Enhancing Urban Climate Models with NATURF's High-Resolution Data
NATURF generates high-resolution urban parameters for the Weather Research and Forecasting (WRF) model, enhancing microclimate studies with high-resolution building-level data.
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Understanding how urban morphology influences microclimates in cities and is a big challenge. Our research introduces a tool called NATURF to help with this. NATURF uses data about buildings, like their shape and height, to better how they influence local weather dynamics. This is important because buildings can make areas hotter or cooler, which affects energy use and health. Urban planners can use NATURF to see how new buildings might change the urban microclimate dynamics in a neighborhood. This helps make better decisions for future planning.
Our research introduces NATURF, a tool that helps us understand how buildings affect local weather patterns. This is important because cities can change the climate around them, impacting health and energy use. NATURF is the first tool of its kind to offer high-resolution building data compatible with WRF from a scalable and extensible open-source software. It allows scientists to study urban microclimate effects more precisely.
We develop NATURF, open-source Python software designed to generate urban parameters for use with the WRF model. By leveraging building-level data, NATURF provides high-resolution, three-dimensional representations of urban surfaces, enabling detailed studies of urban microclimate effects on energy use. Unlike previous tools that rely on satellite data, NATURF uses geospatial vector data containing building footprint and height information, allowing for high-resolution modeling at any location with available data. This flexibility is crucial for urban modelers to assess how building and neighborhood morphology impact local climate.