Urban-rural Temperature Differences Research Articles

Feasibility of Urban–Rural Temperature Difference Method in Surface Urban Heat Island Analysis under Non-Uniform Rural Landcover: A Case Study in 34 Major Urban Agglomerations in China

The urban–rural temperature difference is widely used in measuring surface urban heat island intensity (SUHII), where the accurate determination of rural background is crucial. However, traditionally, the entire permeable rural surface has been selected to represent the background temperature, leaving uncertainty about the impact of non-uniform rural surfaces with multiple land covers on the accuracy of SUHII quantification. In this study, we proposed two quantifications of SUHII derived from the primary (SUHII1) and secondary (SUHII2) land types, respectively, which successively occupy over 40–50% of whole rural regions. The spatial integration and temporal variation of SUHII1 and SUHII2 were compared with the result from whole rural regions (SUHII) within 34 urban agglomerations (UAs) in China. The results showed that the SUHII1 and SUHII2 differed slightly with SUHII, and the correlation coefficients of SUHII and SUHII1/SUHII2 are generally above 0.9 in most (32) UAs. Regarding the long-term SUHII between 2003 and 2019, the three methods demonstrated similar seasonal patterns, although SUHII1 (or SUHII2) tended to overestimate or underestimate compared to SUHII. As for the multi-year integration at the regional scale, the day–night cycle and monthly variations of SUHII1 and SUHII were found to be identical for each geographical division separately, indicating that the spatiotemporal pattern revealed by SUHII is minimally affected by the diversity of rural landcover types. The findings confirmed the viability of the urban–rural LST difference method for measuring long-term regional SUHII patterns under non-uniform rural land cover types.

Machine Learning for Simulation of Urban Heat Island Dynamics Based on Large-Scale Meteorological Conditions

This study considers the problem of approximating the temporal dynamics of the urban-rural temperature difference (ΔT) in Moscow megacity using machine learning (ML) models and predictors characterizing large-scale weather conditions. We compare several ML models, including random forests, gradient boosting, support vectors, and multi-layer perceptrons. These models, trained on a 21-year (2001–2021) dataset, successfully capture the diurnal, synoptic-scale, and seasonal variations of the observed ΔT based on predictors derived from rural weather observations or ERA5 reanalysis. Evaluation scores are further improved when using both sources of predictors simultaneously and involving additional features characterizing their temporal dynamics (tendencies and moving averages). Boosting models and support vectors demonstrate the best quality, with RMSE of 0.7 K and R2 > 0.8 on average over 21 years. For three selected summer and winter months, the best ML models forced only by reanalysis outperform the comprehensive hydrodynamic mesoscale model COSMO, supplied by an urban canopy scheme with detailed city-descriptive parameters and forced by the same reanalysis. However, for a longer period (1977–2023), the ML models are not able to fully reproduce the observed trend of ΔT increase, confirming that this trend is largely (by 60–70%) driven by megacity growth. Feature importance assessment indicates the atmospheric boundary layer height as the most important control factor for the ΔT and highlights the relevance of temperature tendencies as additional predictors.

Understanding the differences in the effect of urbanization on land surface temperature and air temperature in China: insights from heatwave and non-heatwave conditions

