BEGIN:VCALENDAR VERSION:2.0 PRODID:-//pretalx//talks.osgeo.org//foss4g-2026//speaker//TUWFP9 BEGIN:VTIMEZONE TZID:JST BEGIN:STANDARD DTSTART:20000101T000000 RRULE:FREQ=YEARLY;BYMONTH=1 TZNAME:JST TZOFFSETFROM:+0900 TZOFFSETTO:+0900 END:STANDARD END:VTIMEZONE BEGIN:VEVENT UID:pretalx-foss4g-2026-RTTEQX@talks.osgeo.org DTSTART;TZID=JST:20260901T140000 DTEND;TZID=JST:20260901T143000 DESCRIPTION:Urban microclimate modelling has become an important tool for a nalysing urban heat island effects\, thermal comfort\, and the environment al performance of urban design interventions. High-resolution microscale m odels allow researchers to investigate the interaction between urban morph ology\, surface materials\, vegetation\, and atmospheric processes at the scale of individual streets or neighbourhoods. Among these models\, ENVI-m et is widely used for simulating urban microclimate conditions due to its ability to resolve airflow\, radiation exchange\, heat transfer\, and vege tation–atmosphere interactions within complex urban environments.\nDespi te their advanced capabilities\, microscale models require detailed meteor ological forcing data as input. These forcing datasets typically include t ime series of air temperature\, wind speed and direction\, relative humidi ty\, and radiation parameters\, which are usually obtained from nearby sur face meteorological observations. In practice\, however\, such observation al datasets are often unavailable\, incomplete\, or insufficiently represe ntative of the simulated urban area. This limitation is particularly prono unced in smaller cities\, complex terrain environments\, or rapidly develo ping urban regions where meteorological monitoring networks are sparse. As a result\, the lack of reliable forcing data often represents a key barri er to the application of microscale urban climate models for real case-stu dy scenarios.\nAt the same time\, mesoscale numerical weather prediction m odels provide continuous spatial and temporal coverage of atmospheric vari ables and represent a valuable alternative source of meteorological data. The Weather Research and Forecasting (WRF) model (Skamarock et al. 2019)\, especially when coupled with an Urban Canopy Model (UCM) (Tewari et al. 2 007)\, enables the simulation of urban surface–atmosphere interactions a t spatial resolutions ranging from several kilometres down to hundreds of metres. Mesoscale models incorporate land-use characteristics\, surface en ergy balance processes\, and regional atmospheric dynamics\, allowing them to simulate realistic meteorological conditions across large spatial doma ins. While such models cannot explicitly resolve street-level urban geomet ry\, they capture the broader atmospheric conditions and synoptic influenc es that drive local microclimate variability.\nThis study presents a metho dology for generating meteorological forcing data for microscale urban cli mate simulations using outputs from an open-source mesoscale numerical wea ther prediction model. The proposed approach integrates ERA5 reanalysis da tasets and WRF coupled with an Urban Canopy Model (WRF-UCM) to provide bou ndary forcing for simulations performed in the ENVI-met microscale modelli ng environment. The objective of the study is to demonstrate that mesoscal e model outputs can effectively substitute for local meteorological observ ations in situations where surface measurement data are unavailable or ins ufficient.\nThe methodology follows a multi-scale modelling framework link ing mesoscale and microscale atmospheric simulations. In the first stage\, WRF-UCM simulations are performed for the broader study region using a sy stem of nested domains to achieve progressively higher spatial resolution over the target urban area (Košice city\, Slovakia). The mesoscale model configuration includes appropriate land-use classifications\, urban parame terizations\, and atmospheric boundary conditions to simulate key meteorol ogical variables such as air temperature\, wind speed and direction\, humi dity\, and radiation fluxes.\nIn the second stage\, selected meteorologica l variables from the WRF-UCM output are processed and transformed into for cing datasets compatible with ENVI-met boundary conditions. These datasets provide time-series information for near-surface atmospheric parameters r equired to initialize and drive microscale simulations. The generated forc ing data are subsequently used as input for ENVI-met simulations represent ing detailed urban morphologies at the neighbourhood scale. Within this en vironment\, the microscale model resolves local airflow patterns\, radiati on exchange between urban surfaces\, vegetation interactions\, and turbule nt heat transfer processes.