The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 4 (L4) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, gridded over a global regular cylindrical projection (1°x1° resolution), averaging valid and good measurements from all available altimeters on a monthly basis (using the L2P products also available). These L4 products are meant for statistics and visualization. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2021 ( Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 2P (L2P) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution, separated per satellite and pass, including all measurements with flags, corrections and extra parameters from other sources. These are expert products with rich content and no data loss. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions spanning from 2002 to 2022021 (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

In recent years, large datasets of in situ marine carbonate system parameters (partial pressure of CO2 (pCO2), total alkalinity, dissolved inorganic carbon and pH) have been collated. These carbonate system datasets have highly variable data density in both space and time, especially in the case of pCO2, which is routinely measured at high frequency using underway measuring systems. This variation in data density can create biases when the data are used, for example for algorithm assessment, favouring datasets or regions with high data density. A common way to overcome data density issues is to bin the data into cells of equal latitude and longitude extent. This leads to bins with spatial areas that are latitude and projection dependent (eg become smaller and more elongated as the poles are approached). Additionally, as bin boundaries are defined without reference to the spatial distribution of the data or to geographical features, data clusters may be divided sub-optimally (eg a bin covering a region with a strong gradient). To overcome these problems and to provide a tool for matching in situ data with satellite, model and climatological data, which often have very different spatiotemporal scales both from the in situ data and from each other, a methodology has been created to group in situ data into ‘regions of interest’, spatiotemporal cylinders consisting of circles on the Earth’s surface extending over a period of time. These regions of interest are optimally adjusted to contain as many in situ measurements as possible. All in situ measurements of the same parameter contained in a region of interest are collated, including estimated uncertainties and regional summary statistics. The same grouping is done for each of the other datasets, producing a dataset of matchups. About 35 million in situ datapoints were then matched with data from five satellite sources and five model and re-analysis datasets to produce a global matchup dataset of carbonate system data, consisting of 287,000 regions of interest spanning 54 years from 1957 to 2020. Each region of interest is 100 km in diameter and 10 days in duration. An example application, the reparameterisation of a global total alkalinity algorithm, is shown. This matchup dataset can be updated as and when in situ and other datasets are updated, and similar datasets at finer spatiotemporal scale can be constructed, for example to enable regional studies. This dataset was funded by ESA Satellite Oceanographic Datasets for Acidification (OceanSODA) project which aims at developing the use of satellite Earth Observation for studying and monitoring marine carbonate chemistry.

The ESA Sea State Climate Change Initiative (CCI) project has produced global daily merged multi-sensor time-series of along-track satellite altimeter significant wave height data (referred to as Level 3 (L3) data) with a particular focus for use in climate studies. This dataset contains the Version 3 Remote Sensing Significant Wave Height product, which provides along-track data at approximately 6 km spatial resolution. It has been generated from upstream Sea State CCI L2P products, edited and merged into daily products, retaining only valid and good quality measurements from all altimeters over one day, with simplified content (only a few key parameters). This is close to what is delivered in Near-Real Time by the CMEMS (Copernicus - Marine Environment Monitoring Service) project. It covers the date range from 2002-2021. The altimeter data used in the Sea State CCI dataset v3 come from multiple satellite missions (Envisat, CryoSat-2, Jason-1, Jason-2, Jason-3, SARAL, Sentinel-3A), therefore spanning over a shorter time range than version 1.1. Unlike version 1.1, this version 3 involved a complete and consistent retracking of all the included altimeters. Many altimeters are bi-frequency (Ku-C or Ku-S) and only measurements in Ku band were used, for consistency reasons, being available on each altimeter but SARAL (Ka band).

In order to better characterize the genetic diversity of Cetaceans and especially the common Dolphin from the Bay of Biscay, sequences from the mitochondrial Cytochrome B region were obtained from water samples acquired close to groups of dolphins.

The SARWAVE project is developing a new sea state processor from SAR images to be applied over open ocean, sea ice, and coastal areas, and exploring potential synergy with other microwave and optical EO products.

The ESA Sea State Climate Change Initiative (CCI) project has produced global multi-sensor time-series of along-track satellite synthetic aperture radar (SAR) integrated sea state parameters (ISSP) data from ENVISAT (referred to as SAR Wave Mode onboard ENVISAT Level 2P (L2P) ISSP data) with a particular focus for use in climate studies. This dataset contains the ENVISAT Remote Sensing Integrated Sea State Parameter product (version 1.1), which forms part of the ESA Sea State CCI version 3.0 release. This product provides along-track significant wave height (SWH) measurements at 5km resolution every 100km, processed using the Li et al., 2020 empirical model, separated per satellite and pass, including all measurements with flags and uncertainty estimates. These are expert products with rich content and no data loss. The SAR Wave Mode data used in the Sea State CCI SAR WV onboard ENVISAT Level 2P (L2P) ISSP v3 dataset come from the ENVISAT satellite mission spanning from 2002 to 2012.

