Thermal load in a medium-sized European city using the example of Aachen, Germany

Buttstädt, Mareike; Schneider, Christoph

doi:10.3112/erdkunde.2014.02.01

Cited by 11 publications

(3 citation statements)

References 22 publications

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“…Multiple linear regression (MLR) based models often reached considerable goodness of fit as shown e.g. by Unger et al (2001) for Szeged, Hungary, Bottyán et al (2005) for Debrecen, Hungary, Alcoforado & Andrade (2006) for Lisbon, Portugal, Szymanowski & Kryza (2012) for Wrocław, Poland, Buttstädt & Schneider (2014) for Aachen, Germany, Heusinkveld et al (2014) for Rotterdam, Netherlands, Ketterer & Matzarakis (2015) for Stuttgart, Germany as well as Bernard et al (2017) for Nantes, Angers and La Roche-sur-Yon in western France. Another statistical approach successfully utilized to derive spatio-temporal patterns of air temperature were Regression Trees, e.g.…”

Section: Introductionmentioning

confidence: 99%

Statistical modelling of spatial patterns of the urban heat island intensity in the urban environment of Augsburg, Germany

Straub

Berger²,

Breitner

et al. 2019

Urban Climate

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Spatial and temporal variability of meteorological variables across urban areas due to differences in land surface characteristics is a common phenomenon. Most pronounced is the effect of land use on air temperature. In this study, parametric and non-parametric statistical approaches (stepwise multiple linear regression and random forests) were applied in order to model sub-daily as well as daily spatial patterns of the urban heat island intensity in the major city of Augsburg, Southern Germany, and its rural surroundings. A large number of model setups utilizing variables from different land surface data sets as predictors and taking into account different seasonal, daily and meteorological situations was examined. The results were compared concerning different measures of model performance (mean squared skill score, mean squared error, explained variance). For individual setups and situations considerable skill of up to 85% explained variance was reached. The best performing models were obtained from multiple linear regression for anticyclonic situations with low or negative net radiation. Selected models were utilized to derive continuous spatial distributions of the air temperature deviations from a rural reference station. The resulting maps can be useful for various applications, e.g. in the context of urban planning. Keywordsmultiple linear regression; random forests; urban air temperature; urban climate; urban heat island; Augsburg Taxonomy Urban Climate, Urban Heat Island Effects

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Section: Introductionmentioning

confidence: 99%

Statistical modelling of spatial patterns of the urban heat island intensity in the urban environment of Augsburg, Germany

Straub

Berger²,

Breitner

et al. 2019

Urban Climate

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“…In existing LUR studies, such specific cold air variables are often not incorporated (e.g. [4,26,27]) or the focus is set on ventilation paths (e.g. with the proxy front area index, [28,29]) which do not account for CAD caused by terrain features, since the spatial connectivity between cold-air source areas (production) and urban areas (impact) is not considered [24].…”

Section: Introductionmentioning

confidence: 99%

Modeling the intra-urban nocturnal summertime air temperature fields at a daily basis in a city with complex topography

2022

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Detailed knowledge about the intra-urban air temperature variability within a city is crucial for the implementation of adaptation strategies to counteract the negative effects of urban heat stress. Various methods to model urban-rural temperature differences exist, but they often only cover certain periods (heatwave, hot day) or meteorological conditions (sunny and calm) due to computational limitations or limited data availability. Here, we present a land use regression approach to model nocturnal air temperature fields for every single night of the summers 2018 to 2020 in a city with complex terrain (Bern, Switzerland). Furthermore, we investigate the applicability of different model structures and straight-forward computable GIS variables to model cold air drainage, which exerts an important influence on the local-scale climate of cities with complex terrain. The geostatistical models are calibrated with in-situ data of a dense low cost air temperature measurement network and high resolution spatiotemporal (land use and meteorology) data, which are all publicly available. The resulting land use regression models are capable to model and map intra-urban air temperature differences with a good model performance (R2: 0.65–0.71; RMSE: 0.69–0.76 K). Evaluations with data from additional measurement stations and periods (summer 2021) show that the models are able to estimate different meteorological and spatial conditions, but that the representation of small-scale topographic features remains difficult. However, the comparatively low computational and financial effort needed to calculate nocturnal air temperature fields at daily basis enable new applications for cities with restricted resources for various areas of interest, such as urban planning (e.g. effect of heat mitigation policies) or heat risk management (e.g. analyze small-scale urban heat vulnerability).

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“…In addition, spatial patterns and the temporal development of urban thermal climates at different scales have also been analysed using computer-assisted modelling (Früh et al 2011;Schubert et al 2012;Buttstädt and Schneider 2014) or crowdsourced data from citizen weather stations (Chapman et al 2017;Fenner et al 2017;Meier et al 2017;Feichtinger et al 2020;Venter et al 2020). Moreover, urban tree growth has been modelled and simulated under present and future climate conditions (Broadbent et al 2019;Buccolieri et al 2018;Canetti et al 2017;Rötzer et al 2019).…”

Section: Introductionmentioning

confidence: 99%

Using the dendro-climatological signal of urban trees as a measure of urbanization and urban heat island

Schneider

Neuwirth²,

Schneider

et al. 2021

Urban Ecosyst

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Using dendroclimatological techniques this study investigates whether inner city tree-ring width (TRW) chronologies from eight tree species (ash, beech, fir, larch, lime, sessile and pedunculate oak, and pine) are suitable to examine the urban heat island of Berlin, Germany. Climate-growth relationships were analyzed for 18 sites along a gradient of increasing urbanization covering Berlin and surrounding rural areas. As a proxy for defining urban heat island intensities at each site, we applied urbanization parameters such as building fraction, impervious surfaces, and green areas. The response of TRW to monthly and seasonal air temperature, precipitation, aridity, and daily air-temperature ranges were used to identify climate-growth relationships. Trees from urban sites were found to be more sensitive to climate compared to trees in the surrounding hinterland. Ring width of the deciduous species, especially ash, beech, and oak, showed a high sensitivity to summer heat and drought at urban locations (summer signal), whereas conifer species were found suitable for the analysis of the urban heat island in late winter and early spring (winter signal).The summer and winter signals were strongest in tree-ring chronologies when the urban heat island intensities were based on an area of about 200 m to 3000 m centered over the tree locations, and thus reflect the urban climate at the scale of city quarters. For the summer signal, the sensitivity of deciduous tree species to climate increased with urbanity.These results indicate that urban trees can be used for climate response analyses and open new pathways to trace the evolution of urban climate change and more specifically the urban heat island, both in time and space.

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Thermal load in a medium-sized European city using the example of Aachen, Germany

Cited by 11 publications

References 22 publications

Statistical modelling of spatial patterns of the urban heat island intensity in the urban environment of Augsburg, Germany

Statistical modelling of spatial patterns of the urban heat island intensity in the urban environment of Augsburg, Germany

Modeling the intra-urban nocturnal summertime air temperature fields at a daily basis in a city with complex topography

Using the dendro-climatological signal of urban trees as a measure of urbanization and urban heat island

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