Liu Yanchun

Influence of Tide Models on the Use of Altimetry Data to Research Sea Level Anomaly

A tide model (named DN1.0), which contains 12 principal constituents over China seas and the Northwest Pacific is estimated by along-track harmonic analysis with TOPEX/Poseidon altimetry data taken from 1993 to 2002. CSR3.0, FES95.2 and DN1.0 are used respectively to detide the data for the time series of sea level anomaly (SLA) in the Yellow Sea, East China Sea, South China Sea and Northwest Pacific. The SLA curves and the power spectral density show that the major components that exist in SLA in China seas arise from the error of the tide models.

Rank-Defect Adjustment Model for Survey-Line Systematic Errors in Marine Survey Net

In this paper, the structure of systematic and random errors in marine survey net are discussed in detail and the adjustment method for observations of marine survey net is studied, in which the rank-defect characteristic is discovered first up to now. On the basis of the survey-line systematic error model, the formulae of the rank-defect adjustment model are deduced according to modern adjustment theory. An example of calculations with really observed data is carried out to demonstrate the efficiency of this adjustment model. Moreover, it is proved that the semi-systematic error correction method used at present in marine gravimetry in China is a special case of the adjustment model presented in this paper.

Comparisons of Three Inversion Approaches for Recovering Gravity Anomalies From Altimeter Data

One of the major applications of satellite altimetry is to recover gravity information. In this paper, three methods (i.e., analytical and numerical inversion of the stokes formula, and the inverse Vening Meinesz formula) for deriving gravity anomalies from altimeter data are developed and studied in detail. The three formulae are implemented using fast Fourier transform (FFT) technique. And a series of modified spherical 2D FFT formula for the computation of gravity anomaly have been proposed in this step. Then they are compared and tested using synthetic data from an ultra high degree geopotential model MOD99c to degree and order 1440. The stability of the three approaches is investigated using simulated data, and many numerical tests are done to quantify the feature of the three approaches. Finally, the three formulae are employed to compute gravity anomalies over the South China Sea using geoidal undulations and deflections from Seasat, Geosat, ERS-1 and TOPEX/POSEIDON (T/P) satellite altimetry. And the estimated gravity anomalies are compared to marine gravity data from shipboard measurements in the studied area.

A Modified Method for Recovering Bathymetry from Altimeter Data

At present, there exist two types of methods to recover the bathymetry from altimeter data, i.e. the deterministic method and the stochastic one. This paper first reviews the general principles of the two aforementioned methods in order to form the basis for the development of the new approach. Then, based on the theory of least-squares collocation, a modified statistical model for recovering bathymetry from altimeter data is proposed. The new model is used to compute the ocean depth in the South China Sea from altimetry-derived gravity anomalies. Finally the predicted depths are compared to the shipborne ones. The results show that the achievable agreement is very good. Taking into account the existence of errors in the shipborne depths, it can be believed that the relative error of altimetry-derived depths reaches the level of about 7%.

Data fusion technique for multibeam echosoundings

On the basis of an analysis of the error sources in multibeam echosounding system, a data processing method for compensating systematic errors in multibeam survey is proposed. In order to improve the accuracy of overall swath, a data fusion technique using single beam survey data as control information for single beam and multibeam echosounding is then presented. Some questions involved in solving the adjustment problem, such as its feasibility and the numerical stability, are discussed in detail, and a two-step adjustment method is suggested. Finally, a practical survey data set is used as a case study to prove the efficiency and reliability of the proposed methods.