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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>
<issn pub-type="epub">1866-3591</issn>
<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-2026-65</article-id>
<title-group>
<article-title>TED: A global temperature-driven thermoelastic displacement dataset for GNSS reference stations (2000&amp;ndash;2023)</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Lu</surname>
<given-names>Ran</given-names>
<ext-link>https://orcid.org/0009-0005-8948-472X</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Zhao</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Ye</surname>
<given-names>Lingfeng</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Yuan</surname>
<given-names>Peng</given-names>
<ext-link>https://orcid.org/0000-0002-1717-8425</ext-link>
</name>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Feng</surname>
<given-names>Yanming</given-names>
<ext-link>https://orcid.org/0000-0001-6548-3347</ext-link>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>GNSS Research Center, Hubei Luojia Laboratory, Wuhan University, No. 129 Luoyu Road, Wuhan 430079, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>School of Geodesy and Geomatics, Wuhan University, No. 129 Luoyu Road, Wuhan, 430079, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Faculty of Science, Queensland University of Technology, Brisbane, 4000, Australia</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>GFZ Helmholtz Centre for Geosciences, Potsdam, Germany</addr-line>
</aff>
<pub-date pub-type="epub">
<day>04</day>
<month>02</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>29</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Ran Lu 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-2026-65/">This article is available from https://essd.copernicus.org/preprints/essd-2026-65/</self-uri>
<self-uri xlink:href="https://essd.copernicus.org/preprints/essd-2026-65/essd-2026-65.pdf">The full text article is available as a PDF file from https://essd.copernicus.org/preprints/essd-2026-65/essd-2026-65.pdf</self-uri>
<abstract>
<p>The nonlinear signals in global GNSS station height time series reflects both non-tidal mass loading (atmospheric, oceanic, and hydrological) and temperature-driven thermoelastic deformation (TED). However, a globally consistent and reproducible TED data product has long been lacking. Here we present a global dataset of vertical TED for ~15,000 GNSS stations spanning 2000&amp;ndash;2023, generated using a full-spectrum, layered finite-element model. The model is driven by hourly ERA5 soil-temperature profiles and parameterized with depth-dependent thermophysical properties from the SoilGrids dataset, enabling consistent quantification of TED from semi-diurnal/diurnal variability through seasonal to interannual timescales. Compared with an identical homogeneous-medium benchmark, subsurface stratification typically changes annual amplitudes by ~0.3 mm and shifts the timing of the annual maximum by ~1 month, yielding regionally coherent and smoothly varying spatial patterns. At stations with independent site characterization, the site-constrained solutions agree closely with SoilGrids-based solutions, with annual-amplitude differences of 0.01&amp;ndash;0.03 mm and annual-phase differences mostly within 1&amp;ndash;3&amp;deg;. Sensitivity tests using &amp;plusmn;10% perturbations in thermal expansion, thermal diffusivity, and Young&amp;rsquo;s modulus indicate that annual-cycle amplitude and phase are robust. Globally, annual TED amplitudes are typically 1&amp;ndash;2 mm, exceed 2&amp;ndash;3 mm at some stations, and reach peak-to-peak values up to ~5 mm, with the largest signals concentrated in arid inland and continental climate regions. When TED corrections are applied together with non-tidal mass-loading corrections, the residual vertical dispersion decreases at most stations, with vertical scatter reduced by up to ~70 % at selected sites. The dataset is publicly available for direct use in GNSS coordinate time series correction and related geophysical applications: https://doi.org/10.5281/zenodo.18256342 (Lu 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>424B2026</award-id>
<award-id>42574041</award-id>
<award-id>42192531</award-id>
<award-id>42388102</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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