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This study investigates the intersection of urban security and climate resilience, emphasizing the urgent need to prioritize climate adaptation and mitigation in urban planning. Through a comprehensive global survey of 256 experts across various fields, we uncover a consensus on climate change as a major threat to urban areas, affecting water, ecosystem, health, economic, and food security. Despite this recognition, our findings reveal a significant lack of preparedness and confidence in governmental responses. We highlight the interconnectedness of climate and economic factors, underscoring the challenges in decoupling economic growth from fossil fuel dependency. Furthermore, we explore the potential of smart technologies, such as early warning systems, data analytics, and green infrastructure, to enhance urban resilience. Our study advocates for a proactive and comprehensive approach to climate resilience, emphasizing the need for urban planners to incorporate innovative technological solutions that address both climate adaptation and mitigation. By focusing on these distinct yet interconnected strategies, we aim to foster secure, sustainable, and livable urban environments that effectively respond to current and future climate challenges. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect has become a prominent urban characteristic in the last few decades and brings significant changes to the local urban climate. Such changes have severe impacts on the lifetime efficiency and performance of "critical urban infrastructure" (CUI). As CUI forms the backbone of vital urban systems and socio-economic processes, it becomes important to understand the various impacts of UHI on different CUI elements. The impacts of UHI on CUI have consequently become a prominent study area within the urban research domain. This study presents a systematic bibliometric review of 118 relevant articles published within the last decade (2012–2022), selected from a variety of indexed, scholarly databases. The articles mainly focused on developed regions and large urban areas. The review shows a consistent upward trend in the annual number of publications on UHI effects with a peak reached in 2020. Of the four major CUI groups studied for UHI impacts, built form and energy and communication (with a strong focus on increased energy consumption) are the most prominent topics in the current literature, followed by transportation, and water and sanitation. Research on other CUI elements is still quite sparse, and significant efforts would be needed to identify the nature of UHI's impacts on these factors. This review highlights that the UHI impact on CUI is a developing research area that requires further attention and illustrates the state of knowledge and gaps present in current research. These findings provide a clear direction for future UHI impact studies. [ABSTRACT FROM AUTHOR]

Local Climate Zoning (LCZ) appears as a crucial framework, intricately deciphering the nuanced climatic variations within urban landscapes, centering on the physical structure and surface attributes of cities. With 17 distinct classes standing for diverse features, LCZ provides a nuanced lens for studying urban microclimates. In this study, a meticulous classification of Tehran's local climate classes was conducted using the Automated Geoscientific Analyses (SAGA) GIS software, complemented by sample verification through Google Earth. The findings illuminate Tehran's diverse urban climate, revealing two predominant classes: dense semi-tall and denser, shorter categories. A granular district-wise analysis unfolds varying climatic scenarios: Central and Northern Districts (e.g., Districts 1, 2, 3, 4, 5, 6, 7, 8, 10, 11, 12, 14, and 17): Marked by densely built-up areas (LCZ1 and LCZ2). Southern and Western Districts (e.g., Districts 9, 15, 16, 18, 19, 20, 21, and 22): Hosting a mix of industrial zones and green expanses. While green spaces nestled among buildings are less conspicuous, predominantly confined to city parks (LCZ4 to LCZ6), the classifications strategically show areas with implications for high urban heat loads, pollution hotspots, best air circulation, and air quality. This insightful district-level analysis supplies a robust foundation for steering sustainable urban development. Field validation through on-site visits and meticulous photo documentation rigorously substantiates the accuracy of the output map. The research underscores the profound significance of LCZ, unraveling Tehran's climatic intricacies at a district level. This comprehensive understanding proves essential for steering sustainable urban development, navigating the complexities within the diverse topography of Tehran's districts. [ABSTRACT FROM AUTHOR]

Historically, green spaces have the potential to mitigate the negative effects of urban microclimate. They play an important role in regulating the urban climate and have a positive effect on air temperature. The aim of the study is to test an urban green space in Erzurum, a city with a cold climate and different urban texture/density around it, through climate simulations and to determine the effect of different urban textures around it on the microclimate. During the study, vegetation cover, density analysis of the surrounding residential area and temperature measurements were made for the selected urban green area. ENVI-met program was used to produce maps of the analyzes. As a result of the simulation, it was determined that the urban green area was 2.01 oC cooler in summer and 1.2 oC warmer in winter compared to its built environment. As you move away from the urban green area, the temperature increases in summer and decreases in winter. In the built-up areas around the urban green area, it was found that the region with less dense / high-rise construction was warmer in summer and colder in winter compared to other regions. The results show that the temperature differences vary according to the urban texture, the microclimate effect of the urban green area is not only dependent on the green area and the characteristics of the immediate built environment are also effective. [ABSTRACT FROM AUTHOR]

Understanding how cities develop climate plans is crucial to capture their potential to achieve ambitious climate goals. Previous literature has highlighted the role of external pressures or heroic actors in driving local changes. By highlighting the everyday practices of actors in urban climate planning, we reveal new sets of contradictions in climate governance. Drawing from social practice theory, this paper examines how contradictions were managed in the process of developing a new climate plan in Bergen, Norway. Through a variety of empirical sources, we explore the strategic value these offer, and the organisational work accomplished by the navigation of contradictions. We highlight three strategic benefits of negotiating contradictions: the legitimisation, expansion and signalling of climate work. In conclusion, the paper argues that considering practices of climate planning reveals novel forms of agency, namely the potential of mundane organisational processes and the pivotal role of civil servants in this work. [ABSTRACT FROM AUTHOR]

Although the climate has admittedly always been hot and humid in cities like Karachi, increasingly hotter temperatures are exacerbating the impact of heat on informal, precariously employed outdoor workers such as street vendors, guards and rickshaw drivers, who must negotiate their right and access to shade at the everyday scale. Recalling Mike Davis' radical, political claim that shade is an inalienable human right, this paper proposes that few people working in the outdoor spaces of the South Asian city today understand or experience shade in these terms. Rather shade is something that must be claimed, alongside other rights and entitlements. Moreover, shade alone is insufficient as it cannot reduce the exposure of bodies to harmful ambient radiations and overall thermal discomfort. This paper makes three broad propositions for outlining a theory for the social study of shade in the South Asian city. By paying closer attention to the ways that outdoor workers negotiate shade in Karachi, this paper opens up for analysis a wider spectrum of claims-making activity in changing South Asian urban climates. It places workers' search for shade in the broader context of shade policing and urban management aimed at creating spatial as well as social order. Finally, this article emphasises key directions and questions for future research. [ABSTRACT FROM AUTHOR]

Until the 1990s and the spread of air-conditioning, cooling down during the hot, humid and windless summers in the city of Chongqing (Southwest China) was mainly practised outdoors: sleeping on the rooftops of multistorey buildings, playing mah-jongg in the streets, fanning oneself with a hand fan or installing bamboo beds in the compounds' leafy courtyards. With the availability of affordable electricity and the popularisation of mechanical cooling, refreshing oneself has been relocated to the indoors. The transforming practices in and around the house have led not only to an increasing dependency on electricity for cooling but also to a socio-economic stratification. This paper traces the history of heat mitigation in Chongqing since the 1950s. Based on five months of anthropological fieldwork, semi-structured interviews, and oral history, I analyse how Chongqing residents cope with heat in and around the built environment. Practices of cooling are closely intertwined with the architectural history of the city, for example, building design, construction materials, green spaces, or the arrangement of houses. Staying cool in the socialist era buildings from the 1960s meant something different compared to the high-rise buildings in the early-21st century. Theoretically, the paper engages with urban energy landscapes as 'connective tissue' where everyday heat mitigating practices are intertwined with the locally built environment including architecture, energy infrastructure and technologies. By focusing on the material culture involved in cooling, I shift our perspective from the large infrastructure to the small objects that co-constitute the energy landscape of urban heat mitigation. [ABSTRACT FROM AUTHOR]

