This dataset provides global maps describing the land surface into 22 classes, which have been defined using the United Nations Food and Agriculture Organization’s (UN FAO) Land Cover Classification System (LCCS). In addition to the land cover (LC) maps, four quality flags are produced to document the reliability of the classification and change detection.

calendar_today Interval/period: Wed, 01/01/1992 - Sat, 01/01/2022

This dataset contains monthly daytime and nighttime clear-sky land surface temperatures (LSTs) and their uncertainty estimates from multiple Infra-Red (IR) instruments on polar orbiting satellites. Daytime and nighttime temperatures correspond to 10:00 and 22:00 local solar time (local solar time is defined as the time in a 24 hour day with 12 noon occurring when the sun is at its highest point at that longitude).

calendar_today Interval/period: Thu, 06/01/1995 - Tue, 12/31/2024

This catalogue entry provides satellite-derived estimates of two related variables: Leaf Area Index (LAI) and fraction of Absorbed Photosynthetically Active Radiation (fAPAR). LAI and fAPAR are both Essential Climate Variables (ECVs) as defined by the Global Climate Observing System (GCOS), meaning they have been designated as essential for contributing to a comprehensive view of Earth’s climate, its variability and trends.

calendar_today Interval/period: Tue, 09/01/1981 - Sun, 12/01/2024

This dataset provides daily gridded data of sea ice concentration for both hemispheres derived from satellite passive microwave brightness temperatures. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or its retreat has a strong impact on air-sea interactions, the Earth’s energy budget as well as marine ecosystems. It is recognised by the Global Climate Observing System as an Essential Climate Variable.

calendar_today Interval/period: Sun, 10/01/1978 - Mon, 09/29/2025

This dataset provides daily gridded fields of sea ice drift vectors for both hemispheres derived from satellite passive microwave brightness temperatures and atmospheric reanalysis data. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or retreat significantly affects ocean-atmosphere interactions, the Earth’s energy budget as well as marine ecosystems. It is classified as an Essential Climate Variable by the Global Climate Observing System.

calendar_today Interval/period: Tue, 01/01/1991 - Thu, 12/31/2020

This dataset provides daily gridded data of sea ice edge and sea ice type derived from brightness temperatures measured by satellite passive microwave radiometers. Sea ice is an important component of our climate system and a sensitive indicator of climate change. Its presence or its retreat has a strong impact on air-sea interactions, the Earth’s energy budget as well as marine ecosystems. It is recognized by the Global Climate Observing System as an Essential Climate Variable. Sea ice edge and type are some of the parameters used to characterise sea ice.

calendar_today Interval/period: Wed, 10/25/1978 - Wed, 09/24/2025

This dataset provides daily and monthly sea ice surface temperature (IST) fields over the polar oceans from 1982 to the present. The data are derived from thermal infrared measurements from a single satellite sensor type: the Advanced Very High Resolution Radiometer (AVHRR) onboard National Oceanic and Atmospheric Administration (NOAA) and Meteorological Operational (MetOp) satellites.

calendar_today Interval/period: Mon, 01/01/1979 - Tue, 09/30/2025

This dataset provides gridded sea ice thickness data for the Arctic, derived from satellite observations. Sea ice plays a vital role in the climate system, influencing air-sea interactions, the Earth’s energy balance, and marine ecosystems. It is recognised by the Global Climate Observing System (GCOS) as an Essential Climate Variable (ECV). Sea ice thickness is a key characteristic used alongside other parameters such as concentration, edge, and type, all available in the Climate Data Store (CDS).

calendar_today Interval/period: Tue, 10/01/2002 - Sat, 04/12/2025

This dataset provides gridded daily and monthly mean global estimates of sea level anomaly based on satellite altimetry measurements. The rise in global mean sea level in recent decades has been one of the most important and well-known consequences of climate warming, putting a large fraction of the world population and economic infrastructure at greater risk of flooding. However, changes in the global average sea level mask regional variations that can be one order of magnitude larger.

