Showing papers on "Urban climate published in 2022"

Urbanization Impact on Regional Climate and Extreme Weather: Current Understanding, Uncertainties, and Future Research Directions

Abstract: Urban environments lie at the confluence of social, cultural, and economic activities and have unique biophysical characteristics due to continued infrastructure development that generally replaces natural landscapes with built-up structures. The vast majority of studies on urban perturbation of local weather and climate have been centered on the urban heat island (UHI) effect, referring to the higher temperature in cities compared to their natural surroundings. Besides the UHI effect and heat waves, urbanization also impacts atmospheric moisture, wind, boundary layer structure, cloud formation, dispersion of air pollutants, precipitation, and storms. In this review article, we first introduce the datasets and methods used in studying urban areas and their impacts through both observation and modeling and then summarize the scientific insights on the impact of urbanization on various aspects of regional climate and extreme weather based on more than 500 studies. We also highlight the major research gaps and challenges in our understanding of the impacts of urbanization and provide our perspective and recommendations for future research priorities and directions.城市环境位于社会、文化和经济活动的结合点,城市下垫面具有独特的生物物理特征。在城市化过程中持续的基础设施建设导致自然景观被建筑物替代。在过去很长时间,绝大部分城市影响天气气候的研究和城市热岛效应(城市及上空温度高于周边地区)有关。除了城市热岛效应,城市化也影响大气湿度、风、边界层结构、云的形成、污染物扩散、降水和暴雨。在这篇综述文章中,我们阅览了超过五百篇文献,从观测和模拟两个方面,首先介绍了用于城市化及影响研究的数据资料和方法,总结了城市化影响区域气候和极端天气的各个领域的科学要点。我们也例举了在理解城市化影响方面目前存在的主要问题和挑战,提出了相应的未来研究重点和方向。.

A global dataset of annual urban extents (1992–2020) from harmonized nighttime lights

Abstract: Abstract. Understanding the spatiotemporal dynamics of global urbanization over a long time series is increasingly important for sustainable development goals. The harmonized nighttime light (NTL) time-series composites created by fusing multi-source NTL observations provide a long and consistent record of the nightscape for characterizing and understanding global urban dynamics. In this study, we generated a global dataset of annual urban extents (1992–2020) using consistent NTL observations and analyzed the spatiotemporal patterns of global urban dynamics over nearly 30 years. The urbanized areas associated with locally high intensity human activities were mapped from the global NTL time-series imagery using a new stepwise-partitioning framework. This framework includes three components: (1) clustering of NTL signals to generate potential urban clusters, (2) identification of optimal thresholds to delineate annual urban extents, and (3) check of temporal consistency to correct pixel-level urban dynamics. We found that the global urban land area percentage of the Earth's land surface rose from 0.22 % to 0.69 % between 1992 and 2020. Urban dynamics over the past 3 decades at the continent, country, and city levels exhibit various spatiotemporal patterns. Our resulting global urban extents (1992–2020) were evaluated using other urban remote sensing products and socioeconomic data. The evaluations indicate that this dataset is reliable for characterizing spatial extents associated with intensive human settlement and high-intensity socioeconomic activities. The dataset of global urban extents from this study can provide unique information to capture the historical and future trajectories of urbanization and to understand and tackle urbanization impacts on food security, biodiversity, climate change, and public well-being and health. This dataset can be downloaded from https://doi.org/10.6084/m9.figshare.16602224.v1 (Zhao et al., 2021).

A global map of local climate zones to support earth system modelling and urban-scale environmental science

Abstract: Abstract. There is a scientific consensus on the need for spatially detailed information on urban landscapes at a global scale. These data can support a range of environmental services, since cities are places of intense resource consumption and waste generation and of concentrated infrastructure and human settlement exposed to multiple hazards of natural and anthropogenic origin. In the face of climate change, urban data are also required to explore future urbanization pathways and urban design strategies in order to lock in long-term resilience and sustainability, protecting cities from future decisions that could undermine their adaptability and mitigation role. To serve this purpose, we present a 100 m-resolution global map of local climate zones (LCZs), a universal urban typology that can distinguish urban areas on a holistic basis, accounting for the typical combination of micro-scale land covers and associated physical properties. The global LCZ map, composed of 10 built and 7 natural land cover types, is generated by feeding an unprecedented number of labelled training areas and earth observation images into lightweight random forest models. Its quality is assessed using a bootstrap cross-validation alongside a thematic benchmark for 150 selected functional urban areas using independent global and open-source data on surface cover, surface imperviousness, building height, and anthropogenic heat. As each LCZ type is associated with generic numerical descriptions of key urban canopy parameters that regulate atmospheric responses to urbanization, the availability of this globally consistent and climate-relevant urban description is an important prerequisite for supporting model development and creating evidence-based climate-sensitive urban planning policies. This dataset can be downloaded from https://doi.org/10.5281/zenodo.6364594 (Demuzere et al., 2022a).