Local wind, such as sea breezes, play a crucial role in cooling coastal cities. This study presents new insights about the thermo‐hygrometric influence of the Tagus and Atlantic Ocean breezes (sea and estuarine breezes [SEBs]) in Lisbon's urban climate (Portugal). SEB events were identified in the summer of 2022 according to a wind rotation criterion: the interruption of prevailing North and Northwest (Nortada) winds during the morning, the wind shift to Northeast/East/Southeast and, sometimes, to further South/Southwest/West (rotation between 22.6° and 292.5°) and the return of the regional flow at late afternoon. Additionally, air temperature and absolute humidity anomalies (ΔT/Haurb) were calculated according to the distance to the riverfront area. Results show that SEB occurred on 37 (31%) out of 120 days, mainly in July (43%) and August (32%), between, on average, 10:00 AM and 4:00 PM, and average wind speeds of 3.4 m/s. According to the daily thermo‐hygrometric cycle, the areas up to 4 km of the Tagus estuary were, on average, cooler than northern Lisbon during SEB events, especially the areas up to 500 m (average ΔTurb reached −1.7°C). Additionally, there was a significant increase in the moisture content during SEB hours across the city but especially close to the riverfront area: the areas up to 500 m registered, on average, ΔHaurb of 4.2 g/m3 on SEB events (12:00 PM) against 2.1 g/m3 during typical Nortada days. This research is a starting point for a future delimitation and preservation of SEB penetration zones in Lisbon to address outdoor thermal discomfort during summer. [ABSTRACT FROM AUTHOR]

Analyzing the temporal dynamics of ecological communities can shed light on coexistence mechanisms and help understand how populations and communities will behave in the face of climate change. However, little is known about how frog communities respond to climate in urban ecosystems, especially in tropical countries. Here, we analyzed how frog species richness and abundance are influenced by weather variables both intra‐ and inter‐annually. We surveyed a peri‐urban area in central Brazil, monthly for 3 years. To test the effect of weather variables on species richness and abundance, we used Generalized Additive Mixed‐effects Models. We assessed seasonality using circular statistics. We also tested for differences in temporal beta diversity within and among years by estimating species disappearance and temporal rank shift, in addition to a multivariate model‐based method to test the effect of year on species composition. Finally, we tested how taxonomic and phylogenetic alpha diversity changed through time using a novel approach based on Hill numbers. We found that species richness varied little among years and was affected only by photoperiod, while species abundance was more variable both between and within years, being mostly affected by humidity, temperature, and photoperiod. Species composition varied little between years, mostly between the first and subsequent years. Conversely, beta diversity was highest within years. Only the effective number of species changed significantly through time. Our results help not only understand temporal mechanisms that allow species coexistence, but also allow to make inferences about the impact of urbanization on biodiversity in recently urbanized landscapes, showing that species composition in peri‐urban sites remains unaltered in a mid‐timescale, especially when climate conditions change little across years. [ABSTRACT FROM AUTHOR]

Rapid urbanization worldwide offers numerous benefits but also introduces challenges, particularly concerning urban climate comfort, which affects the physical and social well-being in cities. This study examined the microclimatic characteristics of the Burç neighborhood in the historical core of Burdur city, using ENVI-Met models with temperature, relative humidity, wind and PET data collected over a 33,665 m2 area at 06:00, 09:00, 12:00, 15:00, 18:00 and 21:00 on 15 August 2023. The analysis revealed that thermal comfort decreases significantly from 09:00 onwards, especially on hard surfaces like asphalt, concrete and parquet, which lack vegetation and intensify heat retention. By contrast, green areas were found to enhance bioclimatic comfort by reducing perceived temperatures by up to 20% in shaded and vegetated zones. Based on these findings, it is recommended that urban areas reduce heat-absorbing materials, such as asphalt and concrete and prioritize green spaces in landscape planning to improve thermal comfort and create more sustainable urban environments. [ABSTRACT FROM AUTHOR]

Urban surfaces such as rooftops, facades, and infrastructure offer significant potential for solar energy integration, contributing to energy efficiency and sustainability in cities. This article introduces an advanced multi-criteria assessment (MCA) framework designed to evaluate the suitability of various urban surfaces for solar energy deployment. The framework extends beyond traditional economic, environmental, and technological factors to include social, political, legal, health and safety, cultural, and psychological dimensions, providing a comprehensive evaluation of photovoltaic (PV) applications in urban contexts. By synthesizing existing literature and applying this holistic MCA framework, this research offers valuable insights for urban planners, architects, and policymakers, enabling strategic optimization of solar energy integration in urban environments. The findings underscore the importance of sustainable urban development and climate resilience, highlighting key factors influencing solar technology deployment and proposing actionable recommendations to address existing challenges. [ABSTRACT FROM AUTHOR]

The urban heat island effect (UHI) is among the major challenges of urban climate, which is continuously intensifying its impact on urban life and functioning. Against the backdrop of increasingly prolonged heatwaves observed in recent years, practical questions about adaptation measures in cities are growing—questions that traditional meteorological monitoring can hardly answer adequately. On the other hand, UHI has long been the focus of research interest, but due to the technological complexity of providing accurate spatially referenced data at high spatial resolution and the requirement to survey at strictly defined parts of the day, information provision is becoming a major challenge. This is one of the main reasons why UHI research results are less often used directly in urban spatial planning. However, advances in geospatial technologies, including unmanned aerial systems (UASs), are providing more and more reliable tools that can be applied to achieve better and higher-quality information resources that adequately characterize the UHI phenomenon. This paper presents a developed and tested methodology for the rapid and efficient assessment and mapping of the effects of surface urban heat island (SUHI). It is entirely based on the integrated use of data from unmanned aerial systems (UAS)-based remote sensing methods, including thermal photogrammetry and GIS-based analysis methods. The study follows the understanding that correct SUHI research depends on a proper understanding of the urban geosystem, its spatial and structural heterogeneity, and its functional systems, which in turn can only be achieved by supporting the research process with accurate and reliable information resources. In this regard, the possibilities offered by the proposed methodological scheme for efficient geospatial registration of SUHI variations at the microscale, including the calculation of intra-urban SUHI intensity, are discussed in detail. The methodology builds on classical approaches for using local climate zoning (LCZ), adding capabilities for precise delineation of individual zone types and for geostatistical characterization of the urban surface heat island (SUHI). Finally, the proposed scheme is based on state-of-the-art technological tools that provide flexible and automated capabilities to investigate the phenomenon at microscales, including by enabling flexible observation of its dynamics in terms of heat wave manifestation and evolution. Results are presented from a series of sequential tests conducted on the largest residential area in Bulgaria's capital city, Sofia, in terms of area and population, over a relatively long period from 2021 to 2024. [ABSTRACT FROM AUTHOR]

Meteorological mesoscale models with different urban parametrization are used to predict the local urban climate at 250 m resolution. The authors propose a hybrid machine learning approach to improve the mesoscale prediction accuracy using measured air temperature data from a sensor network and remove simulation bias. The simulation of the urban climate of Zurich during a hot summer is used as case study showing the improvements of the simulation accuracy. Based on the hybrid model results, a cumulative heat exposure index is proposed to map local hotspots in the city and assess the difference of cooling loads between rural and urban environments. Furthermore, intra-urban microclimatic differences of a typical mid-latitude city are explored to highlight the benefits of detailed simulations for building physics purposes. [ABSTRACT FROM AUTHOR]

