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Urban climate studies often overlook the study of nighttime urban heat island (UHI) at high spatial resolutions, such as those provided by Landsat. Previous research has primarily focused on daytime and nighttime UHI at coarser spatial resolutions, such as those offered by MODIS. Furthermore, there is a lack of studies that compare two Landsat night images over a period to assess temporal changes, which has not been comprehensively explored. In this study, the Global Artificial Impervious Area dataset was utilized to define urban, while Landsat-5 & 8 daytime and nighttime data (1988, 2015) were employed to classify land cover and extract nighttime land surface temperature (LST). Statistically significant hotspot analysis was applied to quantify the UHI. The findings revealed a 94% increase in urban cover and a 1.8% decrease in vegetation cover between 1988 and 2015. This urban expansion contributed to an average increase of 10 °C in LST across Greater Cairo. The analysis further indicated that every 42.7 km2 increase in urban cover corresponds to a 1 °C rise in LST. Streets and industrial areas exhibited the highest LST readings, while compact buildings, especially older structures, recorded higher surface LSTs compared to open buildings with diverse architectural designs, which experienced lower LST values. Hotspot analysis identified an increase in UHI intensity, with a rise from 2.5 °C in 1988 to 2.7 °C in 2015. These findings highlight the critical need for sustainable urban planning and climate-responsive policies to mitigate the adverse effects of urbanization on thermal environments. This study provides a foundation for future research and emphasizes the importance of using high-resolution nighttime thermal imagery for UHI assessments in cities worldwide. [ABSTRACT FROM AUTHOR]

The Covid-19 outbreak rapidly became a global pandemic in December 2019, spreading through droplets, direct contact, and possibly airborne transmission. Southeast Asian nations like Malaysia and Indonesia experienced delayed outbreaks but saw a surge in cases. Analysing Covid-19 spatial patterns, especially concerning temperature and humidity, provides valuable insights. Utilizing remote sensing, allows studying the correlation between temperature conditions and Covid-19 outbreak patterns. This study focuses on investigating the impact of urban heat islands (UHIs) on Covid-19 outbreaks in Jakarta and Greater Kuala Lumpur, given their significant caseloads in Indonesia and Malaysia, respectively. The research integrates remote sensing, secondary data, and statistical analysis methods. Remote sensing was used to acquire land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI). The analysis revealed that industrial and commercial areas were hotter than others during normal times, but during the pandemic, LST and UHI shifted from industrial to settlement areas due to large-scale social restrictions. This shift corresponded with the cessation of office, tourism, and industrial activities during lockdowns in March and July 2020 in Jakarta and Greater Kuala Lumpur, respectively. The concentration of people shifted from central business and industrial areas to residential areas during lockdowns, resulting in changes in UHI patterns. [ABSTRACT FROM AUTHOR]

Previous research has found higher temperature trends at urban observatories. This study examines in depth the features of the urban environment, the thermal behaviour of land use and land cover, and the changes that have taken place in five urban areas of the Spanish Mediterranean. The CORINE Land Cover database was used to delimit the primary land use land cover (LULC) and its changes between 1990 and 2018. Once this had been established, land surface temperatures (LSTs) between 1985 and 2023 were retrieved from the Landsat database available on the Climate Engine website. There has been a significant advance in artificial land uses, which have become the main uses in the urban areas in Valencia and Alicante. An analysis of the primary land cover showed the greatest thermal increase in artificial surfaces, especially in the industrial, commercial, and transport units that are common on their outskirts, without exception in any urban area. The results are less clear for urban fabrics and agricultural areas due to their diversity and complexity. The density of vegetation is a key factor in the magnitude of the UHI, which is higher in the urban areas with more vegetated agriculture areas, therefore showing lower LST than both industrial units and urban fabrics. Another important conclusion is the role of breezes in limiting or eliminating the strength of the UHI. Sea breezes help to explain the monthly variation of UHIs. Both bodies of water and areas of dense tree vegetation provided the lowest LST, a fact of special interest for mitigating the effects of heat waves in increasingly large urban areas. This study also concludes the different effect of each LULC on the temperatures recorded by urban observatories and enables better decision-making when setting up weather stations for a more detailed time study of the urban heat island (UHI). [ABSTRACT FROM AUTHOR]

