Catalogue PIGMA
Catalogue PIGMA (PIGMA)
Continents, countries, sea regions of the world.
Saint-Jean d'Illac : Plan Local d'Urbanisme (PLU)
Blue-Action - Arctic Impact on Weather and Climate is a Research and Innovation action.
Businesses, policymakers, and local communities need to access reliable weather and climate information to safeguard human health, wellbeing, economic growth, and environmental sustainability. However, important changes in climate variability and extreme weather events are difficult to pinpoint and account for in existing modelling and forecasting tools. Moreover, many changes in the global climate are linked to the Arctic, where climate change is occurring rapidly, making weather and climate prediction a considerable challenge. Blue-Action evaluated the impact of Arctic warming on the northern hemisphere and developed new techniques to improve forecast accuracy at sub-seasonal to decadal scales. Blue-Action specifically worked to understand and simulate the linkages between the Arctic and the global climate system, and the Arctic’s role in generating weather patterns associated with hazardous conditions and climatic extremes. In doing so, Blue-Action aimed to improve the safety and wellbeing of people in the Arctic and across the Northern Hemisphere, reduce the risks associated with Arctic operations and resource exploitation, and support evidence-based decision-making by policymakers worldwide.
Bycatch by pelagic towed gears in Europe Seas, Jan. 2020
The raster dataset represents fishing intensity (kilowatt per fishing hour) by pelagic towed gears in the European seas. The dataset has been derived from Automatic Identification System (AIS) based pelagic fishing intensity data received from the European Commission’s Joint Research Centre - Independent experts of the Scientific, Technical and Economic Committee for Fisheries (JRC STECF), as well as from Vessel Monitoring System (VMS) and logbook based pelagic fishing effort data from HELCOM Commission. The temporal extent varies between the data sources (between 2013 and 2015). The dataset has been transformed to a logarithmic scale (ln1). This dataset has been prepared for the calculation of the combined effect index, produced for the ETC/ICM Report 4/2019 "Multiple pressures and their combined effects in Europe's seas" available on: https://www.eionet.europa.eu/etcs/etc-icm/etc-icm-report-4-2019-multiple-pressures-and-their-combined-effects-in-europes-seas-1.
License CC-BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Copyright holder: European Environment Agency (EEA). Furthermore, and as a data product derived from pelagic fishing effort data downloaded from the HELCOM Map and Data service, it can be used freely given that the source is cited (ICES. 2017. Spatial data layers of fishing intensity/pressure per gear type for surface and subsurface abrasion, for the years 2009 and 2016 in the HELCOM area).
The dataset was created from Automatic Identification System (AIS) based pelagic fishing intensity data (temporal coverage: October 2014 – September 2015) received from the European Commission’s Joint Research Centre - Independent experts of the Scientific, Technical and Economic Committee for Fisheries (JRC STECF), as well as Vessel Monitoring System (VMS) and logbook based pelagic fishing effort data downloaded from HELCOM (Fishing effort midwater trawl 2013, metadata available on: http://metadata.helcom.fi/geonetwork/srv/eng/catalog.search#/metadata/49fe4828-be70-4108-9098-381690afa0cd). HELCOM data superseded the JRC STECF data where they overlapped spatially. The cell values have been transformed into a logarithmic scale (ln1).
Temperature of the water column | Temperature of the water body | International Council for the Exploration of the Sea (ICES) | IROC TimeSeries
486_Bathymetry_Bay of Biscay - Channel (DTM resolution : 1000m ; ed. : 2008)
The Digital Terrain Model of the Bay of Biscaye and of the Channel is the result of the processing of a compilation of single and multibeam echosounder data, of DTMs and of chart countours produced before 2008 for hydrodynamic modeling..
(c) Ifremer - SHOM 2010 Obligation of citation : Loubrieu B., Bourillet J.F., Moussat E.Bathy-morphologie régionale du Golfe de Gascogne et de la Manche, modèle numérique 2008 - Rapport interne Ifremer DCD/GM/CTDI/08-01. (c) SHOM 2006 Works carried out using data transmitted by Service Hydrographique et Océanographique de la Marine (contract E97-2006) - www.shom.fr - SHOM is not responsible of the results and of the use of the results. All rights reserved except for Research and Education.
