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Urban microclimate exerts a significant influence on building indoor thermal performance, yet the coupled assessment of outdoor–indoor conditions, and the predictive evaluation of urban interventions prior to implementation, remain computationally and methodologically demanding. This study develops an automated, user-oriented workflow to evaluate how neighbourhood-scale urban interventions influence both outdoor heat exposure and indoor thermal comfort. The proposed parametric pipeline links open-source Geographic Information Systems (GIS) data, Grasshopper-based algorithmic modelling, the Vertical City Weather Generator (VCWG), and EnergyPlus Weather file morphing for building energy simulation. The workflow automates urban data extraction, parametric model generation, remote microclimate simulation, and climate-file preparation, allowing seasonal assessments without requiring Python programming expertise. Its capabilities are compared with Urban Weather Generator (UWG) and ENVI-met, revealing that, among the analysed tools, VCWG provides a balanced combination of sensitivity to radiative properties and vegetation changes, long-term simulation capacity, and operational computation times. The workflow is applied to a mid-20th century residential neighbourhood in Seville, Spain, under three scenarios: baseline, higher-reflectance surfaces, and a combined reflectance and vegetation strategy. Results illustrate the pipeline’s capacity to capture multi-scale thermal effects: outdoor air temperature reductions of up to −3 °C (mean summer decrease of −0.84 °C) translated into a mean indoor temperature reduction of −1.1 °C and a 14% increase in passively comfortable summer hours under the modelled conditions, achieved solely through urban modifications. These results demonstrate that urban-scale surface and vegetation strategies can measurably improve indoor comfort. The workflow offers a practical, replicable decision-support tool for climate-adaptation planning in heat-vulnerable urban neighbourhoods.

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