Arctic Sea Level Variability from Oceanic Reanalysis and Observations

Quantifying the contributions to Arctic sea level(ASL)variability is critical to understand how the Arctic is responsing to ongoing climate change.Here,we use Ocean Reanalysis System 5(ORAS5)reanalysis data and tide gauge and satellite altimetry observations to quantify contributions from different physical processes on the ASL variability.The ORAS5 reanalysis shows that the ASL is rising with a trend of 2.5±0.3 mm yr−1(95%confidence level)over 1979-2018,which can be attributed to four components:(i)the dominant component from the global sea level increase of 1.9±0.5 mm yr−1,explaining 69.7%of the total variance of the ASL time series;(ii)the Arctic Oscillation-induced mass redistribution between the deep central basin and shallow shelves,with no significant trend and explaining 6.3%of the total variance;(iii)the steric sea level increase centering on the Beaufort Gyre region with a trend of 0.5±0.1 mm yr−1 and explaining 29.1%of the total variance of the ASL time series;and(iv)the intrusion of Pacific water into the Arctic Ocean,with no significant trend and contributing 14.2%of the total ASL variability.Furthermore,the dramatic sea ice melting and the larger area of open water changes the impact of the large-scale atmospheric forcing on the ASL variability after 1995,and the ocean dynamic circulation plays a more important role in the ASL variability.

A study of long-term sea level variability in the East China Sea

From the analyses of the satellite altimeter Maps of Sea Level Anomaly （MSLA） data, tidal gauge sea level data and historical sea level data, this paper investigates the long-term sea level variability in the East China Sea （ECS）. Based on the correlation analysis, we calculate the correlation coefficient between tidal gauge and the closest MSLA grid point, then generate the map of correlation coefficient of the entire ECS. The results show that the satellite altimeter MSLA data is effective to observe coastal sea level variability. An important finding is that from map of correlation coefficient we can identify the Kuroshio. The existence of Kuroshio decreases the correlation between coastal and the Pacific sea level. Kurishio likes a barrier or a wall, which blocks the effect of the Pacific and the global change. Moreover, coastal sea level in the ECS is mainly associated with local systems rather than global change. In order to calculate the long-term sea level variability trend, the empirical mode decomposition （EMD） method is applied to derive the trend on each MSLA grid point in the entire ECS. According to the 2-D distribution of the trend and rising rate, the sea level on the right side of the axis of Kuroshio rise faster than in its left side. This result supports the barrier effect of Kuroshio in the ECS. For the entire ECS, the average sea level rose 45.0 mm between 1993 and 2010, with a rising rate of （2.5_＋0.4） mm/a which is slower than global average. The relatively slower sea level rising rate further proves that sea level rise in the ECS has less response to global change due to its own local system effect.

A study of sea level variability and its long-term trend in the South China Sea

On the basis of the satellite maps of sea level anomaly（MSLA） data and in situ tidal gauge sea level data,correlation analysis and empirical mode decomposition（EMD） are employed to investigate the applicability of MSLA data,sea level correlation,long-term sea level variability（SLV） trend,sea level rise（SLR） rate and its geographic distribution in the South China Sea（SCS）.The findings show that for Dongfang Station,Haikou Station,Shanwei Station and Zhapo Station,the minimum correlation coefficient between the closest MSLA grid point and tidal station is 0.61.This suggests that the satellite altimeter MSLA data are effective to observe the coastal SLV in the SCS.On the monthly scale,coastal SLV in the western and northern part of SCS are highly associated with coastal currents.On the seasonal scale,SLV of the coastal area in the western part of the SCS is still strongly influenced by the coastal current system in summer and winter.The Pacific change can affect the SCS mainly in winter rather than summer and the affected area mostly concentrated in the northeastern and eastern parts of the SCS.Overall,the average SLR in the SCS is 90.8 mm with a rising rate of（5.0±0.4） mm/a during1993–2010.The SLR rate from the southern Luzon Strait through the Huangyan Seamount area to the Xisha Islands area is higher than that of other areas of the SCS.