India is one of the rapidly urbanizing major economies in the developing world. As it embarks on its urban transition, many small tier-2 cities are already experiencing a large-scale transformation. This study examines the effects of surface urban heat island intensity (SUHI) effect from 2001 to 2020 on a tropical coastal urban complex, Bhubaneswar and Cuttack, a rapidly expanding tier-2 twin city in the Eastern Indian region. Our study reveals a clear discernible annual nighttime SUHI for both Bhubaneswar and Cuttack (0.75 ± 0.08 and 1.22 ± 0.07 °C) with a growth rate of 0.18 ± 0.07 and 0.13 ± 0.07 °C/decade, respectively. Surprisingly, the annual daytime SUHI is weakening for Bhubaneswar. Both night and daytime SUHI showed substantial seasonality with a clear asymmetry during the day and night. Daytime urban cool island effect was observed for Cuttack with Bhubaneswar reporting weak SUHI for daytime during dry seasons. Around the periphery of the cities, the diurnal temperature range (DTR) was found to be the highest. Furthermore, A decrease of 2 °C in the DTR has been reported over the past two decades. The urbanization effect on the local thermal climate of both cities is seen beyond the physical urban limits. Such changes, even in tier-2 cities, have significant potential to modulate local climate and underscore the need for detailed studies in the rapidly urbanizing cities of India and the world to enable disaster resilience, climate-proofing, and sustainability. [ABSTRACT FROM AUTHOR]

This work presents a high‐resolution spatiotemporal analysis of the urban heat island (UHI) effect in Swiss cities during the last 6 years. The entire alpine country is simulated at once using the COSMO model at 1.1 km resolution, validated against a dense national measurement network. Additionally, the bulk parametrisation TERRA URB is used to model the dynamical and thermal effects of urban areas. The resulting data allows us to perform the first comprehensive analysis over the entire Switzerland, with a focus on the UHI effect with intra‐urban and across cities comparisons, and to report on the current state of urban warming. Despite the medium‐small size of the cities, the UHI is of considerable magnitude especially when considering peak values in ideal weather conditions. The present results confirm previous analyses performed for individual cities, and shed new light on the country‐wide picture by highlighting features such as the marked seasonality of the UHI intensity as well as the influence of local climate and topographical features on the urban climate. A thorough discussion is also presented highlighting the absence of simple relationships between UHI intensity and bulk city parameters and weather patterns. [ABSTRACT FROM AUTHOR]

Previous research has found higher temperature trends at urban observatories. This study examines in depth the features of the urban environment, the thermal behaviour of land use and land cover, and the changes that have taken place in five urban areas of the Spanish Mediterranean. The CORINE Land Cover database was used to delimit the primary land use land cover (LULC) and its changes between 1990 and 2018. Once this had been established, land surface temperatures (LSTs) between 1985 and 2023 were retrieved from the Landsat database available on the Climate Engine website. There has been a significant advance in artificial land uses, which have become the main uses in the urban areas in Valencia and Alicante. An analysis of the primary land cover showed the greatest thermal increase in artificial surfaces, especially in the industrial, commercial, and transport units that are common on their outskirts, without exception in any urban area. The results are less clear for urban fabrics and agricultural areas due to their diversity and complexity. The density of vegetation is a key factor in the magnitude of the UHI, which is higher in the urban areas with more vegetated agriculture areas, therefore showing lower LST than both industrial units and urban fabrics. Another important conclusion is the role of breezes in limiting or eliminating the strength of the UHI. Sea breezes help to explain the monthly variation of UHIs. Both bodies of water and areas of dense tree vegetation provided the lowest LST, a fact of special interest for mitigating the effects of heat waves in increasingly large urban areas. This study also concludes the different effect of each LULC on the temperatures recorded by urban observatories and enables better decision-making when setting up weather stations for a more detailed time study of the urban heat island (UHI).

