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In the past century, local-scale warming caused by a strengthening urban heat island effect has brought inevitable systematic bias to observational data from surface weather stations located in or near urban areas. In this study, the land use situation around U.S. Climate Reference Network (USCRN) stations was used as a reference for rural station selection; stations with similar environmental conditions in the U.S. Historical Climatology Network (USHCN) were selected as reference stations using a machine learning method, and then the maximum surface air temperature (Tmax) series, minimum surface air temperature (Tmin) series and mean surface air temperature (Tmean) series of rural stations during 1921–2020 were compared with those for all nearby stations (including both rural and urban stations) to evaluate urbanization effects in the USHCN observation data series of the contiguous United States, which can be regarded as urbanization bias contained in the latest homogenized USHCN observation data. The results showed that the urbanization effect on the Tmean trend of USHCN stations is 0.002 °C dec−1, and the urbanization contribution is 35%, indicating that urbanization around USHCN stations has led to at least one-third of the overall warming recorded at USHCN stations over the last one hundred years. The urbanization effects on Tmax and Tmin trends of USHCN stations are −0.015 °C dec−1 and 0.013 °C dec−1, respectively, and the urbanization contribution for Tmin is 34%. These results have significance for understanding the systematic bias in USHCN temperature data, and they provide a reference for subsequent studies on data correction and climate change monitoring. [ABSTRACT FROM AUTHOR]

Throughout the summer months in the Southeast United States (SEUS), the initiation of isolated convection (CI) can occur abundantly during the daytime with weak synoptic support (e.g., weak wind shear). Centered around this premise, a dual-summer, limited-area case study of CI events concerning both geographical and meteorological features was conducted. The goal of this study was to help explain SEUS summertime CI in weak synoptic environments, which can enhance CI predictability. Results show that spatial CI nonrandomness event patterns arise, with greater CI event density appearing over high elevation by midday. Later in the day, overall CI event counts subside with other mechanisms/factors emerging (e.g., urban heat island). Antecedent rainfall, instability, and moisture features are also higher on average where CI occurred. In a random forest feature importance analysis, elevation was the most important variable in dictating CI events in the early to midafternoon while antecedent rainfall and wind direction consistently rank highest in permutation importance. The results cumulatively allude to, albeit in a muted, nonsignificant statistical signal, and a degree of spatial clustering of CI event occurrences cross the study domain as a function of daytime heating and contributions of features to enhancing CI probabilities (e.g., differential heating and mesoscale thermal circulations). Significance Statement: Widespread isolated thunderstorms in the Southeast United States summer season with weak synoptic support have been commonly observed. With forecasting these remaining a challenge, a dual-summer intercomparison of geographical/meteorological features with convective initiation events was conducted. Radar data with a minimum threshold for convective initiation detection (35 dBZ) were used. Spatial nonrandomness was discovered with greater event density appearing over higher elevation by midday. Features such as prior rainfall and atmospheric instability/moisture were higher on average where initiation occurred. In a feature importance analysis, elevation ranked higher in the early to midafternoon hours while antecedent rainfall and wind direction ranked highest overall in permutation importance. These results allude to the contribution of localized phenomena to the nonrandomness (e.g., mesoscale circulations). [ABSTRACT FROM AUTHOR]

Climate change and the urban heat island (UHI) effect are increasing extreme heat risk in cities across the world, and have already made extreme heat the top weather-related cause of death in the United States. Despite this, understanding of viable strategies to address extreme heat is still limited, for both decision-makers and the public. Using a design-based research methodology, we developed an interactive educational game, Chill City, which teaches players about possible heat planning strategies and their tradeoffs. We surveyed adult, non-expert players to understand the game's reception and impacts. Players expressed that they enjoyed the game and that it helped them better understand heat planning strategies and the environmental, social, and economic tradeoffs associated with them. We argue that environmental games offer educational potential for adult learners on issues of extreme heat and climate change that should be further explored to inform effective approaches and designs. [ABSTRACT FROM AUTHOR]

Extreme heat is the deadliest climate hazard in the United States. Climate change and the urban heat island effect are increasing the number of dangerously hot days in cities worldwide and the need for communities to plan for extreme heat. Existing literature on heat planning focuses on heat island mapping and modeling, whereas few studies delve into heat planning and governance processes. We surveyed planning professionals from diverse cities across the United States to establish critical baseline information for a growing area of planning practice and scholarship that future research can build on. Survey results show that planners are concerned with extreme heat risks, particularly environmental and public health impacts from climate change. Planners already report impacts from extreme heat, particularly to energy and water use, vegetation and wildlife, public health, and quality of life. Especially in affected communities, planners claim they address heat in plans and implement heat mitigation and management strategies such as urban forestry, emergency response, and weatherization, but perceive many barriers related to human and financial resources and political will. Planners are concerned about extreme heat, especially in the face of climate change. They are beginning to address heat through different strategies and plan types, but we see opportunities to better connect planners to existing heat information sources and leverage existing planning tools, including vegetation, land use regulations, and building codes, to mitigate risks. Although barriers to heat planning persist, including human and capital resources, planners are uniquely qualified to coordinate communities' efforts to address the rising threat of extreme heat. [ABSTRACT FROM AUTHOR]

Satellite-derived land surface temperature (LST) is widely utilized to study urban heat islands in the context of human health and thermal exposure. However, there is growing evidence to suggest that LST may be a poor indicator of apparent temperature, or the human-perceived equivalent temperature that reflects both heat and humidity. Moreover, heat index (HI), the apparent temperature metric used by the US National Weather Service, has yet to be computed at an increased spatial resolution and coverage beyond weather station observations. The goals of this study were to: 1) assess the extent to which HI can be estimated by a combination of Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and other satellite-derived products available at continental scales, and 2) determine which factors are most important in this estimation. Specifically, daily maximum 1-km HI from May through September of 2012 was modelled across the conterminous United States as a function of MODIS LST, precipitable water vapor (PWV), and near-infrared indices, in addition to static variables capturing land cover, topographic, and locational factors.The derived model was capable of estimating HI within a reasonable level of error (R2 = 0.83, RMSE = 4.4°F). This is the first time that HI has been directly estimated using exclusively remotely sensed products and validated over a large spatial extent. Analysis of individual variables indicated that LST and PWV were, by far, the most important factors for estimation. However, the incorporation of additional parameters further improved model performance (R2: +0.14, RMSE: -1.6°F). We hope that our work will eventually result in a national HI product assisting researchers in a variety of fields, including epidemiology, building energy demand, and environmental justice. Further work to interpolate cloud-contaminated satellite observations and downscale estimates to a 60-m resolution would considerably increase the utility of this HI estimation methodology. [ABSTRACT FROM AUTHOR]

