Sea Level Variations Inferred From GRACE,Altimetry And Thermohaline Data

Sea level has been rising in the past 100 years,which has created great challenges to the production and life of people living in coastal low-altitude areas.The main factors leading to sea level variations(SLV)are the steric SLV and the mass-induced SLV.Satellite altimetry technology can provide accurate overall sea level variations.GRACE data can be used to invert mass-induced SLV,and thermohaline data can be used to calculate steric SLV.This paper combines satellite altimetry data,GRACE satellite data and temperature and salt data to study global and South China Sea level variations.The specific content and results of this thesis are summarized as follows:(1)The development of sea level measurement and results of previous research are briefly described.The theory and method of using GRACE temporal gravity field model to invert mass-induced SLV and temperature and salt data to calculate steric SLV are analyzed in detail.Some analysis methods commonly used in data post-processing are highlighted,including time series analysis,correlation analysis and principal component analysis.(2)Using satellite altimetry data,GRACE satellite gravity data and oceanographic data to study global sea level variations over the past decade,which proves that the three measurement methods are in good agreement with each other.The rates of mean SLV inferred from altimetry is 2.4�0.8mm/a.The rates of mass-induced SLV inferred from GRACE 1.4�0.2mm/a and The rates of steric SLV 0.9�0.4 mm/a.This result shows that the mass-induced SLV is the main factor for the global sea level variation.The contribution of bipolar ice sheet ablation to sea level is about 0.7mm/a by GRACE calculation,which is the main factor for global seawater quality variations.The study found that ENSO has a significant effect on the interannual variation of global sea level,especially in the equatorial Pacific.(3)We study the the South China Sea using satellite gravity data,satellite altimeter data,and thermohaline data.The results show that compared with the global mean sea level rising rate,the rising rate of South China Sea is very fast.And the sea level variation in the South China Sea is mainly modulated by the steric SLV.Principal component analysis was used to extract the first mode associated with ENSO in the interannual signals of the South China Sea.The sea level of the South China Sea declined during El Ni?o and rose during La Ni?a.The relationship between sea level in the South China Sea and global sea level change is analyzed.It is found that the global sea level modulates the sea level of the South China Sea through the variation of seawater quality.The characteristics of the South China Sea sea level are mainly from the steric SLV caused by the variation of thermohaline.