甘肃省加权平均温度时空分布特征分析与模型建立
|
摘要
加权平均温度是大气可降水量研究过程中的一个重要参数,直接影响着大气可降水量反演的精度。针对适合于甘肃地区的加权平均温度模型较少且已有模型精度较低的情况,文章主要利用甘肃地区7个探空站2013-2017年的数据,统计分析了甘肃地区加权平均温度时空分布特征,依据最小二乘原理建立了本地化分区、分季、分月模型,并结合已有模型对其精度进行了验证。结果表明,甘肃地区加权平均温度具有明显的时空分布特征,建立分区、分季、分月模型是非常有必要的,且分区、分季、分月模型精度均优于已有模型,具有重要的实际应用价值。
The weighted average temperature is an important parameter in the research of atmospheric precipitable water vapor,which directly affects its precision.In view of the less weighted average temperature model suitable for Gansu Province and the low accuracy of existing models,we mainly use the data of 7 atmospheric sounding stations in Gansu from2013 to 2017,and statistically analyze the spatial and temporal characteristics of the weighted average temperature in Gansu Province.Then based on the principle of least squares,localized partition,sub-quarter and sub-month models are established,and the accuracy of the model is verified by the existing models.The results show that the weighted average temperature in Gansu has obvious spatial and temporal characteristics.Therefore,it is very necessary to establish partition,sub-quarter and sub-month models.The precision of partition,subquarter and sub-month models is better than the existing models,which has important practical value.
The weighted average temperature is an important parameter in the research of atmospheric precipitable water vapor,which directly affects its precision.In view of the less weighted average temperature model suitable for Gansu Province and the low accuracy of existing models,we mainly use the data of 7 atmospheric sounding stations in Gansu from2013 to 2017,and statistically analyze the spatial and temporal characteristics of the weighted average temperature in Gansu Province.Then based on the principle of least squares,localized partition,sub-quarter and sub-month models are established,and the accuracy of the model is verified by the existing models.The results show that the weighted average temperature in Gansu has obvious spatial and temporal characteristics.Therefore,it is very necessary to establish partition,sub-quarter and sub-month models.The precision of partition,subquarter and sub-month models is better than the existing models,which has important practical value.
引文
[1]郭金运,刘智敏,赵春梅,等.区域CORS网数据处理方法及应用[M].北京:科学出版社,2016:114-124.
[2]司海燕.利用CORS资料反演区域大气可降水量的研究[D].西安:长安大学,2011:1-18.
[3]BEVIS M,BUSINGER S,HERRING T A,et al.GPS Meteorology:Remote sensing of atmospheric water vapor using the global positioning system[J].JGeophys Res,1992,97(D14):15787-15801.
[4]LAN ZEYING,ZHANG BAO,GENG YICHAO.Establishment and analysis of global gridded Tm-Ts relationship model[J].Geodesy and Geodynamics,2016,7(2):101-107.
[5]姚宜斌,张豹,许超衿,等.Tm-Ts的相关行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.
[6]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):133-141.
[7]王晓英,戴仔强,曹云昌,等.中国地区地基GPS加权平均温度Tm统计分析[J].武汉大学学报(信息科学版),2011,36(4):412-416.
[8]龚绍琦.中国区域大气加权平均温度的时空变化及模型[J].应用气象学报,2013,24(3):332-341.
[9]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.
[10]李黎,樊奕茜,王亮,等.湖南地区加权平均温度的影响因素分析及建模[J].大地测量与地球动力学,2018,38(1):48-52.
[11]李黎,田莹,谢威,等.基于探空资料的湖南地区加权平均温度本地化模型研究[J].大地测量与地球动力学,2017,38(1):282-291.
[12]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):54-65.
[13]张洛恺,杨力,王艳玲,等.郑州地区大气加权平均温度模型确定[J].测绘科学技术学报,2014,31(6):565-569.
[14]狄丽娟,李星光,邓南山.徐州地区大气加权平均温度模型研究[J].导航定位学报,2015,3(2):81-93.
[15]朱爽.郑州地区地基GPS加权平均温度计算本地化模型研究[J].测绘工程,2014,23(4):28-32.
[16]谢劭峰,靳利洋,王新桥,等.广西地区大气加权平均温度模型[J].科学技术与工程,2017,17(4):133-136.
[17]黎俊宇,刘立龙,蔡成辉,等.新疆地区地基GPS加权平均温度模型的建立与分析[J].桂林理工大学学报,2017,37(1):108-113.
[18]谢劭峰,黎俊宇,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):472-476.
[2]司海燕.利用CORS资料反演区域大气可降水量的研究[D].西安:长安大学,2011:1-18.
[3]BEVIS M,BUSINGER S,HERRING T A,et al.GPS Meteorology:Remote sensing of atmospheric water vapor using the global positioning system[J].JGeophys Res,1992,97(D14):15787-15801.
[4]LAN ZEYING,ZHANG BAO,GENG YICHAO.Establishment and analysis of global gridded Tm-Ts relationship model[J].Geodesy and Geodynamics,2016,7(2):101-107.
[5]姚宜斌,张豹,许超衿,等.Tm-Ts的相关行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.
[6]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):133-141.
[7]王晓英,戴仔强,曹云昌,等.中国地区地基GPS加权平均温度Tm统计分析[J].武汉大学学报(信息科学版),2011,36(4):412-416.
[8]龚绍琦.中国区域大气加权平均温度的时空变化及模型[J].应用气象学报,2013,24(3):332-341.
[9]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.
[10]李黎,樊奕茜,王亮,等.湖南地区加权平均温度的影响因素分析及建模[J].大地测量与地球动力学,2018,38(1):48-52.
[11]李黎,田莹,谢威,等.基于探空资料的湖南地区加权平均温度本地化模型研究[J].大地测量与地球动力学,2017,38(1):282-291.
[12]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):54-65.
[13]张洛恺,杨力,王艳玲,等.郑州地区大气加权平均温度模型确定[J].测绘科学技术学报,2014,31(6):565-569.
[14]狄丽娟,李星光,邓南山.徐州地区大气加权平均温度模型研究[J].导航定位学报,2015,3(2):81-93.
[15]朱爽.郑州地区地基GPS加权平均温度计算本地化模型研究[J].测绘工程,2014,23(4):28-32.
[16]谢劭峰,靳利洋,王新桥,等.广西地区大气加权平均温度模型[J].科学技术与工程,2017,17(4):133-136.
[17]黎俊宇,刘立龙,蔡成辉,等.新疆地区地基GPS加权平均温度模型的建立与分析[J].桂林理工大学学报,2017,37(1):108-113.
[18]谢劭峰,黎俊宇,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):472-476.