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Global warming is one of the most pressing challenges of our time, contributing to climate change effects and with far-reaching implications for built environments. The main aim of this study is to assess the extent to which Annaba city, Algeria, as part of the Mediterranean region, is affected by global climate change and its broader influences. The study investigated climatic shifts in Annaba city, using a multi-step methodology integrating data collection and analysis techniques. Data collection included 23 years of climate data (2000–2023) from Annaba's meteorological station, on-site measurements of microclimatic variations, and a questionnaire survey. The collected data underwent four main analyses: a time series analysis to describe climate parameters over 23 years, a statistical analysis to predict potential future climatic conditions (2024–2029) and the correlation of various climatic variables using specialized bioclimate tools to highlight seasonal variability, a spatial study of the urban heat island (UHI) phenomenon and perceived climatic shifts, and an analysis of extreme weather events characterizing heat atmospheric events in the context of urban climate change in the Mediterranean region. The findings revealed a consistent warming trend in Annaba city, with prolonged extreme climate conditions observed, particularly in the last four years (2020–2023). Significant temperature fluctuations were emphasized, notably in July 2023, with record-breaking maximum temperatures reaching 48.2 °C, the hottest on record with an increase of 3.8 °C, and presenting challenges amplified by the urban heat island effect, causing temperature differentials of up to 6 °C within built-up areas. Projections for 2029 suggest a tendency towards heightened aridity with a significant shift towards a new climate seasonality featuring two distinct main seasons—moderate and hot challenging. The abrupt disruption of calm weather conditions in Annaba on 24 July 2023 highlighted the influence of atmospheric circulation within the Mediterranean region featured for both anticyclones and atmospheric blocking phenomena on local weather patterns. [ABSTRACT FROM AUTHOR]

A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed Is and Ic trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean Is trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding Ic trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime Is trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime Ic trend. At night, both global Is and Ic trends are mainly controlled by background climate. Plain Language Summary: Surface and canopy urban heat islands (surface and canopy UHIs, termed Is and Ic) are two major UHI types. These two counterparts are both related to urban population heat exposure and have long been a focus of urban climate research. However, the differences in the trends and major determinants of Is and Ic over global cities remain largely unclear. Based on spatially continuous land surface temperature and surface air temperature observations from 2003 to 2020, we find that the global mean Is trends are about 6.3 times and 2 times the Ic trends during the day and at night, respectively. During the day, the global Is trend is more regulated by surface property than by background climate, and vice versa for global Ic trend. At night, both the global Is and Ic trends are mainly regulated by background climate. These findings are important for better understanding global urban climate change and informing heat mitigation strategies. Key Points: The global Is trend is six‐fold and twofold larger than the Ic trend during the day and at night, respectivelyDuring the day, global Is trend is slightly more controlled by surface property, yet background climate plays a dominant role in Ic trendAt night, both global Is and Ic trends are more regulated by background climate [ABSTRACT FROM AUTHOR]

Global warming is one of the most pressing challenges of our time, contributing to climate change effects and with far-reaching implications for built environments. The main aim of this study is to assess the extent to which Annaba city, Algeria, as part of the Mediterranean region, is affected by global climate change and its broader influences. The study investigated climatic shifts in Annaba city, using a multi-step methodology integrating data collection and analysis techniques. Data collection included 23 years of climate data (2000–2023) from Annaba’s meteorological station, on-site measurements of microclimatic variations, and a questionnaire survey. The collected data underwent four main analyses: a time series analysis to describe climate parameters over 23 years, a statistical analysis to predict potential future climatic conditions (2024–2029) and the correlation of various climatic variables using specialized bioclimate tools to highlight seasonal variability, a spatial study of the urban heat island (UHI) phenomenon and perceived climatic shifts, and an analysis of extreme weather events characterizing heat atmospheric events in the context of urban climate change in the Mediterranean region. The findings revealed a consistent warming trend in Annaba city, with prolonged extreme climate conditions observed, particularly in the last four years (2020–2023). Significant temperature fluctuations were emphasized, notably in July 2023, with record-breaking maximum temperatures reaching 48.2 °C, the hottest on record with an increase of 3.8 °C, and presenting challenges amplified by the urban heat island effect, causing temperature differentials of up to 6 °C within built-up areas. Projections for 2029 suggest a tendency towards heightened aridity with a significant shift towards a new climate seasonality featuring two distinct main seasons—moderate and hot challenging. The abrupt disruption of calm weather conditions in Annaba on 24 July 2023 highlighted the influence of atmospheric circulation within the Mediterranean region featured for both anticyclones and atmospheric blocking phenomena on local weather patterns.

