The ONOMASTICA project was a European-wide research initiative within the scope of the Linguistic Research and Engineering Programme, the aim of which was the construction of a multi-language pronunciation lexicon of proper names. That project covered eleven European languages: Danish, Dutch, English, French, German, Greek, Italian, Norwegian, Portuguese, Spanish and Swedish.Although the ONOMASTICA project ended in June 1995, the work continued with the introduction of new partners, addressing names in Eastern and Central European languages: Czech, Estonian, Latvian, Polish, Romanian, Slovakian, Slovenian and Ukrainian, in a new project funded by the European Commission?s Copernicus Programme.The corpus consists of a collection of 1,783,390 transcriptions of 1,705,653 names, broken down as follows:· Czech: 257,700 entries consisting of 244,025 names prepared by Dr. Pavel Kolar of the Language Institute, Silesian University, Opava, Czech Republic.· Estonian: 209,515 entries consisting of 208,380 names prepared by Dr. Peeter Päll of the Institute for the Estonian Language, Estonian Academy of Sciences, Tallinn, Estonia.· Latvian: 258,214 entries consisting of 245,331 names prepared by Dr. Andrejs Spektors of the Institute of Mathematics and Computer Science, University of Latvia, Riga, Latvia.· Polish: 285,412 entries consisting of 244,632 names prepared by Prof. Wiktor Jassem of the Institute of Fundamental Technological Research, Polish Academy of Sciences, Posnan, Poland.· Slovak: 228,257 entries consisting of 228,257 names prepared by Dr. Peter Durco of the Department of Foreign Languages, Police Academy of the Slovak Republic, Bratislava, Slovak Republic.· Slovenian: 285,862 entries consisting of 283,449 names prepared by Dr. Zdravko Kacic of the Faculty of Technical Sciences, University of Maribor, Maribor, Slovenia.· Ukrainian: 258,430 entries consisting of 251,579 names prepared by Dr. Yevgeniy Ludovik of the Institute of Cybernetics, Ukraine Academy of Sciences, Kiev, Ukraine.The databases are presented in Microsoft Access format and in ASCII text format, together with a database browser software prepared by Keith Edwards of the Centre for Communication Interface Research, The University of Edinburgh.

Copernicus is the Earth observation component of the European Union’s Space programme, looking at our planet and its environment to benefit all European citizens. It offers information services that draw from satellite Earth Observation and in-situ (non-space) data. The European Commission manages the Programme. It is implemented in partnership with the Member States, the European Space Agency (ESA), the European Organisation for the Exploitation of Meteorological Satellites (EUMETSAT), the European Centre for Medium-Range Weather Forecasts (ECMWF), EU Agencies and Mercator Océan. Vast amounts of global data from satellites and ground-based, airborne, and seaborne measurement systems provide information to help service providers, public authorities, and other international organisations improve European citizens' quality of life and beyond. The information services provided are free and openly accessible to users. But why is it called Copernicus you may ask? By choosing Copernicus's name, we are paying homage to a great European scientist and observer: Nicolaus Copernicus. Copernicus' theory of the heliocentric universe made a pioneering contribution to modern science. Copernicus opened man to an infinite universe, previously limited by the rotation of the planets and the sun around the Earth, and created an understanding of a world without borders. Humanity was able to benefit from his insight. This set in motion a spirit of discovery through scientific research, which allowed us to understand better the world we live in. These value-adding activities are streamlined through six thematic streams of Copernicus services: - Atmosphere CAMS - Marine CMEMS - Land CLMS - Climate Change C3S - Security - Emergency EMS

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. We provide two instances of Copernicus DEM named GLO-30 Public and GLO-90. GLO-90 provides worldwide coverage at 90 meters. GLO-30 Public provides limited worldwide coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that in both cases ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs and comes from Copernicus DEM 2021 release.

