White roof is a widely studied urban heat mitigation strategy and frequently incorporated into climate adaptation plans by cities. The effects of white roofs on temperature are often studied within the framework of applied meteorology, with most research focusing on quantifying air temperature reductions under various white roof scenarios (e.g., differing study areas, durations, roof albedos, and adoption rates). Here, the white roof problem is reframed to a climate science problem by focusing on the roof surface temperature and incorporating concepts of climate forcing, sensitivity, and feedback. Different from the Albedo Cooling Effectiveness (ACE) index used for quantifying white roof effects, a new index called Albedo Cooling Sensitivity (ACSs, where the subscript 's' indicates surface) is proposed as a stepping stone towards understanding white roof effects. Moreover, a linearized surface energy balance (SEB) model is utilized to interpret the variability of ACSs simulated by the Weather Research and Forecasting (WRF) model. The variability of ACSs across space and across different model runs with different boundary layer schemes is found to be strongly related to the variability of convective heat transfer efficiency. It is recommended that climate forcing, sensitivity, and feedback be systematically integrated into the analysis of diverse urban adaptation strategies.

How to cite: Li, D.: Bridging the gap between applied meteorology and climate science: a white roof example, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-73, https://doi.org/10.5194/icuc12-73, 2025.

In recent years, different models to simulate urban climate variables have been applied to cities around the world to model, among other variables, the intra-urban air temperature variabilty. Since the modeling of urban climates is complex and subject to resulting uncertainties, validation of the model outputs with in-situ data is crucial. However, intercomparing different urban climate models remains challenging, since they are usually applied to different study areas with varying input data and specific research questions.

In the city of Bern, Switzerland, four urban climate models have been applied recently. This includes a geostatistical land use regression model (LUR) and the numerical model MUKLIMO_3, which were run by the University of Bern, and the numerical models PALM and FITNAH 3D which were set up by private companies (Meteotest AG and GEO-NET Umweltconsulting GmbH). Although the different stakeholders used varying model domains, study periods, and spatiotemperoral resolutions, an intercomparison of the nighttime intra-urban air temperature variability was enabled using air temperature data from 70 stations of an urban air temperature measurement network.

In our study, we compare the outputs of the models with measured data of a specific (which was modeled by LUR, MUKLIMO and PALM) and an average heat night (similar to the FITNAH scenario). Our analysis reveals that MUKLIMO_3 outputs show a weak urban air temperature variability for the city of Bern, while strong small-scale temperature gradients are modeled by FITNAH 3D. PALM outputs are the only ones that reproduce the impact of a large-scale ventilation pattern, but have in general a large positive bias. The most accurate estimates of the urban air temperature variability are obtained from the LUR model. For future applications of urban climate models, we reinforce the need of validation with in-situ measurements, since the outputs (and subsequent policies) depend substantially on the selection of the model.

How to cite: Burger, M., Gubler, M., Holtmann, A., and Brönnimann, S.: Spoilt for choice - Intercomparison of four urban climate models , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-78, https://doi.org/10.5194/icuc12-78, 2025.

In areas with a long summer season, especially where heat stress prevails throughout the day, such as Mediterranean coastal cities, Urban Heat Island (UHI) causes further thermal discomfort and an increase in energy consumption. As the climate continues to warm, additional cooling of homes and public spaces will likely be required, creating a feedback loop and raising temperatures even further. Previous studies have identified a pronounced UHI in Tel Aviv under favorable synoptic conditions, but none have attempted to quantify the direct contribution of urban waste heat from buildings and transportation to the UHI. This study analyses the characteristics of the summer UHI of Tel Aviv under different weather conditions, using meteorological data combined with energy consumption data from two seasons (2023-2024), and develops a statistical downscaling model that predicts the UHI intensity (UHII), based on synoptic, mesoscale and anthropogenic thermal forcing variables. A refined model assessing the direct contribution of waste heat from anthropogenic emissions based on synoptic conditions was developed and exhibited a logarithmic correlation of R=0.83 between the calculated anthropogenic forcing and the UHII.  While energy consumption, primarily from the use of air conditioning (AC) was strongly correlated with nocturnal heat stress, a conflicting finding was the inverse relationship between the nocturnal temperature and the UHII.   A multi-regression statistical predictive model for the UHI shows that while anthropogenic forcing is positively correlated to the UHII, and its direct contribution can be estimated at 0.5°C-1°C during most nights, the direct anthropogenic contribution is overwhelmingly determined by synoptic conditions and not by variations in heat flux. Further research in cities with similar climates could provide recommendations for improved mitigation of waste heat dispersal thus limiting the predicted feedback. 

How to cite: Zohar, M., Saaroni, H., and Ziv, B.: Estimating the anthropogenic contribution to the summer urban heat island in a Mediterranean coastal city - the case of Tel Aviv, Israel, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-106, https://doi.org/10.5194/icuc12-106, 2025.

Sophisticated urban climate systems emerge from the intricate interplay between mesoscale circulations and microscale forcing, making it difficult to fully capture their effects using conventional mesoscale or microscale models alone. Furthermore, high-quality urban morphology data are crucial for quantifying the highly heterogeneous and fragmented urban thermal environment. Here, we present an innovative multi-scale modeling framework that integrates a coupled mesoscale–microscale numerical model with unmanned aerial vehicle (UAV)-based remote sensing to acquire high-resolution urban surface data. This approach enables the accurate representation of fine-scale urban microclimate dynamics within a mesoscale meteorological context. Applying this framework to a heatwave event in Xiong'an New Area, China, we find that riverfront areas exhibit lower temperatures, enhanced ventilation, higher humidity, and reduced thermal stress compared to both high-density and low-density urban zones, with physiological equivalent temperature (PET) reduced by 2.3°C. In high-density built-up areas, radiative energy is primarily stored as ground heat (Q_s) and released as sensible heat (Q_h) at night, exacerbating nocturnal heat stress. By contrast, in riverfront zones, a greater fraction of radiative energy is converted into latent heat flux, mitigating heat stress. Additionally, shaded surfaces exhibit significantly lower heat fluxes than sunlit areas. These findings highlight the potential of this multi-scale framework as a powerful tool for sustainable urban climate design, offering new insights into the sensitivity of microclimatic processes to urban morphology, new developments, and the spatial configuration of blue-green infrastructure.

How to cite: Xu, Y., Hang, J., Hua, J., Wang, W., Zhao, B., Zeng, L., and Du, Y.: A framework for urban meteorological simulations integrating multi-scale modeling and UAV aerial photography, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-138, https://doi.org/10.5194/icuc12-138, 2025.

Estimating pedestrian thermal comfort in urban settings is crucial for climate adapted planning of buildings and districts. Practitioners and urban planners are increasingly relying on simulation tools to assess the local thermal conditions in projects. Simulation tools are now widely available, however, performance comparisons between tools are rare regarding computational load and accuracy. This makes it difficult to choose the optimal tool for a certain urban planning project considering urban heat mitigation.

