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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.2024.1463214</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>Propagation and dissipation of typhoon-induced surface waves along the Pearl River Estuary</article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname>Liang</surname>
<given-names>Mingen</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>
<uri xlink:href="https://loop.frontiersin.org/people/2788923"/>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-original-draft/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Zhu</surname>
<given-names>Suijie</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>
<role content-type="https://credit.niso.org/contributor-roles/conceptualization/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname>Qiu</surname>
<given-names>Heyong</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>
<role content-type="https://credit.niso.org/contributor-roles/data-curation/"/>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
<contrib contrib-type="author" corresp="yes">
<name>
<surname>Jia</surname>
<given-names>Liangwen</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="author-notes" rid="fn001">
<sup>*</sup>
</xref>
<role content-type="https://credit.niso.org/contributor-roles/writing-review-editing/"/>
</contrib>
</contrib-group>
<aff id="aff1">
<sup>1</sup>
<institution>School of Ocean Engineering and Technology, Sun Yat-Sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country>
</aff>
<aff id="aff2">
<sup>2</sup>
<institution>Southern Marine Science and Engineering, Guangdong Laboratory (Zhuhai)</institution>, <addr-line>Zhuhai</addr-line>, <country>China</country>
</aff>
<aff id="aff3">
<sup>3</sup>
<institution>Guangdong Province Engineering Research Center of Coasts, Islands and Reefs, Sun Yat-Sen University</institution>, <addr-line>Guangzhou</addr-line>, <country>China</country>
</aff>
<author-notes>
<fn fn-type="edited-by">
<p>Edited by: Yang Yang, Nanjing Normal University, China</p>
</fn>
<fn fn-type="edited-by">
<p>Reviewed by: Mei Xuefei, East China Normal University, China</p>
<p>Liqin Zuo, Nanjing Hydraulic Research Institute, China</p>
<p>Bo Hong, South China University of Technology, China</p>
</fn>
<fn fn-type="corresp" id="fn001">
<p>*Correspondence: Liangwen Jia, <email xlink:href="mailto:jialwen@126.com">jialwen@126.com</email>
</p>
</fn>
</author-notes>
<pub-date pub-type="epub">
<day>20</day>
<month>09</month>
<year>2024</year>
</pub-date>
<pub-date pub-type="collection">
<year>2024</year>
</pub-date>
<volume>11</volume>
<elocation-id>1463214</elocation-id>
<history>
<date date-type="received">
<day>11</day>
<month>07</month>
<year>2024</year>
</date>
<date date-type="accepted">
<day>19</day>
<month>08</month>
<year>2024</year>
</date>
</history>
<permissions>
<copyright-statement>Copyright &#xa9; 2024 Liang, Zhu, Qiu and Jia</copyright-statement>
<copyright-year>2024</copyright-year>
<copyright-holder>Liang, Zhu, Qiu and Jia</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>The propagation and dissipation of typhoon-induced surface waves are vital to morphological evolution and related engineering within coastal and estuarine regions. An observation system was operated during Typhoon Higos, and TELEMAC&#x2013;TOMAWAC numerical modeling was performed for Typhoons Hagupit, Hato, and Higos along the central coast of Guangdong and the Pearl River Estuary in China to explore variations in wave propagation and dissipation during typhoons. The results showed that wind waves were dominant before typhoon landfall, and the intense wind waves dissipated rapidly during typhoon decay, while they could stay longer within the estuarine regions. Landward wave propagation had a tendency to convert from being convergence-dominated to being dissipation-dominated with the morphological change and tended to converge at the mouth-bar region. Within the estuarine regions, waves dissipated more rapidly at the prismatic estuary than at the bell-shaped bays due to the limited width and rapid contraction of the outlet. Moreover, the track and scale of typhoons had critical effects on the generated wave field, and they dominated the intensity, propagation, and dissipation of the overall wave field. Specifically, typhoons with broader scales and longer moving tracks within the coastal regions of Guangdong Province enhanced the wind&#x2013;wave interaction and induced a stronger and wider wave field, despite that their typhoon intensities were comparable (i.e., Hagupit vs. Hato). Furthermore, waves generated by compact and regular cyclone structures dissipated more strongly along the moving track of typhoons (i.e., Hato and Higos). Except for typhoons directly attacking the Pearl River Estuary, waves within the estuarine regions tended to dissipate/converge when located on the right/left side of the moving track of typhoons.</p>
</abstract>
<kwd-group>
<kwd>Pearl River Estuary</kwd>
<kwd>typhoon track</kwd>
<kwd>typhoon intensity</kwd>
<kwd>wave propagation</kwd>
<kwd>wave dissipation</kwd>
</kwd-group>
<counts>
<fig-count count="12"/>
<table-count count="2"/>
<equation-count count="20"/>
<ref-count count="70"/>
<page-count count="18"/>
<word-count count="8936"/>
</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>Typhoon-induced surface waves are a critical factor affecting the morphological evolution of coastal and estuarine regions as well as related engineering. The impacts of typhoons on coastal areas are continuously intensifying in association with climate change (<xref ref-type="bibr" rid="B11">Emanuel, 1987</xref>; <xref ref-type="bibr" rid="B30">Knutson et&#xa0;al., 2010</xref>). Therefore, elucidating the propagation and dissipation of typhoon-induced surface waves within coastal and estuarine regions is essential.</p>
<p>The movement and strength of the typhoons vary significantly spatially and temporally in short time periods. Therefore, the composition and distribution of typhoon-induced waves exhibit spatial and temporal differences as well. Within the coastal regions, the wind wave component increased as typhoons approached (<xref ref-type="bibr" rid="B66">Xu et&#xa0;al., 2005</xref>). The maximum wave height mainly occurred on the right side of the typhoon track, whereas the maximum wind speed and wave height occurred with a time lag due to the wave propagation (<xref ref-type="bibr" rid="B46">Peng et&#xa0;al., 2023</xref>; <xref ref-type="bibr" rid="B64">Wu et&#xa0;al., 2023</xref>). As waves propagate landward, the complex morphological features at the coastal regions enhance the evolution of wave propagation. For example, <xref ref-type="bibr" rid="B68">Yin et&#xa0;al. (2019)</xref> showed that the storm wave heights reduced significantly when waves propagated through the shallow elongated ebb shoal at the outlets of Deben Estuary, UK. <xref ref-type="bibr" rid="B6">Cheng et&#xa0;al. (2015)</xref> declared that the waves penetrating the bay attenuated rapidly beyond the narrow mouth of Tillamook Bay, USA, while the inner part of the bay lacked wave action due to its far distance from the outer sea regions and limited fetch for wind wave generation.</p>
<p>Furthermore, the features of typhoon-induced wave fields within the estuarine regions are influenced by multiple factors. First, intense winds during typhoons are the driving force of the related wave fields. The wind field features, including local wind composition and the fetch scale for wind&#x2013;wave interaction, directly dominated the spatial distribution and temporal evolution of typhoon-induced waves (<xref ref-type="bibr" rid="B65">Xie et&#xa0;al., 2018</xref>). The regulation processes of wave propagation during typhoons vary from those under normal weather conditions. <xref ref-type="bibr" rid="B38">Manchia and Mulligan (2022)</xref> found that deep-water wave processes, including wind input, white capping, and quadruplet wave interactions, dominated the wave action balance, whereas shallow-water wave processes such as bottom friction were negligible in Onslow Bay and its adjacent shelf areas (10&#x2013;100-m depths) in the USA during Hurricanes Florence and Isaias. <xref ref-type="bibr" rid="B41">Mengual et&#xa0;al. (2022)</xref> found that the depth-limited wave breaking over the ebb shoal was enhanced under the storm condition, leading to a reduction of the shoreward wave height in the Tagus Estuary of Portugal. The interaction processes between the waves and other hydrodynamic processes also influence the wave features. <xref ref-type="bibr" rid="B36">Luo et&#xa0;al. (2021)</xref> discussed the interacting mechanism between storm surges and waves in the near-shore regions of the Pearl River Estuary, including the water level regulating the modulations in wave height, and the sharp depth decrease-induced wave breaking contributed to the wave setup. <xref ref-type="bibr" rid="B16">Gong et&#xa0;al. (2018)</xref> indicated that the interaction between the waves and landward flow reduced the significant wave height and postponed the peak wave height inside the Modaomen Estuary, China. Moreover, the external procedures, including the anthropogenic events and the global warming-induced sea level rise, have potential impacts on the typhoon-induced wave field. <xref ref-type="bibr" rid="B70">Zhang et&#xa0;al. (2023)</xref> simulated the impacts of the land reclamation conducted from 1990 to 2020 within the Pearl River Estuary on the maximum significant wave heights during typhoons; their results showed that the change rate induced by reclamation ranged from &#x2212;40% to 14% under the Typhoon Mangkhut scenario in different regions. <xref ref-type="bibr" rid="B69">Yin et&#xa0;al. (2017)</xref> discussed the influences of sea level rise on the typhoon-induced wave field, indicating that the increasing sea level reduced the wave dissipation due to the breaking locations of waves shifting shoreward in the Pearl River Estuary. Furthermore, <xref ref-type="bibr" rid="B12">Fairchild et&#xa0;al. (2021)</xref> explored the attenuation of wetlands to the local wave, and estuary-scale surge reduced 8% of flooding intensity near the wave-exposed estuary mouths along the coast of Wales, UK.</p>
<p>The wave fields varied when different typhoons attacked (<xref ref-type="bibr" rid="B45">Pan and Liu, 2015</xref>). The intensity of the typhoon-induced wave field had a positive correlation with the typhoon strength (<xref ref-type="bibr" rid="B37">Lyddon et&#xa0;al., 2019</xref>; <xref ref-type="bibr" rid="B70">Zhang et&#xa0;al., 2023</xref>), whereas the influences of typhoon path on the hydrodynamic processes were mainly concentrated on storm surges and saltwater intrusion. <xref ref-type="bibr" rid="B9">Du et&#xa0;al. (2020)</xref> explored the smaller angle between the typhoon tracks and coastline as well as the slower moving speed that induced higher storm surges in the Pearl River Estuary. <xref ref-type="bibr" rid="B17">Hashimura and Takikawa (2012)</xref> simplified 13 typhoon paths based on the previous typhoons and estimated the path that induced serious storm surges along the coastal regions located in the Kumamoto Prefecture, Japan. <xref ref-type="bibr" rid="B58">Wang et&#xa0;al. (2024)</xref> compared the simulated storm surges under three representative typhoon scenarios in the Yangtze River Estuary, China, and concluded that the occurring regions of maximum storm surges related to the typhoon path while the typhoon intensity was more critical to the storm surge rise. <xref ref-type="bibr" rid="B44">Pan et&#xa0;al. (2018)</xref> indicated that the typhoon landing on the west side of Modaomen Estuary induced strong landward salt flux transportation due to the northwestward wind, contributing to the rise of water level. Thus, the regulation of typhoon tracks and scale to the generated wave field as well as the dominant typhoon characteristic factors to wave intensity, propagation, and dissipation remains unclear.</p>