Climate change elevates the rate of emergence of urban heat islands (UHIs), especially in the tropics. UHIs severely affect human comfort and health. Many studies have suggested that urban areas should be properly mitigated or planned. To cope with this, it is best to present the issue using easy-to-understand approaches to allow for better decision-making, especially during urban planning. Based on the information, adaptations and mitigation strategies can be suggested in order to reduce the impact. Hence, this research was aimed at determining the heat vulnerability index (HVI) of urban areas. This study was conducted in Malaysia in the Klang Valley, a tropical city with a complex urban morphology. Remote sensing techniques were employed to extract and derive the spatial index values for exposure, sensitivity, and adaptive capacity. A principal component analysis (PCA) was used to estimate the vulnerability as well as to generate the HVI. The most vulnerable districts were found to be Petaling (1.00), Kuala Lumpur (0.99), and Putrajaya (0.95). Kuala Lumpur had a level of exposure that was high (0.56), a level of sensitivity that was high (0.84), and capacity to adapt that was low (0.54), while Petaling had a high exposure value (0.56), very high sensitivity (1), and high adaptive capacity (0.72). A Pearson's correlation (r) test also revealed that the variables used were highly correlated. From the preliminary findings, the vulnerability of the population to high temperatures in the Klang Valley can be identified to help develop adaptative plans that are targeted as a response to rapid warming in the future in Malaysia. [ABSTRACT FROM AUTHOR]

Although the urban heat island (UHI) phenomenon is more commonly studied in summer, its influence is also important in winter. In this study, the authors focused on the winter UHI in Ljubljana (Slovenia) and its impact on the urban population, as well as in comparison with a UHI study from 2000. Through a combination of mobile and stationary temperature measurements in different parts of the city, the winter intensity of the UHI in Ljubljana was studied in a dense spatial network of measurements. It was found that the intensity of the winter UHI in Ljubljana decreases as winters become warmer and less snowy. The results showed that the winter UHI in Ljubljana intensifies during the night and reaches the greatest intensity at sunrise. During the winter radiation type of weather, the warmest part of Ljubljana reaches an intensity of 3.5 °C in the evening. In total, 22% of the urban area is in the evening UHI intensity range of 2–4 °C, and 65% of the urban population lives in this range. In the morning, the UHI in Ljubljana has a maximum intensity of 5 °C. The area of >4 °C UHI intensity covers 7% of the urban area, and 28% of the total urban population lives in this area. Higher temperatures in urban centers in winter lead to a longer growing season, fewer snow cover days, lower energy consumption and cold stress, and lower mortality from cold-related diseases compared to the colder periphery.

Although the urban heat island (UHI) phenomenon is more commonly studied in summer, its influence is also important in winter. In this study, the authors focused on the winter UHI in Ljubljana (Slovenia) and its impact on the urban population, as well as in comparison with a UHI study from 2000. Through a combination of mobile and stationary temperature measurements in different parts of the city, the winter intensity of the UHI in Ljubljana was studied in a dense spatial network of measurements. It was found that the intensity of the winter UHI in Ljubljana decreases as winters become warmer and less snowy. The results showed that the winter UHI in Ljubljana intensifies during the night and reaches the greatest intensity at sunrise. During the winter radiation type of weather, the warmest part of Ljubljana reaches an intensity of 3.5 °C in the evening. In total, 22% of the urban area is in the evening UHI intensity range of 2–4 °C, and 65% of the urban population lives in this range. In the morning, the UHI in Ljubljana has a maximum intensity of 5 °C. The area of >4 °C UHI intensity covers 7% of the urban area, and 28% of the total urban population lives in this area. Higher temperatures in urban centers in winter lead to a longer growing season, fewer snow cover days, lower energy consumption and cold stress, and lower mortality from cold-related diseases compared to the colder periphery. [ABSTRACT FROM AUTHOR]

