A Partition Modeling for Anthropogenic Heat Flux Mapping in China

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.

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Satellite data based approach for the estimation of anthropogenic heat flux over urban areas

Fifth International Conference on Remote Sensing and Geoinformation of the Environment (RSCy2017) ◽

10.1117/12.2280826 ◽

2017 ◽

Author(s):

Dimitrios Bliziotis ◽

Theodoros Nitis ◽

George Tsegas ◽

Dimitrios Gounaridis ◽

Nicolas Moussiopoulos

Keyword(s):

Heat Flux ◽

Satellite Data ◽

Urban Areas ◽

Anthropogenic Heat ◽

Anthropogenic Heat Flux

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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 ◽

10.3390/cli7060075 ◽

2019 ◽

Vol 7 (6) ◽

pp. 75 ◽

Cited By ~ 4

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.

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

Journal of Applied Meteorology and Climatology ◽

10.1175/jamc-d-18-0126.1 ◽

2019 ◽

Vol 58 (6) ◽

pp. 1399-1415 ◽

Cited By ~ 3

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%.

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

Atmosphere ◽

10.3390/atmos11121349 ◽

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.

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

Atmosphere ◽

10.3390/atmos12020237 ◽

2021 ◽

Vol 12 (2) ◽

pp. 237 ◽

Cited By ~ 1

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.

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