Highly resolved WRF-BEP/BEM simulations over Barcelona urban area with LCZ

Ribeiro, Isabel; Martilli, Alberto; Falls, Marcus; Zonato, Andrea; Villalba, Gara

doi:10.1016/j.atmosres.2020.105220

Cited by 75 publications

(22 citation statements)

References 28 publications

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“…The same results were also found for Berlin in a recent work [29]. The further introduction of a Building Energy Model (BEM) coupled with BEP minimizes the RMSE for 2-m temperature and 2-m relative humidity in Barcelona [30].…”

Section: Introductionsupporting

confidence: 78%

Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities

Garbero¹,

Milelli

Mercogliano

et al. 2021

Atmosphere

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The increase in built surfaces constitutes the main reason for the formation of the Urban Heat Island (UHI), that is a metropolitan area significantly warmer than its surrounding rural areas. The urban heat islands and other urban-induced climate feedbacks may amplify heat stress and urban flooding under climate change and therefore to predict them correctly has become essential. Currently in the COSMO model, cities are represented by natural land surfaces with an increased surface roughness length and a reduced vegetation cover, but this approach is unable to correctly reproduce the UHI effect. By increasing the model resolution, a representation of the main physical processes that characterize the urban local meteorology should be addressed, in order to better forecast temperature, moisture and precipitation in urban environments. Within the COSMO Consortium a bulk parameterization scheme (TERRA_URB or TU) has been developed. It parametrizes the effects of buildings, streets and other man-made impervious surfaces on energy, moist and momentum exchanges between the surface and atmosphere, and additionally accounts for the anthropogenic heat flux as a heat source from the surface to the atmosphere. TU implements an impervious water-storage parameterization, and the Semi-empirical Urban canopy parametrization (SURY) that translates 3D urban canopy into bulk parameters. This paper presents evaluation results of the TU scheme in high-resolution simulations with a recent COSMO model version for selected European cities, namely Turin, Naples and Moscow. The key conclusion of the work is that the TU scheme in the COSMO model reasonably reproduces UHI effect and improves air temperature forecasts for all the investigated urban areas, despite each city has very different morphological characteristics. Our results highlight potential benefits of a new turbulence scheme and the representation of skin-layer temperature (for vegetation) in the model performance. Our model framework provides perspectives for enhancing urban climate modelling, although further investigations in improving model parametrizations, calibration and the use of more realistic urban canopy parameters are needed.

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Section: Introductionsupporting

confidence: 78%

Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities

Garbero¹,

Milelli

Mercogliano

et al. 2021

Atmosphere

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“…WRF, COSMO, ENVIRO-HIRLAM) successfully implemented (a hierarchy of) urban parameterizations with different complexities and reached suitable spatial resolutions (Baklanov et al, 2008;Salamanca et al, 2011Salamanca et al, , 2018Sharma et al, 2017;Huang et al, 2019;Mussetti et al, 2020;Trusilova et al, 2016;Wouters et al, 2016;Schubert and Grossman-Clarke, 2014) for an effective description of atmospheric flow in urban areas. The application of urban parameterizations implemented inside limited-area meteorological mod-els is becoming a common approach to drive urban air quality analysis, allowing the improved urban meteorology description in different climatic and environmental conditions (Ribeiro et al, 2021;Salamanca et al, 2018;Gariazzo et al, 2020;Pavlovic et al, 2020;Badia et al, 2020). However, activities to improve the parameterizations (Gohil and Jin, 2019) and provide reliable estimation of the input urban features (Brousse et al, 2016) are continuing.…”

Section: Urban-scale Interactionsmentioning

confidence: 99%

Advances in air quality research – current and emerging challenges

et al. 2022

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Abstract. This review provides a community's perspective on air quality research focusing mainly on developments over the past decade. The article provides perspectives on current and future challenges as well as research needs for selected key topics. While this paper is not an exhaustive review of all research areas in the field of air quality, we have selected key topics that we feel are important from air quality research and policy perspectives. After providing a short historical overview, this review focuses on improvements in characterizing sources and emissions of air pollution, new air quality observations and instrumentation, advances in air quality prediction and forecasting, understanding interactions of air quality with meteorology and climate, exposure and health assessment, and air quality management and policy. In conducting the review, specific objectives were (i) to address current developments that push the boundaries of air quality research forward, (ii) to highlight the emerging prominent gaps of knowledge in air quality research, and (iii) to make recommendations to guide the direction for future research within the wider community. This review also identifies areas of particular importance for air quality policy. The original concept of this review was borne at the International Conference on Air Quality 2020 (held online due to the COVID 19 restrictions during 18–26 May 2020), but the article incorporates a wider landscape of research literature within the field of air quality science. On air pollution emissions the review highlights, in particular, the need to reduce uncertainties in emissions from diffuse sources, particulate matter chemical components, shipping emissions, and the importance of considering both indoor and outdoor sources. There is a growing need to have integrated air pollution and related observations from both ground-based and remote sensing instruments, including in particular those on satellites. The research should also capitalize on the growing area of low-cost sensors, while ensuring a quality of the measurements which are regulated by guidelines. Connecting various physical scales in air quality modelling is still a continual issue, with cities being affected by air pollution gradients at local scales and by long-range transport. At the same time, one should allow for the impacts from climate change on a longer timescale. Earth system modelling offers considerable potential by providing a consistent framework for treating scales and processes, especially where there are significant feedbacks, such as those related to aerosols, chemistry, and meteorology. Assessment of exposure to air pollution should consider the impacts of both indoor and outdoor emissions, as well as application of more sophisticated, dynamic modelling approaches to predict concentrations of air pollutants in both environments. With particulate matter being one of the most important pollutants for health, research is indicating the urgent need to understand, in particular, the role of particle number and chemical components in terms of health impact, which in turn requires improved emission inventories and models for predicting high-resolution distributions of these metrics over cities. The review also examines how air pollution management needs to adapt to the above-mentioned new challenges and briefly considers the implications from the COVID-19 pandemic for air quality. Finally, we provide recommendations for air quality research and support for policy.

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“…As part of the collaboration between the Wellcome-funded CUSSH and Health and Economic impacts of Reducing Overheating in Cities (HEROIC) projects, 12 simulations will be run with the WRF model at 1 km resolution (see Section 4.3) for some of the CUSSH cities-most likely London, Nairobi and Kisumu. The BEP-BEM UCM parameterised by 17 LCZs (see Section 4.4) will be used, building on previous work in Birmingham (UK), Madrid and Barcelona (Spain), Vienna (Austria), Bologna (Italy), Kampala (Uganda) (Brousse et al 2016(Brousse et al , 2020Hammerberg et al 2018;Heaviside et al 2015;Ribeiro et al 2021;Zonato et al 2020). This type of modelling at 1 km resolution can be combined with projections from GCMs/RCMs to investigate the impacts of changes to urban infrastructure and climate change on heat-related mortality (Heaviside et al 2016).…”

Section: Using Climate Projections In Cusshmentioning

confidence: 99%