<p>Guangdong Province is located in southern China, with a long latitudinal coastline along the South China Sea (SCS). The Pearl River Estuary (PRE) forms the central part of the coastline, consisting of two bell-shaped bays and a prismatic-shaped estuary (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). From the offshore to the coast, the bathymetry of the sea and the configuration and morphology of the estuaries changed greatly, which affected the wave propagation and dissipation significantly. Studies on the propagation and dissipation of surface waves within this area have generally been conducted under normal weather conditions (<xref ref-type="bibr" rid="B59">Wang et&#xa0;al., 2006</xref>; <xref ref-type="bibr" rid="B61">Wei et&#xa0;al., 2020</xref>) or have focused on the influence of the wave&#x2013;current interaction (<xref ref-type="bibr" rid="B36">Luo et&#xa0;al., 2021</xref>), reclamation (<xref ref-type="bibr" rid="B70">Zhang et&#xa0;al., 2023</xref>), and sea level rise (<xref ref-type="bibr" rid="B69">Yin et&#xa0;al., 2017</xref>) on the wave field under typhoon conditions. Thus, typhoon-specific observations were conducted in the prismatic-shaped Modaomen Estuary during Typhoon Higos, and a numerical model covering the central coast of Guangdong and the PRE during Typhoons Hagupit, Hato, and Higos was constructed based on the TOMAWAC wave module in the TELEMAC&#x2013;MASCARET modeling system. The main objectives of the present study were to examine spatial and temporal variations in the propagation and dissipation of typhoon-induced surface waves within a large coastal region containing multiple estuaries and to analyze the impacts of different typhoon characteristic factors on the propagation and dissipation of typhoon-induced waves. Of the typhoons selected, Hagupit and Hato followed different tracks and had similar intensity, whereas Hato and Higos followed similar tracks and had different intensities (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>), allowing for comparative analyses of the effects of typhoons with various tracks, scales, and intensities on surface waves.</p>
<fig id="f1" position="float">
<label>Figure&#xa0;1</label>
<caption>
<p>Locations of the study area, observation stations, and typhoon tracks. <bold>(A)</bold> Coastal region of Guangdong Province. <bold>(B)</bold> Huangmaohai Bay. <bold>(C)</bold> Modaomen Estuary. <bold>(D)</bold> Lingding Bay.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g001.tif"/>
</fig>
</sec>
<sec id="s2">
<label>2</label>
<title>Study area</title>
<p>The Pearl River Delta consists of the Xijiang, Dongjiang, and Beijiang deltas and is connected to the SCS through eight estuaries (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). Four estuaries in the east enter the SCS through the bell-shaped Lingding Bay (LDY) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1D</bold>
</xref>), and two estuaries in the west enter the SCS through a smaller bay named Huangmaohai (HMH) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1B</bold>
</xref>), whereas the Modaomen (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>) and Jitimen Estuaries directly enter the sea. Based on a long-term wave station (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>) deployed in the outer part of Modaomen Estuary (ME) from September 2015 to July 2016 (no typhoon directly affected the study area during this period), the ranges of significant wave height, wave period, and wave direction were 0.12&#x2013;1.48 m, 1.30&#x2013;5.90 s, and 23.00&#xb0;&#x2013;360.00&#xb0; (clockwise from north), with mean values of 0.49 m, 2.32 s, and 205.10&#xb0;, respectively.</p>
<p>The SCS is a major site of tropical cyclone activity, with an average of 12 cyclones per year; of these, 54.52% have wind speeds greater than 33 m/s (<xref ref-type="bibr" rid="B33">Le et&#xa0;al., 2021</xref>). From 1949 to 2008, 5.7 typhoons made direct landfall in the PRE each year, making the PRE one of the main typhoon landing areas in the world (<xref ref-type="bibr" rid="B44">Pan et&#xa0;al., 2018</xref>). Thus, the central coast of Guangdong and the PRE are affected by typhoons with high frequency and intensity. Based on data recorded by the National Meteorological Centre of China, the maximum wind speeds and landing times of Typhoons Hagupit, Hato, and Higos were 50 m/s, 52 m/s, and 35 m/s on 06:45 September 24, 2008 (GMT+8), 12:50 August 23, 2017, and 06:00 August 19, 2020, respectively. The typhoon tracks are shown in <xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>, with Hagupit making landfall in Maoming, while Hato and Higos both landed in Zhuhai.</p>
</sec>
<sec id="s3">
<label>3</label>
<title>Data and methods</title>
<sec id="s3_1">
<label>3.1</label>
<title>Field observation</title>
<p>Field observations were conducted from 14:00 August 18, 2020, to 10:30 August 20, 2020, during Typhoon Higos. Two instrumented stations were deployed on the south (#1) and north (#2) sides of the mouth-bar region in the ME (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1C</bold>
</xref>). Acoustic wave and current (AWAC) measurements were taken to determine the significant wave height, wave period, and wave direction, with the sampling period and the number of observations per period set to 30 min and 1,024, respectively. The tidal effect from the observed data by the AWAC was removed by reducing the observed tide level at each sampling period based on <xref ref-type="bibr" rid="B15">Geng et&#xa0;al. (2014)</xref>. The cross-zero method was applied to calculate the significant wave heights and wave periods. In addition, hourly significant wave height and wave direction data recorded at a long-term buoy station (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>) were collected for analysis.</p>
</sec>
<sec id="s3_2">
<label>3.2</label>
<title>Wave composition analysis</title>
<p>The wave steepness is used to evaluate variations in wave conditions (<xref ref-type="bibr" rid="B52">Thompson and Reynolds, 1976</xref>). During wave propagation, the condition of the wave field can be described in terms of wave composition, including wind waves, swells, and immature swells. The wave steepness can be calculated as follows:</p>
<disp-formula id="eq1">
<label>(1)</label>
<mml:math display="block" id="M1">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>&#x3b4;</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>H</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mi>L</mml:mi>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>L</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>g</mml:mi>
<mml:msup>
<mml:mi>T</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
</mml:mrow>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mi>&#x3c0;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mi>tanh</mml:mi>
<mml:mi>k</mml:mi>
<mml:mi>h</mml:mi>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>&#x3b4;</italic> is the wave steepness, <inline-formula>
<mml:math display="inline" id="im1">
<mml:mrow>
<mml:msub>
<mml:mi>H</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the significant wave height, <italic>L</italic> is the wavelength calculated using the wave dispersion equation, <italic>T</italic> is the significant wave period, <italic>k</italic> is the wavenumber, and <italic>h</italic> is the water depth. According to <xref ref-type="bibr" rid="B51">Thompson et&#xa0;al. (1984)</xref>, <inline-formula>
<mml:math display="inline" id="im2">
<mml:mrow>
<mml:mi>&#x3b4;</mml:mi>
<mml:mo>&#x2265;</mml:mo>
<mml:mn>0.025</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> represents wind waves, <inline-formula>
<mml:math display="inline" id="im3">
<mml:mrow>
<mml:mi>&#x3b4;</mml:mi>
<mml:mo>&lt;</mml:mo>
<mml:mn>0.01</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> represents swell, and <inline-formula>
<mml:math display="inline" id="im4">
<mml:mrow>
<mml:mn>0.01</mml:mn>
<mml:mo>&#x2264;</mml:mo>
<mml:mi>&#x3b4;</mml:mi>
<mml:mo>&lt;</mml:mo>
<mml:mn>0.025</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> represents immature swell conditions.</p>
</sec>
<sec id="s3_3">
<label>3.3</label>
<title>Wave dissipation rate</title>
<p>When waves propagate into coastal and estuarine regions, depth limitation causes enhanced bottom friction, leading to the dissipation of the wave. Based on <xref ref-type="bibr" rid="B29">Kang and Di Iorio (2006)</xref>, the dissipation rate induced by bottom friction was calculated from the energy conservation equation of steady-state waves:</p>
<disp-formula id="eq2">
<label>(2)</label>
<mml:math display="block" id="M2">
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>F</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:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula id="eq3">
<label>(3)</label>
<mml:math display="block" id="M3">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>F</mml:mi>
<mml:mo>=</mml:mo>
<mml:mi>E</mml:mi>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>g</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>E</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>&#x3c1;</mml:mi>
<mml:mi>g</mml:mi>
<mml:msubsup>
<mml:mi>H</mml:mi>
<mml:mi>s</mml:mi>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mrow>
<mml:mn>16</mml:mn>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>g</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>L</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>sinh</mml:mi>
<mml:mn>2</mml:mn>
<mml:mi>k</mml:mi>
<mml:mi>h</mml:mi>
<mml:mo>+</mml:mo>
<mml:mn>2</mml:mn>
<mml:mi>k</mml:mi>
<mml:mi>h</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:mi>T</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi>sinh</mml:mi>
<mml:mn>2</mml:mn>
<mml:mi>k</mml:mi>
<mml:mi>h</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>F</italic> is the energy flux, <italic>E</italic> is the total wave energy, <inline-formula>
<mml:math display="inline" id="im5">
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mi>g</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the wave group velocity, and <inline-formula>
<mml:math display="inline" id="im6">
<mml:mi>x</mml:mi>
</mml:math>
</inline-formula> is along the direction of wave propagation. Although <xref ref-type="disp-formula" rid="eq2">Equations 2</xref> and <xref ref-type="disp-formula" rid="eq3">3</xref> neglect the contributions of other wave dissipation processes, these calculations include observed wave information and reflect the temporal variation of wave dissipation. Thus, integrating <xref ref-type="disp-formula" rid="eq2">Equation 2</xref> along the direction of wave propagation <italic>x</italic>,</p>
<disp-formula id="eq4">
<label>(4)</label>
<mml:math display="block" id="M4">
<mml:mrow>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mrow>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mrow>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:msubsup>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>F</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>x</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mi>d</mml:mi>
<mml:mi>x</mml:mi>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where &lt;&gt; represents the spatial mean, <italic>&#x3b8;</italic> is the angle between the wave propagation direction and the line connecting two observation stations, and <inline-formula>
<mml:math display="inline" id="im7">
<mml:mrow>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the distance between the two stations. <xref ref-type="disp-formula" rid="eq4">Equation 4</xref> can be rewritten as</p>
<disp-formula id="eq5">
<label>(5)</label>
<mml:math display="block" id="M5">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
<mml:mo>&#x2248;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>F</mml:mi>
<mml:mi>o</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>F</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>&#x3c1;</mml:mi>
<mml:mi>g</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>4</mml:mn>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:msubsup>
