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This study introduces a multi-source data fusion model of the tropospheric delay over China and uses GNSS data, meteorological data, and Global Pressure and Temperature 2 wet (GPT2w) model data to derive the model coefficients. Fifty-one nationwide GNSS stations were selected to evaluate the accuracy of the fusion model through a detailed analysis of the model performance based on factors including the overall accuracy, seasonal accuracy, and impact of the station location. The results show that the multi-source data fusion model integrates the advantages of various individual models and thus has a higher accuracy and stability despite the occurrence of a certain degree of decline in accuracy in the individual models under certain conditions. A comparison with previous models developed using only GNSS data demonstrates that this fusion model improves the overall accuracy by 17.7%.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The terms on which this article has been published allow the posting of the Accepted Manuscript in a repository by the author(s) or with their consent.
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