Maximum Urban Heat Island Intensity Research Articles

Multi-Temporal Analysis of the Impact of Summer Forest Dynamics on Urban Heat Island Effect in Yan’an City

In this study, MODIS land products and China land cover datasets were used to extract normalized difference vegetation index, land surface temperature, and vegetation cover type in Yan’an City during the summers of 2017–2022. On this basis, analysis of spatial change and correlation were carried out as a way to study the mitigation effect on urban heat islands in Yan’an City with forest. The study showed that: (1) The coverage of normalized difference vegetation index over 0.4 in summer in Yan’an City increased from 59.38% to 69.12%, and the vegetation showed good growth conditions. It has a spatial distribution pattern of more in the south and less in the north. (2) The proportion of the urban heat island in Yan’an City increased from 15.51% to 16.86%. Urban heat island intensity fluctuated year by year, with the maximum urban heat island intensity of 6.26 °C appearing in 2019. It has a spatial distribution pattern of less in the south and less in the north. The transition rate of temperature field grade from low to high is 73.32%, and the transition rate to low is only 0.31%. (3) There is a negative correlation between land surface temperature and normalized difference vegetation index in Yan’an City. Vegetation has a mitigating effect on the UHI and the best cooling effect among the vegetation is shown by forest. The cooling effect of forest in Yan’an City is attenuated by an increase in distance, and the effective range is greater than 1000 m. In this study, the regulation effect of forest on the urban heat island was obtained by digging deeper into the intrinsic connection between spatial change in vegetation cover and land surface temperature change in Yan’an City. It provides an important reference for the formulation of meteorological protection policy as well as the promotion of sustainable development of the urban ecological environment and is of guiding significance for future urban planning and ecological construction.

Characteristics of the Urban Heat Island in Dhaka, Bangladesh, and Its Interaction with Heat Waves

This study examines the characteristics of the urban heat island (UHI) in Dhaka, the densely populated capital city of Bangladesh under the influence of the South Asian monsoon, and its interaction with heat waves. For this, meteorological data at Dhaka (urban) and Madaripur (rural) stations and reanalysis data for the period of 1995–2019 are used for analysis. Here, the UHI intensity is defined as the urban-rural difference in 2-m temperature, and a heat wave is defined as the phenomenon which persists for two or more consecutive days with the daily maximum 2-m temperature exceeding its 90th percentile. The UHI intensity in Dhaka is in an increasing trend over the past 25 years (0.21 °C per decade). The average UHI intensity in Dhaka is 0.48 °C. The UHI is strongest in winter (0.95 °C) and weakest in the monsoon season (0.23 °C). In all seasons, the UHI is strongest at 2100 LST. The average daily maximum UHI intensity in Dhaka is 2.15 °C. Through the multiple linear regression analysis, the relative importance of previous-day daily maximum UHI intensity (PER), wind speed, relative humidity (RH), and cloud fraction which affect the daily maximum UHI intensity is examined. In the pre-monsoon season, RH is the most important variable followed by PER. In the monsoon season, RH is the predominantly important variable. In the post-monsoon season and winter, PER is the most important variable followed by RH. The occurrence frequency of heat waves in Dhaka shows a statistically significant increasing trend in the monsoon season (5.8 days per decade). It is found that heat waves in Bangladesh are associated with mid-to-upper tropospheric anticyclonic-flow and high-pressure anomalies in the pre-monsoon season and low-to-mid tropospheric anticyclonic-flow and high-pressure anomalies in the monsoon season. Under heat waves, the UHI intensity is synergistically intensified in both daytime and nighttime (nighttime only) in the pre-monsoon (monsoon) season. The decreases in relative humidity and cloud fraction are favorable for the synergistic UHI-heat wave interaction.

