Even though it is known that urbanization affects rainfall, studies vary regarding the magnitude and location of rainfall change. To develop a comprehensive understanding of rainfall modification due ...to urbanization, a systematic meta-analysis is undertaken. The initial search identified over 2000 papers of which 489 were carefully analyzed. From these papers, 85 studies from 48 papers could be used in a quantitative meta-analysis assessment. Results were analyzed for case studies versus climatological assessments, observational versus modeling studies and for day versus night. Results highlight that urbanization modifies rainfall, such that mean precipitation is enhanced by 18% downwind of the city, 16% over the city, 2% on the left and 4% on the right with respect to the storm direction. The rainfall enhancement occurred approximately 20-50 km from the city center. Study results help develop a more complete picture of the role of urban processes in rainfall modification and highlight that rainfall increases not only downwind of the city but also over the city. These findings have implications for urban flooding as well as hydroclimatological studies. This meta-analysis highlights the need for standardizing how the results are presented in future studies to aid the generalization of findings.
Many streams worldwide are affected by heavy metal contamination, mostly due to past and present mining activities. Here we present a meta-analysis of 38 studies (reporting 133 cases) published ...between 1978 and 2014 that reported the effects of heavy metal contamination on the decomposition of terrestrial litter in running waters. Overall, heavy metal contamination significantly inhibited litter decomposition. The effect was stronger for laboratory than for field studies, likely due to better control of confounding variables in the former, antagonistic interactions between metals and other environmental variables in the latter or differences in metal identity and concentration between studies. For laboratory studies, only copper + zinc mixtures significantly inhibited litter decomposition, while no significant effects were found for silver, aluminum, cadmium or zinc considered individually. For field studies, coal and metal mine drainage strongly inhibited litter decomposition, while drainage from motorways had no significant effects. The effect of coal mine drainage did not depend on drainage pH. Coal mine drainage negatively affected leaf litter decomposition independently of leaf litter identity; no significant effect was found for wood decomposition, but sample size was low. Considering metal mine drainage, arsenic mines had a stronger negative effect on leaf litter decomposition than gold or pyrite mines. Metal mine drainage significantly inhibited leaf litter decomposition driven by both microbes and invertebrates, independently of leaf litter identity; no significant effect was found for microbially driven decomposition, but sample size was low. Overall, mine drainage negatively affects leaf litter decomposition, likely through negative effects on invertebrates.
•A meta-analysis was done to assess the effects of heavy metals on litter decomposition.•Heavy metals significantly and strongly inhibited litter decomposition in streams.•The magnitude of the effect depended on methodological and environmental conditions.•The effects were significantly stronger for laboratory than for field studies.•Mine drainage inhibited leaf (not wood) and total (not microbial) decomposition.
Heavy metals have negative effects on litter decomposition, but magnitude of the effect depends on methodological and environmental conditions.
Hydrometeorological impacts due to urbanization for cities close to complex terrain are poorly understood due to the complexities of terrain‐related circulation and urban perturbations of atmospheric ...flow. In this study, we examine urban impacts on extreme monsoon rainfall and the resultant flooding over central Arizona based on high‐resolution atmospheric and hydrological model simulations. Strong positive rainfall anomalies at the urban‐rural interface downwind of the city are mainly related to dynamic effects (increased surface roughness) on convective outflow boundaries. Urban‐related thermodynamic disturbances slightly increase rain rates over the downtown core of Phoenix. Contrasting rainfall anomalies for two consecutive storm episodes highlight the importance of flow regime analysis in understanding urban impacts on extreme rainfall in complex terrain. Urban‐induced rainfall anomalies result in amplification of flood peak magnitudes by as much as a factor of 2 for Phoenix watersheds. Our results highlight the urban impacts on regional flood hydrology through land‐atmosphere interactions.
Key Points
Contrasting rainfall anomalies for two consecutive storm episodes in the Phoenix metropolitan region show a strong dependence on flow regime
The dynamic perturbation to terrain‐related circulations dominates urban‐induced rainfall anomalies in complex terrain
The impacts of urban‐induced rainfall anomalies on flood response are assessed through hydrological modeling experiments
The impacts of cities and climate warming on extreme rainfall under strong synoptic conditions are not well understood. Here, we carry out the first model‐based assessment of urban impacts on extreme ...flood‐producing storms for the European region. We identify contrasting roles of cities and climate warming in determining the space‐time variability of the July 14, 2021 storm over western Europe. While climate warming dominates the temporal rainfall variability over the domain, cities further enhance total rainfall over their suburbs by dynamically modifying the intensity and position of moisture convergence. There is a cyclonic structure of flow anomalies around the city induced by urban surface roughness. The rainfall anomaly induced by the interactive impacts of cities and climate warming is 50% larger than by those urban impacts alone. We highlight a need to develop a regional framework by reconciling the emerging urban‐rural contrasts in vulnerability and preparedness to hydrometeorological extremes.
