To cope with weather and climate-induced impacts as well as with air pollution in cities, the German research programme “Urban Climate Under Change” (UC2) aims at developing, testing and validating a ...new urban climate model, which is able to cover the full range of temporal and spatial scales of urban atmospheric processes. The project “Three-dimensional Observation of Atmospheric Processes in Cities” (3DO), which forms the module B of the UC2 research programme, aims at acquisition of comprehensive, accurate three-dimensional observational data sets on weather, climate and air quality in the German cities of Berlin, Hamburg and Stuttgart. Data sets from long-term observations and intense observation periods allow for evaluation of the performance of a new urban climate model called PALM‑4U that is developed by the project “Model-based city planning and application in climate change” (MOSAIK), which forms the module A of the UC2 research programme. This article focuses on collaborative activities for compilation of existing and acquisition of new observational data within the 3DO project.
In cities, vegetation temperature is important for quantifying water use, microclimates, and water and energy fluxes, as demonstrated by urban climate models and in situ studies. Remote sensing is ...capable of observing land surface temperatures (LST) across a city; however, its ability to quantify vegetation canopy temperatures is limited because of LST variability resulting from urban surface heterogeneity, differences in vegetation fraction and non-vegetated material, and the coarse resolution of available thermal imagery. This study is a large-scale analysis of urban surface composition and temperature variability across the Los Angeles, USA, metropolitan area (4466 km2). Sub-pixel fractions of two plant functional types (tree and turfgrass) and four urban materials (impervious surface, commercial roof, non-photosynthetic vegetation, and soil) were quantified using hyperspectral imagery (Airborne Visible/Infrared Imaging Spectrometer). Fractional cover gradients of plant types and non-vegetated materials were developed using 1.7 million pixels, from which we modeled LST changes using simultaneously collected thermal imagery (MODIS-ASTER Airborne Simulator). Vegetation LST variability was mapped by subtracting modeled LST from observed LST and investigated relative to building density and vegetation management. Overall, LST varied significantly among plant functional types and urban material types. Across heterogeneous mixtures, LST and vegetation fraction exhibited a negative, linear relationship, with the slopes of LST change showing significant differences between trees and turfgrass. The map of vegetation LST variability had a standard deviation of 3.5 °C, indicating significant variability across Los Angeles independent of vegetation type or fractional cover. Building density was observed to affect tree and turfgrass LST differently, while a negative relationship was observed between vegetation LST and irrigation (R2 = 0.55). Our results show that an LST signal of vegetation function, distinct from that of vegetation fractional cover, can be observed and modeled at city-scales in fractional mixture analysis, indicating potential for improved understanding of urban microclimates.
•We mapped 6 sub-pixel classes, including tree and turf, across Los Angeles (4466 km2).•Tree cover had a smaller effect on surface temperature than did turfgrass cover.•Mixed pixel temperature depended on both vegetation type and non-vegetated material.•City-wide canopy temperature variability was correlated with irrigation and income.•Building density affected tree temperatures more than it affected turf temperatures.
The urban context is often simplified or neglected in Building Energy Models (BEMs) due to the difficulties of taking accurately into account all the heat fluxes emanating from the environment. ...Oversimplifying the urban context can impact the accuracy of the BEM predictions. Nevertheless, several approaches can be used to allow for the impact of the urban environment on the dynamic behavior of a building, its heating and cooling demands, and thermal comfort. This state of the art review provides a critical overview of the different methods currently used to take into account the urban microclimate in building design simulations. First, both the microclimate and building models are presented, focusing on their assumptions and capabilities. Second, a few examples of coupling, performed between both modeling scales are analyzed. Last, the discussion highlights the differences obtained between simulations that take the urban context into consideration and those that simplify or neglect urban heat fluxes. The remaining scientific obstacles to a more effective consideration of the urban context impacting the BEMs are indicated.
•The local data produced by a selection of urban climate models (UCMs) are presented.•An analysis of how the urban context is taken into account in building energy models (BEMs) is given.•Several chaining or coupling strategies to link UCMs and BEMs are analyzed and compared.•Using local climate data leads to a noticeable impact on the thermal behavior of buildings.•Recommendations for better consideration of the urban context in BEMs are formulated.