In this study, to specifically assess performance of the most relevant simulation tools for pedestrian thermal comfort, we present a benchmark case  comparing simple microclimate models (SMM) and all-physics microclimate models (AMM). As SMM we consider SOLWEIG which does not use complex CFD solving of the flow around buildings. As AMM codes we consider urbanMicroclimateFoam, developed by the authors, PALM and ENVI-met, all resolving the flow around buildings based on different CFD turbulence models among other differences in their modeling approaches. The benchmark case is based on an idealized geometry of an isolated street canyon. Simulation conditions are harmonized as much as possible between the different tools. The comparison focuses on heatwave conditions.

Based on the results and workflow, the authors make suggestions for using these tools in research and practice.

How to cite: Strebel, D., Kubilay, A., Carmeliet, J., and Derome, D.: Comparison of different urban climate modelling tools for predicting pedestrian thermal comfort, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-597, https://doi.org/10.5194/icuc12-597, 2025.

Anthropogenic encroachments in urban environments significantly alter energy fluxes and elevate temperatures within cities. Despite extensive research on urban heat islands, limited attention has been paid to the heat exchange between the subsurface and the atmosphere as a bottom-up mechanism. In this work, the impacts of elevated subsurface temperatures, as we find them for example near underground infrastructures, on atmospheric energy fluxes in Berlin are analyzed, using the large eddy simulation urban climate model PALM-4U.

Our findings reveal pronounced differences in sensible heat flux (SHF), ground heat flux (GHF), surface temperature, and potential temperature, while horizontal wind speed shows minimal variation. There is a high intrinsic variability driven by different urban materials and structures. For example, a 5 K increase in soil temperature at 2.91 m depth (lowest soil layer in the model) results in a domain-averaged increase of 0.03 K in 2 m potential temperature over the course of a day. However, at specific locations, maximum differences of 0.86 K are observed (14:00 local time), already after two days of simulation. With increasing height, the influence of elevated soil temperatures diminishes.

These results highlight the importance of understanding soil-atmosphere interactions for urban climate studies. In future, the findings could inform strategies to mitigate urban heat islands - not by adding, but subtracting heat from the soil. One promising approach is shallow geothermal heat recycling, which could sustainably cool urban surfaces and support the development of climate-resilient cities.

How to cite: Glocke, P., Holst, C. C., and Benz, S. A.: Subsurface heat accumulation as an unseen driver of urban energy fluxes , 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-271, https://doi.org/10.5194/icuc12-271, 2025.

With rising global temperatures, urban environments are facing escalating heat stress, often worsened by the Urban Heat Island (UHI) effect. Previous research has predominantly focused on characterizing the Urban Heat Island (UHI) effect in major metropolitan areas across the United States, often neglecting the extreme heat conditions in smaller cities. However, smaller urban areas are also critical for understanding UHI-induced meteorological impacts, as several atmospheric processes, such as pollutant dispersion, are directly or indirectly influenced by UHI. A key knowledge gap in UHI research is the role of urban heat advection (UHA)—the transport of heat by mean winds—in shaping spatial temperature distributions within and around the cities. Current numerical weather prediction models, such as the High-Resolution Rapid Refresh (HRRR) model, face challenges in accurately quantifying and predicting UHI dynamics under varying meteorological and seasonal conditions. This study investigates the spatial variability of urban heat and UHA and assesses the performance of the HRRR model in simulating urban heat features in and around Lubbock, Texas—a small-sized city located in a semi-arid environment in the southwest U.S. Observational data were collected between July 1, 2023, and June 30, 2024, using 23 data loggers from the Urban Heat Island Experiment in Lubbock, Texas (U-HEAT) Micronet, along with five stations from the West Texas Mesonet. The results reveal a pronounced cold bias in modeled nighttime 2-m air temperature and a warm bias during daytime at urban sites. Furthermore, the HRRR model was unable to capture UHA effects under any meteorological conditions. Analysis of the model's performance suggests that prediction errors stem from both urban influences and inherent systematic biases. The findings of this study are expected to enhance operational urban heat forecasting, meanwhile highlighting the importance of improved urban planning and risk management strategies for mitigating UHI effects in smaller cities.

How to cite: Huang, Y., Wang, C., Lee, T., Danzig, T., and Pal, S.: Evaluation of a high-resolution operational numerical weather prediction product in capturing urban heat dynamics in a small city, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-493, https://doi.org/10.5194/icuc12-493, 2025.

The outdoor thermal environment varies significantly across time and space due to changing weather conditions and complex urban geometries. A comprehensive, high-resolution annual analysis is essential to capture these dynamics and support informed urban design decisions. This study presents a framework for calculating and evaluating urban thermal conditions on an annual basis while maintaining an affordable computational burden. The framework utilizes satellite imagery to recognize city geometry, identifying buildings, trees, and water bodies. Meteorological data drives the rapid simulation of key parameters in outdoor thermal environment: Wind speed and Mean Radiant Temperature (MRT). The system combines Fast Fluid Dynamics (FFD) and Proper Orthogonal Decomposition (POD) for efficient wind simulations, alongside GPU-parallel ray-tracing algorithms for MRT calculations, ensuring accurate and efficient evaluations of complex urban environments. After annual hourly flow and radiation fields are obtained, outdoor thermal stress is quantified through the Universal Thermal Climate Index (UTCI), with the assumption of uniform air temperature and humidity distribution. The framework was validated with measured data from Shanghai Jiao Tong University (SJTU) campus, achieving robust predictive performance with an R² value of 0.95 for UTCI estimations. The framework spent a computational time of 5.67 hours on a 64 core workstation to predict annual thermal environment of the entire SJTU campus (2.3km×1.3km) . The results provide key insights for urban planners, including Outdoor Thermal Comfort Autonomy (OTCA) maps for identifying areas that require improvement and hourly thermal stress evaluations to pinpoint critical discomfort periods. These outputs inform strategic decisions on functional zoning, urban renewal, and seasonal adaptive design, ultimately enhancing urban comfort and health.

How to cite: Rui, S., Liu, W., and Lai, D.: Simulation and Evaluation of Hourly Outdoor Thermal Environment on an Annual Basis, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-871, https://doi.org/10.5194/icuc12-871, 2025.

