of the ozonolysis path under the excess amount of ozone, which is typical in urban air. We concluded that the oxidation of the biogenic hydrocarbon with O3 or NO3 radicals is a source to produce a sizable amount of nocturnal SOA, despite of the low emission at night.
Qin, Yue; Liao, Weilin; Li, Dan(
, Journal of Climate)
Abstract The two-resistance mechanism (TRM) attribution method, which was designed to analyze the urban–rural contrast of temperature, is improved to study the urban–rural contrast of heat stress. The improved method can be applied to diagnosing any heat stress index that is a function of temperature and humidity. As an example, in this study we use it to analyze the summertime urban–rural contrast of simplified wet bulb globe temperature (SWBGT) simulated by the Geophysical Fluid Dynamics Laboratory land model coupled with an urban canopy model. We find that the urban–rural contrast of SWBGT is primarily caused by the lack of evapotranspiration in urban areas during the daytime and the release of heat storage during the nighttime, with the urban–rural differences in aerodynamic features playing either positive or negative roles depending on the background climate. Compared to the magnitude of the urban–rural contrast of temperature, the magnitude of the urban–rural contrast of SWBGT is damped due to the moisture deficits in urban areas. We further find that the urban–rural contrast of 2-m air temperature/SWBGT is fundamentally different from that of canopy air temperature/SWBGT. Turbulent mixing in the surface layer leads to much smaller urban–rural contrasts of 2-m air temperature/SWBGT than their canopy air counterparts. Significance Statement Heat leads to serious public health concerns, but urban and rural areas have different levels of heat stress. Our study explains the magnitude and pattern of the simulated urban–rural contrast in heat stress at the global scale and improves an attribution method to quantify which biophysical processes are mostly responsible for the simulated urban–rural contrast in heat stress. We highlight two well-known causes of higher heat stress in cities: the lack of evapotranspiration and the stronger release of heat storage. Meanwhile, we draw attention to the vegetation types in rural areas, which determine the urban–rural difference in surface roughness and significantly affect the urban–rural difference in heat stress. Last, we find the urban–rural contrasts of 2-m air temperature/SWBGT are largely reduced relative to their canopy air counterparts due to the turbulent mixing effect.
Schlaerth, Hannah L.; Silva, Sam J.; Li, Yun; Li, Dan(
, Journal of Geophysical Research: Atmospheres)
Abstract
Urban greening is often proposed for urban heat island (UHI) mitigation because vegetation provides shade and increases evapotranspiration. However, vegetation has lower albedo and higher emissivity than the bare soil it often replaces, which increases incoming energy fluxes. Here, we use the Weather Research and Forecasting model to quantify and compare the albedo and non‐albedo effects (i.e., changes in emissivity, surface roughness, and evaporative fluxes) of urban greening in the Los Angeles Basin under policy relevant urban greening scenarios. When albedo‐induced effects were included in the model, daytime surface temperatures in urban areas warmed by 0.70 ± 0.89°C with increases in the sensible heat flux outweighing increases in the latent heat flux from increased evapotranspiration. In contrast, daytime surface temperatures cooled by 0.27 ± 0.72°C when the albedo‐induced effects were ignored. At night, including albedo‐induced effects of urban greening resulted in only half the cooling modeled in the non‐albedo simulations. Near surface air temperatures also had contrasting model results, with nighttime cooling of 0.21 ± 0.47°C outweighing slight daytime warming of 0.04 ± 0.32°C in the non‐albedo simulations and daytime warming of 0.33 ± 0.41°C outweighing slight nighttime cooling of 0.05 ± 0.46°C in the albedo simulations. Our results reveal the critical role that albedo plays in determining the net surface climate effects of urban greening. Reductions in albedo from urban greening should be carefully considered by policy makers and urban planners, especially as high albedo roofs and pavements are simultaneously being deployed for UHI mitigation in many cities.
