These gridded products are produced from the along-track (or Level-3) SEA LEVEL products (DOI: doi.org/10.48670/moi-00147) delivered by the Copernicus Marine Service (CMEMS, marine.copernicus.eu) for satellites SARAL/AltiKa, Cryosat-2, HaiYang-2B, Jason-3, Copernicus Sentinel-3A&B, Sentinel 6A, SWOT nadir, and SWOT Level-3 KaRIn sea level products (DOI: https://doi.org/10.24400/527896/A01-2023.018). Three mapping algorithms are proposed: MIOST, 4DvarNET, 4DvarQG: - the MIOST approach which give the global SSH solutions: the MIOST method is able of accounting for various modes of variability of the ocean surface topography (e.g., geostrophic, barotrope, equatorial waves dynamic …) by constructing several independent components within an assumed covariance model. - the 4DvarNET approach for the regional SSH solutions: the 4DvarNET mapping algorithm is a data-driven approach combining a data assimilation scheme associated with a deep learning framework. - the 4DvarQG approach for the regional SSH solutions: the 4DvarQG mapping technique integrates a 4-Dimensional variational (4DVAR) scheme with a Quasi-Geostrophic (QG) model. References: - Ballarotta, M., Ubelmann, C., Bellemin-Laponnaz, V., Le Guillou, F., Meda, G., Anadon, C., Laloue, A., Delepoulle, A., Faugère, Y., Pujol, M.-I., Fablet, R., and Dibarboure, G., 2024: Integrating wide swath altimetry data into Level-4 multi-mission maps, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2024-2345 - Beauchamp, M., Febvre, Q., Georgenthum, H., and Fablet, R., 2023: 4DVarNet-SSH: end-to-end learning of variational interpolation schemes for nadir and wide-swath satellite altimetry, Geosci. Model Dev., 16, 2119–2147, https://doi.org/10.5194/gmd-16-2119-2023 - Fablet, R., Beauchamp, M., Drumetz, L., and Rousseau, F., 2021: Joint Interpolation and Representation Learning for Irregularly Sampled Satellite-Derived Geophysical Fields, Front. Appl. Math. Stat., 7, 655224, https://doi.org/10.3389/fams.2021.655224 - Le Guillou, F., Metref, S., Cosme, E., Ubelmann, C., Ballarotta, M. Le Sommer, J. Verron, J., 2021: Mapping Altimetry in the Forthcoming SWOT Era by Back-and-Forth Nudging a One-Layer Quasigeostrophic Model, J. Atmos. Oceanic Technol., 38, 697–710, https://doi.org/10.1175/JTECH-D-20-0104.1 - Ubelmann, C., Dibarboure, G., Gaultier, L., Ponte, A., Ardhuin, F., Ballarotta, M., & Faugère, Y., 2021: Reconstructing ocean surface current combining altimetry and future spaceborne Doppler data. Journal of Geophysical Research: Oceans, 126, e2020JC016560. https://doi.org/10.1029/2020JC016560

Multimission altimeter satellite gridded sea surface heights and derived variables computed with respect to a twenty-year mean. Previously distributed by Aviso+, no change in the scientific content. All the missions are homogenized with respect to a reference mission. The acquisition of various altimeter data is a few days at most. The sla is computed with a non-centered computation time window (6 weeks before the date).

Monomission altimeter satellite along-track sea surface heights computed with respect to a twenty-year mean. Previously distributed by Aviso+, no change in the scientific content. All the missions are homogenized with respect to a reference mission which is currently OSTM/Jason-2. The sla is computed with an optimal and centered computation time window (6 weeks before and after the date). Two kinds of datasets are proposed: filtered (nominal dataset) and unfiltered.

Monomission altimeter product: OSTM/Jason-2. These products were produced by CLS in the framework of the Pistach project, funded by Cnes.

Barystatic and manometric sea level changes represent the mass component of sea level changes at global and regional scales respectively. Barystatic and manometric sea level changes are estimated here using the sea level budget approach combining satellite altimetry with in situ measurements of the seawater temperature and salinity. This sea level budget approach is adapted from Barnoud et al., (2023). Two products are distributed over the January 1993 to December 2020 period: - Barystatic sea level changes from sea level budget with uncertainties at 1-sigma: monthly time series, - Manometric sea level changes from sea level budget with uncertainties at 1-sigma: monthly grids with 1 degree spacing.

