Estimation of sea level variability in the South China Sea from satellite altimetry and tide gauge data. Fu, Y., Zhou, X., Zhou, D., Li, J., & Zhang, W. Advances in Space Research, August, 2019. ![Estimation of sea level variability in the South China Sea from satellite altimetry and tide gauge data [link]](https://bibbase.org/img/filetypes/link.svg "link")
Paper doi abstract bibtex Sea level variability in the South China Sea (SCS) was investigated by means of satellite altimetry and tide gauge data over a 24 years period 1993–2016. The sea level anomalies (SLAs) retrieved from satellite and tide gauge data were compared. The differences between the two datasets showed a normal distribution with 87% within ±10 cm. Considering the individual time series, the results revealed that satellite and tide gauge SLAs are in good agreement, with root mean square deviations in the range 0.9–9.9 cm (average value is 2.7 cm), and correlation coefficients exceeding 0.7 for 85% of stations. Positive linear trends of sea level were estimated for both datasets, with good agreement in most cases. The averaged linear trend of SLAs in the SCS showed a rise of 4.4 ± 0.3 mm year−1 during 1993–2016, consistent with the nonlinear trend of satellite and tide gauge (4.3 ± 0.3 and 3.9 ± 0.1 mm year−1, respectively) extracted through empirical mode decomposition.
@article{fu_estimation_2019,
title = {Estimation of sea level variability in the {South} {China} {Sea} from satellite altimetry and tide gauge data},
issn = {0273-1177},
url = {http://www.sciencedirect.com/science/article/pii/S0273117719304910},
doi = {10.1016/j.asr.2019.07.001},
abstract = {Sea level variability in the South China Sea (SCS) was investigated by means of satellite altimetry and tide gauge data over a 24 years period 1993–2016. The sea level anomalies (SLAs) retrieved from satellite and tide gauge data were compared. The differences between the two datasets showed a normal distribution with 87\% within ±10 cm. Considering the individual time series, the results revealed that satellite and tide gauge SLAs are in good agreement, with root mean square deviations in the range 0.9–9.9 cm (average value is 2.7 cm), and correlation coefficients exceeding 0.7 for 85\% of stations. Positive linear trends of sea level were estimated for both datasets, with good agreement in most cases. The averaged linear trend of SLAs in the SCS showed a rise of 4.4 ± 0.3 mm year−1 during 1993–2016, consistent with the nonlinear trend of satellite and tide gauge (4.3 ± 0.3 and 3.9 ± 0.1 mm year−1, respectively) extracted through empirical mode decomposition.},
language = {en},
urldate = {2019-12-09},
journal = {Advances in Space Research},
author = {Fu, Yanguang and Zhou, Xinghua and Zhou, Dongxu and Li, Jie and Zhang, Wanjun},
month = aug,
year = {2019},
keywords = {Satellite altimetry, Sea level anomaly, Sea level variability, Spatiotemporal analysis, The South China Sea}
}
Downloads: 0
{"_id":"bHX644ZwR2spyzKrv","bibbaseid":"fu-zhou-zhou-li-zhang-estimationofsealevelvariabilityinthesouthchinaseafromsatellitealtimetryandtidegaugedata-2019","authorIDs":[],"author_short":["Fu, Y.","Zhou, X.","Zhou, D.","Li, J.","Zhang, W."],"bibdata":{"bibtype":"article","type":"article","title":"Estimation of sea level variability in the South China Sea from satellite altimetry and tide gauge data","issn":"0273-1177","url":"http://www.sciencedirect.com/science/article/pii/S0273117719304910","doi":"10.1016/j.asr.2019.07.001","abstract":"Sea level variability in the South China Sea (SCS) was investigated by means of satellite altimetry and tide gauge data over a 24 years period 1993–2016. The sea level anomalies (SLAs) retrieved from satellite and tide gauge data were compared. The differences between the two datasets showed a normal distribution with 87% within ±10 cm. Considering the individual time series, the results revealed that satellite and