Pokhrel, Rabindra; Walker, Andy; González, Jorge E.(
, ASME Journal of Engineering for Sustainable Buildings and Cities)
Abstract As a consequence of the warm and humid climate of tropical coastal regions, there is high energy demand year-round due to air conditioning to maintain indoor comfort levels. Past and current practices are focused on mitigating peak cooling demands by improving heat balances by using efficient building envelope technologies, passive systems, and demand side management strategies. In this study, we explore city-scale solar photovoltaic (PV) planning integrating information on climate, building parameters and energy models, and electrical system performance, with added benefits for the tropical coastal city of San Juan, Puerto Rico. Energy balance on normal roof, flush-mounted PV roof, and tilted PV roof are used to determine PV power generation, air, and roof surface temperatures. To scale up the application to the whole city, we use the urbanized version of the Weather Research and Forecast (WRF) model with the building effect parameterization (BEP) and the building energy model (BEM). The city topology is represented by the World Urban Database Access Portal Tool (WUDAPT), local climate zones (LCZs) for urban landscapes. The modeled peak roof temperature is maximum for normal roof conditions and minimum when inclined PV is installed on a roof. These trends are followed by the building air conditioning (AC) demand from urbanized WRF, maximum for normal roof and minimum for inclined roof-mounted PV. The net result is a reduced daytime Urban Heat Island (UHI) for horizontal and inclined PV roof and increased nighttime UHI for the horizontal PV roof as compared with the normal roof. The ratio between coincident AC demand and PV production for the entire metropolitan region is further analyzed reaching 20% for compact low rise and open low rise buildings due to adequate roof area but reaches almost 100% for compact high rise and compact midrise buildings class, respectively.
Palou, Francisco Salamanca, and Mahalov, Alex. Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment. Weather and Forecasting 34.6 Web. doi:10.1175/WAF-D-19-0054.1.
Palou, Francisco Salamanca, & Mahalov, Alex. Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment. Weather and Forecasting, 34 (6). https://doi.org/10.1175/WAF-D-19-0054.1
Palou, Francisco Salamanca, and Mahalov, Alex.
"Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment". Weather and Forecasting 34 (6). Country unknown/Code not available: American Meteorological Society. https://doi.org/10.1175/WAF-D-19-0054.1.https://par.nsf.gov/biblio/10124140.
@article{osti_10124140,
place = {Country unknown/Code not available},
title = {Summer- and Wintertime Variations of the Surface and Near-Surface Urban Heat Island in a Semiarid Environment},
url = {https://par.nsf.gov/biblio/10124140},
DOI = {10.1175/WAF-D-19-0054.1},
abstractNote = {Abstract This paper examines summer- and wintertime variations of the surface and near-surface urban heat island (UHI) for the Phoenix metropolitan area using the Moderate Resolution Imaging Spectroradiometer (MODIS), near-surface meteorological observations, and the Weather Research and Forecasting (WRF) Model during a 31-day summer- and a 31-day wintertime period. The surface UHI (defined based on the urban–rural land surface temperature difference) is found to be higher at night and during the warm season. On the other hand, the morning surface UHI is low and frequently exhibits an urban cool island that increases during the summertime period. Similarly, the near-surface UHI (defined based on the urban–rural 2-m air temperature difference) is higher at night and during summertime. On the other hand, the daytime near-surface UHI is low but rarely exhibits an urban cool island. To evaluate the WRF Model’s ability to reproduce the diurnal cycle of near-surface meteorology and surface skin temperature, two WRF Model experiments (one using the Bougeault and Lacarrere turbulent scheme and one with the Mellor–Yamada–Janjić turbulent parameterization) at high spatial resolution (1-km horizontal grid spacing) are conducted for each 31-day period. Modeled results show that the WRF Model (coupled to the Noah-MP land surface model) tends to underestimate to some extent surface skin temperature during daytime and overestimate nighttime values during the wintertime period. In the same way, the WRF Model tends to accurately reproduce the diurnal cycle of near-surface air temperature, including maximum and minimum temperatures, and wind speed during summertime, but notably overestimates nighttime near-surface air temperature during wintertime. This nighttime overestimation is especially remarkable with the Bougeault and Lacarrere turbulent scheme for both urban and rural areas.},
journal = {Weather and Forecasting},
volume = {34},
number = {6},
publisher = {American Meteorological Society},
author = {Palou, Francisco Salamanca and Mahalov, Alex},
}
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