Assessing the urban heat island effect of different local climate zones in Guangzhou, China

The urban heat island (UHI) effect has significant implications on urban development, human health, and climate change. Local climate zones (LCZs) provide an objective and systematic classification of field sites for studying the UHI effect. Accurately characterizing the UHI features in each LCZ is fundamental to mitigating the UHI effect. This study aimed to analyze the UHI effect in six LCZs in Guangzhou. Temperature data were collected simultaneously using fixed-point measurements over 405 days from October 1, 2019 to March 31, 2022. The UHI characteristics of the LCZs under various weather conditions were analyzed by examining the hourly, daily, and seasonal UHI intensities (UHIIs). Consistent diurnal variation patterns were observed in the daily average UHII under different weather conditions but with varying peak values. Ideal days with weak winds and clear skies significantly contribute to the development of maximum UHII, occurring most frequently between 18:00 and 23:00 with a frequency of 45%. In comparison, UHI events on precipitation days have a lower frequency. Furthermore, UHI effects varied significantly among different LCZs, with higher UHII observed in high-density built-up LCZs compared to open low-rise LCZs. Variations were particularly pronounced during the night in autumn and winter with a maximum UHII mean of 5.30 °C. UHI event frequencies and hourly warming/cooling rates were also examined to provide a more comprehensive assessment of the UHI effects on LCZs. This study is of great significance for understanding the UHI characteristics within Guangzhou, and for guiding urban planning and management to mitigate UHI in LCZs.

Application of a Semi-Empirical Approach to Map Maximum Urban Heat Island Intensity in Singapore

Differences in land surface characteristics across a city produce great spatial and temporal variability in air temperature. This fact is particularly pronounced between urban and surrounding rural areas giving rise to the canopy-layer urban heat island (CL-UHI) phenomenon. In the present study, we apply the dimensional analysis technique to develop a simple semi-empirical equation to map daily maximum CL-UHI (UHImax) intensities during nighttime over the city of Singapore for specific weather conditions. By adopting the methodology proposed by Theeuwes et al., but selecting meteorological and morphological parameters that affect UHImax intensity most for Singapore, evaluation of the developed equation shows good agreement with observations (RMSE = 1.13 K and IOA = 0.76). Model performance depends strongly on wind conditions and is best during weak winds when ‘ideal’ conditions for UHI development are approached (RMSE = 0.65 K and IOA = 0.85). Results using the simple equation developed to map UHImax intensities in Singapore under dry weather conditions are comparable to those obtained from more sophisticated numerical models, which demand significant computational resources, and the complex parameterizations involved require expertise to carry out the simulations. The resulting maps of the present study can be used to investigate less favorable thermal conditions and assess population vulnerability to a certain temperature excess, as well as provide insights for urban planning strategies of mitigation measures according to the land cover and morphology of a location.

Analysis of a City's Heat Island Effect on the Micro-Climate Parameters within Cities

The Urban Heat Island (UHI) is a micro-climatic phenomenon that influences the urban areas by elevating its temperature. UHI not only causes the thermal discomfort but also exert serious health issues along with aggravation of urban microclimate. Although a lot of research has been done on this phenomenon but UHI effect on micro scale is still less explored. This paper attempts to make a contribution in UHI studies of micro-climate. It consists of examination of UHI impact on microclimate of Aligarh city areas using mobile traverse method. This study determined the presence and extent of UHI’s microclimate variation within urban communities of different environmental layout and functional uses. The UHI effect started to appear from early afternoon and continue to rise with maximum UHI intensity recorded at early night. The highest recorded UHI intensity was 3.1 °C (at 21:00 hrs.), and the lowest was 0.6 °C (at 09:00 hrs.). A comparison of two districts of the same city located at a distance of 3 km and differing in population density, the number of buildings and landscaping showed that in the L1 area with more dense population and low landscaping, the temperature was consistently higher during the daily period; also in the L1 region had less humidity, which, combined with the already high temperature, makes it difficult to breathe and control the microclimate. These findings can be used for consideration for the future sustainable development of the affected area in regard of thermal comfort, environmental health and urban planning.