The Copernicus App Lab project: Easy Access to Copernicus Data

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. This DSM is derived from an edited DSM named WorldDEM, where flattening of water bodies and consistent flow of rivers has been included. In addition, editing of shore- and coastlines, special features such as airports, and implausible terrain structures has also been applied. The WorldDEM product is based on the radar satellite data acquired during the TanDEM-X Mission, which is funded by a Public Private Partnership between the German State, represented by the German Aerospace Centre (DLR) and Airbus Defence and Space. OpenTopography is providing access to the global 90m (GLO-90) DSM through the public AWS S3 bucket established by Sinergise. Note: In the original datasets, the longitudinal spacing of cells increases as a function of latitude for latitudes north of 50N and south of 50S. See the original documentation for details. In order to keep the pixel dimensions uniform, OpenTopography interpolates data north of 50 degrees latitude and south of -50 degrees latitude in order to output a consistent 90m product. GLO-90 is available on a free basis for the general public under the terms and conditions of the License found here

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 hourly data on pressure levels from 1940 to present".

Here we provide a mosaic of the Copernicus DEM 30m for Europe and the corresponding hillshade derived from the GLO-30 public instance of the Copernicus DEM. The CRS is the same as the original Copernicus DEM CRS: EPSG:4326. Note that GLO-30 Public provides limited coverage at 30 meters because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. The original GLO-30 provides worldwide coverage at 30 meters (refers to 10 arc seconds). Note that ocean areas do not have tiles, there one can assume height values equal to zero. Data is provided as Cloud Optimized GeoTIFFs. Note that the vertical unit for measurement of elevation height is meters. The Copernicus DEM for Europe at 30 m in COG format has been derived from the Copernicus DEM GLO-30, mirrored on Open Data on AWS, dataset managed by Sinergise (https://registry.opendata.aws/copernicus-dem/). Processing steps: The original Copernicus GLO-30 DEM contains a relevant percentage of tiles with non-square pixels. We created a mosaic map in https://gdal.org/drivers/raster/vrt.html format and defined within the VRT file the rule to apply cubic resampling while reading the data, i.e. importing them into GRASS GIS for further processing. We chose cubic instead of bilinear resampling since the height-width ratio of non-square pixels is up to 1:5. Hence, artefacts between adjacent tiles in rugged terrain could be minimized: gdalbuildvrt -input_file_list list_geotiffs_MOOD.csv -r cubic -tr 0.000277777777777778 0.000277777777777778 Copernicus_DSM_30m_MOOD.vrt The pixel values were scaled with 1000 (storing the pixels as integer values) for data volume reduction. In addition, a hillshade raster map was derived from the resampled elevation map (using r.relief, GRASS GIS). Eventually, we exported the elevation and hillshade raster maps in Cloud Optimized GeoTIFF (COG) format, along with SLD and QML style files.

This dataset provides gridded Sea Surface Temperature data derived from the Advance Very High Resolution Radiometer (AVHRR) series of satellites. Data is available separately for the AVHRR instruments on NOAA-19, METOP-A and METOP-B.

This dataset is produced as an Intermediate Climate Data Record for the Copernicus Climate Change Service (C3S). V2.0 extends from 2017-2021.

A historic Climate Data Record (CDR) has also been produced under the ESA Climate Change Initiative Sea Surface Temperature (CCI_sst). This is available as a separate dataset in the CEDA catalgoue and through the ESA CCI Open Data Portal.

This catalogue entry provides the gridded climate data (monthly/annual timeseries) used for the Copernicus Climate Change Service Atlas (C3S Atlas). The gridded datasets consist of in-situ and satellite observation-based datasets, reanalyses (CERRA, ERA5, ERA5-Land, and ORAS5) and global (CMIP5 and CMIP6) and regional (CORDEX) climate projections for the variables and indices included in the C3S Atlas. This dataset complements the Gridded monthly climate projection dataset underpinning the IPCC AR6 Interactive Atlas (IPCC Atlas dataset hereafter), including new datasets, variables and indices. The variables and indices describe various types of climatic impact characteristics: heat and cold, wet and dry, snow and ice, wind and radiation, ocean, circulation and drought characteristics of the climate system. All data sources included in this entry are available in the Climate Data Store (CDS, see “Related data” in the sidebar). Contrary to the frozen IPCC Atlas dataset, this entry will update adding new data on a regular basis. This dataset includes gridded information with monthly/annual temporal resolution for observations/reanalyses of the recent past and climate projections for the 35 variables and indices computed from daily/monthly data across the different datasets. The climate projections are based on Representative Concentration Pathways (RCP) / Shared Socioeconomic Pathways (SSP) scenarios. The datasets are harmonised using regular latitude-longitude grids. Bias correction is available for threshold-based indices. Two methods are available, depending on the variable; linear scaling and the ISIMIP method. This dataset allows the reproduction, expansion and customisation of the climate change products provided interactively by the Copernicus Interactive Climate Atlas. This is an interactive web application displaying global/regional maps of observed trends and climate changes for future periods across scenarios or for global warming levels, and regionally aggregated time series, seasonal cycle plots and climate stripes.