Accelerated urbanization and frequent heatwave events pose significant threats to human health. Analyses of the differences in air and land surface temperature (LST) under extreme climates can aid in understanding human-nature ecosystem coupling and the required adaptations to climate change. In this study, we quantified differences in urban and rural temperatures in China under heatwave (CHW) and non-heatwave periods (NHW) conditions and the influence of meteorological factors on these differences. Based on impervious surface data, 2421 urban and rural stations were dynamically classified from 2008 to 2017. Heatwaves were identified using relative thresholds, and differences were explored using meteorological data and MODIS LST data. For LST, urban–rural temperature difference (U-RTempdiff) was highest during the day, whereas air temperature peaks occurred at night, under both NHW and CHW conditions. During CHWs, the daytime U-RTempdiff was greater for LST than for air temperature, reaching 4.24 ± 3.38 °C. At night, U-RTempdiff was slightly lower (1.04 ± 1.41 °C). The proportion of air U-RTempdiff contributed by rural air temperature was significantly higher during CHW nights than during NHW nights, whereas the proportion of land surface and air U-RTempdiff remained relatively stable during daytime. Spatially, the daytime temperature difference in the north decreased with latitude, whereas the difference in the south was lower. Under CHWs, urbanization had a stronger effect on LST than on air temperature, with a slightly smaller difference (0.01 °C yr−1) during the day and a slightly larger difference (0.03 °C yr−1) at night. The contribution of urbanization to LST was higher than that to air temperature, particularly during the day (16.34%). The effects of wind speed and precipitation on the average air urban–rural temperature difference was greater than those of LST under CHW, accounting for 16.13%, with the effects of wind speed being more significant. These results show that a comprehensive perspective is needed to understand the risks associated with a temperature rise risk under extreme climate conditions and to formulate effective mitigation measures that will they improve human thermal comfort under climate change.

Urban Warming Challenges Verification of Frost Advisories and Freeze Warnings in Madison, Wisconsin

Abstract Urban heat islands (UHIs) may increase the likelihood that frost sensitive plants will escape freezing nighttime temperatures in late spring and early fall. Using data from 151 temperature sensors in the Madison, Wisconsin, region during March 2012–October 2016, we found that during time periods when the National Weather Service (NWS) issued freeze warnings (threshold of 0.0°C) or frost advisories (threshold of 2.22°C) were valid, temperatures in Madison’s most densely populated, built-up areas often did not fall below the respective temperature thresholds. Urban locations had a mean minimum temperature of 0.72° and 1.39°C for spring and fall freeze warnings, respectively, compared to −0.52° and −0.53°C for rural locations. On average, 31% of the region’s land area experienced minimum temperatures above the respective temperature thresholds during freeze warnings and frost advisories, and the likelihood of temperatures falling below critical temperature thresholds increased as the distance away from core urban centers increased. The urban–rural temperature differences were greatest in fall compared to spring, and when sensor temperatures did drop below thresholds, the maximum time spent at or below thresholds was highest for rural locations during fall freeze warnings (6.2 h) compared to urban locations (4.8 h). These findings potentially have widely varying implications for the general public and industry. UHIs create localized, positive perturbations to nighttime temperatures that are difficult to account for in forecasts; therefore, freeze warnings and frost advisories may have varying degrees of verification in medium-sized cities like Madison, Wisconsin, that are surrounded by cropland and natural vegetation. Significance Statement The purpose of this study was to understand whether the urban heat island effect in Madison, Wisconsin, creates localized temperature patterns where county-scale frost advisories and freeze warnings may not verify. Approximately one-third of Madison’s urban core area and most densely populated region experienced temperatures that were consistently above critical low temperature thresholds. This is important because gardening and crop management decisions are responsive to the perceived risk of cold temperatures in spring and fall that can damage or kill plants. These results suggest that urban warming presents forecast challenges to the issuance of frost advisories and freeze warnings, supporting the need for improved numerical weather prediction at higher spatial resolution to account for complex urban meteorology.

Modeling the intra-urban nocturnal summertime air temperature fields at a daily basis in a city with complex topography

