New Wind-Wave Climate Records in the Western Mediterranean Sea

2021 · doi:10.21203/rs.3.rs-689001/v1
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This study analyzed 41 years of wind and wave data in the Western Mediterranean Sea, finding significant increasing trends in wave height and wind speed, with about half the coast experiencing records since 2013.

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This paper analyzed changes in wind and wave climate in the Western Mediterranean Sea using 41 years of wind and wave hindcasts, aiming to quantify recent shifts in wave climate and identify coastal areas most affected. Using Theil–Sen slope estimates and Mann–Kendall trend testing, the authors assessed trends in mean and maximum significant wave height (SWH) and wind speed (WS) across seasonal and annual timescales, and mapped “new” wave records observed since 2010 by locating where and when maxima exceeded prior (at least since 1979) conditions. They report significant increasing trends in annual maximum SWH and WS for much of the basin with inter-seasonal variability, noting that since 2013 about half of the coastline experienced wave-climate records not seen since 1979, including areas with three successive records. As a limitation, the work is a preprint not peer reviewed by a journal. The paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract This study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analyzed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in a large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends. Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilization to prevent probable catastrophic wave storms and ensure sustainable and economic development.
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New Wind-Wave Climate Records in the Western Mediterranean Sea | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article New Wind-Wave Climate Records in the Western Mediterranean Sea Khalid AMAROUCHE, Bilal Bingölbali, Adem Akpinar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-689001/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 03 Nov, 2021 Read the published version in Climate Dynamics → Version 1 posted 5 You are reading this latest preprint version Abstract This study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analyzed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in a large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends. Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilization to prevent probable catastrophic wave storms and ensure sustainable and economic development. Civil Engineering Wave climate Climate change Climate records Coastal storm Climate change trends Mediterranean climate Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Full Text Tables Table 4. Error statistic results of the calibrated SWAN coarse grid model obtained by comparing simulation results against SWH measurements recorded in 24 buoys between July 2019 and March 2020. Buoys N R BIAS (m) RMSE (m) MAE (m) Mean ,obs. (m) Mean ,sim. (m) SI NMB (m) d HH B1 6778 0.82 -0.10 0.23 0.17 0.48 0.37 0.49 -0.22 0.88 0.45 B2 3030 0.94 0.06 0.23 0.15 0.63 0.69 0.36 0.09 0.97 0.25 B3 6744 0.93 0.15 0.34 0.24 1.03 1.17 0.33 0.15 0.30 0.14 B4 7300 0.94 0.17 0.34 0.23 1.04 1.21 0.33 0.20 0.28 0.16 B5 7197 0.94 0.08 0.30 0.21 0.86 0.94 0.35 0.09 0.29 0.09 B6 6432 0.92 -0.06 0.21 0.14 0.56 0.50 0.37 0.07 0.20 -0.11 B7 2205 0.92 0.06 0.23 0.15 0.70 0.76 0.32 0.06 0.22 0.09 B8 7263 0.93 0.07 0.35 0.22 1.10 1.17 0.32 0.08 0.34 0.07 B9 5948 0.92 -0.04 0.21 0.14 0.75 0.72 0.27 0.04 0.20 -0.05 B10 4227 0.95 -0.08 0.17 0.13 0.45 0.37 0.37 0.08 0.14 -0.18 B11 14363 0.94 0.08 0.28 0.20 0.68 0.76 0.41 0.11 0.26 0.11 B12 13109 0.94 -0.02 0.23 0.16 0.69 0.67 0.34 0.03 0.23 -0.03 B13 6560 0.96 0.19 0.43 0.29 1.30 1.48 0.33 0.24 0.36 0.14 B14 14408 0.94 0.08 0.28 0.18 0.65 0.73 0.43 0.13 0.25 0.13 B15 13709 0.93 0.05 0.24 0.17 0.72 0.77 0.34 0.06 0.24 0.08 B16 5172 0.95 0.09 0.38 0.26 1.36 1.46 0.28 0.09 0.37 0.07 B17 6493 0.96 0.23 0.55 0.36 1.50 1.73 0.37 0.36 0.41 0.15 B18 6440 0.92 0.15 0.31 0.20 0.73 0.88 0.43 0.18 0.26 0.20 B19 13846 0.94 0.09 0.30 0.20 0.92 1.01 0.32 0.13 0.27 0.10 B20 8898 0.92 0.30 0.58 0.37 1.23 1.53 0.47 0.38 0.44 0.25 B21 12348 0.89 -0.05 0.27 0.18 0.74 0.70 0.37 0.07 0.26 -0.06 B22 6441 0.95 0.16 0.41 0.27 1.11 1.27 0.37 0.26 0.33 0.15 B23 10844 0.95 -0.00 0.33 0.22 1.23 1.23 0.27 0.01 0.33 0.00 B24 10213 0.93 -0.04 0.22 0.15 0.70 0.67 0.31 0.04 0.22 -0.05 Cite Share Download PDF Status: Published Journal Publication published 03 Nov, 2021 Read the published version in Climate Dynamics → Version 1 posted Reviews received at journal 08 Jul, 