Assessing the synergies between heat waves and urban heat islands of different local climate zones in Guangzhou, China

Urban heat island (UHI) effects and heat waves (HWs) increase, posing a threat to human health and urban ecological systems. However, the synergistic mechanisms of UHI and HWs are yet to be fully elucidated. This study aims to assess the characteristics of UHI under HWs in different Local Climate Zones (LCZs) using temperature observations from Guangzhou, China. Fixed-point measurements were employed to simultaneously collect air temperature from nine LCZs in 2021. The results showed a localised interplay between HWs and UHI. During HWs, the UHI effect was significantly amplified in built-type LCZ, where the UHI intensity (UHII) was amplified by 0.1–0.5 °C throughout the day, 0.4–1 °C at night, but slightly reduced by 0–0.4 °C during daytime. The UHII was significantly reduced in land-cover type LCZ, and the urban cold effect was amplified during HWs. Furthermore, with strong solar radiation and low wind speed in HWs, the daily maximum UHII of LCZs increased 0.4–1.1 °C. Finally, correlations between UHII and morphological characteristics of LCZs are examined in HWs and non-heat waves (NHWs). During HWs, the increase in impervious surface fraction (ISF) and building surface fraction (BSF) and the decrease in sky view factor (SVF) exacerbate UHII, particularly at night. The augment in surface vegetation fraction (Fveg), does not significantly contribute to reducing the UHI and is less effective than NHWs at night. Therefore, different measures should be taken in different LCZs to mitigate UHII amplification during HWs. This study can serve as a reference for preventing responses to climate extremes.

Climate Change Trends for the Urban Heat Island Intensities in Two Major Portuguese Cities

Urban Heat Island (UHI) intensities are analyzed for the metropolitan areas of the two major Portuguese cities, Lisbon and Porto, in the period 2008–2017. Projections for the UHI intensity averaged over 2008–2017 and a future period 2021–2050 are calculated under the Representative Concentration Pathway (RCP) 8.5. The spatiotemporal characteristics of the UHI intensity are assessed for daytime, nighttime, and average daily conditions. This analysis is carried out for the winter (Dec-Jan-Feb, DJF) and summer (Jun-Jul-Aug, JJA) meteorological seasons. Maximum UHI intensities of about 3.5 °C were reached in 2008–2017 in both metropolitan areas, but over a wider region during winter nighttime than during summer nighttime. Contrariwise, the most intense urban cool island effect reached −1.5 °C/−1 °C in Lisbon/Porto. These UHI intensities were depicted during summer daytime and in less urbanized areas. Overall, the UHI intensities were stronger during the winter than in the summer for both cities. Results show that the UHI intensity is closely related to underlying surfaces, as the strongest intensities are confined around the most urbanized areas in both cities. Until 2050, under RCP8.5, the highest statistically significant trends are projected for summer daytime, of about 0.25 °C (per year) for Lisbon and 0.3 °C (per year) for the UHI 99th percentile intensities in both metropolitan areas. Conversely, the lowest positive statistically significant trends (0.03 °C/0.02 °C per year) are found for the winter daytime UHI intensities in Lisbon and the winter nighttime and average UHI intensities in Porto, respectively. These statistically significant patterns (at a 5% significance level) are in line with the also statistically significant trends of summer mean and maximum temperatures in Portugal, under RCP8.5 until 2050. Scientists, urban planners, and policymakers face a significant challenge, as the contribution of urbanization and the forcing promoted by global warming should be duly understood to project more sustainable, go-green, carbon-neutral, and heat-resilient cities.

Investigating the Impact of Weather Conditions on Urban Heat Island Development in the Subtropical City of Hong Kong

Subtropical monsoon climates, high-density and heterogeneous urban built environments, as well as coastal–mountainous geographical environments influence the development of urban heat island (UHI) effects in Hong Kong. For better weather control of in situ observations and spatial analysis of UHI effects, it is necessary to quantitatively understand the influence of weather conditions on UHI development in Hong Kong and establish weather-based UHI estimation models. Meteorological records of four urban stations, one rural reference station, and one wind reference station at an hourly interval during the period of 2002–2012 were collected from Hong Kong observatory. A frequency analysis of the mean values of multiple meteorological elements and UHI parameters in urban stations was conducted to examine the prevailing and critical weather conditions, as well as the associated UHI conditions in Hong Kong. Multiple Linear Regression (MLR) was used to estimate the daily maximum UHI intensity (UHImax) based on a set of meteorological elements including cloud amount, wind speed, wind direction, relative humidity, and air temperature, as well as a UHI parameter of the daily maximum UHI intensity of the previous day (UHIpre-max). The results showed that MLR-based models can explain 33% and 56% variations of the UHImax in the summer and the whole year, respectively. The relative importance of each meteorological element on UHI development differed in the summer and annual periods, and the UHImax tended to be intensified under high temperature conditions in the summer.

