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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ESSDD</journal-id>
<journal-title-group>
<journal-title>Earth System Science Data Discussions</journal-title>
<abbrev-journal-title abbrev-type="publisher">ESSDD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Earth Syst. Sci. Data Discuss.</abbrev-journal-title>
</journal-title-group>
<publisher><publisher-name></publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/essd-2026-646</article-id>
<title-group>
<article-title>Tongji-GMMG2025C: A High-Resolution Global Gravity Field Solution Integrated from Heterogeneous Gravity Data via a Grid-based VCE Method</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xuan</surname>
<given-names>Jianhao</given-names>
<ext-link>https://orcid.org/0009-0009-0182-4654</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Chen</surname>
<given-names>Qiujie</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Shen</surname>
<given-names>Yunzhong</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Xingfu</given-names>
<ext-link>https://orcid.org/0000-0001-5305-7017</ext-link>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Xiao</surname>
<given-names>Yun</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>College of Surveying and Geo-informatics, Tongji University, Shanghai, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Xi&apos;an Research Institute of Surveying and Mapping, Xi&apos;an, China</addr-line>
</aff>
<pub-date pub-type="epub">
<day>21</day>
<month>10</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>29</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Jianhao Xuan et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-646/">This article is available from https://essd.copernicus.org/preprints/essd-2026-646/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-646/essd-2026-646.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-646/essd-2026-646.pdf</self-uri>
<abstract>
<p>In this study, we present Tongji-GMMG2025C, a high-resolution global gravity field solution complete to degree and order (d/o) 2190. The solution combines GRACE and GOCE satellite gravity information with five marine gravity datasets derived from satellite altimetry, four topographic gravity field models, pseudo terrestrial observations generated from EGM2008 up to d/o 719, high-resolution Antarctic gravity anomaly grids (AntGG2021), and Arctic Gravity Project (ArcGP) datasets. Grid-level variance component&amp;nbsp;estimation (VCE) is used to combine the marine and topographic datasets separately. The Tongji-GMMG2021S satellite-based full normal equation system is then combined with a terrestrial block-diagonal normal equation derived from global 5&amp;rsquo;&amp;times;5&amp;rsquo;&amp;nbsp;gravity anomaly grids. As a multi-source integrated solution, Tongji-GMMG2025C demonstrates lower residual statistics than single-source based solutions, exhibiting improvements of 0.01~0.21 mGal in measured free-air gravity anomalies and shipborne gravity anomaly enhancements of 0.08~0.54 mGal. Comparison with other existing gravity field solutions EGM2008, EIGEN-6C4, SGG-UGM-2, and XGM2019e reveals a good performance of our new combination solution Tongji-GMMG2025C and the closest agreement with XGM2019e. In oceanographic applications, Tongji-GMMG2025C achieves a root mean square error (RMSE) of 75.27 cm/s in geostrophic current determination relative to the DTU22MDT, outperforming EIGEN-6C4 by over 4.87 cm/s. Continental geoid evaluations in data-sparse regions yield accuracies of 38.94 cm (surrounding Brazil), 34.45 cm (surrounding Africa), and 50.60 cm (surrounding India), representing a 24 % improvement over EGM2008 in the surrounding Brazil region. Validation against millions of shipborne gravity measurements indicates that Tongji-GMMG2025C performs favourably, particularly in the 0~10 km coastal zone, where it achieves an accuracy of 6.99 mGal, outperforming existing models by 9 % to 24 %. Similarly, the model establishes an accuracy improvement of approximately 40 % compared to EGM2008 over Antarctica. These results demonstrate that Tongji-GMMG2025C may provide useful complementary gravity information in data-sparse regions. The Tongji-GMMG2025C solution is available at &lt;a href=&quot;https://doi.org/10.5281/zenodo.22667828&quot; target=&quot;_blank&quot; rel=&quot;noopener&quot;&gt;https://doi.org/10.5281/zenodo.22667828&lt;/a&gt; (Xuan et al., 2026).</p>
</abstract>
<counts><page-count count="29"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>42192532</award-id>
<award-id>42374100</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Fundamental Research Funds for the Central Universities</funding-source>
<award-id>None</award-id>
</award-group>
</funding-group>
</article-meta>
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