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 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 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 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 A Partition Modeling for Anthropogenic Heat Flux Mapping in China

2019 ◽  
Vol 11 (9) ◽  
pp. 1132 ◽  
Author(s):  
Shasha Wang ◽  
Deyong Hu ◽  
Shanshan Chen ◽  
Chen Yu
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Spatial Distribution ◽  
High Resolution ◽  
Urban Areas ◽  
Thermal Environment ◽  
Modeling Method ◽  
Anthropogenic Heat ◽  
Regional Characteristics ◽  
Anthropogenic Heat Flux

Anthropogenic heat (AH) generated by human activities has a major impact on urban and regional climate. Accurately estimating anthropogenic heat is of great significance for studies on urban thermal environment and climate change. In this study, a gridded anthropogenic heat flux (AHF) estimation scheme was constructed based on socio-economic data, energy-consumption data, and multi-source remote sensing data using a partition modeling method, which takes into account the regional characteristics of AH emission caused by the differences in regional development levels. The refined AHF mapping in China was realized with a high resolution of 500 m. The results show that the spatial distribution of AHF has obvious regional characteristics in China. Compared with the AHF in provinces, the AHF in Shanghai is the highest which reaches 12.56 W·m−2, followed by Tianjin, Beijing, and Jiangsu. The AHF values are 5.92 W·m−2, 3.35 W·m−2, and 3.10 W·m−2, respectively. As can be seen from the mapping results of refined AHF, the high-value AHF aggregation areas are mainly distributed in north China, east China, and south China. The high-value AHF in urban areas is concentrated in 50–200 W·m−2, and maximum AHF in Shenzhen urban center reaches 267 W·m−2. Further, compared with other high resolution AHF products, it can be found that the AHF results in this study have higher spatial heterogeneity, which can better characterize the emission characteristics of AHF in the region. The spatial pattern of the AHF estimation results correspond to the distribution of building density, population, and industry zone. The high-value AHF areas are mainly distributed in airports, railway stations, industry areas, and commercial centers. It can thus be seen that the AHF estimation models constructed by the partition modeling method can well realize the estimation of large-scale AHF and the results can effectively express the detailed spatial distribution of AHF in local areas. These results can provide technical ideas and data support for studies on surface energy balance and urban climate change.

scholarly journals Integrating Urban Form, Function, and Energy Fluxes in a Heat Exposure Indicator in View of Intra-Urban Heat Island Assessment and Climate Change Adaptation

Climate ◽  
2019 ◽  
Vol 7 (6) ◽  
pp. 75 ◽  
Author(s):  
Ilias Agathangelidis ◽  
Constantinos Cartalis ◽  
Mat Santamouris
Keyword(s):  
Climate Change ◽  
Heat Flux ◽  
Urban Heat Island ◽  
Urban Form ◽  
Heat Exposure ◽  
Geographical Information ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Anthropogenic Heat Flux ◽  
Urban Heat

Cities worldwide are getting warmer due to the combined effects of urban heat and climate change. To this end, local policy makers need to identify the most thermally vulnerable areas within cities. The Local Climate Zone (LCZ) scheme highlights local-scale variations; however, its classes, although highly valuable, are to a certain extent generalized in order to be universally applicable. High spatial resolution indicators have the potential to better reflect city-specific challenges; in this paper, the Urban Heat Exposure (UHeatEx) indicator is developed, integrating the physical processes that drive the urban heat island (UHI). In particular, the urban form is modeled using remote sensing and geographical information system (GIS) techniques, and used to estimate the canyon aspect ratio and the storage heat flux. The Bowen ratio is calculated using the aerodynamic resistance methodology and downscaled remotely sensed surface temperatures. The anthropogenic heat flux is estimated via a synergy of top–down and bottom–up inventory approaches. UHeatEx is applied to the city of Athens, Greece; it is correlated to air temperature measurements and compared to the LCZs classification. The results reveal that UHeatEx has the capacity to better reflect the strong intra-urban variability of the thermal environment in Athens, and thus can be supportive for adaptation responses. High-resolution climate projections from the EURO-CORDEX ensemble for the region show that the adverse effects of the existing thermal inequity are expected to worsen in the coming decades.

