GPT3模型在中国地区的精度分析  

Accuracy Analysis of GPT3 Model in China

作　　者：高壮 何秀凤[1] 常亮[2] GAO Zhuang;HE Xiufeng;CHANG Liang(College of Earth Sciences and Engineering,Hohai University,Nanjing 211100,China;College of Marine Science,Shanghai Ocean University,Shanghai 201306,China)

机构地区：[1]河海大学地球科学与工程学院,江苏南京211100 [2]上海海洋大学海洋科学学院,上海201306

出　　处：《武汉大学学报（信息科学版）》2021年第4期538-545,共8页Geomatics and Information Science of Wuhan University

基　　金：国家自然科学基金重点项目(41830110)。

摘　　要：为验证分析最新全球气压气温模型(GPT3模型)在中国区域的模型精度,以中国区域18个IGS站为例,分别利用全球大地测量观测系统(Global Geodetic Observing System,GGOS)Atmosphere机构提供的2015-2017年气象数据和国际卫星导航服务(International GNSS Service,IGS)数据中心提供的2015年对流层延迟数据对GPT3模型气象参数和天顶对流层延迟(zenith troposphere delay,ZTD)进行验证,并联合全球其他GNSS站点共同进行GPT3模型误差特性分析。结果表明,相比GPT和GPT2模型,GPT3模型的精度和稳定性明显提高;GPT3模型在取得与GPT2w模型相近精度的同时,稳定性有所提高。GPT3模型精度受纬度影响显著,气温和气压的精度和稳定性由赤道向两极地区逐渐降低,水汽压精度几乎不受纬度影响,稳定性在中纬度和部分低纬度区域比高纬度地区差。GPT3模型对气象参数估值的偏差在低海拔地区具有随机性,以气压偏差最为明显,随着海拔升高,气压和水汽压偏差逐渐稳定在±2 hPa内,气温偏差在±2℃内。Objectives: In order to test and analyze the accuracy of the latest global pressure and temperature model(GPT3 model), we choose 18 IGS stations in China for test. Methods: The meteorological data in 2015-2017 from Global Geodetic Observing System(GGOS) Atmosphere and the tropospheric delay data in 2015 provided by International GNSS Service(IGS) are used to test the model meteorological parameters and the zenith tropospheric delay(ZTD). And the error characteristics of GPT3 model are analyzed jointly with other GNSS stations all over the world. Results: The results show that the accuracy and the stability of GPT3 model are significantly improved compared with GPT and GPT2 models. The accuracy of GPT3 model is as same as that of GPT2w model and the stability is slightly improved. The GPT3 model is obviously sensitive to latitude change. In addition to water vapor pressure, the accuracy and stability of the model for estimating pressure and temperature decrease with the increase of latitude. The stability of water vapor pressure in the mid-latitude area and part of the low-latitude area is worse than that in the high-latitude area. The bias of GPT3 model is random in the low-altitude area, and the pressure bias is more obvious. When the altitude increases, the bias of pressure and water vapor pressure gradually stabilizes within ±2 hPa, and the temperature bias within ±2 ℃. Conclusions: GPT3 model shows strong stability and accurate prediction results than previous GPT models.

关 键 词：GPT3模型 误差特性 天顶对流层延迟 精度评估 

分 类 号：P228[天文地球—大地测量学与测量工程]