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<front>
<journal-meta>
<journal-id journal-id-type="publisher-id">Front. Mar. Sci.</journal-id>
<journal-title>Frontiers in Marine Science</journal-title>
<abbrev-journal-title abbrev-type="pubmed">Front. Mar. Sci.</abbrev-journal-title>
<issn pub-type="epub">2296-7745</issn>
<publisher>
<publisher-name>Frontiers Media S.A.</publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.3389/fmars.2025.1621833</article-id>
<article-categories>
<subj-group subj-group-type="heading">
<subject>Marine Science</subject>
<subj-group>
<subject>Original Research</subject>
</subj-group>
</subj-group>
</article-categories>
<title-group>
<article-title>Estimating the summer residual flow based on sea surface temperature within a narrow strait</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Xie</surname>
<given-names>Juncheng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Bai</surname>
<given-names>Peng</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1742198/overview"/>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Xu</surname>
<given-names>Xiaowei</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Xie</surname>
<given-names>Lingling</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<uri xlink:href="https://loop.frontiersin.org/people/1320252/overview"/>
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</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Li</surname>
<given-names>Mingming</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
<xref ref-type="author-notes" rid="fn001">
<sup>*</sup>
</xref>
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</contrib>
<contrib contrib-type="author">
<name>
<surname>Gao</surname>
<given-names>Ying</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
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</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>Marine Science and Technology College, Zhejiang Ocean University</institution>, <addr-line>Zhoushan</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Zhoushan Natural Resource Surveying and Mapping Design Center, Zhoushan Natural Resources and Planning Bureau</institution>, <addr-line>Zhoushan</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>College of Ocean and Meteorology, Guangdong Ocean University</institution>, <addr-line>Zhanjiang</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Meilin Wu, Chinese Academy of Sciences (CAS), China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Junliang Gao, Jiangsu University of Science and Technology, China</p>
<p>Jianhuang Qin, Hohai University, China</p>
<p>Zhixiong Yao, Ministry of Natural Resources, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Peng Bai, <email xlink:href="mailto:pengbai@zjou.edu.cn">pengbai@zjou.edu.cn</email>; Mingming Li, <email xlink:href="mailto:limm@gdou.edu.cn">limm@gdou.edu.cn</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>13</day>
<month>06</month>
<year>2025</year>
</pub-date>
<pub-date pub-type="collection">
<year>2025</year>
</pub-date>
<volume>12</volume>
<elocation-id>1621833</elocation-id>
<history>
<date date-type="received">
<day>02</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="accepted">
<day>27</day>
<month>05</month>
<year>2025</year>
</date>
<date date-type="rev-recd">
<day>23</day>
<month>05</month>
<year>2025</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2025 Xie, Bai, Xu, Xie, Li and Gao</copyright-statement>
<copyright-year>2025</copyright-year>
<copyright-holder>Xie, Bai, Xu, Xie, Li and Gao</copyright-holder>
<license xlink:href="http://creativecommons.org/licenses/by/4.0/">
<p>This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.</p>
</license>
</permissions>
<abstract>
<p>Residual flow in straits manifests the interactions of multiple dynamic processes and serves as pivotal connectors between these processes, playing a crucial role in marine material-energy transport and ecosystem evolution. Current research predominantly relies on <italic>in-situ</italic> measurements and numerical modeling, yet both approaches incur high costs and struggle to obtain long-term residual current datasets, constraining our understanding of marine environments in straits and their adjacent basins. Addressing this gap, we developed an innovative algorithm to inversely calculate residual flow using satellite-derived sea surface temperature (SST) data, with a case study on the tide-dominated narrow Qiongzhou Strait in the northern South China Sea. Capitalizing on its distinctive summer SST pattern (eastern cooling vs. western warming) and prevailing westward residual current regime, we demonstrated that the thermal structure can be effectively characterized by a 1D balance equation incorporating temporal variation, horizontal advection, diffusion, and thermal forcing terms. Applying this framework to MODIS SST data (2003&#x2013;2022), we reliably estimated summer residual flow velocities and fluxes over two decades. The analysis further revealed significant interannual variability in westward flow intensity, modulated by large-scale air-sea interactions: cyclonic wind anomalies over the northwestern South China Sea enhance westward currents, while anticyclonic anomalies induce weakening. This approach provides a cost-effective paradigm for monitoring long-term strait dynamics.</p>
</abstract>
<kwd-group>
<kwd>residual flow</kwd>
<kwd>sea surface temperature</kwd>
<kwd>upwelling</kwd>
<kwd>MODIS</kwd>
<kwd>Qiongzhou Strait</kwd>
</kwd-group>
<counts>
<fig-count count="8"/>
<table-count count="1"/>
<equation-count count="2"/>
<ref-count count="49"/>
<page-count count="13"/>
<word-count count="5020"/>
</counts>
<custom-meta-wrap>
<custom-meta>
<meta-name>section-in-acceptance</meta-name>
<meta-value>Coastal Ocean Processes</meta-value>
</custom-meta>
</custom-meta-wrap>
</article-meta>
</front>
<body>
<sec id="s1" sec-type="intro">
<label>1</label>
<title>Introduction</title>
<p>A strait, defined as a narrow waterway connecting two seas or oceans between adjacent landmasses, serves not only as a critical maritime corridor and shipping hub with strategic military importance but also plays a pivotal role in global oceanographic processes. As crucial conduits linking distinct marine basins, straits regulate regional and even global thermohaline transport and material cycling through their complex water exchange patterns, circulation structures, and energy transfer mechanisms. For instance, the Mediterranean Overflow via the Gibraltar Strait significantly influences the Atlantic Meridional Overturning Circulation (<xref ref-type="bibr" rid="B20">Hern&#xe1;ndez-Molina et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B33">Swingedouw et&#xa0;al., 2019</xref>), while water exchange through the Bering Strait governs the physico-chemical and biological environments of both the Arctic and North Pacific Oceans (<xref ref-type="bibr" rid="B37">Woodgate et&#xa0;al., 2005</xref>; <xref ref-type="bibr" rid="B19">Grebmeier et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B38">Woodgate et&#xa0;al., 2012</xref>). Even in smaller-scale systems like the Qiongzhou Strait, intense tidal currents directly shape the unique &#x201c;butterfly delta&#x201d; submarine geomorphology at its eastern and western outlets (<xref ref-type="bibr" rid="B29">Ni et&#xa0;al., 2014</xref>).</p>