Applying a diagnostic equation for maximum urban heat island intensity based on local climate zones for Guangzhou, China

The Urban Heat Island (UHI) is a widely studied phenomenon, characterized by unique spatiotemporal variations depending on urban structure. Seeking a simple and rapid method to monitor the Urban Heat Island Intensity (UHII) for local urban area with multiple inner morphology is essential for energy saving, citizen health, and urban planning. Hence, this study proposed a diagnostic equation for daily maximum urban heat island intensity (UHIImax) based on routine meteorological data and basic urban properties. The applicability of equation, previously proposed by European scholars, was evaluated based on Local Climate Zone (LCZ) scheme by a long-term temperature observation experiment conducted in Guangzhou. Overall, the underestimation of UHIImax was caused by LCZ1,2,3,4, in which the morphological parameters were outside the application range of the original equation. Then, a revised equation was proposed by adding the impervious surface fraction (ISF) in morphological parameters based on the spatiotemporal variance of UHII for different LCZ. The revised equation was evaluated against a year dataset and revealed a higher accuracy than the original one with a decrease of RMSE and MEAE at 0.4K, 0.15K, an increase of dr at 0.1. Moreover, the efficiency of the equations for all the seasons and LCZs were elucidated. In summary, the results can be used as a tool for monitoring the development of UHI in outdoor temperature studies.

Comparative Analysis and Mitigation Strategy for the Urban Heat Island Intensity in Bari (Italy) and in Other Six European Cities

The presence of higher air temperatures in the city in comparison with the surrounding rural areas is an alarming phenomenon named the urban heat island (UHI). In the last decade, the scientific community demonstrated the severity of the phenomenon amplified by the combination of heat waves. In southern Italy, the UHI is becoming increasingly serious due to the presence of a warming climate, extensive urbanization and an aging population. In order to extensively investigate such phenomenon in several cities, recent research calibrated quantitative indexes to forecast the maximum UHI intensity in urban districts by exploiting multicriteria approaches and open-source data. This paper proposes different mitigation strategy to mitigate the Urban Heat Island Intensity in Bari. Firstly, the research evaluates the absolute max UHI intensity of the 17 urban districts of Bari (a city in southern Italy, Puglia) by exploiting the recent index-based approach IUHII. Secondly, a comparative evaluation of seven European cities (Bari, Alicante, Madrid, Paris, Berlin, Milan and London) is achieved to point out the positives and negative aspects of the different urban districts. In total, the comparison required the analysis of 344 districts of 7 European cities: 17 districts in Bari (Italia); 9 districts in Alicante (Spain); 21 in Madrid (Spain); 80 in Paris (France); 96 in Berlin (Germany); 88 in Milan (Italy) and 33 in London (UK). Finally, the results emphasize some virtuous examples of UHII mitigation in the major European cities useful to draw inspiration for effective mitigation strategies suitable for the urban context of Bari.

