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Sensitivity Study on High-Resolution Numerical Modeling of Static Topographic Data

机译：静态地形数据高分辨率数值建模的敏感性研究

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Both research-grade and operational numerical weather prediction models perform simulations with horizontal grid spacings as fine as 1 km, and their multi-scale terrain data have become increasingly important for high-resolution model forecasting. This study focused on the influence of multi-scale surface databases of topographical height and land use on the modeling of atmospheric circulation in a megacity. The default data were the global 30S United States Geographic Survey terrain data set and Moderate Resolution Imaging Spectroradiometer land-use data. The capacity for topographical expression under the combined scale effect was evaluated against observational data. The experiments showed that surface input data using finer resolutions for the Weather Research and Forecasting model with 1-km resolution gave better topographical expression and meteorological reproduction in a megacity and agreed with observational data in the fields of temperature and relative humidity, but precipitation values were not sensitive to the surface input data when verified against a suite of observational data including, but not limited to, ground-based instruments. The results indicated that the use of high-resolution databases improved the local atmospheric circulation in a megacity and that a fine-scale model was sensitive to the resolution of the surface input data whereas a coarse-scale model was less sensitive to it.
机译：研究级和可操作的数值天气预报模型都可以使用水平网格间距精确到1 km进行模拟，并且它们的多尺度地形数据对于高分辨率模型预测变得越来越重要。这项研究集中于地形高度和土地利用的多尺度表面数据库对特大城市大气环流建模的影响。默认数据是全球30S美国地理调查地形数据集和中分辨率成像光谱仪土地使用数据。根据观察数据评估了组合比例效应下的地形表达能力。实验表明，对于分辨率为1 km的“天气研究和预报”模型，使用更高分辨率的地表输入数据在特大城市中具有更好的地形表达和气象再现性，并且与温度和相对湿度领域的观测数据相符，但降水量为当对照一组观测数据（包括但不限于地面仪器）进行验证时，对地面输入数据不敏感。结果表明，高分辨率数据库的使用改善了大城市的局部大气环流，精细模型对表面输入数据的分辨率敏感，而粗糙模型对表面输入数据的敏感性较低。

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