Abstract A comprehensive comparison of the trends and drivers of global surface and canopy urban heat islands (termed Is and Ic trends, respectively) is critical for better designing urban heat mitigation strategies. However, such a global comparison remains largely absent. Using spatially continuous land surface temperatures and surface air temperatures (2003–2020), here we find that the magnitude of the global mean Is trend (0.19 ± 0.006°C/decade, mean ± SE) for 5,643 cities worldwide is nearly six‐times the corresponding Ic trend (0.03 ± 0.002°C/decade) during the day, while the former (0.06 ± 0.004°C/decade) is double the latter (0.03 ± 0.002°C/decade) at night. Variable importance scores indicate that global daytime Is trend is slightly more controlled by surface property, while background climate plays a more dominant role in regulating global daytime Ic trend. At night, both global Is and Ic trends are mainly controlled by background climate.

Climate change and rapid urbanization are two global processes that have significantly aggravated natural disasters, such as drought and flooding. Urbanization without resilient and sustainable planning and execution could lead to undesirable changes in landscapes and stormwater regulation capacity. These changes have exacerbated the effects of extreme climatic events with disastrous consequences in many cities worldwide. Unfortunately, the major storm in Zhengzhou, China on 20 July 2021 was one of these examples. This event provided a rare opportunity to study the key roles of green infrastructures (GI) in mitigating flooding risks in a major urban center after a devasting flood event. Using the data from high-resolution images collected via two satellites, a comprehensive study of the Jialu System in Greater Zhengzhou was conducted to systematically compare how far the river water had reached before and after the 20 July 2021 major storm in order to identify the main weak links in the city's GI and stormwater management system. A flood inundation intensity index (FI) in the Upper (UJLR), Middle (MJLR), and Lower (LJLR) Regions of the Jialu River System was generated. Bivariate Moran's I, a correlation coefficient between FI and landscape characteristics, was calculated and used to identify problem areas for future improvements. Our results showed that the MJLR had the severest flooding impacts. LJLR had the biggest change in how far the river water reached after flooding, ranging from 4.59 m to 706.28 m. In UJLR, the percentages of mine, crop land, and green space had the highest global bivariate Moran's I correlation coefficients. In MJLR, the percentages of vacant land, impervious surfaces, and water body had the highest global bivariate Moran's I correlation coefficients. In LJLR, the percentages of vacant land, water body, and crop land had the highest global bivariate Moran's I correlation coefficients. The total percentages of both high landscape characteristics indices-high flood inundation intensity indices and low landscape characteristics indices-high flood inundation intensity indices areas are 12.96%, 13.47%, and 13.80% in UJLR, MJLR, and LJLR, respectively. These land cover composition types identified for each region can be treated as areas of primary focus. However, GeoDector Model (GDM) analyses showed that our eight variables of landscape characteristics were not independent. Hence, a more comprehensive approach integrating all eight variables is still necessary in future flood mitigation efforts. [ABSTRACT FROM AUTHOR]

Climate change is one of the great global challenges. Cities are both drivers and responders of climate change. In recent years, the literature associated with climate change and cities has grown rapidly, but few studies have used a bibliometric analysis and visualization approach to conduct deep mining and explore the current situation and development trends of this field. By using bibliometric and text mining methods, the authors conducted a knowledge map analysis of the research on cities and climate change. Moreover, this article attempts to identify the research hotspots and research gaps in this field. The following findings are distilled. First, research in this field is rapidly emerging, and the current research distribution is extremely uneven. China and the US contributed 36% of total paper output. Second, previous research focused on six topics: Impact of Climate Change and Urbanization, Urban Climate Change Adaptation, Urban Heat Island Effect, Urban Greenhouse Emission, Urban Climate Change and Water, and Urban Energy Systems. The first two topics are currently the most popular directions of research. Third, empirical research shows positive interest in big cities, while climate change research in small and medium-sized cities has been neglected. The results of this work will not only help researchers clarify the current situation in cities and climate change science but also provide guidance for future research. [ABSTRACT FROM AUTHOR]

In urban heat island (UHI) effect modeling, traditional 3D morphological indexes often homogenize elements within units, leading to a loss of spatial detail. Here we introduce detailed stereoscopic urban morphology indices, including the Height Variation Coefficient, the Height Gravity Index, the Mixed Degree, and the Aggregation Degree, using urban building and vegetation height data to represent the 3D structures within urban units. We employed ensemble learning algorithms to explore nonlinear effects and statistical correlations across 20 buffer radii (100 m to 2000 m) related to the UHI effect. The integration of these inhomogeneous indexes substantially improved model accuracy, with XGBoost achieving an R2 of 0.95. The optimal scale for calculating such indexes was found to be between 300 m and 400 m. Our findings suggest optimizing UHI mitigation by lowering the Building Height Coefficient in high-density areas and increasing it in low-density regions. Furthermore, we propose tailoring the Vegetation Height Coefficient for green spaces, advocating higher values for larger parks and lower values for smaller ones. This approach offers practical insights for mitigating urban heat effects through customized morphological strategies, emphasizing the importance of precise urban planning and environmental management. • Stereoscopic Urban Morphology Indexes enhance LST prediction accuracy. • We recommend lower BHC in high-density areas, raise it in low-density areas. • Forest parks require higher VHC, while pocket parks demand lower VHC • The optimal scale for examining the 3D urban structure-UHI link is 300-400 m [ABSTRACT FROM AUTHOR]

