arXiv subjects

Dominik Strebel

Publications and source records attributed to Dominik Strebel.

5 recordsLinked to original sources

arXiv2025

Interpretable Machine Learning for Urban Heat Mitigation: Attribution and Weighting of Multi-Scale Drivers

Urban heat islands (UHIs) are often accentuated during heat waves (HWs) and pose a public health risk. Mitigating UHIs requires urban planners to first estimate how urban heat is influenced by different land use types (LUTs) and drivers across scales - from synoptic-scale climatic background processes to small-scale urban- and scale-bridging features. This study proposes to classify these drivers into driving (D), urban (U), and local (L) features, respectively. To increase interpretability and enhance computation efficiency, a LUT-distinguishing machine learning approach is proposed as a fast emulator for Weather Research and Forecasting model (WRF) coupled to the Noah land surface model (LSM) to predict ground- (TSK) and 2-meter air temperature (T2). Using random forest regression (RFR) with extreme gradient boosting (XGB) trained on WRF output over Zurich, Switzerland, during heatwave (HW) periods in 2017 and 2019, this study proposes LUT-based (LB) models that categorize features by scales and practical controllability, allowing optional categorical weighting. This approach enables category-specific feature ranking and sensitivity estimation of T2 and TSK to most important small-scale drivers - most notably surface emissivity, albedo, and leaf area index (LAI). Models employing the LB framework are statistically significantly more accurate than models that do not, with higher performance when more HW data is included in training. With RFR-XGB robustly performing optimal with unit weights, the method substantially increase interpretability. Despite the needs to reduce uncertainties and test the method on other cities, the proposed approach offers urban planners a direct framework for feasibility-centered UHI mitigation assessment.

physics.ao-ph↗

arXiv2024

Highly inhomogeneous interactions between background climate and urban warming across typical local climate zones in heatwave and non-heatwave days

Urban heat island (UHI) in conjunction with heatwave (HW) leads to exacerbation of thermal stress in urban areas. Prior research on UHI and HW has predominantly concentrated on examining the thermal conditions at the surface and near-surface, with few investigations extending to the radiative and dynamical interactions of UHI and HW, particularly with a focus on the inhomogeneities across local climate zones (LCZs). Here, we analyse the temperature disparity between HW and non-HW conditions across LCZs in the Sydney area by quantifying the contributions of individual radiative and dynamical processes using the coupled surface-atmosphere climate feedback-response analysis method (CFRAM). Three HW events in 2017, 2019, and 2020 are simulated using the Weather Research and Forecasting (WRF) model coupled with the Single-Layer Urban Canopy Model (SLUCM). The maximum temperature difference between HW and non-HW days may reach up to 10 K, with the increased net solar radiation during HWs being comparable to the typical level of anthropogenic heat flux in urban areas. It is also found that the reduction of clouds, the presence of vapor, and the increase of sensible heat contribute to the warming effect at different levels, with the contribution of clouds being the most dominant. Conversely, the generation of dry convection and the increase of latent heat flux lead to mitigating effects, with the latter being more dominant and capable of causing up to 10 K surface temperature difference between LCZ1 (compact high-rise) and LCZ9 (sparsely built). The differences in the contributions of climate feedback processes across different LCZs become more evident during more severe and humid HWs. These findings underscore the necessity of implementing local climate zone-tailored heat mitigation strategies.

physics.ao-ph↗

arXiv2023

Using Clustering to Understand Intra-city Warming in Heatwaves: Insights into Paris, Montreal, and Zurich

We introduce a novel methodological advancement by clustering paired near-surface air temperature with the planetary boundary layer height (PBLH) to characterize intra-city clusters for analytics. To illustrate this approach, we analyze three heatwaves (HW): the 2019 HW in Paris, the 2018 HW in Montreal, and the 2017 HW in Zurich. We assess cluster-based characteristics before, during, and after heatwave events. Using the objective hysteresis model, we determine the overall strength coefficient of the hysteresis loop between ground storage flux and all-wave downward radiative flux, ranging from 0.414 to 0.457 for urban clusters and from 0.126 to 0.157 for rural clusters during the heatwave periods. Across all cities, we observe a consistent refueling-restoration mode in the cumulative ground heat flux as the heatwaves progress. Future developments of this proposed two-component clustering approach, with the integration of more influential physics, will offer a more comprehensive characterization of cities for urban climate analytics.

physics.ao-ph↗

arXiv2023

Understanding the Impact of Heatwave on Urban Heat Island in Greater Sydney: Temporal Surface Energy Budget Change with Land Types

The impact of heatwaves (HWs) on urban heat island (UHI) is a contentious topic with contradictory research findings. A comprehensive understanding of the response of urban and rural areas to HWs, considering the underlying cause of surface energy budget changes, remains elusive. This study attempts to address this gap by investigating a 2020 HW event in the Greater Sydney Area using the Advanced Weather Research and Forecasting (WRF) model. Findings indicate that the HW intensifies the nighttime surface UHI by approximately 4°C. An analysis of surface energy budgets reveals that urban areas store more heat during the HW due to receiving more solar radiation and less evapotranspiration compared to rural areas. The maximum heat storage flux in urban during the HW can be around 200 W/m2 higher than that during post-HW. The stored heat is released at nightime, raising the air temperature in the urban areas. Forests and savannas have relatively lower storage heat fluxes due to high transpiration and albedo, and the maximum heat storage flux is only around 50 W/m2 higher than that during post-HW. In contrast, a negative synergistic effect is detected between the 2-m UHI and HW. This may be because other meteorological conditions including wind have substantial impacts on the air temperature pattern. The strong hot and dry winds coming from the west and the proximity of tall buildings to the coast diminish the sea breeze coming from the east, resulting in a higher air temperature in the western urban district. Meanwhile, the western forest area also experiences higher temperatures due to the westward winds. In addition, changes in wind direction alter the temperature distribution in the northern rural region. Based on the present study, urban climate simulation data and associated findings can be used to develop urban heat mitigation strategies for UHI during HW.

physics.ao-ph↗

arXiv2021

Betweenness centrality illuminates intermittent frictional dynamics

Dense granular systems subjected to an imposed shear stress undergo stick-slip dynamics with systematic patterns of dilation-compaction. During each stick phase, as the frictional strength builds up, the granular system dilates to accommodate shear strain, developing stronger force networks. During each slip event, when the stored energy is released, particles experience large rearrangements and the granular network can significantly change. Here, we use numerical simulations of 3D, sheared frictional packings to show that the mean betweenness centrality -- a property of network of interparticle connections -- follows consistent patterns during the stick-slip dynamics, showing sharp spikes at each slip event. We identify the source of this behavior as arising from the connectivity and contact arrangements of granular network during dilation-compaction cycles, and find that a lower potential for connection between particles leads to an increase of mean betweenness centrality in the system. Furthermore, we show that at high confinements, few particles lose contact during slip events, leading to a smaller change in granular connectivity and betweenness centrality.

cond-mat.soft↗