<p>Residual flow refers to the time-averaged, non-tidal components of oceanic flow that persist after filtering out high-frequency motions such as tides, inertial oscillations, and wind-driven surface waves. Residual flow in straits, emerging as net water transport from the interplay of multiple dynamic processes, serve as both a manifestation of complex hydrodynamic interactions and a key linkage connecting various oceanographic processes. The spatiotemporal characteristics of residual flow fundamentally control suspended particulate transport pathways, pollutant dispersion ranges, and nutrient cycling efficiency within straits. In strongly tidal straits, residual flow dominates the formation of sediment &#x201c;trapping zones&#x201d; through long-term cumulative effects, thereby modifying submarine topography and posing navigational challenges (<xref ref-type="bibr" rid="B34">Van Maren and Gerritsen, 2012</xref>; <xref ref-type="bibr" rid="B29">Ni et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B1">Ai et&#xa0;al., 2024</xref>). Notably, the Taiwan Strait acts as a conduit for wintertime transport of East China Sea water masses to the northeastern South China Sea under northeast monsoon forcing, significantly impacting local marine environments (<xref ref-type="bibr" rid="B7">Chen et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B25">Li et&#xa0;al., 2024</xref>) and consequently influencing fishery resource distribution patterns. These mechanisms underscore the irreplaceable scientific value of studying residual currents in straits for understanding marine material transport, ecosystem stability, and anthropogenic impacts.</p>
<p>The Qiongzhou Strait, situated between the Leizhou Peninsula of Guangdong Province and Hainan Island, China (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1a</bold>
</xref>), serves as the sole natural conduit for water exchange between the northern South China Sea and the Beibu Gulf, and ranks among China&#x2019;s three major straits. This east-west oriented strait extends approximately 80 km in length, with a minimum width of 19.4 km, averaging 44 m in water depth and reaching a maximum depth of 114 m. A 33-km-long tidal channel with water depths exceeding 60 m dominates the central strait, exhibiting asymmetric topography across its northern and southern flanks: the northern flank is relatively gentle whereas the southern side is steeper. During summer, the Qiongzhou Strait is dominated by the southerly monsoon (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref>). Distinct thermal regimes characterize its eastern and western entrances: cold waters occupy the eastern entrance due to the development of coastal upwelling, while the western entrance is governed by vertically well-mixed warm waters resulting from intense tidal mixing combined with strong solar radiation (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref>; <xref ref-type="bibr" rid="B21">Hu et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B2">Bai et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B27">Lin et&#xa0;al., 2016</xref>; <xref ref-type="bibr" rid="B5">Bai et&#xa0;al., 2020a</xref>, <xref ref-type="bibr" rid="B4">2022</xref>).</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>
<bold>(a)</bold> Geographical setting and bathymetric distribution of the Qiongzhou Strait; <bold>(b)</bold> Climatological summer SST and wind vector field distribution in the Qiongzhou Strait; <bold>(c)</bold> Climatological summer sea surface chlorophyll-a (Chl-a) concentration distribution in the Qiongzhou Strait.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g001.tif"/>
</fig>
<p>The Qiongzhou Strait is a strong tide-dominated channel. Within the strait, diurnal tidal constituents predominantly propagate east to west. At the western entrance, the amplitude of diurnal tides (<inline-formula>
<mml:math display="inline" id="im1">
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mtext>O</mml:mtext>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mtext>K</mml:mtext>
<mml:mn>1</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:mfrac>
</mml:mrow>
</mml:math>
</inline-formula>) reaches 70 cm, gradually decreasing eastward to 25 cm at the eastern entrance. The maximum phase lag occurs in the southwestern strait (with minimal phase lags at both entrances), where tidal waves from both ends interact. The phase speed of westward-propagating diurnal tides measures approximately 10&#xa0;m/s, significantly faster than eastward-propagating diurnal constituents. In contrast, the semidiurnal M<sub>2</sub> constituent propagates exclusively west-to-east from the Beibu Gulf, with its amplitude increasing from 20 cm at the western entrance to 40 cm at the eastern entrance. The phase lag difference between the strait&#x2019;s two ends is approximately 100&#xb0; (equivalent to 6.5 hours), yielding a propagation speed of ~4.7 m/s, slower than diurnal tidal speeds. Both diurnal and semidiurnal tidal current ellipses align nearly parallel to the strait&#x2019;s axis. Diurnal tidal currents peak in the 5&#x2013;10 m water layer, exhibiting amplitudes of ~30 cm/s at the western entrance and up to 100 cm/s at the eastern entrance. Notably, near-bottom currents (within 3 m of the seabed) maintain substantial amplitudes of 30&#x2013;50 cm/s. The M<sub>2</sub> semidiurnal currents display weaker intensities (10&#x2013;20 cm/s), approximately one order of magnitude smaller than diurnal currents. Unlike diurnal constituents, semidiurnal currents show minimal vertical variability, with near-identical surface and near-bed current magnitudes (<xref ref-type="bibr" rid="B32">Shi et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B6">Chen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>).</p>
<p>In coastal shallow seas, waves alongside tides are key hydrodynamic drivers (e.g., <xref ref-type="bibr" rid="B15">Gao et&#xa0;al., 2017</xref>, <xref ref-type="bibr" rid="B16">2021</xref>, <xref ref-type="bibr" rid="B17">2023</xref>, <xref ref-type="bibr" rid="B14">2024</xref>). During summer, the southwest monsoon weakens as it encounters Hainan Island (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref>), resulting in mild wind waves with disorganized directional distribution in Qiongzhou Strait. In contrast, the northeast winter monsoon directly impacts the strait. Waves from the open sea east of the strait also propagate unimpeded into the region, generating larger waves (~1 m height). Strong tidal currents in the strait further modulate wave dynamics. Current-induced convergence and wavenumber shifts can amplify significant wave height at the strait&#x2019;s eastern entrance. Additionally, tidal flow regulates peak wave directions through current-induced refraction (<xref ref-type="bibr" rid="B3">Bai et&#xa0;al., 2020b</xref>).</p>