Plain Language Summary
Western Europe experienced catastrophic extreme rainfall and flooding during mid‐July 2021 with >200 fatalities, making it one of the deadliest floods in European history. Based on high‐resolution weather simulations, we show urbanization plays an important role in enhancing rainfall and flood hazards for this storm over the suburbs of the Rotterdam‐Brussels‐Cologne metropolitan region. The rainfall anomalies are a result of both dynamical and thermo‐dynamical feedbacks from urban roughness, heat, and the mesoscale convergence. We show that the impact of urbanization on rainfall is different from that of global warming, with the latter mainly influencing the temporal variability of rainfall over the entire domain. Urban‐induced rainfall anomalies are more pronounced under a warmer climate compared to the pre‐industrial climate conditions. This is the first model‐based study to show strong urban signatures in extreme rainfall for the European region. The role of cities has not been adequately considered in the attribution analysis of weather extremes. Future adaptation and mitigation strategies to climate change need to consider the emerging urban‐rural contrasts in the exposure and vulnerability of hydrometeorological extremes.
Key Points
We present the first model‐based assessment of urban impacts on extreme rainfall for the European region
Climate change dominates temporal rainfall variability over the entire domain, while cities enhance total rainfall over their suburbs
We reveal an underappreciated role of cities in shaping urban‐rural contrasts of extreme rainfall and flood risks in a warming climate
Prior evaluations of the relationship between COVID-19 and weather indicate an inconsistent role of meteorology (weather) in the transmission rate. While some effects due to weather may exist, we ...found possible misconceptions and biases in the analysis that only consider the impact of meteorological variables alone without considering the urban metabolism and environment. This study highlights that COVID-19 assessments can notably benefit by incorporating factors that account for urban dynamics and environmental exposure. We evaluated the role of weather (considering equivalent temperature that combines the effect of humidity and air temperature) with particular consideration of urban density, mobility, homestay, demographic information, and mask use within communities. Our findings highlighted the importance of considering spatial and temporal scales for interpreting the weather/climate impact on the COVID-19 spread and spatiotemporal lags between the causal processes and effects. On global to regional scales, we found contradictory relationships between weather and the transmission rate, confounded by decentralized policies, weather variability, and the onset of screening for COVID-19, highlighting an unlikely impact of weather alone. At a finer spatial scale, the mobility index (with the relative importance of 34.32%) was found to be the highest contributing factor to the COVID-19 pandemic growth, followed by homestay (26.14%), population (23.86%), and urban density (13.03%). The weather by itself was identified as a noninfluential factor (relative importance < 3%). The findings highlight that the relation between COVID-19 and meteorology needs to consider scale, urban density and mobility areas to improve predictions.
Modern urban climatology is a part of boundary-layer climatology with a focus on the urban effects on the atmosphere. The best known of these effects is the urban heat island (UHI), which has been a ...subject of study for more than 200 years and may be categorised into air, surface and substrate types. Progress on this topic has occurred in various phases associated with theoretical developments, improvements in technology (instruments and computing) and study design, to isolate the causative drivers. The history of the field can be categorised into response-based (descriptive) and process-based (analytic) periods associated with hypothesis generation and testing, respectively. Myrup’s paper on simulating the UHI, published in 1969, is at the forefront of this shift in approach and is the first application of numerical modelling to the topic. Its computational methods place the UHI within the context of the surface energy budget and the exchanges of energy, urban characteristics, and the substrate as well as overlying air. The paper is a classic that had considerable impact on the approach that geographical climatology took to examining the UHI; however, it is not without its limitations Careful reading of Myrup's work provides insights into how the field has evolved in the last 50 years. In particular the recurring issues associated with conceputalising the urban thermal effect and challenge of comparing models results with field observations. Remarkably, key urban climate questions on how to cool cities, how to plan cities for future climate, and the factors that impact UHI are still being studied, albeit with more sophisticated models. A numerical model of the urban heat island is part of a rich literature on the UHI that illustrates the development of the urban climate science that deserves to be read and cited.
Cities foster economic growth. However, growing cities also contribute to air pollution and climate change. The paper provides a perspective regarding the opportunity available in addressing the ...urban air quality management (UAQM) issues using smart city framework in the context of ‘urban computing’. Traditionally, UAQM has been built on sparse regulatory monitoring, enhanced with satellite data and forecast models. The ‘Fourth Industrial Revolution’ (4IR) technologies such as Internet of Things (IoT), big data, artificial intelligence, smartphones, social and cloud computing are reshaping urban conglomerates, worldwide. Cities can harness these ubiquitous technologies in concert with traditional methods for betterment of air quality governance and to improve quality of life. This paper discusses the role of urban computing in UAQM through a review of scientific publications and ‘grey literature’ from technical reports of governments, international organizations and institutional websites. It provides an interdisciplinary knowledge repository on urban computing applications for air quality functions. It highlights the potential of integrated technologies in enabling data driven, strategic and real-time mitigation governance actions and helping citizens to take informed decisions. It recommends ‘fit for the purpose’ multitechnology framework for UAQM services in emerging smart cities.
