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

2021 ◽  
Author(s):  
Valeria Garbero ◽  
Massimo Milelli ◽  
Francesca Bassani ◽  
Edoardo Bucchignani ◽  
Paola Mercogliano ◽  
...  
Keyword(s):  
Air Temperature ◽  
Weather Prediction ◽  
Urban Climate ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Climate Modelling ◽  
Model Framework ◽  
European Cities ◽  
Cosmo Model ◽  
Anthropogenic Heat Flux

<p>Nowadays, cities are the preferred location for more than half of the human population and the places where major human-perceived climate change impacts occur. In an increasingly urbanized world, it is essential to represent such areas adequately in Numerical Weather Prediction (NWP) models, not only to correctly forecast air temperature, but also the human heat stress and the micro-climate phenomena induced by the cities. Among them, the best known is the Urban Heat Island (UHI) effect, which refers to the significantly higher temperatures experienced by a metropolitan area than its rural surroundings. Currently, the COSMO model employs a zero-order urban description, which is unable to correctly reproduce the UHI effect: cities are simply represented as natural lands with increased surface roughness length and reduced vegetation cover. However, the reproduction of the urban climate features in NWP and regional climate models is possible with the use of the so-called urban canopy models, that are able to parameterize the interaction between the urbanized surface and the overlying atmosphere. In this context, a new bulk parameterization scheme, TERRA_URB (TU), has been developed within the COSMO Consortium. TU offers an intrinsic representation of urban physics: the effect of buildings, streets and other man-made layers on the surface-atmosphere interaction is described by parameterizing the impervious water balance, translating the 3D urban-canopy parameters into bulk parameters with the Semi-empirical Urban canopy parameterization (SURY) and using the externally calculated anthropogenic heat flux as additional heat source. In this work, we present high-resolution simulations with the TU scheme, for different European cities, Turin, Naples and Moscow. An in-depth evaluation and verification of the performances of the recent COSMO version with TU scheme and new implemented physical parameterizations, such the ICON-like surface-layer turbulence scheme and the new formulation of the surface temperature, have been carried out. The validation concerned the 2-meter temperature and was performed for 1- or 2-week selected periods over the 3 European cities characterized by different environment and climate, namely the Moscow megacity in Russia and Turin and Naples in Italy. Even if the three domains are morphologically different, the results follow a common behavior. In particular, the activation of TERRA_URB provides a substantial improvement in capturing the UHI intensity and improving air temperature forecasts in urban areas. Potential benefits in the model performance also arise from a new turbulence scheme and the representation of skin-layer temperature (for vegetation). Our model framework provides promising perspectives for enhancing urban climate modelling, although further investigations are needed.</p>

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

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 237 ◽  
Author(s):  
Valeria Garbero ◽  
Massimo Milelli ◽  
Edoardo Bucchignani ◽  
Paola Mercogliano ◽  
Mikhail Varentsov ◽  
...  
Keyword(s):  
Urban Areas ◽  
Morphological Characteristics ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Climate Modelling ◽  
Model Framework ◽  
European Cities ◽  
Cosmo Model ◽  
Anthropogenic Heat Flux ◽  
Urban Heat

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.

scholarly journals Impact of Urban Canopy Parameters on a Megacity’s Modelled Thermal Environment

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1349
Author(s):  
Mikhail Varentsov ◽  
Timofey Samsonov ◽  
Matthias Demuzere
Keyword(s):  
Urban Areas ◽  
Climate Model ◽  
Thermal Environment ◽  
Weather Prediction ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Climate Modelling ◽  
Local Climate ◽  
Anthropogenic Heat Flux ◽  
Local Climate Zones

Urban canopy parameters (UCPs) are essential in order to accurately model the complex interplay between urban areas and their environment. This study compares three different approaches to define the UCPs for Moscow (Russia), using the COSMO numerical weather prediction and climate model coupled to TERRA_URB urban parameterization. In addition to the default urban description based on the global datasets and hard-coded constants (1), we present a protocol to define the required UCPs based on Local Climate Zones (LCZs) (2) and further compare it with a reference UCP dataset, assembled from OpenStreetMap data, recent global land cover data and other satellite imagery (3). The test simulations are conducted for contrasting summer and winter conditions and are evaluated against a dense network of in-situ observations. For the summer period, advanced approaches (2) and (3) show almost similar performance and provide noticeable improvements with respect to default urban description (1). Additional improvements are obtained when using spatially varying urban thermal parameters instead of the hard-coded constants. The LCZ-based approach worsens model performance for winter however, due to the underestimation of the anthropogenic heat flux (AHF). These results confirm the potential of LCZs in providing internationally consistent urban data for weather and climate modelling applications, as well as supplementing more comprehensive approaches. Yet our results also underline the continued need to improve the description of built-up and impervious areas and the AHF in urban parameterizations.

