顾及周期性误差修正的加权平均温度模型构建
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摘要
针对目前多数大气加权平均温度(Tm)模型没有考虑季节性影响这一问题,该文首先利用IGRA 2005—2010年全球探空数据,分别建立了各探空站点与地表温度有关的线性Tm模型、与地表水汽压有关的指数Tm模型以及与地表温度和水汽压均有关的混合Tm模型。然后以探空站积分Tm值为参考,对上述3类模型的误差时间序列进行了分析,发现这3种模型均存在周期性误差,并在此基础上构建了考虑周期性误差修正的3类Tm新模型。利用2011—2014年全球探空数据对3类新模型进行精度验证,结果表明:3类Tm新模型的精度相比于原模型均有所提升,模型的周期性误差影响基本得以消除,且3类Tm新模型的精度基本一致。
Aiming at the problem that many weighted mean temperature(Tm)models ignore the influence of seasonal variation,in this paper,we first built the line Tmmodel(L-Tm),power Tmmodel(P-Tm)and mix Tm model(M-Tm)at each selected integrated global radiosonde archive(IGRA)station using the sounding data provided by IGRA in the year 2005-2010.Then the performances of different Tm models were verified by taking integrated Tm as reference.It was found that these traditional models suffered from seasonal errors.Thus three improved Tmmodels that considered the influence of seasonal variation were proposed to reduce the influence of such errors.The results showed that compared with the traditional models,the improved models were more accurate while they were verified by IGRA data in 2011-2014.Additionally,the seasonal errors presented in the traditional models almost disappeared in the improved models,and the accuracy of three different improved Tmmodels was also similar.
Aiming at the problem that many weighted mean temperature(Tm)models ignore the influence of seasonal variation,in this paper,we first built the line Tmmodel(L-Tm),power Tmmodel(P-Tm)and mix Tm model(M-Tm)at each selected integrated global radiosonde archive(IGRA)station using the sounding data provided by IGRA in the year 2005-2010.Then the performances of different Tm models were verified by taking integrated Tm as reference.It was found that these traditional models suffered from seasonal errors.Thus three improved Tmmodels that considered the influence of seasonal variation were proposed to reduce the influence of such errors.The results showed that compared with the traditional models,the improved models were more accurate while they were verified by IGRA data in 2011-2014.Additionally,the seasonal errors presented in the traditional models almost disappeared in the improved models,and the accuracy of three different improved Tmmodels was also similar.
引文
[1]BEVIS M,BUSINGER S,HERRING T A,et al.GPSmeteorology:remote sensing of the atmospheric water vapor using the global positioning system[J].Journal of Geophysical Research,1992,97(D14):15787-15801.
[2]YAO Yibin,XU Chaoqian,ZHANG Bao,et al.GTmIII:a new global empirical model for mapping zenith wet delays onto precipitable water vapour[J].Geophysical Journal International,2014,197(1):202-212.
[3]BHM J,MLLER 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.
[4]陈鹏,陈家君.利用NCEP再分析资料建立全球大气加权平均温度模型[J].大地测量与地球动力学,2014,34(3):133-136,141.(CHEN Peng,CHEN Jiajun.Establishment of global atmospheric weighted average temperature model using NCEP reanalysis data[J].Journal of Geodesy and Geodynamics,2014,34(3):133-136,141.)
[5]谢劭峰,黎峻宇,刘立龙,等.新疆地区GGOS Atmosphere加权平均温度的精化[J].大地测量与地球动力学,2017,37(5):472-477.(XIE Shaofeng,LI Junyu,LIU Lilong,et al.Refinement of GGOS atmosphere weighted mean temperature in Xinjiang[J].Journal of Geodesy and Geodynamics,2017,37(5):472-477.)
[6]BEVIS M,BUSINGER S,CHISWELL S,et al.GPSmeteorology:mapping zenith wet delays onto precipitable water[J].Journal of Applied Meteorology,1994,33(3):379-386.
[7]MENDES V B,PRATES G,SANTOS L,et al.An evaluation of the accuracy of models of the determination of the weighted mean temperature of the atmosphere[C]∥ION 2000National Technical Meeting.[S.l.]:[s.n.],2000:26-28.