The impact of heat on human health is well‐recognized, with excess heat stress in urban areas (urban heat stress intensity, UHSI) adversely affecting rapidly growing urban populations. However, the physical associations of UHSI with urban heat island (UHI), urban‐induced change in moisture (UQI) and background temperature are not well understood. Multi‐year convection‐permitting simulations over the US show that UHI effect peaks during nighttime (2–5°C) but maximum UQI occurs in daytime (0.01–2 g kg−1), resulting in competing effects on UHSI. UHI dynamics dominate the diurnal variations in UHSI with intensified urban‐induced human discomfort during nighttime (3–5 hr day−1). UHSI is very sensitive to the background temperature, especially over the southeastern US, with distinct nightime UHSI amplification of ∼0.5 hr day−1 degree−1 rise in the background temperature. Spatial variability of UHSI is also dominated by the UHI with possible constrains from background moisture availability. Plain Language Summary: While urbanization increases the temperature of urban regions compared to rural regions, it also decreases the moisture in the urban air. Thus, urbanization can have heterogeneous effect on heat stress (a net effect of ambient temperature and moisture) on warmer days. In this study, we employed convection‐permitting simulations for six consecutive summer seasons over the US to examine the spatiotemporal variability of urban‐induced heat stress and its variation on relatively warmer days. We show that the heat stress is distinctly greater over the urban regions compared to surrounding rural regions in Eastern US and specifically over southeastern US. Moreover, this urban effect on heat stress grows stronger on warmer periods, specifically during nighttime, while the association can be opposite during daytime due to the dominant moisture effect. Quantitatively, urbanization can increase heat caution hours by 3–5 hr day−1 and its sensitivity to background temperature is ∼0.5 hr day−1 degree−1 over many US cities. Key Points: Multiyear cloud resolving simulations are done to understand the thermodynamical constrains of urban‐induced heat stressWhile urban‐induced temperature increase peaks during nighttime, the associated moisture reduction is maximum during daytimeHeat related human discomfort exposure increases by 3–5 hr day−1 due to urbanization [ABSTRACT FROM AUTHOR]

During and after rainfall events, the interaction of precipitation with hot urban pavements leads to hot runoff, and its merger with urban streams can result in an abrupt change in water temperature that can harm aquatic ecosystems. To understand this phenomenon and its relation to land cover and hydrometeorological parameters, we analyzed data spanning two years from 100 sites in the eastern United States. To identify surges, we first isolated temperature jumps of at least 0.5°C over 15 min occurring simultaneously with water flow increase. Surge magnitude was defined as the difference between peak stream temperature and baseflow temperature right before the jump. At least 10 surges were observed in 53 of the studied streams, with some surges exceeding 10°C. Our results demonstrate that the watershed developed area and vegetation fraction are the best descriptors of surge frequency (Spearman correlation of 0.76 and 0.77, respectively). On the other hand, for surge magnitude and peak temperature, the primary drivers are stream discharge and stream temperature immediately before the surge. In general, the more urbanized streams were found to be already warmer than their more "vegetated" counterparts during baseflow conditions, and were also the most affected by temperature surges. Together, these findings suggest the existence of a hydrological urban heat island, here defined as the increase in stream temperature (chronic and/or acute), caused by increased urbanization. [ABSTRACT FROM AUTHOR]

Large cities account for a significant share of national population and wealth, and exert high pressure on local and regional resources, exacerbating socioenvironmental risks. The replacement of natural landscapes with higher heat capacity materials because of urbanization and anthropogenic waste heat are some of the factors contributing to local climate change caused by the urban heat island (UHI) effect. Because of synergistic effects, local climate change can exacerbate the impacts of global warming in cities. Disentangling the contributions to warming in cities from global and local drivers can help to understand their relative importance and guide local adaptation policies. The canopy UHI intensity is commonly approximated by the difference between temperatures within cities and the surrounding areas. We present a complementary approach that applies the concept of common trends to extract the global contributions to observed warming in cities and to obtain a residual warming trend caused by local and regional factors. Once the effects of global drivers are removed, common features appear in cities' temperatures in the eastern part of the United States. Most cities experienced higher warming than that attributable to global climate change, and some shared a period of rapid warming during urban sprawl in the mid‐20th century in the United States. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect is strongly modulated by urban-scale changes to the aerodynamic, thermal, and radiative properties of the Earth's land surfaces. Interest in this phenomenon, both from the climatological and public health perspectives, has led to hundreds of UHI studies, mostly conducted on a city-by-city basis. These studies, however, do not provide a complete picture of the UHI for administrative units using a consistent methodology. To address this gap, we characterize clear-sky surface UHI (SUHI) intensities for all urbanized areas in the United States using a modified Simplified Urban-Extent (SUE) approach by combining a fusion of remotely-sensed data products with multiple US census-defined administrative urban delineations. We find the highest daytime SUHI intensities during summer (1.91 ± 0.97 °C) for 418 of the 497 urbanized areas, while the winter daytime SUHI intensity (0.87 ± 0.45 °C) is the lowest in 439 cases. Since urban vegetation has been frequently cited as an effective way to mitigate UHI, we use NDVI, a satellite-derived proxy for live green vegetation, and US census tract delineations to characterize how vegetation density modulates inter-urban, intra-urban, and inter-seasonal variability in SUHI intensity. In addition, we also explore how elevation and distance from the coast confound SUHI estimates. To further quantify the uncertainties in our estimates, we analyze and discuss some limitations of these satellite-derived products across climate zones, particularly issues with using remotely sensed radiometric temperature and vegetation indices as proxies for urban heat and vegetation cover. We demonstrate an application of this spatially explicit dataset, showing that for the majority of the urbanized areas, SUHI intensity is lower in census tracts with higher median income and higher proportion of white people. Our analysis also suggests that poor and non-white urban residents may suffer the possible adverse effects of summer SUHI without reaping the potential benefits (e.g., warmer temperatures) during winter, though establishing this result requires future research using more comprehensive heat stress metrics. This study develops new methodological advancements to characterize SUHI and its intra-urban variability at levels of aggregation consistent with sources of other socioeconomic information, which can be relevant in future inter-disciplinary research and as a possible screening tool for policy-making. The dataset developed in this study is visualized at: https://datadrivenlab.users.earthengine.app/view/usuhiapp. [ABSTRACT FROM AUTHOR]

High air temperatures are a public health threat, causing 1300 deaths annually in the United States (US) along with heat-related morbidity and increased electricity consumption for air-conditioning (AC). Increasing tree canopy cover has been proposed as one way to reduce urban air temperatures. Here, we assemble tree cover and developed land-cover information for 97 US cities, housing 59 million people, and use regression relationships to analyze how much current urban tree cover reduces summer (JJA) air temperatures and associated heat-related mortality, morbidity, and electricity consumption. We find that 78% of urban dwellers are in neighborhoods with less than 20% tree cover. Some 15.0 million people (25% of total) experience a reduction of 0.5–1.0°C from tree cover, with another 7.9 million (13% of total) experiencing a reduction of greater than 1.0°C. Current relationships between temperature and health outcomes imply that urban tree cover helps avoid 245–346 deaths annually. Heat–mortality relationships in the 1980s, when a smaller fraction of US households had AC, imply a greater role in the past for urban tree cover in avoiding heat-related mortality. As AC availability has increased, the value of tree cover for avoiding heat-related mortality has decreased, while the value of tree cover for reducing electricity consumption likely has increased. Currently, for the 97 cities studied, the total annual economic value of avoided mortality, morbidity, and electricity consumption is an estimated $1.3–2.9 billion, or $21–49 annually per capita. Applying our results to the entire US urban population, we estimate urban tree cover annually supplies heat-reduction services worth $5.3–12.1 billion. [ABSTRACT FROM AUTHOR]

