A subset of ECMWF real-time forecast data from the IFS and AIFS models is made available to the public free of charge. Their use is governed by the Creative Commons CC-BY-4.0 licence and the ECMWF Terms of Use.

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The Climate Change Adaptation Digital Twin dataset (Version 1) - delivering global high-quality climate information at scales that matter to society

The DestinE Digital Twin for Climate Change Adaptation (Climate DT) supports adaptation activities through the provision of innovative climate information on multi-decadal timescales, at scales at which the impacts of climate change are observed.

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The Weather-Induced Extremes Digital Twin - sharpening the prediction of extreme weather and its impacts

The DestinE Digital Twin for Weather-Induced Extremes (Extremes DT) supports rapid decision-making in response to meteorological, hydrological and air quality extremes.

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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.

calendar_today 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

calendar_today 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.

calendar_today 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.

calendar_today 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

calendar_today 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.

calendar_today 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.

calendar_today Interval/period: Wed, 01/01/2003 - Wed, 12/03/2025

This data set contains gridded distributions of global anthropogenic and natural emissions.

calendar_today 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.

calendar_today 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.

calendar_today 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).

calendar_today Interval/period: Mon, 01/01/1979 - Wed, 12/31/2025

Overview

The AI Weather Quest (AI WQ), organised by ECMWF, is an ambitious international competition designed to harness artificial intelligence (AI) and machine learning (ML) in advancing weather forecasting.

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15-member coupled IFS (cycle 43R1) extended-range reforecast experiment covering the period 1989-2015. The atmosphere is configured with 91 vertical levels and uses the Tco399 cubic octahedral reduced Gaussian grid. The IFS is coupled hourly to the 75 level version of the NEMO v3.4 ocean model and the LIM2 sea-ice model, both of which use the ORCA025 tripolar grid. Coupling follows the implementation used in ECMWF operational forecasts.

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15-member coupled IFS (cycle 43R1) extended-range reforecast experiment covering the period 1989-2015 with bias-corrected sea-surface temperatures (SSTs) in the North Atlantic region. This experiment can be compared with gkzp, which is the relevant control without bias-correction. The atmosphere is configured with 91 vertical levels and uses the Tco399 cubic octahedral reduced Gaussian grid.

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An eddy-permitting ocean reanalysis spanning the period 1979–2012. Includes increased horizontal and vertical resolution, an prognostic sea-ice component, new versions of the ocean and data assimilation system, revised surface fluxes, new version and treatment of satellite sea surface height data, and assimilation of sea-ice concentration, among others.

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Uses a sophisticated data assimilation methodology which includes a model bias correction. The ocean model used is forced by atmospheric daily surface fluxes, relaxed to SST and bias corrected.

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The ECMWF OCEAN5 system is a new global eddy-permitting ocean-sea ice ensemble reanalysis analysis system. This Technical Memorandum gives a full description of the OCEAN5 system, with the focus on its Behind-Real-Time (BRT) component, the reanalysis product ORAS5. The OCEAN5 Real-Time (RT) component includes all upgrades developed for ORAS5 and runs daily using the latest observations and forcing fields from the operational Numerical Weather Prediction (NWP).

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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.

calendar_today 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

calendar_today 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

calendar_today 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.

calendar_today 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.

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