Detailed knowledge about the intra-urban air temperature variability within a city is crucial for the implementation of adaptation strategies to counteract the negative effects of urban heat stress. Various methods to model urban-rural temperature differences exist, but they often only cover certain periods (heatwave, hot day) or meteorological conditions (sunny and calm) due to computational limitations or limited data availability. Here, we present a land use regression approach to model nocturnal air temperature fields for every single night of the summers 2018 to 2020 in a city with complex terrain (Bern, Switzerland). Furthermore, we investigate the applicability of different model structures and straight-forward computable GIS variables to model cold air drainage, which exerts an important influence on the local-scale climate of cities with complex terrain. The geostatistical models are calibrated with in-situ data of a dense low cost air temperature measurement network and high resolution spatiotemporal (land use and meteorology) data, which are all publicly available. The resulting land use regression models are capable to model and map intra-urban air temperature differences with a good model performance (R2: 0.65–0.71; RMSE: 0.69–0.76 K). Evaluations with data from additional measurement stations and periods (summer 2021) show that the models are able to estimate different meteorological and spatial conditions, but that the representation of small-scale topographic features remains difficult. However, the comparatively low computational and financial effort needed to calculate nocturnal air temperature fields at daily basis enable new applications for cities with restricted resources for various areas of interest, such as urban planning (e.g. effect of heat mitigation policies) or heat risk management (e.g. analyze small-scale urban heat vulnerability).

Blue Green Systems for urban heat mitigation: mechanisms, effectiveness and research directions

Abstract Reflected in the growing body of literature, urban heat mitigation is increasingly relevant as cities experience extreme heat, exacerbated by climate change and rapid urbanisation. Most studies focus on urban–rural temperature differences, known as the Urban Heat Island, which does not provide insight into urban heat dynamics. Here, we synthesise current knowledge on spatio-temporal variations of heat sources and sinks, showing that a targeted and absolute understanding of urban heat dynamics rather than an urban–rural comparison should be encouraged. We discuss mechanisms of heat sinks for microclimate control, provide a clear classification of Blue Green Systems and evaluate current knowledge of their effectiveness in urban heat mitigation. We consider planning and optimisation aspects of Blue Green Infrastructure (greenery and water bodies/features), interactions with hard surfaces and practices that ensure space and water availability. Blue Green Systems can positively affect urban microclimates, especially when strategically planned to achieve synergies. Effectiveness is governed by their dominant cooling mechanisms that show diurnal and seasonal variability and depend upon background climatic conditions and characteristics of surrounding urban areas. Situationally appropriate combination of various types of Blue Green Systems and their connectivity increases heat mitigation potential while providing multiple ecosystem services but requires further research.

Observational evidence of intensified nocturnal urban heat island during heatwaves in European cities

A heatwave (HW) is a large-scale meteorological event characterised by persistent and extremely high-temperature condition. At the local scale, the urban heat island (UHI) is another thermal-related phenomenon defined as an urban area warmer than its surrounding regions due to different surfaces’ capabilities to absorb and store heat. However, the assessment about the effect produced on UHI by HW events is not homogeneous. Indeed, regarding the capability of HWs to influence the urban-rural temperature difference, several studies report different conclusions describing both an exacerbation and a reduction of UHI during HW events. In this context, the present study analyses in situ long records of temperature measurements (20 years) to provide observational shreds of evidence of UHI modification under HW conditions. We examine data from the European Climate Assessment & Dataset and World Meteorological Organization computing the UHI index (UHII) to quantify the UHI effect intensity in 37 European cities during the last 20 summers. The results show an UHII intensification for 28 of the 32 cities affected by positive UHI during extremely high temperatures at night, while substantial variations are not observed during the daytime. The time evolution of UHI during a HW highlights that a more significant and persistent urban-rural temperature gradient explains the UHI intensification. Finally, the relationship between the large and local-scale temperature phenomena reveals that continental high-temperature periods are often associated with prominent temperature differences between small-scale urban and rural environments, assessing the impact of large-scale features on thermal stress at the local scale.

Analysis of urban Heat Island intensity through air mass persistence: A case study of four United States cities

In conjunction with the ongoing rise in global air temperature, there is evidence to suggest that mid-latitude synoptic air masses have changed in frequency and persistence. The research presented here focuses on an analysis of urban heat island (UHI) intensity through the period of synoptic-scale air mass stagnation for four UHI-prone United States cities. It is theorized that the thermal inertia associated with a stagnant air mass conducive to UHI development causes an intensification of the urban-rural temperature difference through time. Results indicate that UHI intensification is responsive to more than just the thermal characteristics of the respective air mass in place. While the magnitude of UHI was found to be smallest under a cool, dry air mass, it generally intensifies with persistence. Conversely, commonly associated with the greatest UHI intensity, a warm, moist air mass exhibits little change in UHI intensity or even a de-intensification with persistence. The warm, moist air masses that are conducive to a stronger UHI appear to be increasing in frequency, partly due to greater persistence. However, somewhat encouraging is that the results here do not show UHI intensification through the period of their persistence.

