TOPEX Constrained Solution of Mean Sea Surface by Joint Processing of TOPEX, ERS-1 and GEOSAT Altimetric Measurements

We present an improved crossover adjustment procedure to determine mean sea surface height using TOPEX, 35-day repeat phase ERS-1, Geosat, and 168-day repeat phase ERS-1 satellite altimeter data. The mean sea surface frame defined by the TOPEX data is imposed as certain constraints in our crossover adjustment procedure rather than held fixed as in some other procedures. The new procedure is discussed in detail. Equations are developed to incorporate the a priori information of Topex data as well as other satellite altimeter data. The numerical computation result shows that the rms crossover discrepancies are reduced by an order of 1 cm when the Topex data is not fixed. Furthermore, the computed mean sea surface is less noisy and more realistic than that computed by the traditional procedure.     

Effect of Sea Level Variability on the Estimation of Mean Sea Surface Gradients

It is demonstrated that an along-track mean sea surface (MSS) model estimated with TOPEX altimeter data, including the large 1997-1998 El Niño event, is slightly less accurate than a MSS model calculated from less data where El Niño signals are small. The manner in which true sea level variability corrupts the estimation of MSS gradients is discussed. A model is proposed to reduce the error, based on scaling climate indices such as the Southern Oscillation Index, while accounting for phase shifts using a Hilbert transform. After modeling and removing the seasonal and interannual sea level variations, parameters to a plane MSS model are estimated using TOPEX altimeter data from January 1993 to June 2000. Results indicate an overall improvement over the earlier model based on four years of data, and no apparent degradation due to aliasing of sea level variability.     

Dependence of Mean Sea Surfaces from Altimeter Data on the Reference Model Used

A mean sea surface model is used as the frame of reference in processing altimeter data. This article focuses on ascertaining the extent to which results depend on the different mean sea surface models used. In particular, we have analyzed the results from the OSU95MSS and the CLS_SHOMv.98.2 models in an area in the North Atlantic Ocean comprising the Canary and Azores Islands. Special attention has been paid to data editing and several criteria were proposed. The amount of detected data is quite small because we used a well corrected data set. However, it was enough to show important relations between the applied criteria and the kind of area. Therefore we analyzed the best way to apply these criteria according to the areas where the points have been found. Singular areas related to several factors have been detected by all the suggested criteria. In particular, rough sea bottom features, dynamic circulation, and amphidromic points of the tidal waves, among others. As a result of this analysis, we have not considered it appropriate to remove all the detected points. Two time-averaged and corrected mean sea surfaces were determined in the test area.     

Dependence of Mean Sea Surfaces from Altimeter Data on the Reference Model Used

A mean sea surface model is used as the frame of reference in processing altimeter data. This article focuses on ascertaining the extent to which results depend on the different mean sea surface models used. In particular, we have analyzed the results from the OSU95MSS and the CLS_SHOMv.98.2 models in an area in the North Atlantic Ocean comprising the Canary and Azores Islands. Special attention has been paid to data editing and several criteria were proposed. The amount of detected data is quite small because we used a well corrected data set. However, it was enough to show important relations between the applied criteria and the kind of area. Therefore we analyzed the best way to apply these criteria according to the areas where the points have been found. Singular areas related to several factors have been detected by all the suggested criteria. In particular, rough sea bottom features, dynamic circulation, and amphidromic points of the tidal waves, among others. As a result of this analysis, we have not considered it appropriate to remove all the detected points. Two time-averaged and corrected mean sea surfaces were determined in the test area.     

Gravity, Mean Sea Surface, and Bathymetry Models Comparison in the Canary Islands

In geodetic and oceanographic studies generally, some reference surfaces are needed. These surfaces must represent as much as possible the gravity field of the Earth and the height/bathymetry systems. In the last years, several gravimetric, bathymetric, and mean sea surface models have appeared. Analyzing them it is possible to see that there are significant discrepancies between the models provided by different authors or organizations; there are also differences between the models and data obtained by independent measurements. We present the analysis of such differences and determine the most representative choice of models, in our opinion, for the Canary Islands region.     

Gravity,Mean Sea Surface,and Bathymetry Models Comparison in the Canary Islands

In geodetic and oceanographic studies generally, some reference surfaces are needed. These surfaces must represent as much as possible the gravity field of the Earth and the height/bathymetry systems. In the last years, several gravimetric, bathymetric, and mean sea surface models have appeared. Analyzing them it is possible to see that there are significant discrepancies between the models provided by different authors or organizations; there are also differences between the models and data obtained by independent measurements. We present the analysis of such differences and determine the most representative choice of models, in our opinion, for the Canary Islands region.     

An intercomparison of GEOSAT, TOPEX and ERS1 measurements of wind speed and wave height

Mean monthly values of altimeter wind speed and wave height are compared with data from NDBC buoys. As a result of these comparisons, corrections are made to the raw data products available from these satellites. Data from the GEOSAT, TOPEX and ERS1 missions corrected in this fashion are used to show that there have been no measurable changes in the global wind and wave climate during the 10 years spanned by these various missions. It is proposed that the corrected values of wind speed and wave height provide the basis for the formation of a long-term global data base which spans the periods of these multiple missions.     

Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea Revealed by Satellite Altimetric Data

Temporal and spatial variations of sea surface circulation in the South China Sea were revealed with use of altimetric data provided by TOPEX/POSEIDON from December 1992 to October 1997. The estimated distribution of sea surface dynamic heights from altimetric data coincide well with the results of observation by Soong et al. (1995) and Chu et al. (1998). The RMS variability of sea surface dynamic height, which is obtained after tidal correction based on Yanagi et al. (1997), is high in the central part of the South China Sea, the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand. The high RMS variability in the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand is due to set up and set down of sea water by the East Asian monsoon, which is northeasterly during winter and southwesterly during summer. Also, the high RMS variability in the central part of the South China Sea is due to the variations of basin-wide circulation. The circulations are dominant in the central part of the South China Sea during summer and winter, an anticyclonic circulation during summer and a cyclonic circulation during winter. It is suggested that these circulations are controlled by the East Asian monsoon. Hence, there is an interannual variability of the basin-wide circulation associated with the variation of the East Asian monsoon.