A novel risk-based design framework for urban heat island: A case study of Kempten, Germany

Studies on the urban heat island (UHI) effect have increased over the past decades, mainly focusing on topics such as thermal comfort, building energy, and sensitivity studies. However, there is currently a research gap in the development of risk-based design criteria for UHI. This paper proposes a novel risk-based UHI design criteria using heat-related mortality risk. The design criteria was developed based on the annual hottest seven-day mean temperatures. Frequency-consequence curves (or F–N curves) were used to quantify tolerable levels of societal risk. Exposure-response relationships for temperature and mortality for southern Germany were also used to determine the heat-related mortality rate. The heat-related mortality rate was used with the F–N curves to obtain a maximum allowable UHI intensity (UHII) for several risk scenarios. This allowable UHII was compared to the actual 50-year UHII for a residential district in Kempten, Germany. The Urban Weather Generator was used to model the UHII. If the actual UHII did not exceed the allowable UHII, the analyzed area was considered adequate. The 50-year UHII of the study area was 0.17 °C. The calculated allowable UHII ranged from 0.3 °C–13.2 °C. Therefore, the study area was adequate for all risk scenarios that were considered. This research lays the foundation for decision-makers and urban planners to incorporate more precise design targets in a number of applications from planning new developments to mitigation of UHI in existing urban areas.

Climate driven trends in London's urban heat island intensity reconstructed over 70 years using a generalized additive model

Long-term urban heat island (UHI) observations are uncommon and where available, are generally unable to distinguish changing climate drivers from urban expansion; neither driver is treated independently. We overcome this limitation using a generalized additive model to learn the variability in UHI intensity (UHII) at a central London weather station (St James's Park) over a 10-year observation period (2010–2019). We then use the model to reconstruct 70 years (1950–2019) of monthly night-time UHII variability using ERA5 reanalysis data both as a reference in UHII calculation and for the predictors. We find considerable variability both seasonally and annually within the UHII time series (monthly mean maximum UHIIs are 1.4–2.9 °C). Applying extreme value analysis to the time series we show that monthly mean maximum UHIIs are likely to exceed 2.75 °C once every 11 years. Considering that most studies observe or model UHIIs for less than a year, they will likely misrepresent this UHII variability. Nevertheless, despite moving to a warmer background climate, London's UHII has not significantly changed across the period of analysis (1950–2019). The data-driven methods we create in this study are easily transferable to other cities.

Evaluation of Absolute Maximum Urban Heat Island Intensity Based on a Simplified Remote Sensing Approach

The Urban Heat Island (UHI) phenomenon can be harmful during the summer season jeopardizing the safety of some vulnerable population classes. Typically, the study of the UHI requires long data acqu...

A Method for Selecting the Typical Days with Full Urban Heat Island Development in Hot and Humid Area, Case Study in Guangzhou, China

The urban heat island (UHI) poses a significant threat to urban ecosystems, human health, and urban energy systems. Hence, days with a relatively higher UHI intensity should be selected for UHI observation and analysis. However, there is still a lack in the method and criteria for selecting the typical meteorological days for UHI survey and simulation. In this study, field measurements were conducted based on Local Climate Zone (LCZ) schemes over a one-year period to assess the UHI behavior in Guangzhou, China. The relationship between the diurnal temperature range (DTR) and UHI intensity was evaluated and analyzed quantitatively under different meteorological conditions classified by precipitation. The average daily maximum UHI intensity (UHIImax) during precipitation days was approximately 1.8 °C lower than that during non-precipitation days, confirming that precipitation has a negative effect on UHI development. The monthly DTR distribution was similar to the daily UHIImax distribution, which was higher in autumn and winter, but lower in spring and summer. DTR has a significant linear correlation with the daily UHIImax, with a Pearson’s correlation coefficient of >0.7 and statistical significance of <0.001. Based on a quantitative evaluation of our results, we determined that 10 °C could be regarded as the appropriate DTR threshold to identify the meteorological conditions conducive to UHI development; the meteorological conditions exhibited a high daily UHIImax in Guangzhou. This study provides a simple method to select typical meteorological days for UHI measurement and simulation, and a method to early-warning of intense UHI events based on weather forecasts.

Is Urban Heat Island intensity higher during hot spells and heat waves (Dijon, France, 2014–2019)?