<mml:mi>H</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>o</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mn>4</mml:mn>
</mml:mfrac>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>g</mml:mi>
<mml:mi>o</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msubsup>
<mml:mi>H</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mn>4</mml:mn>
</mml:mfrac>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mrow>
<mml:mi>g</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where the subscripts <italic>o</italic> and <italic>i</italic> represent the outer and inner locations, respectively.</p>
<p>As for the observation station where wave period information was not collected, the component <italic>F</italic> in <xref ref-type="disp-formula" rid="eq5">Equation 5</xref> is replaced by <italic>E</italic> because the evolution of wave energy was directly associated with the variation of wave height under the major effect of wave transformation (<xref ref-type="bibr" rid="B48">Pruszak et&#xa0;al., 2008</xref>). Thus, the wave energy dissipation rate <inline-formula>
<mml:math display="inline" id="im8">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> was calculated as follows:</p>
<disp-formula id="eq6">
<label>(6)</label>
<mml:math display="block" id="M6">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>E</mml:mi>
<mml:mi>o</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>E</mml:mi>
<mml:mi>i</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mi>&#x3c1;</mml:mi>
<mml:mi>g</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mn>4</mml:mn>
<mml:msub>
<mml:mi>L</mml:mi>
<mml:mi>s</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b8;</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:msubsup>
<mml:mi>H</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>o</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mn>4</mml:mn>
</mml:mfrac>
<mml:mo>&#x2212;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msubsup>
<mml:mi>H</mml:mi>
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>i</mml:mi>
</mml:mrow>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
<mml:mn>4</mml:mn>
</mml:mfrac>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>Moreover, Normalized Dissipation Rate (<italic>NDR</italic>) is proposed to explore the relatively dominant variation of the wave dissipation and convergence processes between the analytical points and was calculated as follows:</p>
<disp-formula id="eq7">
<label>(7)</label>
<mml:math display="block" id="M7">
<mml:mrow>
<mml:mi>N</mml:mi>
<mml:mi>D</mml:mi>
<mml:mi>R</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mrow>
<mml:mo>|</mml:mo>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>+</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
<mml:mo>|</mml:mo>
</mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mrow>
<mml:mo>|</mml:mo>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>-</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
<mml:mo>|</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mrow>
<mml:mrow>
<mml:mo>|</mml:mo>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>+</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
<mml:mo>|</mml:mo>
</mml:mrow>
<mml:mo>+</mml:mo>
<mml:mrow>
<mml:mo>|</mml:mo>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>-</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
<mml:mo>|</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im9">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>+</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im10">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mrow>
<mml:mi>f</mml:mi>
<mml:mo>-</mml:mo>
</mml:mrow>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> are respectively the positive and negative temporal integration results of dissipation rate <inline-formula>
<mml:math display="inline" id="im11">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> at each profile. Therefore, <italic>NDR</italic> closer to 1 or &#x2212;1 means dissipation- or convergence-dominant, respectively.</p>
</sec>
<sec id="s3_4">
<label>3.4</label>
<title>Model description</title>
<p>Numerical simulations were performed using the TELEMAC&#x2013;MASCARET modeling system (<ext-link ext-link-type="uri" xlink:href="http://www.opentelemac.org">www.opentelemac.org</ext-link>), which was developed by the Laboratoire national d&#x2019;Hydraulique et Environnement (LNHE), a research department of &#xc9;lectricit&#xe9; de France (EDF). The TELEMAC system is an integrated modeling tool that includes free-surface hydrodynamics, sediment transport, water quality, and wave and groundwater flow modules in which simulation is conducted based on the finite element method, and the model domain is discretized in the form of an unstructured grid. This system is suitable for coastal and estuarine environments with irregular and complex geometries. In this study, we used the TELEMAC wave module TOMAWAC for simulation.</p>
<sec id="s3_4_1">
<label>3.4.1</label>
<title>Wave module</title>
<p>The TOMAWAC wave module uses the wave energy density direction spectrum function <italic>N</italic> to represent a random wave and simulates the wave field using the governing equation of propagation:</p>
<disp-formula id="eq8">
<label>(8)</label>
<mml:math display="block" id="M8">
<mml:mrow>
<mml:mi>N</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi mathvariant="bold-italic">x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">k</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mi>N</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>y</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula id="eq9">
<label>(9)</label>
<mml:math display="block" id="M9">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</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:mover accent="true">
<mml:mi>x</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</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:mover accent="true">
<mml:mi>y</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>y</mml:mi>
</mml:msub>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>y</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
<mml:mo>=</mml:mo>
<mml:mi>Q</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>y</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>N</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:mi mathvariant="bold-italic">V</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi>g</mml:mi>
<mml:mi>r</mml:mi>
<mml:mi>a</mml:mi>
<mml:msub>
<mml:mi>d</mml:mi>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>k</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mi>N</mml:mi>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mi>Q</mml:mi>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im12">
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> is the direction vector of the spatial location based on the Cartesian coordinate system, <inline-formula>
<mml:math display="inline" id="im13">
<mml:mrow>
<mml:mi>k</mml:mi>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>y</mml:mi>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>k</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi>sin</mml:mi>
<mml:mi>&#x3b7;</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>k</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3b7;</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> is the wavenumber vector after the discretization of the directional spectrum, <inline-formula>
<mml:math display="inline" id="im14">
<mml:mi>&#x3b7;</mml:mi>
</mml:math>
</inline-formula> is the direction of wave propagating, and <italic>t</italic> is simulation time. <italic>Q</italic> represents the source terms governing wave propagation and dissipation, including wind-driven (<xref ref-type="bibr" rid="B25">Janssen, 1989</xref>, <xref ref-type="bibr" rid="B26">1991</xref>; <xref ref-type="bibr" rid="B50">Snyder et&#xa0;al., 1981</xref>; <xref ref-type="bibr" rid="B67">Yan, 1987</xref>) and white-capping dissipation (<xref ref-type="bibr" rid="B5">Cavaleri et&#xa0;al., 2007</xref>; <xref ref-type="bibr" rid="B26">Janssen, 1991</xref>; <xref ref-type="bibr" rid="B31">Komen et&#xa0;al., 1984</xref>; <xref ref-type="bibr" rid="B56">van der Westhuysen et&#xa0;al., 2007</xref>), bottom friction dissipation (<xref ref-type="bibr" rid="B3">Bouws and Komen, 1983</xref>; <xref ref-type="bibr" rid="B20">Hasselmann et&#xa0;al., 1973</xref>), depth-induced breaking dissipation (<xref ref-type="bibr" rid="B1">Battjes and Janssen, 1978</xref>; <xref ref-type="bibr" rid="B24">Izumiya and Horikawa, 1984</xref>; <xref ref-type="bibr" rid="B49">Roelvink, 1993</xref>; <xref ref-type="bibr" rid="B53">Thornton and Guza, 1983</xref>), non-linear transfers between frequencies (<xref ref-type="bibr" rid="B14">Gagnaire-Renou et&#xa0;al., 2010</xref>; <xref ref-type="bibr" rid="B18">Hasselmann, 1962</xref>, <xref ref-type="bibr" rid="B19">1963</xref>; <xref ref-type="bibr" rid="B21">Hasselmann and Hasselmann, 1985a</xref>; <xref ref-type="bibr" rid="B22">Hasselmann et&#xa0;al., 1985b</xref>; <xref ref-type="bibr" rid="B32">Lavrenov, 2001</xref>; <xref ref-type="bibr" rid="B55">Tolman, 2004</xref>), triad interaction (<xref ref-type="bibr" rid="B2">Becq, 1998</xref>; <xref ref-type="bibr" rid="B10">Eldeberky and Battjes, 1995</xref>), and wave blocking (<xref ref-type="bibr" rid="B23">Hedges et&#xa0;al., 1985</xref>; <xref ref-type="bibr" rid="B57">van der Westhuysen, 2012</xref>). <inline-formula>
<mml:math display="inline" id="im15">
<mml:mrow>
<mml:mover accent="true">
<mml:mi>x</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mo>,</mml:mo>
<mml:mover accent="true">
<mml:mi>y</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>,</mml:mo>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>y</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are related to the conditions of waves and currents, as follows:</p>
<disp-formula id="eq10">
<label>(10)</label>
<mml:math display="block" id="M10">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mo>&#x3a9;</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi mathvariant="bold-italic">k</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi mathvariant="bold-italic">x</mml:mi>
<mml:mo>,</mml:mo>
<mml:mi>t</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mi>&#x3c3;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi mathvariant="bold-italic">k</mml:mi>
<mml:mo>&#xb7;</mml:mo>
<mml:mi mathvariant="bold-italic">U</mml:mi>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mover accent="true">
<mml:mi>x</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mo>&#x3a9;</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>x</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mover accent="true">
<mml:mi>y</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mo>&#x3a9;</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:msub>
<mml:mi>k</mml:mi>
<mml:mi>y</mml:mi>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>x</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mo>&#x3a9;</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>x</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mover accent="true">
<mml:mi>k</mml:mi>
<mml:mo>&#x2d9;</mml:mo>
</mml:mover>
<mml:mi>y</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mo>&#x2212;</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mo>&#x3a9;</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2202;</mml:mo>
<mml:mi>y</mml:mi>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <bold>
<italic>U</italic>
</bold> is the current vector and <italic>&#x3c3;</italic> is the natural or relative angular frequency.</p>
</sec>
<sec id="s3_4_2">
<label>3.4.2</label>
<title>Typhoon model</title>
<p>An appropriate model that can reproduce the wind and barometric pressure fields of a typhoon is vital to the numerical simulation of typhoon conditions. The barometric pressure was calculated using the Jelesnianski model (<xref ref-type="bibr" rid="B27">Jelesnianski, 1965</xref>):</p>
<disp-formula id="eq11">
<label>(11)</label>
<mml:math display="block" id="M11">
<mml:mrow>