• Suspended pavement practices can increase opportunities to manage urban stormwater. • Performance of two bioretention suspended pavement systems studied over 27 months. • Exfiltration, evapotranspiration were major hydrologic pathways from both systems. • Limited surface ponding, drainage-treatment area ratio led to high volume reduction. • Bioretention suspended pavement systems effectively reduced influent runoff volumes. Trees supply numerous ecosystem services to the urban environment, including mitigating the urban heat island, improving air quality, and providing habitat for wildlife. However, due to the structural stability requirements of infrastructure such as sidewalks, roadways, and parking areas, urban soils are commonly characterized by high compaction levels, low porosity, and nutrient deficiency, often to the detriment of urban tree health. By transmitting surface loads to a compacted subbase, suspended pavement systems create a matrix of uncompacted soil that promotes tree health through increased root access to oxygen, water, and nutrients. Recently, interest has grown in making suspended pavement systems multi-functional by designing them to act as subsurface bioretention practices in ultra-urban areas where space may be limited due to concentrated development and high land costs. Despite this interest, only one study has tested suspended pavement systems in this application. Further, the study utilized lined installations to allow a controlled water quality assessment; however, this negated the ability to fully quantify runoff reduction. Two unlined suspended pavement systems designed to function as subsurface bioretention practices were installed in Knoxville, Tennessee, USA, in 2015 and monitored over 27-months. During that period, over 99% of runoff volumes were reduced by the free-drained north system, which completely captured runoff from 79% of storms. The underdrained south system reduced influent runoff by over 88% and captured all runoff from 83% of events during the study. Influent TSS concentrations were significantly reduced by the south suspended pavement system, though no other significant differences between influent and effluent pollutant concentrations were observed, presumably due to low influent concentrations. This study demonstrates the viability of field-scale suspended pavement systems in a stormwater management application and illustrates the hydrologic and pollutant removal capabilities of these systems to manage urban stormwater runoff. [ABSTRACT FROM AUTHOR]

• A bilinear aging albedo model for asphalt pavements was calibrated from field cores. • Visible reflectance and albedo have a strong correlation for asphalt pavements. • Albedo, emissivity, and location impact radiative forcing. • Differences in thermal and optical properties affect surface temperature. Pavements contribute significantly to the development of Urban Heat Islands (UHIs). The impact of pavements on UHI depends on multiple material factors, including its thermal and optical properties. Field cores from asphalt concrete (AC) pavements from four locations in Illinois and one in Indiana, USA, were used to evaluate the optical and thermal properties of the corresponding pavements. Thermal conductivity ranged from 1.0 to 3.0 W/mK (average of 2.2 W/mK), diffusivity 0.6–2.0 mm2/s (average of 1.5 mm2/s), and heat capacity 0.7–3.0 MJ/m3K (average of 1.5 MJ/m3K), which differ significantly from values typically recommended in pavement design. The same cores were used to calibrate a simplified bilinear aging albedo model, with the asymptotic albedo and at-construction albedo being largely within the expected range of 0.10–0.20 and 0.05–0.10, respectively. The emissivity was found to be between 0.70 and 0.90, which agrees with values reported in the literature. These properties were used to evaluate the local pavement Radiative Forcing ( RF p ) and Global Warming Potential (GWP) as well as the diurnal net surface heat flux and surface temperature of the pavements. The RF p varied depending on aging albedo and emissivity, while surface temperature and net surface heat flux also depended on thermal properties. [ABSTRACT FROM AUTHOR]

Global urbanization drastically reshapes the land–atmosphere interactions, biogeochemical cycles, and ecosystems in the integrated earth system. Urban trees are used extensively for providing desirable ecosystem services, especially to mitigate elevated thermal stress in cities. Urban trees differ markedly from their natural counterparts in the physiology due to their close interactions with anthropogenic stressors. Here we present the cooling capacity of urban trees in response to thermal extremes in cities of the contiguous United States. The cooling capacity is quantified as the surface cooling rate, which is expressed as the negative ratio of land surface temperature (LST) changes to fractional tree cover (FTC) changes, i.e., –ΔLST/ΔFTC. Results show that the surface cooling rate is dominated by plant transpiration up to 1.336 °C per percentage of FTC in heat waves; its temperature dependence remarkably resembles the thermodynamic liquid-water-vapor equilibrium. Urban trees also exert pseudo cooling effect in cold waves in contrast to the anthropogenic heat emission. The average surface cooling rate in cold waves is 0.022 °C per percentage of FTC, which is much smaller than that in heat waves (0.202 °C per percentage of FTC). The enhanced cooling capacity of urban trees will enable their provision of better ecosystem services to the urban environment for projected future increase of extreme heat. Unlabelled Image • The surface cooling rate of urban trees during heat and cold waves is quantified. • Temperature dependence of tree cooling resembles the phase equilibrium of water. • The cooling of urban trees is dominated by plant transpiration in heat waves. • The synthetic cooling of cities is regulated by anthropogenic heat in cold waves. • Urban trees are ahead of the global change responses than their rural counterparts. [ABSTRACT FROM AUTHOR]

High‐resolution gridded climate data products are crucial to research and practical applications in climatology, hydrology, ecology, agriculture, and public health. Previous works to produce multiple data sets were limited by the availability of input data as well as computational techniques. With advances in machine learning and the availability of several daily satellite data sets providing unprecedented information at 1 km or higher spatial resolutions, it is now possible to improve upon earlier data sets in terms of representing spatial variability. We developed the NEX (NASA Earth Exchange) Gridded Daily Meteorology (NEX‐GDM) model, which can estimate the spatial pattern of regional surface climate variables by aggregating several dozen two‐dimensional data sets and ground weather station data. NEX‐GDM does not require physical assumptions and can easily extend spatially and temporally. NEX‐GDM employs the random forest algorithm for estimation, which allows us to find the best estimate from the spatially continuous data sets. We used the NEX‐GDM model to produce historical 1‐km daily spatial data for the conterminous United States from 1979 to 2017, including precipitation, minimum temperature, maximum temperature, dew point temperature, wind speed, and solar radiation. In this study, NEX‐GDM ingested a total of 30 spatial variables from 13 different data sets, including satellite, reanalysis, radar, and topography data. Generally, the spatial patterns of precipitation and temperature produced were similar to previous data sets with the exception of mountain regions in the western United States. The analyses for each spatially continuous data set show that satellite and reanalysis led to better estimates and that the incorporation of satellite data allowed NEX‐GDM to capture the spatial patterns associated with urban heat island effects. The NEX‐GDM data is available to the community through the NEX data portal. [ABSTRACT FROM AUTHOR]

Optimizing urban greenspace spatial pattern has been widely recommended to mitigate urban heat island (UHI) effect, mainly based on the statistically significant relationships between temperature and measurements of urban greenspace spatial pattern at local scale within a city. However, the scientific evidence at the city level is scarce, even though the importance of urban greenspace spatial pattern in mitigating UHI effect at the city level has been recognized. This study aims to fill this gap by investigating the relationship between the city level surface UHI intensity (SUHII) and a series of explanatory variables belonging to urban greenspace spatial pattern, urban morphology, and urban-rural difference of surface characteristics, using the region of Illinios-Indiana-Ohio in the USA as a case study. Results showed that urban greenspace spatial pattern variables were significantly correlated with SUHII, even after controlling for the impacts of urban-rural difference of surface characteristics (e.g., urban-rural difference of vegetation index) and urban morphology (e.g., urban size). SUHII was negatively correlated with patch density and mean patch shape of urban greenspace, and positively correlated with edge density of urban greenspace. Variance partitioning showed significant overlaps of the explanatory ability of these three groups of variables, which jointly explained 38% of the SUHII variation. Urban greenspace spatial pattern had a slightly larger independent role in explaining the SUHII variation than urban morphology (5% vs 2%), even though the urban-rural difference of surface characteristics was the major determinant (19%). Findings of this study extended our understanding of the impact of urban greenspace spatial pattern on SUHII from the local scale to the city scale and can help design effective urban planning and management strategies at the city scale to improve urban thermal environment. [ABSTRACT FROM AUTHOR]

