Evaluation and Modeling of Urban Heat Island Intensity in Basel, Switzerland

Wicki, Andreas; Parlow, Eberhard; Feigenwinter, Christian

doi:10.3390/cli6030055

Cited by 45 publications

(38 citation statements)

References 84 publications

(139 reference statements)

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“…T αmin was selected to be examined, as UHI UCL is predominantly a nocturnal phenomenon [43,131] due to slower cooling rates for the denser urban areas. Since long-term canopy layer temperatures for the study area were not available, measurements in the RSL were used (Section 2.3), corresponding to a combined effect of microscale and local-scale processes [89]. The results presented in Table 6 indicate that UHeatEx values follow the T αmin measurements well, reflecting both the stored warmth during the day and the subsequent nighttime release.…”

Section: Resultsmentioning

confidence: 99%

“…Considering the contribution of individual surface types (k), OHM can be applied as: where Q* is the net radiation flux [W m −2 ], f is the fractional cover of the different surfaces (estimated from data in Section 2.2) and a 1 , a 2 , and a 3 are the OHM model coefficients (Table 1). Q* is calculated as in [89], using the surface parameters, the remote sensing data, and the atmospheric variables presented in Sections 2.2 and 2.3. The average daily course of Q* for the cloud-free days of July-measured from the World Radiation Centre (WRC) group during the Thermopolis 2009 campaign [78] and included in the previously mentioned ESA dataset-was used to derive the second term in Equation (5).…”

Section: Net Storage Heat Fluxmentioning

confidence: 99%

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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

Agathangelidis

Cartalis

Santamouris

2019

Climate

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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.These four decisive parameters for the urban climate (H/W, β, ∆Q S , Q F ) are estimated in this work using meteorological, earth observation, and geographical information system (GIS) data; the Climate 2019, 7, 75 3 of 28 different variables are subsequently incorporated in the UHeatEx composite indicator via principal component analysis (PCA). An additional mapping of the study area using the LCZ scheme is applied, and similarities and differences between UHeatEx and LCZs are discussed. Both results are correlated with air temperature measurements from a network of automatic weather stations (AWSs) in the area under examination, for a six-year period (the warm period months). A qualitative and quantitative analysis examines the presence of thermal inequity in Athens and its relationship with socioeconomic characteristics. The growing importance of thermal indicators in sustainable urban planning, due to climate change, is demonstrated by presenting the simulated future conditions of the city. To this end, high-resolution climate projections from an ensemble of regional climate models (RCMs) were used.

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Section: Resultsmentioning

confidence: 99%

Section: Net Storage Heat Fluxmentioning

confidence: 99%

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

Agathangelidis

Cartalis

Santamouris

2019

Climate

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“…Ordinary least squares (OLS) regression has been commonly used in similar studies examining the drivers of atmospheric UHIs [62][63][64]. The OLS regression analysis was conducted in two steps.…”

Section: -D 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d mentioning

confidence: 99%

“…However, we acknowledge limitations with OLS regression including multicollinearity [65], predictor selection problems, and addressing overestimates of parameters [66]. To address these issues, we ran an 1) elastic net (EN) regression analysis and 2) variance inflation factor (VIF) in SPSS to test the validity of the OLS models and test how inflated the variance of the predictors variables are due to correlation between variables [63,66]. EN regression combines ridge and lasso regression to address instances of small number of dependent variables with a large number of predictor variables and helps address instances where there may be correlation between predictors.…”

Section: -D 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d (%∆) 2-d 3-d mentioning

confidence: 99%

Accurate Characterization of Land Cover in Urban Environments: Determining the Importance of Including Obscured Impervious Surfaces in Urban Heat Island Models

Coseo

Larsen

2019

Atmosphere

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Urban heat islands (UHI) increase summer temperatures and can threaten human well-being during extreme heat events. Since urbanization plays a key role in UHI development, accurate quantification of land cover types is critical to their identification. This study examines how quantifying land cover types using both two- and three-dimensional approaches to land cover quantification affects an UHI model’s explanatory power. Two-dimensional approaches treat tree canopies as a land cover, whereas three-dimensional approaches document the land cover areas obscured under tree canopies. We compare how accurately the two approaches explain elevated air temperatures in Chicago, Illinois. Our results show on average 14.1% of impervious surface areas went undocumented using a two-dimensional approach. The most common concealed impervious surfaces were sidewalks, driveways, and parking lots (+6.2%), followed by roads (+6.1%). Yet, the three-dimensional approach did not improve the explanatory power of a UHI model substantially. At 2 a.m., the adjusted R2 increased from 0.64 for a two-dimensional analysis to 0.68 for a three-dimensional analysis. We found that the less time consuming two-dimensional quantification of land covers was sufficient to predict neighborhood UHIs. As climate change exacerbates UHI, more cities will map urban hotspots and this research increases our understanding of alternative approaches.

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“…Second, we present an application and comprehensive evaluation of COSMO-BEP-Tree over the transnational urban agglomeration of Basel (Switzerland, Germany and France) during a heatwave event in June-July 2015. The evaluation makes 30 use of the extensive measurement infrastructure for urban climate studies available in Basel Wicki et al, 2018) including an urban flux tower and a network of surface stations and additionally uses land surface temperature (LST) observations from satellite. In order to verify the model's response to the parameters that define the street trees, a sensitivity analysis is also presented.…”

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confidence: 99%

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

Mussetti¹,

Brunner²,

Henne³

et al. 2019

Preprint

Self Cite

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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.

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Evaluation and Modeling of Urban Heat Island Intensity in Basel, Switzerland

Cited by 45 publications

References 84 publications

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

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

Accurate Characterization of Land Cover in Urban Environments: Determining the Importance of Including Obscured Impervious Surfaces in Urban Heat Island Models

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

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