<mml:mi>P</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mi>r</mml:mi>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:mn>1</mml:mn>
<mml:mn>4</mml:mn>
</mml:mfrac>
<mml:mo>&#x394;</mml:mo>
<mml:mi>P</mml:mi>
<mml:msup>
<mml:mrow>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mfrac>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mn>3</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mtd>
<mml:mtd>
<mml:mrow>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mo>&#x2264;</mml:mo>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>&#x221e;</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mfrac>
<mml:mn>3</mml:mn>
<mml:mn>4</mml:mn>
</mml:mfrac>
<mml:mo>&#x394;</mml:mo>
<mml:mi>P</mml:mi>
<mml:msup>
<mml:mrow>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mfrac>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mrow>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
</mml:msup>
</mml:mrow>
</mml:mtd>
<mml:mtd>
<mml:mrow>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mo>&gt;</mml:mo>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <italic>r</italic> is the distance from the simulation point to the typhoon center. <inline-formula>
<mml:math display="inline" id="im16">
<mml:mrow>
<mml:mo>&#x394;</mml:mo>
<mml:mi>P</mml:mi>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>&#x221e;</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula>, where <inline-formula>
<mml:math display="inline" id="im17">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>&#x221e;</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the standard barometric pressure of 1,010.30 hPa, <inline-formula>
<mml:math display="inline" id="im18">
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the barometric pressure at the typhoon center, and <inline-formula>
<mml:math display="inline" id="im19">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the maximum radius of the typhoon, calculated as follows (<xref ref-type="bibr" rid="B43">Ou et&#xa0;al., 2002</xref>):</p>
<disp-formula id="eq12">
<label>(12)</label>
<mml:math display="block" id="M12">
<mml:mrow>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mn>28.52</mml:mn>
<mml:mi>tanh</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">[</mml:mo>
<mml:mrow>
<mml:mn>0.0873</mml:mn>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mi>&#x3d5;</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mn>28</mml:mn>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
<mml:mo stretchy="false">]</mml:mo>
</mml:mrow>
<mml:mo>+</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mn>12.22</mml:mn>
</mml:mrow>
<mml:mrow>
<mml:mi>exp</mml:mi>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
<mml:mfrac>
<mml:mrow>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mi>&#x221e;</mml:mi>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:msub>
<mml:mi>P</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:mn>33.86</mml:mn>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
<mml:mo>)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mfrac>
<mml:mo>+</mml:mo>
<mml:mn>0.2</mml:mn>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mn>37.22</mml:mn>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im20">
<mml:mi>&#x3d5;</mml:mi>
</mml:math>
</inline-formula> (&#xb0;) and <inline-formula>
<mml:math display="inline" id="im21">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> (m/s) are the latitude and moving speed of the typhoon center, respectively.</p>
<p>The empirical wind field was calculated based on the Jelesnianski model (<xref ref-type="bibr" rid="B28">Jelesnianski, 1966</xref>):</p>
<disp-formula id="eq13">
<label>(13)</label>
<mml:math display="block" id="M13">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>m</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>c</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mfrac>
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
<mml:mrow>
<mml:msup>
<mml:mi>r</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula id="eq14">
<label>(14)</label>
<mml:math display="block" id="M14">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mn>2</mml:mn>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
<mml:mi>r</mml:mi>
</mml:mrow>
<mml:mrow>
<mml:msup>
<mml:mi>r</mml:mi>
<mml:mn>2</mml:mn>
</mml:msup>
<mml:mo>+</mml:mo>
<mml:msubsup>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
<mml:mn>2</mml:mn>
</mml:msubsup>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im22">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>m</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im23">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are the moving and rotating wind components, respectively. The total empirical wind speed composed of <inline-formula>
<mml:math display="inline" id="im24">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>m</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im25">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is transformed into X and Y directions based on the Cartesian coordinate system (<xref ref-type="bibr" rid="B47">Powell et&#xa0;al., 2003</xref>; <xref ref-type="bibr" rid="B54">Tian and Zhang, 2021</xref>; <xref ref-type="bibr" rid="B63">Willoughby, 1990</xref>), as follows:</p>
<disp-formula id="eq15">
<label>(15)</label>
<mml:math display="block" id="M15">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>m</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mi>&#x3d5;</mml:mi>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
<mml:mi>cos</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mn>90</mml:mn>
<mml:mo>+</mml:mo>
<mml:mi>&#x3d5;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>&#x3b2;</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>m</mml:mi>
</mml:msub>
<mml:mi>sin</mml:mi>
<mml:mi>&#x3d5;</mml:mi>
<mml:mo>+</mml:mo>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mi>r</mml:mi>
</mml:msub>
<mml:mi>sin</mml:mi>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mn>90</mml:mn>
<mml:mo>+</mml:mo>
<mml:mi>&#x3d5;</mml:mi>
<mml:mo>+</mml:mo>
<mml:mi>&#x3b2;</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im26">
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>1</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mn>1.00</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> is a factor for converting wind speed to the value at 10-m height, <inline-formula>
<mml:math display="inline" id="im27">
<mml:mrow>
<mml:msub>
<mml:mi>c</mml:mi>
<mml:mn>2</mml:mn>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mn>0.80</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula> is a factor for converting the speed at 10-m height to the top boundary layer of the atmosphere, and <inline-formula>
<mml:math display="inline" id="im28">
<mml:mrow>
<mml:mi>&#x3b2;</mml:mi>
<mml:mo>=</mml:mo>
<mml:msup>
<mml:mrow>
<mml:mn>20</mml:mn>
</mml:mrow>
<mml:mtext>o</mml:mtext>
</mml:msup>
</mml:mrow>
</mml:math>
</inline-formula> is the angle of incidence based on the same positive axis as the Cartesian coordinate system and calculated counterclockwise.</p>
<p>Generally, empirical calculation of the typhoon wind field leads to underestimation of the wind speed around the typhoon structure, whereas the wind field obtained from the reanalysis dataset underestimates the central wind speed of the typhoon. Thus, a mixing calculation was performed to remodel the typhoon wind field (<xref ref-type="bibr" rid="B4">Carr and Elsberry, 1996</xref>):</p>
<disp-formula id="eq16">
<label>(16)</label>
<mml:math display="block" id="M16">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>&#x3bb;</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mi>&#x3bb;</mml:mi>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mo>-</mml:mo>
<mml:mi>N</mml:mi>
<mml:mi>C</mml:mi>
<mml:mi>E</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>m</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>=</mml:mo>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>&#x3bb;</mml:mi>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>&#x2212;</mml:mo>
<mml:mi>c</mml:mi>
<mml:mi>a</mml:mi>
<mml:mi>l</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>+</mml:mo>
<mml:mi>&#x3bb;</mml:mi>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>-</mml:mo>
<mml:mi>N</mml:mi>
<mml:mi>C</mml:mi>
<mml:mi>E</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<disp-formula id="eq17">
<label>(17)</label>
<mml:math display="block" id="M17">
<mml:mrow>
<mml:mrow>
<mml:mo>{</mml:mo>
<mml:mrow>
<mml:mtable>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>&#x3bb;</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:msup>
<mml:mi>C</mml:mi>
<mml:mn>4</mml:mn>
</mml:msup>
</mml:mrow>
<mml:mrow>
<mml:mn>1</mml:mn>
<mml:mo>+</mml:mo>
<mml:msup>
<mml:mi>C</mml:mi>
<mml:mn>4</mml:mn>
</mml:msup>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
<mml:mtr>
<mml:mtd>
<mml:mrow>
<mml:mi>C</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mi>r</mml:mi>
<mml:mrow>
<mml:mi>n</mml:mi>
<mml:msub>
<mml:mi>R</mml:mi>
<mml:mn>0</mml:mn>
</mml:msub>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:mtd>
</mml:mtr>
</mml:mtable>
</mml:mrow>
</mml:mrow>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im29">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>X</mml:mi>
<mml:mo>-</mml:mo>
<mml:mi>N</mml:mi>
<mml:mi>C</mml:mi>
<mml:mi>E</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im30">
<mml:mrow>
<mml:msub>
<mml:mi>V</mml:mi>
<mml:mrow>
<mml:mi>Y</mml:mi>
<mml:mo>-</mml:mo>
<mml:mi>N</mml:mi>
<mml:mi>C</mml:mi>
<mml:mi>E</mml:mi>
<mml:mi>P</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are wind speeds obtained from The National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR), <italic>&#x3bb;</italic> is a weighting factor, and <italic>n</italic> is a correction factor to minimize error (n = 6, 9, and 9 for Typhoons Hagupit, Hato, and Higos, respectively).</p>
</sec>
<sec id="s3_4_3">
<label>3.4.3</label>
<title>Model setup</title>
<p>The model grid and computational domain are presented in <xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>. The unstructured grid had spatial resolution ranging from 5,000 m in the offshore region to 50 m in the upper river area. The computational domain encompassed 85% of the coastline of Guangdong Province, with upper boundaries at the upstream rivers and an open boundary extending 200 km from the ME. Based on the observed seasonal wave characteristics (<xref ref-type="bibr" rid="B35">Lu et&#xa0;al., 2020</xref>), the input wave parameters at the open boundary were set as fixed values (southwesterly wave with <italic>H<sub>s</sub>
</italic> = 1.0 m, <italic>T</italic> = 5 s).</p>
<fig id="f2" position="float">
<label>Figure&#xa0;2</label>
<caption>
<p>Computational grid and analytical profiles.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g002.tif"/>
</fig>
<p>The computed time step was 60 s, and the total computation period was 8 days, from 4 days before landfall to 3 days after landfall. The computational setup ensured the stability and applicability of the model.</p>
</sec>
<sec id="s3_4_4">
<label>3.4.4</label>
<title>Model validation</title>
<p>Three parameters were used to evaluate the model performance. The first is the correlation coefficient (<italic>r</italic>) between the modeled and observed data, which measures the linear relationship between the two values. The second is the root mean square error (<italic>RMSE</italic>), which can evaluate the relative error between the modeled and observed values. The third is the model skill score (<italic>ss</italic>), which is a dimensionless value obtained after the standard deviation normalization of the modeled values (<xref ref-type="bibr" rid="B39">Matte et&#xa0;al., 2017</xref>; <xref ref-type="bibr" rid="B62">Willmott et&#xa0;al., 1985</xref>). These parameters were calculated as follows:</p>
<disp-formula id="eq18">
<label>(18)</label>
<mml:math display="block" id="M18">
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mo>=</mml:mo>
<mml:mfrac>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:munderover>