Climate change and its urban dimensions have become more actively debated topics since the beginning of the millennium. As a result of being such a recent concern, the available definitions of what is at stake and what is needed to deal with it—in particular who should deal with it—are often too broad, vague and even disputable depending on the interlocutors, and often focussed on the rural areas. In the context of urban climate change in Luanda and in Maputo, there is an undefined set of tasks and responsibilities to deal with the impacts and prevent further negative effects to the urban dwellers and the poor in particular. This article identifies recurrently mentioned areas where the state is considered absent (and should be present). Based on fieldwork conducted in Luanda and in Maputo, the available literature, accounts of expert stakeholders, and the appraisals and claims of the urban dwellers, this article analyses the existing legal and policy dispositions and the existing systems and resources to deal with climate change. This is simultaneously confronted with what policy stakeholders, urban practitioners and urban dwellers on the ground see that is missing, needs to be improved, and is urgent and capable of improving daily lives. The main findings are that responsibilities and attributions, despite being unclear and not fully defined, predominantly rely on the state and state institutions. [ABSTRACT FROM AUTHOR]

Climate change and rapid urbanization are two global processes that have significantly aggravated natural disasters, such as drought and flooding. Urbanization without resilient and sustainable planning and execution could lead to undesirable changes in landscapes and stormwater regulation capacity. These changes have exacerbated the effects of extreme climatic events with disastrous consequences in many cities worldwide. Unfortunately, the major storm in Zhengzhou, China on 20 July 2021 was one of these examples. This event provided a rare opportunity to study the key roles of green infrastructures (GI) in mitigating flooding risks in a major urban center after a devasting flood event. Using the data from high-resolution images collected via two satellites, a comprehensive study of the Jialu System in Greater Zhengzhou was conducted to systematically compare how far the river water had reached before and after the 20 July 2021 major storm in order to identify the main weak links in the city’s GI and stormwater management system. A flood inundation intensity index (FI) in the Upper (UJLR), Middle (MJLR), and Lower (LJLR) Regions of the Jialu River System was generated. Bivariate Moran’s I, a correlation coefficient between FI and landscape characteristics, was calculated and used to identify problem areas for future improvements. Our results showed that the MJLR had the severest flooding impacts. LJLR had the biggest change in how far the river water reached after flooding, ranging from 4.59 m to 706.28 m. In UJLR, the percentages of mine, crop land, and green space had the highest global bivariate Moran’s I correlation coefficients. In MJLR, the percentages of vacant land, impervious surfaces, and water body had the highest global bivariate Moran’s I correlation coefficients. In LJLR, the percentages of vacant land, water body, and crop land had the highest global bivariate Moran’s I correlation coefficients. The total percentages of both high landscape characteristics indices-high flood inundation intensity indices and low landscape characteristics indices-high flood inundation intensity indices areas are 12.96%, 13.47%, and 13.80% in UJLR, MJLR, and LJLR, respectively. These land cover composition types identified for each region can be treated as areas of primary focus. However, GeoDector Model (GDM) analyses showed that our eight variables of landscape characteristics were not independent. Hence, a more comprehensive approach integrating all eight variables is still necessary in future flood mitigation efforts.

Climate change impacts are intensifying social inequalities locally and globally. Exposure to climate risks, as well as the ability to prepare for and recover from them, are affected by complex power structures. An expanding body of literature uses an intersectional lens to explicate a more nuanced understanding of how co-constituted power structures manufacture differential climate vulnerabilities. Despite the increasing focus on intersectional approaches to institutionalized climate planning, there are limited quantitative studies examining how the co-constituted processes of being racialized and gendered influence climate change perceptions in the United States. In contribution to these conversations, we examine how race and gender together shape experiences of climate impacts, perceptions of future risk, and desires for adaptation actors in Austin, Texas. Using a survey of Austin area households, we explored climate perceptions including residents self-reported experience of four types of climate events, assessment of changing climate risks, overall climate change concerns, and desires for resilience actions by a variety of actors. Our research suggests that race and gender, income levels, and political party are related to which climate events people report experiencing, their perception of changes to various climate risks, their overall climate concern, and their support for various climate adaptation actors. • Urban climate plans often overlook how race and gender influence climate perceptions. • We examine how race and gender shape climate impacts, concern, and desired actors. • Race, gender, politics, income, and education affect climate perceptions in Austin, TX. • Black women reported the fewest climate impacts but the highest climate concern. • Over 85% of residents support local government climate adaptation actions. [ABSTRACT FROM AUTHOR]

