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超快速星历的实测信息和预报信息反演大气可降水量的误差分析 被引量:4

Error Analysis of Inversion of Atmospheric Precipitable Water Vapor by Measured and Forecast of Ultra-rapid Ephemeris
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摘要 在近实时观测水汽中,需要精确的卫星星历文件。为了确定IGU的实测星历和预报星历对PWV的误差影响,采用陆态网2016年GPS站点的观测数据和GAMIT软件,利用从IGS中心下载IGU的实测星历和预报星历分别反演PWV,并以精度最高的IGF为标准,确定二者对PWV的影响。结果表明:IGU的实测星历和预报星历的轨道误差为4.5 cm,造成PWV的误差约为0.09 mm,用两种方法反演的PWV在均方差上都小于0.3 mm,平均偏差不超过0.06 mm,相关系数达到99%,说明IGU的实测PWV和预报PWV在变化上有很好的一致性。以IGF为标准,最终星历和IGU实测星历的均方根误差约为0.327 mm,与IGU预报星历的均方根误差约为0.16 mm,使用实测星历比预报星历误差增大0.167 mm,差别不大,对PWV的结果影响较小,表明使用IGU的实测星历和预报星历可以满足近实时遥测水汽的需求。 Accurate satellite ephemeris files are needed in the NRT water vapor remote sensing. In this paper,in order to determine the influence of measured and forecast of IGU ephemeris on the error of PWV,the observed data from Terrestrial GPS network were processed by using the GAMIT software and the PWV is retrieved respectively by using the measured and predicted ephemeris files downloaded from IGS website,and the highest accuracy of IGF is used as the standard to determine the impact of the IGU on the PWV error. The results show that the orbit error of the measured and the predicted IGU ephemeris is 4.5 cm,resulting in PWV error of about 0.09 mm. The mean square error of the PWV retrieved by the measured and predicted IGU ephemeris is less than 0.3 mm,and the average deviation is not more than0.06 mm. Moreover,the correlation coefficient is 99 %,which indicates that the measured PWV and forecast PWV have a great consistency on the changing trend. Based on the IGF,the mean square error of atmospheric precipitation is about0.327 mm and 0.16 mm by using the measured and predicted of IGU ephemeris respectively,which has little effect on PWV results. Therefore,the IGU ephemeris can meet the requirement of GPS NRT water vapor remote sensing.
出处 《成都信息工程大学学报》 2017年第6期577-583,共7页 Journal of Chengdu University of Information Technology
基金 国家重大科技专项资助项目(GFZX03030303)
关键词 气象探测技术 大气可降水量 超快速星历 轨道误差 GPS 水汽探测 meteorological detection technology PWV IGU ephemeris orbit error GPS water vapor detection
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