The dominant modes of recent sea level variability from 1993 to 2020 in the China Seas

Abstract

A better understanding of internal climatic variability is essential for estimating and predicting regional sea level rise in the coming decades. Based on the satellite altimeter data, the cyclostationary empirical orthogonal function (CSEOF) analysis is used to extract and examine the seasonal signal, trend, El Niño-Southern Oscillation (ENSO)-related, and low-frequency mode of sea level anomaly in the China Seas from 1993 to 2020. The interannual changes in the annual cycle of sea level were significantly influenced by the mean surface pressure and the 10-m zonal wind component. Furthermore, strong El Niño events (1997/1998) can significantly affect seasonal fluctuations through precipitation and runoff. By recombining the loading vector and principal component time series of the trend mode, we estimate the sea level trends to be about 3.63 ± 0.37 mm/yr. The South China Sea, followed by the Yellow Sea, is where ENSO's effects on sea level fluctuations are most noticeable. The 2015–2016 El Niño, which was a combination of the Central Pacific (CP) ENSO Eastern Pacific (EP) ENSO, had average sea levels that were much lower than those of the 1997–1998 (CP ENSO) and 2009–2010 (CP ENSO). The Pacific Decadal Oscillation (PDO) can significantly affect the low frequency mode, but other sources also contribute to this mode. The South China Sea, especially to the west of Luzon Island, exhibits the highest level of variability in the low-frequency mode. Finally, our work shows that, in contrast to global or oceanic scales, regional CSEOF analysis does, in fact, capture regional sea level variability more accurately and detailed.