[8]SCHULER T,POSFAY A,HEIN G W,et al.A global analysis of the mean atmospheric temperature for GPSwater vapor estimation[C/OL]∥Proceedings of the14th International Technical Meeting of the Satellite Division of the Institute of Navigation,2011[2018-05-03].https:∥www.researchgate.net/publication/228788628.
[9]李黎,宋越,易金花,等.湖南三地加权平均温度分区分时模型研究[J].测绘科学,2018,43(1):54-58,65.(LILi,SONG Yue,YI Jinhua,et al.Research on subregional and seasonal modeling of weighted average temperature in three region of Hunan[J].Science of Surveying and Mapping,2018,43(1):54-58,65.)
[10]范进伟,郭承军.基于区域GPS网大气降水量预测建模研究[J].计算机仿真,2017,34(1):401-404.(FANJinwei,GUO Chengjun.The modeling research of the atmospheric precipitable water vapor forecast based on regional GPS networks[J].Computer Simulation,2017,34(1):401-404.)
[11]张化疑,刘焱雄,周兴华,等.渤海区域对流层加权平均温度研究[J].测绘信息与工程,2010,35(4):1-2.(ZHANG Huayi,LIU Yanxiong,ZHOU Xinghua,et al.Weighted mean temperature in Bohai[J].Journal of Geomatics,2010,35(4):1-2.)
[12]穆宝胜,施昆.地基GPS水汽反演昆明地区加权平均温度的模型建立[J].测绘科学,2013,38(3):98-99.(MU Baosheng,SHI Kun.Model establishment of weighted average temperature in Kunming area by ground-based GPS water vapor inversion[J].Science of Surveying and Mapping,2013,38(3):98-99.)
[13]姚宜斌,张豹,许超钤,等.Tm-Ts的相关性分析及全球纬度相关的线性关系模型构建[J].科学通报,2014,59(9):816-824.(YAO Yibin,ZHANG Bao,XU Chaoqian,et al.Analysis of the global Tm-Tscorrelation and establishment of the latitude-related linear model[J].Chinese Science Bulletin,2014,59(9):816-824.)
[14]许九靖,赵兴旺,申建华.大气加权平均温度建模及其在GPS/PWV中的应用[J].全球定位系统,2018,43(1):60-64.(XU Jiujing,ZHAO Xingwang,SHEN Jianhua.Modeling of weighted mean temperature and its application in GPS/PWV[J].GNSS World of China,2018,43(1):60-64.)
[15]于胜杰,柳林涛.水汽加权平均温度回归公式的验证与分析[J].武汉大学学报(信息科学版),2009,34(6):741-744.(YU Shengjie,LIU Lintao.Validation and analysis of the water-vapor-weighted mean temperature fromTm-Tsrelationship[J].Geomatics and Information Science of Wuhan University,2009,34(6):741-744.)
[16]王晓英,宋连春,戴仔强,等.香港地区加权平均温度特征分析[J].南京信息工程大学学报(自然科学版),2011,3(1):47-52.(WANG Xiaoying,SONG Lianchun,DAI Zaiqiang,et al.Feature analysis of weighted mean temperature Tmin Hong Kong[J].Journal of Nanjing University of Information Science and Technology(Natural Science Edition),2011,3(1):47-52.)
[17]YAO Yibin,ZHANG Bao,XU Chaoqian,et al.Improved one/multi-parameter models that consider seasonal and geographic variations for estimating weighted mean temperature in ground-based GPS meteorology[J].Journal of Geodesy,2014,88(3):273-282.
[2]YAO Yibin,XU Chaoqian,ZHANG Bao,et al.GTmIII:a new global empirical model for mapping zenith wet delays onto precipitable water vapour[J].Geophysical Journal International,2014,197(1):202-212.
[3]BHM J,MLLER 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.
[4]陈鹏,陈家君.利用NCEP再分析资料建立全球大气加权平均温度模型[J].大地测量与地球动力学,2014,34(3):133-136,141.(CHEN Peng,CHEN Jiajun.Establishment of global atmospheric weighted average temperature model using NCEP reanalysis data[J].Journal of Geodesy and Geodynamics,2014,34(3):133-136,141.)
