Datasets
This dataset provides aerosol optical depths and aerosol-radiation radiative effects for four different aerosol origins: anthropogenic, mineral dust, marine, and land-based fine-mode natural aerosol. The latter mostly consists of biogenic aerosols.
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This dataset provides geographical distributions of the radiative forcing (RF) by key atmospheric constituents. The radiative forcing estimates are based on the CAMS reanalysis and additional model simulations and are provided separately for...
- carbon dioxide
- methane
- tropospheric ozone
- stratospheric ozone
- interactions between anthropogenic aerosols and radiation
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EAC4 (ECMWF Atmospheric Composition Reanalysis 4) is the fourth generation ECMWF global reanalysis of atmospheric composition. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using a model of the atmosphere based on the laws of physics and chemistry.
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EAC4 (ECMWF Atmospheric Composition Reanalysis 4) is the fourth generation ECMWF global reanalysis of atmospheric composition. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using a model of the atmosphere based on the laws of physics and chemistry.
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The CAMS solar radiation services provide historical values (2004 to present) of global (GHI), direct (BHI) and diffuse (DHI) solar irradiation, as well as direct normal irradiation (BNI). The aim is to fulfil the needs of European and national policy development and the requirements of both commercial and public downstream services, e.g. for planning, monitoring, efficiency improvements and the integration of solar energy systems into energy supply grids.
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Interval/period: Sun, 01/01/1950 - Wed, 12/01/2100
Interval/period: Sat, 01/01/1949 - Sun, 08/09/2026
Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019
to contain all available observations from balloons ascents through the atmosphere.
The main geophysical variables are temperature, humidity, and wind speed and wind direction,
as functions of atmospheric pressure levels. The observation platforms include pilot balloons, radiosondes, and ozonesondes.
The main observation data sources are:
- the NOAA Integrated Global Radiosonde Archive (IGRA version 2),
- the NCAR Upper-Air Database (UADB), and
Interval/period: Tue, 01/01/1901 - Tue, 12/31/2024
Interval/period: Mon, 01/01/1940 - Fri, 12/31/2100
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Interval/period: Mon, 01/01/1979 - Mon, 06/30/2025
This dataset provides daily air quality analyses and forecasts for Europe.
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This dataset provides annual air quality reanalyses for Europe based on both unvalidated (interim) and validated observations.
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CAMS produces global forecasts for atmospheric composition twice a day. The forecasts consist of more than 50 chemical species (e.g. ozone, nitrogen dioxide, carbon monoxide) and seven different types of aerosol (desert dust, sea salt, organic matter, black carbon, sulphate, nitrate and ammonium aerosol). In addition, several meteorological variables are available as well.
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Emissions of atmospheric pollutants from biomass burning and vegetation fires are key drivers of the evolution of atmospheric composition, with a high degree of spatial and temporal variability, and an accurate representation of them in models is essential.
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This data set contains gridded distributions of global anthropogenic and natural emissions.
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This dataset is part of the ECMWF Atmospheric Composition Reanalysis focusing on long-lived greenhouse gases: carbon dioxide (CO2) and methane (CH4). The emissions and natural fluxes at the surface are crucial for the evolution of the long-lived greenhouse gases in the atmosphere. In this dataset the CO2 fluxes from terrestrial vegetation are modelled in order to simulate the variability across a wide range of scales from diurnal to inter-annual.
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This dataset is part of the ECMWF Atmospheric Composition Reanalysis focusing on long-lived greenhouse gases: carbon dioxide (CO2) and methane (CH4). The emissions and natural fluxes at the surface are crucial for the evolution of the long-lived greenhouse gases in the atmosphere. In this dataset the CO2 fluxes from terrestrial vegetation are modelled in order to simulate the variability across a wide range of scales from diurnal to inter-annual.
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This data set contains net fluxes at the surface, atmospheric mixing ratios at model levels, and column-mean atmospheric mixing ratios for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N20).
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Interval/period: Sun, 01/01/1950 - Thu, 12/31/2099
Interval/period: Mon, 01/01/1979 - Mon, 12/31/2018
LAPrec1871 starts in 1871 and is based on data from 85 input series;
LAPrec1901 starts in 1901 and is based on data from 165 input series.
Interval/period: Sun, 01/01/1871 - Sun, 08/09/2026
Interval/period: Sat, 01/01/2000 - Sun, 12/31/2017
ECV datasets provide the empirical evidence needed to understand the current climate and predict future changes.
CIIs contain condensed climate information which facilitate relatively quick and efficient subsequent analysis. Therefore, CIIs make climate information accessible to application focussed users within a sector.
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