利用CORS站研究多因子分季节可降水量转换模型

Research on multi-factor seasonal precipitable water vapor model based on CORS station

针对GNSS气象学中可降水量转换过程较为复杂的问题,利用2017年江苏CORS站及其并址探空数据,分析大气可降水量(PWV)与天顶对流层延迟(ZTD)、温度和气压之间的相关性,采用线性回归拟合法建立多因子分季节PWV模型,并用2017—2018年数据验证模型精度。结果表明PWV与ZTD有很强的线性相关性,相关系数为0.9803,PWV与温度和气压有较强的相关性,相关系数分别为0.6112和-0.6136;全年PWV模型中,单、双、多因子模型的RMS分别为2.88、1.70和0.49 mm,精度依次提高;多因子PWV模型中,分季节PWV模型较全年PWV模型的RMS分别提高0.23、0.20、0.18和0.37 mm,精度明显优于全年模型。因此,多因子分季节PWV模型预测精度优于1 mm,满足GNSS监测水汽的气象应用精度要求。

In view of the complicated conversion process of precipitable water vapor(PWV)in GNSS meteorology,the GNSS and radiosonde data of CORS station in Jiangsu province during 2017 were used to analyze the correlation between atmospheric PWV and zenith tropospheric delay(ZTD),temperature and air pressure in this paper.Several multi-factor seasonal PWV models were established by using linear regression fitting and their accuracy were verified by the data during 2017-2018.The results show that PWV has a strong linear correlation with ZTD,with a correlation coefficient of 0.9803.PWV has a strong correlation with temperature and air pressure,with a correlation coefficient of 0.6112 and-0.6136 respectively.The RMS of single,double and multifactor yearly PWV models are 2.88 mm,1.70 mm and 0.49 mm respectively.The multi-factor seasonal PWV models are improved by 0.23 mm,0.20 mm,0.18 mm and 0.37 mm compared to the yearly PWV model.Therefore,the accuracy of multi-factor seasonal PWV models are better than 1 mm,which meets the application accuracy requirements of GNSS meteorology for monitoring atmospheric water vapor.