This dataset provides daily mid-morning measurements for Lake Surface Water Temperature (LSWT) derived from satellite observations. LSWT, together with five other variables (lake ice cover and thickness, water leaving reflectance, water level and extent) is recognised as the Essential Climate Variable (ECV) "Lakes" by the Global Climate Observing System (GCOS). LSWT is a key parameter in determining lake ecological conditions as it influences physical, chemical and biological processes.

calendar_today Interval/period: Thu, 06/01/1995 - Sat, 05/09/2026

This dataset provides lake water levels for 311 selected lakes on four continents derived from satellite radar altimetry.

calendar_today Interval/period: Wed, 01/01/1992 - Sat, 05/09/2026

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 dataset presents climate impact indicators related to extreme precipitation in Europe under current climate conditions. The suite of indicators include recent historic records, recurrence intervals, and other relevant statistical measures to evaluate the magnitude and frequency of extreme precipitation events. These are provided as gridded products, with one product covering the whole of Europe, and the other higher resolution product focused on 20 European cities that were identified as vulnerable to urban pluvial flooding based on stakeholder surveys.

calendar_today Interval/period: Sun, 01/01/1950 - Tue, 12/31/2019

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.

calendar_today 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.

calendar_today 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.

calendar_today 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.

calendar_today Interval/period: Sat, 01/01/2000 - Sun, 12/31/2017

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

calendar_today Interval/period: Thu, 10/18/2018 - Wed, 07/31/2019

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)

calendar_today Interval/period: Thu, 10/11/2018 - Mon, 04/06/2026

open_in_newview in EWDS

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
Soil moisture for three soil layers
Snow water equivalent

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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)

calendar_today Interval/period: Tue, 11/05/2019 - Thu, 05/07/2026

open_in_newview in EWDS
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)

calendar_today 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)

calendar_today Interval/period: Mon, 01/01/1979 - Tue, 05/05/2026

This dataset provides gridded modelled hydrological time series forced with medium- to sub-seasonal range meteorological reforecasts. The data is a consistent representation of the most important hydrological variables across the European Flood Awareness System (EFAS) domain. The temporal resolution is 20 years of sub-daily reforecasts initialised twice weekly (Mondays and Thursdays) of:

River discharge
Volumetric soil moisture
Snow water equivalent
Soil wetness index (root zone)
Runoff water equivalent (surface plus subsurface)

calendar_today Interval/period: Wed, 10/14/2020 - Sat, 05/09/2026

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).

calendar_today Interval/period: Sun, 01/03/1999 - Sat, 11/25/2023

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.

calendar_today Interval/period: Sat, 09/01/1990 - Sat, 02/28/2026

This dataset provides daily air quality analyses and forecasts for Europe.

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This dataset provides annual air quality reanalyses for Europe based on both unvalidated (interim) and validated observations.

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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.

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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.

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

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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

calendar_today Interval/period: N/A

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: N/A

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: N/A