<mml:mrow>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>b</mml:mi>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>b</mml:mi>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
<mml:mo stretchy="false">)</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
<mml:mrow>
<mml:msqrt>
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
<mml:mrow>
<mml:mi>i</mml:mi>
<mml:mo>=</mml:mo>
<mml:mn>1</mml:mn>
</mml:mrow>
<mml:mrow>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:munderover>
<mml:mrow>
<mml:msup>
<mml:mrow>
<mml:mrow>
<mml:mo stretchy="false">(</mml:mo>
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
<mml:mo>&#x2212;</mml:mo>
<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
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</mml:mrow>
</mml:math>
</disp-formula>
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<label>(19)</label>
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<label>(20)</label>
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<mml:munderover>
<mml:mo>&#x2211;</mml:mo>
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</mml:munderover>
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<mml:mrow>
<mml:mrow>
<mml:mo>(</mml:mo>
<mml:mrow>
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<mml:mo>|</mml:mo>
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<mml:mover accent="true">
<mml:mrow>
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<mml:mi>X</mml:mi>
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<mml:mi>b</mml:mi>
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</mml:msub>
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<mml:mo>&#xaf;</mml:mo>
</mml:mover>
</mml:mrow>
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</mml:mrow>
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<mml:mrow>
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<mml:mi>b</mml:mi>
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</mml:mrow>
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<mml:mover accent="true">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>b</mml:mi>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
<mml:mo>&#xaf;</mml:mo>
</mml:mover>
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</mml:mrow>
</mml:mrow>
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</mml:mrow>
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</mml:msup>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:mfrac>
</mml:mrow>
</mml:math>
</disp-formula>
<p>where <inline-formula>
<mml:math display="inline" id="im31">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>m</mml:mi>
<mml:mi>o</mml:mi>
<mml:mi>d</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> and <inline-formula>
<mml:math display="inline" id="im32">
<mml:mrow>
<mml:msub>
<mml:mi>X</mml:mi>
<mml:mrow>
<mml:mi>o</mml:mi>
<mml:mi>b</mml:mi>
<mml:mi>s</mml:mi>
</mml:mrow>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> are the modeled and observed values, respectively, and <inline-formula>
<mml:math display="inline" id="im33">
<mml:mrow>
<mml:msub>
<mml:mi>n</mml:mi>
<mml:mi>n</mml:mi>
</mml:msub>
</mml:mrow>
</mml:math>
</inline-formula> is the number of data used for validation. Better simulation results are indicated by <inline-formula>
<mml:math display="inline" id="im34">
<mml:mrow>
<mml:mrow>
<mml:mo>|</mml:mo>
<mml:mi>r</mml:mi>
<mml:mo>|</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:math>
</inline-formula> and <italic>ss</italic> values closer to 1 and lower <italic>RMSE</italic> values.</p>
<p>Validated data for the wind field at Hong Kong and Macau stations were collected from the National Centers for Environmental Information (NCEI) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The validation results and temporal comparisons are shown in <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3A&#x2013;L</bold>
</xref>. Generally, the wind speed simulation results were satisfactory, with <inline-formula>
<mml:math display="inline" id="im35">
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mo>&gt;</mml:mo>
<mml:mn>0.80</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math display="inline" id="im36">
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>s</mml:mi>
<mml:mo>&gt;</mml:mo>
<mml:mn>0.89</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula>, and <italic>RMSE</italic> ranging from 1.80 to 3.20 m/s. The wind direction was in accordance with the general trend of observations. Thus, the selected typhoon model is applicable.</p>
<fig id="f3" position="float">
<label>Figure&#xa0;3</label>
<caption>
<p>Comparison of simulated and observed wind speed <bold>(A&#x2013;F)</bold>, wind direction <bold>(G&#x2013;L)</bold>, and wave height <bold>(M&#x2013;Q)</bold>.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g003.tif"/>
</fig>
<p>The wave field data were validated based on the observations collected during the selected typhoons (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). The resulting validation parameters and temporal comparisons are shown in <xref ref-type="fig" rid="f3">
<bold>Figures&#xa0;3M&#x2013;Q</bold>
</xref>. The simulation results for wave height were acceptable, with <inline-formula>
<mml:math display="inline" id="im37">
<mml:mrow>
<mml:mi>r</mml:mi>
<mml:mo>&gt;</mml:mo>
<mml:mn>0.80</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula>, <inline-formula>
<mml:math display="inline" id="im38">
<mml:mrow>
<mml:mi>s</mml:mi>
<mml:mi>s</mml:mi>
<mml:mo>&gt;</mml:mo>
<mml:mn>0.83</mml:mn>
</mml:mrow>
</mml:math>
</inline-formula>, and <italic>RMSE</italic> ranging from 0.43 to 0.60 m. Thus, the model was appropriate for the analysis of wave propagation and dissipation during typhoons.</p>
</sec>
</sec>
</sec>
<sec id="s4">
<label>4</label>
<title>Observation results for Typhoon Higos</title>
<sec id="s4_1">
<label>4.1</label>
<title>Characteristics of the observed waves</title>
<p>Wave heights at all stations increased significantly during the typhoon, showing patterns similar to wind speed, but with differing peak times (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4A, B</bold>
</xref>). Wave height increased sharply as the typhoon approached, reaching maxima of 4.80 m, 3.98 m, and 3.69 m on August 19, 2020, at 00:00, 04:00, and 05:30 at the buoy station, station #1, and station #2, respectively. Wind speed reached maxima of 26.60 m/s and 27.30 m/s on August 19 at 02:00 and 06:00 at the buoy and Macau stations, respectively. Thus, wave height peaked before wind speed. The time of peak wave height was 2 h earlier than the time of peak wind speed at the buoy station. At stations #1 and #2, the peak wave height occurred 2 h and 0.5 h earlier, respectively, than the time of maximum wind speed at the Macau meteorological station within the ME.</p>
<fig id="f4" position="float">
<label>Figure&#xa0;4</label>
<caption>
<p>Time series of observation results during Typhoon Higos. <bold>(A)</bold> Significant wave height, <bold>(B)</bold> Wind speed, <bold>(C)</bold> Wave direction, <bold>(D)</bold> Wind direction, <bold>(E)</bold> Significant wave period.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g004.tif"/>
</fig>
<p>The wave and wind directions corresponded to the typhoon cyclone structure, and their fluctuations increased landward (<xref ref-type="fig" rid="f4">
<bold>Figures&#xa0;4C, D</bold>
</xref>). The wave direction captured at station #2 fluctuated strongly due to mouth-bar disturbance driven by the presence of an obstacle at the entry of the estuary. In contrast, the data captured at the buoy station and station #1 were relatively stable. However, the wave direction shifted significantly when the wind speed increased rapidly from 16.3 m/s and 14.4 m/s to its maximum at the buoy station and Macau station, respectively. Specifically, the wind and wave directions both shifted from northeastern to northwestern at the buoy station, while the wave direction shifted from southeastern to southern at station #1 with the wind direction transitioning from northeastern to southern at Macau station. The transition trend indicated that the directions of wind and wave vectors were comparable in this period due to the enhancement of wind force. With the typhoon decaying, the wind directions at both stations gradually transitioned to the east in the counterclockwise direction. The wave direction presented another shift from northwestern back to northeastern on August 19 at 15:00 at the buoy station, while the wave vectors remained in the south at station #1. Thus, the forcing intensity of wind to wave changes with typhoon movement; the significant transition of wind and wave directions aligned with the approach of typhoon cyclone structure. Moreover, the recovery period of wave direction was longer at the outlet of ME than in the open sea.</p>
<p>The temporal variation in the wave period had no apparent regularity but showed similar trends at stations #1 and #2 (<xref ref-type="fig" rid="f4">
<bold>Figure&#xa0;4E</bold>
</xref>). The average wave periods were 5.19 s and 3.96 s at stations #1 and #2, respectively, indicating a landward attenuation of the wave period. The wave period at stations #1 and #2 shortened during the peak wave height, which could be caused by the strong wave current interaction due to the current having a regulated effect on the wave period during typhoons (<xref ref-type="bibr" rid="B7">Cui et&#xa0;al., 2012</xref>).</p>
</sec>
<sec id="s4_2">
<label>4.2</label>
<title>Variation in wave composition</title>
<p>Wind waves were the dominant component of waves while the typhoon approached at both stations (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5A</bold>
</xref>). The wave steepness sharply increased from 0.043 and 0.041 to 0.171 and 0.187 at stations #1 and #2, respectively, indicating enhanced instability of wave structure and the wind waves composing the wave field in the mouth-bar region of ME under the intense typhoon wind force. After the typhoon landfall, the wave composition remained wind wave-dominant at station #2, while the composition gradually transitioned to immature swell dominance at station #1. With the wind force continuously decaying, the wave steepness showed a declining trend, reducing to 0.019 and 0.066 on August 19 at 12:30 (i.e., 6.5 h after typhoon landfall) at stations #1 and #2, respectively. Subsequently, the wave steepness at station #1 remained below 0.025, while the value at station #2 stayed above 0.025. The decreased in wave steepness indicated a rapid decay of the intense wind wave component and the reappearance of the swell component in the coastal regions. Moreover, the spatial variation of wave composition pointed out that the wind waves persisted longer within the mouth-bar region compared to its outer area.</p>
<fig id="f5" position="float">
<label>Figure&#xa0;5</label>
<caption>
<p>Time series of <bold>(A)</bold> wave steepness and <bold>(B)</bold> wave dissipation rate during Typhoon Higos. Gray dotted lines represent the time when the wave heights reached the peak at buoy station and stations #1 and #2.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g005.tif"/>
</fig>
</sec>
<sec id="s4_3">
<label>4.3</label>
<title>Variation in wave dissipation and convergence</title>
<p>The intensity of wave dissipation and convergence increased as the typhoon approached (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). The absolute value of the dissipation rate from the buoy station to station #1 increased from August 18 at 15:00 to August 19 at 01:00, with wave height reaching its maximum on August 19 at 00:00 at the buoy station. The absolute value of the dissipation rate from station #1 to station #2 increased from August 19 at 00:00 to August 19 at 14:30, with wave height reaching the maxima on August 19 at 04:00 and 05:00 at stations #1 and #2, respectively. Thus, the dissipation rate increased with the intensification of the wave field, which resulted from the approach of a typhoon.</p>