The present study is based on remote sensing techniques focusing on Land Surface Temperature (LST) and Normalized Difference Vegetation Index (NDVI) to investigate their influence on land use and land cover dynamics, and the assessment of the Urban Heat Island (UHI) effect in Delhi, India. The objective of this study is to calculate LST, NDVI, and UHI values to understand the changes in LULC patterns, urbanization, and temperature increase within the city. Unlike previous studies conducted with Landsat-8, the present study employs Landsat-9 data, ensuring a higher level of authenticity in the results. Landsat-9, equipped with state-of-the-art sensors and instrumentation, provides superior data quality, enhanced image resolution, and advanced capabilities for precise monitoring and analysis. The methodology encompasses six steps for LST retrieval, enabling the calculation of UHI values and intensity. Ground data from 32 meteorological stations validate the LST results. Pearson correlation coefficients between LST and NDVI exhibit correlations ranging from −0.58 to −0.68 for three dates. On Dec 8, 2023, there is a weak negative correlation of −0.004. The analysis of changing land cover with variation in NDVI and LST unveils a diverse landscape, primarily characterised by green cover (47.34%), followed by built-up area (44.57%), barren land (7.57%), and water (0.52%). The study identifies the minimum value of UHI intensity for Delhi to be 8.13 °C on 26-Feb 2023 and the maximum value of UHI was estimated 10.29 °C on 2-June 2023. The study of Urban Heat Island (UHI) patterns revealed distinctive seasonal trends. The urban areas exhibited relatively cooler temperatures compared to surrounding rural regions on Dec 8, 2023. The conclusion drawn from this comprehensive analysis is that rapid urbanization in Delhi has significantly contributed to the increase in LST and UHI values. This rise can largely be attributed to the extensive use of concrete in construction activities, which exacerbates the UHI effect. Moreover, this analysis signifies the dynamic nature of UHI and emphasizes the urgency for strategic urban planning and climate-sensitive design approaches. Implementing such measures can create more sustainable and resilient urban environments. • Landsat-9 provides superior data quality and enhanced image resolution for precise monitoring and analysis. • The analysis of changing land cover with variation in NDVI and LST unveils a diverse landscape characterized by green cover. • The study identifies the min and max values of UHI for Delhi to be 8.13 °C on 26-Feb 2023 and 10.29 °C on 2-June 2023. • The study of Urban Heat Island (UHI) patterns revealed distinctive seasonal trends. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect is a serious health risk for people living in cities and thus calls for effective mitigation strategies in urban areas. Satellite data enable monitoring of the surface urban heat island (SUHI) over large areas at high spatial resolution. Here we analysed SUHI in the city of Stuttgart (Germany) based on land surface temperature (LST) data from Landsat at 30 m resolution. The overall SUHI in Stuttgart decreased by 1.4 °C between the investigated time periods 2004–2008 and 2016–2020, while the absolute LST increased by 2.5 °C. We identified local hotspots of strong warming and cooling in Stuttgart through the change in SUHI and categorised them based on the predominant land cover change occurring at the hotspot using the Normalised Difference Vegetation Index (NDVI) from Landsat as well as visual information on land cover changes from Google Earth Pro. The establishment of green roofs, as well as albedo changes, are predominantly responsible for cooling spots, while warming spots are mostly associated with the sealing of surfaces. This highlights that vegetation has a dominant influence on SUHI development in Stuttgart. Combining satellite-based LST data with visual information thus provides an effective method to identify local warming and cooling hotspots, which allows monitoring of the success of city policies against heat stress and guides future policy. [ABSTRACT FROM AUTHOR]