scholarly journals On the Assessment of a Cooling Tower Scheme for High-Resolution Numerical Weather Modeling for Urban Areas

2019 ◽  
Vol 58 (6) ◽  
pp. 1399-1415 ◽  
Author(s):  
Miao Yu ◽  
Jorge González ◽  
Shiguang Miao ◽  
Prathap Ramamurthy
Keyword(s):  
Heat Flux ◽  
Latent Heat ◽  
Urban Areas ◽  
Cooling Tower ◽  
Absolute Humidity ◽  
Heat Fluxes ◽  
Anthropogenic Heat ◽  
Near Surface ◽  
Anthropogenic Heat Flux ◽  
Temperature Errors

AbstractA cooling tower scheme that quantifies the sensible and latent anthropogenic heat fluxes released from buildings was coupled to an operational forecasting system [Rapid Refresh Multiscale Analysis and Prediction of the Beijing Urban Meteorological Institute (RMAPS-Urban)] and was evaluated in the context of the megacity of Beijing, China, during summer months. The objective of this scheme is to correct for underestimations of surface latent heat fluxes in regional climate modeling and weather forecasts in urban areas. The performance for surface heat fluxes by the modified RMAPS-Urban is greatly improved when compared with a suite of observations in Beijing. The cooling tower scheme increases the anthropogenic latent heat partition by 90% of the total anthropogenic heat flux release. Averaged surface latent heat flux in urban areas increases to about 64.3 W m−2 with a peak of 150 W m−2 on dry summer days and 40.35 W m−2 with a peak of 150 W m−2 on wet summer days. The model performance of near-surface temperature and humidity is also improved. Average 2-m temperature errors are reduced by 1°C, and maximum and minimum temperature errors are improved by 2°–3°C; absolute humidity is increased by 5%.

scholarly journals Features of Urban Heat Island in Mountainous Chongqing from a Dense Surface Monitoring Network

Atmosphere ◽  
2019 ◽  
Vol 10 (2) ◽  
pp. 67 ◽  
Author(s):  
Ping Jiang ◽  
Xiaoran Liu ◽  
Haonan Zhu ◽  
Yonghua Li
Keyword(s):  
Urban Heat Island ◽  
Urban Areas ◽  
Surface Wind ◽  
Warm Season ◽  
Monitoring Network ◽  
Anthropogenic Heat ◽  
Heat Island ◽  
Near Surface ◽  
Urban Heat ◽  
Surface Monitoring

The spatial and temporal features of urban heat island (UHI) intensity in complex urban terrain are barely investigated. This study examines the UHI intensity variations in mountainous Chongqing using a dense surface monitoring network. The results show that the UHI intensity is closely related to underlying surfaces, and the strongest UHI intensity is confined around the central urban areas. The UHI intensity is most prominent at night and in warm season, and the magnitude could reach ~4.5 °C on summer night. Our quantitative analysis shows a profound contribution of urbanization level to UHI intensity both at night and in summer, with regression coefficient b = 4.31 and 6.65, respectively. At night, the urban extra heat such as reflections of longwave radiation by buildings and release of daytime-stored heat from artificial materials, is added into the boundary layer, which compensates part of urban heat loss and thus leads to stronger UHI intensity. In summer, the urban areas are frequently controlled by oppressively hot weather. Due to increased usage of air conditioning, more anthropogenic heat is released. As a result, the urban temperatures are higher at night. The near-surface wind speed can serve as an indicator predicting UHI intensity variations only in the diurnal cycle. The rural cooling rate during early evening transition, however, is an appropriate factor to estimate the magnitude of UHI intensity both at night and in summer.

scholarly journals Impact of an improved WRF urban canopy model on diurnal air temperature simulation over northern Taiwan