<p>The southwest monsoon governs the entire northwestern South China Sea, leading to the early assumption that summer water transport from the Beibu Gulf through the Qiongzhou Strait to the eastern shelf seas of the Leizhou Peninsula would generate eastward residual flow within the strait. However, <xref ref-type="bibr" rid="B32">Shi et&#xa0;al. (2002)</xref> demonstrated, using 37-year observational datasets of tidal elevation and currents combined with numerical modeling, that a persistent westward residual flow (10&#x2013;40 cm/s) exists year-round in the strait. This flow contributes a summer water transport of 0.1&#x2013;0.2 Sv into the Beibu Gulf. Subsequently, <xref ref-type="bibr" rid="B44">Yang et&#xa0;al. (2003)</xref> identified westward residual flow structures in the Qiongzhou Strait during summer using drifter bottle data. Employing a three-dimensional ECOM model, <xref ref-type="bibr" rid="B6">Chen et&#xa0;al. (2009)</xref> systematically investigated tidal-induced residual flow, wind-driven currents, and density-driven circulation. Their results confirmed that westward residual flow dominates the strait in both winter and summer, with tidal rectification generating westward residual currents of 5&#x2013;30 cm/s. These currents fully suppress wind-driven eastward flows (5&#x2013;15 cm/s), establishing tidal dynamics as the primary driver of the strait&#x2019;s westward residual flow. <xref ref-type="bibr" rid="B36">Wang et&#xa0;al. (2014)</xref> analyzed summer Acoustic Doppler Current Profiler (ADCP) measurements, revealing meridional variability in the westward residual flow, with peak velocities reaching -0.34 m/s and a mean westward transport of 0.16 Sv. Recently, <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al. (2024)</xref> implemented the SCHISM model to further elucidate residual flow dynamics in the Qiongzhou Strait. Their study quantified a mean summer westward residual flow of 0.2 m/s and identified that wind stress curl differences between the eastern and western strait entrances can induce transient eastward residual flows. According to <xref ref-type="bibr" rid="B32">Shi et&#xa0;al. (2002)</xref>, summer westward transport through the Qiongzhou Strait accounts for approximately 44% of the Beibu Gulf&#x2019;s water renewal. A series of studies (<xref ref-type="bibr" rid="B39">Wu et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B11">Ding et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B42">Yang et&#xa0;al., 2020</xref>; <xref ref-type="bibr" rid="B45">Zavala-Garay et&#xa0;al., 2022</xref>) have confirmed that this transport mechanism critically governs the formation of summer cyclonic circulation within the Beibu Gulf. Additionally, the summer westward residual flow significantly modulates thermal patterns at the western strait entrance (<xref ref-type="bibr" rid="B4">Bai et&#xa0;al., 2022</xref>) and influences seabed geomorphology and sediment deposition (<xref ref-type="bibr" rid="B29">Ni et&#xa0;al., 2014</xref>).</p>
<p>Current research methodologies for investigating residual flow in the Qiongzhou Strait primarily rely on two approaches: <italic>in situ</italic> data analysis and ocean numerical modeling (<xref ref-type="bibr" rid="B32">Shi et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B44">Yang et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B9">Chen et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B43">Yan et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B6">Chen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B36">Wang et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B48">Zhu et&#xa0;al., 2014</xref>, <xref ref-type="bibr" rid="B49">2015</xref>; <xref ref-type="bibr" rid="B45">Zavala-Garay et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B8">Chen et&#xa0;al., 2025</xref>). However, both methodologies demand substantial human, material, and temporal resources while yielding limited long-term residual flow records. This constraint has directly contributed to significant discrepancies in residual flow intensity reported in previous studies focusing on different summer periods within the strait. To address these limitations, this study proposes an innovative algorithm for residual flow inversion based on the unique east-west thermal contrast (cooler eastern vs. warmer western sectors) and westward residual flow background during summer seasons. By solving a one-dimensional thermal balance equation using MODIS-derived sea surface temperature (SST) data, we achieved cost-effective and physically reasonable estimations of summer residual flow patterns in the Qiongzhou Strait from 2003 to 2022. The remainder of this paper is organized as follows: Section 2 describes the primary datasets employed in this study. Section 3 details the residual flow inversion algorithm derived from SST observations. Section 4 presents the estimated summer residual flow patterns and evaluates the reliability of the proposed methodology. Section 5 investigates the interannual variability mechanisms through selected representative years. Section 6 concludes with a summary of key findings and implications.</p>
</sec>
<sec id="s2">
<label>2</label>
<title>Data</title>
<sec id="s2_1">
<label>2.1</label>
<title>Remote-sensed SST</title>
<p>Satellite-derived SST has emerged as a critical observational tool for oceanic studies, providing essential insights into diverse marine phenomena including marine heatwaves, ecosystem dynamics, frontal processes, mesoscale eddies, typhoon-ocean interactions, and air-sea exchange mechanisms. For residual flow quantification in the Qiongzhou Strait, we utilized the Moderate Resolution Imaging Spectroradiometer (MODIS) Level 3 SST product (2003&#x2013;2022 summer months) obtained from NASA Ocean Color Platform (<ext-link ext-link-type="uri" xlink:href="http://oceancolor.gsfc.nasa.gov/">http://oceancolor.gsfc.nasa.gov/</ext-link>). This dataset contains observations from both Aqua (MODIS-A) and Terra (MODIS-T) satellite platforms, offering 4 km spatial resolution gridded data through optimal spatiotemporal compositing algorithms.</p>
</sec>
<sec id="s2_2">
<label>2.2</label>
<title>Chl-a data</title>
<p>The summer climatology (June&#x2013;August) of monthly chlorophyll-a (Chl-a) concentration, obtained from the NASA Ocean Color database (<ext-link ext-link-type="uri" xlink:href="https://oceancolor.gsfc.nasa.gov/">https://oceancolor.gsfc.nasa.gov/</ext-link>), was employed to determine Jerlov water types (<xref ref-type="bibr" rid="B22">Jerlov, 1968</xref>) in the Qiongzhou Strait. The MODIS-derived Chl-a dataset, with a spatial resolution of 4 km, demonstrated sufficient sensitivity to resolve the spatiotemporal Chl-a distribution patterns characteristic of this semi-enclosed Qiongzhou Strait.</p>
</sec>
<sec id="s2_3">
<label>2.3</label>
<title>Satellite-observed winds</title>
<p>The Cross-Calibrated Multi-Platform (CCMP) Level-4 wind vector product was employed to characterize the atmospheric dynamic forcing in the study region. This advanced dataset synthesizes microwave sensor-derived ocean surface wind observations (10 m elevation) with ECMWF reanalysis background fields through variational assimilation, providing gap-free spatial continuity at 0.25&#xb0; &#xd7; 0.25&#xb0; gridding with six-hour temporal resolution. The CCMP product can be obtained from the Remote Sensing Systems website (<ext-link ext-link-type="uri" xlink:href="http://www.remss.com/ccmp/">http://www.remss.com/ccmp/</ext-link>).</p>
</sec>
<sec id="s2_4">
<label>2.4</label>
<title>Reanalyzed air-sea heat fluxes</title>