Accurate urban parameterizations in mesoscale models are essential to simulate spatial distribution of air temperature and heat stress in urban areas. To achieve accuracy, high-quality urban data is key. Existing approaches, however, have major limitations. LiDAR-based methods, while highly accurate, require extensive processing and are impractical for large-scale applications. WUDAPT-based approaches (World Urban Database and Access Portal Tools) are easier to implement but rely on generalized classifications that fail to capture fine-scale urban heat patterns, leading to significant temperature biases. This study presents WRFUP (WRF Urban Parameters), a Python tool that automates the ingestion of high-resolution global urban morphology datasets into WRF, making accurate urban modeling significantly easier. WRFUP computes building height, urban fraction, and surface fraction using globally available datasets such as World Settlement Footprint 3D (90m resolution) and Global Urban Fraction (100m resolution) and a custom Machine Learning-based dataset for building surface fraction (CitySurfAce, 100 m). Using WRF with the Building Effect Parameterization (BEP), the Building Energy Model (BEM), and the COMFORT module, along with a high-density urban temperature measurement network over the Grenoble area (France), we demonstrate that WRFUP achieves results as accurate as LiDAR-based methods, while being far simpler to use. Compared to WUDAPT-based parameterization, WRFUP significantly improves spatial temperature and heat stress distributions and reduces nighttime temperature overestimation, offering a practical balance between accuracy and computational efficiency. These findings establish WRFUP as an accessible, high-accuracy alternative for urban parameterization in WRF, bridging the gap between oversimplified WUDAPT classifications and complex LiDAR data processing. By providing a streamlined workflow, WRFUP opens the door to more accessible urban climate modeling, improving predictions of urban heat island intensity, heat stress, and energy demand in cities.

How to cite: Gabeiras, J., Staquet, C., Chemel, C., and Martilli, A.: WRFUP: WRF Urban Parameters Python Package, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1123, https://doi.org/10.5194/icuc12-1123, 2025.

Climate change drives global temperature rises. In cities, where most people live, urbanisation further exacerbates how people experience this excessive heat. The resulting urban heat disrupts businesses, economies, and power grids on a large scale, while causing discomfort, heat stress and strain, and in severe cases, morbidity and mortality at the individual level. Climate models are a key tool in quantifying the multi-scale drivers and impacts of urban heat, as well as mapping its distribution in the city - required to future planning and mitigating negative impacts. However, to date, urban areas have not been realistically represented in climate models, while recent technological advancements have enabled measuring data on urban fabric and form at sub-metre scales. Despite these advancements, how detailed urban data should be for accurate heat exposure modelling is in question. To address this, we have designed four scenarios in the Weather Research and Forecast (WRF) model to examine the effect of locally measured versus global urban data as well as the processing method: local climate zones (LCZs) versus detailed gridded datasets. We then compare them with one scenario without considering intra-urban variabilities. Sydney is the case study. All the experiments are conducted using BEP-BEM-Comfort, an urban canopy model that outputs the subgrid-scale range of Universal Thermal Climate Index (UTCI) for a more comprehensive representation of human heat exposure. Together, these experiments guide urban representation choices for a more accurate heat modelling that in turn better informs large-scale policies for urban heat mitigation and adaptation strategies.

How to cite: Fazeli, M., Nazarian, N., Evans, J., Gabeiras Penas, J., Sharma, S., and Martilli, A.: Are high-resolution urban datasets necessary for accurate heat exposure modelling in cities?, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-104, https://doi.org/10.5194/icuc12-104, 2025.

Urban citizens are particularly exposed to heat stress during heatwaves due to the urban climate conditions. Introducing more trees and/or changing building density and ground cover materials are examples of planning measures that can be used to mitigate heat stress. One challenge as an urban planner is to have knowledge on which mitigation measure to implement to achieve the highest cooling effect. The aim of this high-resolution modelling of outdoor thermal comfort on city-wide domains is to examine how different real-world urban settings reduce or exacerbate heat stress related building density, tree cover and/or ground cover. Here, we exploit an open-source tool, the Urban Multi-scale Environmental Predictor (UMEP), to investigate the influence of real-world information on building density, tree and ground cover on thermal comfort for the three largest cities in Sweden (Stockholm, Göteborg and Malmö). Two thermal comfort indices are calculated and compared: Physiological Equivalent Temperature (PET) and Universal Thermal Comfort Index (UTCI). Automated chain processes using Python scripting is demonstrated making it possible to derive microscale outdoor thermal comfort information (2-meter resolution) using only a standard personal computer and open data sources. Preliminary results show that tree cover is the single most effective heat mitigation factor, especially in areas with low building density. Results also show that altering ground cover has a minor cooling effect. The output from this study will be used as input in practical guidelines to resilient urban planning strategies against heat stress.

How to cite: Lindberg, F., Wallenberg, N., Thorsson, S., Haeger-Eugensson, M., Lönn, J., Holmberg, B., Frid, M., and Fahlström, J.: City-wide analysis of outdoor thermal comfort during heatwaves: influence of building geometry, vegetation and ground cover, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-131, https://doi.org/10.5194/icuc12-131, 2025.

Cities are in the spotlight of environmental research in the face of climate change and local populations’ vulnerability. Land surface models are constantly being improved to better capture urban dynamics with better accuracy and scaling potential to address these challenges. In this study, the Surface Energy and Water Balance Scheme (SUEWS) is evaluated using one year (2023) of energy balance fluxes in Berlin while exploring vegetation parameters derived from near-surface remote sensing and satellite observations.

As the latent heat flux (QE) is strongly influenced by vegetation phenology—particularly leaf area index (LAI)—we evaluate the model’s ability to capture seasonal variations in QE using one year (2023) of 60-minute eddy covariance flux measurements in Berlin. Hourly comparisons show a mean absolute error (MAE) of 25 W m⁻² and a mean bias error (MBE) of approximately 0.5 W m⁻², underscoring the challenges in accurately representing Leaf Area Index (LAI) dynamics and vegetation state throughout the seasons. In contrast, net all-wave radiation exhibits a systematic yet overall low MAE and MBE (~10 W m⁻²), demonstrating the model’s robustness in these calculations.

We further explore the impact of varying data coverage, resolution, and accuracy on model vegetation-parameters sensitivity. Our findings underscore the trade-offs between local and global/regional data inputs and their implications for model accuracy, which is especially relevant for modelling applications in data-sparse regions. The study also emphasizes the potential of Earth observation products—such as ESA World Cover and Copernicus services—to enhance large-scale urban climate modeling. These insights are invaluable for future efforts aiming to improve the accuracy and scalability of predictions across diverse urban environments, especially when accounting for seasonal vegetation dynamics.

How to cite: Tsirantonakis, D., Chrysoulakis, N., Christen, A., Grimmond, S., Fenner, D., and Meier, F.: Evaluation of SUEWS sensitivity to vegetation parameters in a residential area in Berlin, Germany, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-404, https://doi.org/10.5194/icuc12-404, 2025.

