| 长三角地区分季节多因子本地化T_m模型研究 |
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| 引用本文： | 李媛,李黎,张振,顾嘉伟,周嘉陵,谢威.长三角地区分季节多因子本地化T_m模型研究[J].大地测量与地球动力学,2020,40(2):140-145. |
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| 作者姓名： | 李媛 李黎 张振 顾嘉伟 周嘉陵 谢威 |
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| 作者单位： | 苏州科技大学环境科学与工程学院;江苏省气象科学研究所;长安大学地质工程与测绘学院 |
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| 基金项目： | 江苏省高等学校大学生创新创业训练计划(201810332018Z);国家自然科学基金(41304029);湖南省自然科学基金(2016JJ3061);江苏省自然科学基金(BK20161603)~~ |
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| 摘 要： | 针对GNSS气象学中大气加权平均温度(Tm)受时空影响的问题,利用长三角地区7个探空站2015~2017年数据,分析Tm与地面温度(Ts)、水汽压(es)和气压(Ps)的线性关系,并基于最小二乘法进行多元线性拟合,建立长三角地区本地化Tm模型。实验结果表明:1)本地化单因子模型效果优于Bevis模型,且双因子和多因子模型与单因子模型效果相当;2)分季节多因子模型优于全局模型,对秋冬季改善效果最为显著;3)分季节多因子Tm模型计算GNSS大气可降水量(PWV)的效果优于Bevis模型。分季节多因子本地化Tm模型更适用于长三角地区,可获得更准确的Tm和PWV。
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| 关 键 词： | 大气加权平均温度 长三角地区 GNSS气象学 本地化模型 大气可降水量 |
Research on Seasonal and Multifactor Model of Weighted Average Temperature in Yangtze River Delta |
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| LI Yuan,LI Li,ZHANG Zhen,GU Jiawei,ZHOU Jialing,XIE Wei.Research on Seasonal and Multifactor Model of Weighted Average Temperature in Yangtze River Delta[J].Journal of Geodesy and Geodynamics,2020,40(2):140-145. |
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| Authors: | LI Yuan LI Li ZHANG Zhen GU Jiawei ZHOU Jialing XIE Wei |
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| Institution: | (School of Environmental Science and Engineering,Suzhou University of Science and Technology,99 Xuefu Road,Suzhou 215009,China;Jiangsu Research Institute of Meteorological Sciences,16 Kunlun Road,Nanjing 210009,China;School of Geology Engineering and Geomatics,Chang’an University,South-Erhuan Road,Middle Section,Xi’an 710064,China) |
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| Abstract: | Aiming at the problem that the weighted average atmospheric temperature (Tm) is affected by time and space in GNSS meteorology, this paper uses the data of seven sounding stations in the Yangtze river delta from 2015 to 2017. The linear relationships between Tm and the ground temperature (Ts), water vapor pressure (es) and air pressure (Ps) are analyzed. The multifactor linear fitting localized Tm model for Yangtze river delta is established based on the least square method. Experiments show that the one-factor Tm model are better compared to Bevis model. However, the effects of the two-factor and multi-factor models are comparable to the single-factor model. The seasonal multi-factor Tm model is better than the yearly model and improved prominently in autumn and winter. GNSS PWV calculated by the multi-factor Tm model is also better than the Bevis model. The results show that the seasonal multi-factor localized Tm model is more suitable for the Yangtze river delta and it can obtain more accurate Tm and PWV. |
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| Keywords: | weighted average temperature Yangtze river delta GNSS meteorology localization model atmospheric perceptible water vapor |
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