Rapid urbanization and climate change significantly contribute to worsening urban human thermal comfort: A national 183-city, 26-year study in China

Abstract: Urban residents are gradually being exposed to increasing urban high temperatures and extreme heatwave events under rapid urbanization and global warming. Although there is an increase in air and surface temperatures observed, spatiotemporal changes in urban human thermal comfort and their drivers are rarely considered when assessing the urban thermal environment, especially at a national scale in China. Based on weather stations, we combined daily meteorological data, including air temperature, solar radiation, wind speed, and humidity, to comprehensively assess the annual dynamics of urban thermal comfort and their relationship with rapid urbanization and climate change in 183 Chinese cities from 1990 to 2016. Our results show that urban air temperature and solar radiation have increased, and urban humidity and wind speed have decreased at the national scale. Following these changes, urban residents' thermal comfort is deteriorating, with physiological equivalent temperature and uncomfortable days increasing in 68% and 59% of cities, respectively, during summer in China, predominantly located in temperate monsoon and continental climatic zones. The worsening of urban thermal comfort was largely explained by climate change, and rapid urbanization contributed 10.9% in our study. Climate change (e.g., global warming, precipitation, and wind speed decrease) and rapid urbanization had positive effects (P < 0.05) on the deteriorative urban thermal environment. Our findings could enrich the knowledge on spatiotemporal changes in the urban thermal environment under climate change and rapid urbanization.

Global climate-driven trade-offs between the water retention and cooling benefits of urban greening

Abstract: Urban greening can potentially help mitigate heat-related mortality and flooding facing the >4 billion urban population worldwide. However, the geographical variation of the relative combined hydrological and thermal performance benefits of such interventions are unknown. Here we quantify globally, using a hydrological model, how climate-driven trade-offs exist between hydrological retention and cooling potential of urban greening such as green roofs and parks. Using a Budyko framework, we show that water retention generally increases with aridity in water-limited environments, while cooling potential favors energy-limited climates. Our models suggest that common urban greening strategies cannot yield high performance simultaneously for addressing both urban heat-island and urban flooding problems in most cities globally. Irrigation, if sustainable, may enhance cooling while maintaining retention performance in more arid locations. Increased precipitation variability with climate change may reduce performance of thinner green-infrastructure more quickly compared to greened areas with thicker soils and root systems. Our results provide a conceptual framework and first-order quantitative guide for urban development, renewal and policymaking.

Greenhouse gas emissions from global cities under SSP/RCP scenarios, 1990 to 2100

Abstract: • Urban areas have accounted for the majority of global GHG emissions in 2015 (61.8%). • Urban emission scenarios are established within seven pathway combinations to 2100. • The scenarios have implications for urban mitigation and climate neutrality targets. • Two regions can represent up to 73.3% of cumulative consumption-based urban emissions during 2020–2100. • The study provides a new approach for quantifying urban emissions within scenarios. Projections of greenhouse gas (GHG) emissions are critical to enable a better understanding and anticipation of future climate change under different socio-economic conditions and mitigation strategies. The climate projections and scenarios assessed by the Intergovernmental Panel on Climate Change, following the Shared Socioeconomic Pathway (SSP)-Representative Concentration Pathway (RCP) framework, have provided a rich understanding of the constraints and opportunities for policy action. However, the current emissions scenarios lack an explicit treatment of urban emissions within the global context. Given the pace and scale of urbanization, with global urban populations expected to increase from about 4.4 billion today to about 7 billion by 2050, there is an urgent need to fill this knowledge gap. Here, we estimate the share of global GHG emissions driven by urban areas from 1990 to 2100 based on the SSP-RCP framework. The urban consumption-based GHG emissions are presented in five regional aggregates and based on a combination of the urban population share, 2015 urban per capita CO 2 eq carbon footprint, SSP-based national CO 2 eq emissions, and recent analysis of urban per capita CO 2 eq trends. We find that urban areas account for the majority of global GHG emissions in 2015 (61.8%). Moreover, the urban share of global GHG emissions progressively increases into the future, exceeding 80% in some scenarios by the end of the century. The combined urban areas in Asia and Developing Pacific, and Developed Countries account for 65.0% to 73.3% of cumulative urban consumption-based emissions between 2020 and 2100 across the scenarios. Given these dominant roles, we describe the implications for potential urban mitigation in each of the scenario narratives in order to meet the goal of climate neutrality within this century.

Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model

Abstract: Urban heat island (UHI), driving by urbanization, plays an important role in urban sustainability under climate change. However, the quantification of UHI's response to urbanization is still challenging due to the lack of robust and continuous temperature and urbanization datasets and reliable quantification methods. This study proposed a framework to quantify the response of surface UHI (SUHI) to urban expansion using the annual temperate cycle model. We built a continuous annual SUHI series at the buffer level from 2003 to 2018 in the Jing-Jin-Ji region of China using MODIS land surface temperature and imperviousness derived from Landsat. We then investigated the spatiotemporal dynamic of SUHI under urban expansion and examined the underlying mechanism. Spatially, the largest SUHI interannual variations occurred in suburban areas compared to the urban center and rural areas. Temporally, the increase in SUHI under urban expansion was more significant in daytime compare to nighttime. We found that the seasonal variation of SUHI was largely affected by the seasonal variations of vegetation in rural areas and the interannual variation was mainly attributed to urban expansion in urban areas. Additionally, urban greening led to the decrease in summer daytime SHUI in central urban areas. These findings deepen the understanding of the long-term spatiotemporal dynamic of UHI and the quantitative relationship between UHI and urban expansion, providing a scientific basis for prediction and mitigation of UHI.

Future air temperature projection in high-density tropical cities based on global climate change and urbanization – a study in Singapore

Abstract: Urban air temperature projection is essential to prepare cities for future heat risks. This study aims to anticipate future air temperature increment contributed by climate change and urbanization. First, we identified the rural area in Singapore by historical data, and downscaled global/regional modelling results to investigate climate change at the identified rural area. Representative concentration pathway 8.5 was chosen at the downscaling study for the worst case scenario. Results indicate air temperature at the rural area will increase by 0.4–0.6 °C in 2030s, 1.2–1.6 °C in 2050s, and 2.2–3.8 °C in 2080s. Secondly, we estimated future urbanization based on master planning by planning department, and associated urbanization with air temperature using linear regression. Based on planned plot ratio for future, we calculated sky view factor and site coverage ratio as urban morphology and planning index respectively. Linear regression analysis indicates that air temperature at urban areas could increase 0.05 °C - 0.79 °C in 2030s due to various urbanization in Singapore. This study conducted projections, which are based on global/regional modelling results and associated closely with urban planning. Projection results indicate that pre-emptive urban planning and design strategies are needed at the districts with potential heat risk and enables urban planners to make evidence-based decisions.

Surface warming in global cities is substantially more rapid than in rural background areas

Abstract: Abstract Warming trends in cities are influenced both by large-scale climate processes and by local-scale urbanization. However, little is known about how surface warming trends of global cities differ from those characterized by weather observations in the rural background. Here, through statistical analyses of satellite land surface temperatures (2002 to 2021), we find that the mean surface warming trend is 0.50 ± 0.20 K·decade −1 (mean ± one S.D.) in the urban core of 2000-plus city clusters worldwide, and is 29% greater than the trend for the rural background. On average, background climate change is the largest contributor explaining 0.30 ± 0.11 K·decade −1 of the urban surface warming. In city clusters in China and India, however, more than 0.23 K·decade −1 of the mean trend is attributed to urban expansion. We also find evidence of urban greening in European cities, which offsets 0.13 ± 0.034 K·decade −1 of background surface warming.