calendar_today Interval/period: Fri, 01/01/1993 - Sun, 12/31/2023

This dataset provides global daily sea surface temperature (SST) data from the Group for High Resolution Sea Surface Temperature (GHRSST) multi-product ensemble (GMPE) produced by the European Space Agency SST Climate Change Initiative (ESA SST CCI). The GMPE system was designed to allow users to compare the outputs from different SST analysis systems and understand their similarities and differences. Although originally intended for comparison of near real time data, it has also been used to compare long historical datasets.

calendar_today Interval/period: Tue, 09/01/1981 - Sat, 12/31/2016

The Essential Climate Variables for assessment of climate variability from 1979 to present dataset contains a selection of climatologies, monthly anomalies and monthly mean fields of Essential Climate Variables (ECVs) suitable for monitoring and assessment of climate variability and change. Selection criteria are based on accuracy and temporal consistency on monthly to decadal time scales.

calendar_today Interval/period: Mon, 01/01/1979 - Wed, 04/01/2026

The Burned Area products provide global information of total burned area (BA) at pixel and grid scale. The BA is identified with the date of first detection of the burned signal in the case of the pixel product, and with the total BA per grid cell in the case of the grid product. The products were obtained through the analysis of reflectance changes from medium resolution sensors (Terra MODIS, Sentinel-3 OLCI), supported by the use of MODIS thermal information.

calendar_today Interval/period: Mon, 01/01/2001 - Fri, 04/01/2022

The dataset presents projections of fire danger indicators for Europe based upon the Canadian Fire Weather Index System (FWI) under future climate conditions. The FWI is a meteorologically based index used worldwide to estimate the fire danger and is implemented in the Global ECMWF Fire Forecasting model (GEFF). In this dataset, daily FWI values, seasonal FWI values, and other FWI derived, threshold-specific, indicators were modelled using the GEFF model to estimate the fire danger in future climate scenarios.

calendar_today Interval/period: N/A

This data set provides complete historical reconstruction of meteorological conditions favourable to the start, spread and sustainability of fires. The fire danger metrics provided are part of a vast dataset produced by the Copernicus Emergency Management Service for the

calendar_today Interval/period: Wed, 01/03/1940 - Tue, 05/05/2026

This dataset provides global information on the timing and location of Active Fires (AF) burning on Earth's surface during satellite overpasses, and also records their Fire Radiative Power (FRP) as a measure of strength. FRP relates to a fire's combustion rate, and the rate at which smoke containing greenhouse gases, reactive gases and particular matter is released into the atmosphere. The vast majority of detected hotspots are related to landscape fires, however other high temperature targets such as active volcanoes and gas flares are also present in the data.

calendar_today Interval/period: Wed, 01/01/2020 - Fri, 02/28/2025

This dataset provides agroclimatic indicators used to characterise plant-climate interactions for global agriculture. Agroclimatic indicators are useful in conveying climate variability and change in the terms that are meaningful to the agricultural sector. The objective of this dataset is to provide these indicators at a global scale in an easily accessible and usable format for further downstream analysis and the forcing of agricultural impact models.

calendar_today Interval/period: Mon, 01/01/1951 - Sat, 05/09/2026

This dataset provides daily surface meteorological data for the period from 1979 to present as input for agriculture and agro-ecological studies. This dataset is based on the hourly ECMWF ERA5 data at surface level and is referred to as AgERA5. Acquisition and pre-processing of the original ERA5 data is a complex and specialized job. By providing the AgERA5 dataset, users are freed from this work and can directly start with meaningful input for their analyses and modelling.

calendar_today Interval/period: Mon, 01/01/1979 - Thu, 04/30/2026

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.

calendar_today Interval/period: Thu, 01/01/2015 - Wed, 05/06/2026

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.

calendar_today Interval/period: Tue, 03/01/2011 - Tue, 06/09/2026

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 - Thu, 05/07/2026

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: 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.

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: 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.

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: N/A