Waterbase serves as the EEA’s central database for managing and disseminating data regarding the status and quality of Europe's rivers, lakes, groundwater bodies, transitional, coastal, and marine waters. It also includes information on the quantity of Europe’s water resources and the emissions from point and diffuse sources of pollution into surface waters. Specifically, Waterbase - Biology focuses on biology data from rivers, lakes, transitional and coastal waters collected annually through the Water Information System for Europe (WISE) – State of Environment (SoE) reporting framework. The data are expected to be collected within monitoring programs defined under the Water Framework Directive (WFD) and used in the classification of the ecological status or potential of rivers, lakes, transitional and coastal water bodies. These datasets provide harmonised, quality-assured biological monitoring data reported by EEA member and cooperating countries, as Ecological Quality Ratios (EQRs) from all surface water categories (rivers, lakes, transitional and coastal waters).
The Seismicity Catalog Collection is a compilation dataset on over four million earthquakes dating from 2150 BC to 1996 AD from NOAA's National Geophysical Data Center and U.S. Geological Survey's National Earthquake Information Center. The data include information on epicentral time of origin, location, magnitudes, depth and other earthquake-related parameters. This database is static and is no longer being updated. The CD collection was a compilation of all of the earthquake catalogs, both US and non-US, in the National Geophysical Data Center (NGDC) archive available in 1996. The purpose was to provide users with access to all the seismicity data in one place. Data can be accessed through the GeoVu data access and visualization software included on the CDs. This software allows visualization of pre-computed histograms as well as reformatting of data files to a format specified by the user. Many of the more popular data bases are available in several different formats so the user will not have to reformat large data bases. Files can be formatted for use on IBM PCs, Macs, or UNIX machines. Format information, data dictionary and statistical information are also included. A bibliography of earthquake-related materials at NCEI and the Summary of Earthquake Data Base (KGRD-21) are included on the CD-ROM. NOAA and NCEI make no warranty, expressed or implied, regarding these data, nor does the fact of distribution constitute such a warranty. NOAA and NCEI cannot assume liability for any damages caused by any errors or omissions in these data. If appropriate, NCEI can only certify that the data it distributes are an authentic copy of the records that were accepted for inclusion in the NCEI archives. This dataset has been archived in the framework of the PANGAEA US data rescue initiative 2025.
This metadata refers to the geospatial dataset representing the status of the EEA Industrial Reporting database as of 15 December 2025 (version 15). The release and emissions data cover the period 2007-2024 as result of the data reported under the E-PRTR facilities, 2017-2024 for IED installations and WI/co-WIs, and 2016-2024 for LCPs. These data are reported to EEA under Industrial Emissions Directive (IED) 2010/75/EU Commission Implementing Decision 2018/1135 and the European Pollutant Release and Transfer Register (E-PRTR) Regulation (EC) No 166/2006 Commission Implementing Decision 2019/1741. The dataset brings together data formerly reported separately under E-PRTR Regulation Art.7 and under IED Art.72. Additional reporting requirements under the IED are also included.
Littorina littorea was collected at the study site. The foot of Littorina littorea was used for stable isotope analysis (δ15N and δ13C). The stable isotope composition of possible food sources was also determined. Samples were taken in spring, summer and autumn. For the analysis a diet tissue discrimination factor (DTDF) of 2.4 for δ15N and 1.0 for δ13C was subtracted, respectively. The data in the sheet are the raw data without the DTDF.
This dataset includes updated versions of high-resolution age models derived from six sedimentary cores collected from the southwestern Svalbard margin. The dataset presented here represents a refinement of a previous version (Caricchi et al., 2020; 2022), achieved through correlation of the stratigraphic trends of the ARM/k parameter with the GICC05modelext timescale and the NGRIP record (Rasmussen et al., 2014). Additional refinement was obtained from newly acquired and recalibrated radiometric data, as well as from improved lithological constraints. The dataset enables the calculation of sedimentation rates during glacial and interglacial periods and during short-lived, widespread meltwater pulses and Heinrich-like events, thereby allowing the reconstruction of ice-sheet instability and meltwater events along the Svalbard–Barents Sea margin over the last 60,000 years.
Aerosols are an indicator for episodic aerosol plumes from dust outbreaks, volcanic ash, and biomass burning. Daily observations are binned onto a regular latitude-longitude grid. The Aerosol layer height is provided in kilometres. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
UV Index (UVI) as derived from TROPOMI observations. The UVI describes the intensity of the solar ultraviolet radiation. Values around zero indicate low, values greater than 10 indicate very high UV exposure on the ground. The TROPOMI instrument onboard the Copernicus SENTINEL-5 Precursor satellite is a nadir-viewing, imaging spectrometer that provides global measurements of atmospheric properties and constituents on a daily basis. It is contributing to monitoring air quality and climate, providing critical information to services and decision makers. The instrument uses passive remote sensing techniques by measuring the top of atmosphere solar radiation reflected by and radiated from the earth and its atmosphere. The four spectrometers of TROPOMI cover the ultraviolet (UV), visible (VIS), Near Infra-Red (NIR) and Short Wavelength Infra-Red (SWIR) domains of the electromagnetic spectrum. The operational trace gas products generated at DLR on behave ESA are: Ozone (O3), Nitrogen Dioxide (NO2), Sulfur Dioxide (SO2), Formaldehyde (HCHO), Carbon Monoxide (CO) and Methane (CH4), together with clouds and aerosol properties. This product is created in the scope of the project INPULS. It develops (a) innovative retrieval algorithms and processors for the generation of value-added products from the atmospheric Copernicus missions Sentinel-5 Precursor, Sentinel-4, and Sentinel-5, (b) cloud-based (re)processing systems, (c) improved data discovery and access technologies as well as server-side analytics for the users, and (d) data visualization services.