<p>The ERA5 reanalysis dataset was utilized to quantify surface net heat flux and shortwave radiation through comprehensive air-sea heat flux components. This state-of-the-art reanalysis integrates multi-source observations (satellites, meteorological stations, ships, and buoys) with advanced numerical weather prediction simulations via 4D-Var data assimilation, delivering continuous meteorological records at 0.25&#xb0; &#xd7; 0.25&#xb0; spatial resolution. Recognized for its high assimilation quality and comprehensive physical parameterization, ERA5 has been extensively utilized in climate-ocean interaction studies, particularly for resolving energy budget dynamics and extreme meteorological events.</p>
</sec>
<sec id="s2_5">
<label>2.5</label>
<title>Reanalyzed circulation data</title>
<p>To validate the interannual variability of residual flow derived in this study, the GLORYS12V1 reanalysis product from the Copernicus Marine Environment Monitoring Service (CMEMS) (<ext-link ext-link-type="uri" xlink:href="https://marine.copernicus.eu/access-data">https://marine.copernicus.eu/access-data</ext-link>) was employed. This dataset provides global three-dimensional fields of seawater temperature, salinity, and current velocities since 1993, featuring a horizontal resolution of 1/12&#xb0; with 50 vertical layers that adequately resolve the Qiongzhou Strait&#x2019;s bathymetry. Developed on the NEMO ocean modeling platform, the product enhances accuracy through multivariate data assimilation techniques including reduced-order Kalman filtering and 3D-var analysis, and has been extensively adopted in global marine science research.</p>
<p>It should be noted that while this product cannot accurately represent tidally-induced residual flow (i.e., net residual flow) due to the exclusion of tidal forcing, it effectively captures wind-driven residual flow and baroclinic-effect-induced residual flow. Given that tidal adjustment contributions to residual flow remain relatively invariant interannually at seasonal scales, the GLORYS12V1 product demonstrates sufficient capability to characterize interannual variations of residual flow in the strait, despite its limitations in quantifying absolute residual flow magnitudes.</p>
</sec>
</sec>
<sec id="s3">
<label>3</label>
<title>Residual flow retrieval algorithm</title>
<sec id="s3_1">
<label>3.1</label>
<title>One-dimensional thermal balance equation for the strait</title>
<p>
<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref> depicts the climatological summer SST and wind field distribution in the Qiongzhou Strait. The eastern strait is dominated by cold water masses originating from the northeastern Hainan upwelling system (<xref ref-type="bibr" rid="B2">Bai et&#xa0;al., 2016</xref>, <xref ref-type="bibr" rid="B5">2020a</xref>, <xref ref-type="bibr" rid="B4">2022</xref>; <xref ref-type="bibr" rid="B27">Lin et&#xa0;al., 2016</xref>), while the western strait exhibits elevated SST due to strong tidal mixing synergized with intense solar radiation (<xref ref-type="bibr" rid="B21">Hu et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B4">Bai et&#xa0;al., 2022</xref>). Persistent westward residual flow, as consistently reported in previous studies, facilitates the westward transport of cold water from the eastern strait, generating a characteristic westward-protruding SST tongue structure (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref>). The study area experiences substantial net heat flux in the upper ocean during summer, compounded by the strait&#x2019;s unique east-west oriented narrow topography.</p>
<p>Integrating these dynamic, thermodynamic, and bathymetric factors, <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2a</bold>
</xref> schematically illustrates the summer SST pattern, net surface heat flux distribution, and residual flow configuration. The narrow geometry permits simplification of the upper mixed layer thermal balance equation to a one-dimensional formulation expressed as (<xref ref-type="bibr" rid="B31">Qu, 2003</xref>; <xref ref-type="bibr" rid="B26">Liang and Wu, 2013</xref>; <xref ref-type="bibr" rid="B35">Wang et&#xa0;al., 2023</xref>; <xref ref-type="bibr" rid="B46">Zhang et&#xa0;al., 2023</xref>):</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>
<bold>(a)</bold> Schematic of summer SST, net surface heat flux, and residual flow patterns in the Qiongzhou Strait; <bold>(b)</bold> 1-D simplified thermal model with governing equation for summertime Qiongzhou Strait.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g002.tif"/>
</fig>
<disp-formula id="eq1">
<label>(1)</label>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>T</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>T</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>x</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>Q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>d</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>h</mml:mi>
<mml:mi>&#x3c1;</mml:mi>
<mml:msub>
<mml:mi>C</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:mi>a</mml:mi>
<mml:mfrac>
<mml:mrow>
<mml:msup>
<mml:mo>&#x2202;</mml:mo>
<mml:mn>2</mml:mn>
</mml:msup>
<mml:mi>T</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msup>
<mml:mi>x</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>T</italic> is the temperature in the surface mixed layer, <italic>t</italic> is time, <italic>x</italic> is the east-west coordinate, <inline-formula>
<mml:math display="inline" id="im2">
<mml:mrow>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the residual flow within the strait, <italic>Q</italic> is the sum of air-sea heat fluxes, including shortwave radiation, longwave radiation, sensible heat flux, and latent heat flux, <inline-formula>
<mml:math display="inline" id="im3">
<mml:mrow>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>d</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the shortwave radiation penetrating below the mixed layer, <italic>h</italic> is the mixed layer depth, <inline-formula>
<mml:math display="inline" id="im4">
<mml:mrow>
<mml:mi>&#x3c1;</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1022.0</mml:mn>
<mml:mtext>&#xa0;kg</mml:mtext>
<mml:mo stretchy="false">/</mml:mo>
<mml:msup>
<mml:mtext>m</mml:mtext>
<mml:mn>3</mml:mn>
</mml:msup>
</mml:mrow>
</mml:math>
</inline-formula> is the seawater density, <inline-formula>
<mml:math display="inline" id="im5">
<mml:mrow>
<mml:msub>
<mml:mi>C</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mn>4002.6</mml:mn>
<mml:mtext>&#xa0;J</mml:mtext>
<mml:mo stretchy="false">/</mml:mo>
<mml:mtext>kg</mml:mtext>
<mml:mo>&#xb7;</mml:mo>
<mml:mtext>&#xb0;C</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> is the specific heat capacity of seawater, <inline-formula>
<mml:math display="inline" id="im6">
<mml:mrow>
<mml:mi>a</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>k</mml:mi>
<mml:mrow>
<mml:mi>&#x3c1;</mml:mi>
<mml:msub>
<mml:mi>C</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</inline-formula> is the heat transfer coefficient of seawater and <inline-formula>
<mml:math display="inline" id="im7">
<mml:mrow>
<mml:mi>k</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>0.616</mml:mn>
<mml:mtext>&#xa0;W</mml:mtext>
<mml:mo stretchy="false">/</mml:mo>
<mml:mtext>m</mml:mtext>
<mml:mo>&#xb7;</mml:mo>
<mml:mtext>&#xb0;C</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> is the coefficient of seawater thermal conductivity. Notably, (<xref ref-type="disp-formula" rid="eq1">
