Datasets
Displaying 76 - 100 of 165
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.
Interval/period: N/A
Fire radiative power and active fire pixels from 2020 to present derived from satellite observations
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.
Interval/period: Wed, 01/01/2020 - Fri, 02/28/2025
This dataset provides global Terrestrial Water Storage Anomalies (TWSA) on a 0.5° regular grid. TWSA represent deviations from the long-term average of water stored on or below the Earth’s surface in the form of soil moisture, groundwater, surface water, snow and ice. Designated as an Essential Climate Variable (ECV) as defined by the Global Climate Observing System (GCOS), TWSA is considered essential for contributing to a comprehensive view of Earth’s climate, its variability, and trends.
Interval/period: Thu, 04/04/2002 - Tue, 04/01/2025
This catalogue entry provides a time series of thermal comfort indices, organised to make time the primary dimension for analysis and extraction. For any user-defined location (point) or small area, the dataset returns the temporal evolution of the selected variables, enabling efficient time-series studies without requiring users to download and manage full global gridded files.
Interval/period: Mon, 01/01/1940 - Fri, 05/09/2025
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 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 provides a gridded modelled time series of river discharge forced with 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: Thu, 01/01/1981 - Sat, 07/01/2023
The dataset presents wave climate indicators based upon ocean surface wave parameters computed for a European-wide domain. This dataset provides an understanding of the European wave climate under the impact of climate change. It provides added value for various coastal sectors and studies such as port, shipping, and coastal management.
Interval/period: Thu, 01/01/1976 - Fri, 12/31/2100
The dataset presents time series of the coastal wave climate based upon ocean surface wave parameters computed for a European-wide domain. This dataset provides an understanding of the wave climate under the impact of climate change for the Northwest European Shelf and Mediterranean Sea. It provides added value for various coastal sectors and studies such as port, shipping, and coastal management.
Interval/period: Thu, 01/01/1976 - Fri, 12/31/2100
This catalogue entry provides monthly mean time series from the global ocean and sea-ice reanalysis ORAS5 (Ocean Reanalysis System 5), with data organised to prioritise temporal access at grid point locations rather than full spatial fields. The dataset enables users to efficiently retrieve long, continuous time series for individual ocean points, supporting analyses of ocean variability and change without the need to download and process large global gridded datasets.
Interval/period: Wed, 01/01/1958 - Wed, 01/01/2025
This dataset provides monthly averaged ozone values derived from a large set of satellite sensors with global coverage. Ozone is naturally formed in the atmosphere through the interaction between molecular oxygen and solar radiation. In the stratosphere, it acts as a shield protecting us from the UV radiation emitted by the Sun. At ground level however, it is a human health irritant and a component of smog. Ozone and climate change are strongly related.
Interval/period: Wed, 04/01/1970 - Tue, 07/01/2025
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: Tue, 10/01/1985 - Wed, 12/31/2025
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: Sun, 09/01/1985 - Wed, 12/31/2025
This dataset provides atmospheric CH₄ observations as derived from satellite radiances. It consists of two types of products each covering a different part of the atmosphere: (i) The average CH₄ mixing ratio of the entire atmosphere from the Earth’s surface to the top of the atmosphere. These column-averaged mixing ratio products are referred to as “XCH4” products. (ii) Mid-tropospheric (MT) CH₄ mixing ratio products. These products are referred to as "MTCH4" products. These products can be used to monitor the spatial distribution and temporal evolution of CH₄.
Interval/period: Tue, 10/01/2002 - Mon, 06/30/2025
Water vapour is has been recognised as an Essential Climate Variable as it provides the basis for all cloud formation and physics and furthermore influences the Earth's heat budget due to its high absorbance of long and short-wave radiation. Total column water vapour (TCWV) is a measure of the integrated water vapour content of the atmosphere.
This catalogue entry provides the TCWV data product usually called Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS).
This catalogue entry provides the TCWV data product usually called Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data (HOAPS).
Interval/period: Wed, 05/01/2002 - Thu, 03/01/2012
This dataset provides meteorological and snow indicators for Europe, characterizing operating conditions of winter ski resorts under past and future climate scenarios. The dataset consists of 39 indicators of atmospheric and snow conditions computed in a similar manner for all mountain regions in Europe at the scale of NUTS-3 regions (Nomenclature of Territorial Units for Statistics) and by steps of 100 m elevation.
Interval/period: Sun, 01/01/1950 - Fri, 01/01/2100
This dataset provides hydrological seasonal reforecasts of monthly mean river discharge across Europe for the period 1993 to 2016. The first is an E-HYPE multi-model system comprising eight model realisations using a catchment-based resolution. The second comprises the E-HYPEgrid, VIC-WUR and LISFLOOD-EFAS hydrological models at a 5km gridded resolution.
Interval/period: Fri, 01/01/2021 - Sat, 07/04/2026
This dataset provides bias-corrected reconstruction of near-surface meteorological variables derived from the fifth generation of the European Centre for Medium-Range Weather Forecasts (ECMWF) atmospheric reanalyses (ERA5). It is intended to be used as a meteorological forcing dataset for land surface and hydrological models.
Interval/period: Mon, 01/01/1979 - Tue, 12/31/2024
The Nordic Gridded Climate Dataset (NGCD) is a high resolution, observational, gridded dataset of daily minimum, maximum and mean temperatures and daily precipitation totals, covering Finland, Sweden and Norway. The time period covered begins in January 1961 and continues to the present.
Spatial interpolation methods are applied to observational datasets to create gridded datasets.
In general, there are three types of such methods: deterministic (type 1), stochastic (type 2) and pure mathematical (type 3).
Spatial interpolation methods are applied to observational datasets to create gridded datasets.
In general, there are three types of such methods: deterministic (type 1), stochastic (type 2) and pure mathematical (type 3).
Interval/period: Sun, 01/01/1961 - Thu, 09/18/2025
This set of data holdings provides access to data collected from land surface meteorological observations across the globe. Data are available at the observational level and also at daily and monthly aggregations. Data have been collated and harmonised and quality control checks have been performed, but no attempt has been made to assess for potential biases. Data are provided for a range of commonly observed variables.
Interval/period: Sun, 01/01/1978 - Wed, 10/17/2018
This dataset provides surface-level particulate matter (PM2.5 and PM10) concentrations derived from in situ low-cost sensor (LCS) measurements, produced by the European Centre for Medium-Range Weather Forecasts (ECMWF) in the context of the Horizon Europe All Data for Green Deal project. This dataset differs from existing air quality datasets by combining crowdsourced observations with a robust correction framework, producing high-resolution, reference-aligned gridded products.
Interval/period: Mon, 01/01/2018 - Tue, 12/31/2024