This work provides a physical based approach to assess Land Surface Temperature (LST) at urban context, to analyze the Surface Urban Heat Island Intensity (SUHII).  We developed and tested a hydrological-energy balance model, Poli-HE, to compute surface energy, and mass fluxes between soil surfaces, and shallow atmospheric layers in the city of Milan, Italy. Land Surface Temperature (LST) was calculated under given climate conditions and land cover, and spatially distributed with a resolution of 500 m. For mixed paved/green pixels, Vegetation Fraction (VF) was applied. Energy and water balances were integrated, linking soil moisture and latent heat flux to LST. Due to rapid global urbanization, average temperatures in cities have risen more than in the surrounding areas. The temperature difference between urban and rural areas refers to the Surface Urban Heat Island (SUHI) phenomenon. During summer, where LST is in Milan is about 35 °C, paved and green surfaces differ by about + 3.7 °C, reaching up to +4.5°C at times. The Poli-HE outcomes indicate that the presence of green areas can provide a cooling effect and reduce LST, as also shown by satellite observations. In particular, it was proved that an increase of ΔVF = +10% corresponds to a decrease of ΔLST = -0.26°C. This quantitative approach could support urban authorities and professionals, providing a practical tool for current and future planning and projects within the framework of national and international adaptation and mitigation measures.

How to cite: Morgese, S.: A hydrological-energy balance model to assess land surface temperature at the urban scale: the case study of Milano, Italy, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-409, https://doi.org/10.5194/icuc12-409, 2025.

The launch of the "Beating the Heat: the Sustainable Cooling Handbook for Cities" by the UNEP (UN Environment Programme) Cool Coalition has sparked an unprecedented surge in research on the urban thermal and wind environment. Extreme high temperatures and severe pollution in cities usually occur under stable stratification of the atmosphere. City scale buoyancy-driven flow, often referred to as urban heat dome flow, will dominate city ventilation, pollutants dispersion and heat removal under calm condition. Owing to the advantages of well-controlled boundary conditions compared with field measurements, reduced scale water tank experiments, full scale and reduced scale numerical models are normally used for studying urban heat dome flows. To accurately replicate the structures of prototype urban heat dome flows in both reduced scale water tank experiments and numerical models, establishing an appropriate similarity criterion is crucial. A newly dimensionless number (m_Fr) was proposed for the similarity criterion between full-scale and reduced-scale models in urban heat dome flow studies. As m_Fr increases, the extent of the upper-level outflow branch over square city areas in the lateral direction decreases. m_Fr can be used as an index to evaluate the aspect-ratio and side outflow extent in the lateral direction of square urban heat dome flow. Therefore, m_Fr is a pivotal parameter in the study of urban heat dome flows, which can serve as a basis for the design of reduced scale experiments and numerical simulations. In addition to its relevance to city-scale flow studies, our work is also useful for general applications in natural convection. This study contributes to a deeper understanding of the flow mechanism over a stably stratified square horizontal plate. We believe this study has significant implications on urban climate modeling, ultimately underpining urban planning to mitigate hot spots in vulnerable areas and enhance the well-being of residents.

How to cite: Teng, X. and Fan, Y.: Similarity criteria for city scale natural convective flow study under calm condition, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-47, https://doi.org/10.5194/icuc12-47, 2025.

It is well established that the frequency of cumulus cloud formation over the leeward areas of central Tokyo, as well as cumulonimbus development and precipitation, is higher than in surrounding areas. Urban-induced cloud and precipitation generation is generally attributed to two primary mechanisms: thermal and dynamic effects. Here, the dynamic effects involve airflow modification, such as the inhibition of thermals due to obstacles like buildings, which force air parcels to ascend or divert around them. However, the dynamic effect has not been fully investigated using building-resolving models; instead, it has primarily been studied with mesoscale models incorporating urban canopy parameterization schemes. The purpose of this study is to disentangle the thermal and dynamic effects of Tokyo on cloud formation using the building-resolving City-LES model (Kusaka et al., 2024). The study focuses on central Tokyo, with simulations conducted for a clear-sky summer day when a daytime sea breeze reaches the area. The key findings are as follows: (1) Thermals form and are transported by southerly winds, generating roll convection. (2) The thermals reach the lifting condensation level (LCL). The atmospheric boundary layer is well mixed from the surface to the upper planetary boundary layer. Furthermore, sensitivity experiments were conducted to isolate the thermal and dynamic effects of urban areas on cloud formation. The results indicate that: The thermal effect of the city enhances thermal generation, thereby promoting cloud formation. The local-scale dynamic effect suppresses thermal development and inhibits cloud formation, which may differ from the mesoscale dynamic effect. These findings provide new insights into the mechanisms of urban-induced cloud formation and highlight the importance of resolving both thermal and dynamic processes in high-resolution urban meteorological models.

How to cite: Kusaka, H., Nanbara, A., and Sato, T.: Investigating Thermal and Dynamic Effects of Urban Areas on Cumulus Cloud Formation Using the City-LES Model, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-511, https://doi.org/10.5194/icuc12-511, 2025.

Numerical Weather Prediction (NWP) models make weather forecasts at increasing resolution. At higher spatial resolution, urban surface representation becomes more heterogeneous, making conventional land-surface exchange parameterizations invalid. New parameterizations are needed to incorporate these inhomogeneities.

We develop a multi-scale planar-averaging framework for urban flows to address: “What are the requirements for NWP models as resolution increases?” Our computationally efficient method uses convolution filters for coarse graining. To investigate the heterogeneity, we apply the multi-scale framework to a large-eddy simulation of an idealised heterogeneous urban environment of 512 buildings based on a typical London height distribution. Figure 1 shows the plane views of streamwise velocity at various averaging filter lengths, where a decrease in heterogeneity can be observed as the length increases (the resolution lows). We conclude that for this geometry, the characteristic urban length scale is L=50 m, which is the averaging length scale at which as much variance in the flow is resolved as is unresolved. For L>400 m, the problem is approximately homogeneous, allowing non-building-resolving NWP models to be used without modification for the case under consideration.

Figure 1. The streamwise velocity field at various averaging lengths at the mean building level. (a) The original field, (b) L =6 m, (c) L=24 m, (d) L= 96 m, (e) L= 384 m, and (f) the plane-averaged field. The white boxes represent the buildings.

We then focus on the parameterisations of the distributed drag which is important in momentum transport. We show that a universal drag distribution holds reasonably well for resolutions L above 200 m, but at higher resolutions the problem becomes inhomogeneous, and the parameterisation works less well. Parameterisations of unresolved turbulence and dispersive stress are also examined, and the appropriateness of different turbulence closures is discussed.

How to cite: Huang, J. and van Reeuwijk, M.: Multi-scale analysis of flow over heterogeneous urban environments, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-540, https://doi.org/10.5194/icuc12-540, 2025.