<bold>Equation 1</bold>
</xref>) should theoretically contain an additional residual term on its right-hand side, primarily consisting of vertical entrainment and mixing processes. However, given its relatively minor magnitude compared to dominant terms and for numerical tractability, this term has been systematically neglected in our formulation. Consequently, the simplified one-dimensional thermal balance model governing summer sea surface temperature variations in the Qiongzhou Strait, along with its control equations, can be mathematically expressed as shown in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2b</bold>
</xref>.</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Discretization of the 1D thermal balance equation</title>
<p>
<xref ref-type="disp-formula" rid="eq1">
<bold>Equation 1</bold>
</xref> governs the thermal dynamics within the strait, incorporating four principal components: the temporal variation term, advection term, horizontal diffusion term, and heat source term. Specifically, the advection term arises from the westward transport of cold water mass by residual flow. Through Forward Time Central Space (FTCS) discretization, the numerical formulation of <xref ref-type="disp-formula" rid="eq1">
<bold>Equation 1</bold>
</xref> becomes:</p>
<disp-formula id="eq2">
<label>(2)</label>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mi>i</mml:mi>
<mml:mrow>
<mml:mi>j</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo>+</mml:mo>
<mml:mi>a</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:msup>
<mml:mi>x</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfrac>
<mml:mo>&#xb7;</mml:mo>
<mml:mo stretchy="false">(</mml:mo>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>2</mml:mn>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo stretchy="false">)</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#xb7;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>x</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>&#xb7;</mml:mo>
<mml:mo stretchy="false">(</mml:mo>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo>&#x2212;</mml:mo>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>j</mml:mi>
</mml:msubsup>
<mml:mo stretchy="false">)</mml:mo>
<mml:mo>+</mml:mo>
<mml:mo>&#x394;</mml:mo>
<mml:mi>t</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>Q</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>d</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mi>h</mml:mi>
<mml:mi>&#x3c1;</mml:mi>
<mml:msub>
<mml:mi>C</mml:mi>
<mml:mi>p</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im8">
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mn>2</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mn>3</mml:mn>
<mml:mo>&#x22ef;</mml:mo>
<mml:mo>,</mml:mo>
<mml:mtext>&#xa0;I</mml:mtext>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>,</mml:mo>
<mml:mtext>&#xa0;I</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> denotes the discrete spatial grid points along the x-axis, <inline-formula>
<mml:math display="inline" id="im9">
<mml:mrow>
<mml:mi>j</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mn>2</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mn>3</mml:mn>
<mml:mo>&#x22ef;</mml:mo>
<mml:mo>,</mml:mo>
<mml:mtext>&#xa0;J</mml:mtext>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo>,</mml:mo>
<mml:mtext>&#xa0;J</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> represents the discrete time layers, <inline-formula>
<mml:math display="inline" id="im10">
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>t</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>60</mml:mn>
<mml:mtext>&#xa0;s</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> is the temporal step size, and <inline-formula>
<mml:math display="inline" id="im11">
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>x</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>2100</mml:mn>
<mml:mtext>&#xa0;m</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula>is the spatial step size. The question then arises: how should the boundary and initial conditions for <italic>T</italic> be established? This study selects a control line AB along the west-east central axis of the strait (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3a</bold>
</xref>), utilizing the SST distribution along this transect to inversely calculate the westward residual flow. This approach effectively eliminates interference from meridional dynamic and thermodynamic processes on SST variations. For boundary conditions, we set <inline-formula>
<mml:math display="inline" id="im12">
<mml:mrow>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mtext>i</mml:mtext>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>A</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math display="inline" id="im13">
<mml:mrow>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mtext>i</mml:mtext>
<mml:mo>=</mml:mo>
<mml:mtext>I</mml:mtext>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>B</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, where <inline-formula>
<mml:math display="inline" id="im14">
<mml:mrow>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>A</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im15">
<mml:mrow>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>B</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> correspond to the SST values at the western (left) and eastern (right) endpoints of control line AB, respectively, obtainable from MODIS SST. Regarding initial conditions, given the observed east-to-west thermal gradient within the strait (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1b</bold>
</xref>), this study adopts the formulation <inline-formula>
<mml:math display="inline" id="im16">
<mml:mrow>
<mml:msubsup>
<mml:mi>T</mml:mi>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>&#x2208;</mml:mo>
<mml:mo stretchy="false">[</mml:mo>
<mml:mn>2</mml:mn>
<mml:mo>,</mml:mo>
<mml:mtext>&#xa0;I</mml:mtext>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
<mml:mo stretchy="false">]</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mi>j</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msubsup>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>T</mml:mi>
<mml:mtext>B</mml:mtext>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>
<bold>(a)</bold> Locations of SST used for inverse calculation of the westward residual flow (control line AB); <bold>(b)</bold> Summer climatological SST distribution along control line AB; <bold>(c)</bold> Bathymetric distribution along control line CD employed for computing westward transport.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g003.tif"/>
</fig>
<p>
<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3b</bold>
</xref> displays the climatological SST distribution along control line AB during summer, revealing a quasi-linear increasing pattern from the eastern to the western strait. This thermal profile aligns with the temperature distribution constrained by the one-dimensional simplified governing equation presented in (<xref ref-type="disp-formula" rid="eq1">
<bold>Equation 1</bold>
</xref>), thereby validating the inverse calculation method for residual flow within the strait under this theoretical framework. Simultaneously, the control line CD was designated as the volumetric flux calculation transect (<xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3a</bold>
