Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean
The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III (WW3) to the variation in sea surface temperature (SST) in the Arctic Ocean. The simulated significant wave height (SWH) were validated against the products from Haiyang-2B (HY-2B) in 2021, obtaining a root mean...
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Veröffentlicht in: | Journal of Ocean University of China 2024, Vol.23 (5), p.1151-1162 |
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description | The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III (WW3) to the variation in sea surface temperature (SST) in the Arctic Ocean. The simulated significant wave height (SWH) were validated against the products from Haiyang-2B (HY-2B) in 2021, obtaining a root mean squared error (RMSE) of 0.45 with a correlation of 0.96 and scatter index of 0.18. The wave-induced effects,
i.e.
, wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift, were calculated from WW3, ERA-5 wind, SST, and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model. The results showed that an RMSE of 0.81 °C with wave-induced effects was less than the RMSE of 1.11 °C achieved without the wave term compared with the simulated SST with the measurements from Argos. Considering the four wave effects and sea ice freezing, the SST in the Arctic Ocean decreased by up to 1 °C in winter. Regression analysis revealed that the SWH was linear in SST (values without subtraction of waves) in summer and autumn, but this behavior was not observed in spring or winter due to the presence of sea ice. The interannual variation also presented a negative relationship between the difference in SST and SWH. |
doi_str_mv | 10.1007/s11802-024-5797-4 |
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i.e.
, wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift, were calculated from WW3, ERA-5 wind, SST, and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model. The results showed that an RMSE of 0.81 °C with wave-induced effects was less than the RMSE of 1.11 °C achieved without the wave term compared with the simulated SST with the measurements from Argos. Considering the four wave effects and sea ice freezing, the SST in the Arctic Ocean decreased by up to 1 °C in winter. Regression analysis revealed that the SWH was linear in SST (values without subtraction of waves) in summer and autumn, but this behavior was not observed in spring or winter due to the presence of sea ice. The interannual variation also presented a negative relationship between the difference in SST and SWH.</description><identifier>ISSN: 1672-5182</identifier><identifier>EISSN: 1993-5021</identifier><identifier>EISSN: 1672-5174</identifier><identifier>DOI: 10.1007/s11802-024-5797-4</identifier><language>eng</language><publisher>Heidelberg: Science Press</publisher><subject>Annual variations ; Earth and Environmental Science ; Earth Sciences ; Freezing ; Meteorology ; Ocean models ; Oceanography ; Regression analysis ; Root-mean-square errors ; Salinity data ; Sea ice ; Sea surface temperature ; Significant wave height ; Surface waves ; Wave breaking ; Wave effects ; Wave height ; Waves ; Wind stress ; Winter</subject><ispartof>Journal of Ocean University of China, 2024, Vol.23 (5), p.1151-1162</ispartof><rights>Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2024</rights><rights>Ocean University of China, Science Press and Springer-Verlag GmbH Germany 2024.</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c316t-a2b5268aa97512d9f582bb6c9bc00332e64b8bf057cf7d9f4be45f500ef029603</citedby><cites>FETCH-LOGICAL-c316t-a2b5268aa97512d9f582bb6c9bc00332e64b8bf057cf7d9f4be45f500ef029603</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s11802-024-5797-4$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s11802-024-5797-4$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,777,781,27905,27906,41469,42538,51300</link.rule.ids></links><search><creatorcontrib>Wei, Meng</creatorcontrib><creatorcontrib>Shao, Weizeng</creatorcontrib><creatorcontrib>Shen, Wei</creatorcontrib><creatorcontrib>Hu, Yuyi</creatorcontrib><creatorcontrib>Zhang, Yu</creatorcontrib><creatorcontrib>Zuo, Juncheng</creatorcontrib><title>Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean</title><title>Journal of Ocean University of China</title><addtitle>J. Ocean Univ. China</addtitle><description>The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III (WW3) to the variation in sea surface temperature (SST) in the Arctic Ocean. The simulated significant wave height (SWH) were validated against the products from Haiyang-2B (HY-2B) in 2021, obtaining a root mean squared error (RMSE) of 0.45 with a correlation of 0.96 and scatter index of 0.18. The wave-induced effects,
i.e.
, wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift, were calculated from WW3, ERA-5 wind, SST, and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model. The results showed that an RMSE of 0.81 °C with wave-induced effects was less than the RMSE of 1.11 °C achieved without the wave term compared with the simulated SST with the measurements from Argos. Considering the four wave effects and sea ice freezing, the SST in the Arctic Ocean decreased by up to 1 °C in winter. Regression analysis revealed that the SWH was linear in SST (values without subtraction of waves) in summer and autumn, but this behavior was not observed in spring or winter due to the presence of sea ice. The interannual variation also presented a negative relationship between the difference in SST and SWH.</description><subject>Annual variations</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Freezing</subject><subject>Meteorology</subject><subject>Ocean models</subject><subject>Oceanography</subject><subject>Regression analysis</subject><subject>Root-mean-square errors</subject><subject>Salinity data</subject><subject>Sea ice</subject><subject>Sea surface temperature</subject><subject>Significant wave height</subject><subject>Surface waves</subject><subject>Wave breaking</subject><subject>Wave effects</subject><subject>Wave height</subject><subject>Waves</subject><subject>Wind stress</subject><subject>Winter</subject><issn>1672-5182</issn><issn>1993-5021</issn><issn>1672-5174</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp1kE1LAzEQhoMoWKs_wFvAc3Qyu0l2j6WoFSo9tOIxJDHRLXa3JlnBf--WFT15mmHej4GHkEsO1xxA3STOK0AGWDKhasXKIzLhdV0wAciPh10qZIJXeErOUtoCiEJINSGP867NsbF9brqWdoGu-xiM8_TZfPpEc0fX3vweN36399HkPg5a09L85uksutw4unLetOfkJJj35C9-5pQ83d1u5gu2XN0_zGdL5gouMzNoBcrKmFoJji91EBVaK11tHUBRoJelrWwAoVxQg1xaX4ogAHwArCUUU3I19u5j99H7lPW262M7vNQFB6wQJB5cfHS52KUUfdD72OxM_NIc9IGaHqnpgZo-UNPlkMExkwZv--rjX_P_oW-Q_W52</recordid><startdate>2024</startdate><enddate>2024</enddate><creator>Wei, Meng</creator><creator>Shao, Weizeng</creator><creator>Shen, Wei</creator><creator>Hu, Yuyi</creator><creator>Zhang, Yu</creator><creator>Zuo, Juncheng</creator><general>Science Press</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7T7</scope><scope>7TN</scope><scope>8FD</scope><scope>C1K</scope><scope>F1W</scope><scope>FR3</scope><scope>H95</scope><scope>H96</scope><scope>L.G</scope><scope>P64</scope></search><sort><creationdate>2024</creationdate><title>Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean</title><author>Wei, Meng ; Shao, Weizeng ; Shen, Wei ; Hu, Yuyi ; Zhang, Yu ; Zuo, Juncheng</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c316t-a2b5268aa97512d9f582bb6c9bc00332e64b8bf057cf7d9f4be45f500ef029603</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>Annual variations</topic><topic>Earth and Environmental Science</topic><topic>Earth Sciences</topic><topic>Freezing</topic><topic>Meteorology</topic><topic>Ocean models</topic><topic>Oceanography</topic><topic>Regression analysis</topic><topic>Root-mean-square errors</topic><topic>Salinity data</topic><topic>Sea ice</topic><topic>Sea surface temperature</topic><topic>Significant wave height</topic><topic>Surface waves</topic><topic>Wave breaking</topic><topic>Wave effects</topic><topic>Wave height</topic><topic>Waves</topic><topic>Wind stress</topic><topic>Winter</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Wei, Meng</creatorcontrib><creatorcontrib>Shao, Weizeng</creatorcontrib><creatorcontrib>Shen, Wei</creatorcontrib><creatorcontrib>Hu, Yuyi</creatorcontrib><creatorcontrib>Zhang, Yu</creatorcontrib><creatorcontrib>Zuo, Juncheng</creatorcontrib><collection>CrossRef</collection><collection>Industrial and Applied Microbiology Abstracts (Microbiology A)</collection><collection>Oceanic Abstracts</collection><collection>Technology Research Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Engineering Research Database</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 1: Biological Sciences & Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Biotechnology and BioEngineering Abstracts</collection><jtitle>Journal of Ocean University of China</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Wei, Meng</au><au>Shao, Weizeng</au><au>Shen, Wei</au><au>Hu, Yuyi</au><au>Zhang, Yu</au><au>Zuo, Juncheng</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean</atitle><jtitle>Journal of Ocean University of China</jtitle><stitle>J. Ocean Univ. China</stitle><date>2024</date><risdate>2024</risdate><volume>23</volume><issue>5</issue><spage>1151</spage><epage>1162</epage><pages>1151-1162</pages><issn>1672-5182</issn><eissn>1993-5021</eissn><eissn>1672-5174</eissn><abstract>The aim of our study was to examine the contribution of surface waves from WAVEWATCH-III (WW3) to the variation in sea surface temperature (SST) in the Arctic Ocean. The simulated significant wave height (SWH) were validated against the products from Haiyang-2B (HY-2B) in 2021, obtaining a root mean squared error (RMSE) of 0.45 with a correlation of 0.96 and scatter index of 0.18. The wave-induced effects,
i.e.
, wave breaking and mixing induced by nonbearing waves resulting in changes in radiation stress and Stokes drift, were calculated from WW3, ERA-5 wind, SST, and salinity data from the National Centers for Environmental Prediction and were taken as forcing fields in the Stony Brook Parallel Ocean Model. The results showed that an RMSE of 0.81 °C with wave-induced effects was less than the RMSE of 1.11 °C achieved without the wave term compared with the simulated SST with the measurements from Argos. Considering the four wave effects and sea ice freezing, the SST in the Arctic Ocean decreased by up to 1 °C in winter. Regression analysis revealed that the SWH was linear in SST (values without subtraction of waves) in summer and autumn, but this behavior was not observed in spring or winter due to the presence of sea ice. The interannual variation also presented a negative relationship between the difference in SST and SWH.</abstract><cop>Heidelberg</cop><pub>Science Press</pub><doi>10.1007/s11802-024-5797-4</doi><tpages>12</tpages></addata></record> |
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subjects | Annual variations Earth and Environmental Science Earth Sciences Freezing Meteorology Ocean models Oceanography Regression analysis Root-mean-square errors Salinity data Sea ice Sea surface temperature Significant wave height Surface waves Wave breaking Wave effects Wave height Waves Wind stress Winter |
title | Contribution of Surface Waves to Sea Surface Temperatures in the Arctic Ocean |
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