The Urban Heat Island (UHI) phenomenon is frequently associated with heat waves, both in scientific literature and in the media. Health problems and other issues often result from the co-occurrence of these two phenomena. Previous studies have not yet provided sufficient evidence to validate potential links between UHIs and heat waves. The MUSTARDijon network was set up in 2014, in Dijon, France. Its spatial density (60 sensors) and temporal depth (6 summers) provide information about several Hot Spells and Heat Waves (HS&HW), as well as the daily intensity of UHIs. For the period from June to August (the warmer months), no statistical relationship could be established between temperature and UHI intensity. The UHI phenomenon is strong when days are sunny and not very windy; these two conditions are frequently met during HS&HW, but not systematically. By contrast, these conditions can be fulfilled even without high temperatures. Strong UHIs can thus develop outside Hot Spell/Heat Wave (HS/HW) events. These HS&HW are not necessarily in phase with UHIs: maximum UHI intensity tends to occur before the onset or during the first few days of HS&HW. The intensity of the UHI decreases during HS&HW because nocturnal urban temperature generally remains stationary, whereas rural temperature tends to increase at night. The hypothesis proposed is that this increase in rural night temperature during HS&HW could be linked to the decrease in Actual Evapotranspiration (ETa) and soil wetness.

Development of a holistic urban heat island evaluation methodology

Urban Heat Island (UHI) phenomenon concerns the development of higher ambient temperatures in urban districts compared to the surrounding rural areas. Several studies investigated the influence of individual parameters in the UHI phenomenon, on the other hand, an exhaustive study that quantifies the influence of each parameter in the resulting UHI is missing in the related literature. This paper proposes a new index aimed at quantifying the hazard of the absolute maximum UHI intensity in urban districts during the Summer season by taking all the parameters influencing the phenomenon into account. In addition, for the first time, the influence of each parameter has been quantified. City albedo and the presence of greenery represent the most important characteristics with an influence of 29% and 21%. Population density, width of streets, canyon orientation and building height has a medium influence of 12%, 10%, 9% and 8% respectively. The remaining parameters have an overall influence of 11%. These results are achieved by exploiting three synergistically related techniques: the Analytic Hierarchy Processes to analyse the parameters involved in the UHI phenomenon; a state-of-the-art technique to acquire a large set of data; and an optimization procedure involving a involving a Jackknife resampling approach to calibrate the index by exploiting the effective UHI intensity measured in a total of 41 urban districts and 35 European Cities.

Analysis of Urban Morphological Effect on the Microclimate of the Urban Residential Area of Kampung Baru in Kuala Lumpur Using a Geospatial Approach

As a Malay Agricultural Settlement established in 1900, Kampung Baru which is located in Kuala Lumpur, has become a subject of prolonged national interests in terms of economic, social, environment, and political issues along with the pressure of modern and future development. This study investigated the urban morphological impact of Kampung Baru on the intensity of urban heat island (UHI) by developing a smart geodatabase for urban climatic mapping. The database provided baseline data which was crucial to unveil the spatiotemporal characteristics of UHI in Kampung Baru. Determination of the urban heat island intensity (UHII) in Kampung Baru was carried out through two approaches, mobile and fixed measurements. In a period of six days, the mobile measurement was conducted within the target area at night using a motorcycle equipped with the temperature and relative humidity data logger while the fixed measurement was conducted using the similar equipment installed at a school building in the area. Building height data were also collected while building footprints were digitized using a topographical map and the satellite image was used as the base map. To estimate the UHII, the reference data for rural temperature was obtained from the Malaysian Meteorological Department (MMD). All of the data were analyzed using ArcGIS to portray the temperature pattern in the study area. The analysis revealed the presence of UHI effect in Kampung Baru at the average building height of six to ten metres. The results of the fixed measurement showed an island-like local maximum in the study area with the average and maximum UHII values of 4.4 °C and 6.0 °C, respectively. The results from the mobile measurement also showed that the highest temperature was recorded in Kampung Baru rather than in the surrounding areas of different land-use types throughout the observation days. The spatial temperature distribution in the study area also showed that the most affected part was the south-west of Kampung Baru which is surrounded by tall buildings. The findings of this study could be utilized in the planning of new development in the city of Kuala Lumpur.

