Datasets
Displaying 26 - 50 of 159
This data set provides observational records of aerosol properties obtained from observations collected by various satellite instruments. Aerosols are minor constituents of the atmosphere by mass, but critical components in terms of impact on climate. Aerosols influence the global radiation balance directly by scattering and absorbing radiation, and indirectly through influencing cloud reflectivity, cloud cover and cloud lifetime.
Interval/period: Thu, 06/01/1995 - Thu, 07/31/2025
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.
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.
Interval/period: Mon, 01/01/1979 - Thu, 04/30/2026
The C3S Arctic Regional Reanalysis second generation (CARRA2) dataset contains daily and monthly meteorological variables at 2.5 km resolution. These variables are specified at single levels (including surface) and also at soil, height, pressure and model levels. 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: Wed, 01/01/1986 - Sun, 12/31/2023
The C3S Arctic Regional Reanalysis second generation (CARRA2) dataset contains 3-hourly analyses at 2.5 km resolution. These variables are specified at single levels (including surface) and also at soil, height, pressure and model levels. Additionally, hourly forecasts are available between the analysis times and particularly forecasts up to 18 hours initialised from the analyses at 00 and 12 UTC.
Interval/period: Wed, 01/01/1986 - Sun, 12/31/2023
Within the hydrological cycle, precipitation is the main component of water transport from the atmosphere to the Earth’s surface. Precipitation varies strongly, depending on geographical location, season, synopsis, and other meteorological factors. The supply of freshwater through precipitation is vital for many subsystems of the climate and the environment, but there are also hazards related to extensive precipitation or the lack of precipitation.
Interval/period: Mon, 01/01/1979 - Mon, 09/30/2024
This dataset provides global estimates of daily accumulated and monthly means of precipitation. The precipitation estimates are based on a merge of passive microwave observations from two different radiometer classes operating on multiple Low Earth Orbit (LEO) satellites.
Interval/period: Sat, 01/01/2000 - Sun, 12/31/2017
This dataset provides monthly and zonally averaged tropospheric humidity profiles derived from globally distributed GPS radio occultation (RO) measurements from EUMETSAT's Metop polar-orbiting satellites. Humidity plays an important role in the Earth's climate system, due to the strong greenhouse effect of water vapour but also for its role in the global energy transport, vertically in the atmosphere and horizontally between different geographical regions.
Interval/period: Fri, 12/01/2006 - Mon, 12/01/2025
The present UERRA dataset contains analyses of atmospheric variables on height levels, from 1961 to 2019.
Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019
The present UERRA dataset contains analyses of atmospheric variables on pressure levels, from 1961 to 2019.
It has been generated using the UERRA-HARMONIE system by combining model data with observations into a complete and consistent dataset using the laws of physics.
It has been generated using the UERRA-HARMONIE system by combining model data with observations into a complete and consistent dataset using the laws of physics.
Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019
This UERRA dataset contains analyses of surface and near-surface essential climate variables from
UERRA-HARMONIE and MESCAN-SURFEX systems. Forecasts up to 30 hours initialised
from the analyses at 00 and 12 UTC are available only through the CDS-API (see Documentation).
UERRA-HARMONIE is a 3-dimensional variational data assimilation system,
while MESCAN-SURFEX is a complementary surface analysis system.
Using the Optimal Interpolation method, MESCAN provides the best estimate of daily accumulated precipitation
UERRA-HARMONIE and MESCAN-SURFEX systems. Forecasts up to 30 hours initialised
from the analyses at 00 and 12 UTC are available only through the CDS-API (see Documentation).
UERRA-HARMONIE is a 3-dimensional variational data assimilation system,
while MESCAN-SURFEX is a complementary surface analysis system.
Using the Optimal Interpolation method, MESCAN provides the best estimate of daily accumulated precipitation
Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019
The UERRA dataset provides estimations of the climate in Europe based on model data
combined with observations using the UERRA-HARMONIE system and MESCAN-SURFEX system.
UERRA-HARMONIE is a 3-dimensional data assimilation system, whereas
MESCAN-SURFEX is a complementary surface analysis system. In general, the
assimilation systems are able to estimate biases between observations and to
sift good-quality data from poor data. The laws of physics allow for estimates
combined with observations using the UERRA-HARMONIE system and MESCAN-SURFEX system.
UERRA-HARMONIE is a 3-dimensional data assimilation system, whereas
MESCAN-SURFEX is a complementary surface analysis system. In general, the
assimilation systems are able to estimate biases between observations and to
sift good-quality data from poor data. The laws of physics allow for estimates
Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019
Upper Tropospheric Humidity (UTH) is of key importance to the Earth’s greenhouse effect and understanding of climate change. It is considered an Essential Climate Variable (ECV) because it controls key atmospheric processes, including those involved in water vapour and cloud feedbacks, that can amplify the climate system’s response to increases in other greenhouse gases. The Upper Tropospheric Humidity is defined as the integrated amount of Water Vapour in the atmospheric layer between ~500 hPa and ~200 hPa.