scholarly journals COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees

2020 ◽  
Vol 13 (3) ◽  
pp. 1685-1710 ◽  
Author(s):  
Gianluca Mussetti ◽  
Dominik Brunner ◽  
Stephan Henne ◽  
Jonas Allegrini ◽  
E. Scott Krayenhoff ◽  
...  
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Urban Climate ◽  
Coupled Model ◽  
Urban Canopy ◽  
Small Scale ◽  
Climate Modelling ◽  
Street Trees ◽  
Effective Measure ◽  
Weather And Climate

Abstract. Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and, for example, do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and hence cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the Building Effect Parameterisation with Trees (BEP-Tree) vegetated urban canopy model and the Consortium for Small-scale Modeling (COSMO) mesoscale weather and climate model. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for nighttime air temperature and humidity, which can mainly be traced back to limitations in the simulation of the nighttime stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in nighttime air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.

scholarly journals COSMO-BEP-Tree v1.0: a coupled urban climate model with explicit representation of street trees

2019 ◽  
Author(s):  
Gianluca Mussetti ◽  
Dominik Brunner ◽  
Stephan Henne ◽  
Jonas Allegrini ◽  
E. Scott Krayenhoff ◽  
...  
Keyword(s):  
Air Temperature ◽  
Climate Model ◽  
Urban Climate ◽  
Coupled Model ◽  
Urban Canopy ◽  
Climate Modelling ◽  
Street Trees ◽  
Night Time ◽  
Effective Measure ◽  
Weather And Climate

Abstract. Street trees are more and more regarded as an effective measure to reduce excessive heat in urban areas. However, the vast majority of mesoscale urban climate models do not represent street trees in an explicit manner and for example do not take the important effect of shading by trees into account. In addition, urban canopy models that take interactions of trees and urban fabrics directly into account are usually limited to the street or neighbourhood scale and, hence, cannot be used to analyse the citywide effect of urban greening. In order to represent the interactions between street trees, urban elements and the atmosphere in realistic regional weather and climate simulations, we coupled the vegetated urban canopy model BEP-Tree and the mesoscale weather and climate model COSMO. The performance and applicability of the coupled model, named COSMO-BEP-Tree, are demonstrated over the urban area of Basel, Switzerland, during the heatwave event of June–July 2015. Overall, the model compared well with measurements of individual components of the surface energy balance and with air and surface temperatures obtained from a flux tower, surface stations and satellites. Deficiencies were identified for night-time air temperature and humidity, which can mainly be traced back to limitations in the simulation of the night-time stable boundary layer in COSMO. The representation of street trees in the coupled model generally improved the agreement with observations. Street trees produced large changes in simulated sensible and latent heat flux, and wind speed. Within the canopy layer, the presence of street trees resulted in a slight reduction in daytime air temperature and a very minor increase in night-time air temperature. The model was found to realistically respond to changes in the parameters defining the street trees: leaf area density and stomatal conductance. Overall, COSMO-BEP-Tree demonstrated the potential of (a) enabling city-wide studies on the cooling potential of street trees and (b) further enhancing the modelling capabilities and performance in urban climate modelling studies.

scholarly journals A High-Resolution Monitoring Approach of Canopy Urban Heat Island using Random Forest Model and Multi-platform Observations

2021 ◽  
Author(s):  
Shihan Chen ◽  
Yuanjian Yang ◽  
Fei Deng ◽  
Yanhao Zhang ◽  
Duanyang Liu ◽  
...  
Keyword(s):  
High Resolution ◽  
Random Forest ◽  
Urban Heat Island ◽  
Air Temperature ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Model Framework ◽  
Rapid Urbanization ◽  
Urban Heat ◽  
The City

