Scale matching of multiscale digital elevation model (DEM) data and the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong
Scale matching of multiscale digital elevation model (DEM) data and the Weather Research and Forecasting (WRF) model: a case study of meteorological simulation in Hong Kong
复制标题
多尺度数字高程模型（DEM）数据与天气研究及预报（WRF）模型的尺度匹配：以香港气象模拟为例
DOI：
10.1007/s12517-014-1273-6
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发表时间：
2014
期刊：
影响因子：
--
通讯作者：
Liang Yang
中科院分区：
文献类型：
--
作者：
Chunxiao Zhang;Hui Lin;Min Chen;Liang Yang
将地理数据和动态模型结合起来为解决问题和地理认知提供信息变得越来越容易。然而，数据、模型和过程的规模依赖性可能会混淆结果。本研究将静态地理格局的传统尺度研究延伸到动态过程，重点研究多尺度地理数据和动态模型的组合尺度效应。以香港多尺度地形数据和气象过程为例，研究组合尺度效应下的地形表达能力。根据香港天文台站的数据评估了组合尺度效应的气象模拟。实验表明：(1) 使用 3 角秒数据和 1 公里分辨率的天气研究和预报 (WRF) 模型的数字高程模型 (DEM) 可以在香港提供更好的地形表达和气象再现； (2)细尺度模型对DEM数据的分辨率敏感，而粗尺度模型对DEM数据的分辨率不太敏感； (3) 单独更好的地形表达并不能改善天气过程模拟； (4) DEM 数据与动态模型之间的尺度不匹配所产生的不确定性可能占某些气象变量（例如温度）方差的 38%。该案例研究清楚地解释了多尺度地理数据和动态模型的尺度匹配的意义和实现。
It is becoming easier to combine geographical data and dynamic models to provide information for problem solving and geographical cognition. However, the scale dependencies of the data, model, and process can confuse the results. This study extends traditional scale research in static geographical patterns to dynamic processes and focuses on the combined scale effect of multiscale geographical data and dynamic models. The capacity for topographical expression under the combined scale effect was investigated by taking multiscale topographical data and meteorological processes in Hong Kong as a case study. A meteorological simulation of the combined scale effect was evaluated against data from Hong Kong Observatory stations. The experiments showed that (1) a digital elevation model (DEM) using 3 arc sec data with a 1 km resolution Weather Research and Forecasting (WRF) model gives better topographical expression and meteorological reproduction in Hong Kong; (2) a fine-scale model is sensitive to the resolution of the DEM data, whereas a coarse-scale model is less sensitive to it; (3) better topographical expression alone does not improve weather process simulation; and (4) uncertainty arising from a scale mismatch between the DEM data and the dynamic model may account for 38 % of the variance in certain meteorological variables (e.g., temperature). This case study gives a clear explanation of the significance and implementation of scale matching for multiscale geographical data and dynamic models.