2021 Reviewers invited by journal 08 Jul, 2021 Editor assigned by journal 08 Jul, 2021 First submitted to journal 05 Jul, 2021 Editorial decision: Minor Revision 21 May, 2021 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-689001","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":38281439,"identity":"bfd66f5d-ce93-450c-9f52-d1c691c6d952","order_by":0,"name":"Khalid AMAROUCHE","email":"data:image/png;base64,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","orcid":"https://orcid.org/0000-0001-7983-4611","institution":"Bursa Uludağ Üniversitesi: Bursa Uludag Universitesi","correspondingAuthor":true,"prefix":"","firstName":"Khalid","middleName":"","lastName":"AMAROUCHE","suffix":""},{"id":38281440,"identity":"923a531c-bd34-46c3-898c-fe78b3c6a4a3","order_by":1,"name":"Bilal Bingölbali","email":"","orcid":"","institution":"Bursa Uludağ Üniversitesi: Bursa Uludag Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Bilal","middleName":"","lastName":"Bingölbali","suffix":""},{"id":38281441,"identity":"09968064-4c6f-46b3-92cd-ac8cd0d7e14d","order_by":2,"name":"Adem Akpinar","email":"","orcid":"","institution":"Bursa Uludağ Üniversitesi: Bursa Uludag Universitesi","correspondingAuthor":false,"prefix":"","firstName":"Adem","middleName":"","lastName":"Akpinar","suffix":""}],"badges":[],"createdAt":"2021-07-05 12:27:52","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-689001/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-689001/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00382-021-05997-1","type":"published","date":"2021-11-03T06:27:44+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":11390028,"identity":"8a6deeca-aa08-405f-99bb-5f5d3da82542","added_by":"auto","created_at":"2021-07-12 18:54:15","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":112615,"visible":true,"origin":"","legend":"The locations of wave and wind buoy measurements","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/5521660e5543ea74448d0c6b.jpg"},{"id":11390769,"identity":"52cc0063-1999-46e2-94a1-bcfcb6789458","added_by":"auto","created_at":"2021-07-12 19:00:15","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":163717,"visible":true,"origin":"","legend":"The map of satellites observations used for the spatial validation of the wave hindcast data, showing the position of the wave buoy used for the satellite data accuracy assessment (left), and a Density scatter plot with error statistics obtained by comparing the satellite observations against the buoys measurement (right); the color bar indicates the normalized density of observations in the scatter plot.","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/0f6e45e95d234b063ec95c78.jpg"},{"id":11389658,"identity":"9ea05e64-5f52-483c-9b8c-7014d7ac007e","added_by":"auto","created_at":"2021-07-12 18:51:15","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":145921,"visible":true,"origin":"","legend":"Spatial distribution of the error indicator HH index and the correlation coefficient R obtained by comparing the SWH results of the SWAN model with satellite measurements between July 2019 and March 2020.","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/f3cf593cceaee317c0916b82.jpg"},{"id":11390316,"identity":"6ab87d3a-3a16-498e-b7bf-c99cdbc1ebb1","added_by":"auto","created_at":"2021-07-12 18:57:15","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":139447,"visible":true,"origin":"","legend":"Scatter plot of CFSR wind speed versus observed wind speed at Nice and Lion Buoys between July 2019 and March 2020. The color bar indicates the normalized density of observations in the scatter plots.","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/0678c6ee6da5cd72c2589659.jpg"},{"id":11389661,"identity":"a2146427-4b4f-4d32-b233-ee1ab55f5212","added_by":"auto","created_at":"2021-07-12 18:51:15","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":245582,"visible":true,"origin":"","legend":"Spatial distribution of Theil-Sen slope estimates (left column) and the significance (right column) of long-term trends according to the Mann Kendall Test at different confidence levels for both annual SWH_Mean [cm/year] (upper panel) and annual WS_Mean [cm.s-1/year] (lower panel).","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/b75acd994bdf94e9f992f716.jpg"},{"id":11389666,"identity":"320bb4ab-1e2d-4716-8c8e-d11c3b02c676","added_by":"auto","created_at":"2021-07-12 18:51:15","extension":"jpg","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":321487,"visible":true,"origin":"","legend":"Spatial distribution of Theil-Sen slope estimates (the first and third columns) and the significance (the second and fourth columns) of long-term trends according to the Mann Kendall Test at different confidence levels for both seasonal SWH_Mean [cm/year] (the first two columns) and seasonal WS_Mean [cm.s-1/year] (the last two columns).","description":"","filename":"6.