High-resolution urban climate projections are needed for local decision-making on climate change adaptation. Regional climate models have resolutions that are too coarse to simulate the urban climate at such resolutions. A novel statistical–dynamical downscaling (SDD) approach is used here to downscale the EURO-CORDEX ensemble to a resolution of 1 km while adding the effect of the city of Paris (France) on air temperature. The downscaled atmospheric fields are then used to drive the Town Energy Balance urban canopy model to produce high-resolution temperature maps over the period 1970–2099, while maintaining the city's land cover in its present state. The different steps of the SDD are evaluated for the summer season. The regional climate models simulate minimum (maximum) temperatures (TN/TX) that are too high (low). After correction and downscaling, the urban simulations inherit some of these biases but give satisfactory results for summer urban heat islands (UHIs), with average biases of −0.6 K at night and +0.3 K during the day. Changes in future summer temperatures are then studied for two greenhouse gas emission scenarios, RCP4.5 and RCP8.5. Outside the city, the simulations project average increases of 4.1 and 4.8 K for TN and TX for RCP8.5, respectively. In the city, warming is lower, resulting in a decrease in UHIs of −0.19 K at night (from 2.1 to 1.9 K) and −0.16 K during the day. The changes in UHIs are explained by higher rates of warming in rural temperatures due to lower summer precipitation and soil water content and are partially offset by increased ground heat storage in the city. [ABSTRACT FROM AUTHOR]

Accurate and reliable estimation of rainfall is crucial for scientific research and various applications. However, the observed rainfall data is often limited. With the advancements in technology, many global gridded rainfall products are now available, but their accuracy levels vary across the world. In this study, we comprehensively analyzed the reliability and effectiveness of 23 publicly available global rainfall datasets against the observed rainfall for Patna, representing a typical urban monsoon climate in India. Thirteen continuous and ten categorical statistical metrics were applied at daily, weekly, monthly, and annual intervals over 16 years (2000–2015). The results indicate that the reliability of all derived rainfall datasets varied on different temporal scales and reference datasets used. Overall, in continuous metrics, MERRA2 and MSWEP consistently outperformed in all the temporal scales whereas in categorical metrics for analyzing the rainfall detection ability, AIMERG, followed by MERRA2 demonstrated superior performance among others. Furthermore, IMD GRID, GSMAP, PCCS, AIMERG, and IMERG performed well in estimating different rainfall intensities. MERRA2 and MSWEP, which have not been widely considered for evaluation in a monsoon climate were found to be outstanding performers consistently. Therefore, we suggest broadening the selection of global rainfall products in the evaluation to fully utilize the potentiality of all available options. Furthermore, our approach offers a reliable framework to comprehensively assess the performance of different gridded rainfall products and assist in the selection of the best rainfall product for a particular region and purpose. [ABSTRACT FROM AUTHOR]

The Local Climate Zone (LCZ) scheme representing urban structure and land use pattern is essential for urban heat island (UHI) research. Fine-grained LCZ mapping considering spatial and temporal heterogeneity can provide a more precise characterization of surface thermal properties, thereby enabling a comprehensive analysis and understanding of spatiotemporal trends in climate change research. However, data-driven deep learning-based methods have limitations in coping with the complex urban landscapes of the real-world scenarios, including the spectral similarity of different LCZ and the geospatial heterogeneity of urban LCZ categories. In this study, we constructed a geographic knowledge base for enhanced LCZ characterization with the consideration of prior surface spatial information, including a set of spectral indices and urban morphological parameters (UMPs). Then, we integrated the explicable geographic knowledge base into a learnable deep learning framework in an end-to-end manner for accurate LCZ mapping by fusing multi-source heterogeneous data with a multi-level fusion strategy. The constructed Chinese Climate Zone Time Series LCZ (CClimate-TLCZ) dataset derived from Landsat-8 data with a 30 m spatial resolution, covering 18 representative cities in China, were used to evaluate the proposed framework. The experimental results demonstrate that the proposed framework achieved optimal outcomes across 18 cities, with an average overall accuracy exceeding 94 %, which is more than 20 % higher than that obtained by the standard WUDAPT method. Furthermore, the analysis of LCZ mapping-driven land surface temperature (LST) and surface UHI (SUHI) applications shows that cities within the same climate zone have similar LST distribution patterns, while significant heterogeneity exist between different zones. The annual consistency of LST patterns within each climate zone supports the validity of the LCZ classification scheme and accurate LCZ mapping for urban thermal environment studies. From 2016 to 2022, SUHI intensity initially increases and then decreases, indicating improvements in the urban thermal environment. These findings underscore the critical role of precise LCZ mapping in urban climate resilience and sustainable urban planning. [ABSTRACT FROM AUTHOR]

Local governments have taken an active role in climate change policymaking and have filled in gaps from the national and state levels in the USA. However, even with the growing scholarly interest in urban climate policymaking, there is still a lot that scholars do not understand about it. The current research project seeks to provide a deeper investigation into how municipalities interact with their citizens in sustainability and climate change policymaking. It further analyzes the specific ways that citizens are included in climate policymaking. To examine these questions, the research uses a mixed methods approach, combining survey and interview data. Findings reveal that municipal characteristics are related to citizen involvement around climate change, but that there are also specific motivations for how local governments interact with their citizens, particularly related to increasing citizen buy-in and diversity. The research provides implications for how local governments conceptualize citizen involvement for sustainability policymaking and how they might approach the issue in the future. [ABSTRACT FROM AUTHOR]

Research has provided considerable evidence that temperature significantly influences species biology. Its influence is so great that climate corridors have been proposed to assist species in tracking their climatic niche at macroecological scales, reinforcing the importance of accounting for this variable at all scales to address the climatic threat to biodiversity. This threat is exacerbated in cities where artificialization enhances the effect of climate change, to the extent that urban temperatures are a public health concern, with heatwaves causing excess human mortality and having a stark impact on biodiversity. Recent developments in climate monitoring networks enable characterizing the spatiotemporal structure of urban climates in ever greater detail, with many cities already equipped with such networks. The impact of temperature on biodiversity, on the same scale as these networks allows, has never been explored. Characterizing urban climate infrastructures and cool corridors, and thus thermal connectivity for species, would enrich and strengthen existing ecological infrastructures, on the basis of scientific evidence. In this perspective, we discuss how stronger collaborations between ecologists and climatologists could help leverage the full potential of urban climate monitoring networks. We highlight research opportunities they could offer in terms of studying the impact of urban climate on biodiversity and the efforts that need to be pursued to enable co‐designing and make interdisciplinary collaborations operational. Such interdisciplinary research on urban climate and its impact is all the more important that its outcomes can help better inform urban planning and mitigate the impacts of climate change on people and biodiversity. This article is categorized under:Climate and Development > Urbanization, Development, and Climate ChangeAssessing Impacts of Climate Change > Observed Impacts of Climate ChangeClimate, Ecology, and Conservation > Observed Ecological Changes [ABSTRACT FROM AUTHOR]

The complexities of urban climate and environmental challenges have garnered significant attention in the 21st century. Numerical simulations, offering high spatiotemporal resolution meteorological data, are essential tools in meteorological research and atmospheric science. Accurate representation of urban morphology parameters is crucial for enhancing the precision of these simulations in urban areas. Despite the availability of urban canopy parameter (UCP) data for 44 major cities in the United States and 60 in China for the weather research and forecasting (WRF) model, a comprehensive global dataset representing urban morphology remains absent. This study addresses this gap by leveraging existing global three-dimensional vector data of buildings, including footprints and heights, to compile a global 1 km spatially continuous UCP (GloUCP) dataset for the WRF model. Our findings indicate that GloUCP not only surpasses existing datasets in accuracy but also provides superior spatial coverage. In key urban agglomerations such as Beijing-Tianjin-Hebei, the Yangtze River Delta, and the Guangdong-Hong Kong-Macao Greater Bay Area in China, GloUCP offers detailed and reliable urban morphological information that closely aligns with reference datasets, outperforming other available sources. Similarly, in U.S. cities like Seattle, San Francisco, and Philadelphia, GloUCP consistently achieves lower RMSE values and higher correlation coefficients, demonstrating its robustness in modeling diverse urban environments. Furthermore, GloUCP's capability to effectively capture the vertical distribution of buildings, particularly in high-rise areas, highlights its utility in urban climate modeling and related applications. As UCPs are pivotal in regulating atmospheric responses to urbanization, the availability of this globally consistent urban description is a crucial prerequisite for advancing model development and informing climate-sensitive urban planning policies. The GloUCP dataset, converted to WRF binary file format, is available for download at https://doi.org/10.6084/m9.figshare.27011491 (Liao et al., 2024). [ABSTRACT FROM AUTHOR]