Interval/period: Tue, 07/05/1994 - Sun, 02/28/2021
This dataset provides climate indicators of windstorms associated with extratropical cyclones, derived from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses (ERA5) over a pan-European domain. Developed as part of Copernicus Climate Change Service's (C3S) Enhanced Windstorm Service (EWS), and responding to requirements from users in the insurance sector, this dataset extends the previous C3S Windstorm Service (winter months only) to include the entire year.
Interval/period: Thu, 02/01/1940 - Fri, 01/23/2026
This dataset provides climatological indicators on European winter windstorms and their economic impact derived from ERA5 reanalysis. Also provided are risk indicators from a synthetically derived set of physically realistic windstorm events based on modelled climatic conditions. The primary users include the insurance sector, reinsurers and insurance industry service providers in response to their requirements for a catalogue of historic windstorm events within Europe.
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
Volumetric soil moisture
Snow water equivalent
Soil wetness index (root zone)
Runoff water equivalent (surface plus subsurface)
River discharge
Volumetric soil moisture
Snow water equivalent
Soil wetness index (root zone)
Runoff water equivalent (surface plus subsurface)
Interval/period: Thu, 10/11/2018 - Mon, 04/06/2026
This dataset provides an ensemble of forecast time series of gridded hydrological data. The data set is a product of the Global Flood Awareness System (GloFAS) and offers a consistent representation of key hydrological variables across the global domain including:
River discharge
Soil wetness index (root zone)
Snow water equivalent
Runoff water equivalent (surface plus subsurface)
River discharge
Soil wetness index (root zone)
Snow water equivalent
Runoff water equivalent (surface plus subsurface)
Interval/period: Tue, 11/05/2019 - Thu, 05/07/2026
This dataset provides gridded modelled sub-daily and daily hydrological time series forced with meteorological observations. The data set is a consistent representation of the most important hydrological variables across the European Flood Awareness System (EFAS) domain. The temporal resolution is up to 30 years modelled time series of:
River discharge
Volumetric soil moisture
Snow water equivalent
Soil wetness index (root zone)
Runoff water equivalent (surface plus subsurface)
River discharge
Volumetric soil moisture
Snow water equivalent
Soil wetness index (root zone)
Runoff water equivalent (surface plus subsurface)
Interval/period: Tue, 01/01/1991 - Tue, 05/05/2026
This dataset provides gridded modelled daily hydrological time series forced with meteorological reanalysis data. The data set is a product of the Global Flood Awareness System (GloFAS) and offers a consistent representation of key hydrological variables across the global domain including:
River discharge
Soil wetness index (root zone)
Snow water equivalent
Runoff water equivalent (surface plus subsurface)
River discharge
Soil wetness index (root zone)
Snow water equivalent
Runoff water equivalent (surface plus subsurface)
Interval/period: Mon, 01/01/1979 - Tue, 05/05/2026
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 - 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.
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
This dataset provides a gridded modelled time series of river discharge, forced with medium- to sub-seasonal range meteorological reforecasts. The data is a consistent representation of a key hydrological variable across the global domain, and is a product of the Global Flood Awareness System (GloFAS). It is accompanied by an ancillary file for interpretation that provides the upstream area (see the related variables table and associated link in the documentation).
Interval/period: Sun, 01/03/1999 - Sat, 11/25/2023
This dataset, also known as the Long-term Alpine Precipitation Reconstruction (LAPrec), provides gridded fields of monthly precipitation for the Alpine region (eight countries). The dataset is derived from station observations and is provided in two issues:
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.
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
The daily and monthly data of the C3S Arctic Regional Reanalysis (CARRA) dataset contains daily and monthly meteorological variables at 2.5 km resolution. This includes fields at the single levels (including surface) and on pressure, height, soil and model levels.
These daily and monthly data are pre-calculated and have the following types depending on the variables: daily and monthly averages, extremes and totals.
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
The C3S Arctic Regional Reanalysis (CARRA) dataset contains hourly data including 3-hourly analyses and hourly short term forecasts of atmospheric height level meteorological variables (temperature, humidity, wind, and other thermodynamic variables) at 2.5 km resolution. Additionally, forecasts up to 30 hours initialised from the analyses at 00 and 12 UTC are available.
Interval/period: Sat, 09/01/1990 - Sat, 02/28/2026