顾及非线性高程归算的全球加权平均温度模型

Global Weighted Mean Temperature Model Considering Nonlinear Vertical Reduction

  • 摘要: 加权平均温度(Tm)是全球导航卫星系统技术中反演可降水量的关键参数。利用欧洲中期天气预报中心(European Centre for Medium-Range Weather Forecasts,ECMWF)的产品对Tm在垂直方向上的分布特性进行分析,并构建了一种新的全球Tm模型。利用ECMWF和无线电探空数据对该模型进行检验,并将其与现存的高精度Tm模型进行比较。实验结果显示,Tm在高程方向上存在非线性变化特征,而且该特征在高纬度地区特别是两极区域尤为明显。当利用ECMWF和探空数据检验构建的Tm模型时,其均方根误差分别为3.84 K和4.36 K,相比于现存的Tm模型精度分别提升了27%和20%。构建的模型可以显著提升Tm在垂直方向上的归算效果,由该模型计算出的Tm廓线与参考值更加接近。

     

    Abstract: Weighted mean temperature (Tm) is a critical parameter in global navigation satellite system technology to retrieve precipitable water vapor. In this paper, the products from the European Center for Medium-Range Weather Forecasts (ECMWF) are used to analyze the distribution trait of Tm along the vertical direction, and to establish a new global Tm model. The ECMWF and radiosonde data are used to validate this newly built model, and an existing high-accuracy Tm model is employed for comparison. The results show that Tm has nonlinear variation trait along the vertical direction, and this trait is specifically apparent in the high-latitude regions, especially in the polar areas. When tested with the ECMWF and the radiosonde data, the root mean square (RMS) of the newly built model are 3.84 K and 4.36 K, respectively, achieving accuracy improvements of 27% and 20% compared to the existing model. The correction performance for Tm along the vertical direction is increased noticeably and the Tm profile calculated by the model proposed in this paper is much closer to the reference.

     

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