Under consideration of climate change, high-resolution (100 m × 100 m) assessments of heat events were performed for Augsburg, Southern Germany, for the extended summer season (May–September). Heat (anomaly) days were defined as days exceeding absolute (relative) temperature thresholds. The focus is on the assessment of how the number and duration of events change under future climate conditions and how e.g., green spaces or sealed areas affect the intra-urban structure of heat (anomaly) events. Assessments were performed under consideration of two Representative Concentration Pathways (RCP4.5 and RCP8.5). The method is based on a two-step statistical approach: a novel analog technique (Normal VECtor of circulation patterns, NVEC) to downscale large-scale information on point observation and a spatial model (Multiple Linear Regression, MLR) for estimating temperature patterns across the entire urban area. The model calibration and validation were performed by an urban meteorological network of 38 monitoring stations for air temperature. Results show that differences between RCP4.5 and RCP8.5 are only small until 2040. At the end of the 21st century, the number of heat days for RCP8.5 is four times higher than under consideration of RCP4.5 and 33 times higher than within the reference period (1970–2000) leading to more and longer lasting events. • A two-step statistical downscaling approach was used to estimate temperatures for the city of Augsburg • Assessments of temperatures and heat events for the 21st century were made at a high spatial resolution (100 m × 100 m) • Significant differences between RCP4.5 and RCP8.5 first occur around the mid-21st century • The cooler regions of the city in particular are feeling the consequences of higher greenhouse gas emissions • By the end of the 21st century, the duration of the heat day period increases significantly, especially under RCP8.5 [ABSTRACT FROM AUTHOR]

The effects of climate change (CC) have intensified in Ghana, especially in the Greater Accra region over the last two decades. CC assessment under the new IPCC scenarios and consistent local station data is limited. Consequently, CC assessment is becoming difficult in data-scarce regions in Ghana. This study utilizes six different Regional Climate Models under the 6th IPCC Report's Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, which were bias-corrected with CMhyd over Greater Accra using ground station and PUGMF reanalysis data. The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs. Maximum temperature is expected to increase by 0.81–1.45 °C, 0.84–1.54 °C, 0.96–1.70 °C and 0.98–1.73 °C, while minimum temperature would likely increase by 1.33–2.02 °C, 1.49–2.22 °C, 1.71–4.75 °C and 1.75–4.83 °C under SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5 scenarios, respectively. Thus, temperature will likely increase, especially at night in the near future. Rising temperatures and changes in precipitation have impacts on all strata of society, from agricultural production to power generation and beyond. These findings can help inform Ghanaian policymaking on Sustainable Development Goals 11 and 13 as well as nationally determined contributions within the Paris Agreement. • The study utilizes six different Regional Climate Models to assess the Shared Socioeconomic Pathway scenarios (SSPs) of the CMIP6, over Greater Accra • The study reveals that Greater Accra is projected to be vulnerable to climate change in the future • The study reveals a reduction and potential shift in the intensity of precipitation in the region under the SSPs • Temperature will likely increase, especially at night in the near future. • These findings can help inform Ghanaian policymaking on Sustainable Development Goals 11 and 13 [ABSTRACT FROM AUTHOR]

Recent studies on fine-scale spatial variations of urban air temperature revealed that urban environments are urban heat "archipelagos", rather than "islands," and there are locations with higher temperatures which suffer more intensive urban heat, and people in these areas are likely to experience greater heat stress and health risks. However, study of this phenomenon is limited because of insufficient air temperature data at the fine scale. This study attempted to quantify the heterogeneity of air and land surface temperature (LST), and their relationship in a fine-scale urban environment using field-measured air temperature and Landsat 8-based LST data. We found: (1) there was a strong thermal heterogeneity at the fine scale even between the measurement points on the edges of a large urban park. The maximum temperature difference reached 4.2 °C for air temperature and 8 °C for LST in the study area. (2) Air and surface temperatures were positively correlated. However, their cool and hot spots did not always overlap in space. (3) air temperature is more complex than LST, and more parameters in the urban environment can influence air temperature. (4) Urban landscape and climatological parameters can enhance the applicability of LST as a proxy for air temperature from 39% to 57%. The results have theoretical and practical implications for identifying the locations on a fine scale with extreme heat and attracting the attention of urban planners to take adoption measures. • Fine-scale air temperature variations were considered based on field-measurement data. • There is a strong thermal heterogeneity in fine-scale intra-urban areas. • LST might be applicable as a proxy to study air temperature variations. • Considering landscape and climatological parameters enhances such applicability. [ABSTRACT FROM AUTHOR]