Driving forces of UHI changes in China's major cities from the perspective of land surface energy balance

As remarkable human-induced temperature anomalies on the land surface, variations of urban heat island (UHI) and its driving factors have been investigated in numerous studies. However, few studies discussed the spatiotemporal heterogeneity of the driving forces exerted by land surface energy fluxes, i.e., net radiation, sensible heat, latent heat and heat storage, on UHI behaviors at large scale and long term. In this study, a comprehensive application of multisource datasets and statistical methods have been implemented based on land surface energy balance theory, the spatiotemporal variations of surface UHI intensity (urban-rural temperature difference) and changes of their driving forces have been quantified. The results demonstrate the dynamics of UHI intensity in 32 major cities of China from 2003 to 2017 are generally coherent with the common perception, the overall surface UHI intensity is 4.57 K higher in summer than in winter. The spatial variations of the fluxes that alter UHI intensity can be largely attributed to the varied energy interactions between vegetated/paved surface and atmosphere and the differences of background temperature and precipitation, the contribution of latent heat to UHI changes declines nearly 40% from semiarid/arid climate at the north to subtropical humid climate at the south, while the contributions of other fluxes are stable. The temporal changes of the effect of these fluxes, however, imply more complex mechanisms. The contributions of sensible heat and latent heat to UHI intensity variations are three times and eight times larger in the warm season than in the cold season respectively, indicating the influence of seasonality of background temperature, precipitation and vegetation. The low contributions of these fluxes in the cold season also suggest the significant effect of other driving forces such as anthropogenic heat, especially in semiarid/semihumid climate zones. This study highlights the temporal shifts of major driving forces of UHI intensity, the mitigation tactics for UHI in different cities and seasons should be customized for better validity.

Global long-term mapping of surface temperature shows intensified intra-city urban heat island extremes

Surface temperatures are generally higher in cities than in rural surroundings. This phenomenon, known as Surface Urban Heat Island (SUHI), increases the risk of heat-related human illnesses and mortality. Past global studies analysed this phenomenon aggregated at city scale or over seasonal and annual time periods, while human impacts strongly depend on shorter term heat stress experienced locally. Here we develop a global long-term high-resolution dataset of daytime SUHI, offering an insight into the space–time variability of the urban–rural temperature differences which is unprecedented at global scale. Our results show that across urban areas worldwide over the period 2003–2020, 3-day SUHI extremes are on average more than twice as high as the warm-season median SUHI, with local exceedances up to 10 K. Over this period, SUHI extremes have increased more rapidly than warm-season medians, and averaged worldwide are now 1.04 K or 31% higher compared to 2003. This can be linked with increasing urbanisation, more frequent heatwaves, and greening of the earth, processes that are all expected to continue in the coming decades. Within many cities there are hotspots where extreme SUHI intensity is 10–15 K higher compared to relatively cooler city parts. Given the limited human adaptability to heat stress, our results advocate for mitigation strategies targeted at reducing SUHI extremes in the most vulnerable and exposed city neighbourhoods.