</xref>), with its bathymetric profile shown in <xref ref-type="fig" rid="f3">
<bold>Figure&#xa0;3c</bold>
</xref>. For computational purposes, we assumed uniform residual flow distribution across the entire CD cross-section during flux calculations.</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Key parameters</title>
<p>A critical question arises: how should the mixed layer thickness <italic>h</italic> in the heat flux forcing term be appropriately determined? <xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4</bold>
</xref> displays the vertical temperature profiles measured at stations S1&#x2013;S5 in the eastern Qiongzhou Strait during July 2018. These observations reveal a shallow summer mixed layer (~5 m) in the study area, with increasingly uniform vertical thermal stratification at stations closer to the strait interior (S4, S5). Consequently, we select the upper 5 m water column (<italic>h</italic>=5 m) to calculate the net surface heat flux contribution to seawater heating within this layer.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Vertical distributions of shipboard-measured sea temperature at stations S1&#x2013;S5 in the eastern Qiongzhou Strait during summer, with station locations illustrated in the lower right panel.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g004.tif"/>
</fig>
<p>To determine the net heat flux absorbed by the upper 5 m layer, it is essential to account for the residual shortwave radiation <inline-formula>
<mml:math display="inline" id="im17">
<mml:mrow>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>d</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> penetrating to 5 m depth. <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1c</bold>
</xref> illustrates the climatological summer sea surface Chl-a concentration distribution in the Qiongzhou Strait, showing central strait values of 2&#x2013;3 mg/m&#xb3;. Based on the empirical relationship between Jerlov water types and Chl-a concentrations (<xref ref-type="bibr" rid="B28">Morel, 1988</xref>) and results from <xref ref-type="bibr" rid="B45">Zavala-Garay et&#xa0;al. (2022)</xref>, the water type along the central axis corresponds to intermediate Jerlov II&#x2013;III classifications. Further calculations of <inline-formula>
<mml:math display="inline" id="im18">
<mml:mrow>
<mml:msub>
<mml:mi>Q</mml:mi>
<mml:mi>d</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> employ the shortwave radiation attenuation coefficients for different Jerlov water types as defined by <xref ref-type="bibr" rid="B30">Paulson and Simpson (1977)</xref>.</p>
<p>With all terms except the residual flow <inline-formula>
<mml:math display="inline" id="im19">
<mml:mrow>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> in the one-dimensional SST control (<xref ref-type="disp-formula" rid="eq2">
<bold>Equation 2</bold>
</xref>) now constrained by observational and theoretical constraints (<xref ref-type="disp-formula" rid="eq2">
<bold>Equation 2</bold>
</xref>), we implement an inversion workflow: (1) prescribe westward residual flow velocities using a test range of <inline-formula>
<mml:math display="inline" id="im20">
<mml:mrow>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2208;</mml:mo>
<mml:mo stretchy="false">[</mml:mo>
<mml:mn>0.0</mml:mn>
<mml:mo>,</mml:mo>
<mml:mo>&#xa0;</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>0.5</mml:mn>
<mml:mo stretchy="false">]</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> with a&#xa0;-0.005 m/s increments. (2) generate numerical SST solutions along control line AB for each velocity value. (3) identify the velocity corresponding to the optimal solution of SST along control line AB as the magnitude of residual flow. This approach yields the climatological (or annual) summer westward residual flow speed.</p>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>Residual flow and flux in 2003&#x2013;2022</title>
<p>The summer climatological residual current for 2003&#x2013;2022 in the Qiongzhou Strait was estimated using the aforementioned inverse calculation methodology. <xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5</bold>
</xref> presents a comparative analysis between MODIS satellite-derived SST measurements (red line) and the optimal simulated SST distribution (thick blue dashed line) along control line AB. The optimal calculated SST demonstrates good agreement with the observed SST pattern along control line AB. The corresponding residual current <inline-formula>
<mml:math display="inline" id="im21">
<mml:mrow>
<mml:msub>
<mml:mi>U</mml:mi>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mi>e</mml:mi>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
<mml:mi>d</mml:mi>
<mml:mi>u</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>0.130</mml:mn>
<mml:mtext>&#xa0;m</mml:mtext>
<mml:mo stretchy="false">/</mml:mo>
<mml:mtext>s</mml:mtext>
</mml:mrow>
</mml:math>
</inline-formula> (negative values indicate westward direction) derived from this optimal SST solution drives a water transport of approximately 0.1102 Sv from the Qiongzhou Strait into the Beibu Gulf. This finding aligns with prior research documenting summer residual currents of 0.05&#x2013;0.3 m/s (equivalent to 0.026&#x2013;0.2 Sv transport) in the Qiongzhou Strait (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>), thereby validating the reasonableness of our results.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Modeled SST distributions along control line AB under different westward residual current scenarios (gray dashed lines); the red solid line represents the MODIS-observed summer climatological SST along control line AB, while the blue dashed line indicates the optimal simulated SST.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g005.tif"/>
</fig>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Previous studies on residual flow and flux in Qiongzhou Strait.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" rowspan="2" align="left">Reference</th>
<th valign="middle" colspan="4" align="left">Westward residual current velocity (m/s)</th>
<th valign="middle" colspan="4" align="left">Westward volume transport (Sv)</th>
<th valign="middle" rowspan="2" align="center">Method</th>
</tr>
<tr>
<th valign="middle" align="left">winter</th>
<th valign="middle" align="left">spring</th>
<th valign="middle" align="left">summer</th>
<th valign="middle" align="left">autumn</th>
<th valign="middle" align="left">winter</th>
<th valign="middle" align="left">spring</th>
<th valign="middle" align="left">summer</th>
<th valign="middle" align="left">autumn</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" align="center">
<xref ref-type="bibr" rid="B32">Shi et&#xa0;al. (2002)</xref>
</td>
<td valign="middle" colspan="2" align="center">0.2&#x2013;0.4</td>
<td valign="middle" colspan="2" align="center">0.1&#x2013;0.3</td>
<td valign="middle" colspan="2" align="center">0.2&#x2013;0.4</td>
<td valign="middle" colspan="2" align="center">0.1&#x2013;0.2</td>
<td valign="middle" align="center">Observation analysis</td>
</tr>
<tr>
<td valign="middle" align="center">
<xref ref-type="bibr" rid="B6">Chen et&#xa0;al. (2009)</xref>
</td>