2016 ◽  
Vol 16 (3) ◽  
pp. 1809-1822 ◽  
Author(s):  
Chuan-Yao Lin ◽  
Chiung-Jui Su ◽  
Hiroyuki Kusaka ◽  
Yuko Akimoto ◽  
Yang-Fan Sheng ◽  
...  
Keyword(s):  
Land Surface ◽  
Urban Areas ◽  
Urban Canopy ◽  
Anthropogenic Heat ◽  
Surface Model ◽  
Urban Canopy Model ◽  
Simulation Performance ◽  
The Impact ◽  
Canopy Model ◽  
Northern Taiwan

Abstract. This study evaluates the impact of urbanization over northern Taiwan using the Weather Research and Forecasting (WRF) Model coupled with the Noah land-surface model and a modified urban canopy model (WRF–UCM2D). In the original UCM coupled to WRF (WRF–UCM), when the land use in the model grid is identified as "urban", the urban fraction value is fixed. Similarly, the UCM assumes the distribution of anthropogenic heat (AH) to be constant. This may not only lead to over- or underestimation of urban fraction and AH in urban and non-urban areas, but spatial variation also affects the model-estimated temperature. To overcome the abovementioned limitations and to improve the performance of the original UCM model, WRF–UCM is modified to consider the 2-D urban fraction and AH (WRF–UCM2D).The two models were found to have comparable temperature simulation performance for urban areas, but large differences in simulated results were observed for non-urban areas, especially at nighttime. WRF–UCM2D yielded a higher correlation coefficient (R2) than WRF–UCM (0.72 vs. 0.48, respectively), while bias and RMSE achieved by WRF–UCM2D were both significantly smaller than those attained by WRF–UCM (0.27 and 1.27 vs. 1.12 and 1.89, respectively). In other words, the improved model not only enhanced correlation but also reduced bias and RMSE for the nighttime data of non-urban areas. WRF–UCM2D performed much better than WRF–UCM at non-urban stations with a low urban fraction during nighttime. The improved simulation performance of WRF–UCM2D in non-urban areas is attributed to the energy exchange which enables efficient turbulence mixing at a low urban fraction. The result of this study has a crucial implication for assessing the impacts of urbanization on air quality and regional climate.

The WRF-SUEWS coupled system: development and evaluation in two UK cities

2020 ◽  
Author(s):  
Hamidreza Omidvar ◽  
Ting Sun ◽  
Zhenkun Li ◽  
Ning Zhang ◽  
Wenjuan Huang ◽  
...  
Keyword(s):  
Energy Balance ◽  
Land Surface ◽  
Urban Areas ◽  
Large Scale ◽  
Climate Models ◽  
Coupled System ◽  
Anthropogenic Heat ◽  
Physical Processes ◽  
Atmospheric Measurements ◽  
Anthropogenic Heat Flux

<p>To capture complex physical processes in cities with high degree of heterogeneity, sophisticated urban land surface models (ULSMs) are used with various anthropogenic activities considered. These ULSMs can be used either offline, using atmospheric measurements as forcing inputs, or online, coupled with large-scale climate models. One downside of using ULSMs in offline mode is that most of atmospheric measurements in cities are spatially limited (e.g. a few points or sites) preventing the physical processes across extremely diverse or heterogeneous conditions in cities from being studied in their entire complexity. Coupling ULSMs with meso-scale models helps us study two-way interactions between the urban surface and atmosphere, and provides spatio-temporal information about the effect of urban climate on various city-related environmental issues such as the urban heat island and urban stormwater.</p><p>Here we couple and evaluate state-of-the-art surface urban energy and water scheme (SUEWS) with the weather research and forecasting (WRF) model. The coupled system (WRF-SUEWS) is evaluated in two UK cities: London (dense urban) and Swindon (suburban) for four two-week periods in each season. In general, WRF-SUEWS models the surface energy balance fluxes well in both cities across all periods. One strength of the coupled system is the ability to model the spatial and temporal distribution of anthropogenic heat in urban areas. We study how the difference between the anthropogenic heat flux of residential and commercial areas affects the energy balance as well as atmospheric variables over these areas.</p>

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