Datasets
The total ozone estimates are based on solar UV radiation measurements made by ground-based spectrophotometers (Dobson or Brewer type spectrophotometers).
The vertical profiles of ozone concentration are estimated primarily using ozonesonde observations.
Data are available for 159 Dobson stations, 109 Brewer stations and 135 ozonesondes stations.
Interval/period: Tue, 01/01/1924 - Sat, 05/09/2026
United States Climate Reference Network (USCRN) stations.
There are over 130 USCRN stations over the conterminous United States (U.S.), Alaska, and Hawaii.
The USCRN stations are managed and maintained by the U.S. National Oceanic and Atmospheric Administration (NOAA).
The USCRN observations include air temperature, humidity, wind speed, precipitation, solar radiation,
Interval/period: Sun, 01/01/2006 - Sat, 05/09/2026
Interval/period: Mon, 01/01/1979 - Wed, 04/01/2026
The data are bias adjusted using the Distribution Based Scaling (DBS) method versus the global reference dataset HydroGFD2.0, both bias adjustment method and global reference dataset developed by the Swedish Meteorological and Hydrological Institute (SMHI).
The DBS method is a parametric quantile-mapping variant.
Interval/period: Thu, 10/12/2000 - Thu, 10/18/2018
Interval/period: Wed, 01/01/1986 - Sun, 12/31/2023
Interval/period: Wed, 01/01/1986 - Sun, 12/31/2023
Interval/period: Mon, 01/01/1979 - Mon, 09/30/2024
Interval/period: Sat, 01/01/2000 - Sun, 12/31/2017
The DestinE Digital Twin for Weather-Induced Extremes (Extremes DT) supports responding and adapting to extreme events in a changing world by providing a capability to produce tailored simulations and address what-if scenarios related to extreme events in a past, present and future climate, complementing existing capabilities at national and European level.
Interval/period: N/A
Interval/period: Thu, 02/01/1940 - Fri, 01/23/2026
Interval/period: Sat, 03/01/1986 - Wed, 11/30/2011
This dataset provides gridded modelled hydrological time series forced with medium-range meteorological forecasts. The data is a consistent representation of the most important hydrological variables across the European Flood Awareness System (EFAS) domain. The temporal resolution is sub-daily high-resolution and ensemble forecasts of:
River discharge
Soil moisture for three soil layers
Snow water equivalent
Interval/period: N/A
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 - Wed, 05/06/2026
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 - Tue, 06/09/2026
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 - Sat, 05/09/2026
These daily and monthly data are pre-calculated and have the following types depending on the variables: daily and monthly averages, extremes and totals.
Interval/period: Sat, 09/01/1990 - Sat, 02/28/2026
This dataset provides daily air quality analyses and forecasts for Europe.
Interval/period: N/A
This dataset provides annual air quality reanalyses for Europe based on both unvalidated (interim) and validated observations.
Interval/period: N/A
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: N/A
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: N/A
This data set contains gridded distributions of global anthropogenic and natural emissions.
Interval/period: N/A
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: N/A
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: N/A
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: N/A
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: N/A