Interpolating diurnal surface temperatures of an urban facet using sporadic thermal observations
Interpolating diurnal surface temperatures of an urban facet using sporadic thermal observations
复制标题
使用零星热观测值插值城市面的日表面温度
DOI：
10.1016/j.buildenv.2012.05.005
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发表时间：
2012-11
影响因子：
7.4
通讯作者：
Ma, Wei
中科院分区：
文献类型：
--
作者：
Zhan, Wenfeng;Chen, Yunhao;Voogt, James;Zhou, Ji;Wang, Jinfei;Liu, Wenyu;Ma, Wei
城市地表温度（USTs）的内插对于利用卫星的时间零星观测和理解城市气候至关重要。这项研究直接连接昼夜UST与热惯性，并提出了一种基于物理的方法来插值的昼夜UST的城市方面与零星的热观测。将解析法和数值法相结合，求解了多力边界条件下的热传导方程。日平面温度和日气温参数化表示环境强迫。结果表明，日平表面温度和日气温都是较好的选择，但前者更能反映城市峡谷的环境强迫。利用真实的建筑物和缩尺模型的数据进行了验证，结果表明UST的内插均方根误差在2 K以内。方法之间的相互比较也表明，所提出的模型是有效的预测不连续的热观测的UST。
The interpolation of urban surface temperatures (USTs) is crucial to the utilization of temporally sporadic observations from satellites and to understanding urban climate. This study directly connects diurnal USTs with thermal inertia and presents a physically based approach to interpolate the diurnal USTs of an urban facet with sporadic thermal observations. Analytical and numerical methods are combined to solve the heat conduction equation constrained by a multi-force boundary condition. The diurnal flat surface temperatures and the diurnal air temperatures are parameterized to denote the environmental forcing. The results indicate that both the diurnal flat surface temperatures and the diurnal air temperatures are good options, but the former are better than the latter at representing environmental forcing in urban canyons. Data from both the real building and the scale model are utilized in validations, and results show that the interpolated root mean square errors of the UST are within 2 K. The inter-comparison between methods also suggests the presented model is efficient for predicting USTs with discontinuous thermal observations.
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影响因子：
4.3
作者：
JOHNSON, GT;OKE, TR;VOOGT, JA
通讯作者：
VOOGT, JA
影响因子：
3.4
作者：
A. Cracknell;Yong Xue
通讯作者：
A. Cracknell;Yong Xue
影响因子：
1.9
作者：
N. Ben-yosef;S. Lashansky;K. Wilner;M. Abitbol
通讯作者：
N. Ben-yosef;S. Lashansky;K. Wilner;M. Abitbol
影响因子：
8.2
作者：
W. Zhan;Yunhao Chen;Ji Zhou;Jing Li;Wenyu Liu-
通讯作者：
W. Zhan;Yunhao Chen;Ji Zhou;Jing Li;Wenyu Liu-
影响因子：
1.3
作者：
R. Balling;Sandra W. Brazel
通讯作者：
R. Balling;Sandra W. Brazel