External datasets catalogue

Climatic suitability for the presence and seasonal activity of the 𝘈𝘦𝘥𝘦𝘴 𝘢𝘭𝘣𝘰𝘱𝘪𝘤𝘵𝘶𝘴 mosquito for Europe derived from climate projections — 19 Sep 2022

Premature deaths in the EU per 100,000 population by age range for both air pollution and lead, 2019 — 19 Sep 2022

Heat waves and cold spells in Europe derived from climate projections — 19 Sep 2022

ETC/ATNI Report 17/2021: Wheat yield loss in 2019 in Europe due to ozone exposure (direct link to the datasets is not available) — 07 Sep 2022

Gross domestic product at market prices — 06 Sep 2022

Rail and waterborne-best for low-carbon motorised transport (direct link to the dataset is not available) — 30 Aug 2022

ICES Statistical Areas — 03 Aug 2022

The ICES Statistical Areas delineates the divisions and subdivisions of FAO Major Fishing area 27. A description of the area and its subareas, divisions and subdivisions follows: All waters of the Atlantic and Arctic Oceans and their dependent seas bounded by a line from the geographic North Pole along the meridian of 40°00' west longitude to the north coast of Greenland; thence in an easterly and southerly direction along the coast of Greenland to a point at 44°00' west longitude; thence due south to 59°00' north latitude; thence due east to 42°00' west longitude; thence due south to 36°00' north latitude; thence due east to a point on the coast of Spain (Punta Marroqui isthmus) at 5°36' west longitude; thence in a northwesterly and northerly direction along the southwest coast of Spain, the coast of Portugal, the north-west and north coasts of Spain, and the coasts of France, Belgium, the Netherlands, and Germany to the western terminus of its boundary with Denmark; thence along the west coast of Jutland to Thyborøn; thence in a southerly and easterly direction along the south coast of the Limfjord to Egensekloster Point; thence in a southerly direction along the east coast of Jutland to the eastern terminus of the boundary of Denmark with Germany; thence along the coasts of Germany, Poland, Russian Federation, Lithuania, Latvia, Estonia, Russian Federation, Finland, Sweden, and Norway, and the north coast of the Russian Federation to Khaborova; thence across the western entry of the Strait of Yugorskiy Shar; thence in a westerly and northerly direction along the coast of Vaigach Island; thence, across the western entry of the Strait of the Karskiye Vorota; thence west and north along the coast of the south island of Novaya Zemlya; thence across the western entry of the Strait of Matochkin Shar; thence along the west coast of the north island of Novaya Zemlya to a point at 68°30' east longitude; thence due north to the geographic North Pole.

ICES Statistical Rectangles — 03 Aug 2022

Vector polygon representation of the ICES Statistical Rectangles. The ICES statistical Rectangles are used as bounding areas for the calculation of fish statistics, e.g. catch per unit effort (CPUE) and stock estimates,

Contaminants in biota from EMODnet Chemistry — 19 Jul 2022

EMODnet Chemistry Portal gives free and open access to measurement data, as delivered by the originators, for groups of chemical variables. Clicking on Chemicals by region you can visualise the Matrix indicating, per sea region and per chemicals group, how many measurement data have been gathered from tens of data providers in the EMODnet Chemistry network.

Contaminants in biota from ICES DOME (Marine Environment) — 19 Jul 2022

A large portion of the data held are monitoring data submitted for the OSPAR CEMP and HELCOM COMBINE monitoring programmes and therefore follow specific monitoring programme guidelines. While these programmes have key components which are monitored yearly at defined stations, components which are under development are also included. The result is a broad spectrum of chemical parameters from metals, PAHs, brominated flame retardants, TBT and TBT effects in sediment and biota, to histopathology, ocean acidification and benthos and plankton data. DOME also includes methods and quality assurance data such as the reporting of uncertainty on a single component basis to help in assessing comparable data.

