Precipitable Water Vapor (PWV) is a crucial parameter in climate research. However, obtaining high precision PWV data remains a problem. Discrepancies in water vapor elevation data from diverse observation sources pose challenges, emphasizing the need for precise vertical correction. In this paper, we proposed the precipitable water vapor model with systematic difference correction by using ERA5 (the fifth generation of European Centre for Medium-Range Weather Forecasts Reanalysis) data and GNSS (Global Navigation Satellite System) data. In this proposed method, two vertical correction models, employing cubic polynomial and exponential functions, were developed. The exponential function demonstrated superior overall performance with the RMS error of 0.96 mm, effectively capturing vertical characteristics across diverse regions, while the cubic polynomial function had the RMS (Root Mean Square) error of 2.77 mm validated by ERA5 PWV. The cubic polynomial function was found more suitable for low-elevation regions, while the exponential function excelled in high-elevation regions. Validated by radiosonde PWV, the cubic polynomial function and the exponential function show a strong correlation with latitude. Both functions exhibit smaller RMS values at higher latitudes and larger RMS values at lower latitudes. Validated by GNSS PWV, the cubic polynomial function exhibits superior accuracy, with the RMS of 2.39 mm, compared to the exponential function, particularly in specific regions. Analyzing six years of data reveals significant systematic differences between ERA5 and GNSS PWV. This discrepancy exhibits a noticeable annual periodic variation. The global GNSS stations were organized into grids, with stations within the same region grouped together for correction. Models considering systematic differences exhibited substantial RMS reductions and better accuracy. These findings can provide reference in atmospheric correction and the study of extreme weather events.

中文翻译：

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一种改进的可降水汽垂直校正全局网格模型的开发方法


可降水蒸气 （PWV） 是气候研究中的关键参数。然而，获得高精度的脉搏波速度数据仍然是一个问题。来自不同观测源的水蒸气高程数据的差异带来了挑战，强调了精确垂直校正的必要性。在本文中，我们利用 ERA5 （第五代欧洲中期天气预报中心再分析） 数据和 GNSS（全球导航卫星系统）数据提出了具有系统差异校正的可降水汽模型。在这种提出的方法中，开发了两个垂直校正模型，采用三次多项式和指数函数。指数函数表现出卓越的整体性能，RMS 误差为 0.96 mm，有效捕获了不同区域的垂直特性，而三次多项式函数的 RMS（均方根）误差为 2.77 mm，经 ERA5 PWV 验证。发现三次多项式函数更适合于低海拔地区，而指数函数在高海拔地区表现出色。经无线电探空仪 PWV 验证，三次多项式函数和指数函数与纬度呈强相关性。这两个函数在较高纬度地区表现出较小的 RMS 值，在较低纬度地区表现出较大的 RMS 值。经 GNSS PWV 验证，与指数函数相比，三次多项式函数表现出更高的精度，RMS 为 2.39 mm，尤其是在特定区域。分析六年的数据揭示了 ERA5 和 GNSS PWV 之间的显着系统差异。这种差异表现出明显的年度周期性变化。全球 GNSS 站被组织成网格，同一区域内的站被分组在一起进行校正。 考虑系统差异的模型表现出显著的 RMS 降低和更好的准确性。研究结果可为大气校正和极端天气事件研究提供参考。