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下投式探空仪风速测量误差修正

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针对下投式探空仪在风速变化过程中所产生的滞后误差问题,设计了适用于0~16 km下投式探空仪的风速修正软件,对探空仪测量的风速进行修正.使用计算流体动力学(computational fluid dynamics,CFD)方法对探空仪在高空中不同海拔和不同风速进行仿真;随后,基于仿真结果,采用BP(back propagation)神经网络模型拟合风速误差修正方程,并将其嵌入到所设计的软件中进行实际应用.为验证方程的准确性,进行外场探空仪低空投放实验.实验结果表明,经系统软件修正后的风速与基准值的均方根误差(root mean square error,RMSE)和平均绝对误差(mean absolute error,MAE)分别为0.371 m·s-1和0.138 m·s-1,显著提高了风速测量的准确性.
Error correction of wind speed measurement for dropwindsonde
A wind speed correction software for 0~16 km dropwindsonde was designed as a countermeasure to the problem of hyster-esis error of dropwindsonde in the process of wind speed change. Computational fluid dynamics (CFD) method was utilized to simu-late for dropwindsonde in different high altitude and wind speeds. The BP neural network model was used subsequently based on the simulation results to fit the wind speed error correction equations,which were embedded into the designed software for practical application. Additionally,to verify the accuracy of the equations,the outfield sounding device placement experiments were carried out. The experimental results show that the root mean square error (RMSE) and the mean absolute error (MAE) of the wind speed values corrected by the system software concerning the reference values are 0.371 m·s-1 and 0.138 m·s-1,respectively,indicating a significantly improvement of the wind speed measurement accuracy.

dropwindsondewind errorcomputational fluid dynamics(CFD)BP neural network

刘鸿、刘清惓、邹永奇、王柯、杨俊辉

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南京信息工程大学江苏省大气环境与装备技术协同创新中心,南京 210044

江苏省气象探测与信息处理重点实验室(南京信息工程大学),南京 210044

南京信息工程大学电子与信息工程学院,南京 210044

下投式探空仪 风速误差 计算流体动力学 BP神经网络

2024

中国科技论文
教育部科技发展中心

中国科技论文

影响因子:0.466
ISSN:2095-2783
年,卷(期):2024.19(12)