| 高分辨地形对华南区域GRAPES模式地面要素预报影响的研究 |
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| 引用本文： | 朱文达,陈子通,张艳霞,杨静,张媛.高分辨地形对华南区域GRAPES模式地面要素预报影响的研究[J].热带气象学报,2019,35(6):801-811. |
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| 作者姓名： | 朱文达 陈子通 张艳霞 杨静 张媛 |
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| 作者单位： | 1.贵州省气象台, 贵州 贵阳 550001 |
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| 基金项目： | 国家自然科学基金41565001 |
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| 摘 要： | 华南区域GRAPES模式动力框架的更新使得高分辨地形数据能够进入模式。引入SRTM数据实现静态数据更新，结合模式内置数据，进行了批量模拟试验；通过站点检验方式，对批量试验结果进行对比，得出以下结论:对比业务使用的Topo10 m地形、Topo30 s地形、SRTM地形和基于SRTM多种插值方案得到的地形，海拔偏差的空间分布和分位数统计都有明显的改善，复杂地形区域的改善效果更显著。通过地面要素平均绝对误差(MAE)箱须图统计和模式西部站点绝对误差(AE)时间序列图对比分析，发现高分辨地形试验的2 m气温和10 m风速MAE和AE有大幅度的改善。高分辨地形对模式静态数据的改善是2 m气温和10 m风速MAE下降的主要原因，地形复杂区域对MAE改善的贡献高于模式其他区域。高分辨地形进入模式后会引起动力过程计算的虚假扰动，适当的滤波平滑能够抑制扰动，从而进一步提高预报精度。
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| 关 键 词： | GRAPES 高分辨地形 SRTM 插值方法 箱须图 MAE空间分布 |
| 收稿时间： | 2019-03-18 |
THE IMPACT OF HIGH RESOLUTION TERRAIN ON THE PREDICTION OF GROUND ELEMENTS FROM GRAPES MODEL IN SOUTH CHINA |
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| ZHU Wen-d,CHEN Zi-tong,ZHANG Yan-xi,YANG Jing and ZHANG Yuan.THE IMPACT OF HIGH RESOLUTION TERRAIN ON THE PREDICTION OF GROUND ELEMENTS FROM GRAPES MODEL IN SOUTH CHINA[J].Journal of Tropical Meteorology,2019,35(6):801-811. |
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| Authors: | ZHU Wen-d CHEN Zi-tong ZHANG Yan-xi YANG Jing and ZHANG Yuan |
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| Institution: | 1.Guizhou Meteorological Observatory, Guiyang 550002, China2.Guangzhou Institute of Tropical and Marine Meteorology/Guangdong Provincial Key Laboratory of Regional Numerical Weather Prediction, CMA, Guangzhou 510641, China3.Guizhou Air Traffic Management Bureau of CAAC, Guiyang 550012, China |
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| Abstract: | The updating of the GRAPES model dynamics framework in south China enabled the model to include high-resolution terrain data. The Shuttle Radar Topography Mission (SRTM) data was introduced to update the static data of the model, and combined with the built-in terrain data of the model, a batch simulation experiment was carried out. The batch test was compared by using the station verification method. The results are shown as follows. Topo30 s terrain data, SRTM terrain, and terrain derived from various SRTM-based interpolation schemes, compared to the Topo10 m terrain currently used in the comparison mode, improve significantly in both the spatial distribution of altitude deviation and quartile statistics, especially so in complex terrain areas. The statistics of the boxplot of Mean Absolute Error (MAE) and the comparison of the Absolute Error (AE) time series of stations in the west of the model show that the MAE and AE of 2 m temperature and 10m wind speed of the high-resolution terrain experiments are greatly improved. The improvement of static data with high-resolution terrain is the main reason for the decrease of MAE in 2 m temperature and 10 m wind speed. Complex terrain contributes more to MAE improvement than other areas of the model. When the high-resolution terrain is introduced to the model, it causes the fictitious disturbance of the dynamic process calculation, and proper filtering suppresses it and further improves the prediction accuracy. |
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| Keywords: | GRAPES high resolution terrain SRTM interpolation method boxplot spatial distribution of MAE |
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