Sensitivity Study of Weather Research and Forecasting Physical Schemes and Evaluation of Cool Coating Effects in Singapore by Weather Research and Forecasting Coupled with Urban Canopy Model Simulations

AbstractMesoscale meteorological modeling was conducted to evaluate air temperature at 2‐m above surface (T2), wind speed/direction, and relative humidity (RH) in Singapore, a tropical city, for a dry period. A sensitivity study was conducted to determine the best combination of schemes for the physical modules. The model was used to study the urban heat island (UHI) effect and urban cooling effect by applying cool coating on various urban surfaces. Maximum UHI intensity of 3.2°C is found at nighttime (21:00) at a hot spot in the Commercial/Industrial area. At nighttime, when the UHI effect is generally more intense than daytime, applying cool coating on all urban surfaces can reduce the UHI effect by about 30% in residential areas and about 6% in commercial/industrial areas. Maximum T2 reduction of 3.1°C and surface skin temperature (TSK) reduction of 9.8°C due to cool coating is found at 13:00 at certain locations. The cool urban surfaces reduce radiative heat absorption during daytime, reducing heat storage in urban structures. This leads to subsequent reduction of stored heat release from urban structures, mitigating UHI effect during nighttime. Applying cool coating on horizontal surfaces (roofs and roads) provides more cooling effect than vertical surfaces (walls). Cool roofs provide more cooling effect than cool roads since roofs cover more urban horizontal surfaces than roads do in the current setting. Part of the radiation reflected by cool roads could be absorbed by other urban structures, reducing its cooling effect as compared to cool roofs.

Statistical prediction of the nocturnal urban heat island intensity based on urban morphology and geographical factors - An investigation based on numerical model results for a large ensemble of French cities

Taking into account meteorological data in urban planning increases in relevance in the context of changing climate and enhanced urbanisation. The present article focusses on the nocturnal urban heat island intensity (UHII) simulated with a physically based atmospheric model for >200,000 Reference Spatial Units (RSU), which correspond to building patches delimited by roads or water bodies in 42 French urban agglomerations. First are investigated the statistical relationships between the UHII and six predictors: Local Climate Zone, distance to the agglomeration centre, population, distance to the coast, climatic region, and elevation differences. It is found that the maximum UHII of an agglomeration increases proportional to the logarithm of its population, decreases for cities closer than 10 km to the coast, and is shaped by the regional climate. Secondly, a Random Forest model and a regression-based model are developed to predict the UHII based on the predictors. The advantage of the regression-based model is that it is easier to understand than the black box Random Forest model. The Random Forest model is able to predict the UHII with <0.5 K absolute error for 54% of the RSU. The regression-based model performs slightly worse than the Random Forest model and predicts the UHII with <0.5 K absolute error for 52% of the RSU. A future challenge is to conduct a similar investigation at global scale, which is to date limited by the availability of a robust description of urban form and functioning.

Quantitative methods for identifying meteorological conditions conducive to the development of urban heat islands

Meteorological conditions significantly influence the development of urban heat islands (UHIs); hence, a reliable assessment and understanding of UHIs depends primarily on the days selected for observation and analysis. Numerous studies were conducted on the characteristics and causes of UHIs; however, few studies focused on the methods and criteria for identifying meteorological conditions conducive to UHI development. The objective of this study is to investigate the performances of four quantitative methods for identifying meteorological conditions conducive to UHI development based on three years of observations in Nanjing, China. The methods include the widely used method based on cloud cover and wind speed and three methods that combine the effects of multiple meteorological variables on UHIs into a single indicator. Correlations analysis between the daily maximum urban heat island intensity (UHIImax) and the meteorological variables indicates that it is inadequate to identify meteorological conditions conducive to UHI development using a single variable, such as solar radiation, cloud cover, or wind speed. The correlations between the daily UHIImax and the indicators are significant (r > 0.60, P < 0.001). The observations are split into calibration and validation sets. Then, the performances of the four methods are evaluated, and the appropriate thresholds for identifying meteorological conditions conducive to UHI development in Nanjing are determined. The results demonstrate that all four methods can be used for identifying meteorological conditions conducive to UHI development in Nanjing. The features and limitations of the four methods and the potential applications are discussed.