Abstract. Due to rapid urbanization and intense human activities, the urban heat island (UHI) effect has become a more concerning climatic and environmental issue. A high spatial resolution canopy UHI monitoring method would help better understand the urban thermal environment. Taking the city of Nanjing in China as an example, we propose a method for evaluating canopy UHI intensity (CUHII) at high resolution by using remote sensing data and machine learning with a Random Forest (RF) model. Firstly, the observed environmental parameters [e.g., surface albedo, land use/land cover, impervious surface, and anthropogenic heat flux (AHF)] around densely distributed meteorological stations were extracted from satellite images. These parameters were used as independent variables to construct an RF model for predicting air temperature. The correlation coefficient between the predicted and observed air temperature in the test set was 0.73, and the average root-mean-square error was 0.72 °C. Then, the spatial distribution of CUHII was evaluated at 30-m resolution based on the output of the RF model. We found that wind speed was negatively correlated with CUHII, and wind direction was strongly correlated with the CUHII offset direction. The CUHII reduced with the distance to the city center, due to the de-creasing proportion of built-up areas and reduced AHF in the same direction. The RF model framework developed for real-time monitoring and assessment of high-resolution CUHII provides scientific support for studying the changes and causes of CUHII, as well as the spatial pattern of urban thermal environments.

scholarly journals Anthropogenic Heat Flux Estimation Based on Luojia 1-01 New Nighttime Light Data: A Case Study of Jiangsu Province, China

2020 ◽  
Vol 12 (22) ◽  
pp. 3707
Author(s):  
Zhongli Lin ◽  
Hanqiu Xu
Keyword(s):  
Heat Flux ◽  
Energy Consumption ◽  
Urban Climate ◽  
Power Estimation ◽  
Anthropogenic Heat ◽  
Economic Activities ◽  
Estimation Model ◽  
Nighttime Light Data ◽  
Anthropogenic Heat Flux ◽  
Nighttime Light

With the rapid process of urbanization, anthropogenic heat generated by human activities has become an important factor that drives the changes in urban climate and regional environmental quality. The nighttime light (NTL) data can aptly reflect the spatial distribution of social-economic activities and energy consumption, and quantitatively estimate the anthropogenic heat flux (AHF) distribution. However, the commonly used DMSP/OLS and Suomi-NPP/VIIRS NTL data are restricted by their coarse spatial resolution and, therefore, cannot exhibit the spatial details of AHF at city scale. The 130 m high-resolution NTL data obtained by Luojia 1-01 satellite launched in June 2018 shows a promise to solve this problem. In this paper, the gridded AHF spatial estimation is achieved with a resolution of 130 m using Luojia 1-01 NTL data based on three indexes, NTLnor (Normalized Nighttime Light Data), HSI (Human Settlement Index), and VANUI (Vegetation Adjusted NTL Urban Index). We chose Jiangsu, a fast-developing province in China, as an example to determine the best AHF estimation model among the three indexes. The AHF of 96 county-level cities of the province was first calculated using energy-consumption statistics data and then correlated with the corresponding data of three indexes. The results show that based on a 5-fold cross-validation approach, the VANUI power estimation model achieves the highest R2 of 0.8444 along with the smallest RMSE of 4.8277 W·m−2 and therefore has the highest accuracy among the three indexes. According to the VANUI power estimation model, the annual mean AHF of Jiangsu in 2018 was 2.91 W·m−2. Of the 96 cities, Suzhou has the highest annual mean AHF of 7.41 W·m−2, followed by Wuxi, Nanjing, Changzhou and Zhenjiang, with the annual mean of 3.80–5.97 W·m−2, while the figures of Suqian, Yancheng, Lianyungang, and Huaian, the cities in northern Jiangsu, are relatively low, ranging from 1.41 to 1.59 W·m−2. This study has shown that the AHF estimation model developed by Luojia 1-01 NTL data can achieve higher accuracy at city-scale and discriminate the spatial detail of AHF effectively.

15 year re-analysis of the urban climate of Amsterdam using WRF

2020 ◽  
Author(s):  
Sytse Koopmans ◽  
Gert-Jan Steeneveld ◽  
Ronald van Haren ◽  
Albert Holtslag
Keyword(s):  
Data Assimilation ◽  
The Netherlands ◽  
Thermal Comfort ◽  
Prediction Models ◽  
Weather Prediction ◽  
Urban Climate ◽  
Urban Canopy ◽  
Human Thermal Comfort ◽  
Weather Observations ◽  
Simulated Precipitation