Hectometric scale numerical weather prediction (NWP) models are expected to provide improved spatio-temporal weather and climate information in urban regions. Key to understanding the interaction of urban surfaces with the overlying atmosphere is knowledge of the depth of the mixed-layer. Here, we use simulations with the UK Met Office Unified Model with grid-spacing down to 100 m over Berlin, Germany during two days with significantly different weather conditions (18 April 2022 and 4 August 2022) and obtain fields of mixed-layer height from model output (Z_mod) with a new algorithm (termed MMLH). We evaluate MMLH using aerosol attenuated backscatter-derived mixed-layer height from a network of 25 automatic lidar-ceilometers (Z_obs) operated in the city and its surroundings as part of the urbisphere-Berlin campaign, that was designed for observing intra-urban and urban-rural differences in boundary-layer characteristics.  Z_mod compares best to Z_obs in the afternoon and is consistently able to reproduce the vertical extent of the mixed-layer during late afternoon on both case days. MMLH performance is better at 100 m grid-resolution relative to a 300 m configuration. This could be related to higher vertical resolution on the 100 m grid, allowing for tighter vertical gradients in aerosol to be resolved. Both days show a distinct influence of the city on the mixed-layer height , with an urban plume downwind of the city evident in both the observations and model. By nighttime, the model’s urban plume leads to a deeper mixed-layer 10 km downwind of the city compared to upwind (~200 m 18 April; ~500 m 4 August). Both Z_obs and Z_mod show a similar urban plume at night on both days, but on 18 April Z_obs was generally higher by ~100 m over the city. From this study, we identify future avenues to improve hectometric-scale models in urban environments.  

How to cite: Glazer, R., Grimmond, S., Blunn, L., Lean, H., Fenner, D., Christen, A., Looschelders, D., and Morrison, W.: Evaluation of mixed-layer height from a hectometric-scale NWP model using a dense LiDAR network in Berlin, Germany, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-682, https://doi.org/10.5194/icuc12-682, 2025.

Urbanization alters land surface properties, impacting local and regional climates and increasing vulnerability to extreme weather events, such as heavy rainfall and heat waves. Understanding these effects requires high-resolution, long-term urban land use and land cover (LULC) data. To address this, we developed a scalable method that generates the first high-resolution, multi-year Local Climate Zone (LCZ) classification map for Greater Sydney (1990–2020) at five-year intervals. These maps reveal significant urban densification after 2005, with growth in mid- and high-rise LCZs and declines in open low-rise areas. We integrated these maps into the Weather Research and Forecasting (WRF) model by replacing a single dense urban category thereby enabling a more realistic representation of urban morphology (ranging from dense to sparse buildings across 1–10 categories) for long-term simulations. Next, to assess the impact of urbanization on Sydney's rainfall, sensitivity tests of extreme precipitation events were undertaken, comparing simulations using the default (USGS land cover) and LCZ land cover. These reveal significant differences in rainfall distribution both downwind and within urban areas. Additionally, daily mean surface temperature variations of around 1°C were found between the simulations. These results highlight the value of accurate land cover representation in capturing precipitation and temperature variations. Next, we are also employing weather radar-based storm object detection to examine how urban areas influence storm characteristics, including intensity, shape, and behaviour (e.g. merging, splitting). The findings will provide valuable insights into the complex relationship between urban growth and rainfall extremes.

How to cite: Sharma, S., Evans, J., and Pitman, A.: Understanding Urbanization’s Influence on Rainfall in Sydney Through High-Resolution Modeling and Storm Analysis, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1115, https://doi.org/10.5194/icuc12-1115, 2025.

We present results from Phase 2 of the Urban-PLUMBER project, where we assess the ability to represent the surface energy balance across 30 land surface models at 20 sites, ranging from highly urbanised to highly vegetated. Our findings broadly support those of Phase 1, that community efforts have led to better representation of sensible and latent heat fluxes. However, at sites with higher impervious fractions (i.e. areas with little vegetation or bare soil), urbanised models tend to underestimate, and non-urbanised models overestimate the magnitude of observed latent heat fluxes, with urbanised models performing better overall. We find the performance of models without urban representation diverges at approximately 30% impervious fraction.

Our comparison with simple empirically based benchmark models indicates capacity for improvement in longwave radiation and momentum flux representation. Through this benchmarking methodology, we find this study’s group of models perform better than those in the original PLUMBER projects, which tested non-urban land surface models at non-urban sites.

The Urban-PLUMBER project has involved more than 60 contributing scientists, including those providing flux tower and meteorological data, undertaking simulations, developing models and evaluation methods. This presentation focuses on the modelling results for Phase 2. The observational forcing and benchmark data will be openly available, providing tools for future model development and modeller training.

How to cite: Lipson, M., Grimmond, S., and Best, M. and the Urban-PLUMBER modelling co-authors: The Urban-PLUMBER multi-site model evaluation project: Phase 2 initial results, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-981, https://doi.org/10.5194/icuc12-981, 2025.

The urban weather generator (UWG) is a lightweight, free, and easy to use simulation tool that predicts the urban heat island intensity. One limitation of the UWG is that it takes as an input parameter the nighttime urban boundary layer (UBL) height, which is a time-varying physical quantity that is very little known. To overcome this limitation, a physically based dynamic model for the prediction of the nighttime UBL height is implemented in the UWG. The effect of this model implementation on the behavior of the UWG is analyzed in detail.

A primarily analysis aims at understanding deeply the behavior of the base UBL model under various weather conditions, with various nighttime UBL heights. It reveals that when the nighttime UBL height is high, the temperature predictions of the base UWG model do not depend on the characteristics of the urban layout, which renders the model inappropriate for assessing the performance of urban heat mitigation strategies. When the nighttime UBL height is low, spurious fluctuations occur in the predicted temperatures.  The dynamic nighttime UBL height model reconnects the air temperature predictions to the characteristics of the urban layout and regulates the thermal behavior of the UBL to avoid spurious fluctuations. The model predicts nighttime UBL height values that optimize the UWG prediction accuracy; however, these values remain considerably low compared with measured nighttime UBL heights.

How to cite: David, D.: Improving the urban weather generator with a physically based dynamic model of the nighttime urban boundary layer height, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-175, https://doi.org/10.5194/icuc12-175, 2025.

We have developed a simple urban canopy and building energy model SLUCM+BEM (v1.0) (Takane et al. 2024 GMD) that can simulate dynamic anthropogenic heat (Q_F) and electricity (EC) consumption through heating and air-conditioning (HAC) use. However, v1.0 assumes that the interior wall and ceiling temperatures are constant as the target temperature for the HAC system (indoor temperature (T_in) is not modelled), which means that v1.0 does not allow the simulation of a naturally ventilated situation. This assumption could lead to an overestimation of EC from HAC use (EC_HAC). To address this limitation, we have developed v2.0, which can simulate T_in. Comparison of simulated and observed T_in in naturally ventilated residential buildings in London during the summer of 2023 showed that v2.0 can well capture the daily variation and uncertainty of the observed situations. We also confirmed that the reproducibility of EC_HAC by SLUCM+BEM improved significantly from v1.0 to v2.0 in Tokyo for both summer and winter seasons. This means that v2.0 could simulate Q_F by HAC more realistically than v1.0. These results suggest that v2.0 is applicable not only for urban outdoor temperature, Q_F, EC_HAC, but also for indoor temperature in cities worldwide.