Improvements in high-resolution satellite remote sensing and computational advancements have sped up the development of global datasets that delineate urban land, crucial for understanding climate risks in our increasingly urbanizing world. Here, we analyze urban land cover patterns across spatiotemporal scales from several such current-generation products. While all the datasets show a rapidly urbanizing world, with global urban land nearly tripling between 1985 and 2015, there are substantial discrepancies in urban land area estimates among the products influenced by scale, differing urban definitions, and methodologies. We discuss the implications of these discrepancies for several use cases, including for monitoring urban climate hazards and for modeling urbanization-induced impacts on weather and climate from regional to global scales. Our results demonstrate the importance of choosing fit-for-purpose datasets for examining specific aspects of historical, present, and future urbanization with implications for sustainable development, resource allocation, and quantification of climate impacts. There has been a surge in global datasets of urban land recently. This paper shows large discrepancies in urban area across scales among multiple such datasets, which can influence the magnitude and direction of estimated urban climate impacts. [ABSTRACT FROM AUTHOR]

Remote sensing satellite data have been a crucial tool in understanding urban climates. The variety of sensors with different spatiotemporal characteristics and retrieval methodologies gave rise to a multitude of approaches when analyzing the surface urban heat island effect (SUHI). Although there are considerable advantages that arise from these different characteristics (spatiotemporal resolution, time of observation, etc.), it also means that there is a need for understanding the ability of sensors in capturing spatial and temporal SUHI patterns. For this, several land surface temperature products are compared for the cities of Madrid and Paris, retrieved from five sensors: the Spinning Enhanced Visible and InfraRed Imager onboard Meteosat Second Generation, the Advanced Very-High-Resolution Radiometer onboard Metop, the Moderate-resolution Imaging Spectroradiometer onboard both Aqua and Terra, and the Thermal Infrared Sensor onboard Landsat 8 and 9. These products span a wide range of LST algorithms, including split-window, single-channel, and temperature–emissivity separation methods. Results show that the diurnal amplitude of SUHI may not be well represented when considering daytime and nighttime polar orbiting platforms. Also, significant differences arise in SUHI intensity and spatial and temporal variability due to the different methods implemented for LST retrieval. [ABSTRACT FROM AUTHOR]

Urban parks, as a vital component of green infrastructure, significantly contribute to alleviating the impacts of climate change and enhancing the urban ecosystem. This paper examines the EVFBS Cemetery Park in Berlin as a case study to elucidate the significant role of centralized urban greening, exemplified by urban cemetery parks, in addressing the challenges posed by urban climate change. Through field research, data collection, and various methodologies, this study examines the specific planning and design measures employed to address climate-related challenges, including air purification, temperature regulation, and mitigation of the urban heat island effect. Additionally, it explores the multifaceted roles of urban parks in enhancing the quality of the urban ecological environment, promoting biodiversity, and providing recreational spaces for residents. The aim is to elucidate the significance of diverse urban parks within the climate regulation strategies of contemporary metropolises. By comparing and discussing relevant practices and successful experiences in climate-adaptive design from Berlin, and summarizing advanced concepts and planning experiences that may serve as valuable references for the development of urban green spaces in China, it examines the significance of urban park greening for climate regulation in contemporary cities. [ABSTRACT FROM AUTHOR]

The connection between plant species and nest site preference for the Asian weaver ant Oecophylla smaragdina remains poorly understood despite their common occurrence in the urban areas of tropical regions. We predicted that plant species with specific leaf characteristics influence the nesting preference of Asian weaver ants, given that plant foliage is the main component of their nest structure. We studied the leaf characteristics of the tree species in which their nests were detected, including leaf shape, leaf apex shape, and leaf arrangement. Of the 206 total trees among the 20 tree species sampled, 185 trees from 18 tree species had at least one nest. Trees of the genus Lagerstroemia had the highest median nest abundance, whereas all Roystonea regia and Caryota no trees, and some Samanea saman trees, were not occupied by O. smaragdina. For the trees found to have O. smaragdina nests, the nest abundance in each tree ranged between 1 and 16 nests, with the majority having fewer than 10 nests per tree (4.38 ± 4.45). Based on nest abundance, the oblong and elliptic leaf shapes (LS), the cuspidate leaf apex shape (LX), and the opposite leaf arrangement (LR) were the most used for nest construction, consisting of more than 50% of the total in each respective category. A Kruskal-Wallis test revealed that O. smaragdina nest site preference is influenced by LX and LR but not by LS. Additionally, O. smaragdina nest abundance was negatively correlated to leaf surface ratio but insignificant for leaf surface area. These preferred qualitative and quantitative leaf characteristics determine the species of plants used as nesting sites to facilitate nest-building efficiency and the establishment of Asian weaver ant colonies. [ABSTRACT FROM AUTHOR]

Urban Land Surface Models (ULSMs) simulate energy and water exchanges between the urban surface and atmosphere. However, earlier systematic ULSM comparison projects assessed the energy balance but ignored the water balance, which is coupled to the energy balance. Here, we analyze the water balance representation in 19 ULSMs participating in the Urban‐PLUMBER project using results for 20 sites spread across a range of climates and urban form characteristics. As observations for most water fluxes are unavailable, we examine the water balance closure, flux timing, and magnitude with a score derived from seven indicators expecting better scoring models to capture the latent heat flux more accurately. We find that the water budget is only closed in 57% of the model‐site combinations assuming closure when annual total incoming fluxes (precipitation and irrigation) fluxes are within 3% of the outgoing (all other) fluxes. Results show the timing is better captured than magnitude. No ULSM has passed all water balance indicators for any site. Models passing more indicators do not capture the latent heat flux more accurately refuting our hypothesis. While output reporting inconsistencies may have negatively affected model performance, our results indicate models could be improved by explicitly verifying water balance closure and revising runoff parameterizations. By expanding ULSM evaluation to the water balance and related to latent heat flux performance, we demonstrate the benefits of evaluating processes with direct feedback mechanisms to the processes of interest. Plain Language Summary: Urban environments have their own local climates including typically higher nocturnal temperatures compared with rural areas. Ideally, modeling cities should capture their influences on the atmosphere above them. As the energy and water balances are linked by evaporation, a good water balance representation will support a good energy balance simulation. Focusing on the water balance, we find the water balance in models could be improved by paying attention to closure and runoff. Key Points: We evaluate the water balance in 19 urban land surface models (ULSM) from the Urban‐PLUMBER projectULSMs capture the timing of water fluxes more accurately than their magnitudeThe water balance appears unclosed in 43% of the model runs (19 models at 20 sites) [ABSTRACT FROM AUTHOR]

The Model for Prediction Across Scales–Atmosphere (MPAS-A) has been widely used for larger scale simulations, but its performance in mesoscale, particularly in tropical regions, is less evaluated. This study aimed to assess MPAS-A in simulating extreme surface air temperature in Jakarta during the hot spells of October 2023 with eight different simulation setups. Several validation metrics were applied to near-surface meteorological variables, land surface temperature (LST), and vertical atmospheric profile. From the eight simulations, MPAS-A captured diurnal patterns of the near-surface variables well, except for wind direction. The model also performed well in LST simulations. Moreover, the biases in the vertical profiles varied with height and were sensitive to the initial/boundary conditions used. Simulations with modified terrestrial datasets showed higher LST and air temperatures over the sprawling urban areas. MPAS-A successfully simulated the extreme event, showing higher air temperatures in southern Jakarta (over 36 °C) compared to the northern part. Negative temperature advection by sea breeze helped lower air temperature in the northern area. This study highlights the role of sea breezes as natural cooling mechanisms in coastal cities. Additionally, MPAS-A is feasible for several applications for urban climate studies and climate projection, although further development is needed. [ABSTRACT FROM AUTHOR]