This study compares three popular approaches to quantify the urban heat island (UHI) effect in Moscow megacity in a summer season (June-August 2015). The first approach uses the measurements of the near-surface air temperature obtained from weather stations, the second is based on remote sensing from thermal imagery of MODIS satellites, and the third is based on the numerical simulations with the mesoscale atmospheric model COSMO-CLM coupled with the urban canopy scheme TERRA_URB. The first approach allows studying the canopy-layer UHI (CLUHI, or anomaly of a near- surface air temperature), while the second allows studying the surface UHI (SUHI, or anomaly of a land surface temperature), and both types of the UHI could be simulated by the atmospheric model. These approaches were compared in the daytime, evening and nighttime conditions. The results of the study highlight a substantial difference between the SUHI and CLUHI in terms of the diurnal variation and spatial structure. The strongest differences are found at the daytime, at which the SUHI reaches the maximal intensity (up to 10°С) whereas the CLUHI reaches the minimum intensity (1.5°С). However, there is a stronger consistency between CLUHU and SUHI at night, when their intensities converge to 5–6°С. In addition, the nighttime CLUHI and SUHI have similar monocentric spatial structure with a temperature maximum in the city center. The presented findings should be taken into account when interpreting and comparing the results of UHI studies, based on the different approaches. The mesoscale model reproduces the CLUHI-SUHI relationships and provides good agreement with in situ observations on the CLUHI spatiotemporal variations (with near-zero biases for daytime and nighttime CLUHI intensity and correlation coefficients more than 0.8 for CLUHI spatial patterns). However, the agreement of the simulated SUHI with the remote sensing data is lower than agreement of the simulated CLUHI with in situ measurements. Specifically, the model tends to overestimate the daytime SUHI intensity. These results indicate a need for further in-depth investigation of the model behavior and SUHI–CLUHI relationships in general.

Calculation of the cooling production costs of façade‐bound greening systems in urban areas. This paper presents a new method for the economic valuation of a building's greenery. Based on already published economic analyses, this article refers to a calculation method which has not been considered in this area up to now and which is currently mostly used in the energy industry. In this method the production costs are determined. For the first time, the cooling production costs of a south‐facing green façade are calculated. Three independent parameters affect these cooling production costs: the evaporation capacity of the green façade, the total costs for the green system and the number of summer days. Accordingly, the type of construction, the planting, the life cycle costs and the location of the façade greening, among other things, influence the height of the cooling production costs. The result of these example calculations for Vienna shows that such cooling of the environment costs 0.80 €/kWh extracted heat energy. This type of cooling can counteract the Urban Heat Island effect. [ABSTRACT FROM AUTHOR]

The increase in built surfaces constitutes the main reason for the formation of the Urban Heat Island (UHI), that is a metropolitan area significantly warmer than its surrounding rural areas. The urban heat islands and other urban-induced climate feedbacks may amplify heat stress and urban flooding under climate change and therefore to predict them correctly has become essential. Currently in the COSMO model, cities are represented by natural land surfaces with an increased surface roughness length and a reduced vegetation cover, but this approach is unable to correctly reproduce the UHI effect. By increasing the model resolution, a representation of the main physical processes that characterize the urban local meteorology should be addressed, in order to better forecast temperature, moisture and precipitation in urban environments. Within the COSMO Consortium a bulk parameterization scheme (TERRA_URB or TU) has been developed. It parametrizes the effects of buildings, streets and other man-made impervious surfaces on energy, moist and momentum exchanges between the surface and atmosphere, and additionally accounts for the anthropogenic heat flux as a heat source from the surface to the atmosphere. TU implements an impervious water-storage parameterization, and the Semi-empirical Urban canopy parametrization (SURY) that translates 3D urban canopy into bulk parameters. This paper presents evaluation results of the TU scheme in high-resolution simulations with a recent COSMO model version for selected European cities, namely Turin, Naples and Moscow. The key conclusion of the work is that the TU scheme in the COSMO model reasonably reproduces UHI effect and improves air temperature forecasts for all the investigated urban areas, despite each city has very different morphological characteristics. Our results highlight potential benefits of a new turbulence scheme and the representation of skin-layer temperature (for vegetation) in the model performance. Our model framework provides perspectives for enhancing urban climate modelling, although further investigations in improving model parametrizations, calibration and the use of more realistic urban canopy parameters are needed.

