摘要
提出一种基于GPT2w模型化加权平均温度反演大气可降水量的方法,并分析附加系统偏差改正的模型化加权平均温度对可降水量的影响。结果表明,基于GPT2w模型化加权平均温度反演的大气可降水量的精度与基于Bevis公式计算的加权平均温度反演的大气可降水量的精度相当;对GPT2w模型化加权平均温度进行系统偏差改正后,大气可降水量的精度有一定改善,但改善率不到1%。
We propose a method based on weighted mean temperature derived from GPT2 w to retrieve precipitable water vapor, and analyze the influence of the weighted mean temperature with systematic correction derived from GPT2 w on precipitable water vapor. The results show that the precision of precipitable water vapor based on weighted mean temperature derived from GPT2 w is comparable with that of precipitable water vapor based on weighted mean temperature by Bevis formula, and that weighted mean temperature with systematic correction has little influence on precipitable water vapor, the improvement rate is less than 1%.
引文
[1] Braun J J,Rocken C.Water Vapor Tomography within the Planetary Boundary Layer Using GPS[C].International Workshop on GPS Meteorology,Tsukyba,2003
[2] 张双成,刘经南,叶世榕,等.顾及双差残差反演GPS信号方向的斜路径水汽含量[J].武汉大学学报:信息科学版,2009,34(1):100-104(Zhang Shuangcheng,Liu Jingnan,Ye Shirong,et al.Retrieval of Water Vapor along the GPS Slant Path Based on Double-Differenced Residuals[J].Geomatics and Information Science of Wuhan University,2009,34(1):100-104)
[3] 范士杰,臧建飞,刘焱雄,等.GPT/2模型用于GPS大气可降水量反演的精度分析[J].测绘工程,2016,25(3):1-5(Fan Shijie,Zang Jianfei,Liu Yanxiong,et al.Accuracy Analysis on GPS Precipitable Water Vapor Inversion Using GPT/2 Models[J].Engineering of Surveying and Mapping,2016,25(3):1-5)
[4] B?hm J,M?ller G,Schindelegger M,et al.Development of an Improved Empirical Model for Slant Delays in the Troposphere(GPT2w)[J].GPS Solutions,2015,19(3):433-441
[5] Saastamoinen J.Contribution to the Theory of Atmospheric Refraction PartⅡ,Refraction Corrections in Satellite Geodesy[J].Bulletin Geodesique,1972,107:13-34
[6] Bevis M,Businger S,Herring T A,et al.GPS Meteorology:Remote Sensing of Atmospheric Water Vapor Using the Global Positioning System [J].Journal of Geophysical Research,1992,97(D14):15 787-15 801
[7] 陈正生.大规模GNSS测量数据分布式计算关键技术研究[D].郑州:信息工程大学,2014(Chen Zhengsheng.Research on the Key Techniques of Distributed Processing on Large Scale GNSS Observation Data[D].Zhengzhou:Information Engineering University,2014)
[8] 滑中豪,柳林涛,梁星辉.GPT2w模型检验以及对流层模型的参数互融[J].武汉大学学报:信息科学版,2017,42(10):1 468-1 473(Hua Zhonghao,Liu Lintao,Liang Xinghui.An Assessment of GPT2w Model and Fusion of a Troposphere Model with in Situ Data[J].Geomatics and Information Science of Wuhan University,2017,42(10):1 468-1 473)