Enhanced surface urban heat islands due to divergent urban-rural greening trends

Satellite observations show that the surface urban heat island intensity (SUHII) has been increasing over the last two decades. This is often accompanied by an increased urban-rural contrast of vegetation greenness. However, the contribution of uneven vegetation trends in urban and rural areas to the trend of SUHII is unclear, due to the confounding effects of climate change and changes in man-made infrastructures and anthropogenic heat sources. Here we use a data-model fusion approach to quantify such contributions during the peak growing season. We show that the LAIdif (the urban-rural difference of leaf area index) is increasing (P< 0.05) in 189 of the selected 228 global megacities. The increasing trend of LAIdif from 2000 to 2019 accounts for about one quarter of the trend in satellite-derived SUHII, and the impact is particularly evident in places with rapid urbanization and rural cropland intensification. The marginal sensitivity of SUHII to LAIdif is the strongest in hot-humid megacities surrounded by croplands and in hot-dry megacities surrounded by mixed woody and herbaceous vegetation. Our study highlights the role of long-term vegetation trends in modulating the trends of urban-rural temperature differences.

The Multiple-Scale Nature of Urban Heat Island and Its Footprint on Air Quality in Real Urban Environment

The complex interaction between the Urban Heat Island (UHI), local circulation, and air quality requires new methods of analysis. To this end, this study investigates the multiple scale nature of the UHI and its relationship with flow and pollutant dispersion in urban street canyons with and without the presence of vegetation. Two field experimental campaigns, one in summer and one in winter, were carefully designed in two parallel urban street canyons in the city of Bologna (44°29′ N, 11°20′ E; Italy) characterized by a similar orientation with respect to the impinging background flow but with a different aspect ratio and a different presence of vegetation. In addition to standard meteorological variables, the dataset collected included high-resolution flow data at three levels and concentration data of several pollutants. The UHI has been evaluated by combining surface temperature of building facades and ground surfaces acquired during two intensive thermographic campaigns with air temperature from several stations in order to verify the presence of intra-city neighborhood scale UHIs additional to the more classical urban–rural temperature differences. The presence of trees together with the different morphologies was shown to mitigate the UHI intensity of around 40% by comparing its value in the center of the city free of vegetation and the residential area. To capture the multiple-scale nature of UHI development, a simple relationship for the UHI convergence velocity, used as a surrogate for UHI strength, is proposed and used to establish the relationship with pollutant concentrations. The reliability of the proposed relationship has been verified using a Computational Fluid Dynamics (CFD) approach. The existence of a robust relationship between UHI strength and pollutant concentration may indicate that the positive effect of mitigation solutions in improving urban thermal comfort likely will also positively impact on air pollution. These results may be useful for a quick assessment of the pollutant accumulation potential in urban street canyons.

The Urban Heat Island at a Regional University in Kentucky, USA

Constructing buildings, sidewalks, parking lots, and roads inadvertently affects local climate. The best studied example of this, the urban heat island (UHI), manifests as elevated temperatures in developed areas compared to less developed areas nearby. This phenomenon affects many things including plants, wildlife, energy consumption, and human health. We assess the UHI at Eastern Kentucky University (EKU) using simultaneous air temperature observations from two stations. The “urban” station is located on EKU's Richmond campus; the “rural” station is in a non-irrigated pasture 12.9 km away. EKU's heat island follows a typical diurnal pattern, developing during the hours surrounding sunset and dissipating soon after sunrise. Dry air masses with little to no cloud cover and calm winds are favorable for UHI development. Analyzing only nocturnal observations when wind speed was less than 1 m/s, revealed an average urban-rural temperature difference of 3.35°C, though concurrent differences sometimes exceed 10°C. At EKU, the smallest average monthly UHI occurs in February and the largest average monthly UHI occurs in August and September. Strategic tree planting offers an attractive means of mitigating negative impacts on warm season cooling costs and human comfort, while also contributing to campus sustainability goals.

