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Maxime Ballarotta
,
Clément Ubelmann
,
Marine Rogé
,
Florent Fournier
,
Yannice Faugère
,
Gérald Dibarboure
,
Rosemary Morrow
, and
Nicolat Picot

1. Introduction The production of accurate sea surface height (SSH) maps is a major challenge for the ocean remote sensing community. Near-real-time and delayed-time multimission reference altimetric SSH maps are distributed by the AVISO+ ( https://www.aviso.altimetry.fr/en/home.html ) and the Copernicus Marine Environment Monitoring Service (CMEMS; http://marine.copernicus.eu/ ) portals and are widely adopted for maritime operation managements, for understanding the ocean surface circulations

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G. Dibarboure
,
F. Boy
,
J. D. Desjonqueres
,
S. Labroue
,
Y. Lasne
,
N. Picot
,
J. C. Poisson
, and
P. Thibaut

1. Introduction a. Context and objectives Satellite radar altimetry is used to observe a wide range of spatial scales, ranging from basin scale to small mesoscale, that is, less than 100 km. For multialtimeter maps [e.g., Archiving, Validation, and Interpretation of Satellite Oceanographic data (AVISO)/Data Unification and Altimeter Combination System (DUACS) from Le Traon et al. 2003 ; Dibarboure et al. 2011 ] the main limitation is in the cross-track direction, and it stems from the number

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Edward D. Zaron

1. Introduction Satellite altimetry has enriched our understanding of ocean dynamics by providing a sustained and near-global view of mean sea level and mesoscale eddies during the last 25 years ( Fu and Cazenave 2001 ). It is now widely used in ocean forecasting ( Willis et al. 2010 ), and it is contributing to a broad range of research on ocean and climate processes ( Łyszkowicz and Bernatowicz 2017 ). Studies of ocean tides have been invigorated by the unique datasets generated with

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Megan Jeramaz Lickley
,
Carling C. Hay
,
Mark E. Tamisiea
, and
Jerry X. Mitrovica

they are defined relative to different coordinate systems. Both GRACE and altimetry measurements are tied to the International Terrestrial Reference Frame (ITRF; e.g., Altamimi et al. 2016 ) through data processing. Nominally, for long-term changes considered in this manuscript, this should place the measurements in a center of mass (CM) frame. [On shorter time scales, the altimetry measurements may be more aligned with a center of figure (CF) frame (e.g., Melachroinos et al. 2013 ; Ray et al

Open access
Zhongxiang Zhao

. 2020 ; Olbers et al. 2020 ; Pollmann et al. 2019 ; Savage et al. 2020 ; Shakespeare 2020 ; Vic et al. 2021 ; Zhao 2021 ). Among them, satellite altimetry observes the global two-dimensional internal tide field from space, thanks to its near-global coverage ( Dushaw 2015 ; Ray and Zaron 2016 ; Zhao et al. 2016 ; Zaron 2019a ; Ubelmann et al. 2022 ). Previous estimates of internal tides from satellite altimetry are usually based on about 25 years of SSH measurements made by exact

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John Lillibridge
,
Remko Scharroo
,
Saleh Abdalla
, and
Doug Vandemark

.0 GHz. The primary frequency for previous satellite radar altimeters has been at Ku band: 13.5–13.8 GHz. There are several advantages for Ka-band altimetry: smaller antenna, reduced sensitivity to ionospheric path delay, and higher along-track spatial resolution with lower range noise. However, there is one serious drawback: increased sensitivity to water vapor and liquid water in the atmosphere. At Ka band there is more attenuation of the radar signal from moisture than at Ku band, with the

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Edward D. Zaron
and
Shane Elipot

frequencies (for altimetry) and Lagrangian sampling (for drifters) makes it problematic to compute accurate tidal harmonic constants from these data, which would provide the best information for comparing with tide models. Instead, a variance reduction statistic, the explained variance, is used to compare the models; however, interpreting this statistic requires attention to the influence of signals that are correlated with the tides of interest. Stammer et al. (2014) compared three different types of

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R. D. Ray
,
S. B. Luthcke
, and
T. van Dam

1. Introduction Correcting satellite altimeter measurements for ocean tidal loading—that is, for the elastic deformation of the solid earth induced by the weight of the overlying ocean tide—is a standard part of altimetry data processing ( Francis and Mazzega 1990 ). Correcting altimetry for loading by other geophysical fluids has rarely been considered, a notable exception being a study by Kuo et al. (2008) . In part this neglect has persisted because other fluids were so poorly known, at

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Edward D. Zaron
,
Ruth C. Musgrave
, and
Gary D. Egbert

1. Introduction In a series of papers, Egbert and Ray (2000 , 2001 , 2003 ) combined satellite altimetry data with a global dynamical tide model to infer the rate of tidal energy dissipation in the ocean. They found that about 1/3 of the semidiurnal dissipation, and 1/10 of the diurnal dissipation, occurs in the deep ocean, presumably through the generation of baroclinic tides at underwater topography, and their work prompted a reinterpretation of earlier investigations that had

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G. Abessolo Ondoa
,
R. Almar
,
B. Castelle
,
L. Testut
,
F. Léger
,
Z. Sohou
,
F. Bonou
,
E. W. J. Bergsma
,
B. Meyssignac
, and
M. Larson

energetic hydrodynamic conditions reduce the possibility to observe a range of processes, such as total coastal sea level fluctuations. There is a need for observations of sea level at the coast ( Cazenave et al. 2018 ; Melet et al. 2018 ). More than in other geosciences, nearshore research historically faces difficulties in investigating the complex and energetic environment. Satellite altimetry, optimized for the open ocean, performs poorly within 25 km of the coast since landmasses perturb the radar

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