一种基于Emardson-H的GPT3改进模型构建方法

An Improved GPT3 Model Established by Emardson-H Method

针对GPT3模型各气象参数存在明显周期性误差的问题,以2015~2019年长三角地区7个探空站资料作为参考,分析GPT3模型残差的季节性周期变化,并利用Emardson-H模型构建一种新的GPT3改进模型。实验结果表明:1)与探空资料相比,GPT3模型气压、温度、水汽压和加权平均温度(T_(m))的均方根(RMS)均值分别为5.09 hPa、3.90 K、4.01 hPa和4.54 K;2)基于Emardson-H的GPT3改进模型气压、温度、水汽压和T_(m)的RMS均值分别为4.64 hPa、3.53 K、3.73 hPa和3.27 K,比GPT3模型分别提升0.45 hPa、0.37 K、0.28 hPa和1.27 K。综上分析,基于Emardson-H的GPT3改进模型精度相比GPT3模型有所改进。

Aiming at the obvious periodic errors of the meteorological parameters derived from the GPT3 model,we use the seven radiosonde stations in the Yangtze river delta region during 2015 to 2019 as references to analyze the seasonal periodic changes of meteorological residuals of the GPT3 model.We use the Emardson-H model to establish a new improved GPT3 model.The results show that the root mean square(RMS)of pressure,temperature,vapor pressure and weighted average temperature(T_(m))of the GPT3 model are 5.09 hPa,3.90 K,4.01 hPa and 4.54 K respectively compared to the reference values of radiosondes.Their mean RMS of the improved GPT3 model based on Emardson-H are 4.64 hPa,3.53 K,3.73 hPa and 3.27 K respectively,improved by 0.45 hPa,0.37 K,0.28 hPa and 1.27 K in comparison to the GPT3 model.Therefore,the precision of the improved GPT3 model based on Emardson-H is better than that of the GPT3 model.