Datasets
Displaying 1 - 20 of 20
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.
Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017
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
interactions between anthropogenic aerosols and clouds
carbon dioxide
methane
tropospheric ozone
stratospheric ozone
interactions between anthropogenic aerosols and radiation
interactions between anthropogenic aerosols and clouds
Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017
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.
Interval/period: Wed, 01/01/2003 - Thu, 10/31/2024
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.
Interval/period: Wed, 01/01/2003 - Sun, 12/31/2023
This dataset provides historical values of global, direct and diffuse solar
irradiation, as well as direct normal irradiation, on a latitude/longitude grid
covering land surfaces and coastal areas of Europe, Africa, Oceania, Eastern
South America, the Middle East and South-East Asia. It is created from 15 minute
resolved timeseries at each grid point. These timeseries were calculated by the
CAMS Solar Radiation Time Series Service and use information on aerosol, ozone
irradiation, as well as direct normal irradiation, on a latitude/longitude grid
covering land surfaces and coastal areas of Europe, Africa, Oceania, Eastern
South America, the Middle East and South-East Asia. It is created from 15 minute
resolved timeseries at each grid point. These timeseries were calculated by the
CAMS Solar Radiation Time Series Service and use information on aerosol, ozone
Interval/period: Sat, 01/01/2005 - Sun, 12/31/2023
This dataset provides annual air quality reanalyses for Europe based on both unvalidated and validated observations.
Interval/period: Tue, 01/01/2013 - Tue, 12/31/2024
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.
Interval/period: Wed, 01/01/2003 - Wed, 12/03/2025
This data set contains gridded distributions of global anthropogenic and natural emissions.
Interval/period: Sat, 01/01/2000 - Thu, 12/31/2020
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.
Interval/period: Wed, 01/01/2003 - Thu, 12/31/2020
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.
Interval/period: Wed, 01/01/2003 - Thu, 12/31/2020
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).
Interval/period: Mon, 01/01/1979 - Wed, 12/31/2025
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.
Interval/period: Thu, 01/01/2004 - Tue, 06/30/2026
This dataset provides daily air quality analyses and forecasts for Europe.
CAMS produces specific daily air quality analyses and forecasts for the European
domain at significantly higher spatial resolution (0.1 degrees, approx. 10km)
than is available from the global analyses and forecasts. The production is
based on an ensemble of eleven air quality forecasting systems across Europe. A
median ensemble is calculated from individual outputs, since ensemble products
CAMS produces specific daily air quality analyses and forecasts for the European
domain at significantly higher spatial resolution (0.1 degrees, approx. 10km)
than is available from the global analyses and forecasts. The production is
based on an ensemble of eleven air quality forecasting systems across Europe. A
median ensemble is calculated from individual outputs, since ensemble products
Interval/period: Tue, 06/27/2023 - Wed, 07/01/2026
This dataset provides daily air quality forecasts at European observation
stations after optimisation using a statistical post-processing method called
Model Output Statistics (MOS). The unoptimised "raw" forecasts are also
provided in the same format.
The MOS method uses machine learning with predictive variables including
background air quality observation datasets, ECMWF meteorological forecasts and
the "raw" CAMS European air quality ensemble median forecast. The result is
stations after optimisation using a statistical post-processing method called
Model Output Statistics (MOS). The unoptimised "raw" forecasts are also
provided in the same format.
The MOS method uses machine learning with predictive variables including
background air quality observation datasets, ECMWF meteorological forecasts and
the "raw" CAMS European air quality ensemble median forecast. The result is
Interval/period: Wed, 01/17/2024 - Wed, 07/01/2026
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.
Interval/period: Thu, 01/01/2015 - Wed, 07/01/2026
CAMS Global atmospheric composition forecast production system is used to produce the daily forecasts of pollutants, aerosols and greenhouse gases across the globe. Satellite observations of atmospheric composition are merged with a detailed computer simulation of the atmosphere using a method called data assimilation. The resulting analyses, i.e.
Interval/period: N/A
CAMS produces global forecasts for the two main long-lived greenhouse gases once a day. This dataset consists of 5-day high-resolution forecasts of carbon dioxide (CO2) and methane (CH4). Additionally, carbon monoxide (CO) and meteorological parameters relevant to the CAMS greenhouse gas forecast are included.
Interval/period: Fri, 03/01/2024 - Wed, 07/01/2026
The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.
Interval/period: Thu, 01/01/2015 - Mon, 06/29/2026
The Sub-seasonal To Seasonal dataset (S2S) consists of global ensemble real-time forecasts and reforecasts from thirteen numerical weather prediction (NWP) and research centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.
S2S project behind the dataset started in 2013 as a joint initiative of the World Weather Research Programme (WWRP) and the World Climate Research Programme (WCRP).
The goal of S2S project was to improve sub-seasonal forecast skill through combining multiple forecasting systems, enable multi-model evaluations and enhance knowledge sharing between operational centres.
Interval/period: Tue, 03/01/2011 - Sun, 08/09/2026
The International Grand Global Ensemble (TIGGE) dataset consists of global medium-range ensemble forecasts from thirteen numerical weather prediction (NWP) centres.
The dataset has been available since October 2006. TIGGE was established as a key component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts (THORPEX stands for THe Observing system Research and Predictability EXperiment)
The dataset has been available since October 2006. TIGGE was established as a key component of THORPEX: a World Weather Research Programme to accelerate the improvements in the accuracy of 1-day to 2 week high-impact weather forecasts (THORPEX stands for THe Observing system Research and Predictability EXperiment)
Interval/period: Sun, 10/01/2006 - Mon, 06/29/2026