Four years of summertime paired urban‐rural meteorological and radon observations in central Poland are used to assess the relationship between atmospheric stability and urban‐induced changes to the radiation balance and surface energy budget. An existing radon‐based technique for nocturnal stability classification is improved and extended to also infer daytime mixing conditions. The radon‐based scheme is shown to provide a simple, effective, objective means of investigating urban energy budget closure over a range of meteorological conditions, which promises to improve estimates of energy storage and loss terms associated with urban canopies. Special attention is paid to quantifying atmospheric characteristics associated with the arbitrarily assigned radon‐derived stability categories in terms of the more conventional measures: bulk Richardson number and the Monin‐Obukhov stability parameter (z/L). The bulk Richardson number approach is demonstrated to be less effective at grouping periods of similar mean stability, and less selective of extremely stable conditions, than the radon‐based technique. A simple box model is used in conjunction with radon observations and an assumed source function of 15 mBq·m−2·s−1, to show that nocturnal effective mixing heights were deeper and less variable over the urban region. On stable nights hourly median effective mixing heights were 15–20 m over the rural region compared to 40–45 m over the urban region. Plain Language Summary: Since the global population is rising, and more people are living in cities, we need a better understanding of how cities are changing their climate and air quality to guide more efficient and sustainable urban planning. The way in which a city exchanges heat, water, and pollution with the surrounding atmosphere depends very much on prevailing weather conditions (e.g., wind, cloudiness, and rainfall) and their controls of atmospheric mixing. Separating weather‐related from design‐related influences on how the urban surface absorbs and redistributes energy is key to developing mitigation measures and improving urban canopy modeling. Until now, understanding weather‐related controls on atmospheric mixing has required complex analyses of many and varied observations. Here we demonstrate that a superior classification of atmospheric mixing states can be achieved through a single, simple measurement of a naturally occurring gas (radon‐222). This has enabled improved characterization of energy and water exchange between urban regions and their environment. This approach can be readily applied to assess the efficacy of mitigation measures of urban climate effects and to produce computational model evaluation data sets that are tailored to specific atmospheric mixing conditions. It can be applied in a similar way to investigate controls on concentration variability of urban pollutants. Key Points: Radon is used to classify atmospheric stability for urban climate studies and to reduce the uncertainty of urban radiation and energy budgetsOur technique separates weather‐related from design-related urban heat island effects and helps evaluate the efficacy of mitigation measuresWe provide a simple, economical tool to produce model evaluation data sets tailored to specific atmospheric conditions [ABSTRACT FROM AUTHOR]

Abstract: Greening Aspang – Hygrothermal building simulation for analysis and evaluation of various scenarios related to indoor climate. In the research project Greening Aspang [1] measurements were taken from different buildings concerning summery overheating. In the present paper simulations were taken with by „WUFI plus 3.0 dynamic building simulations”. The investigations of the research project serve as a basic for the simulations. The different buildings and its sample flats are explained in detail. The data of the simulation is validated by the measurements and extended to the entire building. The hydrothermal comfort inside the buildings has been investigated and evaluated. It turned out that none of the investigated objects, neither flats nor whole buildings, could satisfy the ÖNORM B 8110‐3 [2]. A comparison between the values of measurements and simulations shows that the simulations are very close to the measured reality. The main difference between this values is, that the measurement values vary in a larger area than the values of the simulation. By means of a variant study the effects of different methods structural measures on the hydrothermal indoor climate during a heatwave is investigated. The different structural measures are exterior shading, airing during the night, change of the colour of the façade, façadegreening and loggiagreening. Each of this structural measures reduce the summery overheating. The most effective one is exterior shading, but the more measures are combined, the better it is. A combination of all leads to the best results. [ABSTRACT FROM AUTHOR]