The relationships between urban-rural temperature difference and vegetation in eight cities of the Great Plains

Interpreting the relationship between urban heat island (UHI) and urban vegetation is a basis for understanding the impacts of underlying surfaces on UHI. The calculation of UHI intensity (UHII) requires observations from paired stations in both urban and rural areas. Due to the limited number of paired meteorological stations, many studies have used remotely sensed land surface temperature, but these time-series land surface temperature data are often heavily affected by cloud cover and other factors. These factors, together with the algorithm for inversion of land surface temperature, lead to accuracy problems in detecting the UHII, especially in cities with weak UHII. Based on meteorological observations from the Oklahoma Mesonet, a world-class network, we quantified the UHII and trends in eight cities of the Great Plains, USA, where data from at least one pair of urban and rural meteorological stations were available. We examined the changes and variability in urban temperature, UHII, vegetation condition (as measured by enhanced vegetation index, EVI), and evapotranspiration (ET). We found that both UHI and urban cold islands (UCI) occurred among the eight cities during 2000–2014 (as measured by impervious surface area). Unlike what is generally considered, UHII in only three cities significantly decreased as EVI and ET increased (p<0.1), indicating that the UHI or UCI cannot be completely explained simply from the perspective of the underlying surface. Increased vegetative cover (signaled by EVI) can increase ET, and thereby effectively mitigate the UHI. Each study station clearly showed that the underlying surface or vegetation affects urban-rural temperature, and that these factors should be considered during analysis of the UHI effect over time.

Understanding and Analysing the Urban Heat Island (UHI) Effect in Micro-Scale

The shortage of vegetation cover alongside urban structures and land hardscape in cities causes an artificial temperature increase in urban environments known as the urban heat island (UHI) effect. The artificial heat stress in cities has a particular threat for usability and health-safety of outdoor living in public space. Australia may face a likely 3.8°C increase in surface temperature by 2090. Such an increase in temperature will have a severe impact on regional and local climate systems, natural ecosystems, and human life in cities. This paper aims to determine the patterns of the UHI effect in micro-scale of Adelaide metropolitan area, South Australia. The urban near-surface temperature profile of Adelaide was measured along a linear east-west cross-section of the metropolitan area via mobile traverse method between 26 July 2013 and 15 August 2013. Results indicate that the while the maximum UHI effect occurs at midnight in the central business district (CBD) area in Adelaide, the afternoon urban warmth has more temperature variations (point-to-point variation), especially during the late afternoon when local air temperature is normally in its peak. Thus, critical measurement of heat-health consequences of the UHI effect need to be focused on the afternoon heat stress conditions in UHIs rather than the commonly known night time phenomenon. This mobile traverse urban heat study of Adelaide supports the hypothesis that the UHI effect varies in the built environment during daily cycles and within short distances. Classical UHI measurements are commonly performed during the night – when the urban-rural temperature differences are at their maximum. Thus, they fall short in addressing the issue of excess heat stress on human participants. However, having thermally comfortable urban microclimates is a fundamental characteristic of healthy and vibrant public spaces. Therefore, urban planning professionals and decision makers are required to consider diurnal heat stress alongside nocturnal urban heat islands in planning healthy cities. The results of this article show that the diurnal heat stress varies in the built environment during daily cycles and within short distances. This study confirms that the maximum urban heat stress occurs during late afternoon when both overall temperature and daily urban warmth are at their peak. Literature indicates that diurnal heat stress peaks in hard-landscapes urban settings while it may decrease in urban parklands and near water bodies. Therefore, urban greenery and surface water can assist achieving more liveable and healthy urban environments (generalisation requires further research). A better understanding of daily urban warmth variations in cities assists urban policy making and public life management in the context of climate change.

Spatio -temporal variations in urban heat island and its interaction with heat wave

Most of the urban localities are facing the effects of Urban Heat Island (UHI) and extreme heat wave (HW) events. It is expected that these HW events are likely to be intensified by the effect of UHI in the future. As these events project to increase in both severity and frequency therefore, it is crucial to assess the intensity of UHI and examine the relationship between HW and UHI. In this study, observations for different coastal areas are used to quantify the impacts of UHI during the HW events. The spatial and temporal variability patterns of UHI in the metropolitan city of Karachi were also investigated using hourly temperature observations for a period of 10 years in two phases (a) from 1998 to 2002 (b) from 2012 to 2016. During the first phase (1998–2001), the maximum Urban Heat Island Intensity (UHII) for night time in summer was 1.9 °C, while during the second phase (2012–2016), it increased by 0.6 °C. Despite the fact that both phases have shown similar pattern for seasonal UHII, urban-rural temperature difference was found to be significant in summer especially in the night time. Temporal distribution of UHII for winter shows that average intensity of UHI during daytime varies between 0.1 °C and 3.2 °C, considering the overall time duration. The results indicate that UHII increased significantly during the HW period which caused more than 800 deaths in Karachi between 17th June and 24th June 2015.

