This product integrates sea level observations aggregated and validated from the Regional EuroGOOS consortium (Arctic-ROOS, BOOS, NOOS, IBI-ROOS, MONGOOS) and Black Sea GOOS as well as from the Global telecommunication system (GTS) used by the Met Offices. The latest version of Copernicus delayed-mode Sea level product is also distributed from Copernicus Marine catalogue.

Rapid changes in ocean circulation and climate have been observed in marine-sediment and ice cores over the last glacial period and deglaciation, highlighting the non-linear character of the climate system and underlining the possibility of rapid climate shifts in response to anthropogenic greenhouse gas forcing. To date, these rapid changes in climate and ocean circulation are still not fully explained. One obstacle hindering progress in our understanding of the interactions between past ocean circulation and climate changes is the difficulty of accurately dating marine cores. Here, we present a set of 92 marine sediment cores from the Atlantic Ocean for which we have established age-depth models that are consistent with the Greenland GICC05 ice core chronology, and computed the associated dating uncertainties, using a new deposition modeling technique. This is the first set of consistently dated marine sediment cores enabling paleoclimate scientists to evaluate leads/lags between circulation and climate changes over vast regions of the Atlantic Ocean. Moreover, this data set is of direct use in paleoclimate modeling studies.

Until recently, classical radar altimetry could not provide reliable sea level data  within 10 km to the coast. However dedicated reprocessing of radar waveform  together with geophysical corrections adapted for the coastal regions now allows  to fill this gap at a large number of coastal sites. In the context of the Climate Change Initiative Sea Level project of the European Space Agency, we have recently performed a complete reprocessing of high resolution (20 Hz, i.e., 350m)  along-track altimetry data of the Jason-1, Jason-2 and Jason-3 missions over  January 2002 to June 2021 along the coastal zones of Northeast Atlantic,  Mediterranean Sea, whole African continent, North Indian Ocean, Southeast Asia,  Australia and North and South America. This reprocessing has provided valid sea  level data in the 0-20 km band from the coast. More than 1000 altimetry-based virtual coastal stations have been selected and sea level anomalies time series  together with associated coastal sea level trends have been computed over the study time span. In the coastal regions devoid from tide gauges  (e.g., African coastlines), these virtual stations offer a unique tool for estimating  sea level change close to the coast (typically up to 3 km to the coast but in many  instances up to 1 km or even closer). Results show that at most of the virtual  stations, the rate of sea level rise at the coast is similar to the rate offshore (15 km away from the coast). However, at some stations, the sea level rate in the last 3-4 km to the coast is either faster or slower than offshore.

Satellite altimetry missions provide a quasi-global synoptic view of sea level over more than 25 years. The satellite altimetry constellation is used to build sea level maps and regional sea level indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address some current climate science questions such as climate change detection and attribution or regional sea level budget closure for example. Previous studies have estimated the uncertainty for the global mean sea level (GMSL), but no uncertainty information is available at regional scales. In this study we estimate a regional satellite altimetry error budget and use it to derive maps of confidence intervals for local sea rise rates and accelerations. We analyze 27 years of satellite altimetry maps and derive the satellite altimetry error variance-covariance matrix at each grid point, prior to the estimation of confidence intervals on local trends and accelerations at the 90% confidence level using extended least squares estimators. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr-1 with local values ranging from 0.78 to 1.22 mm.yr-1. For accelerations, uncertainties range from 0.057 to 0.12 mm.yr-2, with a mean value of 0.063 mm.yr-2.   Change history: - 2020/07/08: initial dataset submission over 1993-2018 - 2020/10/21: 1993-2019 update and addition of error levels

Hydrodynamics and sediment dynamics hindcast in the Gironde Estuary (France), produced by coupling the hydrodynamics model MARS3D (with sediment dynamics module MUSTANG) and wave spectral model WAVEWATCH III®.

Times series of water level at four stations of the Gironde Estuary (Pointe de Grave, Le Marquis, Bordeaux and Cadillac) for the the years 1953, 1971, 1982, 1994, 2005 and 2014. The dataset includes all of the time seris used in the publication: To what extent multidecadal changes in morphology and fluvial discharge impact tide in a convergent (turbid) tidal river (2018), Journal of Geophysical Research: Oceans.

