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dc.contributor.authorGuo Jin-Yunen_US
dc.contributor.authorWang Jian-Boen_US
dc.contributor.authorHu Zhi-Boen_US
dc.contributor.authorHwang, Cheinwayen_US
dc.contributor.authorChen Chuan-Faen_US
dc.contributor.authorGao Yong-Gangen_US
dc.date.accessioned2015-12-02T02:59:31Z-
dc.date.available2015-12-02T02:59:31Z-
dc.date.issued2015-09-01en_US
dc.identifier.issn0001-5733en_US
dc.identifier.urihttp://dx.doi.org/10.6038/cjg20150908en_US
dc.identifier.urihttp://hdl.handle.net/11536/128295-
dc.description.abstractVariations of sea level are an important issue associated with global climate change, especially global warming. The sea level rising may lead to serious impact on the social-economic development of a country. Global oceans are continuously observed by altimetry satellite missions for more than 20 years. We use altimeter data of TOPEX/Poseidon (T/P), Jason-1 and Jason-2 from 1993 to 2012 to study the sea level change over China seas. China seas located in the western Pacific Ocean are selected as the study area. T/P MGDR data of 11 to 364 cycles span January 1993 to August 2002. Jason-1 GDR data of 1 to 259 cycles span January 2002 to January 2009. Jason-2 GDR data of 1 to 165 cycles span July 2008 to December 2012. Southern oscillation index (SOT) time series span January 1993 to December 2012. Altimetry data in the tandem stages are used to calibrate biases of sea level anomalies (SLAs) from T/P, Jason-1 and Jason-2 point by point. The spatial distribution of China seas\' level change is studied with the continuous tension spline method. Temporal variations of China seas\' level are analyzed with the linear fitting method and the wavelet analysis. Relationships between the El Nino-Southern Oscillation (ENSO) and sea level changes of the South China Sea and the East China Sea are studied with the correlation analysis. By unifying altimetry data point by point in tandem stages, the mean differences of sea level heights for Jason-1 vs T/P and Jason-2 vs Jason-1 are 0. 21 cm and 0. 03 cm, respectively. SLA time series are constructed after corrections of sea level biases from 1993 to 2012. In general, the mean SLA is positive over China seas. SLAs are higher in the south than those in the north, and lower in the west than those in the east. SLAs are negative over the western Bohai Sea, the northern Yellow Sea, the northern Taiwan Strait and the North Bay. SLAs rise with the increasing longitude and decrease with the growing latitude. This spatial distribution of SLAs over China seas is related to the water flux, sea surface wind stress, oceanic dynamics, monsoon, Kuroshio and ENSO. The mean rising rate of sea level for the 20 years is 4. 64 mm . a(-1) over the whole study area. Sea levels are rising in the Bohai Sea, Yellow Sea, East China Sea and South China Sea with rising rates 4. 44 mm . a(-1), 2. 37 mm . a(-1), 3. 02 mm . a(-1) and 4. 25 mm . a(-1), respectively. The annual sea level variation is obvious in the study area. The sea level is higher in summer and autumn than in winter and spring. The main cycles of sea level change include one year and 9 years over the whole seas. There are also minor cycles of 0. 5 years, 1. 5 years, 2 years and 4 years. Cyclical changes of sea level are related to the geographical position, climate, oceanic dynamics and submarine topography. The correlation coefficients between SOIs and SLAs of the South China Sea and the East China Sea are 0.39 and 0.02, respectively. The correlation coefficient is 0. 44 after the two-month delay for the South China Sea. The correlation coefficient is 0. 17 after the four-month delay for the East China Sea. This indicates that the sea level change over the South China Sea may be largely affected by ENSO. Altimetry data of T/P, Jason-1 and Jason-2 are processed to study the sea level change over China seas from 1993 to 2012. We used the altimetry data in tandem stages to calibrate the sea level biases of these three missions to achieve the seamless SLAs point by point. The spatial distribution of sea level change is given with the continuous tension spline method. The sea level is generally rising at the mean rate of 4. 64 mm . a(-1) over China seas in these 20 years. The sea level variations change with different seas and seasons. The mean rising rates are 4. 44 mm . a(-1), 2. 34 mm . a(-1), 3. 02 mm . a(-1) and 4. 25 mm . a(-1) over Bohai Sea, Yellow Sea, East China Sea and South China Sea, respectively. Temporal-spatial change of sea level over the study area is related to oceanic dynamics, submarine topography, monsoon, Kuroshio and ENSO. The main cycles of sea level change are one year and 9 years as derived from the wavelet analysis. El Nino and La Nina events make stronger effects on sea level variations over the South China Sea than the other seas.en_US
dc.language.isoen_USen_US
dc.subjectSatellite altimetryen_US
dc.subjectChina seasen_US
dc.subjectSea level changeen_US
dc.subjectTOPEX/Poseidonen_US
dc.subjectJason-1en_US
dc.subjectJason-2en_US
dc.titleTemporal-spatial variations of sea level over China seas derived from altimeter data of TOPEX/Poseidon, Jason-1 and Jason-2 from 1993 to 2012en_US
dc.typeArticleen_US
dc.identifier.doi10.6038/cjg20150908en_US
dc.identifier.journalCHINESE JOURNAL OF GEOPHYSICS-CHINESE EDITIONen_US
dc.citation.volume58en_US
dc.citation.spage3103en_US
dc.citation.epage3120en_US
dc.contributor.department土木工程學系zh_TW
dc.contributor.departmentDepartment of Civil Engineeringen_US
dc.identifier.wosnumberWOS:000362059900008en_US
dc.citation.woscount0en_US
Appears in Collections:Articles