Role of City Texture in Urban Heat Islands at Nighttime.

An urban heat island (UHI) is a climate phenomenon that results in an increased air temperature in cities when compared to their rural surroundings. In this Letter, the dependence of an UHI on urban geometry is studied. Multiyear urban-rural temperature differences and building footprints data combined with a heat radiation scaling model are used to demonstrate for more than 50 cities worldwide that city texture-measured by a building distribution function and the sky view factor-explains city-to-city variations in nocturnal UHIs. Our results show a strong correlation between nocturnal UHIs and the city texture.

Daily variation of urban heat island effect and its correlations to urban greenery: A case study of Adelaide

Urban structure and landscape cause an artificial temperature increase in cities, known as the urban heat island effect. The magnitude of such urban–rural temperature difference varies in daily and seasonal basis. Daily patterns of urban heat accumulation in Adelaide is under investigation. In this paper, East–West air temperature profile of Adelaide metropolitan area was mapped in 60 journeys alongside a straight cross route connecting Adelaide Hills to the West Beach under clear sky between 26 July and 15 August 2013. The most intense urban–rural temperature differences of 5.9°C occurred during midnight in Adelaide. However, maximum urban heat variation occurred during the late afternoon when the near-surface urban heat fluctuates by 2°C between the CBD East and Western Parklands. During summer heatwaves, the afternoon heat stress limits public life vibrancy in Adelaide. Increased urban greenery can facilitate resilience to heat by providing shadow and evaporative cooling. A better understanding of daily urban heat variations and the cooling effect of urban greenery assists urban policy making and public life management in the context of climate change.

Patterns of Urban Heat Island Effect in Adelaide: A Mobile Traverse Experiment

Urban structure, hard surfaces and shortage of vegetation cause an artificial temperature increase in cities, known as the urban heat island effect. This paper determines the daily patterns of urban heat in Adelaide, Australia. The near-surface temperature profile of Adelaide was mapped in 60 journeys alongside a straight cross route connecting Adelaide Hills to the West Beach between 26 July and 15 August 2013. Results indicate that the most intense urban-rural temperature differences occurred during midnight in Adelaide. However, the afternoon urban heat had more temperature variation in the urban area. In the late afternoon, the near-surface urban heat fluctuates by 2°C within three kilometres and by 1.2°C in just one kilometer. Afternoon heat stress can vary based on space configurations and urban surface covers. Afternoon heat stress causes the highest heat load on urban dwellers. A better understanding of daily urban heat variations in cities assists urban policy making and public life management in the context of climate change.

Urban-Rural Temperature Differences in Lagos

In this study, the hourly air temperature differences between City hall (urban) and Okoafo (rural) in Lagos, Nigeria, were calculated using one year of meteorological observations, from June 2014 to May 2015. The two sites considered for this work were carefully selected to represent their climate zones. The city core, City hall, is within the Local Climate Zone (LCZ 2) (Compact midrise) while the rural location, Okoafo, falls within LCZ B (Scattered Trees) in the south-western part on the outskirt of the city. This study is one of very few to investigate urban temperature conditions in Lagos, the largest city in Africa and one of the most rapidly urbanizing megacities in the world; findings show that maximum nocturnal UHI magnitudes in Lagos can exceed 7 °C during the dry season, and during the rainy season, wet soils in the rural environment supersede regional wind speed as the dominant control over UHI magnitude.