External datasets catalogue

GESLA2 — 22 Nov 2019

The GESLA (Global Extreme Sea Level Analysis) project grew out of the interests of several people in learning more about the changes in the frequency and magnitude of extreme sea levels. 

Multinet street map (Dataset URL is not available) — 19 Nov 2019

World Economic Outlook database — 18 Nov 2019

Gross Domestic product at current prices non European countries

Farm Accountancy Data Network- FADN — 13 Nov 2019

Coupled Model Intercomparison Project Phase 5 - CMIP5 — 06 Nov 2019

CMIP5 climate projections

NOAA Extended Reconstructed Sea Surface Temperature (ERSST), Version 5 — 05 Nov 2019

The NOAA Extended Reconstructed Sea Surface Temperature (ERSST) dataset is a global monthly sea surface temperature dataset derived from the International Comprehensive Ocean-Atmosphere Dataset (ICOADS). It is produced on a 2 x 2 degree grid with spatial completeness enhanced using statistical methods. This monthly analysis begins in January 1854 continuing to the present and includes anomalies computed with respect to a 1971-2000 monthly climatology. Version 5 (v5) is the newest version of ERSST. Major revisions for v5 include: 1) using unadjusted first-guess instead of adjusted first-guess in QC, 2) using latest International Comprehensive Ocean Atmosphere Data Set (ICOADS) Release 3.0 (R3.0) over 1854-2015 instead of R2.5 over 1854-2007, 3) using Argo temperature above 5 meter depth that has not been used in previous version ERSST and other SST analysis, 4) using latest UK Met Office HadISST2 ice concentration over 1870-2015 instead of HadISST1 ice concentration over 1870-2010, 5) removing damping in high latitudes north of 60 degrees North and south of 50 degrees South in Empirical Orthogonal Teleconnection (EOT) Functions, 6) adding 10 more EOT modes in the Arctic, 7) reducing spatial filtering in training EOTs, and 8) revising ship SST bias correction relative to nighttime marine air temperature (NMAT) to the one relative to buoy SST observations. Other features remain same as in the previous ERSST version 4. The data are written to monthly netCDF files following CF Metadata Conventions.

ESA SST CCI: Level 4 Analysis Climate Data Record — 05 Nov 2019

This v2.1 SST_cci Level 4 Analysis Climate Data Record (CDR) provides a globally-complete daily analysis of sea surface temperature (SST) on a 0.05 degree regular latitude - longitude grid. It combines data from both the Advanced Very High Resolution Radiometer (AVHRR ) and Along Track Scanning Radiometer (ATSR) SST_cci Climate Data Records, using a data assimilation method to provide SSTs where there were no measurements. These data cover the period between 09/1981 and 12/2016. The dataset has been produced as part of the European Space Agency (ESA) Climate Change Initiative Sea Surface Temperature project(ESA SST_cci). The data products from SST_cci accurately map the surface temperature of the global oceans over the period 1981 to 2016 using observations from many satellites. The data provide independently quantified SSTs to a quality suitable for climate research.

HadSST.4.0.1.0 — 05 Nov 2019

The Met Office Hadley Centre's sea surface temperature data set, HadSST.4.0.1.0, is a monthly global field of SST on a 5° latitude by 5° longitude grid from 1850 to date. The data have been adjusted to minimise the effects of changes in instrumentation throughout the record. The data set is presented as a set of interchangeable realisations that capture the temporal and spatial characteristics of the estimated uncertainties in the biases. In addition there are files providing the measurement and sampling uncertainties which must be used in addition to the ensemble to obtain a comprehensive estimate of the uncertainty. The data are not interpolated. The data set initially runs from 1850 to presnet with regular monthly updates.

Time Series of Mean Sea Level Trends over Global Ocean — 05 Nov 2019

The sea level ocean monitoring indicator is derived from the DUACS delayed-time (DT-2018 version) altimeter gridded maps of sea level anomalies based on a stable number of altimeters (two) in the satellite constellation. These products are distributed by the Copernicus Climate Change Service and are also available in the CMEMS catalogue (SEALEVEL_GLO_PHY_CLIMATE_L4_REP_OBSERVATIONS_008_057). The mean sea level evolution estimated in the global ocean is derived from the average of the gridded sea level maps weighted by the cosine of the latitude. The annual and semi-annual periodic signals are adjusted and the time series is low-pass filtered. The curve is corrected for the effect of the Glacial Isostatic Adjustment using the ICE5G-VM2 GIA model (Peltier, 2004).

IPCC SROCC data on sea level rise — 05 Nov 2019

This data archive comprises all data underlying figures and maps in Chapter 4 (Sea Level Rise and Implications for Low Lying Islands, Coasts and Communities) of the Special Report on the Ocean and Cryosphere in a Changing Climate published in 2019.

Projections of Fire Weather Index (PESETA III) — 05 Nov 2019

The JRC PESETA III project has developed projections of the Canadian Fire Weather Index (FWI) for various climate change scenarios. 

Fluorinated greenhouse gases 2019 — 29 Oct 2019

Data reported by companies on the production, import, export and destruction of fluorinated greenhouse gases in the European Union, 2007-2018.

Fluorinated greenhouse gases 2018 — 28 Oct 2019

Data reported by companies on the production, import, export and destruction of fluorinated greenhouse gases in the European Union, 2007-2017.

ERA5 — 25 Oct 2019

ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. ERA5-Land provides a consistent view of the water and energy cycles at surface level during several decades. When complete, ERA5-Land will contain a detailed record from 1950 onwards, with a temporal resolution of 1 hour. The native spatial resolution of the ERA5-Land reanalysis dataset is 9km on a reduced Gaussian grid (TCo1279). The data in the CDS has been regridded to a regular lat-lon grid of 0.1x0.1 degrees. The data presented here is a post-processed subset of the full ERA5-Land dataset. Monthly-mean averages have been pre-calculated to facilitate many applications requiring easy and fast access to the data, when sub-monthly fields are not required. Hourly fields can be found in the  ERA5-Land hourly fields CDS page . Documentation can be found in the  online ERA5-Land documentation .

Statistical pocketbook 2019 — 14 Oct 2019

Special Eurobarometer N° 481: Attitudes of Europeans towards biodiversity — 04 Oct 2019

EUROPEAN COMMISSION, 2019 Public Opinion

Impacts of nutrients and heavy metals in European agriculture (Dataset URL is not available) — 02 Oct 2019

Impacts of nutrients and heavy metals in European agriculture. Current and critical inputs in view of air, soil and water quality  ETC/ULS Report.

EXIOBASE — 24 Sep 2019

EXIOBASE is a global, detailed Multi-Regional Environmentally Extended Supply-Use  Table (MR-SUT) and Input-Output Table (MR-IOT). It was developed by harmonizing and detailing supply-use tables for a large number of countries, estimating emissions and resource extractions by industry. Subsequently the country supply-use tables were linked via trade  creating an MR-SUT and producing a MR-IOTs from this. The MR-IOT that can be used for the analysis of the environmental impacts associated with the final consumption of product groups.

LUCAS Soil, the largest expandable soil dataset for Europe: a review (Dataset URL is not available) — 30 Aug 2019

Potential Sources of Anthropogenic Copper Inputs to European Agricultural Soils (Dataset URL is not available) — 30 Aug 2019