Heat waves are an important type of extreme climate event and directly result in more than 130 deaths per year across the United States. Heat waves have been described by several attributes and combinations which constitute various event typologies. Attributes of heat waves from 10 cities are analyzed over the period 1950–2016 to understand how these attributes determine variability in local heat waves and how climate change affects heat waves across the United States. This study uses eight definitions to differentiate heat waves and tests for temporal trends in key properties of heat waves over the period 1950–2016. At least five harmful attributes of heat waves have increased simultaneously for Dallas, Miami, New York, Phoenix, and Portland.Miami showed the greatest change in heat wave season length, frequency, and timing over the study period. Surprisingly, the greatest mean heat wave intensities above daily thresholds were for Bismarck, ND (+8.2 °C) and Syracuse, NY (+6.5 °C). Similar results across Baltimore, MD, Colorado Springs, CO, Dallas, TX, Des Moines, IA, Miami, FL, New York, NY, Phoenix, AZ, and Portland, OR, are presented to clarify the many quantitative differences in heat wave attributes and variance in quantification approaches across climates. This work explores the nexus of quantitative description and social construction of heat waves through the lens of the various regional metrics to describe heat waves. Ultimately, this assessment will guide the development of various strategies to help communities understand and prepare for heat resilience based on local heat wave components. Plain Language Summary: Heat waves are a series of consecutive days and nights with very high temperatures. They impact human health and increase water and energy demands, particularly in the urban areas. Heat waves have different lengths, occur in various seasons, and have different ranges between daytime and nighttime temperatures. These variations create numerous types of heat waves. Although heat waves happen more frequently in hot regions, residents of cities in northern climates also experience various types of heat waves. Analysis of differences in heat wave occurrences from 1950 to 2016 in 10 cities with various climates across the United States shows how different types of heat waves are changing across the United States. We found that many descriptive characteristics are increasing in value through time. For example, heat wave duration has increased in Miami, FL. The findings of this study are intended to guide policy makers, urban managers, and first responders to better prepare for future changes in regional heat waves and mitigate negative impacts of heat waves on human health and the environment. Key Points: This study uses many different definitions for heat wave to make broad comparisonsRegional differences in heat wave components complicate uniform public health and urban management strategiesFrequency and intensity of extreme climate‐related urban heat wave events are increasing for the various climates of the United States [ABSTRACT FROM AUTHOR]

The aim of this work is to exploit the large-scale analysis capabilities of the innovative Google Earth Engine platform in order to investigate the temporal variations of the Urban Heat Island phenomenon as a whole. A intuitive methodology implementing a largescale correlation analysis between the Land Surface Temperature and Land Cover alterations was thus developed. The results obtained for the Phoenix MA are promising and show how the urbanization heavily affects the magnitude of the UHI effects with significant increases in LST. The proposed methodology is therefore able to efficiently monitor the UHI phenomenon. [ABSTRACT FROM AUTHOR]

A reduction in both power and electricity usage was determined using a previously validated zero-dimensional energy balance model that implements mitigation strategies used to reduce the urban heat island (UHI) effect. The established model has been applied to show the change in urban characteristic temperature when executing four common mitigation strategies: increasing the overall (1) emissivity, (2) vegetated area, (3) thermal conductivity, and (4) albedo of the urban environment in a series of increases by 5, 10, 15, and 20% from baseline values. Separately, a correlation analysis was performed involving meteorological data and total daily energy (TDE) consumption where the 24-h average temperature was shown to have the greatest correlation to electricity service data in the Phoenix, Arizona, USA, metropolitan region. A methodology was then developed for using the model to predict TDE consumption reduction and corresponding cost-saving analysis when implementing the four mitigation strategies. The four modeled UHI mitigation strategies, taken in combination, would lead to the largest percent reduction in annual energy usage, where increasing the thermal conductivity is the single most effective mitigation strategy. The single least effective mitigation strategy, increasing the emissivity by 5% from the baseline value, resulted in an average calculated reduction of about 1570 GWh in yearly energy usage with a corresponding 157 million dollar cost savings. When the four parameters were increased in unison by 20% from baseline values, an average calculated reduction of about 2050 GWh in yearly energy usage was predicted with a corresponding 205 million dollar cost savings. [ABSTRACT FROM AUTHOR]

[Display omitted] • Extreme heat increased cardiovascular morbidity risk and burden in older adults. • Female, 75 and older, and chronic condition populations were most heat vulnerable. • Areas with high urban heat island intensity (UHII) had elevated heat-related impacts. • High UHII exacerbated heat-related risk and burden in heat-vulnerable populations. • The impacts of extreme heat and UHII varied geographically across 120 US cities. Many United States (US) cities are experiencing urban heat islands (UHIs) and climate change-driven temperature increases. Extreme heat increases cardiovascular disease (CVD) risk, yet little is known about how this association varies with UHI intensity (UHII) within and between cities. We aimed to identify the urban populations most at-risk of and burdened by heat-related CVD morbidity in UHI-affected areas compared to unaffected areas. ZIP code-level daily counts of CVD hospitalizations among Medicare enrollees, aged 65–114, were obtained for 120 US metropolitan statistical areas (MSAs) between 2000 and 2017. Mean ambient temperature exposure was estimated by interpolating daily weather station observations. ZIP codes were classified as low and high UHII using the first and fourth quartiles of an existing surface UHII metric, weighted to each have 25% of all CVD hospitalizations. MSA-specific associations between ambient temperature and CVD hospitalization were estimated using quasi-Poisson regression with distributed lag non-linear models and pooled via multivariate meta-analyses. Across the US, extreme heat (MSA-specific 99th percentile, on average 28.6 °C) increased the risk of CVD hospitalization by 1.5% (95% CI: 0.4%, 2.6%), with considerable variation among MSAs. Extreme heat-related CVD hospitalization risk in high UHII areas (2.4% [95% CI: 0.4%, 4.3%]) exceeded that in low UHII areas (1.0% [95% CI: −0.8%, 2.8%]), with upwards of a 10% difference in some MSAs. During the 18-year study period, there were an estimated 37,028 (95% CI: 35,741, 37,988) heat-attributable CVD admissions. High UHII areas accounted for 35% of the total heat-related CVD burden, while low UHII areas accounted for 4%. High UHII disproportionately impacted already heat-vulnerable populations; females, individuals aged 75–114, and those with chronic conditions living in high UHII areas experienced the largest heat-related CVD impacts. Overall, extreme heat increased cardiovascular morbidity risk and burden in older urban populations, with UHIs exacerbating these impacts among those with existing vulnerabilities. [ABSTRACT FROM AUTHOR]