land and oceanic climate variables. The data cover the Earth on a 31km grid and resolve the atmosphere using 137 levels from the surface up to a height of 80km. ERA5 includes information about uncertainties for all variables at reduced spatial and temporal resolutions.

The Sentinel-2 satellites provide images in the visible and infrared spectrum. Its 13 channels are optimised for observation of land surfaces. The high resolution of up to 10 m and the sampling width of 290 km are ideal for detecting changes in vegetation and, for example, creating harvest forecasts, mapping forest stocks or determining the growth of wild and crops. The instrument is also used on coasts and inland waters to observe algae growth or to track sediment input in river deltas. All data is accessible free of charge. On the basis of the data base of the Sentinel-2 satellite Digital Orthophoto (DOP) mosaics of Mecklenburg Vorpommern, the Office for Geoinformation, Surveying and Catastrophic Engineering Mecklenburg Vorpommern creates mosaics. Depending on the data situation, a mosaic is sought for each month. If necessary, pictures of the previous month are also used. These mosaics are offered as RGB and CIR images.

The Water Level is defined as the height, in meters above the geoid, of the reflecting surface of continental water bodies. It is observed by space radar altimeters that measure the time it takes for radar pulses to reach the ground targets, directly below the spacecraft (nadir position), and return. Hence, only water bodies located along the satellite's ground tracks can be monitored, with a quality of measurement that not only depends of the size of the water body, but also on the reflecting targets in its surroundings such as topography or vegetation. Water Level is computed as time series: over lakes ; over rivers, at the intersections of the river network with the satellite ground tracks, so-called Virtual Stations. The Water Level of lakes is recognized as an Essential Climate Variable (ECV) by the Global Climate Observing System (GCOS).

This data set provides complete historical reconstruction of meteorological conditions favourable to the start, spread and sustainability of fires. The fire danger metrics provided are part of a vast dataset produced by the Copernicus Emergency Management Service for the European Forest Fire Information System (EFFIS). The European Forest Fire Information System incorporates the fire danger indices for three different models developed in Canada, United States and Australia. In this dataset the fire danger indices are calculated using weather forecast from historical simulations provided by ECMWF ERA5 reanalysis. ERA5 by combining model data and a vast set of quality controlled observations provides a globally complete and consistent data-set and is regarded as a good proxy for observed atmospheric conditions. The selected data records in this data set are regularly extended with time as ERA5 forcing data become available. This dataset is produced by ECMWF in its role of the computational centre for fire danger forecast of the CEMS, on behalf of the Joint Research Centre which is the managing entity of the service.

After 2022-01-25, Sentinel-2 scenes with PROCESSING_BASELINE '04.00' or above have their DN (value) range shifted by 1000. The HARMONIZED collection shifts data in newer scenes to be in the same range as in older scenes. Sentinel-2 is a wide-swath, high-resolution, multi-spectral imaging mission supporting Copernicus Land Monitoring studies, including the …

