This dataset contains level 1b altimetry data from the Synthetic Aperture Radar Altimeter (SRAL) aboard the European Space Agency (ESA) Sentinel 3B Satellite. Sentinel 3B was launched on the 25th of April 2018. These level 1b products are geo-located and fully calibrated multi-looked High-Resolution power echoes. Complex echoes (In-phase (I) and Quadrature (Q)) for the Low-Resolution Mode (LRM) and/or Synthetic Aperture Radar (SAR) mode both for C Band and Ku band. When the altimeter is in SAR mode, this product also contains the so-called Pseudo LRM (PLRM) echoes. All Sentinel-3 Non-Time Critical (NTC) products are available in less than 30 days. Data are provided by ESA and are made available via CEDA to any registered user.

This dataset contains level 1b (L1B-S) altimetry data from the Synthetic Aperture Radar Altimeter (SRAL) aboard the European Space Agency (ESA) Sentinel 3A Satellite. Sentinel 3A was launched on the 16th of February 2016. These data are fully SAR-processed and calibrated High-Resolution (HR) complex echoes arranged in stacks after slant range correction and prior to echo multi-look (multi-look processing reduces noise by averaging of adjacent pixels, and thereby reduces the standard deviation of the noise level). The L1B-S HR product contains information from Doppler beams data. Hence, it has only been defined for the Synthetic Aperture Radar (SAR) processing chain. The Doppler beams associated with a given surface location (also called stack data) are formed through the selection of all the beams that illuminate a given surface location, and that contribute to each L1B HR waveform. Beams are the result of applying Doppler processing to the waveform bursts, which allows division of the conventional altimeter footprint into a certain number of stripes, thus creating a Delay Doppler Map (DDM). With this, contributions coming from different stripes can be identified and collected separately. When all the contributions from different bursts are collected, a stack is formed. The stack waveforms are provided in In-phase (I) and Quadrature-phase (I/Q) samples (complex waveforms) in the frequency domain. Apart from the Doppler processing, the beams of a stack have also been fully calibrated and range aligned. The L1B-S also includes characterisation parameters about the stack itself. The time tag is given at each surface location (defined throughout the L1 processing chain). Data are provided by ESA and are made available via CEDA to any registered user.

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.

This dataset contains various global lake products (1992-2019) produced by the European Space Agency (ESA) Lakes Climate Change Initiative (Lakes_cci) project. This is version 1.1 of the dataset. 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.