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This study investigated monthly variations of surface urban heat island intensity (SUHII) and the applicability of the local climate zones (LCZ) scheme for land surface temperature (LST) differentiation within three spatial contexts, including urban, rural and their combination, in Shenyang, China, a city with a monsoon-influenced humid continental climate. The monthly SUHII and LST of Shenyang were obtained through 12 LST images, with one in each month (within the period between 2018 and 2020), retrieved from the Thermal InfraRed Sensor (TIRS) 10 in Landsat 8 based on a split window algorithm. Non-parametric analysis of Kruskal-Wallis H test and a multiple pairwise comparison were adopted to investigate the monthly LST differentiations with LCZs. Overall, the SUHII and the applicability of the LCZ scheme exhibited spatiotemporal variations. July and August were the two months when Shenyang underwent strong heat island effects. Shenyang underwent a longer period of cool than heat island effects, occurring from November to May. June and October were the transition months of cool–heat and heat–cool island phenomena, respectively. The SUHII analysis was dependent on the definition of urban and rural boundaries, where a smaller rural buffering zone resulted in a weaker SUHI or surface urban cool island (SUCI) phenomenon and a larger urban area corresponded to a weaker SUHI or SUCI phenomenon as well. The LST of LCZs did not follow a fixed order, where in July and August, the LCZ-10 (Heavy industry) had the highest mean LST, followed by LCZ-2 (Compact midrise) and then LCZ-7 (Lightweight low-rise). In comparison, LCZ-7, LCZ-8 (Large low-rise) and LCZ-9 (Sparsely built) had the highest LST from October to May. The LST of LCZs varied with urban and rural contexts, where LCZ-7, LCZ-8 and LCZ -10 were the three built LCZs that had the highest LST within urban context, while LCZ-2, LCZ-3 (Compact low-rise), LCZ-8, LCZ-9 and LCZ-10 were the five built LCZs that had the highest LST within rural context. The suitability of the LCZ scheme for temperature differentiation varied with the month, where from July to October, the LCZ scheme had the strongest capability and in May, it had the weakest capability. Urban context also made a difference to the suitability, where compared with the whole study area (the combination of urban and rural areas), the suitability of built LCZs in either urban or rural contexts weakened. Moreover, the built LCZs had a higher level of suitability in an urban context compared with a rural context, while the land-cover LCZs within rural had a higher level of suitability.

Strong historical and predicted future warming over high-latitudes prompt significant effects on agricultural and forest ecosystems. Thus, there is an urgent need for spatially-detailed information of current thermal growing season (GS) conditions and their past changes. Here, we deployed a large network of weather stations, high-resolution geospatial environmental data and semi-parametric regression to model the spatial variation in multiple GS variables (i.e. beginning, end, length, degree day sum [GDDS, base temperature + 5 °C]) and their intra-annual variability and temporal trends in respect to geographical location, topography, water and forest cover, and urban land use variables over northern Europe. Our analyses revealed substantial spatial variability in average GS conditions (1990–2019) and consistent temporal trends (1950–2019). We showed that there have been significant changes in thermal GS towards earlier beginnings (on average 15 days over the study period), increased length (23 days) and GDDS (287 °C days). By using a spatial interpolation of weather station data to a regular grid we predicted current GS conditions at high resolution (100 m × 100 m) and with high accuracy (correlation ≥ 0.92 between observed and predicted mean GS values), whereas spatial variation in temporal trends and interannual variability were more demanding to predict. The spatial variation in GS variables was mostly driven by latitudinal and elevational gradients, albeit they were constrained by local scale variables. The proximity of sea and lakes, and high forest cover suppressed temporal trends and inter-annual variability potentially indicating local climate buffering. The produced high-resolution datasets showcased the diversity in thermal GS conditions and impacts of climate change over northern Europe. They are valuable in various forest management and ecosystem applications, and in adaptation to climate change.

Rapid and uncontrolled urbanization in tropical Africa is increasingly leading to unprecedented socio-economical and environmental challenges in cities, particularly urban heat and climate change. The latter calls for a better representation of tropical African cities’ properties relevant for urban climate studies. Here, we demonstrate the possibility of collecting urban canopy parameters during a field campaign in the boreal summer months of 2018 for deriving a Local Climate Zone (LCZ) map and for improving the physical representation of climate-relevant urban morphological, thermal and radiative characteristics. The comparison of the resulting field-derived LCZ map with an existing map obtained from the World Urban Data and Access Portal Tool framework shows large differences. In particular, our map results in more vegetated open low-rise classes. In addition, site-specific fieldwork-derived urban characteristics are compared against the LCZ universal parameters. The latter shows that our fieldwork adds important information to the universal parameters by more specifically considering the presence of corrugated metal in the city of Kampala. This material is a typical roofing material found in densely built environments and informal settlements. It leads to lower thermal emissivity but higher thermal conductivity and capacity of buildings. To illustrate the importance of site-specific urban parameters, the newly derived site-specific urban characteristics are used as input fields to an urban parametrization scheme embedded in the regional climate model COSMO-CLM. This implementations decreases the surface temperature bias from 5.34 to 3.97 K. Based on our results, we recommend future research on tropical African cities to focus on a detailed representation of cities, with particular attention to impervious surface fraction and building materials.

