{"title":"Comprehensive comparative analysis of reconstructed sea level datasets in the China Seas: insights from tide gauge and satellite altimetry","authors":"Shuwei Zhang, Yanxiao Li, Jianlong Feng, Yiyang Jin, Jing Zhang, Liang Zhao","doi":"10.3389/fmars.2024.1469173","DOIUrl":null,"url":null,"abstract":"At present, there are many reconstructed datasets at the global scale. To test the applicability of these datasets in the China seas, the study comprehensively analyzes the reliability and accuracy of reconstructed sea level datasets in capturing nuanced temporal patterns of sea level changes in the China Seas. This study applied analysis methods or indicators such as time series, Taylor plots, correlation coefficients, growth rates, and standard deviations. Ocean Data Assimilations (ODAs) outperform Tide Gauge Reconstructions (TGRs) in terms of correlation with measured data in the nearshore, while TGRs exhibit superior capability in capturing oceanic sea level variability. Although the ODAs and TGRs both suffer from the underestimation of sea level variability in China as well as in neighboring seas, the TGRs perform better than the former. ODAs show inconsistency in reflecting the rate of sea level rise, but they, particularly the China Ocean Reanalysis (CORA), demonstrate a better correlation with satellite altimetry datasets. Meanwhile, both of them can reflect the Pacific Decadal Oscillation (PDO) well. TGRs, relying on oceanic tide gauge stations, suffer from poor correlation with tide gauge stations due to limited coverage. Reconstruction discrepancies are attributed to methodological differences and data assimilation techniques. Future studies should explore alternative variables like sea surface temperature and so on to enhance sea-level reconstruction, especially in regions with sparse tide gauge coverage.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.3389/fmars.2024.1469173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
At present, there are many reconstructed datasets at the global scale. To test the applicability of these datasets in the China seas, the study comprehensively analyzes the reliability and accuracy of reconstructed sea level datasets in capturing nuanced temporal patterns of sea level changes in the China Seas. This study applied analysis methods or indicators such as time series, Taylor plots, correlation coefficients, growth rates, and standard deviations. Ocean Data Assimilations (ODAs) outperform Tide Gauge Reconstructions (TGRs) in terms of correlation with measured data in the nearshore, while TGRs exhibit superior capability in capturing oceanic sea level variability. Although the ODAs and TGRs both suffer from the underestimation of sea level variability in China as well as in neighboring seas, the TGRs perform better than the former. ODAs show inconsistency in reflecting the rate of sea level rise, but they, particularly the China Ocean Reanalysis (CORA), demonstrate a better correlation with satellite altimetry datasets. Meanwhile, both of them can reflect the Pacific Decadal Oscillation (PDO) well. TGRs, relying on oceanic tide gauge stations, suffer from poor correlation with tide gauge stations due to limited coverage. Reconstruction discrepancies are attributed to methodological differences and data assimilation techniques. Future studies should explore alternative variables like sea surface temperature and so on to enhance sea-level reconstruction, especially in regions with sparse tide gauge coverage.