Ref:
Takane, Y., Y. Kikegawa. K. Nakajima, and H. Kusaka, 2024: SLUCM+BEM (v1.0): a simple parameterisation for dynamic anthropogenic heat and electricity consumption in WRF-Urban (v4.3.2). Geoscientific Model Development, 17, 8639–8664. doi: 10.5194/gmd-17-8639-2024

How to cite: Takane, Y., Kikegawa, Y., Luo, Z., Kusaka, H., and Grimmond, S.: Development of a simple urban canopy and building energy model SLUCM+BEM (v2.0) for WRF-Urban and global climate models, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-250, https://doi.org/10.5194/icuc12-250, 2025.

A new urban canopy scheme for the ICON atmospheric model is presented. Increasing the resolution of atmospheric models for numerical weather prediction (NWP) or climate simulations allows, among others, for a more realistic description of the processes at the land surface. Here, one field of growing interest are the processes in urban areas. Beside their relevance for the meteorological modelling, there is a general trend in most countries that the number of people living in towns is significantly increasing. During the recent years, an urban canopy parameterisation was developed for the multi-layer land surface scheme TERRA of the Consortium for Small-scale Modeling (COSMO) mesoscale atmospheric model. This parameterisation, TERRA_URB, originally developed for the climate version of COSMO and then ported to the NWP version, was shown to be able to reproduce the key urban meteorological features for different European cities. In the framework of the transition of the COSMO Consortium to the ICON model, TERRA_URB needed to be implemented in ICON. For this purpose, the COSMO Consortium organises the dedicated Priority Project CITTA’. Meanwhile, the implementation of TERRA_URB in ICON is completed. Beside this, CITTA’ addresses the important issue of the urban canopy parameters which are needed to characterize urban areas in the atmospheric model. Currently, ICON uses the land use dataset GlobCover which contains only one urban class. In order to improve on this, the advanced ECOCLIMAP-SG land use dataset is implemented in ICON, containing 10 urban land use classes being based on the concept of local climate zones. Results are presented for TERRA_URB in the ICON limited-area model ICON-LAM for different cities of interest of the CITTA’ partners. They indicate that features like the urban heat island and urban dry island effects are well represented. This is demonstrated on test cases like in the WMO WCRP FPS URB-RCC.

How to cite: Schulz, J.-P., Campanale, A., Adinolfi, M., Raffa, M., Milelli, M., Garbero, V., and Mercogliano, P.: A new urban parameterisation for the ICON atmospheric model, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-1031, https://doi.org/10.5194/icuc12-1031, 2025.

This study evaluates the performance of the Harmonie-AROME Numerical Weather Prediction (NWP) model in reproducing real atmospheric conditions over Paris during an intense heatwave in the summer of 2022. A series of very-high-resolution simulations are conducted at different spatial resolutions and incorporate diverse land use and urban morphology datasets.

The simulations utilized ECMWF operational forecasts at 9 km resolution as boundary conditions for the operational 2.5 km runs, with additional one-way nested domains at 500 m and 200 m resolutions. To assess the impact of urban areas, the Town Energy Balance (TEB) urban canopy parameterization (Masson et al., 2000) was implemented, comparing its single-layer and newly developed multi-layer configurations. Additionally, improvements were introduced to better account for the influence of urban structures on turbulent vertical diffusion.

To investigate the impact of different urban morphology datasets, simulations were performed with:

• ECOCLIMAP-SG land use dataset at 300 m resolution, which classifies urban areas into 10 categories based on the WUDAPT Local Climate Zones (LCZ) classification.
• Geoclimate urban morphology dataset at 100 m resolution, derived from OpenStreetMap (OSM) data (Bernard et al., 2022), utilizing a random forest technique to estimate missing building heights and generate a more realistic representation of urban geometries.

Comparison with observations reveals that category-based land use datasets (ECOCLIMAP-SG) struggle to capture temperature variability in heterogeneous urban areas, even at higher resolutions. In contrast, the OSM-based dataset better represents city heterogeneity and horizontal variability, demonstrating its suitability for high-resolution urban simulations.

At 200 m resolution, results indicate that category-based land use datasets are not adequate for resolving neighborhood-scale variations within a city. Furthermore, employing the multi-layer TEB model significantly improves the simulation of air temperature in high-density districts and wind speed within the whole urban canopy boundary layer, emphasizing the need for vertically coupled urban canopy parameterizations within the planetary boundary layer (PBL) scheme.

How to cite: Zonato, A., Theeuwes, N., de Rooy, W., Schoetter, R., Wurtz, J., and Masson, V.: The influence of using a multi-layer urban canopy scheme and detailed land use in very high-resolution NWP, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-634, https://doi.org/10.5194/icuc12-634, 2025.

Numerical weather prediction (NWP) models, coupled with urban parameterizations, play a crucial role in understanding and forecasting meteorological conditions within urban environments. Urban parameterizations vary in complexity, ranging from simplified slab models to complex multi-layer urban canopy models. In the mesoscale NWP model COSMO, only one urban parameterization, TERRA_URB, is available, which describes the city as a flat surface with modified surface parameters in accordance with the urban canyon geometry. In this study, we have coupled the latest version 6.0 of the COSMO model with a more sophisticated urban canopy model, TEB (Town Energy Balance), which explicitly simulates the energy exchange inside the urban canyon. Here, we present the coupling approach and assessment of model’s sensitivity to urban schemes of different complexity (TEB and TERRA_URB) over the Moscow region for August 2022. Despite using the same external parameters for both schemes, simulations demonstrate notable differences in temperature simulations, with TEB generally producing lower nighttime and morning temperatures. This leads to a greater underestimation of the urban heat island intensity in TEB when compared with the observations. The simulated surface albedo, as well as cell-averaged sensible and latent heat fluxes, differ slightly between the parameterizations and could not explain revealed temperature differences. We attribute the observed temperature discrepancies to the different descriptions of heat conductivity and storage within urban surfaces. Although there are no clear advantages to using a more complex parameterization in terms of model errors, TEB opens up more opportunities to refine input parameters and take into account additional processes. Future research involves the improvement of TEB by incorporating a module of green infrastructure into the urban canyon through coupling with COSMO’s land surface model and by setting the Building Energy Model specifically for Moscow conditions.
The study was supported by Russian Science Foundation Project no. 24-17-00155.