<p>Wave propagation from the buoy station to station #1 was dominated by the dissipation process (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). The wave energy dissipation rate <inline-formula>
<mml:math display="inline" id="im39">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> reached its maxima of 4.40 J/m<sup>3</sup> when the wave height was the highest at the buoy station. The temporal integration of the wave energy dissipation rate <inline-formula>
<mml:math display="inline" id="im40">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> was 7.17 J&#xb7;h/m<sup>3</sup>, indicating that the positive component was much larger than the negative component (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Thus, wave dissipation dominated the wave propagation from the open sea to the outer region of the mouth bar in ME.</p>
<table-wrap id="T1" position="float">
<label>Table&#xa0;1</label>
<caption>
<p>Temporal integration of wave dissipation rate between observation stations.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="top" rowspan="2" align="center">Propagation path</th>
<th valign="top" colspan="3" align="center">
<inline-formula>
<mml:math display="inline" id="im41">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> (W&#xb7;h/m<sup>2</sup>)</th>
<th valign="top" colspan="3" align="center">
<inline-formula>
<mml:math display="inline" id="im42">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> (J&#xb7;h/m<sup>3</sup>)</th>
</tr>
<tr>
<th valign="top" align="center">+</th>
<th valign="top" align="center">&#x2212;</th>
<th valign="top" align="center">Total</th>
<th valign="top" align="center">+</th>
<th valign="top" align="center">&#x2212;</th>
<th valign="top" align="center">Total</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="top" align="left">Buoy to #1</td>
<td valign="top" align="left">\</td>
<td valign="top" align="left">\</td>
<td valign="top" align="left">\</td>
<td valign="top" align="left">7.93</td>
<td valign="top" align="left">&#x2212;0.76</td>
<td valign="top" align="left">7.17</td>
</tr>
<tr>
<td valign="top" align="left">#1 to #2</td>
<td valign="top" align="left">29.76</td>
<td valign="top" align="left">&#x2212;56.84</td>
<td valign="top" align="left">&#x2212;27.08</td>
<td valign="top" align="left">3.52</td>
<td valign="top" align="left">&#x2212;16.50</td>
<td valign="top" align="left">&#x2212;12.99</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>The value &gt;0 indicates wave dissipation, and &lt;0 indicates wave convergence.</p>
</fn>
</table-wrap-foot>
</table-wrap>
<p>Wave propagation from station #1 to #2 was alternately dominated by the processes of dissipation and convergence (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>). When the wave height at station #1 reached its maximum, wave dissipation dominated the wave propagation with a dissipation rate <inline-formula>
<mml:math display="inline" id="im43">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> of 7.64 W/m<sup>2</sup>. When the wave height at station #2 reached its maximum, wave convergence dominated the wave propagation, and the dissipation rate <inline-formula>
<mml:math display="inline" id="im44">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> was &#x2212;4.79 W/m<sup>2</sup>. After the typhoon landfall, the fluctuations of&#xa0;dissipation rate gradually weakened and remained in negative&#xa0;values as the typhoon decayed. The temporal integrals of the wave dissipation rates <inline-formula>
<mml:math display="inline" id="im45">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> and wave energy dissipation rates <inline-formula>
<mml:math display="inline" id="im46">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> were &#x2212;27.08 W&#xb7;h/m<sup>2</sup> and &#x2212;12.99 J&#xb7;h/m<sup>3</sup>, respectively, demonstrating that the negative components were greater than the positive components (<xref ref-type="table" rid="T1">
<bold>Table&#xa0;1</bold>
</xref>). Thus, wave propagation within the mouth-bar region was dominated by wave convergence, and enhancement of both wave dissipation and convergence occurred during typhoons.</p>
</sec>
</sec>
<sec id="s5">
<label>5</label>
<title>Numerical simulation results</title>
<sec id="s5_1">
<label>5.1</label>
<title>Wind field</title>
<p>Simulated wind fields during Typhoon Hagupit are shown in <xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6A&#x2013;H</bold>
</xref>. The wind field before the typhoon landfall contained two regions of high wind speed, which coincided with the movement of the typhoon center. The maximum spatial area with wind speeds &gt;20 m/s occurred on September 24, 2008, at 03:00 (3.75 h before typhoon landfall), covering the coastal areas from Jiangmen to Huizhou, and wind speed gradually decreased from west to east. Wind direction corresponded to the typhoon cyclone structure before landfall, while the study area was dominated by onshore wind after landfall.</p>
<fig id="f6" position="float">
<label>Figure&#xa0;6</label>
<caption>
<p>
<bold>(A&#x2013;H)</bold> Simulated wind field and <bold>(I&#x2013;P)</bold> simulated wave field at 2-h intervals during Typhoon Hagupit. Vectors represent wind direction. Panels <bold>(E, M)</bold> represent the results closest to the landing time. Blue stars indicate the location of the typhoon center; lines between a pair of stars indicate transition of the typhoon between those points.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g006.tif"/>
</fig>
<p>Simulated wind fields during Typhoon Hato are shown in <xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7A&#x2013;H</bold>
</xref>. The wind fields contained one region of high wind speed, which was located near the typhoon center and rotated counterclockwise. The maximum spatial area with wind speeds over 20 m/s occurred on August 23, 2017, at 09:00 (3.83 h before typhoon landfall), covering the coastal regions from Zhuhai to Shenzhen, with wind speed gradually decreasing from the typhoon center to the outer bands. Wind direction corresponded to the typhoon cyclone structure prior to landfall, whereas the western part of the study area was dominated by offshore and longshore winds, while the eastern part of the study area was dominated by onshore wind after landfall.</p>
<fig id="f7" position="float">
<label>Figure&#xa0;7</label>
<caption>
<p>
<bold>(A&#x2013;H)</bold> Simulated wind field and <bold>(I&#x2013;P)</bold> simulated wave field at 2-h intervals during Typhoon Hato. Vectors represent wind direction. Panels <bold>(E, M)</bold> represent the results closest to the landing time. Blue stars indicate the location of the typhoon center, and the orange lines indicate the typhoon tracks.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g007.tif"/>
</fig>
<p>Simulated wind fields during Typhoon Higos are shown in <xref ref-type="fig" rid="f8">
<bold>Figures&#xa0;8A&#x2013;H</bold>
</xref>. Their characteristics were similar to those during Typhoon Hato due to their similar tracks and landing locations. However, the maximum value of wind speed and the scale of typhoon cyclone structures were smaller than those during Hato due to the weaker intensity of Higos. Specifically, the maximum spatial area of the region with wind speeds over 20 m/s occurred on August 19, 2020, at 02:00 (4 h before typhoon landfall), covering the coastal region from Zhuhai to Hong Kong and with wind speed gradually decreasing from the typhoon center to the outer bands.</p>
<fig id="f8" position="float">
<label>Figure&#xa0;8</label>
<caption>
<p>
<bold>(A&#x2013;H)</bold> Simulated wind field and <bold>(I&#x2013;P)</bold> simulated wave field at 2-h intervals during Typhoon Higos. Vectors represent wind direction. Panels <bold>(E, M)</bold> represent the results closest to the landing time. Blue stars indicate the location of the typhoon center, and purple lines indicate the typhoon tracks.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g008.tif"/>
</fig>
</sec>
<sec id="s5_2">
<label>5.2</label>
<title>Wave steepness</title>
<p>Typhoon-induced surface waves were predominantly composed of wind waves. The region with values exceeding 0.025 occupied over 99.37%, 99.82%, and 97.42% of the total study area at the landfall time of Typhoons Hagupit (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9C</bold>
</xref>), Hato (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9G</bold>
</xref>), and Higos (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9K</bold>
</xref>), respectively.</p>
<fig id="f9" position="float">
<label>Figure&#xa0;9</label>
<caption>
<p>Simulated wave steepness at 4-h intervals during Typhoons <bold>(A&#x2013;D)</bold> Hagupit, <bold>(E&#x2013;H)</bold> Hato, and <bold>(I&#x2013;L)</bold> Higos. Panels <bold>(C, G, K)</bold> represent the results closest to the landing time. Blue stars indicate the location of the typhoon center; lines between a pair of stars indicate transition of the typhoon between those points.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g009.tif"/>
</fig>
<p>During Typhoon Hagupit, the region with wave steepness lower than 0.025 corresponded to the outer band of typhoon cyclone structures (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9A&#x2013;C</bold>
</xref>), which were in lower wind speed before typhoon landfall (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6A&#x2013;E</bold>
</xref>); subsequently, the values gradually weakened with typhoon decaying (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9D</bold>
</xref>). During Typhoon Hato, the wave steepness at the coastal areas from Jiangmen to Maoming was lower than 0.025 and gradually increased as the typhoon approached, while the values remained in high intensity in the rest of the study area (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9E&#x2013;G</bold>
</xref>); then, the values decayed more rapidly in the open sea than in the estuarine regions after typhoon landfall (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9H</bold>
</xref>). During Typhoon Higos, the region with a wave steepness lower than 0.025 covered the coastal and offshore regions from Jiangmen to Zhanjiang, with values showing an increasing tendency before typhoon landfall (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9I&#x2013;K</bold>
</xref>); subsequently, the values decreased after typhoon landfall, whereas the estuarine regions had higher values than the open sea (<xref ref-type="fig" rid="f9">
<bold>Figure&#xa0;9L</bold>
</xref>).</p>
</sec>
<sec id="s5_3">
<label>5.3</label>
<title>Wave height and energy distribution</title>
<p>Wave energy was calculated through the wave height, indicating that the temporal and spatial variations of wave height directly reflect the wave energy evolution within the study area during typhoons. The spatial extension of typhoon-induced wave fields coincided with the disturbance area of high wind speeds and the intense wave field located at the east side of the typhoon center (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). The maximum wave heights within the study area were 5.74 m, 5.59 m, 6.39 m, 6.14 m, 5.88 m, 6.06 m, 5.68 m, and 5.28 m; 4.75 m, 5.79 m, 6.16 m, 6.49 m, 5.11 m, 3.84 m, 2.65 m, and 2.12 m; and 4.93 m, 5.47 m, 5.38 m, 5.23 m, 4.97 m, 3.75 m, 2.78 m, and 1.77 m sequentially at the simulated time during Typhoons Hagupit, Hato, and Higos, respectively (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). The results were in positive correlation with the temporal variations of the highest typhoon wind speed, whereas the values of Hato were overall higher than those of Higos and comparable with Hagupit&#x2019;s results before typhoon landfall and then reduced more rapidly when typhoons decayed.</p>
<p>The simulated wave fields during Typhoon Hagupit are shown in <xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>. Two regions of intense wind speed induced two regions of high wave height and then gradually merged as the typhoon moved landward. The maximum area with wave heights &gt;2 m extended from the coastal regions of Maoming to Jieyang and covered over 79% of the coastline of Guangdong Province. Wave energy dissipations were centrally radiated, and the spatial dissipations were sharper toward the shore compared with those toward the open sea. Beyond that, the complex typhoon structures (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6A&#x2013;H</bold>
