THE IMPACT OF HIGH RESOLUTION TERRAIN ON THE PREDICTION OF GROUND ELEMENTS FROM GRAPES MODEL IN SOUTH CHINA
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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。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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Key words:
- GRAPES /
- high resolution terrain /
- SRTM /
- interpolation method /
- boxplot /
- spatial distribution of MAE
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图 2 模式地形高度减实况站点海拔偏差空间分布和绝对海拔偏差箱须图 单位：m。
a. Topo10 m; b. Topo30 s; c. SRTM3 s; d.各试验绝对海拔偏差箱须图。
图 4 个例2 m气温和10 m风速模拟结果对比
a.个例站点选取，横坐标为经度，纵坐标为纬度，填色为海拔高度，▲为选取站点空间分布; b.个例站点海拔对比，横坐标为站号，纵坐标为站点海拔高度，单位：m; c. Control试验24 h预报时效站点2 m气温AE时间序列，横坐标为预报次数，单位：次，纵坐标为温度，单位：℃，2个时次的观测数据缺失，导致线条出现断点; d.同c，但为w16试验; e. Control试验24 h预报时效站点10 m风速AE时间序列，纵坐标为风速，单位：m/s; f.同e，但为w16试验。
图 5 Control试验同w16试验2 m气温和10 m风速MAE空间分布对比
a. Control试验模式24 h预报时效2 m气温MAE空间分布; b.同a，但试验为w16; c. Control试验模式24 h预报时效10 m风速MAE空间分布; d.同c，但试验为w16。
图 6 Control试验和w16试验2017060300个例10 m风速和风向结果对比
a.模式范围24 h预报场Control试验与站点实况10 m风速绝对偏差减去w16试验的空间分布，矩形框为偏差较大区，也是风向偏差重点分析区域，单位：m/s; b.重点分析区域SYNOP资料的16向wind rose(风向玫瑰图)，填色表示风速，风矢端数值为该风向的平均风速; c. Control试验24 h预报时效重点分析区域16向wind rose; d.同c，但为w16试验。
表 1 试验设计表
试验名称 地形数据 试验名称 地形数据 Control Topo10 m w16 SRTM3s w16 30 s Topo30 s w4 SRTM3s w4 3 s SRTM3s 
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