How to cite: Tarasova, M., Varentsov, M., Debolskiy, A., and Stepanenko, V.: Introducing the COSMO model with TEB urban canopy scheme: coupling strategy and comparison with simpler TERRA_URB parameterization, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-956, https://doi.org/10.5194/icuc12-956, 2025.

Human thermal comfort in urban areas, where a growing percentage of the global population live, has been a topic of research for many years. Impacts of heatwaves are often greater in urban areas via the influence of urban heat islands, so the ability to determine indicators of urban heat stress on both weather forecast and climate projection timescales is crucial.

To address this, it is necessary to develop thermal comfort models that account for urban processes and utilise standard weather and climate model output data. In this work, we present a computationally efficient method to calculate wet-bulb globe temperature (WBGT; a standard heat stress metric) in an infinitely long street canyon for this purpose. The radiation calculation is analytical and accounts for longwave, shortwave direct and shortwave diffuse radiation transfer (allowing up to two reflections) to calculate mean radiant temperature of a black globe located anywhere in the canyon. This is combined with model estimates of near-surface temperature, humidity and wind speed to determine WBGT via standard empirical equations.

We calculate WBGT from hectometric weather model simulations over Paris and compare with WBGT values derived from black-globe thermometer measurements from street canyons during the PANAME field campaign. Additionally, we investigate the sensitivity of our WBGT calculations to geometric and optical properties of the canyon, and the background meteorological fields. We find that the model reproduces observed WBGT well in an urban canyon environment, and that values are most sensitive to shading, which is modulated by building geometry. Finally, we demonstrate a potential application of our method by calculating WBGT along the Paris 2024 Olympics marathon route and, comparing with published WBGT safety thresholds for long-distance running, demonstrate how our method could be used to advise event organisers on safety measures, such as event timing and route planning.

How to cite: Shonk, J., Blunn, L., Kumar, V., Wurtz, J., Masson, V., and Lemonsu, A.: An Urban Street Canyon Heat Stress Calculation Method for Weather and Climate Models, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-707, https://doi.org/10.5194/icuc12-707, 2025.

Cities affect local climate by profoundly modifying land use/land cover with associated changes in radiative and morphological properties of land surfaces. Accurately prescribing these boundary conditions is key for urban climate modeling. Fine-scale heterogeneity of urban surface parameters, and a corresponding dearth of intra-urban observations, have been challenges, but global high-resolution urban parameter datasets have recently emerged to address this gap. However, the effects of incorporating these spatially explicit properties on summertime urban climate simulations remain underexplored.

We use the WRF regional climate model to simulate recent extreme heat in 13 US cities at 1 km² resolution with two sets of geographic boundary conditions varying by local climate zone (LCZ) classification: one using default parameters (“default”), and one using the U-Surf satellite-derived, spatially continuous urban parameters (“params”). We show that “params” simulations correspond better with surface temperature observations in terms of both absolute values and intra-urban variation. In large part due to lower impervious fraction estimations, “params” simulations yielded lower air temperature than “default” for most US cities examined, especially in the suburbs and exurbs, leading to a smaller urban heat island. The smaller simulated area of transpiring vegetated land cover resulting from overestimating urban fraction somewhat offsets suburban moist heat overestimations from using default urban parameters.

Finally, we simulate two US cities using continuously varying (i.e. assigned for every grid point) morphological and radiative parameters, finding that this further enhances simulation accuracy. Decomposing the sources of increased accuracy shows that improved impervious fraction is the most important variable. Overall, results suggest that using high-resolution urban parameters enhances accuracy when modeling extreme heat events.

How to cite: Jiang, T., Chakraborty, T., Cheng, Y., Zhao, L., Mukherjee, R., and Martilli, A.: Modeling urban extreme heat using spatially resolved radiative and morphological parameters, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-327, https://doi.org/10.5194/icuc12-327, 2025.

Current numerical models for urban weather and climate simulations still have significant research gaps at the city scale, where heterogeneity in land-use types influences atmospheric processes. The Greater Chicago Area, positioned between rural areas, Lake Michigan, and a dense metropolitan region, presents a complex urban environment with diverse building heights and vegetation distributions that are not accurately represented in existing models. Under the Community Research on Climate and Urban Science (CROCUS) project, advancements have been made to the Weather Research and Forecasting (WRF) model, specifically improving the Building Effect Parameterization (BEP) to better account for urban street trees, low-rise building effects on atmospheric circulations, and detailed representations of urban structures. To evaluate these potential improvements, we utilize data from two Intensive Observational Periods (IOPs, 48 hours each) in July in Chicago. The IOP data include high-spectral-resolution and Doppler lidar profiles, 2- and 10-meter meteorological observations, and radiosondes (balloon launches) across the Chicago area, including the city and southwestern Lake Michigan. These periods feature distinct meteorological conditions, including a lake breeze, a cold front, and a convective system passing through the region, allowing for comprehensive validation of the updated WRF-Urban model and a better physical understanding of city-scale urban heterogeneity. The study highlights urban processes that were previously underrepresented in coarser-resolution models and demonstrates the benefits of high-resolution, realistic simulations, as well as comprehensive urban observations, for improving urban weather and climate modeling.

How to cite: Wang, J., Tan, H., Martili, A., Fytanidis, D., Li, P., Jackson, R., Nesbitt, S., Raut, B., Muradyan, P., O'Brien, J., Collis, S., Kotamarthi, R., and Negri, C.: An Integrated Urban Weather Modeling System for Heterogeneous Urban Processes in Summer Chicago, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-500, https://doi.org/10.5194/icuc12-500, 2025.

Many cities experience a strong Urban Heat Island (UHI) in winter with early snow melt and decreased snowfall. Urban characteristics, snow cover, and human activities are important contributors to these effects. However, the winter UHI magnitude and its different driver contributions are still unclear and still pose many challenges to model. Urban climate models have demonstrated strong performances to simulate the urban climate. But few studies address the representation of the cold urban climate. Thus, we have enhanced the capabilities of the TEB urban climate model to simulate winter conditions. The model has been upgraded with an ice layer, a multilayer snow model, an explicit representation of the traffic impacts on road temperature and snow characteristics, and a snow cover parameterisation for urban environments. These new processes have then been evaluated in open environments with observations from road weather stations and in urban environments from the Helsinki sites available in the Urban-PLUMBER initiative. The snow depth and the artificial surface temperature are better simulated. In particular, snow-melt episodes have improved drastically. At the Helsinki site, the results show better representations of the energy fluxes in winter and spring. We believe that this work is an important step towards addressing the current limitation for cold urban climate modelling.

How to cite: Colas, G. and Masson, V.: Enhancing winter urban simulations in the TEB urban climate model, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-395, https://doi.org/10.5194/icuc12-395, 2025.