</xref>) induced irregular wave fields, indicating that the spatial regularity of wave energy was changing with no apparent trend.</p>
<p>In contrast, the typhoon structures of Hato and Higos were regular and compact (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). The induced wave fields were approximately circular, and their spatial expansions were smaller than those during Hagupit (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). The region of wave heights &gt;2 m kept expanding and covered over 45% and 30% of the coastline of Guangdong Province during Hato and Higos, respectively, while the significantly intense wave fields (i.e., wave height &gt;4 m) had a slighter expansion and shifted corresponding to the typhoon movement. Along the moving tracks of typhoons, the waves propagated farther on their east sides and induced the non-negligible risks of intense waves attacks on the eastern coast of Guangdong, even though the typhoons did not directly make landfall in this region. Moreover, the wave height maintained two regions with high values within the offshore area of ME after Hato&#x2019;s landfall (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7N</bold>
</xref>), the inner one located at the mouth-bar region and the second one located on the southwestern side of Da Wan Shan islands. The maximum wave heights in the inner and outer regions were 3.84 m and 3.59 m, respectively. In contrast, the wave field only maintained one region in high wave energy at the mouth-bar region of ME after Higos&#x2019;s landfall, and the maximum wave height was 3.49 m (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8N</bold>
</xref>).</p>
</sec>
</sec>
<sec id="s6" sec-type="discussion">
<label>6</label>
<title>Discussion</title>
<sec id="s6_1">
<label>6.1</label>
<title>Impacts of estuarine configuration and morphology change on wave propagation and dissipation</title>
<p>The PRE contains multiple estuarine configurations, mainly including the bell-shaped bays (i.e., LDY and HMH) and a prismatic estuary upstream into the mainstream of the Xijiang River (i.e., ME) (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1</bold>
</xref>). In addition, the morphological changes from the open sea to the estuarine regions had critical effects on wave propagation and induced wave dissipation and convergence. Thus, three analytical profiles were set up in the central part of LDY, ME, and HMH, starting from the 50-m isobaths, with analysis points inside the 30-m isobaths spaced equally (<xref ref-type="fig" rid="f2">
<bold>Figures&#xa0;2</bold>
</xref>, <xref ref-type="fig" rid="f10">
<bold>10A</bold>
</xref>). The <italic>NDR</italic> was calculated from 12 h before the typhoon landfall to 12 h after landfall (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10B</bold>
</xref>), and the temporal variation of wave dissipation rate <inline-formula>
<mml:math display="inline" id="im47">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> of each profile is shown in <xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11</bold>
</xref>.</p>
<fig id="f10" position="float">
<label>Figure&#xa0;10</label>
<caption>
<p>
<bold>(A)</bold> Depth along the analytical profiles. <bold>(B)</bold> Results of Normalized Dissipation Rate between the analytical points.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g010.tif"/>
</fig>
<fig id="f11" position="float">
<label>Figure&#xa0;11</label>
<caption>
<p>Time series of wave dissipation rate <inline-formula>
<mml:math display="inline" id="im48">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> along the analytical profiles (<bold>(A&#x2013;C)</bold> ME, <bold>(D&#x2013;F)</bold> LDY, <bold>(G&#x2013;I)</bold> HMH). Purple lines represent the time of typhoon landfall.</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g011.tif"/>
</fig>
<p>The wave propagation and dissipation varied among the estuarine regions. First, the waves directly attacked ME with high intensity, while LDY and HMH prevented the intense waves from propagating into the other estuaries. The maximum wave heights at the time of landfall were 0.72 m, 1.05 m, 0.85 m, 0.72 m, 2.75 m, 1.47 m, 0.28 m, and 0.26 m; 0.74 m, 0.97 m, 0.95 m, 0.84 m, 1.41 m, 1.11 m, 0.52 m, and 0.64 m; and 0.46 m, 0.67 m, 0.66 m, 0.61 m, 1.80 m, 1.50 m, 0.29 m, and 0.33 m at the outlet of the estuaries from east to west during Typhoons Hagupit, Hato, and Higos, respectively (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A</bold>
</xref>, <xref ref-type="fig" rid="f6">
<bold>6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). Second, the upstream expansions of intense waves were stronger at LDY and HMH than at ME, pointing out that the wide outlets and gradual contraction of the bell-shaped bays were conducive to the landward propagation of typhoon waves. The farthest upstream extensions of the 1-m isoline of wave height were 4.95 km, 65.48 km, and 26.73 km at 4 h after Hagupit&#x2019;s landfall (<xref ref-type="fig" rid="f6">
<bold>Figure&#xa0;6O</bold>
</xref>); 4.92 km, 69.97 km, and 33.60 km at 2 h after Hato&#x2019;s landfall (<xref ref-type="fig" rid="f7">
<bold>Figure&#xa0;7N</bold>
</xref>); and 4.84 km, 67.62 km, and 27.72 km at 4 h after Higos&#x2019;s landfall (<xref ref-type="fig" rid="f8">
<bold>Figure&#xa0;8O</bold>
</xref>) at ME, LDY, and HMH, respectively, indicating that the maximum upstream propagating distances within the bell-shaped bays could be tens of times greater than those within a prismatic estuary during typhoons. The results also pointed out that the typhoon-induced waves kept propagating upstream after the typhoon landfall. Third, the wave heights were larger in the western part of LDY and HMH, which were mainly induced by the blocking effect of islands located on the southeast side of the bays. In contrast, the waves were under similar conditions on both sides of ME (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). Furthermore, the spatial variation of wave steepness indicated that the intense wind wave component dissipated more slowly in the estuarine regions than in the offshore regions (<xref ref-type="fig" rid="f9">
<bold>Figures&#xa0;9D, H, L</bold>
</xref>).</p>
<p>The landward wave propagation changed significantly during typhoons. First, the amplitudes of wave dissipation and convergence significantly increased with typhoons approaching and decreased rapidly after landfall along the analytical profiles (<xref ref-type="fig" rid="f5">
<bold>Figures&#xa0;5B</bold>
</xref>, <xref ref-type="fig" rid="f11">
<bold>11</bold>
</xref>). Second, the temporal variation of <inline-formula>
<mml:math display="inline" id="im49">
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>E</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:math>
</inline-formula> shifted from being convergence-dominated to being dissipation-dominated at almost all profiles, indicating the intense wave propagation was a short-term change (<xref ref-type="fig" rid="f11">
<bold>Figure&#xa0;11</bold>
</xref>).</p>
<p>In addition, the morphological changes from the deep offshore areas to the shallow coastal regions influence the overall trend of wave-propagated variation. Wave energy evolution had a tendency to convert from being convergence-dominated to being dissipation-dominated when the wave propagated toward the PRE. The <italic>NDR</italic> gradually converted to being positively dominated within the 30-m isobaths, and the transition depths at profiles HMH, ME, and LDY were between 9.86 m and 30.02 m, 8.01 m and 29.96 m, and 14.07 m and 29.64 m during the selected typhoons, respectively (<xref ref-type="fig" rid="f10">
<bold>Figure&#xa0;10B</bold>
</xref>), indicating that the depth-limited dissipation gradually enhanced due to the wind wave&#x2013;bottom interactions (<xref ref-type="bibr" rid="B8">Dolgikh et&#xa0;al., 2013</xref>). Moreover, wave heights had an increasing tendency toward the mouth-bar region due to the interaction between wave, jet spreading, and bottom friction under normal weather conditions (<xref ref-type="bibr" rid="B42">Nardin et&#xa0;al., 2013</xref>). Likewise, waves tend to converge as they pass through the mouth-bar region during typhoons (<xref ref-type="fig" rid="f5">
<bold>Figure&#xa0;5B</bold>
</xref>), and the wave heights remained relatively high after typhoon landfall (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7N</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8N</bold>
</xref>). Nonetheless, the dominant processes of wave propagation between each analytical point showed inconsistency during the selected typhoons (<xref ref-type="fig" rid="f10">
<bold>Figures&#xa0;10B</bold>
</xref>, <xref ref-type="fig" rid="f11">
<bold>11</bold>
</xref>), which were related to the uniqueness of each typhoon-induced wave field based on the unstable typhoon intensity, track, and scale.</p>
</sec>
<sec id="s6_2">
<label>6.2</label>
<title>Response of wave intensity, propagation, and dissipation to different typhoon characteristic factors</title>
<p>Typhoons are extreme weather events with unpredictable track, speed, intensity, and scale before generation. In this study, the track of Hagupit covered nearly the whole coastal region of Guangdong, whereas Hato and Higos had tracks covering only the central and eastern coastal regions (<xref ref-type="fig" rid="f1">
<bold>Figure&#xa0;1A</bold>
</xref>). The maximum wind speed of both Hagupit and Hato was over 50 m/s, and that of Higos was only 35 m/s. Thus, the typhoons selected for analysis are sufficiently representative for discussion of the dominant typhoon-related factors affecting the intensity, propagation, and dissipation of the generated wave field.</p>
<sec id="s6_2_1">
<label>6.2.1</label>
<title>Impacts of the typhoon intensity on the wave intensity</title>
<p>
<xref ref-type="bibr" rid="B34">Li et&#xa0;al. (2020)</xref> noted that an increase in typhoon intensity induced an increase in maximum significant wave height. The maximum wind speed and wave height recorded during Typhoons Hagupit, Hato, and Higos were 50 m/s and 6.39 m, 52 m/s and 6.49 m, and 35 m/s and 5.47 m, respectively, specifying the positive correlation between the maximum of typhoon wind speed and the induced strongest wave height (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6</bold>
</xref>&#x2013;<xref ref-type="fig" rid="f8">
<bold>8</bold>
</xref>). However, in terms of the spatial distribution of intense waves, the ratio of the maximum area of disturbed wave field (wave height &gt;2 m) during Typhoons Hagupit, Hato, and Higos was 2.37:1.65:1 (<xref ref-type="fig" rid="f12">
<bold>Figure&#xa0;12</bold>
</xref>), while the ratio of the maximum wind speed was 1.43:1.49:1. The results showed that the disturbance area of the wave field during typhoons with similar tracks and cyclone structures was proportional to typhoon intensity, whereas Hagupit and Hato induced diverse wave fields despite their comparable maximum wind speed.</p>
<fig id="f12" position="float">
<label>Figure&#xa0;12</label>
<caption>
<p>Time series of the area enclosed by the contours of <bold>(A)</bold> wind speed and <bold>(B)</bold> wave height (bar graphs based on the left Y-axis). Cumulative length of the typhoon tracks after entering the study area (line graphs based on the right Y-axis).</p>
</caption>
<graphic mimetype="image" mime-subtype="tiff" xlink:href="fmars-11-1463214-g012.tif"/>
</fig>
</sec>
<sec id="s6_2_2">
<label>6.2.2</label>
<title>Impacts of the typhoon tracks and scale on wave intensity</title>
<p>The scale of Typhoon Hagupit was broader than that of Typhoon Hato (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6A&#x2013;H</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7A&#x2013;H</bold>