• Arid and tropical cities showed high sensible heat of 90.33 W m−2 and 108.48 W m−2. • Temperate climate showed increasing annual trends for both UHI and ΔHI. • The later period (2001–2014) demonstrated greater UHI and ΔHI trends. • The UHI was more intense compared to ΔHI. • UHI was positively correlated with temperatures in warm and hot cities while ΔHI correlated with precipitation in cool cities. Rising temperatures that occur in cities resulted in the urban heat island (UHI) which could also amplify the thermal heat stress, leading to climate-related human mortality. Our study investigated the UHI effect and thermal heat stress of heat index (HI) in the U.S. cities of arid, continental, temperate, and tropical climate zones. A long-term simulation of the UHI and HI was conducted using Community Land Model version 5.0 from 1990 to 2014. The relationship between UHI and HI with climate and energy flux variables are analyzed with divided study periods (1990–2000 and 2001–2014) for the urban impact assessment. Higher sensible heat was reported, particularly in the arid and tropical cities. Further, temperate climate showed increasing annual trends for UHI and ΔHI (urban-rural difference of HIs). The later period (2001–2014) demonstrated greater UHI and ΔHI trends, implying a notable change in climate and urban expansion. The UHI, ranging from 0.73 °C to 2.07 °C, was more intense compared with ΔHI, at 0.14 °C to 1.23 °C. The UHI was positively correlated with temperatures in hot cities, while precipitation is the main driver in the continental city. For ΔHI, the relationship with temperatures were dominant in all climate zones. [ABSTRACT FROM AUTHOR]

Global climate change is contributing to a range of adverse environmental and weather shifts, including more intense and more frequent heatwaves and an intensification of the urban heat island effect. These changes are known to produce a set of significant and differentially distributed health problems, with a particularly high burden among poor and marginalized populations. In this article, we report findings from a qualitative study of community knowledge, attitudes, health and other concerns, and behavioral responses regarding mounting urban temperatures and related environmental health issues among Latinos living in the city of Hartford, CT in northeast United States. Findings suggest the need for enhanced participation in knowledge dissemination and preparedness planning based on the coproduction of knowledge about climate change and community responses to it. The special role of anthropology in such efforts is highlighted. [ABSTRACT FROM AUTHOR]

Urban heat island intensity (UHI) has become a cross-cutting quotient to characterize the thermal environment of urban areas. In this study, we use publicly available weather data from ten metropolitan centers located in US to characterize the hourly, seasonal and yearly variability in air temperature based UHI. Our results reveal that while there are phenomenological similarities on UHI causes and trends, their order of influence in different cities is however distinct. Of cities compared here the coastal and arid cities exhibited high diurnal variability during the summer months. During the cold season, except for New York City, other cities had a flatter profile. Our analysis also shows that during extreme heat days in the warm season, the UHI is amplified in most cities. The UHI of cities located along the coast was highly sensitive to sea breeze and in general experience more extreme heat days than the inland cities. [ABSTRACT FROM AUTHOR]

In this study, the Weather Research and Forecasting (WRF) Model and its embedded land surface and urban canopy model are used to simulate effects of urbanization on the local climate of the Las Vegas, Nevada, metropolitan area. High-resolution simulations are performed with a 3-km horizontal resolution over the city. With identical lateral boundary conditions, three land use/land cover (LULC) maps for 2006, 1992, and hypothetical 1900 are used in multiple simulations. The differences in the simulated climate among those cases are used to quantify the urban effect. The study found that urbanization in Las Vegas produces a classic urban heat island (UHI) at night but a minor cooling trend during the day. An analysis of the surface energy balance helps illustrate the major roles of the decreases in surface albedo of solar radiation and increases in the effective emissivity of longwave radiation in shaping the local climate change in Las Vegas. In addition, the emerging urban structures are found to have a mechanical effect of slowing down the climatological wind field over the urban area as a result of an increased effective surface roughness. The slowing down of the diurnal circulation leads to a secondary modification of temperature, which exhibits a complicated diurnal dependence. This suggests the need for more investigations into the coupling of thermodynamic and mechanical effects of urbanization on local climate. [ABSTRACT FROM AUTHOR]

Based on a case study of the Stadshaven port redevelopment in Rotterdam, this paper explores whether existing spatial planning mechanisms and processes can be used to facilitate local-level investment in climate-resilient public infrastructure and/or whether new processes and mechanisms are required to encourage investment in climate adaptation. The study reveals several key findings. First, a lack of conventional funding sources or formalised regulatory framework allowed room for experimentation with existing mechanisms and flexible strategies. Second, project planners are currently ambivalent towards introducing new mechanisms as a means to overcome implementation challenges. The case provides evidence about the role of the governance process, not simply as a means of system coordination that exists in isolation from institutional norms and values, but rather as a space for innovation, which can contribute towards reducing the financial gap associated with climate adaptation. [ABSTRACT FROM AUTHOR]

As part of ASME 4th joint US-European Fluid Engineering Division Summer Meeting, which took place in Chicago in August 2014, a symposium was held on Urban Fluid Mechanics, spanning from urban issues such as climate and heat island effect, to small city-scale effects, such as the flow around isolated buildings. The aim of the present note is to make a synthesis of the presentations, in order to highlight current trends of research and issues. [ABSTRACT FROM AUTHOR]

Heat-related mortality in US cities is expected to more than double by the mid-to-late 21st century. Rising heat exposure in cities is projected to result from: 1) climate forcings from changing global atmospheric composition; and 2) local land surface characteristics responsible for the urban heat island effect. The extent to which heat management strategies designed to lessen the urban heat island effect could offset future heat-related mortality remains unexplored in the literature. Using coupled global and regional climate models with a human health effects model, we estimate changes in the number of heat-related deaths in 2050 resulting from modifications to vegetative cover and surface albedo across three climatically and demographically diverse US metropolitan areas: Atlanta, Georgia, Philadelphia, Pennsylvania, and Phoenix, Arizona. Employing separate health impact functions for average warm season and heat wave conditions in 2050, we find combinations of vegetation and albedo enhancement to offset projected increases in heat-related mortality by 40 to 99% across the three metropolitan regions. These results demonstrate the potential for extensive land surface changes in cities to provide adaptive benefits to urban populations at risk for rising heat exposure with climate change. [ABSTRACT FROM AUTHOR]

Abstract: The Woodlands Township, TX, has a tree protection policy that consists of tree removal permits and minimum tree and shrub cover regulations. This paper examined the effect of The Woodlands’ tree protection policy on surface urban heat island (SUHI) at the neighborhood scale by comparing the mean land surface temperatures (LSTs) derived from 37 thermal infrared bands of Landsat TM images between The Woodlands’ neighborhoods and nearby control neighborhoods without such a policy. To rule out the effect of confounding factors that may influence LSTs, the control neighborhoods were selected to be similar in physical and socioeconomic status to The Woodlands’ neighborhoods. LSTs of The Woodlands’ neighborhoods were, on average, 1.5–3.9°C lower than those of the control neighborhoods. The cooling effect of The Woodlands’ tree protection policy was more prominent in summer when SUHI mitigation was mostly needed. Based on these findings, it can be concluded that a local tree protection policy is effective in mitigating SUHI at the neighborhood scale. [Copyright &y& Elsevier]

A new index of calculating the intensity of urban heat island effects (UHI) for a city using satellite skin temperature and land cover observations is recommended. UHI, the temperature difference between urban and rural regions, is traditionally identified from the 2-m surface air temperatures (i.e., the screen-level temperature T2m) measured at a pair of weather stations sited in urban and rural locations. However, such screen-level UHI is affected by the location, distance, and geographic conditions of the pair of weather stations. For example, choosing a different pair of rural and city sites leads to a different UHI intensity for the same city, due to the high heterogeneity of the urban surface temperature. To avoid such uncertainty, satellite-observed surface skin temperature measurements (i.e., skin level temperature Tskin) is recommended to record UHI, known as skin-level UHI or UHIskin. This new index has advantages of high spatial resolution and aerial coverage to better record UHI intensity than T2m. An assessment of skin-level UHI from 10 yr of the National Aeronautics and Space Administration (NASA)'s Moderate Resolution Imaging Spectroradiometer (MODIS) observations reveals that skin-level UHI has a strong UHI signal during the day and at night. In addition, there are significant diurnal and seasonal variations in skin-level UHI. Furthermore, the skin-level UHI is stronger during the day and summer (July) than during nighttime and winter. This new index is important for more uniformly assessing UHIs over cities around the globe. Nevertheless, whether the seasonality and diurnal variations revealed in this work using skin-level UHI index are valid over desert cities, such as Phoenix, Arizona, need to be examined. [ABSTRACT FROM AUTHOR]

