Contents: along-track sea surface heights above geoid; dynamic topography is the sum of sea level anomaly (SLA) and mean dynamic topography (MDT, Rio05 here) Use: study of the general circulation (ocean gyres ...) The data are global mono altimeter satellite products, homogeneous with other satellites, available in near-real time and in delayed time in NetCDF format. In delayed time, two types of products are available: - "Ref" (Reference) series: homogeneous datasets based on two satellites (Topex/Poseidon, Jason-1 + ERS, Envisat) with the same groundtrack. Sampling is stable in time. - "Upd" (Updated) series: up-to-date datasets with up to four satellites at a given time (adding GFO and/or Topex/Poseidon on its new orbit). Sampling and Long Wavelength Errors determination are improved, but quality of the series is not homogeneous. Regional products with an improved quality are available in local areas ("http://www.aviso.oceanobs.com/html/donnees/produits/hauteurs/regional/")

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• AVISO_ADT

SCIOPS Short Name: AVISO_ADT Version ID: Not provided Unique ID: C1214586177-SCIOPS

Station position and velocity solutions (weekly and cumulative) in Software INdependent EXchange (SINEX) format derived from analysis of Doppler Orbitography by Radiopositioning Integrated on Satellite (DORIS) data. The solutions include daily values of Earth Orientation Parameters (EOPs). These products are the generated by analysis centers in support of the International DORIS Service (IDS). Time series of station coordinate solutions in Station Coordinate Difference (STCD) are also generated by the IDS analysis centers. Weekly solutions represent the IDS contribution to the International Terrestrial Reference Frame (ITRF) determination.

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CDDIS Short Name: CDDIS_DORIS_products_positions Version ID: 1 Unique ID: C1000000020-CDDIS

Global Navigation Satellite System (GNSS) data consists of the U.S. Global Positioning System (GPS) and the Russian GLObal NAvigation Satellite System (GLONASS) (plus other international systems) data sets. The Global Positioning System, developed by the U.S. Department of Defense, has been fully operational since 1994. GPS consists of a constellation of 24 satellites and three active spares each traveling in a 12 hour circular orbit, 20,200 kilometers above the Earth. The satellites are positioned so that six are observable nearly 100 percent of the time from any point on the Earth. The GLObal NAvigation Satellite System (GLONASS), managed and deployed by the Russian Federation, is similar to the U. S. Global Positioning System (GPS) in terms of the satellite constellation, orbits, and signal structure. GNSS receivers detect, decode, and process signals from the GNSS satellites. The satellites transmit the ranging codes on two radio-frequency carriers, allowing the locations of GNSS r

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CDDIS Short Name: CDDIS_GNSS_satellite_data Version ID: 1 Unique ID: C1000000024-CDDIS

This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project.Lakes are of significant interest to the scientific community, local to national governments, industries and the wider public. A range of scientific disciplines including hydrology, limnology, climatology, biogeochemistry and geodesy are interested in distribution and functioning of the millions of lakes (from small ponds to inland seas), from the local to the global scale. Remote sensing provides an opportunity to extend the spatio-temporal scale of lake observation. The five thematic climate variables included in this dataset are:• Lake Water Level (LWL): a proxy fundamental to understand the balance between water inputs and water loss and their connection with regional and global climate changes.• Lake Water Extent (LWE): a proxy for change in glacial regions (lake expansion) and drought in many arid environments, water extent relates to local climate for the cooling effect that water bodies provide.• Lake Surface Water temperature (LSWT): correlated with regional air temperatures and a proxy for mixing regimes, driving biogeochemical cycling and seasonality. • Lake Ice Cover (LIC): freeze-up in autumn and advancing break-up in spring are proxies for gradually changing climate patterns and seasonality. • Lake Water-Leaving Reflectance (LWLR): a direct indicator of biogeochemical processes and habitats in the visible part of the water column (e.g. seasonal phytoplankton biomass fluctuations), and an indicator of the frequency of extreme events (peak terrestrial run-off, changing mixing conditions).Data generated in the Lakes_cci project are derived from data from multiple instruments and multiple satellites including; TOPEX/Poseidon, Jason, ENVISAT, SARAL, Sentinel, Landsat, ERS, Terra/Aqua, Suomi NPP, Metop and Orbview. For more information please see the product user guide in the documents.

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• 3c324bb4ee394d0d876fe2e1db217378

FEDEO Short Name: 3c324bb4ee394d0d876fe2e1db217378 Version ID: NA Unique ID: C2548142668-FEDEO

This dataset contains 17-year-long (June 2002 to May 2018 ), high-resolution (20 Hz), along-track sea level dataset in coastal zones of six regions: Mediterranean Sea, Northeast Atlantic, West Africa, North Indian Ocean, Southeast Asia and Australia. Up to now, satellite altimetry has provided global gridded sea level time series up to 10-15 km from the coast only, preventing the estimation of how sea level changes very close to the coast on interannual to decadal time scales. This dataset has been derived from the ESA SL_cci+ v1.1 dataset of coastal sea level anomalies (also available in the catalogue, DOI:10.5270/esa-sl_cci-xtrack_ales_sla-200206_201805-v1.1-202005), which is based on the reprocessing of raw radar altimetry waveforms from the Jason-1, Jason-2 and Jason-3 satellite missions to derive satellite-sea surface ranges as close as possible to the coast (a process called ‘retracking’) and optimization of the geophysical corrections applied to the range measurements to produce sea level time series. This large amount of coastal sea level estimates has been further analysed to produce the present dataset: it consists in a selection of 429 portions of satellite tracks crossing land for which valid sea level time series are provided at monthly interval together with the associated sea level trends over the 17-year time span at each along-track 20-Hz point, from 20 km offshore to the coast.The main objective of this dataset is to analyze the sea level trends close to the coast and compare them with the sea level trends observed in the open ocean and to determine the causes of the potential differences.The product has been developed within the sea level project of the extension phase of the European Space Agency (ESA) Climate Change Initiative (SL_cci+). See 'The Climate Change Coastal Sea Level Team (2020). Sea level anomalies and associated trends estimated from altimetry from 2002 to 2018 at selected coastal sites. Scientific Data (Nature), in press'.This dataset has a DOI: https://doi.org/10.17882/74354

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• a386504aa8ae492f9f2af04c109346e9

FEDEO Short Name: a386504aa8ae492f9f2af04c109346e9 Version ID: NA Unique ID: C2548142874-FEDEO