Climate change is a major challenge for the global tourism sector, affecting destinations worldwide. Greece, known for its scenery and abundant cultural history, is particularly vulnerable to these impacts. Tourism is a key driver of Greece's economy, yet climate change threatens both natural environments and cultural sites. To evaluate the impacts of climate change on different types of Greek tourism (beach, sightseeing, winter tourism in mountainous areas), the widely used Holiday Climate Index (beach and urban versions) alongside three additional climatic indices customized for Greek climatic conditions, namely the Urban Climate Comfort Index, the Beach Utility Index, and the Mountainous Winter Climate Index were utilized for top tourist destinations of Greece. The results indicate that urban tourism may face challenges during peak summer months due to rising temperatures, but the shoulder seasons (April–May and September–October) will offer improved conditions, potentially extending the tourist season. For beach tourism, favorable conditions are expected to increase from April to October, with significant gains in June and September. Winter tourism in mountainous areas, especially snow-dependent activities like skiing, is at risk due to the declining snow availability. Overall, the study highlights both the challenges and opportunities posed by climate change for Greece's tourism sector. It emphasizes the importance of adaptation strategies, including infrastructural improvements and promoting alternative activities, to minimize negative impacts and enhance the future attractiveness of Greek tourism. [ABSTRACT FROM AUTHOR]

The urban heat island (UHI) effect is a widely recognized phenomenon consisting of heat accumulation by dense urban construction and human activities, resulting in higher temperatures across urban areas compared to their surroundings. This article aims to quantify the UHI effect on several areas throughout the city of Lisbon, Portugal, with the main goal of validating, evaluating, and reinforcing urban climate adaptation and resilience strategies proposed in the recent scientific literature. A set of nine quality-controlled weather stations from the "Lisboa Aberta" network that are compliant with the World Meteorological Organization (WMO) standards and installation requirements were used to characterize Lisbon's UHI, in comparison to a reference weather station from the Instituto Português do Mar e da Atmosfera (IPMA), located at Lisbon Airport. By applying a principal component analysis (PCA) in an innovative way to 10 urban indexes, it is shown that the thermal inertia in Lisbon's urban areas is positively correlated with the UHI intensity and urban density, regardless of the daily heating/cooling cycle. Furthermore, the results show that land use also has an impact on the UHI effect, with continuous, vertical building areas showing the greatest deviations in comparison to the reference, averaging +1.8 °C. Contrastingly, horizontal building areas reveal an average deviation of +1.3 °C, with sparse, discontinuously built areas representing an average UHI effect of +0.2 °C. Finally, through a climatope analysis, it is determined that, across Lisbon, high-density urban areas and ventilation corridors are responsible for inducing average UHI effects of +1.7 °C and +0.2 °C, respectively. [ABSTRACT FROM AUTHOR]

This paper introduces a methodology aimed at bridging the gap between building energy simulation and urban climate modeling. A coupling method was developed through the Building Control Virtual Test Bed (BCVTB) and applied to a case study in Taipei City, Taiwan, to address the microclimate factors of street trees crucial to cooling energy consumption. The use of the Urban Weather Generator for weather file modification revealed a 0.63 °C average air temperature disparity. The coupling method emphasized the importance of accurate wind speed and convective heat transfer coefficients (CHTCs) on building surfaces in determining cooling energy. The results indicated that elevated CHTC values amplify heat exchange, with higher wind velocities playing a crucial role in heat dissipation. The presence of street trees was found to significantly reduce heat flux penetration, leading to a reduction in building surface temperatures by as much as 9.5% during hot months. The cooling energy was lowered by 16.7% in the BCVTB simulations that included trees compared to those without trees. The EnergyPlus-only simulations underestimated the cooling energy needs by approximately 9.3% during summer months. This research offers valuable insights into the complex interactions between buildings and their environments. The results highlight the importance of trees and shading in mitigating the heat island effect and improving energy-efficient urban planning. [ABSTRACT FROM AUTHOR]

The current research on urban heat island (UHI) effect mostly focuses on the analysis of land use type changes and the surface UHI intensity. Few studies on the urban canopy heat island effect at a block scale of local climate zone (LCZ), although the canopy heat island effect is a key factor affecting human thermal comfort. Therefore, this study will combine the LCZ classification system and the urban weather generator (UWG) model to simulate and quantitatively analyse the urban canopy heat island effect in Beijing at the block scale. First, based on Sentinel-2 Multispectral remote sensing images, the residual neural network (ResNet) method was used to obtain the LCZ of Beijing, and the results of LCZs was validated based on the google earth engine (GEE). Then, according to the classification results of local climate zones, the input parameters of the UWG and their corresponding value ranges are calculated. Finally, the UWG model is used to simulate the canopy temperature in different local climate zones, and the urban canopy temperature is validated using the meteorological station dataset. We quantitatively analyse the temperature differences between different types of LCZs. The results shows that the canopy heat island effect in Beijing gradually weakened outward from the city centre. This is mainly due to the relatively dense distribution of compact local climate zones in the centre of Beijing, while the surrounding areas of Beijing have lower building density and better natural coverage. The canopy urban heat island intensity of built-up LCZs is significantly stronger than that of natural-covered LCZs. The heat island intensity of the compact LCZ is higher than that of the open LCZ with the same building height. However, for LCZs with comparable compactness, the heat island intensity of high-level LCZs is higher than that of low-level LCZs. [ABSTRACT FROM AUTHOR]

The numerical weather prediction model HARMONIE-AROME and a multiple linear regression model (referred to in this article as the TURCLIM model after the local climate observation network) were used to model surface air temperature for 25–31 July 2018 in the City of Turku, Finland, to study their performance in urban areas and surrounding rural areas. The 0200 LT (local standard time) temperatures modeled by the HARMONIE-AROME and TURCLIM models were compared to each other and against the observed temperatures to find the model best suited for modeling the urban heat island effect and other spatial temperature variabilities during heatwaves. Observed temperatures were collected from 74 sites, representing both rural and urban environments. Both models were able to reproduce the spatial nighttime temperature variation. However, HARMONIE-AROME modeled temperatures were systematically warmer than the observed temperatures in stable conditions. Spatial differences between the models were mostly related to the physiographic characteristics: for the urban areas, HARMONIE-AROME modeled on average 1.4°C higher temperatures than the TURCLIM model, while for other land-cover types, the average difference was 0.51°C at maximum. The TURCLIM model performed well when the explanatory variables were able to incorporate enough information on the surrounding physiography. Respectively, systematic cold or warm bias occurred in the areas in which the thermophysically relevant physiography was lacking or was only partly captured by the model. Significance Statement: As more and more people are living in an urban environment, the demand for accurate urban climate modeling is growing. This study aims to understand the differences between the numerical weather prediction and multiple linear regression modeling and their limitations in modeling surface air temperature in subkilometer scale. The case study shows that models are capable of predicting the spatial variation of 0200 LT nighttime temperature during a heatwave in a high-latitude coastal city. Both models are therefore valuable assets for city planners who need accurate information about the impacts of the physiography on the urban climate. The results indicate that to improve the performance of the models, more accurate physiographic description and higher spatial resolution of the models are needed. [ABSTRACT FROM AUTHOR]

