GNSS tropospheric tomography is one of the applications of the Global Navigation Satellite Systems (GNSS) signals which attracts more and more interest in the field of meteorology. This method can reconstruct the water vapour of the atmosphere, which has a considerable effect on weather forecasting and early warning systems of severe weather. In GNSS tomography, traditionally, a regular spaced 3D grid stretches from the GNSS network to the effective height of the troposphere in the area of interest. Therefore, this method can offer a permanent monitoring service for water vapour and wet refractivity fields at a low cost and a reasonable spatial resolution compared to conventional observations, like radiosonde and radio occultation profiles. Nevertheless, the quality of the reconstructed field is still one of the challenges in the GNSS tomography. In this research, we propose the concept of spread as a mathematical tool to provide a quality measure without using the reference field and calculating statistical measures like RMSE and Bias. Thereby, two synthetic and one real datasets (part of Germany and Czechia) covering overlapping periods between 29 May and 14 Jun of the year 2013 (DoY 149–165; DoY 160–165; DoY 160–165, 2013) have been tested to investigate the proposed method. According to the obtained results, the proposed tool shows a strong correlation (up to 0.81 for synthetic and 0.72 for real observations) with the standard deviation of the reconstructed wet refractivity with respect to the radiosonde profile reference. The correlation between spread and the Bias of the retrieved wet refractivity field is also significant. However, there is no clear picture depending on the applied spread computation models. Therefore, the spread of the resolution matrix can be used as a proxy for the accuracy of the tomography reconstruction field based on the quality of the observations, the initial field, and the design matrix.

GNSS对流层层析成像是全球导航卫星系统（GNSS）信号的应用之一，在气象领域引起了越来越多的关注。这种方法可以重建大气中的水汽，对恶劣天气的天气预报和预警系统有相当大的影响。在 GNSS 断层扫描中，传统上，规则间隔的 3D 网格从 GNSS 网络延伸到感兴趣区域中对流层的有效高度。因此，与无线电探空仪和无线电掩星剖面等常规观测相比，该方法可以以较低的成本和合理的空间分辨率为水汽和湿折射率场提供永久监测服务。尽管如此，重建场的质量仍然是 GNSS 断层扫描的挑战之一。RMSE和偏差。因此，两个合成数据集和一个真实数据集（德国和捷克的一部分）涵盖了 2013 年 5 月 29 日至 6 月 14 日之间的重叠时期（DoY 149-165；DoY 160-165；DoY 160-165，2013）研究提出的方法。根据获得的结果，所提出的工具显示出与无线电探空仪剖面参考的重建湿折射率的标准偏差有很强的相关性（合成观测值高达 0.81，实际观测值高达 0.72）。价差与偏差之间的相关性检索到的湿折射率场也很重要。然而，根据所应用的传播计算模型，没有清晰的图景。因此，分辨率矩阵的扩展可以作为基于观测质量、初始场和设计矩阵的层析成像重建场准确性的代理。