<td valign="middle" align="center">0.05&#x2013;0.4</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">0.05&#x2013;0.3</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">0.116</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">0.026</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">ECOM simulation</td>
</tr>
<tr>
<td valign="middle" align="center">
<xref ref-type="bibr" rid="B36">Wang et&#xa0;al. (2014)</xref>
</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">0.34</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center"/>
<td valign="middle" align="center">0.16</td>
<td valign="middle" align="center"/>
<td valign="middle" align="center">Observation analysis</td>
</tr>
<tr>
<td valign="middle" align="center">
<xref ref-type="bibr" rid="B47">Zheng et&#xa0;al. (2024)</xref>
</td>
<td valign="middle" align="center">0.4&#x2013;0.5</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">0.2</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">/</td>
<td valign="middle" align="center">SCHISM simulation</td>
</tr>
</tbody>
</table>
</table-wrap>
<p>Furthermore, summer westward residual flow in the Qiongzhou Strait during 2003&#x2013;2022 was estimated using MODIS SST. <xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6</bold>
</xref> compares the MODIS-observed summer SST (solid red lines) with the optimal simulated SST (blue dashed lines) along control line AB for individual years. The results reveal that most years exhibit a linear east-to-west increasing SST pattern along control line AB. Meanwhile, the optimally inverted SST generally aligns well with MODIS observations across most years, which further validates the rationality of both the one-dimensional thermal balance (<xref ref-type="disp-formula" rid="eq1">
<bold>Equation 1</bold>
</xref>) developed in this study and the residual flow inversion methodology. Notably, the thermal control line in the summer 2010 appears shorter than in other years due to missing MODIS SST data in that specific period.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>Comparison of MODIS-observed summer SST (red solid line) and the optimal simulated SST (blue dashed line) along control line AB during 2003&#x2013;2022.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g006.tif"/>
</fig>
<p>Building upon these findings, <xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref> quantitatively illustrates the temporal distribution of summer residual flow and associated volume transport in the Qiongzhou Strait from 2003 to 2022. The results reveal pronounced interannual variability in both residual current intensity and transport magnitude, aligning with the numerical simulations of <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al. (2024)</xref>, which suggest that interannual variability in local winds could lead to potential fluctuations in the intensity of summer residual currents. During the study period, the maximum westward residual flow occurred in 2018, recording values of -0.5040 m/s (velocity) and 0.4271 Sv (transport). In contrast, the minimum westward flow was observed in 2016, with corresponding estimations of -0.0640 m/s and 0.0542 Sv, respectively.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>Temporal evolution of summer residual flow and residual transport in the Qiongzhou Strait from 2003 to 2022.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g007.tif"/>
</fig>
</sec>
<sec id="s5" sec-type="discussion">
<label>5</label>
<title>Discussion</title>
<p>
<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref> demonstrates that the summer westward residual flow velocities in the Qiongzhou Strait during 2004, 2010, and 2018 consistently exceeded 0.3 m/s, significantly surpassing the maximum westward residual currents previously reported based on field measurements or three-dimensional circulation models (<xref ref-type="bibr" rid="B32">Shi et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B6">Chen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>). Does this imply that our original SST-based inversion method for residual flow is unreliable?</p>
<p>The summer residual flow in the Qiongzhou Strait primarily comprises three components: (1) residual flow induced by tidal rectification over complex topography, (2) wind-driven residual currents, and (3) baroclinic-effect-driven residual currents caused by density gradients (<xref ref-type="bibr" rid="B32">Shi et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B6">Chen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B48">Zhu et&#xa0;al., 2014</xref>, <xref ref-type="bibr" rid="B49">2015</xref>; <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>). On seasonal timescales, residual flow forced by tidal rectification remains relatively constant across years. Therefore, interannual variability in the strait&#x2019;s residual flow is predominantly governed by wind-driven and baroclinic-effect-driven components. This variability can be validated using the GLORYS12V1 reanalysis product, which corroborates the interannual trends in our inverted residual flow.</p>
<p>
<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8</bold>
</xref> illustrates the spatial distributions of summer wind anomalies and associated current anomalies in the northwestern South China Sea during 2004, 2010, and 2018. Cyclonic wind anomalies were observed in all three years, which intensified the western Guangdong coastal current. This enhanced flow transported additional water masses from the western Guangdong shelf into the Qiongzhou Strait, where they merged with the westward residual flow and entered the Beibu Gulf. This mechanism coherently explains the anomalously strong westward residual flow in the strait during these years and further validates the reliability of our inversion method. The wind field over the South China Sea exhibits high sensitivity to large-scale air-sea interactions. Previous studies have extensively documented and elucidated the linkage between South China Sea wind anomalies and ENSO events (e.g., <xref ref-type="bibr" rid="B12">Du et&#xa0;al., 2009</xref>, <xref ref-type="bibr" rid="B13">2011</xref>; <xref ref-type="bibr" rid="B41">Xie et&#xa0;al., 2009</xref>, <xref ref-type="bibr" rid="B40">2010</xref>; <xref ref-type="bibr" rid="B10">Chowdary et&#xa0;al., 2011</xref>; <xref ref-type="bibr" rid="B23">Jing et&#xa0;al., 2011</xref>). For instance, during the strong El Ni&#xf1;o summer of 2015, pronounced anticyclonic wind anomalies occurred in the northwestern South China Sea. These anomalies strengthened wind-driven eastward residual currents in the strait (not shown), substantially offsetting the westward residual flow generated by tidal rectification. Consequently, the net residual flow in the strait weakened markedly, with westward residual velocities dropping to the lowest levels observed during the study period (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7</bold>
