Treatment of ocean tide aliasing in the context of a next generation gravity field mission
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Monthly ocean bottom pressure solutions from the Gravity Recovery and Climate Experiment (GRACE), derived using surface spherical cap mass concentration (MC) blocks and spherical harmonics (SH) basis functions, are compared to tide gauge (TG) monthly averaged sea level data over 2003–2015 to evaluate improved gravimetric data processing methods near the coast. MC solutions can explain ≳ 42 per cent of the monthly variance in TG time-series over broad shelf regions and in semi-enclosed marginal seas. MC solutions also generally explain ~ 5–32 per cent more TG data variance than SH estimates. Applying a coastline resolution improvement algorithm in the GRACE data processing leads to ~ 31 per cent more variance in TG records explained by the MC solution on average compared to not using this algorithm. Synthetic observations sampled from an ocean general circulation model exhibit similar patterns of correspondence between modelled TG and MC time-series and differences between MC and SH time-series in terms of their relationship with TG time-series, suggesting that observational results here are generally consistent with expectations from ocean dynamics. This work demonstrates the improved quality of recent MC solutions compared to earlier SH estimates over the coastal ocean, and suggests that the MC solutions could be a useful tool for understanding contemporary coastal sea level variability and change.
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Abstract The recovery of ocean tides from satellite altimetry, an attractive alternative to the hydrodynamical‐numerical approach, is investigated to create a global model of the M2 tide. From the outline of the difficulties faced in altimetry interpretation, we bring out general guidelines to extract the tidal information from a short span of measurements. In particular, we discuss the choice of a reference surface and the effect of the orbit error and tidal aliasing on the recovery. From space‐time harmonic analyses of twenty‐four days of SEASAT altimetry, we derive M2 solutions expanded into series of surface spherical harmonics for the Indian, Pacific, and Atlantic Oceans separately and for the world ocean. The M2 cotidal maps we obtain feature qualitatively realistic tidal patterns and are consistent with the deep sea gages data. We then cast the bases to estimate the error budget of the altimeter tide solutions. The M2 fundamental harmonics involved in tidal energetics are evaluated from a spectral convolution of the global solutions with the ocean function and are used to test and discuss our results. The present tidal recoveries must still be considered as preliminary trials because they are strongly dependent on the limits of the SEASAT mission and subject to improvements via an updating of our analysis procedure. But the altimeter approach of the open ocean tide modelling proves to be efficient, and the objective—to produce highly reliable models with the support of the next generation of satellite altimeters—is reasonably optimistic.
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Comparison of two different ocean tide models especially with respect to the GRACE satellite mission
(TYPE=abstract)The GRACE dual satellite mission (launched in March, 2002) offers the possibility of computing monthly highly accurate mean gravity fields over an expected lifetime of five years. Unfortunately, the quality of these monthly gravity field products does not yet reach the pre-launch expectations. Possible error sources might be insufficient instrument data processing and parameterization or modeling of short-term atmospheric and oceanic mass variations. Another candidate is the ocean tide model. Especially, incomplete subtraction (de-aliasing) of short period tides may be partially aliased into the monthly gravity field solutions. Therefore, we analyzed the difference of two ocean tide models (FES2004 and CSR 4.0) which are used at the GRACE Science Data System
level-2 processing centers at GFZ Potsdam and CSR (Center for Space Research, Austin), respectively, and which may serve as a measure of the ocean tide model error. We have computed: a) straightforward monthly means of tidal elevation differences and b) simulations of tidal elevation
differences at footpoints of GRACE A. The results of a) represent the differences of the monthly means of both tide models with respect to an uniform sampling (grid). The results of b) include the influence of spatially uneven sampling distribution (only along the orbit) and show that for the S2 and K2 tidal constituents, aliasing causes effects which cannot be neglected with respect to the presently achievable GRACE measurement accuracy for degrees
n.le.7 (S2) and n.le.8 (K2).
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SUMMARY Ocean tide (OT) background models (BMs) used for a priori de-aliasing of GRACE/GRACE-FO observations feature distinct spatial uncertainties (primarily in coastal proximity and in latitudes above ±60°), and therefore pose one of the largest contributors to the overall retrieval error. The retrieval performance can be expected to increase if this underlying spatial error distribution is stochastically modelled and incorporated into the data processing chain. In this contribution, we derive realistic error variance-covariance matrices (VCM) based on a set of five state-of-the-art OT models. The additional value of using such VCMs is assessed through numerical closed-loop simulations, where they are rigorously propagated from model to observation level. Further, different approximations of the resulting VCM of observations are assumed, that is full, block-diagonal and diagonal, in order to evaluate the trade-off between computational efficiency and accuracy. It is asserted that correctly weighting the OT BM error can improve the gravity retrieval performance by up to three orders of magnitude, provided no further error contributors are considered. In comparison, the overall gain in retrieval performance is reduced to 75 per cent once instrument noise is taken into account. Here, it is shown that simultaneously modelling the OT BM and the instrument errors is critical, as each effect induces different types of correlations between observations, and exclusively considering covariance information based on the sensor noise may degrade the solution. We further demonstrate that the additional benefit of incorporating OT error VCMs is primarily limited by the de-aliasing performance for non-tidal mass variations of atmosphere (A) and oceans (O). This emphasizes the necessity of best-possible AO-de-aliasing (e.g. through optimized processing techniques and/or improved BMs) in order to optimally exploit the OT BM weighting.
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