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

IF 9.1 Q1 ENVIRONMENTAL STUDIES
Melissa R. Allen-Dumas, Levi T. Sweet-Breu, Christa M. Brelsford, Linying Wang, Joshua R. New, Brett C. Bass
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引用次数: 0

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.

Abstract Image

中尺度模式对城市形态特征输入的敏感性及其对城市可持续性特征的影响
我们研究了在270米水平分辨率下运行的天气研究与预报(WRF)模式,使用10米、100米和1公里分辨率的3D邻域形态输入和不使用形态输入的气象输出的差异。研究发现,城市温度、湿度等气象变量的空间变异性会随着城市三维形态输入的分辨率和覆盖范围的不同而发生变化,并且在没有三维形态输入的模拟与具有某种三维形态输入的模拟之间差异更大。我们还发现,包含输入构建定义的粗糙度长度计算将进一步改善模拟结果。我们表明,这些输入在整个华盛顿特区产生了不同的热浪空间异质性模式。这些发现表明,要理解极端热浪下社区层面的城市可持续性,特别是对脆弱社区而言,需要注意数值天气模式中地表地形的表示。
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