Eionet core data flows 2021 (direct URL to the dataset is not available) — 21 Jun 2022

UN Geoscheme - Standard M49 — 20 Jun 2022

Gross Farm Income (SE410) — 20 Jun 2022

Consideration of vulnerable groups in local climate adaptation plans (dataset under embargo) — 13 Jun 2022

Daily mean temperature, E-OBS gridded dataset version 25.0e — 09 Jun 2022

Global Burden of Disease Results Tool — 03 Jun 2022

Estimating irrigation water requirements in Europe — 25 May 2022

In Southern Europe, irrigated agriculture is by far the largest consumer of freshwater resources. However, consistent information on irrigation water use in the European Union is still lacking. We applied the crop growth model EPIC to calculate irrigation requirements in the EU and Switzerland, combining available regional statistics on crop distribution and crop specific irrigated area with spatial data sources on soils, land use and climate. The model was applied at a 10×10km grid using different irrigation strategies over a period of 8years. The irrigation requirements reflect the spatial distribution of irrigated areas, climatic conditions and crops. Simulated net irrigation requirements range from 53mm/yr in Denmark to 1120mm/yr in Spain, translating into estimated volumetric net irrigation requirements of 107mio.m3 and 35,919mio.m3, respectively. We estimate gross irrigation demands to be 1.3–2.5 times higher than field requirements, depending on the efficiency of transport and irrigation management. A comparison with national and regional data on water abstractions for irrigation illustrates the information deficit related to currently available reported data, as not only model limitations but also different national approaches, country-specific uncertainties (illegal or unrecorded abstractions), and restrictions of actual water use come into play. In support of European environmental and agricultural policies, this work provides a large-scale overview on irrigation water requirements in Europe applying a uniform approach with a sufficiently high spatial resolution to support identification of hot spots and regional comparisons. It will also provide a framework for national irrigation water use estimations and supports further analysis of agricultural pressures on water quantity in Europe. Keywords: Agriculture; Irrigation; Water abstractions; Crop water requirement; Europe; Large-scale modeling

Daily mean temperature, E-OBS gridded dataset version 25.0e (copyrights protected) — 20 May 2022

The E-OBS dataset consists of gridded fields created from station series throughout Europe. The dataset contains preliminary daily updates of the E-OBS dataset for daily mean temperature. Only the last 60 days are saved in this dataset, so the latest month is completely available at all times after the monthly update.

ERA5 monthly averaged data on single levels from 1950 to 1978 (preliminary version) — 19 May 2022

Global Ocean acidification - mean sea water pH time series and trend from Multi-Observations Reprocessing — 18 May 2022

Ocean acidification is quantified by decreases in pH, which is a measure of acidity: a decrease in pH value means an increase in acidity, that is, acidification. The observed decrease in ocean pH resulting from increasing concentrations of CO2 is an important indicator of global change. The estimate of global mean pH builds on a reconstruction methodology, Obtain values for alkalinity based on the so called “locally interpolated alkalinity regression (LIAR)” method after Carter et al., 2016; 2018. Build on surface ocean partial pressure of carbon dioxide (CMEMS product: MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008) obtained from an ensemble of Feed-Forward Neural Networks (Chau et al. 2022) which exploit sampling data gathered in the Surface Ocean CO2 Atlas (SOCAT) ( https://www.socat.info/ ) Derive a gridded field of ocean surface pH based on the van Heuven et al., (2011) CO2 system calculations using reconstructed pCO2 (MULTIOBS_GLO_BIO_CARBON_SURFACE_REP_015_008) and alkalinity. The global mean average of pH at yearly time steps is then calculated from the gridded ocean surface pH field. It is expressed in pH unit on total hydrogen ion scale. In the figure, the amplitude of the uncertainty (1σ ) of yearly mean surface sea water pH varies at a range of (0.0023, 0.0029) pH unit (see Quality Information Document for more details). The trend and uncertainty estimates amount to -0.0017±0.0004e-1 pH units per year. The indicator is derived from in situ observations of CO2 fugacity (SOCAT data base, www.socat.info , Bakker et al., 2016). These observations are still sparse in space and time. Monitoring pH at higher space and time resolutions, as well as in coastal regions will require a denser network of observations and preferably direct pH measurements. A full discussion regarding this OMI can be found in section 2.10 of the Ocean State Report 4 (Gehlen et al., 2020).