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GWMT Global Atmospheric Weighted Mean Temperature Models: Development and Refinement

机译:GWMT全球大气加权平均温度模型:开发和改进

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The atmospheric weighted mean temperature T_m plays a pivotal role in remote sensing water vapor with GNSS technique. However, real-time T_m cannot be obtained at given place due to limitation of modern technology. In order to remove this barrier, a global and season-specific T_m model (GWMT-Ⅰ) based on spherical harmonics analysis was built using land radiosonde data. Combining Global Pressure and Temperature (GPT) model with the Bevis formula to provide virtual T_m observation at sea, a modified T_m model (GWMT-Ⅱ) was presented aimed to improve the accuracy of GWMT-Ⅰ in the ocean areas. Thereafter, the third generation T_m (GWMT-Ⅲ) model, derived from GGOS Atmosphere surface global grid T_m data, came into existence. But on the one hand, these three models fail to accurately describe vertical T_m variation. On the other hand, they are expanded into spherical harmonics up to degree and order nine which may impose restriction to their precision. This paper reconstructs the latest model (GWMT-Ⅳ) with 4D global NCEP/DOE 2 Reanalysis data from 2005 to 2009. Comparison of result between 2010 NCEP2 data and the GWMT-IV model shows that it achieves high accuracy all over the world and its modeling method better conforms to reality.
机译:大气加权平均温度T_m起着遥感水蒸气与GNSS技术中的关键作用。然而,实时T_m不能在给定的位置,由于现代技术的限制而获得。为了消除这一障碍,基于球面调和分析领域的全球和季节特定T_m模型(GWMT-Ⅰ)土地利用探空资料建成。结合全球压力和温度(GPT)模型与贝维斯配方可提供海上虚拟T_m观察,修改T_m模型(GWMT-Ⅱ)上提出了旨在改善的GWMT-Ⅰ的海洋区域的准确性。此后,将第三代T_m(GWMT-Ⅲ)的模式,从大气性GGO表面全球网格T_m数据导出的,开始存在。但是,一方面,这三款车型无法准确地描述垂直T_m变化。在另一方面,它们被扩展成球谐达程度和秩序九位可以决定限制他们的精度。本文重建的最新型号(GWMT-Ⅳ)与4D全球NCEP / DOE 2再分析资料2005年至二○一○年NCEP2数据,它实现了高准确度都在世界各地,其GWMT-IV模型显示结果之间的比较2009建模方法更好地符合实际。

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