Due to its concave topography, the climate in the Rouen region is affected by the impact of urbanization. The urbanized area occupies the bottom of the Seine Valley and extends onto slopes and ...plateaus. These topographic conditions contribute to the formation of well-differentiated local climates. To better understand the urban heat island, an expeditionary measurement campaign was carried out from 25 June to 11 August 2020. This campaign is based on the knowledge of the spatial distribution of temperatures in the city. These measurements were carried out according to different profiles and a specific programme. During this period, the region was affected by three heatwaves.. In this study, we present the results regarding the air temperatures obtained on 25 June 2020. The study also relies on the analysis of “Landsat 8” channel 11 satellite images, with a spatial resolution of 30 m to define surface temperatures. The results obtained during the measurement campaign show the importance of the differences between vegetated and built spaces. They also highlight hotspots (at traffic intersections and on main transport corridors – boulevards). The results obtained from the processing of satellite images show significant temperature differences between the industrial area and the rest of the city. There is an important thermal contrast between green spaces and asphalt squares in the city centre. There is a thermal lag between the “west” plateau, Cailly Valley, and the rest of the city.
Given increasing utility of numerical models to examine urban impacts on meteorology and climate, there exists an urgent need for accurate representation of seasonally and diurnally varying ...anthropogenic heating data, an important component of the urban energy budget for cities across the world. Incorporation of anthropogenic heating data as inputs to existing climate modeling systems has direct societal implications ranging from improved prediction of energy demand to health assessment, but such data are lacking for most cities. To address this deficiency we have applied a standardized procedure to develop a national database of seasonally and diurnally varying anthropogenic heating profiles for 61 of the largest cities in the United Stated (U.S.). Recognizing the importance of spatial scale, the anthropogenic heating database developed includes the city scale and the accompanying greater metropolitan area. Our analysis reveals that a single profile function can adequately represent anthropogenic heating during summer but two profile functions are required in winter, one for warm climate cities and another for cold climate cities. On average, although anthropogenic heating is 40% larger in winter than summer, the electricity sector contribution peaks during summer and is smallest in winter. Because such data are similarly required for international cities where urban climate assessments are also ongoing, we have made a simple adjustment accounting for different international energy consumption rates relative to the U.S. to generate seasonally and diurnally varying anthropogenic heating profiles for a range of global cities. The methodological approach presented here is flexible and straightforwardly applicable to cities not modeled because of presently unavailable data. Because of the anticipated increase in global urban populations for many decades to come, characterizing this fundamental aspect of the urban environment – anthropogenic heating – is an essential element toward continued progress in urban climate assessment.
•City-specific anthropogenic heating profiles are needed for urban climate modeling.•Diurnal and seasonal profiles of anthropogenic heating are developed for 61 US cities.•An extrapolation method for calculating international city profiles is introduced.
•Urbanization effects are expressed as the urban climate and land cover change.•The land cover change effect is recognized as the major effect.•Land cover change effect is stable in time ...series.•Urban climate effect has experienced an increasing trend for the past two decades.
Rapid urbanization leads to changes in the thermal characteristics of urban areas. Despite cities serving as natural laboratories to investigate responses to global change, it remains unclear how urbanization affects the thermal environment during global warming. Urbanization effects can be categorized as either the effect of urban climate (UCE) or land cover change (LCCE). This study proposes a conceptual framework for separating the urbanization effects on the thermal environment in 29 major Chinese cities. Results show that land surface temperature increases with impervious surface fractions in the urban area and decreases with vegetation fractions in rural areas, resulting in significant UCE and LCCE across cities, with LCCE approximately 1.3 to 5.7 times greater than UCE. These findings provide a comprehensive understanding of the thermal environment change caused by urbanization. To mitigate the negative effects of urbanization on the thermal environment, reducing land cover change would be more effective.
The local climate zone (LCZ) system provides a universal classification mechanism for urban and natural landscapes and plays an increasingly important role in urban climate research. With the rapid ...development of various LCZ mapping methods, a thorough survey of the LCZ mapping literature is urgently needed to better understand current progress, challenges, and future directions. Accordingly, this study provided a comprehensive review of the LCZ mapping literature during 2012–2021, with a detailed analysis on literature statistics, research topics, LCZ cities, and active research groups. Furthermore, remote sensing (RS)-based LCZ mapping methods were elucidated from feature sets, classification units, training areas, classification algorithms, and accuracy assessment; geographic information system (GIS)-based LCZ mapping methods were elaborated from LCZ parameters, basic spatial units, classification algorithms, and accuracy assessment; and their combination methods were summarized from two typical integration strategies. Finally, several challenges and future directions for LCZ mapping were discussed. The topics include exploiting multi-source RS and GIS data, determining appropriate LCZ mapping unit sizes, acquiring high-quality LCZ ground truth data, improving LCZ classification algorithms, optimizing LCZ parameters and subclasses, exploring the transferability of LCZ models, conducting global interannual LCZ mapping, and expanding the application of LCZs. The research community can quickly obtain abundant information on the LCZ mapping literature, understand the frameworks of different LCZ mapping methods, and inspire new directions for future research.