<p><strong>15 year re-analysis of the urban climate of Amsterdam using WRF </strong></p><p><strong> </strong></p><p>Sytse Koopmans<sup>1</sup> ([email protected]), Gert-Jan Steeneveld<sup>1</sup>, Ronald van Haren<sup>2</sup>, Albert A.M. Holtslag<sup>1</sup>.</p><p> </p><p><sup>1</sup> Wageningen University and Research, the Netherlands:</p><p><sup>2 </sup>Netherlands eScience Center, the Netherlands:</p><p> </p><p> </p><p>Ongoing world-wide climate change and urbanization illustrate the need to understand urban hydrometeorology and its implications for human thermal comfort and water management. Numerical weather prediction models can assist to understand these issues, as they progress increasingly towards finer scales. With high model resolutions (grid spacing of 100m), effective representation of cities becomes crucial. The complex structures of cities, configuration of buildings, streets and scattered vegetation, require a different modelling approach than the homogeneous rural surroundings. The current urban canopy-layer schemes account for these city specific characteristics, but differ substantially amongst each other due to uncertainty in land use parameters and incomplete physical understanding. Therefore, the hindcasting of the urban environment needs improvement.</p><p>In this study, we improve the WRF (Weather Research and Forecasting) mesoscale model performance by incorporating observations of a variety of sources using data assimilation (WRF-3DVAR) and nudging techniques on a resolution up to 167 meter. Data assimilation aims to accurately describe the most probable atmospheric state by steering the model fields in the direction of the observations. Specific to urban boundary layers, a novel approach has been developed to nudge modelled urban canyon temperatures with quality controlled urban weather observations. Adjusting the urban fabric accordingly is crucial, because of the large heat storage within urban canopies. The road and wall layers of the urban canopy are adjusted depending on the bulk heat transfer coefficient and urban geometry. Other data assimilation sources consists of WMO synoptic weather observations and volume radar data.</p><p>The results of the 15-year climatological urban re-analysis are here presented and it is subdivided in three key questions. First, we attempt to answer how large the trends are in human thermal comfort over the 15 year period. Second, we investigate if there are seasonality’s detected in maximum urban heat island intensities. Earlier found hysteresis-like curves were reproduced to a large extent for for pedestrian level air temperatures. Lastly, we analyse trends in extreme precipitation using simulated precipitation data on one second interval.</p>

scholarly journals Urban climate in Central European cities and global climate change

2018 ◽  
Vol 51-52 (1) ◽  
pp. 7-35 ◽  
Author(s):  
Anita Bokwa ◽  
Petr Dobrovolný ◽  
Tamás Gál ◽  
Jan Geletič ◽  
Ágnes Gulyás ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Climate Change ◽  
Global Climate ◽  
Urban Climate ◽  
Global Changes ◽  
Climate Modelling ◽  
Complex Data ◽  
Central European ◽  
European Cities ◽  
The Impact

Urban areas are among those most endangered with the potential global climate changes. The studies concerning the impact of global changes on local climate of cities are of a high significance for the urban inhabitants' health and wellbeing. This paper is the final report of a project (Urban climate in Central European cities and global climate change) with the aim to raise the public awareness on those issues in five Central European cities: Szeged (Hungary), Brno (Czech Republic), Bratislava (Slovakia), Kraków (Poland) and Vienna (Austria). Within the project, complex data concerning local geomorphological features, land use and long-term climatological data were used to perform the climate modelling analyses using the model MUKLIMO_3 provided by the German Weather Service (DWD).

scholarly journals The Effects of Anthropogenic Heat Release on Urban Meteorology and Implication for Haze Pollution in the Beijing-Tianjin-Hebei Region

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Ruiting Liu ◽  
Zhiwei Han
Keyword(s):  
Heat Release ◽  
Air Temperature ◽  
Wrf Model ◽  
Surface Air Temperature ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Hygroscopic Growth ◽  
Near Surface ◽  
Atmospheric Diffusion ◽  
Haze Pollution

In this study, the effect of anthropogenic heat release (AHR) on meteorological variables and atmospheric diffusion capability and implication for haze pollution in the Beijing-Tianjin-Hebei region in January 2013 were investigated by using Weather Research and Forecasting (WRF) model with an urban canopy model (UCM) and an AHR scheme. The comparison with observation demonstrated the WRF/UCM model taking AHR into account apparently improved meteorological prediction, especially for surface air temperature at 2 m (T2). The model also exhibited a better performance for planetary boundary layer (PBL) height. This study revealed that AHR from cities exerted a significant impact on meteorology by generally increasing surface air temperature and wind speed, decreasing relative humidity, and elevating PBL height and near surface turbulent kinetic energy (TKE), which could consequently reduce surface pollutant concentration and mitigate haze pollution by enhancing atmospheric instability and turbulent mixing and reducing aerosol hygroscopic growth.

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