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/b33613e0e219859c9ffc9307.jpg"},{"id":11390317,"identity":"9cd10889-d959-4094-85b3-7c280068e09b","added_by":"auto","created_at":"2021-07-12 18:57:15","extension":"jpg","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":241097,"visible":true,"origin":"","legend":"Spatial distribution of Theil-Sen slope estimates (left column) and the significance (right column) of long-term trends according to the Mann Kendall Test at different confidence levels for both annual SWH_Max [cm/year] (upper panel) and annual WS_Max [cm.s-1/year] (lower panel).","description":"","filename":"7.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/9c8c732557b90f19b2d114db.jpg"},{"id":11390023,"identity":"a54ce3a3-9e0e-4fd4-9751-89bbf50912e3","added_by":"auto","created_at":"2021-07-12 18:54:15","extension":"jpg","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":331138,"visible":true,"origin":"","legend":"Spatial distribution of Theil-Sen slope estimates (the first and third columns) and the significance (the second and fourth columns) of long-term trends according to the Mann Kendall Test at different confidence levels for both seasonal SWH_Max [cm/year] (the first two columns) and seasonal WS_Max [cm.s-1/year] (the last two columns).","description":"","filename":"8.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/f48830fd52f748a44012eb30.jpg"},{"id":11389663,"identity":"e4fff995-8fcf-4676-9e8c-1abe64359349","added_by":"auto","created_at":"2021-07-12 18:51:15","extension":"jpg","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":209691,"visible":true,"origin":"","legend":"Spatial distribution of Theil-Sen slope estimates (left column) and the significance (right column) of long-term trends (1979 to 2020) according to the Mann Kendall Test at different confidence levels for winters SWH_Mean [cm/year] (the first row) and for winters SWH_Max [cm/year] (the second row).","description":"","filename":"9.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/43ae6f0ca49ec56cb4c00567.jpg"},{"id":11389667,"identity":"f735236b-d8ed-460e-b561-ebba087e109b","added_by":"auto","created_at":"2021-07-12 18:51:15","extension":"jpg","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":148710,"visible":true,"origin":"","legend":"Spatial distributions of long-term trends Theil-Sen slope in [cm/year] of the annual average of monthly SWH-max and their significant trends according to the Mann Kendall Test at different confidence levels.","description":"","filename":"10.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/4dc21241129c1eca3355deb7.jpg"},{"id":11390026,"identity":"4886f901-52a2-473d-ab05-a76c1e2ae82e","added_by":"auto","created_at":"2021-07-12 18:54:15","extension":"jpg","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":242755,"visible":true,"origin":"","legend":"Spatial distributions of the annual new records of SWH between January 2010 and 2020 (the right plot in the upper panel) and the differences between the maximum SWH observed from 2010 to 2020 and those observed from 1979 to 2010 (the right plot in the lower panel) and time series plots of the annual maximum SWH observed by six buoys located in the new records areas (the left two columns). ","description":"","filename":"11.jpg","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1/d8a24b675b98ca761eddd3f6.jpg"},{"id":19318215,"identity":"67de3a49-b703-4099-b92f-b444ef6876ec","added_by":"auto","created_at":"2022-03-17 06:27:51","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1890196,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleCDREVISIONV4UnMarcked.pdf","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1_covered.pdf"},{"id":13657420,"identity":"4851d3e0-cb8b-4dc7-b858-96883c9b7599","added_by":"auto","created_at":"2021-09-17 10:10:24","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1885144,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleCDREVISIONV4UnMarcked.pdf","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1_covered.pdf"},{"id":11390770,"identity":"65c41942-fd1a-4ac3-b02f-16757a141561","added_by":"auto","created_at":"2021-07-12 19:00:25","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1881532,"visible":true,"origin":"","legend":"","description":"","filename":"ArticleCDREVISIONV4UnMarcked.pdf","url":"https://assets-eu.researchsquare.com/files/rs-689001/v1_covered.pdf"}],"financialInterests":"","formattedTitle":"\u003cp\u003eNew Wind-Wave Climate Records in the Western Mediterranean Sea\u003c/p\u003e","fulltext":[{"header":"Full Text","content":"This preprint is available for \u003ca href='/article/rs-689001/latest.pdf' target='_blank'\u003edownload as a PDF\u003c/a\u003e."