This study examines seasonal and diurnal Urban Heat Island (UHI) effects within urban environments. It aims to develop an understanding of UHI dynamics to help guide urban planning and climate resilience. The high-resolution observed meteorological data is obtained at a subhourly scale from seven fixed automatic weather stations in urban and rural settings, installed in Dehradun city, India, to analyse UHI variability for the time period 2021-2023. The research also focused on complex interactions between intracity UHI variability and key meteorological parameters, namely humidity, wind speed, dew point, and solar radiation, and how these factors influence UHI intensity changes. The analysis reveals strong seasonal variations in UHI patterns, with the summer season exhibiting the highest UHI intensities, reaching over 10 °C for most urban stations. The winter season demonstrated the lowest UHI values across all stations, with UHI intensities ranging approximately 3-5 °C. Diurnal UHI patterns showed a clear increase during daylight hours, peaking during mid afternoon, and diminishing during nighttime. The diverse results demonstrate how urban morphology can be combined with atmospheric conditions to better understand the complex urban thermal environment. These findings present crucial implications for urban building planning and management since increased UHI values enhance thermal stress impact on buildings, infrastructure, energy consumption, and human comfort. This study contributes to the broader discourse on sustainable urban development by highlighting the necessity of considering UHI dynamics in urban climate resilience planning. Further, it demonstrates the need to include meteorological data in city planning and how it may assist in mitigating the climate change impacts while promoting sustainable urban development.

Keywords: Urban Heat Island, Seasonal Variability, Diurnal Patterns, Urban Microclimate, Climate Adaptation

How to cite: Mishra, A. and Arya, D. S.: Examining the seasonal and diurnal atmospheric UHI variability using meteorological parameters within an urban microclimate, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-335, https://doi.org/10.5194/icuc12-335, 2025.

Anthropogenic heat (AH) emissions in urban environments alter the surface energy budget and significantly influence urban climates. However, these emissions vary greatly in both time and space, leading to considerable uncertainty in their estimation. As remote sensing in the urban environment advances, where the remotely sensed urban surface temperatures are becoming increasingly available, such as those retrieved from satellite observations and thermal cameras. Yet, assimilating these observations into surface energy modeling for AH estimation has not been fully explored. In this study, a model for AH estimation based on the Kalman filter and surface energy balance is developed (KF-SEB model). Urban meteorological data, including air temperature and building surface temperature, are assimilated into the Kalman filter, yielding sensible heat flux and building heat storage. AH is subsequently calculated using the SEB equation. The KF-SEB model is evaluated using a forward model with predefined AH emissions. The forward model employs a simple SEB approach at the building exterior surface and adopts a 1-D heat conduction equation for the wall. The results show that the KF-SEB model accurately captures the magnitude and temporal variation of AH, with reduced uncertainties compared to previous studies. This study offers a novel approach of AH estimation based on urban meteorological data and provides important insights into the feedback between urban microclimates and anthropogenic energy use. 

How to cite: Cui, Y., Chu, M., Albertson, J., and Li, Q.: Estimating anthropogenic heat flux by assimilating meteorological observations with a Kalman filter approach, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-548, https://doi.org/10.5194/icuc12-548, 2025.

To accurately simulate urban climate under extreme conditions and assess its evolution in the context of climate change, a one-dimensional model, MLUCM BEP+BEM, has been developed. This model integrates the vertical turbulent diffusion approach proposed by Santiago and Martilli (2010) with the Building Effect Parameterization (BEP) from Martilli et al. (2002) and the simplified Building Energy Model (BEM) introduced by Salamanca et al. (2009). Enhancements in turbulent length scales for dissipation and eddy coefficients have been incorporated, accounting for atmospheric stability following the methodology of Bougeault and Lacarrere (1989).
Designed as a standalone model, MLUCM BEP+BEM operates with atmospheric forcing applied at the top boundary, its design enables offline simulations and simplifies its integration in mesoscale models. Additionally, it includes representations of urban greenery and street trees, following the approaches of Zonato et al. (2021) and Stone et al. (2021), respectively, while also introducing new terms for temperature and humidity fluxes.
This study validates MLUCM BEP+BEM using observational data from the Urban-PLUMBER project, assessing its capability to simulate surface-atmosphere fluxes in a suburban area of Preston, Melbourne, Australia. Comparisons with similar models highlight its very good performance in representing urban climate dynamics. Moreover, the intra-urban sensitivity of the parameterization is examined through a case study of Bari, a mid-sized Mediterranean city, evaluating the interplay between mesoscale forcings and urban microscale processes during an intense heatwave. The model, forced by ERA5 reanalysis data, was compared with temperature measurements from sensors placed in different city neighbourhoods. The findings indicate that mesoscale influences play a dominant role in shaping urban microclimate simulations, with urban geometry exerting a secondary effect. 

This work is supported by ICSC – Centro Nazionale di Ricerca in High Performance Computing, Big Data and Quantum Computing, funded by European Union – NextGenerationEU (CUP F83C22000740001).

How to cite: Pappaccogli, G., Zonato, A., Martilli, A., Buccolieri, R., and Lionello, P.: Validation of MLUCM BEP+BEM: Assessing urban microclimate across mesoscale and microscale dynamics, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-877, https://doi.org/10.5194/icuc12-877, 2025.

Urban air pollution poses a significant risk to human health, contributing to respiratory and cardiovascular diseases, whereas greenhouse gases drive climate change by trapping heat in the atmosphere and altering weather patterns. To address these challenges and improve urban environments, we developed a high-resolution modeling framework that enhances our understanding of greenhouse gases and air pollutant distribution in Rotterdam. We conducted high-resolution (100 x 100 m) simulations of greenhouse gases and air pollutant concentrations using the Dutch Large Eddy Simulation (DALES) model. DALES explicitly resolves boundary-layer turbulence, improving the accuracy of atmospheric transport and dispersion modeling in urban environments. A key innovation of our approach is the application of DALES with chemical open boundary conditions derived from LOTOS-EUROS chemistry-transport model outputs, enabling a more realistic representation of background and external pollution contributions to local air quality. Emission inputs were refined using data from the Dutch national and the TNO emission inventories, incorporating statistical and proxy data specific to Rotterdam. This ensures a more accurate spatial representation of emissions at high resolution. Additionally, gas-phase chemistry was involved to account for chemical production and loss within the urban atmosphere. The results of this study will provide valuable input for machine learning-based forecasting tools, enabling real-time estimation of pollution exposure at the individual level. It will support policymakers in designing targeted interventions to mitigate health risks associated with air pollution and reach climate targets.

How to cite: Doyennel, A., Los, A., Manders-Groot, A., Geers, L., Janssen, R., Jansson, F., and Houweling, S.: High-resolution modeling of greenhouse gases and air pollution: linking LOTOS-EUROS and DALES, 12th International Conference on Urban Climate, Rotterdam, The Netherlands, 7–11 Jul 2025, ICUC12-678, https://doi.org/10.5194/icuc12-678, 2025.