Impervious surface area (ISA) from the National Land Cover Database 2001 and land surface skin temperature from MODIS averaged over three annual cycles (2003-2005) are used in a spatial analysis to assess the surface urban heat island (UHI) signature and its relationship to settlement size and shape, development intensity distribution, and land cover composition for 42 urban settlements embedded in forest biomes in the northeastern United States. Development intensity zones, based on percent ISA, are defined for each urban area emanating outward from the urban core to nearby rural areas and are used to stratify land surface temperature. The stratification is further constrained by biome type and elevation to ensure objective intercomparisons between urban zones within an urban settlement and between settlements. Stratification based on ISA allows the definition of hierarchically ordered urban zones that are consistent across urban settlements and scales. For cities within the northeastern US temperate mixed forest biome, we found that settlement size, shape, and development intensity significantly influenced the amplitude of summer daytime UHI. Our study indicates that for cities of similar size, the ISA density distribution within the urban area and the shape of the urbanized area as measured by area to perimeter ratio are significant modulators of UHI magnitude. Our results indicate that remotely sensed satellite data provide a consistent characterization of the UHI magnitude as well as its major drivers across regional scales. [ABSTRACT FROM AUTHOR]

Background: Prior studies from around the world have indicated that very high temperatures tend to increase summertime mortality. However possible effect modification by urban micro heat islands has only been examined by a few studies in North America and Europe. This study examined whether daily mortality in micro heat island areas of Hong Kong was more sensitive to short term changes in meteorological conditions than in other areas. Method: An urban heat island index (UHII) was calculated for each of Hong Kong's 248 geographical tertiary planning units (TPU). Daily counts of all natural deaths among Hong Kong residents were stratified according to whether the place of residence of the decedent was in a TPU with high (above the median) or low UHII. Poisson Generalized Additive Models (GAMs) were used to estimate the association between meteorological variables and mortality while adjusting for trend, seasonality, pollutants and flu epidemics. Analyses were restricted to the hot season (June-September). Results: Mean temperatures (lags 0-4) above 29°C and low mean wind speeds (lags 0-4) were significantly associated with higher daily mortality and these associations were stronger in areas with high UHII. A 1°C rise above 29°C was associated with a 4.1% (95% confidence interval (CI): 0.7%, 7.6%) increase in natural mortality in areas with high UHII but only a 0.7% (95% CI: -2.4%, 3.9%) increase in low UHII areas. Lower mean wind speeds (5th percentile vs. 95th percentile) were associated with a 5.7% (95% CI: 2.7, 8.9) mortality increase in high UHII areas vs. a -0.3% (95% CI: -3.2%, 2.6%) change in low UHII areas. Conclusion: The results suggest that urban micro heat islands exacerbate the negative health consequences of high temperatures and low wind speeds. Urban planning measures designed to mitigate heat island effects may lessen the health effects of unfavorable summertime meteorological conditions. [ABSTRACT FROM AUTHOR]

Abstract: Metropolitan Phoenix has been amongst the most rapidly urbanizing cities in the USA, and is also subject to an urban heat island (UHI) of significant intensity and extent. There is a need to mitigate its detrimental effects through sustainable methods, such as through the application of low-water demand, xerophytic trees with broad canopies within residential yards (i.e. xeriscaping). Urban xeriscaping has the potential to reduce urban water use, urban temperatures and outdoor thermal discomfort, but evaluating its effectiveness has not been widely researched. In this study, we used a micro-scale urban climate model (ENVI-met) to generate xeriscaping scenarios in two residential areas with different existing surface vegetation cover (mesic vs. xeric). We subsequently examined the resulting impacts of xeriscaping on near-surface temperatures and outdoor thermal comfort over different spatial scales and temporal periods. Compared to existing conditions, xerophytic shade trees have strong UHI mitigation potential in existing xeric residential areas in Phoenix, with greater cooling occurring at (i.) microscales (∼2.5 °C) vs. local-scales (∼1.1 °C), and during (ii.) nocturnal (0500 h) vs. daytime periods (1700 h) under high xeriscaping scenarios. Conversely, increased xeriscaping resulted in net warming and increased thermal discomfort over mesic residential neighborhoods over all spatial scales and temporal periods. These varying results over different residential land cover in Phoenix therefore must be considered by stakeholders when considering xeriscaping as a UHI mitigation method. [Copyright &y& Elsevier]

To evaluate the impacts of the urban heat island (UHI) effect on precipitation over a complex geographic environment in northern Taiwan, the next-generation mesoscale model, the Weather Research and Forecasting (WRF) model, coupled with the Noah land surface model and urban canopy model (UCM), was used to study this issue. Based on a better land use classification derived from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite data (the MODIS case), it has significantly improved simulation results for the accumulation rainfall pattern as compared with the original U.S. Geological Survey (USGS) 25-category land use classification (the USGS case). The precipitation system was found to develop later but stronger in the urban (MODIS) case than in the nonurban (USGS) case. In comparison with the observation by radar, simulation results predicted reasonably well; not only was the rainfall system enhanced downwind of the city over the mountainous area, but it also occurred at the upwind plain area in the MODIS case. The simulation results suggested that the correct land use classification is crucial for urban heat island modeling study. The UHI effect plays an important role in perturbing thermal and dynamic processes; it affects the location of thunderstorms and precipitation over the complex geographic environment in northern Taiwan. [ABSTRACT FROM AUTHOR]

This study estimates the excess mortality attributable to excessive heat events (EHEs) for forty major U.S. cities during 1975-1995 and 1975-2004. We calculate these results using the spatial synoptic classification method to identify EHE days. Step-wise regressions are then used to estimate the location-specific mortality algorithms that can account for the impact of the EHEs' duration, severity, and timing. Our excess mortality results are expressed both as lives lost and associated mortality rates (excess deaths per 100,000 residents) using 2000 Census population estimates. Our results generally show a reduction in EHE-attributable mortality rates since 1996. Adjusting our results to account for changes in the average number of EHE days per year in each period does not affect this general conclusion. However, this adjustment has a considerable impact on a measure of the cities' relative performance in terms of reducing this EHE-attributable excess mortality. Our results indicate there is promise for further reductions in EHE-attributable mortality from the approximately 1300 excess deaths per summer we identify using data from the 1975-2004 period. However, the magnitude of this result highlights the significant health burden of EHEs relative to other extreme weather events in the United States and suggests it is worthy of additional attention. Our results also raise important questions with respect to evaluating the performance of EHE notification and response programs and how EHE-attributable mortality should be estimated for future scenarios, notably for climate change projections. [ABSTRACT FROM AUTHOR]