Description of data processing : Data processing has been carried out using krieging for data derived from contours, and simpler griding and merging algorithm for high data density (soundings and source DTMs).
Global Ocean Biogeochemistry Analysis and Forecast
'''Short description:''' The Operational Mercator Ocean biogeochemical global ocean analysis and forecast system at 1/4 degree is providing 10 days of 3D global ocean forecasts updated daily. The time series is aggregated in time, in order to reach a two full year’s time series sliding window. This product includes daily and monthly mean files of biogeochemical parameters (chlorophyll, nitrate, phosphate, silicate, dissolved oxygen, dissolved iron, primary production, phytoplankton, zooplankton, PH, and surface partial pressure of carbon dioxyde) over the global ocean. The global ocean output files are displayed with a 1/4 degree horizontal resolution with regular longitude/latitude equirectangular projection. 50 vertical levels are ranging from 0 to 5700 meters. * NEMO version (v3.6_STABLE) * Forcings: GLOBAL_ANALYSISFORECAST_PHYS_001_024 at daily frequency. * Outputs mean fields are interpolated on a standard regular grid in NetCDF format. * Initial conditions: World Ocean Atlas 2013 for nitrate, phosphate, silicate and dissolved oxygen, GLODAPv2 for DIC and Alkalinity, and climatological model outputs for Iron and DOC * Quality/Accuracy/Calibration information: See the related QuID[https://documentation.marine.copernicus.eu/QUID/CMEMS-GLO-QUID-001-028.pdf] '''DOI (product) :''' https://doi.org/10.48670/moi-00015
The myOcean products depends on other products for production or validation. The detailed list of dependencies is given in ISO19115's aggregationInfo (ISO19139 Xpath = "gmd:MD_Metadata/gmd:identificationInfo/gmd:aggregationInfo[./gmd:MD_AggregateInformation/gmd:initiativeType/gmd:DS_InitiativeTypeCode/@codeListValue='upstream-validation' or 'upstream-production']")
Horizontal velocity of the water column (currents) | Eastward current velocity in the water body | Copernicus Marine Environment Monitoring Service | Atlantic - European North West Shelf - Ocean Physics Analysis and Forecast
Global marine heat waves: frequency, classification and distribution from 1996-2020
This dataset comprises the global frequency, classification and distribution of marine heat waves (MHWs) from 1996-2020, in Chauhan et al. 2023 (https://doi.org/10.3389/fmars.2023.1177571). The classification was done based on their attributes and using different baselines. Daily SST values were extracted from the NOAA-OISST v2 high-resolution (0.25°) dataset from 1982-2020. MHWs were detected using the method presented by Hobday et al. 2016 (https://doi.org/10.1016/j.pocean.2015.12.014), and by using the 95th percentile of the accumulated temperature distribution to flag the extreme events. A shifting baseline of 8-year rolling period was selected between the years 1982-1996, since this period shows relatively stable maximum values of temperature across different ocean regions. The shifting baseline aims to account for the decadal changes of westerly winds, temperatures and ocean gyres circulations. The classification was done using the KMeans clustering algorithm to identify the relevant features of MHWs and classify them into separate groups based on feature similarities. This algorithm takes MHW features, namely duration, maximum intensity, rate onset and rate decline, as input vectors and applies clustering in the 4-dimensional feature space where each data point represents an MHW event. Note that all the MHWs features are standardized because unequal variances can put more weight on variables with smaller variances. This record comprehends the geospatial datasets of: Average number of MHW days per year (i.e., the sum of all MHW days divided by the total number of years, 1996-2020). Average cumulative intensity per year (i.e., the sum of cumulative intensity divided by the total number of years, 1996-2020). Total number of MHW events across the different periods averaged on the total number of years (1989-2020). The period 1982-1988 was only used as an initial baseline without calculating MHWs. Spatial distribution of three MHW categories: moderate MHWs, abrupt and Intense MHWs and extreme MHWs; displaying the total number of MHW days normalized by the number of years considered (i.e., 1989-2020). Distribution of Extreme MHWs across the different periods (A) 1989-1996, (B) 1997-2004, (C) 2005-2012, (D) 2013-2020. The relative frequency (γ) is a ratio of extreme MHWs in a specific period and all extreme MHWs in the same cluster for all periods.