\nA key advantage of the proposed approach lies in its ability to provide physically consistent meteorological forcing de rived from a dynamically simulated atmospheric environment rather than rel ying solely on point measurements from meteorological stations. Mesoscale model outputs capture the influence of large-scale atmospheric circulation patterns\, regional weather systems\, and surrounding terrain features\, all of which significantly influence urban microclimate conditions. Conseq uently\, the generated forcing datasets reflect broader environmental infl uences that may not be represented in boundary conditions by isolated obse rvational measurements.\nThe methodology has been tested for several case studies focusing on urban environments where meteorological observations a re limited or unavailable (Fedor and Hofierka 2022). Simulation results de monstrate that forcing data derived from WRF-UCM outputs can reproduce rea listic temporal variability in key meteorological parameters required for microscale modelling. Comparisons with available observational datasets in dicate that ENVI-met simulations driven by WRF-UCM forcing achieve satisfa ctory agreement with measured temperature and wind conditions\, supporting the reliability of the proposed method.\nThese results suggest that mesos cale model outputs can serve as a viable alternative source of meteorologi cal forcing for microscale urban climate simulations. The approach enables the application of high-resolution urban climate modelling tools in data- scarce environments while maintaining physically consistent boundary condi tions. Additionally\, the integration of mesoscale forcing improves the re presentation of regional atmospheric influences\, including the effects of surrounding topography and synoptic weather patterns.\nThe presented fram ework contributes to the development of multi-scale urban climate modellin g strategies that bridge the gap between regional atmospheric dynamics and local urban microclimates. By combining mesoscale numerical weather predi ction models with detailed microscale simulations\, the approach supports more comprehensive assessments of urban climate processes across spatial s cales.\nThis research builds upon previous studies by the authors investig ating numerical modelling approaches for urban climate analysis and the in tegration of mesoscale and microscale modelling techniques. The proposed m ethodology demonstrates the potential for expanding the applicability of m icroscale urban climate models to regions where conventional observational data are limited\, while maintaining reliable simulation accuracy. In thi s context\, the mesoscale model WRF-UCM\, which is an open-source modellin g system\, provides a transparent and flexible framework for simulating ur ban atmospheric processes and enables reproducible coupling with microscal e models.\nReferences\nFedor\, T.\; Hofierka\, J. 2022: Comparison of urba n heat island diurnal cycles under various atmospheric conditions using WR F-UCM. Atmosphere\, 13(12)\, 2057. DOI: https://doi.org/10.3390/atmos13122 057\nFedor\, T.\; Hofierka\, J. 2025: Estimating heat stress in the urban centre of Košice using ENVI-met and high-resolution surface data. Geograp hia Cassoviensis 19(2)\, pp. 81-94. DOI: https://doi.org/10.3390/atmos1312 2057\nHuttner\, S.\; Bruse\, M.\; Dostal\, P. 2008: Using ENVI-met to simu late the impact of global warming on the microclimate in central European cities. 5th Japanese-German Meeting on Urban Climatology\, October 2008\, pp. 307-312. Available online: https://envi-met.net/documents/papers/Huttn er_etal_2008.pdf (Accessed 4. March 2026).\nSkamarock\, W.C.\; Klemp\, J.B .\; Dudhia\, J. et al. 2019: A Description of the Advanced Research WRF Mo del Version 4. Technical Report NCAR/TN-556+STR. Available online: https: //www.ecampmany.com/docs/cheatsheets/WRF.pdf (Accessed 4. March 2026).\nTe wari\, M.\; Chen\, F.\; Kusaka\, H.\; Miao\, S. 2007: Coupled WRF/Unified Noah/Urban-Canopy Modeling System. Available online: https://ral.ucar.edu/ sites/default/files/public/product-tool/WRF-LSM-Urban.pdf (Accessed 4. Ma rch 2026). DTSTAMP:20260717T220452Z LOCATION:Cosmos2 SUMMARY:Using WRF-UCM as Boundary Forcing for Microscale Models in Data-Sca rce Urban Environments - Tomáš Fedor\, Jaroslav Hofierka URL:https://talks.osgeo.org/foss4g-2026/talk/RTTEQX/ END:VEVENT END:VCALENDAR