Abstract Drawing on data for the 104 largest German cities, and deeper analysis of six mid-sized cities (including forerunners, followers and latecomers in climate mitigation and adaptation), we find that the spread of local mitigation and adaptation strategies across Germany can be explained by a combination of horizontal diffusion and vertical upscaling. Specifically, while the spread of climate mitigation initiatives in the 1990s was triggered primarily by transnational municipal networks (horizontal diffusion), the development and revision of climate mitigation strategies and the emergence of climate adaptation strategies during the last decade have been driven mainly by national and subnational funding programmes (vertical upscaling). Notably, forerunner cities are less dependent on external funding than followers and latecomers, because they have more internal capacity to act. By arguing that upscaling of local climate policies from forerunners to followers and latecomers depends on interventions by national and subnational authorities, we stress that the majority of German municipalities require external support in order to develop and implement effective climate strategies.

During the simulation of the urban heat island phenomenon, the accurate representation of urban geometry in numerical models is crucial. In this study, the local climate zone (LCZ) system was incorporated into the Weather Research and Forecasting (WRF) model in order to facilitate proper land surface information for the model integrations. After the calculation of necessary input canopy parameters, based on local static datasets, simulations were performed to test the model’s performance in predicting near-surface air temperature (Ta) and urban heat island intensity (ΔT) under a heatwave period in July 2017. The modelled values were evaluated against the observations of the local urban climate monitoring system. The results suggest that WRF with a single-layer canopy scheme and the LCZ-based static database was able to capture the spatiotemporal variation of the aforementioned variables reasonably well. The daytime Ta was generally overestimated in each LCZ. At nights, slight overestimations (underestimations) occurred in LCZ 6, LCZ 9, and LCZ D (LCZ 2 and LCZ 5). The mean ΔT was underestimated in the night-time; however, the daytime ΔT was estimated accurately. The mean maxima (minima) of ΔT were underestimated (overestimated) with around 1.5–2 °C, particularly in LCZ 2 and LCZ 5. Some components of the surface energy budget were also computed to shed light on the inter-LCZ differences of Ta. It was concluded that the nocturnal ground heat flux was about five times higher in urban LCZs than in the rural LCZ D, which resulted in a reduced cooling potential over the urbanized areas.

Intense atmosphere‐ocean‐ice interactions in the Ross Sea play a vital role in global overturning circulation by supplying saline and dense shelf waters. Since the 1960s, freshening of the Ross Sea shelf water has led to a decline in Antarctic Bottom Water formation. However, during 2012–2018, salinity of the western Ross Sea has rebounded. This study adopts a global ocean‐sea ice model to investigate the causes of this salinity rebound. Model‐based surface salinity budget analysis indicates that the salinity rebound was driven by increased brine rejection from sea ice formation, triggered by nearly equal effects of local anomalous winds and surface heat flux. The local divergent wind anomalies promoted local sea ice formation by creating a thin ice area, while cooling heat flux anomaly decreased the surface temperature, increasing sea ice production as well. This highlights the importance of understanding local climate variability in projecting future dense shelf water change. Plain Language Summary Previous research linked the recent salinity increase in the western Ross Sea to weakened easterly winds from the Amundsen Sea. However, insufficient observations limit the further investigation of the linkage and underlying mechanisms between atmospheric forcing and shelf water salinity changes. In this study, we use a global ocean‐sea ice coupled model to investigate the factors affecting the recent western Ross Sea shelf water salinity increase. Based on a surface salinity budget analysis, we show that the recent salinity increase was supplied by brine rejection induced by increased sea ice formation, triggered almost equally by local anomalous winds and surface heat flux. The local wind anomalies induced a divergent motion in sea ice, reducing sea ice thickness and promoting local sea ice formation. Meanwhile, a negative heat flux anomaly from the atmosphere cools the surface, increasing sea ice production as well. Our study highlights the impact of local climate variability on dense shelf water. Moreover, the model experiment design and salinity budget analysis undertaken here provide an essential reference for identifying the major drivers of the shelf water salinity variations. Key Points Using a global ocean‐sea ice model, we simulate the recent rebound of Dense Shelf Water salinity in the western Ross Sea during 2012–2018 A model‐based salinity budget analysis reveals increased sea ice formation as the primary driver of the observed salinity rebound Experiments indicate that this increased sea ice formation is triggered by the combined effect of local wind stress and surface heat flux