The French Atlantic coast hosts numerous macrotidal and turbid estuaries that flow into the Bay of Biscay that are natural corridors for migratory fishes. The two best known are those of the Gironde and the Loire. However, there are also a dozen estuaries set geographically among them, of a smaller scale. The physico-chemical quality of estuarine waters is a necessary support element for biological life and determines the distribution of species, on which many ecosystem services (e.g. professional or recreational fishing) depend. With rising temperatures and water levels, declining precipitation and population growth projected for the New Aquitaine region by 2030, the question of how the quality and ecological status of estuarine waters will evolve becomes increasingly critical. The MAGEST (Mesures Automatisées pour l’observation et la Gestion des ESTuaires nord aquitains) high-frequency monitoring of key physico-chemical parameters was first developed in the Gironde estuary in 2004 ; the Seudre and Charente estuaries were instrumented late 2020. First based on real-time automated systems, MAGEST is now equipped by autonomous multiparameter sensors. Depending of the stations, an optode is also deployed to secure dissolved oxygen measurement. By the end of 2020, MAGEST had 12 instrumented sites. Portets is a measuring station located in the upper Gironde estuary (Garonne subestuary, about 20 km upstream of the Bordeaux metropolis.

The ClimateFish database collates abundance data of 15 fish species proposed as candidate indicators of climate change in the Mediterranean Sea. An initial group of eight Mediterranean indigenous species (Epinephelus marginatus, Thalassoma pavo, Sparisoma cretense, Coris julis, Sarpa salpa, Serranus scriba, Serranus cabrilla and Caranx crysos) with wide distribution, responsiveness to temperature conditions and easy identification were selected by a network of Mediterranean scientists joined under the CIESM programme ‘Tropical Signals’ (https://www.ciesm.org/marine/programs/tropicalization.htm; Azzurro et al. 2010). Soon after, and thanks to the discussion with other expert groups and projects, C. crysos was no longer considered, and Lessepsian fishes (Red Sea species entering the Mediterranean through the Suez Canal) were included, namely: Fistularia commersonii, Siganus luridus, Siganus rivulatus, Pterois miles, Stephanolopis diaspros, Parupeneus forskali, Pempheris rhomboidea and Torquigener flavimaculosus. Considering the trend of increase of these species in the Mediterranean Sea (Golani et al. 2021) and their projected distribution according to climate change scenarios (D’Amen and Azzurro, 2020), more data on these tropical invaders are expected to come in the future implementation of the study. Data were collected according to a simplified visual census methodology (Garrabou et al. 2019) along standard transects of five minutes performed at a constant speed of 10m/min, corresponding approximately to an area of 50x5m. Four different depth layers were surveyed:  0-3m, 5-10 m, 11-20 m, 21-30 m. So far, the ClimateFish database includes fish counts collected along 3142 transects carried out in seven Mediterranean countries between 2009 and 2021, for a total number of 101'771 observed individuals belonging to the 15 fish species. Data were collected by a large team of researchers which joined in a common monitoring strategy supported by different international projects, which are acknowledged below. This database, when associated with climate data, offers new opportunities to investigate spatio-temporal effects of climate change in the Mediterranean Sea and test the effectiveness of each species as a possible climate change indicator.   Contacts: ernesto.azzurro(at)cnr.it   References: Azzurro E., Maynou F., Moschella P. (2010). A simplified visual census methodology to detect variability trends of coastal mediterranean fishes under climate change scenarios. Rapp. Comm. int. Mer Médit., 39. D’Amen, M. and Azzurro, E. (2020). Lessepsian fish invasion in Mediterranean marine protected areas: a risk assessment under climate change scenarios. ICES Journal of Marine Science, 77(1), pp.388-397. Garrabou, J., Bensoussan, N., Azzurro, E. (2019). Monitoring climate-related responses in Mediterranean marine protected areas and beyond: five standard protocols. Golani D.,  Azzurro E.,  Dulčić J.,  Massutí E., Orsi-Relini L.  (2021).  Atlas of Exotic Fishes in the Mediterranean Sea.  2nd edition  [F. Briand, Ed.]  365 pages.  CIESM Publishers, Paris, Monaco. ISBN number  978-92-990003-5-9   

This data set is related to the article "Improving the robustness of dissipation rate estimates from microstructure shear data processing in ocean turbulence" (submitted to JTech, AMS). It provides the raw data files (with extension .p) from a vertical microstructure profiler VMP-6000 used for the published study. Raw data files are provided since the study precisely report on the data processing of raw microstructure horizontal velocity shear data to get dissipation rates of turbulent kinetic energy using the manufacturer software. The software (ODAS) can be downloaded from the manufacturer website at: https://rocklandscientific.com. The profiles were collected in the Mediterranean Sea in 2013 (French VAD cruise) and 2014 (Italian MEDOCC cruise), and in the North Atlantic Ocean in 2021 (MoMAR cruise). More details on the profiles are given in the related publication.