•Progress, challenges, and prospects for LCZ mapping are systematically reviewed.•Frameworks of RS- and GIS-based LCZ mapping methods are elaborated.•Data sources, mapping unit sizes, classification algorithms, and validation strategies are analyzed.•Deep learning models, domain adaption methods, and benchmark datasets improve LCZ mapping.•GEE, deep learning, crowdsourcing, and collaboration facilitate global interannual LCZ mapping.
•LCZ mapping is considered as remote sensing scene classification instead of pixel-based classification to fully exploit the urban environment context.•A convolutional neural network integrating ...residual learning and the Squeeze-and-Excitation block is proposed for LCZ mapping.•Image sizes of 32×32 to 64×64 corresponding to 320×320 to 640×640 m2 areas are found suitable for LCZ mapping depending on the region.•LCZ maps are generated for fifteen cities in China.
China, with the world’s largest population, has gone through rapid development in the last forty years and now has over 800 million urban citizens. Although urbanization leads to great social and economic progress, they may be confronted with other issues, including extra heat and air pollution. Local climate zone (LCZ), a new concept developed for urban heat island research, provides a standard classification system for the urban environment. LCZs are defined by the context of the urban environment; the minimum diameter of an LCZ is expected to be 400–1,000 m so that it can have a valid effect on the urban climate. However, most existing methods (e.g., the WUDAPT method) regard this task as pixel-based classification, neglecting the spatial information. In this study, we argue that LCZ mapping should be considered as a scene classification task to fully exploit the environmental context. Fifteen cities covering 138 million population in three economic regions of China are selected as the study area. Sentinel-2 multispectral data with a 10 m spatial resolution are used to classify LCZs. A deep convolutional neural network composed of residual learning and the Squeeze-and-Excitation block, namely the LCZNet, is proposed. We obtained an overall accuracy of 88.61% by using a large image (48×48 corresponding to 480×480 m2) as the representation of an LCZ, 7.5% higher than that using a small image representation (10×10) and nearly 20% higher than that obtained by the standard WUDAPT method. Image sizes from 32×32 to 64×64 were found suitable for LCZ mapping, while a deeper network achieved better classification with larger inputs. Compared with natural classes, urban classes benefited more from a large input size, as it can exploit the environment context of urban areas. The combined use of the training data from all three regions led to the best classification, but the transfer of LCZ models cannot achieve satisfactory results due to the domain shift. More advanced domain adaptation methods should be applied in this application.
Sealed surfaces greatly influence Urban Heat Island (UHI) effects. In this respect, both the composition and spatial patterns of anthropogenic land use play an important role in local thermal ...pattern. The urban environments' climate change adaptation strategy needs adequate knowledge systems urban planners can use to organise and design more resistant and resilient urban spaces. This study examined the relationship between Land Surface Temperature (LST) variations and increasing urbanised areas during the period 2001–2011 in the Po Valley, utilising different urban growth spatial patterns (UGSP). Remotely sensed LST data was obtained from MODIS (MODerate Resolution Imaging Spectroradiometer) at a resolution of 1 km/pixel for an 11 year-period, from 2001 to 2011, with urbanisation data from the ISTAT map (nominal scale 1:10,000) respectively for the 2001 and 2011 time sections. The relationship between dependent (mean annual daytime, nighttime and daily values) and independent (urbanised areas) variables were investigated through ANOVA test and post-hoc analysis (p < 0.01) for all defined UGSP. Results showed that there is a decreasing LST range (in all conditions) associated with progressive increase of urbanised areas. Furthermore, clustered patterns urban growth have a statistically significant relationship with daytime, nighttime and daily conditions while dispersed pattern urban growth have the same with nighttime only. The outcomes are helpful for understanding the effects of different UGSP, which have significant implications for urban planning, and identifying the critical territorial sectors in need of sustainable mitigation actions.
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•Between 2001 and 2011, the Po Valley area saw an increase of 630 km2 in urban areas.•The prevailing model of urban growth is the UDI 0 (aggregated urban growth).•The LST in daytime conditions was an average increase of +1,36 °C in the study area.•Quantitative framework between increased urbanised areas and LST change performed.•The UDI + (urban dispersion) shows an increase in the minimum differential recorded.
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