• A simplified process to obtain UHI measurements through mobile transects is developed. • A low-cost device is connected to a new APP, which performs the UHI calculations automatically. • The results may be exported easily and viewed in the APP with graphs and maps. • An additional web-based tool is included, to obtain maps with spatially-continuous data. • The method has the potential for crowdsourcing, extending UHI data acquisition around the world. The main purpose of Urban Heat Island (UHI) studies and the monitoring of ambient temperatures at large scales is to gather temperature information in a certain area, so as to understand temperature heterogeneity and its drivers or detect locations that lack thermal comfort. However, these studies originate mostly from some research projects, with sufficient budget and manpower to carry out the measurements and the necessary calculations. Thus, there is a scarcity of air temperature information, making it difficult to implement appropriate mitigation actions worldwide. The present work aims to greatly simplify the process to monitor air temperatures and carry out UHI estimations through mobile transects. This is done by introducing the design of a low-cost device and a new APP, which performs automatically most necessary UHI calculations. A web tool based on the Inverse Distance Weighting interpolation method is also included to obtain heat maps. The methodology is illustrated using case studies in Seville (Spain) and New York city (USA). By introducing a straightforward and reproducible methodology, we aim to open the path for a more widespread availability of ambient temperature data anywhere in the world, without the need for costly equipment and many hours of dedication by the researchers. [ABSTRACT FROM AUTHOR]

Characterisation of the effects of varying atmospheric mixing states (stability) in urban climate studies has historically been hampered by problems associated with the complexity of the urban environment, representativity of measurement techniques, and the logistical and financial burdens of maintaining multiple long-term comprehensive measurement sites. These shortcomings, together with a lack of a consistent measurement approach, have limited our ability to understand the physical processes contributing to the urban heat island effect. In this study, we analyse 4 years of continuous hourly near-surface meteorological and atmospheric radon data from an urban–rural site pair in central Poland. A recently-developed radon-based stability classification technique, previously developed for urban pollution characterisation, is employed to characterise the Urban Heat Island Intensity (UHII) and other climatic factors over the full diurnal cycle by season and atmospheric mixing state. By characterising the UHII over a range of atmospheric mixing states in a statistically robust way, this technique provides an effective tool for assessing the efficacy of mitigation measures for urban climate effects in a consistent way over timescales of years to decades. The consistency of approach, ease of application, and unprecedented clarity of findings, provide a strong argument for atmospheric radon observations to be included as part of the ‘standard measurement suite’ for urban climate monitoring networks for non-coastal cities. [ABSTRACT FROM AUTHOR]

Urban areas have well-documented effects on climate, such as the urban heat island (UHI) effect, reduction of wind speeds, enhanced turbulence and boundary layer heights, and changes in cloud cover and precipitation. The aim of this study is to quantify the impact of the urban area of London on local and regional climate. This is achieved through the coupling of the non-hydrostatic mesoscale model METRAS with the sophisticated urban canopy scheme BEP. The model is configured for case studies of the London region, for typical UHI conditions, and the model results are evaluated using data from meteorological monitoring sites. This study develops a methodology to quantify the regional impact of urbanisation from numerical model results. The urban area, in its current form, is found to affect near surface temperature, the diurnal temperature range, the UHI, and the near surface wind speed and direction. For the selected cases, peak UHI intensities of up to 2.5 K are found during night time hours, with the timing and magnitude of the peak showing good agreement with previous experimental studies for London. The timing of the UHI peak intensity for the current urban land cover for London shows a good agreement with the results of measurements. A significant reduction in wind speed over the urban area was also simulated during both daytime and night time, due to the higher roughness of the city compared to the rural domain. The effect is shown to have a regional character, with both urban and surrounding rural areas demonstrating a significant impact. Thus, the UHI can not only be understood when focussing on local data, but the interaction with the surrounding needs to be considered. [ABSTRACT FROM AUTHOR]