For the Global Ocean - Monomission altimeter satellite along-track sea surface heights computed with respect to a twenty-year mean. Previously distributed by Aviso+, no change in the scientific content. All the missions are homogenized with respect to a reference mission which is currently Jason-3. The acquisition of various altimeter data is a few days at most. The sla is computed with a non-centered computation time window (6 weeks before the date).

GDR L2 from ESA Baseline-C converted by CTOH into netCDF, splited by ascending/descending pass and augmented of recent corrections

The global mean level of the oceans is one of the most important indicators of climate change. It incorporates the reactions from several different components of the climate system. Precise monitoring of changes in the mean level of the oceans, particularly through the use of altimetry satellites, is vitally important, for understanding not just the climate but also the socioeconomic consequences of any rise in sea level.

Les variations barystatiques et manométriques du niveau marin représentent la composante de masse des variations du niveau marin aux échelles globale et régionale respectivement. Les variations barystatiques et manométriques du niveau marin sont estimées ici à partir de la gravimétrie, issues des mesures des missions de gravimétrie spatiale GRACE et GRACE - Follow On. Deux produits sont distribués sur la période avril 2002 à août 2022 : - Les variations barystatiques du niveau de la mer à partir de la gravimétrie : séries temporelles mensuelles, - Les variations manométriques du niveau de la mer à partir de la gravimétrie : grilles mensuelles 1x1°. Les variations BARYSTATIQUES du niveau marin représentent les échanges de masses d’eau des continents aux océans et vice versa. La fonte des calottes polaires et des glaciers continentaux constituent les principales sources de variation du niveau barystatique. A l'échelle interannuelle, les échanges d'eau douce avec les grands bassins hydrologiques (par exemple l'Amazone, Mississippi) sont également importants. Les changements MANOMETRIQUES du niveau de la mer sont dus à plusieurs processus, incluant la circulation océanique et atmosphériques, les empreintes du niveau de la mer (sea level fingerprints en anglais) ou le cycle global de l'eau. Les modes climatiques, tels que l'oscillation australe d'El Niño, l'oscillation arctique, l'oscillation nord-atlantique ou le mode annulaire austral, influencent également de manière significative les changements manométriques du niveau de la mer Pfeffer et al., 2022). Les missions GRACE et GRACE Follow-On surveillent les variations temporelles du champ de gravité de façon quasi continue depuis 2002. De nombreux centres distribuent des solutions temporelles du potentiel gravitationnel de la Terre, fournies sous forme de coefficients de Stokes, connues sous le nom de solutions de niveau-2. Les solutions de niveau-2 doivent être corrigées de plusieurs effets géophysiques et erreurs instrumentales, converties en anomalies de masse de surface et projetées sur l'ellipsoïde. Les grilles d'anomalies de masse de surface qui en résultent, après application des corrections appropriées, sont appelées solutions de niveau-3. Plusieurs sources d'erreurs affectent les solutions des niveaux 2 et 3, imposées par la configuration du satellite, les erreurs instrumentales et les incertitudes dans les corrections géophysiques utilisées pour traiter les mesures. L'approche d'ensemble de Blazquez et al. (2018) est utilisée pour estimer de manière robuste les changements manométriques et barystatiques du niveau de la mer et leurs incertitudes. Références bibliographique - Blazquez, A., Meyssignac, B., Lemoine, J.-M., Berthier, E., Ribes, A., Cazenave, A. (2018). Exploring the uncertainty in GRACE estimates of the mass redistributions at the Earth surface: implications for the global water and sea level budgets, Geophysical Journal International, 215 (1), 415–430, https://doi.org/10.1093/gji/ggy293 - Pfeffer, J., Cazenave, A. & Barnoud, A. (2022). Analysis of the interannual variability in satellite gravity solutions: detection of climate modes fingerprints in water mass displacements across continents and oceans. Clim Dyn 58, 1065–1084. https://doi.org/10.1007/s00382-021-05953-z

Multimission altimetry-derived gridded from Ssalto/Duacs products backward-in-time Finite Size Lyapunov Exponents and Orientations of associated eigenvectors