High-resolution urban climate modeling has faced substantial challenges due to the absence of a globally consistent, spatially continuous, and accurate dataset to represent the spatial heterogeneity of urban surfaces and their biophysical properties. This deficiency has long obstructed the development of urban-resolving Earth System Models (ESMs) and ultra-high-resolution urban climate modeling, particularly at large scales. Here, we present a first-of-its-kind 1km-resolution present-day (circa-2020) global continuous urban surface parameter dataset – U-Surf. Using the urban canopy model (UCM) in the Community Earth System Model as a base model for developing dataset requirements, U-Surf leverages the latest advances in remote sensing, machine learning, and cloud computing to provide the most relevant urban surface biophysical parameters, including radiative, morphological, and thermal properties, for UCMs at the facet- and canopy-level. Our high-resolution U-Surf dataset significantly improves the representation of the urban land heterogeneity both within and across cities globally. U-Surf provides essential, high-fidelity surface biophysical constraints to urban-resolving ESMs, enables detailed city-to-city comparisons across the globe, and supports the next-generation kilometer-resolution Earth system modeling across scales. U-Surf parameters can be easily converted or adapted to various types of UCMs, such as those embedded in weather and regional climate models, as well as air quality models. The fundamental urban surface constraints provided by U-Surf are also relevant as features for machine learning models and can have other broad-scale applications for socioeconomic, public health, and urban planning contexts. We expect U-Surf to promote the research frontier on urban systems science, climate-sensitive urban design, and coupled human-Earth systems in the future. The dataset is publicly available at https://doi.org/10.5281/zenodo.11247599 (Cheng et al., 2024). [ABSTRACT FROM AUTHOR]

Urban climatic challenges can motivate urban planners and designers to implement urban climate-responsive design strategies. But does this process occur sufficiently, and if not, why? This study explores the implementation of urban climate-responsive design strategies, potential functional and aesthetic conflicts, availability of policy instruments that support implementation, strengths and weaknesses, and missed opportunities for integrating agendas. Semi-structured interviews were conducted with experts familiar with urban climate-responsive design. The results suggest that greening measures are most often implemented, strategies tend to compete with other land-uses, designers face aesthetic conflicts, and strategies are predominantly mainstreamed within existing policy instruments. [ABSTRACT FROM AUTHOR]

The urbanization and expansion of cities have raised sustainability concerns and impacted the overall quality of life. Numerous studies have explored sustainable cities with climate-adapted urban and architectural designs, particularly focusing on optimizing thermal comfort within different urban morphologies. This publication presents a meticulous systematic review analyzing how urban form influences microclimatic conditions through advanced computer simulations. The PRISMA methodology condenses key indicators to facilitate informed decision making. A robust dataset from reputable databases such as ProQuest, Web of Science, and Scopus was analyzed, revealing discernible climate patterns, with hot arid (Bwh) and humid subtropical (Csa) climates being the most studied. The Thermal Comfort Index predominantly relies on the PET metric, with ENVI-met software as a popular simulation tool. Uncontrolled urban sprawl, surface impermeability, and lack of greenery exacerbate the urban heat island effect, leading to multifaceted environmental, social, and energy-related implications. The study underscores the importance of exploring topics like urban forms and morphology while advocating for increased attention to specific climatic conditions and urban scales. The growing prevalence of computational simulations for climate analysis emerges as a pivotal area of interest for future research. [ABSTRACT FROM AUTHOR]

This study examines the temporal and spatial variability of near‐surface air temperature and the canopy layer urban heat island (UHICL) of Kuwait City. Observations collected at 12 locations across the country of Kuwait and for the period 2010–2022 are analysed on an hourly and 3‐hourly basis to provide monthly and diurnal insights of the city's UHICL characteristics. Research on Kuwait's UHICL was first conducted by Nasrallah et al. (International Journal of Climatology, 10, 401–405). Results presented here have been afforded the benefit of additional stations and more extensive data compared with the earlier study. Mean positive UHICL intensities, ranging from 1.1°C to 3.8°C at night, are observed consistently across all months, owing to the prevalence of clear skies from winter to summer. Negative UHICL intensities, indicating a typical daytime urban cool island (UCICL), are most prominent on summer days, exhibiting a mean hourly magnitude range between 0.6°C and 2.6°C that extends into the early parts of the evening. Heat and cool island effects are maintained up to wind speeds approaching 10 m s−1 at the urban periphery. A coastal site near the city demonstrates strong influences of the Arabian Gulf temperatures and associated sea and land breeze effects on UHICL development. The results can be used for comparison with other desert locales, in the evaluation of urban climate models, for urban planning policies and improving local weather forecasts. This study honours in memoriam Dr. Hassan Nasrallah, who produced the first UHICL study in the Arab World. [ABSTRACT FROM AUTHOR]

Populism is multilayered and involves two main dimensions – ideology and strategy – which are employed within and beyond political parties. These dimensions can result in sometimes overlapping but generally divergent backlashes, targeting specific climate and sustainability interventions in cities. This critical commentary presents episodic populist backlashes against urban climate actions by exploring how they create their own political landscapes across the political spectrum in cities against progressive urban climate agendas. Specifically, the article examines how episodic populist backlashes manifest on an urban scale and highlights the need for urban scholars to pay more attention to the phenomenon. The article proposes two complementary explanations for why populism precedes urban climate actions in episodic and thematic ways. These explanations include policy backlashes against diffused global climate norms in cities, and counter-movements and rhetoric against climate justice and what it entails, such as inclusion in decision-making and intersectionality. The article then concludes by offering a research agenda on the episodic populist backlashes against urban climate actions, which highlights the need for a better understanding of how episodic populist movements might emerge into global climate policy diffusion, and climate justice coupled with intersectionality in cities of the Global North and Global South. [ABSTRACT FROM AUTHOR]

This investigation builds upon and extends prior lightning research in the Bangkok Metropolitan Region (BMR) through the reconstruction of thunderstorm distribution, utilizing a novel lightning tracking algorithm. Five years (2016–2020) of lightning stroke data from the Global Lightning Dataset (GLD360) were used to identify 52 608 thunderstorms. Optimized hotspot analyses, track densities, and analyses of thunderstorms with respect to winds, landcover, and seasons were performed. Our findings suggest that significant modification of thunderstorm distribution within the region was due to urban landcover impacts on the local environment. Thunderstorm intensity, as measured by stroke counts and track length, also appeared to be sensitive to the urban environment. The thunderstorm distribution also highlighted areas prone to hazards such as flash flooding. By visualizing thunderstorms grouped by winds, thunderstorm initiation hotspots and track density corridors were identified. These corridors of augmented thunderstorm production tended to occur during specific months given the seasonal monsoon wind regime occurring across the BMR. As urbanization within the BMR continues, geospatial assessment of thunderstorms is important to inform forecast meteorologists, urban planners, government officials, and others who play a critical role in developing strategies, policies and insfrastructure that could mitigate thunderstorm impacts. [ABSTRACT FROM AUTHOR]

Anthropogenic heat emissions, which are quantified as anthropogenic heat flux (AHF), have attracted significant attention due to their pronounced impacts on urban thermal environments and local climates. However, there remains a notable gap in research regarding the distinctions in the distribution of anthropogenic heat emissions (AHEs) along urban–rural gradients. To address this gap, the present study introduces a new concept—the anthropogenic urban heat island (ArUHI)—where the AHF within urban areas is higher than that in background areas. To quantitatively describe the magnitude and spatial extent of the ArUHI effect, two metrics—namely, ArUHI intensity (ArUHII) and ArUHI footprint (ArUHIFP)—are introduced. We conducted a comprehensive study across 208 cities in China to investigate the spatiotemporal patterns of AHF variations along urban–rural gradients during the period of 2000–2016. In addition, we explored how the complex interactions between land cover and building form components affect changes in the AHF along urban–rural gradients. Additionally, we analyzed how economic zones and city sizes alter the ArUHI intensity and ArUHI footprint. The results showed that 97% (201/208) of Chinese cities exhibited a significant ArUHI effect from 2000 to 2016. The modeled ArUHI intensity value exhibited a substantial increase of nearly fivefold, increasing from 5.55 ± 0.19 W/m2 to 26.84 ± 0.99 W/m2 over time. Regarding the spatial distribution of the ArUHI footprint, the analysis revealed that, for the majority of cities (86% or 179 out of 208), the ArUHI footprint ranged from 1.5 to 5.5 times that in urban areas. City sizes and economic zones yielded significant influences on the ArUHI intensity and ArUHI footprint values. Building forms were significantly positively correlated with AHF, with R2 values higher than 0.94. This study contributes to the understanding of ArUHI effects and their driving factors in China, providing valuable insights for urban climate studies and enhancing our understanding of surface urban heat island mechanisms. [ABSTRACT FROM AUTHOR]