The article analyses the urban and rural humidity differences by means of a climate station pair in Krefeld, Germany from November 2001-October 2002. The analysis is on the basis of hourly averages of water vapor pressure. It focuses on the examination of frequency, timing and duration of the Urban Moisture Excess. The result has found that the urban site was more humid in 31.4 percent of the cases investigated and was only rarely significantly more humid in 4.6 percent. Detailed information regarding the methods and analysis used in the study, as well as the results, is discussed.

The increase in built surfaces constitutes the main reason for the formation of the Urban Heat Island (UHI), that is a metropolitan area significantly warmer than its surrounding rural areas. The urban heat islands and other urban-induced climate feedbacks may amplify heat stress and urban flooding under climate change and therefore to predict them correctly has become essential. Currently in the COSMO model, cities are represented by natural land surfaces with an increased surface roughness length and a reduced vegetation cover, but this approach is unable to correctly reproduce the UHI effect. By increasing the model resolution, a representation of the main physical processes that characterize the urban local meteorology should be addressed, in order to better forecast temperature, moisture and precipitation in urban environments. Within the COSMO Consortium a bulk parameterization scheme (TERRA_URB or TU) has been developed. It parametrizes the effects of buildings, streets and other man-made impervious surfaces on energy, moist and momentum exchanges between the surface and atmosphere, and additionally accounts for the anthropogenic heat flux as a heat source from the surface to the atmosphere. TU implements an impervious water-storage parameterization, and the Semi-empirical Urban canopy parametrization (SURY) that translates 3D urban canopy into bulk parameters. This paper presents evaluation results of the TU scheme in high-resolution simulations with a recent COSMO model version for selected European cities, namely Turin, Naples and Moscow. The key conclusion of the work is that the TU scheme in the COSMO model reasonably reproduces UHI effect and improves air temperature forecasts for all the investigated urban areas, despite each city has very different morphological characteristics. Our results highlight potential benefits of a new turbulence scheme and the representation of skin-layer temperature (for vegetation) in the model performance. Our model framework provides perspectives for enhancing urban climate modelling, although further investigations in improving model parametrizations, calibration and the use of more realistic urban canopy parameters are needed. [ABSTRACT FROM AUTHOR]

The aim of work was to quantify the impact of urbanization on Land Surface Temperature (LST) of Potiskum and Environs, Yobe State, Nigeria. Remotely sensed data of Landsat 7 Enhanced Thematic Mapper (ETM+) of April 2003, April 2008 and Landsat 8 OLI of April 2015 coupled with meteorological data were used to study the LST. The maximum likelihood classifier was employed to classify the satellite data. Less built-up expansion from 2003 to 2008 compared to 2008–2015 was observed. The validation was performed with the available meteorological data of the stations. The rapid population growth is attributed to expansion of the built-up area and migration of rural people to search employment opportunities and good life. The increase in vegetation cover was witnessed in Potiskum and Environs, hence it has some impact on LST. The LST in the urban area showed low value due to afforestation and adoption of good policies to combat with rise in temperature in urban areas. Therefore, the LST classes of 30 °C–40 °C and > 40 °C showed decrease of area covered from 2003 to 2015. The result shows that in 2003, 34.23 °C of LST was observed while 35.29 °C and 35.60 °C of LST values were also observed in 2008 & 2015, respectively. • Landsat data were used for quantification of urban areas. • LST and NDVI were computed using the Landsat satellite data. • Validation of results was performed using the station (meteorological data). [ABSTRACT FROM AUTHOR]