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首页> 外文期刊>Advances in Meteorology >Seasonal Multifactor Modelling of Weighted-Mean Temperature for Ground-Based GNSS Meteorology in Hunan, China
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Seasonal Multifactor Modelling of Weighted-Mean Temperature for Ground-Based GNSS Meteorology in Hunan, China

机译：湖南地下GNSS气象加权平均温度季节性多因素建模

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摘要

In this study, radiosonde observations during the period of 2012-2013 from three stations in the Hunan region, China, were used to establish regional T_m models (RTMs) that are a fitting function of multiple meteorological factors (T_s, E_s, and P_s). One-factor, two-factor, and three-factor RTMs were assessed by comparing their T_m against the radiosonde-derived T_m (as the truth) during the period of 2013-2014. Statistical results showed that the bias and RMS of the one-factor RTM, in comparison to the BTMresult, were reduced by 88% and 28%, respectively.The two-factor and three-factor RTMs showed similar accuracy and both outperformed the one-factor RTM, with an improvement of 7%in RMS.The bias and RMS of all the four seasonal two-factor RTMs were smaller than the yearly two-factor RTM, with the improvements of 3%, 10%, 2%, and 3% in RMS.The improvement of the conversion factors in mean bias and RMS resulting from the seasonal two-factor RTMis 92% and 31%.The bias and RMS of the PWV resulting from the seasonal two-factor RTM are improved by 37% and 12%, respectively.Therefore, the seasonal two-factor RTMs are recommended for the research and applications of GNSS meteorology in the Hunan region, China.
机译：在本研究中，中国湖南地区三个站的可无线电探测观测用于建立区域T_M模型（RTMS），这是多种气象因素的拟合功能（T_S，E_S和P_S） 。通过将它们的T_M与可无线电探测器衍生的T_M（作为真相）进行比较来评估单因素，双因素和三因素RTMS。统计结果表明，与BTMResult相比，单因素RTM的偏差和RM分别降低了88％和28％。双因素和三因素的RTMS显示出类似的准确性，并且两者都表现出了因素RTM，RMS的提高为7％。所有四个季节性双因素RTM的偏差和均方则小于年度双因素RTM，其改善为3％，10％，2％和3 RMS的百分比。季节性双因素RTMIS的平均偏差和RMS的转化因子改善了92％和31％。由季节性双因素RTM产生的PWV的偏差和RMS提高了37％和分别为12％。因此，建议季节性双因素rtms进行中国湖南地区GNSS气象的研究和应用。

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