ERS‐1/2 orbit improvement using TOPEX/POSEIDON: The 2 cm challenge

Abstract

Abstract. The ERS orbit error reduction method using TOPEX/POSEIDON (T/P) data as a reference [Le Traon et al., 1995a] was applied to ERS-1 cycles from phases C, E, F, and G and to the first 16 cycles of the ERS-2 mission (phase A). T/P M-GDR (geophysical data record) (version C) and ERS-1/2 ocean product (OPR) data were used. ERS-1/2 orbits are the D-PAF (processing and archiving facility) orbits and, when necessary, ERS-1/2 altimetric corrections were updated to make the T/P and ERS-1/2 corrections homogeneous. The adjustment method has been refined, and formal error on the estimation is now calculated. The ERS-1/2 orbit error estimation is thus estimated to be precise to within about 2 cm root-mean-square (rms). E-E crossover differences are reduced from 12 to 17 cm to only 6.5 cm rms for all processed cycles. Similarly, the T/P-E crossover differences are reduced from 11 to 14 cm to only 7 cm rms. The adjusted D-PAF orbit error varies between 6 and 12 cm rms. The adjustment has also been performed for the Joint Gravity Model 3(JGM 3) orbits of ERS-1 phases C, E, and F. The rms difference between the corrected orbits for the D-PAF and JGM 3 orbits is only about 1 cm rms, while it is about 11 cm before T/P orbit error correction. This shows that the adjustment is almost insensitive to the initial ERS-1 orbit used. It also confirms the 2 cm precision of the method. We also do repeat-track analysis on the 35 day repeat cycles of ERS-1 phase C. The mean difference in sea level variance before and after orbit error correction is 34 cm 2 (D-PAF orbit) and 17 cm 2 (JGM 3 orbit). The corrected ERS-1 and T/P sea level variabilities, however, are in excellent agreement. The study thus shows that ERS-1/2 orbit error must be corrected before analyzing large-scale oceanic signals and combining ERS-1/2 with T/P data. The proposed method provides a very effective correction and thus significantly enhances the quality of ERS-1/2 data. Corresponding data sets will be distributed to the scientific community by Archiving, Validation, and

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