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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-4696</article-id>
<title-group>
<article-title>Land-Surface Sensitivity and Climate Variability Shape Global Wet-Dry Regime Transitions</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Faiz</surname>
<given-names>Muhammad Abrar</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Liangliang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff6">
<sup>6</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Liu</surname>
<given-names>Dong</given-names>
</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>
<xref ref-type="aff" rid="aff4">
<sup>4</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fu</surname>
<given-names>Qiang</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>Li</surname>
<given-names>Mo</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>Qi</surname>
<given-names>Xiaochen</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>Li</surname>
<given-names>Tianxiao</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>Cui</surname>
<given-names>Song</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff5">
<sup>5</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>School of Hydraulic Science &amp; Engineering, Northeast Agricultural University, Harbin, Heilongjiang 150030, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Joint International Research Laboratory of Habitat Health of Black Soil in Cold Regions, Ministry of Education, Northeast Agricultural University, Harbin, Heilongjiang 150030, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Key Laboratory of Effective Utilization of Agricultural Water Resources of Ministry of Agriculture and Rural Affairs, Northeast Agricultural University, Harbin, Heilongjiang 150030, China</addr-line>
</aff>
<aff id="aff4">
<label>4</label>
<addr-line>Heilongjiang Provincial Key Laboratory of Water Resources and Water Conservancy Engineering in Cold Region, Northeast Agricultural University, Harbin, Heilongjiang 150030, China</addr-line>
</aff>
<aff id="aff5">
<label>5</label>
<addr-line>Research Center for Eco-Environment Protection of Songhua River Basin, Northeast Agricultural University, Harbin, Heilongjiang 150030, China</addr-line>
</aff>
<aff id="aff6">
<label>6</label>
<addr-line>These authors contributed equally to this work.</addr-line>
</aff>
<pub-date pub-type="epub">
<day>18</day>
<month>08</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>18</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Muhammad Abrar Faiz 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://egusphere.copernicus.org/preprints/2026/egusphere-2026-4696/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4696/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4696/egusphere-2026-4696.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-4696/egusphere-2026-4696.pdf</self-uri>
<abstract>
<p>Hydroclimatic change is commonly assessed using gradual wetting or drying trends, yet many regions may shift among persistent wet, persistent dry, and transitional wet-dry states. The global geography of these regime transitions and their associations with land-surface conditions and climate variability remain insufficiently quantified. This study aimed to identify global wet-dry regime transitions across historical and future periods and to evaluate how these transitions relate to land-surface characteristics and large-scale climate variability. A stage-focused standardized index was developed to estimate terrestrial water-storage anomalies from monthly water-balance components, including precipitation, evapotranspiration, and runoff. The index was applied to global gridded observations from 1979 to 2023 and to CMIP6 projections. Four hydroclimatic regimes were classified: wet-gets-wetter, dry-gets-drier, wet-gets-dry, and dry-gets-wet. Land-cover diagnostics and large-scale climate indices were used to examine associations among observed transitions, land-surface conditions, and ocean-atmosphere variability.&lt;/p&gt;
&lt;p&gt;Drying covered 52.9 % of the global land area during 1979&amp;ndash;2000, with persistent drying as the dominant regime. From 1979&amp;ndash;2000 to 2001&amp;ndash;2023, persistent drying remained the largest category but declined to 28.7 %, followed by wet-gets-dry, wet-gets-wetter, and dry-gets-wet regimes, covering 22.7 %, 24.4 %, and 24.3 % of global land, respectively. Land-surface diagnostics showed stronger drying in croplands and urban areas, larger dry-to-wet transitions in wetlands, and elevated wet-to-dry transitions in barren regions. Climate diagnostics indicated that internal variability was linked to large-scale ocean-atmosphere patterns, with the strongest association for the Arctic Oscillation and weaker but spatially coherent associations with the Pacific Decadal Oscillation, North Atlantic Oscillation, and Southern Oscillation Index. Under SSP585, the CMIP6 ensemble mean indicated an increase in wet-gets-wetter regimes to 35.2 % by 2081&amp;ndash;2100 and a reduction in transitional regimes. These findings provide a global diagnostic framework for identifying wet-dry regime transitions and highlight regions where land-surface sensitivity and climate variability may amplify persistent drying, hydroclimatic instability, and risks to future adaptation.</p>
</abstract>
<counts><page-count count="18"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Key Research and Development Program of China</funding-source>
<award-id>2023YFD1501004</award-id>
</award-group>
<award-group id="gs2">
<funding-source>National Natural Science Foundation of China</funding-source>
<award-id>52179008</award-id>
<award-id>52309012</award-id>
<award-id>51579044</award-id>
<award-id>41071053</award-id>
</award-group>
</funding-group>
</article-meta>
</front>
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<back>
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