Monitoring microclimate variables within cities with high resolution and accuracy is crucial for enhancing urban resilience to climate change. Assessing intra-urban characteristics is essential for ensuring satisfactory living standards. This paper presents a comprehensive methodology for studying urban heat islands (UHIs) on a university campus, emphasizing the importance of multi-modal and multi-temporal data collection. The methodology integrates mobile surveys, stationary sensor networks, and drone-based thermal imaging, providing a detailed analysis of temperature variations within urban microenvironments. The preliminary findings confirm the presence of a UHI on the campus and identify several hotspots. This comprehensive approach enhances the accuracy and reliability of UHI assessments, offering a cost-effective, fine-resolution approach that facilitates more effective urban planning and heat mitigation strategies. [ABSTRACT FROM AUTHOR]

Wind speed differences between weekdays and holidays at urban sites in Japan were investigated in search of the influence of urban anthropogenic heat on surface wind speed using data from the Automated Meteorological Data Acquisition System (AMeDAS) of the Japan Meteorological Agency (JMA) for 44 years. The wind speed was found to be lower on holidays than on weekdays, not only in large cities but also in areas with medium degrees of urbanization, which is interpreted to be due to the stronger stability of the surface boundary layer under lower temperatures with smaller amounts of anthropogenic heat. The rate of decrease is about −3% in central Tokyo, and about −0.5% for the average over stations with population densities between 1000 and 3000 km−2. Additionally, an analysis using the spatially dense data on the Air Pollution Monitoring System of Tokyo Metropolis for 28 years showed that negative anomalies in wind speed on holidays were detected at many stations in the Tokyo Wards Area, although negative temperature anomalies were limited to a few stations in the central area or near big roads, suggesting different spatial scales in the response of temperature and wind speed to anthropogenic heat. [ABSTRACT FROM AUTHOR]

In the face of climate change and population growth, Local Climate Zone (LCZ) maps have emerged as crucial tools for urban planners and policymakers to address Urban Heat Island (UHI) effects, thereby playing a significant role in mitigating climate change. This study presents a methodology for classifying major Swiss cities into LCZs, offering an efficient, cost-effective, and uniform tool for supporting climate action plans across municipalities and cantons. Initial results show that Sentinel-2, Landsat 8, and Landsat 5 imagery perform well in LCZ classification with an overall accuracy usually exceeding 80%, and Sentinel-2 displays marginally superior performance. Temporal analysis reveals that the built-up classes of Open low-rise and Open mid-rise have increased by ~3%, while Large low-rise and Bare rock or paved have decreased, and Compact mid-rise remains stable. For the natural classes, Water and Dense trees remain stable, but Low plants have declined (~4%). A general decline in overall accuracy over time is noted, attributed to landscape changes. This preliminary effort emphasizes the need to enhance and automate the methodology, integrate it into the Swiss Data Cube, and potentially extend analyses with climate data to better study UHI effects. Future work will include developing visualization and tracking services for urban planners and authorities. [ABSTRACT FROM AUTHOR]

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Evapotranspiration (ET) $(ET)$ is a key process in the hydrological cycle that can help mitigate urban heat. ET $ET$ depends on the surface cover, as the surface affects the partitioning of precipitation between runoff and evapotranspiration. In urban neighborhoods, this surface cover is highly heterogeneous. The resulting neighborhood‐scale ET $ET$ can be observed with eddy‐covariance systems. However, these observations represent the signal from wind‐ and stability‐dependent footprints resulting in a continuously changing contribution of surface cover types to the observation. This continuous change prevents quantifying the contribution of the surface cover types to neighborhood ET $ET$ and their hourly dynamics. Here, we disentangle this neighborhood‐scale ET $ET$ at two sites in Berlin attributing the patch‐scale ET $ET$ dynamics to the four major surface cover types in the footprint: impervious surfaces, low vegetation, high vegetation, and open water. From the bottom‐up, we reconstruct neighborhood ET $ET$ based on patch‐scale observations and conceptual models. Alternatively, we start top‐down and attribute neighborhood ET $ET$ to the surface cover types solving a system of equations for three eddy‐covariance systems. Although data requirements for the bottom‐up approach are met more frequently, both approaches indicate that vegetation is responsible for more ET $ET$ than proportional to its surface fraction in the footprint related to the large evaporating surface compared to the ground surface. Evaporation from impervious surfaces cannot be neglected, although it is less than from vegetation due to limited water availability. The limited water availability causes impervious surfaces to cease evaporation hours after rainfall, while vegetation and open water sustain ET $ET$ for extended periods. Plain Language Summary: Different types of surfaces, like grass, trees, pavement, and open water, affect how rainwater is divided between evaporation and runoff. In cities with lots of pavement and buildings, more water runs off than in natural areas leaving less water for evaporation. Measurement towers have been observing the evaporation from whole neighborhoods, but separating the effects of different surfaces is hard. In our study, we figure out how much each surface type contributes to evaporation with two methods: one starting from the separate surfaces and rebuilding the neighborhood evaporation, and the other starting with the neighborhood evaporation and breaking it down into evaporation from each surface. Both ways showed that plants evaporate more than proportionally to their surface area, but even built surfaces like pavement evaporate. Our findings confirm that more plants lead to more evaporation, but built surfaces cannot be ignored. This information can help urban planners create cities that manage water better, making cities nicer places to live. Key Points: Neighborhood ET is reconstructed from patch‐scale data (bottom‐up) and disentangled attributing ET to four surface types (top‐down)The neighborhood and patch scale are connected through half‐hourly‐varying eddy‐covariance footprintsET dynamics after rainfall reveal that water limitation drives differences between surface cover types [ABSTRACT FROM AUTHOR]

Global politics has shown increasing interest in cities, particularly in the field of climate policy and governance. Yet, we still have little understanding of which cities engage the most in global urban climate governance. Answering this question is a first step towards understanding who decides for whom in a system that has decisive influence on wider global policy processes. In this article, we seek to identify and analyse the characteristics and position of cities in global urban climate governance to reassess its composition. To do so, we conduct a social network analysis of 15 transnational city networks. Results emphasise that global and large cities are the most central, but small and middle‐size cities are the most numerous actors of the system. Global South cities are larger than their Northern counterparts in the system. Those less central and understudied actors likely have less influence over which norms are shared, yet they should not be seen as followers or imitators of climate policy. It is important to pay more attention to them to understand their multifaceted role in cities' collective efforts to address climate change. [ABSTRACT FROM AUTHOR]

City size is a primary determinant of the urban heat island (UHI) intensity, with its effects further nuanced by the urban form. But how to factor in the urban form into the UHI assessment remains unresolved. We propose an every‐pair‐interaction model that meaningfully incorporates urban size and fractal dimension to characterize the UHI intensity. Regression on the summertime surface UHI intensity of 5,000 European cities shows that the model outperforms the simple linear combination of logarithmic size and fractal dimension. Subject to the interplay between the range of the every‐pair interaction and the urban fractal shape, the model also represents a generalization as it includes power‐law, logarithmic, and saturating size dependence of UHI—all three possibilities have been reported empirically in the literature. Our theoretical framework indicates that the surface UHI intensity saturates with urban size, opening up new research perspectives around UHI intensity. Plain Language Summary: City size is an important determinant of the urban heat island (UHI) intensity. While most studies report a logarithmic dependence of UHI intensity on city size, other functions like power‐law and logistic functions have also been reported. In addition, the urban form plays an important role and, intuitively, increased UHI intensity is expected for compact cities. However, how to incorporate urban size and form for modeling UHI is less clear. Based on the perception that every urban site interacts with every other one, whereas the intensity of interaction decreases with the distance, we propose an every‐pair‐interaction model to characterize the UHI intensity. The model combines urban size and fractal dimension non‐linearly and outperforms the simple linear model. It also represents a generalization of the three functional possibilities reported in the literature. Our model indicates that the surface UHI intensity saturates with urban size. Whether the UHI saturates with the expansion of the urban area or follows a continuously increasing trend is relevant for sustainable urban development. Our approach paves the way for fresh research avenues into UHI intensity and urban climate as a whole. Key Points: We propose an every‐pair interaction model that unifies urban size and fractal dimension to model surface urban heat island (UHI) intensityThe model outperforms multi‐linear models and is a generalization of three functional shapes of the size dependence of surface UHI intensityThe empirical results in combination with our theoretical framework indicate that the surface UHI intensity saturates with urban size [ABSTRACT FROM AUTHOR]