Abstract: Impervious surface area (ISA) from the Landsat TM-based NLCD 2001 dataset and land surface temperature (LST) from MODIS averaged over three annual cycles (2003–2005) are used in a spatial analysis to assess the urban heat island (UHI) skin temperature amplitude and its relationship to development intensity, size, and ecological setting for 38 of the most populous cities in the continental United States. Development intensity zones based on %ISA are defined for each urban area emanating outward from the urban core to the non-urban rural areas nearby and used to stratify sampling for land surface temperatures and NDVI. Sampling is further constrained by biome and elevation to insure objective intercomparisons between zones and between cities in different biomes permitting the definition of hierarchically ordered zones that are consistent across urban areas in different ecological setting and across scales. We find that ecological context significantly influences the amplitude of summer daytime UHI (urban–rural temperature difference) the largest (8°C average) observed for cities built in biomes dominated by temperate broadleaf and mixed forest. For all cities combined, ISA is the primary driver for increase in temperature explaining 70% of the total variance in LST. On a yearly average, urban areas are substantially warmer than the non-urban fringe by 2.9°C, except for urban areas in biomes with arid and semiarid climates. The average amplitude of the UHI is remarkably asymmetric with a 4.3°C temperature difference in summer and only 1.3°C in winter. In desert environments, the LST''s response to ISA presents an uncharacteristic “U-shaped” horizontal gradient decreasing from the urban core to the outskirts of the city and then increasing again in the suburban to the rural zones. UHI''s calculated for these cities point to a possible heat sink effect. These observational results show that the urban heat island amplitude both increases with city size and is seasonally asymmetric for a large number of cities across most biomes. The implications are that for urban areas developed within forested ecosystems the summertime UHI can be quite high relative to the wintertime UHI suggesting that the residential energy consumption required for summer cooling is likely to increase with urban growth within those biomes. [Copyright &y& Elsevier]

Abstract  A zero-dimensional energy balance model was previously developed to serve as a user-friendly mitigation tool for practitioners seeking to study the urban heat island (UHI) effect. Accordingly, this established model is applied here to show the relative effects of four common mitigation strategies: increasing the overall (1) emissivity, (2) percentage of vegetated area, (3) thermal conductivity, and (4) albedo of the urban environment in a series of percentage increases by 5, 10, 15, and 20% from baseline values. In addition to modeling mitigation strategies, we present how the model can be utilized to evaluate human health vulnerability from excessive heat-related events, based on heat-related emergency service data from 2002 to 2006. The 24-h average heat index is shown to have the greatest correlation to heat-related emergency calls in the Phoenix (Arizona, USA) metropolitan region. The four modeled UHI mitigation strategies, taken in combination, would lead to a 48% reduction in annual heat-related emergency service calls, where increasing the albedo is the single most effective UHI mitigation strategy. [ABSTRACT FROM AUTHOR]

The aerosol direct effect, namely, scattering and absorption of sunlight in the atmosphere, can lower surface temperature by reducing surface insolation. By combining National Aeronautics and Space Administration (NASA) AERONET (AErosol RObotic NETwork) observations in large cities with Weather Research and Forecasting (WRF) model simulations, we find that the aerosol direct reduction of surface insolation ranges from 40-100Wm-2, depending on aerosol loading and land-atmosphere conditions. To elucidate the maximum possible effect, values are calculated using a radiative transfer model based on the top quartile of the multiyear instantaneous aerosol data observed by AERONET sites. As a result, surface skin temperature can be reduced by 1°C-2°C while 2-m surface air temperature reductions are generally on the order of 0.5°C-1°C. [ABSTRACT FROM AUTHOR]

The sustainability of our planet is impacted as regions are transformed from rural to urban engineered infrastructures resulting in alterations at the surface and atmosphere. These changes are manifested in urban areas experiencing increased temperatures with respect to their rural counterparts, known as the Urban Heat Island (UHI) Effect. The impact of the UHI on light duty gasoline vehicle emissions was modeled using the U.S. Environmental Protection Agency (EPA) MOBILE6 model. It is shown that the impact on exhaust running emissions as a yearly total is very small while evaporative emissions and starting emissions are increased and decreased throughout the year, respectively. [ABSTRACT FROM AUTHOR]

The article focuses on the significance of adapting climate change models to address adverse effect of the global warming in the U.S. It refers to the measures designed to minimize the damaged brought by the climate change, by protecting infrastructure and communities against flood, erosion and extreme weather. Meanwhile, the Public Health Climate Change Adaptation Strategy in California, is one of the many strategies to suggest the promotion of community resilience and reduce the vulnerability to climate change through changing the built environment with more urban residential density, bike trails and parks designs to minimize the urban heat islands.

• In the US, urban land surface temperature (LST) was higher compared to rural LST. • Despite urbanization, urban LST in India was lower compared to rural LST. • Non-photosynthetic vegetation (NPV) and barren land types influence the results. • Built-up indices used here do not differentiate sparse vegetation and built-up surfaces. • New methods are needed for quantifying urbanization's impact on LST in India. Daytime surface UHI (SUHI) and the factors influencing it across highly populated cities in India and the United States (US) were evaluated. Urban-rural mean land surface temperature (LST) differences (ΔT S) were calculated and correlated with vegetation and built-up surface densities, quantified using the Normalized Difference Vegetation Index (NDVI) and Index Based Built-Up Index (IBI) respectively. The results from the US show a conventional SUHI phenomenon, and LST decrease with increasing vegetation and decreasing built-up surfaces. However, in India, despite existing urban densities, urban areas are cooler than the rural surroundings. The average LST was higher and NDVI was lower compared to the US, and NDVI and LST correlations were weak. Furthermore, in India, the average IBI values calculated for built-up areas, cropland, and other sparse vegetation land covers were approximately equal. The prevalence of non-photosynthetic vegetation (NPV) and barren soil in India are impacting spectral indices and the correlations. Differences in ΔT S and spectral indices trends between India and US highlight the shortcomings of the indices used in appropriately identifying Indian LULC types and establish the need for localized SUHI research methods that can specifically analyze the impact of urbanization on SUHI in India. [ABSTRACT FROM AUTHOR]

• Climatic variation in the effects of UHI on building energy consumption is quantified. • Annual energy impacts of UHI are strongly correlated with degree days, absolute humidity, and solar radiation. • Statistical model to predict annual building energy impacts of UHI is presented. UHI has significant impact on building energy consumption and associated greenhouse gas emissions in urban areas globally. However, the nature and extent of these effects are governed by the year-round climatic conditions at specific locations. In a dualistic relationship, UHI tends to increase the annual energy consumption of buildings located in hot climates and decrease it in cold climates. In this study, we conducted building energy simulations for 43 locations around the United States (U.S.) in order to quantify the relationships among the energy impacts of UHI and climatic variables. The energy impacts of UHI were found to be strongly correlated with several variables including degree days, absolute humidity, and solar radiation, while independent of wind speed and precipitation. Consecutively, we developed a multiple regression model to predict the relative energy impacts of UHI based on climatic context and evaluated the effect of UHI intensity on energy impacts across all 15 U.S. climate zones. The results of this study quantitatively validate the dualistic nature of UHI and present a statistical method to estimate the climatic variation in the impacts of UHI on building energy consumption. This can have significant implications in prioritizing UHI mitigation policies based on location and climate. [ABSTRACT FROM AUTHOR]

