| 两种GPT系列对流层经验模型精度分析 |
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| 引用本文： | 武可强,王建强. 两种GPT系列对流层经验模型精度分析[J]. 测绘与空间地理信息, 2020, 0(3): 76-78 |
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| 作者姓名： | 武可强 王建强 |
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| 作者单位： | 东华理工大学测绘工程学院 |
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| 摘 要： | 针对很多测站不能提供实测气象数据的情况,本文对两种高精度的GPT系列经验模型进行验证。通过对两种模型获得的经验气象数据及对计算可降水汽非常重要的ZHD的精度进行分析,得出如下结论:GPT2w模型的精度要高于GPT2模型,且在无实测气象数据的情况下可以使用GPT2w模型来进行GNSS水汽反演。
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| 关 键 词： | 经验模型 可降水汽 GPT2w模型 气象数据 |
Accuracy Analysis of Two GPT Series Tropospheric Empirical Models |
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| WU Keqiang,WANG Jianqiang. Accuracy Analysis of Two GPT Series Tropospheric Empirical Models[J]. Geomatics & Spatial Information Technology, 2020, 0(3): 76-78 |
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| Authors: | WU Keqiang WANG Jianqiang |
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| Affiliation: | (Faculty of Geomatics,East China Institute of Technology,Nanchang 330013,China) |
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| Abstract: | In view of the fact that many stations cannot provide measured meteorological data,this paper verifies two high-precision GPT series empirical models. The empirical meteorological data obtained from the two models and the accuracy of the ZHD,which is important for calculating the water vapor,are analyzed. It is concluded that the accuracy of the GPT2w model is higher than that of the GPT2 model,and the GPT2w model can be used for GNSS water vapor inversion without the measured meteorological data. |
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| Keywords: | empirical model water vapor GPT2w model meteorological data |
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