引用本文: 朱明晨, 胡伍生, 王来顺. GPT2w模型在中国区域的精度检验与分析[J]. 武汉大学学报 ( 信息科学版), 2019, 44(9): 1304-1311.
ZHU Mingchen, HU Wusheng, WANG Laishun. Accuracy Test and Analysis for GPT2w Model in China[J]. Geomatics and Information Science of Wuhan University, 2019, 44(9): 1304-1311.
 Citation: ZHU Mingchen, HU Wusheng, WANG Laishun. Accuracy Test and Analysis for GPT2w Model in China[J]. Geomatics and Information Science of Wuhan University, 2019, 44(9): 1304-1311.

## Accuracy Test and Analysis for GPT2w Model in China

• 摘要: 全球温度气压湿度（global pressure and temperature 2 wet，GPT2w）模型常被用于计算某一位置的气温、加权平均温度、气压以及水汽压等各种气象参数，是目前公开的标称精度最高的对流层延迟经验模型。利用中国区域参与全球气象交换的86个测站2013-2015年的气象探空数据，对GPT2w得到的各种气象参数进行精度检验及分析。实验结果表明，气温平均偏差为1.31℃，均方根误差为3.62℃；加权平均温度的平均偏差为-1.58 K，均方根误差为4.07 K；气压和水汽压平均偏差的绝对值在1 hPa以内，其均方根误差分别为6.98 hPa与3.04 hPa。利用2006-2015年的数据分析了不同纬度模型精度的周期性特征，结果表明，气温、加权平均温度、气压和水汽压的均方根误差均具有一定的年周期特性，且在不同的纬度区域其周期特性不同。总体而言，GPT2w模型在中国地区范围内具有较高的精度和稳定性。

Abstract: GPT2w model is commonly used to calculate the meteorological parameters at certain location, such as temperature, weighted mean temperature, pressure and vapor pressure. It is also the public empirical model for tropospheric delay with the best nominal accuracy. In this paper, meteorological sounding data from 2013-2015 of 86 stations in China is used, which have participated the global meteorological exchange. Precisions of meteorological parameters from GPT2w are examined and analyzed. It turns out that the average bias (Bias) and root mean square error (RMS) of temperature are 1.31℃ and 3.62℃, respectively. For weighted mean temperature, the Bias is -1.58 K and the RMS is 4.07 K. For pressure and vapor pressure, the absolute values of Bias are smaller than 1 hPa, and the RMS are 6.98 hPa and 3.04 hPa, respectively. Using the data from 2006-2015, periodic characterization of the accuracy of different latitude models are analyzed. It turns out that the RMS of temperature, weighted mean temperature, pressure and vapor pressure shows certain periodic patterns, and differs with different latitude regions. In general, GPT2w model exhibits high precision and stability within the area of China.

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