Urbanization Aggravates Effects of Global Warming on Local Atmospheric Drying

Abstract: Urbanization is known to cause ‘Urban Heat Island’ (UHI) and elevate storm runoff. However, how urbanization influences local atmospheric moisture under global warming is not well-understood. By examining 140 paired urban-rural weather station data (1980–2018), this study finds significant declines in atmospheric humidity or the ‘Urban Dry Island’ (UDI) in multiple large city clusters across a large climatic gradient in China. Global warming, UHI, and reduction in local evapotranspiration and water vapor supplies all contribute to the observed UDI. The magnitude and frequency of UDI are more pronounced in humid regions than arid regions due to differences in background climate and vegetation characteristics that affect both energy and water balances at land surfaces. Mitigating the negative effects of UDI and UHI should focus on restoring the evapotranspiration power of urban ecosystems. The present empirical analyses provide new evidence and mechanistic understanding of environmental change in urban ecosystems.

Many roads to Paris: Explaining urban climate action in 885 European cities

Abstract: Research on urban climate action has identified a broad range of potential factors explaining why and how local governments decide to tackle climate change. However, empirical evidence linking such factors in order to explain actual urban climate action has so far been mixed. To address this roadblock, our paper relies on a novel approach, postulating that different configurations of factors may lead to the same outcome (“equifinality”), through a qualitative comparative analysis (QCA). It is based on an available data set of local climate mitigation plans in 885 European cities. We find that urban climate action is systematically associated with four qualitatively different configurations of factors, each with its own consistent narrative (“networker cities”, “green cities”, “lighthouse cities”, “fundraising cities”). Crucially, some factors play a positive role in some configurations, a negative in others, and no role in further configurations (e.g., whether a city is located in a country with supportive national climate policies). This confirms that there is no single explanation for urban climate action. Achieving greater robustness in empirical research about urban climate action may thus require a shift, both conceptual and methodological, to the interactions between factors, allowing for different explanations in different contexts.

Estimating the cooling effect magnitude of urban vegetation in different climate zones using multi-source remote sensing

Abstract: Vegetation is effective in mitigating the urban heat island effect by canopy shade and evapotranspiration. Acquiring the vegetation cooling effect magnitude (∆T) quickly and accurately has been the focus of thermal mitigation in urban areas. Traditional field observations are usually restricted to one or few cities, while large-scale assessment models mostly focus on inconsistent parameters, leading to contradictory results. In this study, we collected 3970 samples of observed vegetation-induced ∆T worldwide to assess their relationship with leaf area index (LAI) and evapotranspiration (ET) for different vegetation types within various climate zones (arid, semi-arid/humid, humid, and extreme humid zones). Results showed that urban vegetation ET and LAI have diverse correlations (i.e., linear/nonlinear) with ∆T, and the ET-cooling and LAI-shading effect dominate differently in each climate zone. In addition, urban vegetation cooling effect empirical models were established based on a multivariate regression analysis using the above two parameters. Application of global seasonal urban vegetation cooling effect analysis based on these empirical models enable us to readily achieve ∆T on various scales around the world. The finding of this study can be used as guidance to select the appropriate vegetation types for urban green space design and construction to cool the thermal environments in urban areas.

Lower Urban Humidity Moderates Outdoor Heat Stress

Abstract: Surface temperature is often used to examine heat exposure in multi-city studies and for informing urban heat mitigation efforts due to scarcity of urban air temperature measurements. Cities also have lower relative humidity, traditionally not accounted for in large-scale observational urban heat risk assessments. Here, using crowdsourced measurements from over 40,000 weather stations in ≈600 urban clusters in Europe, we show the moderating effect of this urbanization-induced humidity reduction on outdoor heat stress during the 2019 heatwave. We demonstrate that daytime differences in heat index between urban clusters and their surroundings are weak, and associations of this urban-rural difference with background climate, generally examined from the surface temperature perspective, are diminished due to moisture feedbacks. We also examine the spatial variability of surface temperature, air temperature, and heat index within these clusters—relevant for detecting hotspots and potential disparities in heat exposure—and find that surface temperature is a poor proxy for the intra-urban distribution of heat index during daytime. Finally, urban vegetation shows much weaker (∼1/6th as strong) associations with heat index than with surface temperature, which has broad implications for optimizing urban heat stress mitigation strategies. These findings are valid for operational metrics of heat stress for shaded conditions (apparent temperature and humidex), thermodynamic proxies (wet-bulb temperature), and empirical heat indices. Based on this large-scale empirical evidence, surface temperature, used due to the lack of better alternatives, may not be suitable for accurately informing heat mitigation strategies within and across cities, necessitating more urban-scale observations and better urban-resolving models.