</xref>). Note that, prior studies (e.g., <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>; <xref ref-type="bibr" rid="B8">Chen et&#xa0;al., 2025</xref>) also highlighted that wind stress curl modulates residual flow intensity in the strait by altering the sea surface height gradient between its eastern and western ends. In summary, our SST-based inversion method for estimating residual flow in the Qiongzhou Strait is both physically sound and robust, yielding credible results.</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>Anomaly spatial patterns of summer wind field <bold>(a)</bold> and current field <bold>(b)</bold> in the northwestern South China Sea in 2004; <bold>(c-f)</bold> present the corresponding scenarios for 2010 and 2018, respectively.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-12-1621833-g008.tif"/>
</fig>
</sec>
<sec id="s6" sec-type="conclusions">
<label>6</label>
<title>Conclusions</title>
<p>The Qiongzhou Strait serves as the sole west-east conduit connecting the northern South China Sea shelf and the Beibu Gulf. During summer, westward water transport through the strait contributes approximately half of the Beibu Gulf&#x2019;s water renewal volume. This mass exchange plays a decisive role in shaping the summer cyclonic circulation within the Beibu Gulf (e.g., <xref ref-type="bibr" rid="B39">Wu et&#xa0;al., 2008</xref>; <xref ref-type="bibr" rid="B45">Zavala-Garay et&#xa0;al., 2022</xref>) while modulating key processes including thermal patterns, submarine geomorphology, sediment transport, nutrient fluxes, and ecological dynamics in both the strait and the gulf (e.g., <xref ref-type="bibr" rid="B29">Ni et&#xa0;al., 2014</xref>; <xref ref-type="bibr" rid="B4">Bai et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B24">Lao et&#xa0;al., 2022</xref>; <xref ref-type="bibr" rid="B18">Geng et&#xa0;al., 2024</xref>).</p>
<p>Nevertheless, current investigations into residual flow in the Qiongzhou Strait remain constrained to two conventional approaches: <italic>in-situ</italic> observational analysis and numerical ocean modeling. Both methodologies demand substantial human, material, and temporal investments, yet fail to provide long-term residual current datasets. These limitations impede a comprehensive understanding of strait dynamics and broader marine environmental processes in the northwestern South China Sea.</p>
<p>To address these challenges, this study pioneers an innovative algorithm that inversely calculates summer residual flow within the strait using satellite-derived SST data. The algorithm capitalizes on two critical factors: the unique east-west thermal gradient (cooler eastern vs. warmer western sectors) across the strait during summer, and the persistent westward residual flow regime. Principal findings are summarized as follows:</p>
<list list-type="order">
<list-item>
<p>The summer SST pattern in the Qiongzhou Strait can be effectively characterized using a one-dimensional thermal balance equation incorporating the temporal tendency term, horizontal advection term, horizontal diffusion term, and thermal forcing term.</p>
</list-item>
<list-item>
<p>A robust estimation of residual flow and flux in the summer Qiongzhou Strait during the two-decade period (2003&#x2013;2022) has been achieved through satellite-derived SST data, demonstrating the feasibility of remote sensing approaches for long-term hydrodynamic assessments.</p>
</list-item>
<list-item>
<p>Interannual variability in westward residual flow intensity was identified in the summer Qiongzhou Strait, modulated by large-scale air-sea interactions. Enhanced westward residual flow correlates with cyclonic wind anomalies over the northwestern South China Sea, whereas anticyclonic wind anomalies systematically suppress these currents.</p>
</list-item>
</list>
<p>It should be emphasized that the developed one-dimensional thermal balance equation for Qiongzhou Strait incorporates reasonable simplifications accounting for local bathymetry and summer dynamic/thermal conditions, particularly through the exclusion of vertical processes and meridional dynamic influences on SST evolution. Furthermore, our residual flux calculation assumes uniform cross-sectional distribution of the residual flow, despite documented spatial heterogeneity in both horizontal dimensions and vertical profiles (e.g., <xref ref-type="bibr" rid="B32">Shi et&#xa0;al., 2002</xref>; <xref ref-type="bibr" rid="B6">Chen et&#xa0;al., 2009</xref>; <xref ref-type="bibr" rid="B47">Zheng et&#xa0;al., 2024</xref>). While this methodological approach may introduce uncertainties in the current quantification, it does not fundamentally compromise the validity or practical utility of our inversion methodology for deriving residual flow from SST patterns. Future studies could adopt the methodological framework presented here to develop a vertically resolved two-dimensional thermal balance equation, thereby enhancing the precision of residual flow estimates.</p>
</sec>
</body>
<back>
<sec id="s7" sec-type="data-availability">
<title>Data availability statement</title>
<p>Publicly available datasets were analyzed in this study. The MODIS SST and Chl-a are acquired from NASA Ocean Color Web at <uri xlink:href="https://oceancolor.gsfc.nasa.gov/">https://oceancolor.gsfc.nasa.gov/</uri>; the CCMP wind vectors are available at Remote Sensing Systems following <uri xlink:href="https://www.remss.com/">https://www.remss.com/</uri>; the ERA5 reanalyzed air-sea heat fluxes are get from Copernicus Climate Data Store at <uri xlink:href="https://cds.climate.copernicus.eu/">https://cds.climate.copernicus.eu/</uri>; the GLORYS12V1 product are obtained from the Copernicus Marine Data Store at <uri xlink:href="https://data.marine.copernicus.eu/products">https://data.marine.copernicus.eu/products</uri>.</p>
</sec>
<sec id="s8" sec-type="author-contributions">
<title>Author contributions</title>
<p>JX: Conceptualization, Writing &#x2013; review &amp; editing, Funding acquisition, Methodology, Formal analysis, Writing &#x2013; original draft. PB: Visualization, Writing &#x2013; original draft, Funding acquisition, Formal analysis, Conceptualization, Methodology, Investigation, Writing &#x2013; review &amp; editing. XX: Formal analysis, Writing &#x2013; original draft. LX: Supervision, Writing &#x2013; review &amp; editing, Funding acquisition. ML: Data curation, Writing &#x2013; review &amp; editing, Formal analysis. YG: Investigation, Writing &#x2013; original draft, Formal analysis, Validation.</p>
</sec>
<sec id="s9" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare that financial support was received for the research and/or publication of this article. This study was jointly funded by the National Natural Science Foundation of China (Nos. 42106017, 42206004), the Zhejiang Provincial Natural Science Foundation of China (No. LMS25D060003), the Special Fund for Zhejiang Ocean University from Bureau of Science and Technology of Zhoushan (No. 2023C41006), and the Foundation of Guangdong Provincial Observation and Research Station for Tropical Ocean Environment in Western Coastal Waters (No. 2024B1212040008).</p>
</sec>
<sec id="s10" sec-type="COI-statement">
<title>Conflict of interest</title>
<p>The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.</p>
</sec>
<sec id="s11" sec-type="ai-statement">
<title>Generative AI statement</title>
<p>The author(s) declare that no Generative AI was used in the creation of this manuscript.</p>
</sec>
<sec id="s12" sec-type="disclaimer">
<title>Publisher&#x2019;s note</title>
<p>All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.</p>
</sec>
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