Abstract: By using both high-resolution orthoimagery and medium-resolution Landsat satellite imagery with other geospatial information, several land surface parameters including impervious surfaces and land surface temperatures for three geographically distinct urban areas in the United States – Seattle, Washington, Tampa Bay, Florida, and Las Vegas, Nevada, are obtained. Percent impervious surface is used to quantitatively define the spatial extent and development density of urban land use. Land surface temperatures were retrieved by using a single band algorithm that processes both thermal infrared satellite data and total atmospheric water vapor content. Land surface temperatures were analyzed for different land use and land cover categories in the three regions. The heterogeneity of urban land surface and associated spatial extents were shown to influence surface thermal conditions because of the removal of vegetative cover, the introduction of non-transpiring surfaces, and the reduction in evaporation over urban impervious surfaces. Fifty years of in situ climate data were integrated to assess regional climatic conditions. The spatial structure of surface heating influenced by landscape characteristics has a profound influence on regional climate conditions, especially through urban heat island effects. [Copyright &y& Elsevier]

The article presents a study which aims to compare the time-series analyses of urban and rural temperature trends in proximity to the most populous metropolitan areas of the U.S. It also examines the temperature data from the urban and proximate rural stations for 50 large metropolitan areas in the U.S. to determine the mean decadal rate of change in urban temperatures, rural temperatures, as well as heat island intensity between 1951 and 2000. The study reveals that the mean decadal rate of change in the heat island intensity of large cities in the U.S. over the five decades is 0.05 degree Celsius and indicates a division concerning the temperature trends between cities in the northeastern and southern regions in the U.S.

Multiply nested urbanized mesoscale model [Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS)] simulations of the New York–New Jersey metropolitan region are conducted for 4–11 July 2004. The simulations differ only in their specification of sea surface temperatures (SSTs) on nest 4 (1.33-km resolution) and nest 5 (0.44-km resolution). The “control SST” simulation (CONTROL-SST) uses an analyzed SST product, whereas the “New York Harbor Observing and Prediction System (NYHOPS) SST” simulation (NYHOPS-SST) uses hourly SSTs from the NYHOPS model hindcast. Upwelling-favorable (southerly) winds preceding the simulation time period and continuing for much of the first 5 days of the simulation generate cold water adjacent to the New Jersey coast and a cold eddy immediately outside of the harbor in the New York Bight. Both features are prominent in NYHOPS-SST but are not pronounced in CONTROL-SST. The upwelled water has a discernible influence on the overlying atmosphere by cooling near-surface air temperatures by approximately 1°–2°C, slowing the near-surface winds by 15%–20%, and reducing the nocturnal urban heat island effect by up to 1.3°C. At two coastal land-based sites and one overwater station, the wind speed mean bias is systematically reduced in NYHOPS-SST. During a wind shift to northwesterly on day 6 (9 July 2004) the comparatively cooler NYHOPS-SSTs impact the atmosphere over an even broader offshore area than was affected in the mean during the previous 5 days. Hence, air temperature evolution measured at the overwater site is better reproduced in NYHOPS-SST. Interaction of the offshore flow with the cool SSTs in NYHOPS-SST induces internal boundary layer (IBL) formation, sustained and deepened by turbulent kinetic energy advected from adjacent land areas; IBL formation did not occur in CONTROL-SST. [ABSTRACT FROM AUTHOR]

The article focuses on the potential of wasted space in urban areas in the U.S. Some factors to consider to increase the social and environmental value of the wasted space within local rights-of-way are provided, including the physical terms of the streets, their use and their materiality. It discusses the four ecological purposes streets could serve such as protecting and maintaining groundwater supplies, counteracting the urban heat-island effect, combating global warming and providing wildlife habitat and corridors.

Various interests desire information and data on heavy snowfalls to define their spatial and temporal occurrences. Historical data at the nation’s 208 first-order stations for events with 15.2 cm or more snowfall in 2 days or less was assessed, and revealed various serious data problems at 118 stations with climatological quality data available for 90 stations. The data problems are described as guidelines for those seeking to utilize heavy snowfall data, and stations with quality data are listed. [ABSTRACT FROM AUTHOR]

Urban heat island (UHI) analyses for the conterminous United States were performed using three different forms of metadata: nightlights-derived metadata, map-based metadata, and gridded U.S. Census Bureau population metadata. The results indicated that metadata do matter. Whether a UHI signal was found depended on the metadata used. One of the reasons is that the UHI signal is very weak. For example, population was able to explain at most only a few percent of the variance in temperature between stations. The nightlights metadata tended to classify lower population stations as rural compared to map-based metadata while the map-based metadata urban stations had, on average, higher populations than urban nightlights. Analysis with gridded population metadata indicated that statistically significant urban heat islands could be found even when quite urban stations were classified as rural, indicating that the primary signal was coming from the relatively high population sites. If ∼30% of the highest population stations were removed from the analysis, no statistically significant urban heat island was detected. The implications of this work on U.S. climate change analyses is that, if the highest population stations are avoided (populations above 30 000 within 6 km), the analysis should not be expected to be contaminated by UHIs. However, comparison between U.S. Historical Climatology Network (HCN) time series from the full dataset and a subset excluding the high population sites indicated that the UHI contamination from the high population stations accounted for very little of the recent warming. [ABSTRACT FROM AUTHOR]

The effect of rural variability in calculating the urban heat island effect for Phoenix, Arizona, was examined. A dense network of temperature and humidity sensors was deployed across different land uses on an agricultural farm southeast of Phoenix for a 10-day period in April 2002. Temperature data from these sensors were compared with data from Sky Harbor Airport in Phoenix (an urban station) to assess the urban heat island effect using different rural baselines. The smallest and largest temperature differences between locations on the farm at a given time were 0.8° and 5.4°C, respectively. A t test revealed significant temperature differences between stations on the farm over the entire study period. Depending on the choice of rural baselines, the average and maximum urban heat island effects ranged from 9.4° to 12.9°C and from 10.7° to 14.6°C, respectively. Comparison of land cover types of the agricultural farm and land cover percentages in the Phoenix urban fringe was performed with satellite imagery. Classification of the entire urban fringe by using satellite imagery allowed for the local farm data to be scaled to a regional level. [ABSTRACT FROM AUTHOR]

Because of rapid growth and urbanization of Atlanta, Georgia, over the past few decades, the city has developed a pronounced urban heat island (UHI) that has been shown to enhance and possibly to initiate thunderstorms. This study attempts to find patterns and causes of Atlanta's induced precipitation that might not have been initiated otherwise. Land use maps, radar reflectivity, surface meteorological data, upper-air soundings, and airmass classification (spatial synoptic classification) types are all used to determine when, where, and why precipitation is initiated by Atlanta. Findings illustrate significant spatial and temporal patterns based on a 5-yr climatological description of events. July had the most events, with a diurnal peak just after local midnight. Low-level moisture, rather than UHI intensity, appears to be the most important factor for UHI-induced precipitation. However, UHI intensity also plays an important role. Events tended to occur under atmospheric conditions that were more unstable than those on rain-free days but not unstable enough to produce widespread convection. [ABSTRACT FROM AUTHOR]

Growth of the surface temperature urban heat island (UHI) of Houston, TX is determined by comparing two sets of heat island measurements taken 12 years apart. Individual heat island characteristics are calculated from radiative temperature maps obtained using the split-window infrared channels of the Advanced Very High Resolution Radiometer (AVHRR) on board National Oceanic and Atmospheric Administration polar-orbiting satellites. Eighty-two nighttime scenes taken between 1985 and 1987 are compared to 125 nighttime scenes taken between 1999 and 2001. Analysis of the UHI characteristics from these two intervals reveals a mean growth in magnitude of 0.8 K, or 35%. The growth of the mean area of the UHI is found to range between 170 and 650 km2, or from 38% to 88%, depending on the method of analysis. [Copyright &y& Elsevier]