Atmospheric Model high resolution 15-day forecast (HRES)

Single prediction that uses

observations prior information about the Earth-system ECMWF's highest-resolution model

HRES Direct model output Products offers "High Frequency products"  

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A vast amount of data is archived daily containing IFS (Integrated Forecast System) experiments produced by ECMWF's Research Department or by Member States' users at ECMWF. Basically, an experiment can address any area of meteorology and it is archived accordingly. Users wanting to retrieve Research experiments need to know in advance the name of the specific experiment and its nature. For this information please, contact User Support.

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A meso-scale ensemble system focusing on short range probabilistic forecasts and profiting from advanced multi-scale ALARO physics. Its main purpose is to provide probabilistic forecast on daily basis for the national weather services of RC LACE partners. It also serves as a reliable source of probabilistic information applied to downstream hydrology and energy industry.

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It is the Limited-area Ensemble Prediction System (LEPS), based on COSMO-model and implemented within COSMO (COnsortium for Small-scale Modelling, including Germany, Greece, Israel, Italy, Poland, Romania, Russia, Switzerland) implemented and maintained by Arpae-SIMC.

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Each country's experiments can be accessed via the links below:

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HIRETYCS is the High Resolution Ten Year Climate Simulation. This data set consist of 10-year climate simulations produced at three centres: Centre National de Recherches Météorologiques (CNRM), Max-Planck Institute (MPI) and United Kingdom Met Office.

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ECMWF is a participant in the Development of a European Land Data Assimilation System to predict Floods and Droughts (ELDAS) project funded by the European Union.

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European Reanalysis and Observations for Monitoring project is a EU funded project that provides timely and reliable information about the state and evolution of the European climate. It combines observations from satellites, ground-based stations and results from comprehensive model-based regional reanalyses. By closely monitoring European climate, climate variability and change can be better understood and predicted.

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A set of experiments from four centres: ECMWF, Météo-France, EDF and Met Office. The experiments are 120 day runs from 9 consecutive starting days, with write-ups every 24 hours of Pressure level and Surface data.

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The objective of UERRA is to produce ensembles of European regional meteorological reanalyses of Essential Climate Variables (ECVs) for several decades and to estimate the associated uncertainties in the data sets. It also includes recovery of historical (last century) data. UERRA datasets come from 5 Numerical Weather Predication models: COSMO, HARMONIE, MESAN, MESCAN-SURFEX and UM/4DVAR.

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A routine inter-comparison of wave model forecast verification data was first established in 1995, developed around the exchange of model forecast data at an agreed list of moored buoy sites at which instrumented observations of significant wave height, wave period and wind speed are available over the WMO GTS.

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This dataset provides daily air quality analyses and forecasts for Europe.
CAMS produces specific daily air quality analyses and forecasts for the European
domain at significantly higher spatial resolution (0.1 degrees, approx. 10km)
than is available from the global analyses and forecasts. The production is
based on an ensemble of eleven air quality forecasting systems across Europe. A
median ensemble is calculated from individual outputs, since ensemble products

calendar_today Interval/period: Wed, 05/03/2023 - Fri, 05/08/2026

This dataset provides daily air quality forecasts at European observation
stations after optimisation using a statistical post-processing method called
Model Output Statistics (MOS). The unoptimised "raw" forecasts are also
provided in the same format.
The MOS method uses machine learning with predictive variables including
background air quality observation datasets, ECMWF meteorological forecasts and
the "raw" CAMS European air quality ensemble median forecast. The result is

calendar_today Interval/period: Wed, 01/17/2024 - Fri, 05/08/2026

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

calendar_today Interval/period: Tue, 01/01/2013 - Tue, 12/31/2024

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 Global atmospheric composition forecast production system is used to produce the daily forecasts of pollutants, aerosols and greenhouse gases across the globe. Satellite observations of atmospheric composition are merged with a detailed computer simulation of the atmosphere using a method called data assimilation. The resulting analyses, i.e.

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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.

calendar_today Interval/period: Wed, 01/01/2003 - Wed, 12/03/2025

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

calendar_today Interval/period: Sat, 01/01/2000 - Thu, 12/31/2020

CAMS produces global forecasts for the two main long-lived greenhouse gases once a day. This dataset consists of 5-day high-resolution forecasts of carbon dioxide (CO2) and methane (CH4). Additionally, carbon monoxide (CO) and meteorological parameters relevant to the CAMS greenhouse gas forecast are included.

calendar_today Interval/period: Fri, 03/01/2024 - Thu, 05/07/2026

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: Wed, 01/01/2003 - Thu, 12/31/2020

This data set contains net fluxes at the surface, atmospheric mixing ratios at model levels, and column-mean atmospheric mixing ratios for carbon dioxide (CO2), methane (CH4) and nitrous oxide (N20).

calendar_today Interval/period: Mon, 01/01/1979 - Tue, 12/31/2024

This dataset provides aerosol optical depths and aerosol-radiation radiative effects for four different aerosol origins: anthropogenic, mineral dust, marine, and land-based fine-mode natural aerosol. The latter mostly consists of biogenic aerosols.

calendar_today Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017

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
interactions between anthropogenic aerosols and clouds

calendar_today Interval/period: Wed, 01/01/2003 - Sun, 12/31/2017

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: Wed, 01/01/2003 - Thu, 10/31/2024