Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)
Spatial Distribution of Sensible and Latent Heat Flux in the City of Basel (Switzerland)
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DOI：
10.1109/jstars.2018.2807815
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发表时间：
2018-08-01
影响因子：
5.5
通讯作者：
Chrysoulakis, Nektarios
中科院分区：
文献类型：
--
作者：
Feigenwinter, Christian;Vogt, Roland;Chrysoulakis, Nektarios
城市地表是不同土地覆盖和地表材料的复杂混合物；因此，地表能量平衡分量的相对大小在城市中变化很大。涡度协方差(EC)测量提供了对湍流热通量的最佳估计，但仅限于源区。使用地球观测(EO)数据进行陆面建模有利于更大范围的外推，因为全市范围的信息是可能的。湍流感热和潜热通量的计算结合了微气象方法(空气动力学阻力方法，ARM)、EO资料和地理信息系统技术。土地覆盖比例和地表温度等输入数据来自Landsat 8 OLI和TIR，城市形态由高分辨率数字建筑模型和地理信息系统数据层计算，气象数据由通量塔测量提供。分析了覆盖所有季节和不同气象条件的22个陆地卫星场景。感热通量在工业区、火车站和建筑密度高的区域最高，主要对应于地表与空气温差最大的像素。潜热通量的空间分布与水汽饱和亏和不同植被类型的气孔阻力(最小)密切相关。季节变化在很大程度上取决于气象条件，即气温、水汽饱和差和风速。由于建模方法的已知缺陷和EC测量固有的不确定性，特别是在城市地区，将测量的通量与通量塔加权源区的模拟通量进行比较是相当准确的。
Urban surfaces are a complex mixture of different land covers and surface materials; the relative magnitudes of the surface energy balance components therefore vary widely across a city. Eddy covariance (EC) measurements provide the best estimates of turbulent heat fluxes but are restricted to the source area. Land surface modeling with earth observation (EO) data is beneficial for extrapolation of a larger area since citywide information is possible. Turbulent sensible and latent heat fluxes are calculated by a combination of micrometeorological approaches (the aerodynamic resistance method, ARM), EO data, and GIS techniques. Input data such as land cover fractions and surface temperatures are derived from Landsat 8 OLI and TIRS, urban morphology was calculated from high-resolution digital building models and GIS data layers, and meteorological data were provided by flux tower measurements. Twenty-two Landsat scenes covering all seasons and different meteorological conditions were analyzed. Sensible heat fluxes were highest for industrial areas, railway stations, and areas with high building density, mainly corresponding to the pixels with highest surface-to-air temperature differences. The spatial distribution of latent heat flux is strongly related to the saturation deficit of vapor and the (minimum) stomatal resistance of vegetation types. Seasonal variations are highly dependent on meteorological conditions, i.e., air temperature, water vapor saturation deficit, and wind speed. Comparison of measured fluxes with modeled fluxes in the weighted source area of the flux towers is moderately accurate due to known drawbacks in the modeling approach and uncertainties inherent to EC measurements, particularly in urban areas.