Inferring deep ocean tidal energy dissipation from the global high‐resolution data‐assimilative HAMTIDE model

Taguchi, E.; Stammer, Detlef; Zahel, W.

doi:10.1002/2013jc009766

Cited by 92 publications

(69 citation statements)

References 64 publications

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“…The bottom topography was derived from the bedrock version of the fully global ETOPO1 database (Amante and Eakins 2009) by choosing average values over each model grid cell and setting depths between 10-m and the 0-m land–sea boundary to 10 m. Coastlines in the Antarctic come from a recent data-assimilative ocean model (Taguchi et al. 2014) and are similar to those of Padman et al. (2002), with the cavities under the floating ice shelves considered as part of the ocean domain; cf.…”

Section: Numerical Modeling Of the Oceanic S Tidesupporting

confidence: 90%

The Global S $$_1$$ 1 Tide in Earth’s Nutation

et al. 2016

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Diurnal S tidal oscillations in the coupled atmosphere–ocean system induce small perturbations of Earth’s prograde annual nutation, but matching geophysical model estimates of this Sun-synchronous rotation signal with the observed effect in geodetic Very Long Baseline Interferometry (VLBI) data has thus far been elusive. The present study assesses the problem from a geophysical model perspective, using four modern-day atmospheric assimilation systems and a consistently forced barotropic ocean model that dissipates its energy excess in the global abyssal ocean through a parameterized tidal conversion scheme. The use of contemporary meteorological data does, however, not guarantee accurate nutation estimates per se; two of the probed datasets produce atmosphere–ocean-driven S terms that deviate by more than 30 as (microarcseconds) from the VLBI-observed harmonic of as. Partial deficiencies of these models in the diurnal band are also borne out by a validation of the air pressure tide against barometric in situ estimates as well as comparisons of simulated sea surface elevations with a global network of S tide gauge determinations. Credence is lent to the global S tide derived from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) and the operational model of the European Centre for Medium-Range Weather Forecasts (ECMWF). When averaged over a temporal range of 2004 to 2013, their nutation contributions are estimated to be as (MERRA) and as (ECMWF operational), thus being virtually equivalent with the VLBI estimate. This remarkably close agreement will likely aid forthcoming nutation theories in their unambiguous a priori account of Earth’s prograde annual celestial motion.

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Section: Numerical Modeling Of the Oceanic S Tidesupporting

confidence: 90%

The Global S $$_1$$ 1 Tide in Earth’s Nutation

et al. 2016

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“…2011), EOT10a/11a(Savcenko and Bosch 2008), FES2004/2012(Lyard et al 2006), GOT4.7 (Ray 1999, HAMTIDE(Taguchi et al 2014), TPXO7.1/7.2/8(Egbert and Erofeeva 2002), VCE and WCE models (in this study). Pelagic and coastal tide gauges were used where bilinear interpolation of the model tidal constants are possible for all current ocean tide models.…”

mentioning

confidence: 50%

Data fusion of multisatellite altimetry for ocean tides modelling: a spatio-temporal approach with potential oceanographic applications

Fok

2015

International Journal of Image and Data Fusion

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To cite this article: Hok Sum Fok (2015) Data fusion of multisatellite altimetry for ocean tides modelling: a spatio-temporal approach with potential oceanographic applications, International Journal of Image and Data Fusion, 6:3, 232-248, Nowadays, data combination/fusion is a common practice to integrate multiple data sources into a spatially and/or temporally regular data set for facilitating analysis and interpretation. Given the advancement in active remote sensing for monitoring our changing environment (no matter ocean, land or ice), the data acquisition from various spaceborne platforms with different spatio-temporal resolutions is enormous; calling for a need of multisatellite data combination. Instead of equally or spatially weighted solution, this article illustrates a spatio-temporal combination approach that weights data both in space and in time simultaneously for ocean tide modelling using multisatellite altimetry data sets under different spatial and temporal resolutions. The tide models generated from this approach show substantial improvement near coastal regions when compared to other contemporary ocean tide models by using independent pelagic and coastal tide gauges serving as ground truth. The discrepancy of the best model is~23%, three times larger than that of the deep ocean. Further improvement lies in more and better spatio-temporal observations in the near future. We anticipate this approach can be applied to other spatio-temporal data in a similar settings for spatio-temporal dependent unknown parameters, including geodetic, geophysical, oceanographic data and imagery under different spatial and temporal resolutions.

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“…HAMTIDE12 model is based on the generalized inverse methods for tides, developed at the University of Hamburg (Taguchi et al 2014). The principle of the HAMTIDE12 is the direct minimization of the model deficiency and the inaccuracy of the recordings in a least square sense, resulting to solve the over determined algebraic equations and so called normal equation, respectively.…”

Section: Hamtide12mentioning

confidence: 99%

Accuracy Assessment of Recent Global Ocean Tide Models Around Antarctica

Lei

Zhang

Hao

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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ABSTRACT:Due to the coverage limitation of T/P-series altimeters, the lack of bathymetric data under large ice shelves, and the inaccurate definitions of coastlines and grounding lines, the accuracy of ocean tide models around Antarctica is poorer than those in deep oceans. Using tidal measurements from tide gauges, gravimetric data and GPS records, the accuracy of seven state-of-the-art global ocean tide models (DTU10、EOT11a、GOT4.8、FES2012、FES2014、HAMTIDE12、TPXO8) is assessed, as well as the most widely-used conventional model FES2004. Four regions (Antarctic Peninsula region, Amery ice shelf region, Filchner-Ronne ice shelf region and Ross ice shelf region) are separately reported. The standard deviations of eight main constituents between the selected models are large in polar regions, especially under the big ice shelves, suggesting that the uncertainty in these regions remain large. Comparisons with in situ tidal measurements show that the most accurate model is TPXO8, and all models show worst performance in Weddell sea and Filchner-Ronne ice shelf regions. The accuracy of tidal predictions around Antarctica is gradually improving.

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Inferring deep ocean tidal energy dissipation from the global high‐resolution data‐assimilative HAMTIDE model

Cited by 92 publications

References 64 publications

The Global S $$_1$$ 1 Tide in Earth’s Nutation

The Global S $$_1$$ 1 Tide in Earth’s Nutation

Data fusion of multisatellite altimetry for ocean tides modelling: a spatio-temporal approach with potential oceanographic applications

Accuracy Assessment of Recent Global Ocean Tide Models Around Antarctica

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