Local climate zones (LCZs) and urban functional zones (UFZs) can intricately depict the multidimensional spatial elements of cities, offering a comprehensive perspective for understanding the surface urban heat island (SUHI) effect. In this study, we retrieved two types of land surface temperature (LST) data and constructed 12 SUHI scenarios over the Guangdong–Hong Kong–Macao Greater Bay Area Central region using six SUHI identification methods. It compared the SUHI sensitivity differences among different types of LCZ and UFZ to analyze the global and local sensitivity differences of influencing factors in the 12 SUHI scenarios by utilizing the spatial gradient boosting trees, geographically weighted regression, and the coefficient of variation model. Results showed the following: (1) The sensitivity of different LCZ and UFZ types to multi-scenario SUHI was significantly affected by differences in SUHI identification methods and non-urban references. (2) In the morning, the shading effect of building clusters reduced the surface urban heat island intensity (SUHII) of some built environment types (such as LCZ 1 (compact high-rise zone) to LCZ 5 (open midrise zone)). The SUHIIs of LCZ E (bare rock or paved zone) and LCZ 10 (industry zone) were 4.22 °C and 3.87 °C, respectively, and both are classified as highly sensitive to SUHI. (3) The sensitivity of SUHI influencing factors exhibited regional variability, with importance differences in the sensitivity of importance for factors such as the impervious surface ratio, elevation, average building height, vegetation coverage, and average building volume between LCZs and UFZs. Amongst the 12 SUHI scenarios, an average of 87.43% and 89.97% of areas in LCZs and UFZs, respectively, were found to have low spatial sensitivity types. Overall, this study helps urban planners and managers gain a more comprehensive understanding of the complexity of the SUHI effect in high-density cities, providing a scientific basis for future urban climate adaptability planning. [ABSTRACT FROM AUTHOR]

The widespread availability of Land Surface Temperature (LST) data from various sources presents a contemporary challenge for urban climate studies: how to efficiently compare these data with the results of traditional methods of temperature monitoring, which typically assume measurements at 2 m under sheltered conditions. In this line, the current study is based primarily on data extracted from a network of 31 points of hourly temperature monitoring at the 2 m level (Tair2m), in use between 2019 and 2021, in the city of Suceava in north-eastern Romania. These data allowed a detailed mapping for each hourly time step through multiple regression, adjusted by IDW, which was identified as the best interpolation method of Tair2m. These data were analyzed in parallel with LST data derived from Landsat imagery available in the analyzed period for 35 summer days with no or low cloud cover. The mapping results of both the Tair2m and LST data describe the main characteristics of the Suceava urban agglomeration (SvMA) heat island, which presents polynuclear features with intensities—as expressed by the temperature difference between the cores of the heat island and the surrounding rural areas—spanning during the summer noontime between 3.0 °C based on Tair2m and 7.1 °C on LST, respectively. The values of the Tair2m–LST differences were 0.68 °C on average, ranging from 5.33 to −19.17 °C, directly proportional to the imperviousness ratio (IMD) values, reaching the highest values in the local climate zones (LCZs) with a high built-up ratio (up to −19.17 °C) and the lowest (0.5 ÷ −0.5 °C) for those with bare soils, with isolated bushes and trees, with few or no buildings. The study results could serve as a tool to downscale the LST data to the level of Tair2m, which is useful for interpretation of the data derived from these commonly used tools in urban climate monitoring. [ABSTRACT FROM AUTHOR]

The exponential growth in population and physical infrastructure since 1980 has imposed immense pressure on Dhaka Metropolitan City (DMC), triggering extensive urbanization and a surge in built-up areas. This urban expansion has intensified the urban heat island (UHI) effect (the phenomenon where urban areas experience significantly higher temperatures compared to surrounding areas), resulting in adverse global urban climate changes such as temperature spikes, erratic rainfall, and compromised air quality. This study aims to discern the heat wave trends in DMC from 1972 to 2020 and elucidate their impact on public health and livelihoods. Employing a blend of quantitative and qualitative methodologies, the research analysis of land surface temperatures (LST) and land cover indices reveals a significant increase in built-up areas, particularly in western and central parts of the city, correlating with higher LST. Satellite imagery (Landsat 5 and 8) with 30-m resolution and meteorological data indicate a rise in surface temperatures. Analysis reveals April, May, and June as the peak months for heat wave occurrences, with DMC enduring a total of 328 heat wave days according to heat index (a measurement of perceived temperature in human body indicating how hot it feels when relative temperature is added to the actual air temperature) classifications. Notably, the density of built-up areas, particularly in central and western regions, exacerbates the UHI effect, evident in rising surface temperatures reaching 40.1 °C in 2014. The study underscores the dire health hazards posed by heat waves, with vulnerable populations, such as slum dwellers and outdoor laborers, facing heightened risks. Despite widespread impacts, public awareness about heat waves remains deficient, as evidenced by respondents' limited understanding of the term. These outcomes and prepared maps of the current research will be supportive for the local inhabitant, urban planner, and environmental resources management manager, national and international policy advisor, government and non-movement stakeholder, and researcher to observe the urban climate, trend of heat wave, and its impact on exposed people. [ABSTRACT FROM AUTHOR]

Embracing a "more global" urban comparison in scientific assessments of climate actions by cities is essential to drive greater and more inclusive participation in global efforts to curb climate change. This comparison needs to engage cities irrespective of their size and status: when we do so, distinctive patterns of urban climate mitigation actions across a diverse range of cities emerge. Employing K-means clustering as a pattern recognition method, this study compares cities based on selected aspects of their reported mitigation actions to the Carbon Disclosure Project. It explores whether the identified clusters facilitate the comparison of a socio-spatially diverse range of cities. The study identifies five clusters within two themes, namely the nature and finance–implementation of actions, shedding light on shared and distinct governance aspects of mitigation actions by cities. Notably, the study underscores how governance patterns transcend city size and global status. These findings offer valuable insights for broadening the comparative imagination of cities and inter-city networking opportunities. [ABSTRACT FROM AUTHOR]

Understanding the characteristics of minute‐scale short‐duration intense rainfall and its possible link with urbanization is valuable for addressing urban climate change and evaluating biases in high‐resolution historical precipitation data series. This study analyses the long‐term trends of rainy‐season minute‐scale intense rainfall events at different continuous time periods based on precipitation data from 20 national meteorological stations in the Beijing area covering the period from 1961 to 2021. This study shows that during the whole period analysed, the number of events of intense rainfall lasting 15 min or longer decreased, while the number of shorter‐duration events and the accumulated precipitation increased. The frequency and amount of minute‐scale intense rainfall recorded by urban stations are generally higher than those recorded by rural stations in terms of climatological means. The signal of the urbanization effect in minute‐scale precipitation changes is detectable, with the contribution of urbanization to the trends in average precipitation of 30‐min intense rainfall being 68.8%, whereas the contributions with respect to the frequency of 20‐ and 30‐min intense rainfall and the maximum precipitation of intense rainfall with a duration of 45 min reach 100%. The results of the analysis can provide reference for understanding long‐term changes in short‐duration rainfall and the possibility that they are driven by local anthropogenic activity, as well as bias in the minute‐scale precipitation data series of urban observation sites when they are used in studies of large‐scale intense precipitation changes. [ABSTRACT FROM AUTHOR]