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•Review of urban computing applications for air quality management services in smart cities.•Data driven smart cities have a potential to enable emission reductions and climate change mitigation.•IoT, satellite, cloud computing and hybrid models with AI/ML methods are improving air quality and the impact assessment.•AI enables newer methods of urban data acquisition using IoT, mobile phones, crowd sourcing, and social media.•Need for inter-disciplinary research on urban computing framework in air quality management as smart city services.
Croplands are important in land‐atmosphere interactions and in the modification of local and regional weather and climate; however, they are poorly represented in the current version of the coupled ...Weather Research and Forecasting/Noah with multiparameterization (Noah‐MP) land surface modeling system. This study introduced dynamic corn (Zea mays) and soybean (Glycine max) growth simulations and field management (e.g., planting date) into Noah‐MP and evaluated the enhanced model (Noah‐MP‐Crop) at field scales using crop biomass data sets, surface heat fluxes, and soil moisture observations. Compared to the generic dynamic vegetation and prescribed‐leaf area index (LAI)‐driven methods in Noah‐MP, the Noah‐MP‐Crop showed improved performance in simulating leaf area index (LAI) and crop biomass. This model is able to capture the seasonal and annual variability of LAI and to differentiate corn and soybean in peak values of LAI as well as the length of growing seasons. Improved simulations of crop phenology in Noah‐MP‐Crop led to better surface heat flux simulations, especially in the early period of growing season where current Noah‐MP significantly overestimated LAI. The addition of crop yields as model outputs expand the application of Noah‐MP‐Crop to regional agriculture studies. There are limitations in the use of current growing degree days (GDD) criteria to predict growth stages, and it is necessary to develop a new method that combines GDD with other environmental factors, to more accurately define crop growth stages. The capability introduced in Noah‐MP allows further crop‐related studies and development.
Key Points
1.Noah‐MP‐Crop is able to capture the seasonal and annual variability of crop‐specific LAI and biomass.
2.The improved estimation of LAI in Noah‐MP‐Crop led to more accurate surface sensible and latent heat flux simulations.
3.It is necessary to incorporate field management information in Cropland related simulations.
The authors have analyzed twentieth-century temperature and precipitation trends and long-term persistence from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project ...(CMIP5). This study is focused on continental areas (60°S–60°N) during 1930–2004 to ensure higher reliability in the observations. A nonparametric trend detection method is employed, and long-term persistence is quantified using the Hurst coefficient, taken from the hydrology literature. The authors found that the multimodel ensemble–mean global land–average temperature trend (0.07°C decade−1) captures the corresponding observed trend well (0.08°C decade−1). Globally, precipitation trends are distributed (spatially) at about zero in both the models and in the observations. There are large uncertainties in the simulation of regional-/local-scale temperature and precipitation trends. The models’ relative performances are different for temperature and precipitation trends. The models capture the long-term persistence in temperature reasonably well. The areal coverage of observed long-term persistence in precipitation is 60% less (32% of land area) than that of temperature (78%). The models have limited capability to capture the long-term persistence in precipitation. Most climate models underestimate the spatial variability in temperature trends. The multimodel ensemble–average trend generally provides a conservative estimate of local/regional trends. The results of this study are generally not biased by the choice of observation datasets used, including Climatic Research Unit Time Series 3.1; temperature data from Hadley Centre/Climatic Research Unit, version 4; and precipitation data from Global Historical Climatology Network, version 2.
Celotno besedilo
Dostopno za:
BFBNIB, DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Anthropogenic changes are likely to intensify rainfall extremes, posing a risk to human, environmental and urban systems. Understanding the impact of urbanization on rainfall extremes is critical for ...both reliable climate projections as well as sustainable urban development. This study presents the unexplored impacts of changes arising in urban areas on rainfall extremes over the Contiguous United States. The results show a 2.7-fold higher probability of exceeding a 25% change in 50 year rainfall events over urban areas than over rural areas. Spatially, the changes in rainfall extremes over the central, northeast central, southeast, and northwest central zones were more pronounced due to urbanization. Statistical analyses highlight a positive relationship between changes in rainfall extremes and urbanization within a set of concentric ring buffers around rain gauge stations. Here, we show that urbanization, even though a local feature, influences the mesoscale meteorological setting; and, is statistically associated with an intensification of rainfall extremes across the Contiguous United States.
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