</xref>), inducing the differences between their generated wave fields (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f12">
<bold>12</bold>
</xref>). <xref ref-type="bibr" rid="B60">Wei and Hsieh (2018)</xref> demonstrated that typhoons with different tracks exhibited different interactions between typhoon structures and local topography, resulting in variations in their wave fields. The area of the wind speed over 10.8 m/s and 24.5 m/s increased from 55,871.91 km<sup>2</sup> to 93,643.96 km<sup>2</sup> and from 7,911.12 km<sup>2</sup> to 12,630.84 km<sup>2</sup>, respectively, before Hato&#x2019;s landfall, while the value fluctuated between 89,973.64 km<sup>2</sup> and 99,048.82 km<sup>2</sup> within the 10.8-m/s contour and increased from 8,073.30 km<sup>2</sup> to 16,126.59 km<sup>2</sup> and then decreased to 10,186.28 km<sup>2</sup> within the 24.5-m/s contour during Hagupit&#x2019;s approach (<xref ref-type="fig" rid="f12">
<bold>Figure&#xa0;12</bold>
</xref>). The results showed that the disturbed areas of typhoon structures of Hagupit were broader than those of Hato, inducing a significant difference between the range of typhoon-induced wave fields (<xref ref-type="fig" rid="f6">
<bold>Figures&#xa0;6</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7</bold>
</xref>). Moreover, the ratio of the maximum cumulative length of the typhoon tracks within the study area during Typhoons Hagupit and Hato was 1.44:1 (<xref ref-type="fig" rid="f12">
<bold>Figure&#xa0;12</bold>
</xref>), which was in positive correlation with the ratio of the maximum area of a disturbed wave field. The results verified that the longer distance of typhoon movement within the study area contributes to the interaction of wind and wave, further indicating that the typhoon tracks and scale were more prominent to the generated wave field compared to the typhoon intensity.</p>
</sec>
<sec id="s6_2_3">
<label>6.2.3</label>
<title>Impacts of the typhoon characteristic factors on wave propagation and dissipation</title>
<p>The regularity and moving track of typhoon structure dominated the wave propagation and dissipation within the PRE and its offshore regions. Typhoon Hagupit crossed nearly the whole coastal regions of Guangdong Province with an irregular typhoon structure, causing disturbance across a wide range of coastal areas, and the propagation and dissipation of waves within the coastal regions showed no apparent spatial pattern and were widely disturbed by the typhoon (<xref ref-type="fig" rid="f1">
<bold>Figures&#xa0;1A</bold>
</xref>, <xref ref-type="fig" rid="f6">
<bold>6</bold>
</xref>). In contrast, the cyclone structures of Typhoons Hato and Higos were regular and compact (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8</bold>
</xref>). They crossed the central and eastern coastal regions of Guangdong Province, which disturbed smaller ranges of the wave fields within the study area. Therefore, the intense wave fields were approximately circular. Furthermore, the differences between the expanding and moving tendencies of the regions in different wave intensities directly induced the spatial variation of wave energy dissipation (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7I&#x2013;P</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;P</bold>
</xref>). The expansion areas of the regions with wave heights &gt;2 m and &gt;4 m were 41,496.10 km<sup>2</sup> and 9,864.56 km<sup>2</sup>, and 12,936.13 km<sup>2</sup> and 2,620.17 km<sup>2</sup> during Typhoons Hato and Higos, respectively (<xref ref-type="fig" rid="f12">
<bold>Figures&#xa0;12</bold>
</xref>, <xref ref-type="fig" rid="f7">
<bold>7I&#x2013;M</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;M</bold>
</xref>), indicating that the occupied range of lower wave intensity broadened more significantly. Otherwise, the regions with wave height &gt;4 m shifted corresponding to the movement of the typhoons and the wave height dissipated rapidly when the typhoons moved away, while the landward migrations of the region with wave height &gt;2 m were limited by the obstruction of the shoreline since 5.83 h and 6 h before the landfall of Typhoons Hato and Higos, respectively (<xref ref-type="fig" rid="f7">
<bold>Figures&#xa0;7I&#x2013;M</bold>
</xref>, <xref ref-type="fig" rid="f8">
<bold>8I&#x2013;M</bold>
</xref>). Thus, with the continuous movement of significantly intense wave fields (i.e., wave height &gt;4 m) toward the landing destination, wave energy tended to dissipate more intensely along the typhoon tracks.</p>
<p>The dominant process of overall wave propagation from coastal regions to the PRE is related to the typhoon tracks as well. <xref ref-type="bibr" rid="B13">Feng et&#xa0;al. (2011)</xref> and <xref ref-type="bibr" rid="B40">Mellor (2003)</xref> observed that an intense wave-induced radiation stress occurred on the right side of a typhoon track due to the sharp decrease in wave height in this region, indicating the wave energy tended to dissipate. First, the PRE and its adjacent coastal region located on the right side of Hagupit&#x2019;s track (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>) and the total integration results of <inline-formula>
<mml:math display="inline" id="im50">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> were dominated by positive values along all the analytical profiles during Hagupit (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>), indicating the dominant role of wave dissipation. Second, the LDY and HMH were located on the right and left sides of Higos&#x2019;s track, respectively (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>), while the ME was directly attacked. The total integration results of <inline-formula>
<mml:math display="inline" id="im52">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> were dominated by positive and negative values along the analytical profiles of LDY and HMH, respectively. Third, Hato&#x2019;s track crossed the PRE (<xref ref-type="fig" rid="f2">
<bold>Figure&#xa0;2</bold>
</xref>), and the total integration results of <inline-formula>
<mml:math display="inline" id="im53">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> had no apparent regularities in any of the profiles (<xref ref-type="table" rid="T2">
<bold>Table&#xa0;2</bold>
</xref>). Thus, wave propagation from the coastal regions to the PRE was dominated by wave dissipation/convergence if the estuaries were located on the right/left side of the typhoon, except for those directly attacked.</p>
<table-wrap id="T2" position="float">
<label>Table&#xa0;2</label>
<caption>
<p>Temporal integration of wave dissipation rate along selected profiles.</p>
</caption>
<table frame="hsides">
<thead>
<tr>
<th valign="middle" align="center">Typhoon</th>
<th valign="middle" align="center">Profile</th>
<th valign="middle" align="center">
<inline-formula>
<mml:math display="inline" id="im51">
<mml:mrow>
<mml:mstyle displaystyle="true">
<mml:mrow>
<mml:msubsup>
<mml:mo>&#x222b;</mml:mo>
<mml:mn>0</mml:mn>
<mml:mi>t</mml:mi>
</mml:msubsup>
<mml:mrow>
<mml:mo>&lt;</mml:mo>
<mml:msub>
<mml:mi>&#x3f5;</mml:mi>
<mml:mi>f</mml:mi>
</mml:msub>
<mml:mo>&gt;</mml:mo>
</mml:mrow>
</mml:mrow>
</mml:mstyle>
</mml:mrow>
</mml:math>
</inline-formula> (W&#xb7;h/m<sup>2</sup>)</th>
</tr>
</thead>
<tbody>
<tr>
<td valign="middle" rowspan="3" align="center">Hagupit</td>
<td valign="middle" align="center">HMH</td>
<td valign="middle" align="center">251.52</td>
</tr>
<tr>
<td valign="middle" align="center">ME</td>
<td valign="middle" align="center">99.05</td>
</tr>
<tr>
<td valign="middle" align="center">LDY</td>
<td valign="middle" align="center">140.97</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">Hato</td>
<td valign="middle" align="center">HMH</td>
<td valign="middle" align="center">15.85</td>
</tr>
<tr>
<td valign="middle" align="center">ME</td>
<td valign="middle" align="center">32.13</td>
</tr>
<tr>
<td valign="middle" align="center">LDY</td>
<td valign="middle" align="center">&#x2212;12.11</td>
</tr>
<tr>
<td valign="middle" rowspan="3" align="center">Higos</td>
<td valign="middle" align="center">HMH</td>
<td valign="middle" align="center">&#x2212;10.16</td>
</tr>
<tr>
<td valign="middle" align="center">ME</td>
<td valign="middle" align="center">43.82</td>
</tr>
<tr>
<td valign="middle" align="center">LDY</td>
<td valign="middle" align="center">116.46</td>
</tr>
</tbody>
</table>
<table-wrap-foot>
<fn>
<p>The value &gt;0 indicates wave dissipation, and &lt;0 indicates wave convergence.</p>
</fn>
<fn>
<p>HMH, Huangmaohai; ME, Modaomen Estuary; LDY, Lingding Bay.</p>
</fn>
</table-wrap-foot>
</table-wrap>
</sec>
</sec>
</sec>
<sec id="s7" sec-type="conclusions">
<label>7</label>
<title>Conclusion</title>
<p>The main findings of this study are summarized as follows.</p>
<list list-type="order">
<list-item>
<p>Under the intense force of the typhoon wind field, wind waves were the dominant components prior to the typhoon landfall. The intense wind waves dissipated rapidly with the typhoon decaying, whereas it stayed longer within the estuarine regions than in the open sea.</p>
</list-item>
<list-item>
<p>The distributions of wave fields are related to the typhoon structures. First, a typhoon in compact and regular cyclone structure (i.e., Hato and Higos) induced a wave field that was approximately circular, and the generated wave field dissipated more strongly along the typhoon tracks than in the other directions due to the significantly intense wave field (i.e., wave height &gt;4 m) shifted, corresponded to the movement of the typhoons. In contrast, typhoons in complex structures and large scale (i.e., Hagupit) induced a complex wave field with less regularity.</p>
</list-item>
<list-item>
<p>Wave energy evolution is significantly affected by the estuarine configuration and the morphological changes within the coastal regions. First, the rapid contraction and the narrow width of the estuarine outlet contribute to the wave dissipation. Second, the wave energy tends to transition from being convergence-dominated to being dissipation-dominated due to the enhanced depth-limited wind wave&#x2013;bottom interaction with the wave propagation landward. In addition, waves tend to converge within the mouth-bar region of ME based on its morphological features.</p>
</list-item>
<list-item>
<p>Typhoon tracks and scale played a more critical role in wave intensity, propagation, and dissipation than typhoon intensity.</p>
</list-item>
<list-item>
<p>Except for the typhoons directly attacking the PRE, waves within the estuarine regions tend to dissipate/converge when it is located on the right/left side of the moving track of the typhoons.</p>
</list-item>
</list>
</sec>
</body>
<back>
<sec id="s8" sec-type="data-availability">
<title>Data availability statement</title>
<p>The original contributions presented in the study are included in the article/supplementary material. Further inquiries can be directed to the corresponding author.</p>
</sec>
<sec id="s9" sec-type="author-contributions">
<title>Author contributions</title>
<p>ML: Conceptualization, Data curation, Writing &#x2013; original draft. SZ: Conceptualization, Writing &#x2013; review &amp; editing. HQ: Data curation, Writing &#x2013; review &amp; editing. LJ: Writing &#x2013; review &amp; editing.</p>
</sec>
<sec id="s10" sec-type="funding-information">
<title>Funding</title>
<p>The author(s) declare financial support was received for the research, authorship, and/or publication of this article. This study is supported by Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai) (SML2023SP220) and Marine Economic Development Special Program of Guangdong Province (Six Major Marine Industries): Research and Demonstration of Critical Technologies for Comprehensive Prevention and Control of Natural Disaster in Offshore Wind Farms, China (Grant No. 29 (2023)).</p>
</sec>
<sec id="s11" 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="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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