In diesem Projekt sollen gemessene spektrale aktinische UV/VIS-Strahlungsflussdichten von sechs HALO-Missionen verwendet werden, um Strahlungstransportmodell-Vorhersagen zu überprüfen, die auf der Grundlage von Wolkeneigenschaften aus Satellitenbeobachtungen durchgeführt werden. Fünf der HALO-Missionen wurden bereits durchgeführt: TECHNO (2010), NARVAL-I (2014), OMO (2015), EMERGE (2017/2018) und CAFE-Africa (2018), mit einer Gesamtzahl von etwa 75 Forschungsflügen. Zudem sollen die Daten von CAFE-Brazil (2020) in die Auswertung einfließen. Der Hauptzweck der Messungen der aktinischen Strahlungsflussdichten ist die anschließende Berechnung von Photolysefrequenzen, die wichtige Größen in der Photochemie darstellen. Die HALO-Messungen bieten eine seltene Gelegenheit satelliten-gestützte Strahlungstransportmodell-Vorhersagen von Photolysefrequenzen zu überprüfen, da sie hochaufgelöste Stichproben aus verschiedenen Höhen und global verteilten Einsatzgebieten liefern. Zudem wurden während TECHNO, NARVAL und OMO durch einen Missionspartner spektrale Strahldichtemessungen in Nadir-Richtung durchgeführt. Diese Messungen umfassen den gesamten solaren Spektralbereich und bieten daher unabhängige lokale Informationen über Wolken unter dem Flugzeug, was die Interpretation und korrekte Anwendung der verfügbaren Wolkeneigenschaften erleichtern wird. Das Hauptziel des Projektes ist es herauszufinden, ob gemessene und durch ein Strahlungstransportmodell vorhergesagte Photolysefrequenzen durch den Einsatz der Satellitendaten in akzeptable Übereinstimmung gebracht werden können. Sollte dies gelingen, dann könnten auf der Grundlage satellitengestützter Wolkeninformationen nutzer-definierte 3D Felder von Photolysefrequenzen berechnet werden. Diese Felder können genutzt werden, um Vorhersagen von Chemie-Transportmodellen zu überprüfen, oder sie können in zukünftigen Anwendungen direkt in diese Modelle einfließen. Eine entsprechende Fallstudie soll im Rahmen dieses Projektes durchgeführt werden. Davon würden auch zukünftige HALO-Missionen und deren wissenschaftliche Interpretationen profitieren.
The ISXD99 TTAAii Data Designators decode as: T1 (I): Observational data (Binary coded) - BUFR T1T2 (IS): Surface/sea level T1T2A1 (ISX): Other surface data A2 (D): 90°E - 0° northern hemisphere (The bulletin collects reports from stations: 10756;Feuchtwangen-Heilbronn;10761;Weißenburg;10765;Roth;10771;Kümmersbruck;10777;Gelbelsee;10782;Waldmünchen;10796;Zwiesel;10803;Freiburg;10818;Klippeneck;10827;Meßstetten;10837;Laupheim;10840;Ulm-Mähringen;10850;Harburg;10853;Neuburg/Donau (Flugplatz);10856;Lechfeld;10857;Landsberg (Flugplatz);10860;Ingolstadt (Flugplatz);10863;Weihenstephan-Dürnast;10865;München-Stadt;10872;Gottfrieding;10875;Mühldorf;10945;Leutkirch-Herlazhofen;10954;Altenstadt;10963;Garmisch-Partenkirchen;10982;Chieming;) (Remarks from Volume-C: SYNOP HALF HOURLY H+30)
With the introduction of mobile mapping technologies, geomonitoring has become increasingly efficient and automated. The integration of Simultaneous Localization and Mapping (SLAM) and robotics has effectively addressed the challenges posed by many mapping or monitoring technologies, such as GNSS and unmanned aerial vehicles, which fail to work in underground environments. However, the complexity of underground environments, the high cost of research in this area, and the limited availability of experimental sites have hindered the progress of relevant research in the field of SLAM-based underground geomonitoring. In response, we present SubSurfaceGeoRobo, a dataset specifically focused on underground environments with unique characteristics of subsurface settings, such as extremely narrow passages, high humidity, standing water, reflective surfaces, uneven illumination, dusty conditions, complex geometry, and texture less areas. This aims to provide researchers with a free platform to develop, test, and train their methods, ultimately promoting the advancement of SLAM, navigation, and SLAM-based geomonitoring in underground environments. SubSurfaceGeoRobo was collected in September 2024 in the Freiberg silver mine in Germany using an unmanned ground vehicle equipped with a multi-sensor system, including radars, 3D LiDAR, depth and RGB cameras, IMU, and 2D laser scanners. Data from all sensors are stored as bag files, allowing researchers to replay the collected data and export it into the desired format according to their needs. To ensure the accuracy and usability of the dataset, as well as the effective fusion of sensors, all sensors have been jointly calibrated. The calibration methods and results are included as part of this dataset. Finally, a 3D point cloud ground truth with an accuracy of less than 2 mm, captured using a RIEGL scanner, is provided as a reference standard.
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