Absolute sea level variability of Arctic Ocean in 1993–2018 from satellite altimetry and tide gauge observations

Arctic absolute sea level variations were analyzed based on multi-mission satellite altimetry data and tide gauge observations for the period of 1993–2018.The range of linear absolute sea level trends were found-2.00 mm/a to 6.88 mm/a excluding the central Arctic,positive trend rates were predominantly located in shallow water and coastal areas,and negative rates were located in high-latitude areas and Baffin Bay.Satellite-derived results show that the average secular absolute sea level trend was(2.53±0.42)mm/a in the Arctic region.Large differences were presented between satellite-derived and tide gauge results,which are mainly due to low satellite data coverage,uncertainties in tidal height processing and vertical land movement(VLM).The VLM rates at 11 global navigation satellite system stations around the Arctic Ocean were analyzed,among which 6 stations were tide gauge colocated,the results indicate that the absolute sea level trends after VLM corrected were of the same magnitude as satellite altimetry results.Accurately calculating VLM is the primary uncertainty in interpreting tide gauge measurements such that differences between tide gauge and satellite altimetry data are attributable generally to VLM.

Interannual modulation of intraseasonal sea level variability along the southern coast of Java

The intraseasonal variability(ISV) of sea level anomalies(SLAs) along the southern coast of Java and its interannual modulation were studied based on a gridded SLA product produced from the Archiving, Validation, and Interpretation of Satellite Oceanography dataset. This ISV is induced by the propagation of intraseasonal Kelvin waves derived from the central equatorial Indian Ocean(EIO). Wavelet analysis and empirical mode decomposition of intraseasonal SLAs along the southern coast of Java showed interannual variability, with weaker ISV events during El Ni years and positive Indian Ocean Dipole(IOD) years than during normal years. This interannual modulation of the ISV is influenced by the El Ni-Southern Oscillation teleconnection via the Walker Circulation and eastern Indian Ocean upwelling connected to IOD events. The anomalously weaker Walker Circulation during El Ni events generates anomalous surface easterlies over the central-eastern tropical Indian Ocean that produce upwelling Kelvin waves in the EIO and offshore water transport along the southern coasts of Sumatra and Java, resulting in negative SLAs along the southern coast of Java. These negative SLAs damp the positive SLAs induced by the eastward propagation of downwelling Kelvin waves from the central EIO during the following March–May of El Ni years. Similar features of SLAs and sea surface wind anomalies also occur during positive IOD years. Consequently, the sea level ISV along the southern coast of Java is weaker in El Ni and positive IOD years.

Interannual to decadal variation of spring sea level anomaly in the western South China Sea

Satellite observations of sea level anomalies(SLA) from January 1993 to December 2012 are used to investigate the interannual to decadal changes of the boreal spring high SLA in the western South China Sea(SCS) using the Empirical Orthogonal Function(EOF) method. We find that the SLA variability has two dominant modes. The Sea Level Changing Mode(SLCM) occurs mainly during La Ni?a years, with high SLA extension from west of Luzon to the eastern coast of Vietnam along the central basin of the SCS, and is likely induced by the increment of the ocean heat content. The Anticyclonic Eddy Mode(AEM) occurs mainly during El Ni?o years and appears to be triggered by the negative wind curl anomalies within the central SCS. In addition, the spring high SLA in the western SCS experienced a quasi-decadal change during 1993–2012; in other words, the AEM predominated during 1993–1998 and 2002–2005, while the La Ni?a-related SLCM prevailed during 1999–2001 and 2006–2012. Moreover, we suggest that the accelerated sea level rise in the SCS during 2005–2012 makes the SLCM the leading mode over the past two decades.

Subtidal variability in the Taiwan Strait induced by combined forcing of winter monsoon and topography

As an important channel connecting the East and South China Seas, circulations in the Taiwan Strait are strongly influenced by the East Asian monsoon and the topography of the strait, especially the Taiwan Bank(TWB), which is a remarkable topographic feature located at the southern entrance to the strait. Based on a series of pressure gauges deployed roughly 40 km offshore along the western Strait, subtidal sea-level variability under the combined impact of winter monsoon and topography was studied. The analyses show significant along-strait coherences of subtidal sea levels and their coherences with the large-scale monsoon wind for periods from 2 to 14 days. It is suggested that these fluctuations are mainly forced waves driven by the large-scale winds. In addition to the normal cross-shore wind setup, a sea-level setup in the along-strait direction is confirmed, which is induced by the combined forcing of the fluctuating winter monsoon and the blocking of the TWB. A southward current surge driven by a northerly wind event will cause a rising sea level over the TWB inducing a southward alongshore slope anomaly to the north of the TWB and a reversed slope anomaly to the south The subtidal current through the channel to the west of the TWB is found to be influenced by the reversed slope anomalies generated via the along-shore setup.