Satellite altimeters routinely supply sea surface height (SSH) measurements which are key observations to monitor ocean dynamics. However, below a wavelength of about 70 km, along-track altimeter measurements are often characterized by a dramatic drop in the signal-to-noise ratio, making it very challenging to fully exploit available altimeter observations to precisely analyze small mesoscale variations in SSH. Although various approaches have been proposed and applied to identify and filter noise from measurements, no distinctive methodology emerged to be systematically applied in operational products. To best cope with this unresolved issue, the Copernicus Marine Environment Monitoring Service (CMEMS) actually provides simple band-pass filtered data to mitigate noise contamination in the along-track SSH signals and more innovative and adapted noise filtering methods are thus left to users seeking to unveil small-scale altimeter signals. Here demonstrated, a fully data-driven approach is developed and applied to provide robust estimates of noise-free Sea Level Anomaly (SLA) signals. The method combines Empirical Mode Decomposition (EMD), to help analyze non-stationary and non-linear processes, and an adaptive noise filtering technique inspired by Discrete Wavelet Transform (DWT) decompositions. It is now found to best resolve the distribution of the sea surface height variability in the mesoscale 30-120 km wavelength band. A practical uncertainty variable is attached to the denoised SLA estimates that accounts for errors related to the local signal to noise ratio, but also for uncertainties in the denoising process, which assumes that SLA variability results in part from a stochastic process. Here, measurements from the Jason-3, Sentinel-3 A and SARAL/AltiKa altimeters are processed and analyzed, and their energy spectral and seasonal distributions characterized in the small mesoscale domain. Anticipating data from the upcoming Surface Water and Ocean Topography (SWOT) mission, these denoised SLA measurements for three reference altimeter missions already yield valuable opportunities to assess global small mesoscale kinetic energy distributions. This dataset was developed within the Ocean Surface Topography Science Team (OSTST) activities. A grant was awarded to the SASSA (Satellite Altimeter Short-scale Signals Analysis) project by the TOSCA board in the framework of the CNES/EUMETSAT call CNES-DSP/OT 12-2118. Altimeter data were provided by the Copernicus Marine Environment Monitoring Service (CMEMS) and by the Sea State Climate Change Initiative (CCI) project.

This dataset is an aggregation of all availale in situ data from Coriolis and Copernicus in situ data centres, observed in the French DCSMM area. It contains 5167 NetCDF CF files from 1903 to 2017. Each file contains the observations of a specific platform (e.g. vessel, mooring site, sea level station). Observed parameters are temperature, salinity, pressure, oxygen, nitrate, chlorophyll (and other bio-geo-chemicals), current, wave, sea level, river flow.  

The SWOT L3_LR_SSH product provides ocean topography measurements obtained from the SWOT KaRIn and nadir altimeter instruments, merged into a single variable. The dataset includes measurements from KaRIn swaths on both sides of the image, while the measurements from the nadir altimeter are located in the central columns. In the areas between the nadir track and the two KaRIn swaths, as well as on the outer edges of each swath (restricted to cross-track distances ranging from 10 to 60 km), default values are expected. SWOT L3_LR_SSH is a cross-calibrated product from multiple missions that contains only the ocean topography content necessary for thematic research (e.g., oceanography, geodesy) and related applications. This product is designed to be simple and ready-to-use, and can be combined with other altimetry missions. The SWOT L3_LR_SSH product is a research-orientated extension of the L2_LR_SSH product, distributed by the SWOT project (NASA/JPL and CNES). SWOT L3_LR_SSH is managed by the SWOT Science Team project DESMOS. The "Expert" version of SWOT L3_LR_SSH (the "Basic" version is the subject of a separate metadata sheet) includes each algorithm, correction, or external model incorporated into the SWOT L3_LR_SSH product as a separate layer. In addition to the SSH anomalies, this "Expert" version also includes mean dynamic topography (as in the "Basic" version), backscatter coefficient (sigma0), mean sea surface and geostrophic currents (absolute and anomalies).

Global mean sea level is an integral of changes occurring in the climate system in response to unforced climate variability as well as natural and anthropogenic forcing factors. Its temporal evolution allows detecting changes (e.g., acceleration) in one or more components. Study of the sea level budget provides constraints on missing or poorly known contributions, such as the unsurveyed deep ocean or the still uncertain land water component. In the context of the World Climate Research Programme Grand Challenge entitled “Regional Sea Level and Coastal Impacts”, an international effort involving the sea level community worldwide has been recently initiated with the objective of assessing the various data sets used to estimate components of the sea level budget during the altimetry era (1993 to present). These data sets are based on the combination of a broad range of space-based and in situ observations, model estimates and algorithms. Evaluating their quality, quantifying uncertainties and identifying sources of discrepancies between component estimates is extremely useful for various applications in climate research. This effort involves several tens of scientists from about sixty research teams/institutions worldwide (www.wcrp-climate.org/grand-challenges/gc-sea-level). The results presented in this paper are a synthesis of the first assessment performed during 2017-2018. We present estimates of the altimetry-based global mean sea level (average rate of 3.1 +/- 0.3 mm/yr and acceleration of 0.1 mm/yr2 over 1993-present), as well as of the different components of the sea level budget. We further examine closure of the sea level budget, comparing the observed global mean sea level with the sum of components. Ocean thermal expansion, glaciers, Greenland and Antarctica contribute by 42%, 21%, 15% and 8% to the global mean sea level over the 1993-present. We also study the sea level budget over 2005-present, using GRACE-based ocean mass estimates instead of sum of individual mass components. Results show closure of the sea level budget within 0.3 mm/yr. Substantial uncertainty remains for the land water storage component, as shown in examining individual mass contributions to sea level.