There are no limitations on public access to spatial data sets and services.
Daily SST was extracted from NOAA-OISST v2 high resolution (0.25°) dataset from 1982-2020. MHWs are detected using the method presented in Hobday et al. (2016), using the 95th percentile of the accumulated temperature distribution to flag the extreme events. The period from 1982-1996 was used as a baseline. The KMeans clustering algorithm was used for MHW classification. See abstract for further details.
GHRSST Level 2P Global Subskin Sea Surface Temperature from the Advanced Scanning Microwave Radiometer - Earth Observing System (AMSR-E) on the NASA Aqua Satellite
The Advanced Microwave Scanning Radiometer (AMSR-E) was launched on 4 May 2002, aboard NASA's Aqua spacecraft. The National Space Development Agency of Japan (NASDA) provided AMSR-E to NASA as an indispensable part of Aqua's global hydrology mission. Over the oceans, AMSR-E is measuring a number of important geophysical parameters, including sea surface temperature (SST), wind speed, atmospheric water vapor, cloud water, and rain rate. A key feature of AMSR-E is its capability to see through clouds, thereby providing an uninterrupted view of global SST and surface wind fields. Remote Sensing Systems (RSS, or REMSS) is the provider of these SST data for the Group for High Resolution Sea Surface Temperature (GHRSST) Project, performs a detailed processing of AMSR-E instrument data in two stages. The first stage produces a near-real-time (NRT) product (identified by "_rt_" within the file name) which is made as available as soon as possible. This is generally within 3 hours of when the data are recorded. Although suitable for many timely uses the NRT products are not intended to be archive quality. "Final" data (currently identified by "v7" within the file name) are processed when RSS receives the atmospheric model National Center for Environmental Prediction (NCEP) Final Analysis (FNL) Operational Global Analysis. The NCEP wind directions are particularly useful for retrieving more accurate SSTs and wind speeds. This dataset adheres to the GHRSST Data Processing Specification (GDS) version 2 format specifications.
/Activités et Usages/Pêche et Aquaculture
Use of open search engines, searching by name either the data provider or the characteristics
There is detailed information provided to understand data policy
Format not proprietary and content clearly specified (e.g. autodescriptive like ODV, NetCDF CF) or at least with appropriate document describing the content
Online discovery + downloading + viewing services (Advanced services)
The datasets are referenced in a public national catalogue, in an international catalogue service
/Physical Environment/Bathymetry/Digital Terrain Model
Search via reference catalogue (e.g. MyOcean, GEOSS Geoportal…)
Horizontal velocity of the water column (currents)
Online discovery and downloading services
Eastward current velocity in the water body
The datasets are provided through an EU Inspire catalogue service (OGC)
WP5 Assessing state, drivers and tipping points
/Ocean Temperature/Sea Surface Temperature
International Council for the Exploration of the Sea (ICES)
ICES - Working Group Oceanic Hydrography
IFREMER / IDM / SISMER - Scientific Information Systems for the SEA
CLS (editor M.Sutton/E.Rouzies with help L.Soudarin)
Copernicus Marine Environment Monitoring Service
NASA/JPL/PODAAC > Physical Oceanography Distributed Active Archive Center, Jet Propulsion Laboratory, NASA
Wave height and period statistics | Average zero crossing period of waves {Tz} on the water body | Istituto Nazionale di Geofisica e Vulcanologia – INGV, Sede di Bologna | MFS WW3 wave model Mediterranean
Transport activity | Vessel Traffic Density | Vessel Finder |
Manual process: Order form/invoice is requested
Average zero crossing period of waves {Tz} on the water body
Data sets are not referenced in a catalogue or are referenced in a non public catalogue
Information retrieved upon specific request to the data source
There is no information at all on data policy adopted by data providers
There is information, but details are available only on request
Historical AIS data available since 2009.
Istituto Nazionale di Geofisica e Vulcanologia – INGV, Sede di Bologna
Mediterranean decision support system for marine safety
Instituto Português do Mar e da Atmosfera (IPMA)
Vessel Finder - Historical AIS data services