[5]谢劭峰,黎峻宇,刘立龙,等.新疆地区GGOS Atmosphere加权平均温度的精化[J].大地测量与地球动力学,2017,37(5):472-477.(XIE Shaofeng,LI Junyu,LIU Lilong,et al.Refinement of GGOS atmosphere weighted mean temperature in Xinjiang[J].Journal of Geodesy and Geodynamics,2017,37(5):472-477.)
[6]BEVIS M,BUSINGER S,CHISWELL S,et al.GPSmeteorology:mapping zenith wet delays onto precipitable water[J].Journal of Applied Meteorology,1994,33(3):379-386.
[7]MENDES V B,PRATES G,SANTOS L,et al.An evaluation of the accuracy of models of the determination of the weighted mean temperature of the atmosphere[C]∥ION 2000National Technical Meeting.[S.l.]:[s.n.],2000:26-28.
[8]SCHULER T,POSFAY A,HEIN G W,et al.A global analysis of the mean atmospheric temperature for GPSwater vapor estimation[C/OL]∥Proceedings of the14th International Technical Meeting of the Satellite Division of the Institute of Navigation,2011[2018-05-03].https:∥www.researchgate.net/publication/228788628.
[9]李黎,宋越,易金花,等.湖南三地加权平均温度分区分时模型研究[J].测绘科学,2018,43(1):54-58,65.(LILi,SONG Yue,YI Jinhua,et al.Research on subregional and seasonal modeling of weighted average temperature in three region of Hunan[J].Science of Surveying and Mapping,2018,43(1):54-58,65.)
[10]范进伟,郭承军.基于区域GPS网大气降水量预测建模研究[J].计算机仿真,2017,34(1):401-404.(FANJinwei,GUO Chengjun.The modeling research of the atmospheric precipitable water vapor forecast based on regional GPS networks[J].Computer Simulation,2017,34(1):401-404.)
[11]张化疑,刘焱雄,周兴华,等.渤海区域对流层加权平均温度研究[J].测绘信息与工程,2010,35(4):1-2.(ZHANG Huayi,LIU Yanxiong,ZHOU Xinghua,et al.Weighted mean temperature in Bohai[J].Journal of Geomatics,2010,35(4):1-2.)
[12]穆宝胜,施昆.地基GPS水汽反演昆明地区加权平均温度的模型建立[J].测绘科学,2013,38(3):98-99.(MU Baosheng,SHI Kun.Model establishment of weighted average temperature in Kunming area by ground-based GPS water vapor inversion[J].Science of Surveying and Mapping,2013,38(3):98-99.)
[13]姚宜斌,张豹,许超钤,等.Tm-Ts的相关性分析及全球纬度相关的线性关系模型构建[J].科学通报,2014,59(9):816-824.(YAO Yibin,ZHANG Bao,XU Chaoqian,et al.Analysis of the global Tm-Tscorrelation and establishment of the latitude-related linear model[J].Chinese Science Bulletin,2014,59(9):816-824.)
[14]许九靖,赵兴旺,申建华.大气加权平均温度建模及其在GPS/PWV中的应用[J].全球定位系统,2018,43(1):60-64.(XU Jiujing,ZHAO Xingwang,SHEN Jianhua.Modeling of weighted mean temperature and its application in GPS/PWV[J].GNSS World of China,2018,43(1):60-64.)
[15]于胜杰,柳林涛.水汽加权平均温度回归公式的验证与分析[J].武汉大学学报(信息科学版),2009,34(6):741-744.(YU Shengjie,LIU Lintao.Validation and analysis of the water-vapor-weighted mean temperature fromTm-Tsrelationship[J].Geomatics and Information Science of Wuhan University,2009,34(6):741-744.)
[16]王晓英,宋连春,戴仔强,等.香港地区加权平均温度特征分析[J].南京信息工程大学学报(自然科学版),2011,3(1):47-52.(WANG Xiaoying,SONG Lianchun,DAI Zaiqiang,et al.Feature analysis of weighted mean temperature Tmin Hong Kong[J].Journal of Nanjing University of Information Science and Technology(Natural Science Edition),2011,3(1):47-52.)
[17]YAO Yibin,ZHANG Bao,XU Chaoqian,et al.Improved one/multi-parameter models that consider seasonal and geographic variations for estimating weighted mean temperature in ground-based GPS meteorology[J].Journal of Geodesy,2014,88(3):273-282.
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