Sensitivity of mesoscale modeling to urban morphological feature inputs and implications for characterizing urban sustainability

Abstract We examine the differences in meteorological output from the Weather Research and Forecasting (WRF) model run at 270 m horizontal resolution using 10 m, 100 m and 1 km resolution 3D neighborhood morphological inputs and with no morphological inputs. We find that the spatial variability in t...

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Bibliographic Details
Main Authors: Melissa R. Allen-Dumas, Levi T. Sweet-Breu, Christa M. Brelsford, Linying Wang, Joshua R. New, Brett C. Bass
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:npj Urban Sustainability
Online Access:https://doi.org/10.1038/s42949-024-00185-6
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Summary:Abstract We examine the differences in meteorological output from the Weather Research and Forecasting (WRF) model run at 270 m horizontal resolution using 10 m, 100 m and 1 km resolution 3D neighborhood morphological inputs and with no morphological inputs. We find that the spatial variability in temperature, humidity, and other meteorological variables across the city can vary with the resolution and the coverage of the 3D urban morphological input, and that larger differences occur between simulations run without 3D morphological input and those run with some type of 3D morphology. We also find that the inclusion of input-building-defined roughness length calculations would improve simulation results further. We show that these inputs produce different patterns of heat wave spatial heterogeneity across the city of Washington, DC. These findings suggest that understanding neighborhood level urban sustainability under extreme heat waves, especially for vulnerable neighborhoods, requires attention to the representation of surface terrain in numerical weather models.
ISSN:2661-8001