},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https://myfiles.space/user_files/69515_16346c490bab499e/69515_custom_files/img1626104112.png\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https://myfiles.space/user_files/69515_16346c490bab499e/69515_custom_files/img1626104139.png\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"https://myfiles.space/user_files/69515_16346c490bab499e/69515_custom_files/img1626104176.png\"\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cbr\u003e\u003c/strong\u003e\u003c/p\u003e\u003cstrong\u003eTable 4.\u003c/strong\u003e Error statistic results of the calibrated SWAN coarse grid model obtained by comparing simulation results against SWH measurements recorded in 24 buoys between July 2019 and March 2020.\u003cp\u003e\u003c/p\u003e\n\u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eBuoys\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"8.348794063079778%\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"9.090909090909092%\"\u003e\n \u003cp\u003eR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.421150278293135%\"\u003e\n \u003cp\u003eBIAS\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"8.534322820037106%\"\u003e\n \u003cp\u003eRMSE\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.421150278293135%\"\u003e\n \u003cp\u003eMAE\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.38961038961039%\"\u003e\n \u003cp\u003eMean\u003csub\u003e,obs.\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"10.575139146567718%\"\u003e\n \u003cp\u003eMean\u003csub\u003e,sim.\u003c/sub\u003e\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.421150278293135%\"\u003e\n \u003cp\u003eSI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.792207792207792%\"\u003e\n \u003cp\u003eNMB\u003c/p\u003e\n \u003cp\u003e(m)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.421150278293135%\"\u003e\n \u003cp\u003ed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"bottom\" width=\"7.421150278293135%\"\u003e\n \u003cp\u003eHH\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e6778\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.82\u003c/p\u003e\n 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width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e7300\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.534322820037106%\"\u003e\n \u003cp\u003e0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n 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width=\"8.348794063079778%\"\u003e\n \u003cp\u003e6432\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e-0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.534322820037106%\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.38961038961039%\"\u003e\n \u003cp\u003e0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.575139146567718%\"\u003e\n \u003cp\u003e0.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e-0.11\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e2205\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.534322820037106%\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.38961038961039%\"\u003e\n \u003cp\u003e0.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.575139146567718%\"\u003e\n \u003cp\u003e0.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n 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width=\"8.534322820037106%\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.38961038961039%\"\u003e\n \u003cp\u003e0.75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.575139146567718%\"\u003e\n \u003cp\u003e0.72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e4227\u003c/p\u003e\n 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width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.29\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.38961038961039%\"\u003e\n \u003cp\u003e1.30\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"10.575139146567718%\"\u003e\n \u003cp\u003e1.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e14408\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.94\u003c/p\u003e\n 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width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.792207792207792%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.37\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"8.16326530612245%\"\u003e\n \u003cp\u003eB17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.348794063079778%\"\u003e\n \u003cp\u003e6493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"9.090909090909092%\"\u003e\n \u003cp\u003e0.96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"8.534322820037106%\"\u003e\n \u003cp\u003e0.