One of the most evident effects of the cities expansions is the increasing urban temperatures, the so-called urban heat islands, affecting more significantly vulnerable populations. In this study, we examine heat vulnerability in Arica, a medium-sized coastal and desert city in Chile, using the Heat Vulnerability Index (HVI) methodology. We compared the performance of two methodological approaches: Principal Component Analysis (PCA) and Equal Weight (EW), as well as how this vulnerability is distributed among local climate zones. The results show that the general spatial pattern of heat vulnerability indices is moderately heterogeneous in the city. The PCA method grouped all indicators into four independent components that explain 71.7% of the total variance. Specifically, the PCA method overestimated vulnerability in the urban core of the city as well as in Cancha Rayada sector, while the EW method overestimated it in peripheral areas due to inherent differences in how each method weighs and processes spatial data. Regarding vulnerability to heat in the local climatic zones (LCZ) of Arica, both methods agreed that the Lightweight lowrise represents the class with the highest levels of vulnerability, notably in areas such as Cancha Rayada and Pedro Blanquier, the districts most susceptible to extreme heat. This study may help to provide results for future research, as well as to carry on adaptation and mitigation strategies for urban planning in Arica, in a context of implementation of the climate change adaptation and mitigation plans in Chile and the necessary actions at the urban level.

Smart urban planning needs to have a multicriteria-based approach to prevent the deteriorating local thermal climate. Maximizing the cooling potential using the available grey infrastructure would be the utmost priority of future smart cities. Remote sensing and GIS can be the appropriate tools to develop a climate-resilient urban planning framework. Studies are needed to include different features of vertical and horizontal landscaping to mitigate heat stress and enhance liveability at the city level. With this goal, the current work outlined a holistic approach to efficiently using green spaces with minimal reconstruction. The problem of regional climate threat was evaluated with urban heat island characterization. Moran’s I clustering identified nearly 12% of the study area to be under considerable heat stress during summer days. Multiple techniques, such as mapping local climate zones, segment mean shift-based roof extraction, vegetation index computation, solar azimuth-based green wall site selection, etc., were applied to formulate solutions and provide an integrated method for city-level environment enhancement. A considerable area was identified as most suitable for green roof cover, and it was also computed that the transition towards green roof at only these locations may bring down the maximum heat island intensity by 0.74 °C. Additionally, solar zenith, illumination effect, and building height information were combined to create a distinct method where vertical plantation would flourish exceptionally. A rigorous assessment of more than 130 urban green spaces further quantified the relation between landscape geometry and cooling effect to provide optimum green space designs for future urban planning.

This study assesses the accuracy of Local Climate Zone (LCZ) classification and its impact on land surface temperature (LST) analysis in Mediterranean cities using high-resolution ECOSTRESS data. Two classification methods were compared: a Geographic Information System (GIS)-based approach integrating high-resolution geospatial data and an LCZ map derived from WUDAPT. Discrepancies in LCZ classification influenced the spatial distribution of urban forms, with WUDAPT overestimating LCZ 6 (open low-rise) and LCZ 8 (large low-rise) while underrepresenting more compact urban types. LST analysis revealed distinct thermal responses between Milan and Lecce, underscoring the influence of urban morphology and local climate. Densely built zones (LCZ 2, LCZ 5) exhibited the highest temperatures, especially at night, while LCZ 8 also retained significant heat. Milan’s dense urban areas experienced pronounced nighttime overheating, whereas Lecce showed a clear daytime temperature gradient, with historic districts (LCZ 2) maintaining lower LST the light-colored and high thermal capacity of building materials. A Kruskal–Wallis test confirmed significant differences between the GIS-based and WUDAPT-derived LCZ maps, highlighting the impact of classification methodology and spatial resolution on LST analysis. These findings emphasize the need for multi-scale approaches to urban climate adaptation and mitigation, providing valuable advice for urban planners and policymakers in development of sustainable and climate-resilient cities. This research is also among the first to integrate ECOSTRESS data with LCZ maps to examine LST variations across spatial and temporal scales.

Foliar fungi on urban trees are important for tree health, biodiversity and ecosystem functioning. Yet, we lack insights into how urbanization influences foliar fungal communities. We created detailed maps of Stockholm region’s climate and air quality and characterized foliar fungi from mature oaks ( Quercus robur ) across climatic, air quality and local habitat gradients. Fungal richness was higher in locations with high growing season relative humidity, and fungal community composition was structured by growing season maximum temperature, NO 2 concentration and leaf litter cover. The relative abundance of mycoparasites and endophytes increased with temperature. The relative abundance of pathogens was lowest with high concentrations of NO 2 and particulate matter (PM 2.5 ), while saprotrophs increased with leaf litter cover. Our findings show that urbanization influences foliar fungi, providing insights for developing management guidelines to promote tree health, prevent disease outbreaks and maintain biodiversity within urban landscapes.