tide gauge SLAs are in good agreement, with root mean square deviations in the range 0.9–9.9 cm (average value is 2.7 cm), and correlation coefficients exceeding 0.7 for 85% of stations. Positive linear trends of sea level were estimated for both datasets, with good agreement in most cases. The averaged linear trend of SLAs in the SCS showed a rise of 4.4 ± 0.3 mm year−1 during 1993–2016, consistent with the nonlinear trend of satellite and tide gauge (4.3 ± 0.3 and 3.9 ± 0.1 mm year−1, respectively) extracted through empirical mode decomposition.","language":"en","urldate":"2019-12-09","journal":"Advances in Space Research","author":[{"propositions":[],"lastnames":["Fu"],"firstnames":["Yanguang"],"suffixes":[]},{"propositions":[],"lastnames":["Zhou"],"firstnames":["Xinghua"],"suffixes":[]},{"propositions":[],"lastnames":["Zhou"],"firstnames":["Dongxu"],"suffixes":[]},{"propositions":[],"lastnames":["Li"],"firstnames":["Jie"],"suffixes":[]},{"propositions":[],"lastnames":["Zhang"],"firstnames":["Wanjun"],"suffixes":[]}],"month":"August","year":"2019","keywords":"Satellite altimetry, Sea level anomaly, Sea level variability, Spatiotemporal analysis, The South China Sea","bibtex":"@article{fu_estimation_2019,\n\ttitle = {Estimation of sea level variability in the {South} {China} {Sea} from satellite altimetry and tide gauge data},\n\tissn = {0273-1177},\n\turl = {http://www.sciencedirect.com/science/article/pii/S0273117719304910},\n\tdoi = {10.1016/j.asr.2019.07.001},\n\tabstract = {Sea level variability in the South China Sea (SCS) was investigated by means of satellite altimetry and tide gauge data over a 24 years period 1993–2016. The sea level anomalies (SLAs) retrieved from satellite and tide gauge data were compared. The differences between the two datasets showed a normal distribution with 87\\% within ±10 cm. Considering the individual time series, the results revealed that satellite and tide gauge SLAs are in good agreement, with root mean square deviations in the range 0.9–9.9 cm (average value is 2.7 cm), and correlation coefficients exceeding 0.7 for 85\\% of stations. Positive linear trends of sea level were estimated for both datasets, with good agreement in most cases. The averaged linear trend of SLAs in the SCS showed a rise of 4.4 ± 0.3 mm year−1 during 1993–2016, consistent with the nonlinear trend of satellite and tide gauge (4.3 ± 0.3 and 3.9 ± 0.1 mm year−1, respectively) extracted through empirical mode decomposition.},\n\tlanguage = {en},\n\turldate = {2019-12-09},\n\tjournal = {Advances in Space Research},\n\tauthor = {Fu, Yanguang and Zhou, Xinghua and Zhou, Dongxu and Li, Jie and Zhang, Wanjun},\n\tmonth = aug,\n\tyear = {2019},\n\tkeywords = {Satellite altimetry, Sea level anomaly, Sea level variability, Spatiotemporal analysis, The South China Sea}\n}\n\n","author_short":["Fu, Y.","Zhou, X.","Zhou, D.","Li, J.","Zhang, W."],"key":"fu_estimation_2019","id":"fu_estimation_2019","bibbaseid":"fu-zhou-zhou-li-zhang-estimationofsealevelvariabilityinthesouthchinaseafromsatellitealtimetryandtidegaugedata-2019","role":"author","urls":{"Paper":"http://www.sciencedirect.com/science/article/pii/S0273117719304910"},"keyword":["Satellite altimetry","Sea level anomaly","Sea level variability","Spatiotemporal analysis","The South China Sea"],"downloads":0},"bibtype":"article","biburl":"https://cloud.ifremer.fr/index.php/s/R8DnHuvz2f4W30w/download","creationDate":"2021-02-02T15:37:07.526Z","downloads":0,"keywords":["satellite altimetry","sea level anomaly","sea level variability","spatiotemporal analysis","the south china sea"],"search_terms":["estimation","sea","level","variability","south","china","sea","satellite","altimetry","tide","gauge","data","fu","zhou","zhou","li","zhang"],"title":"Estimation of sea level variability in the South China Sea from satellite altimetry and tide gauge data","year":2019,"dataSources":["6ncyk75h5bp4X6eJE"]}