E-OBS is a daily gridded land-only observational dataset over Europe. The blended time series from the station network of the European Climate Assessment & Dataset (ECA&D) project form the basis for the E-OBS gridded dataset. All station data are sourced directly from the European National Meteorological and Hydrological Services (NMHSs) or other data holding institutions. For a considerable number of countries the number of stations used is the complete national network and therefore much more dense than the station network that is routinely shared among NMHSs (which is the basis of other gridded datasets). The density of stations gradually increases through collaborations with NMHSs within European research contracts. Initially, in 2008, this gridded dataset was developed to provide validation for the suite of Europe-wide climate model simulations produced as part of the European Union ENSEMBLES project. While E-OBS remains an important dataset for model validation, it is also used more generally for monitoring the climate across Europe, particularly with regard to the assessment of the magnitude and frequency of daily extremes. The position of E-OBS is unique in Europe because of the relatively high spatial horizontal grid spacing, the daily resolution of the dataset, the provision of multiple variables and the length of the dataset. Finally, the station data on which E-OBS is based are available through the ECA&D webpages (where the owner of the data has given permission to do so). In these respects it contrasts with other datasets. The dataset is daily, meaning the observations cover 24 hours per time step. The exact 24-hour period can be different per region. The reason for this is that some data providers measure between midnight to midnight while others might measure from morning to morning. Since E-OBS is an observational dataset, no attempts have been made to adjust time series for this 24-hour offset. It is made sure, where known, that the largest part of the measured 24-hour period corresponds to the day attached to the time step in E-OBS (and ECA&D).

This collection contains Earth Observations from space created by Geoscience Australia. This collection specifically is focused on data and derived data from the European Commission's Copernicus Programme. Example products include: Sentinel-1-CSAR-SLC, Sentinel-2-MSI-L1C, Sentinel-3-OLCI etc.

The Copernicus DEM is a Digital Surface Model (DSM) which represents the bare-Earth surface and all above ground natural and built features. It is based on WorldDEM™ DSM that is derived from TanDEM-X and is infilled on a local basis with the following DEMs: ASTER, SRTM90, SRTM30, SRTM30plus, GMTED2010, TerraSAR-X Radargrammetric DEM, ALOS World 3D-30m. Copernicus Programme provides Copernicus DEM in 3 different instances: COP-DEM EEA-10, COP-DEM GLO-30 and COP-DEM GLO-90 where "COP-DEM GLO-90" tiles and most of the "COP-DEM GLO-30 " tiles are available worldwide with free license. Sentinel Hub provides two instances named COPERNICUS_90 which uses "COP-DEM GLO-90" and COPERNICUS_30 which uses "COP-DEM GLO-30 Public" and "COP-DEM GLO-90" in areas where "COP-DEM GLO-30 Public" tiles are not yet released to the public by Copernicus Programme. Copernicus DEM provides elevation data and can also be used for the orthorectification of satellite imagery (e.g Sentinel 1).

These are the data needed for the tutorial "Retrieve climate data from Copernicus". These datasets come from .....

Copernicus was the third satellite in the OAO program. It was launched the 21 august of 1972 and operated till 1981. The main instrument was an ultraviolet telescope with a spectrometer to measure interstellar absorption lines in the spectra of stellar objects. However it carried also an X-ray experiment provided by University College of London/MSSL consisted in 4 co-aligned experiments sensitive in the 1-10 keV energy range. This database accesses the raw FITS file containing data obtained from the UCL X-ray Experiment (UCLXE) package on board Copernicus. This is a service provided by NASA HEASARC .

The Copernicus DEM is a Digital Surface Model (DSM) which represents the surface of the Earth including buildings, infrastructure and vegetation. This DSM is derived from an edited DSM named WorldDEM, where flattening of water bodies and consistent flow of rivers has been included. In addition, editing of shore- and coastlines, special features such as airports, and implausible terrain structures has also been applied.

The WorldDEM product is based on the radar satellite data acquired during the TanDEM-X Mission, which is funded by a Public Private Partnership between the German State, represented by the German Aerospace Centre (DLR) and Airbus Defence and Space. OpenTopography is providing access to the global 30m (GLO-30) DSM through the public AWS S3 bucket established by Sinergise.

• GLO-30 coverage is not entirely global because a small subset of tiles covering specific countries are not yet released to the public by the Copernicus Programme. See the AWS landing page for details on which countries are excluded.
• In the original datasets (available via OpenTopography bulk download or the Sinergise aws bucket), the longitudinal spacing of cells increases as a function of latitude for latitudes north of 50N and south of 50S. See the original documentation for details. However, in order to keep the pixel dimensions uniform, OpenTopography resamples data north of 50 degrees latitude and south of -50 degrees latitude in order to output a consistent 30m or 90m product for data accessed through the web-interface or API.
• GLO-30 is available on a free basis for the general public under the terms and conditions of the License found here