Datasets
Displaying 151 - 165 of 165
This entry covers single-level data aggregated on a monthly time resolution.
Interval/period: Thu, 01/01/1981 - Mon, 06/01/2026
This dataset offers modeled daily fire danger time series, driven by seasonal weather forecasts. It provides long-range predictions of meteorological conditions conducive to the initiation, spread, and persistence of fires. The fire danger metrics included in this dataset are part of an extensive dataset produced by the Copernicus Emergency Management Service (CEMS) for the European Forest Fire Information System (EFFIS) and the Global Wildfire Information System (GWIS).
Interval/period: Sun, 02/01/1981 - Fri, 05/01/2026
This entry covers pressure-level data at the original time resolution (once every 12 hours).
Interval/period: Thu, 01/01/1981 - Mon, 06/01/2026
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
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).
Interval/period: Tue, 10/01/2002 - Sun, 04/12/2026
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.
Interval/period: Fri, 01/01/1993 - Fri, 01/16/2026
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, 06/01/2026
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 - Wed, 07/01/2026
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 - Sun, 06/28/2026
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 - Mon, 06/29/2026
This dataset provides global daily estimates of ocean surface chlorophyll-a concentration and remote sensing reflectance derived from multiple satellite sensors. These two products are part of the broader discipline of ocean colour remote sensing, which analyses ocean surface radiances measured from space to derive information about the optical properties and constituents of the upper ocean.
Interval/period: Thu, 09/04/1997 - Tue, 12/31/2024
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
This dataset provides a complete historical reconstruction for a set of indices representing human thermal stress and discomfort in outdoor conditions. This dataset, also known as ERA5-HEAT (Human thErmAl comforT) represents the current state-of-the-art for bioclimatology data record production.
The dataset is organised around two main variables:
the mean radiant temperature (MRT)
the universal thermal climate index (UTCI)
The dataset is organised around two main variables:
the mean radiant temperature (MRT)
the universal thermal climate index (UTCI)
Interval/period: Fri, 12/01/1939 - Fri, 06/26/2026
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