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.421150278293135%\"\u003e\n \u003cp\u003e0.36\u003c/p\u003e\n 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Dynamics](https://www.springer.com/journal/382)","snPcode":"382","submissionUrl":"https://submission.nature.com/new-submission/382/3","title":"Climate Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Wave climate, Climate change, Climate records, Coastal storm, Climate change trends, Mediterranean climate","lastPublishedDoi":"10.21203/rs.3.rs-689001/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-689001/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study presents a detailed analysis of changes in wind and wave climate in the Western Mediterranean Sea (WMed), based on 41 years of accurate wind and wave hindcasts. The purpose of this research is to assess the magnitude of recent changes in wave climate and to locate the coastal areas most affected by these changes. Starting from the Theil-Sen slope estimator and the Mann Kendall test, trends in mean and Max significant wave heights (SWH) and wind speed (WS) are analyzed simultaneously on seasonal and annual scales. Thus, the new wave records observed since 2010 have been located spatially and temporally using a simple spatial analysis method, while the increases in maximum wave heights over the last decade have been estimated and mapped. This work was motivated by evidence pointed out by several authors concerning the influence of global climate change on the local climate in the Mediterranean Sea and by the increase in the number and intensity of wave storm events over recent years. Several exceptional storms have recently been observed along the Mediterranean coasts, including storm Adrian in 2018 and storm Gloria in 2020, which resulted in enormous damage along the French and Spanish coasts. The results of the present study reflect a worrying situation in a large part of the WMed coasts. Most of the WMed basin experiences a significant increasing trend in the annual Max of SWH and WS with evident inter-seasonal variability that underlines the importance of multi-scale analysis to assess wind and wave trends.\u0026nbsp;Since 2013, about half of the WMed coastline has experienced records in wave climate, not recorded at least since 1979, and several areas have experienced three successive records. Several WMed coasts are experiencing a worrying evolution of the wave climate, which requires a serious mobilization to prevent probable catastrophic wave storms and ensure sustainable and economic development.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"New Wind-Wave Climate Records in the Western Mediterranean Sea","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-07-12 18:51:13","doi":"10.21203/rs.3.rs-689001/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2021-07-08T22:14:38+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2021-07-08T15:04:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2021-07-08T14:25:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Climate Dynamics","date":"2021-07-05T08:27:42+00:00","index":"","fulltext":""},{"type":"decision","content":"Minor Revision","date":"2021-05-21T12:52:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"climate-dynamics","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"cldy","sideBox":"Learn more about [Climate Dynamics](https://www.springer.com/journal/382)","snPcode":"382","submissionUrl":"https://submission.nature.com/new-submission/382/3","title":"Climate Dynamics","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"17299961-5f99-4fb0-b243-9783f8784f92","owner":[],"postedDate":"July 12th, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[{"id":5658922,"name":"Civil Engineering"}],"tags":[],"updatedAt":"2022-03-17T06:27:44+00:00","versionOfRecord":{"articleIdentity":"rs-689001","link":"https://doi.org/10.1007/s00382-021-05997-1","journal":{"identity":"climate-dynamics","isVorOnly":false,"title":"Climate Dynamics"},"publishedOn":"2021-11-03 06:27:44","publishedOnDateReadable":"November 3rd, 2021"},"versionCreatedAt":"2021-07-12 18:51:13","video":"","vorDoi":"10.1007/s00382-021-05997-1","vorDoiUrl":"https://doi.org/10.1007/s00382-021-05997-1","workflowStages":[]},"version":"v1","identity":"rs-689001","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-689001","identity":"rs-689001","version":["v1"]},"buildId":"_2-kVJe1T_tPrBINL-cwx","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}

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