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. This principle, called data assimilation, is based on the method used by numerical weather prediction centres and air quality forecasting centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way to allow for the provision of a dataset spanning back more than a decade. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. The assimilation system is able to estimate biases between observations and to sift good-quality data from poor data. The atmosphere model allows for estimates at locations where data coverage is low or for atmospheric pollutants for which no direct observations are available. The provision of estimates at each grid point around the globe for each regular output time, over a long period, always using the same format, makes reanalysis a very convenient and popular dataset to work with. The observing system has changed drastically over time, and although the assimilation system can resolve data holes, the initially much sparser networks will lead to less accurate estimates. For this reason, EAC4 is only available from 2003 onwards. Although the analysis procedure considers chunks of data in a window of 12 hours in one go, EAC4 provides estimates every 3 hours, worldwide. This is made possible by the 4D-Var assimilation method, which takes account of the exact timing of the observations and model evolution within the assimilation window.

including aerosols

ERA5 is the fifth generation ECMWF atmospheric reanalysis of the global climate covering the period from January 1940 to present. It is produced by the Copernicus Climate Change Service (C3S) at ECMWF and provides hourly estimates of a large number of atmospheric, land and oceanic climate variables. The data cover the Earth on a 31km grid and resolve the atmosphere using 137 levels from the surface up to a height of 80km. ERA5 includes an ensemble component at half the resolution to provide information on synoptic uncertainty of its products. ERA5.1 is a dedicated product with the same horizontal and vertical resolution that was produced for the years 2000 to 2006 inclusive to significantly improve a discontinuity in global-mean temperature in the stratosphere and uppermost troposphere that ERA5 suffers from during that period. Users that are interested in this part of the atmosphere in this era are advised to access ERA5.1 rather than ERA5. ERA5 and ERA5.1 use a state-of-the-art numerical weather prediction model to assimilate a variety of observations, including satellite and ground-based measurements, and produces a comprehensive and consistent view of the Earth's atmosphere. These products are widely used by researchers and practitioners in various fields, including climate science, weather forecasting, energy production and machine learning among others, to understand and analyse past and current weather and climate conditions.

ERA5 is the fifth generation ECMWF reanalysis for the global climate and weather for the past 8 decades. Data is available from 1940 onwards. ERA5 replaces the ERA-Interim reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. This principle, called data assimilation, is based on the method used by numerical weather prediction centres, where every so many hours (12 hours at ECMWF) a previous forecast is combined with newly available observations in an optimal way to produce a new best estimate of the state of the atmosphere, called analysis, from which an updated, improved forecast is issued. Reanalysis works in the same way, but at reduced resolution to allow for the provision of a dataset spanning back several decades. Reanalysis does not have the constraint of issuing timely forecasts, so there is more time to collect observations, and when going further back in time, to allow for the ingestion of improved versions of the original observations, which all benefit the quality of the reanalysis product. ERA5 provides hourly estimates for a large number of atmospheric, ocean-wave and land-surface quantities. An uncertainty estimate is sampled by an underlying 10-member ensemble at three-hourly intervals. Ensemble mean and spread have been pre-computed for convenience. Such uncertainty estimates are closely related to the information content of the available observing system which has evolved considerably over time. They also indicate flow-dependent sensitive areas. To facilitate many climate applications, monthly-mean averages have been pre-calculated too, though monthly means are not available for the ensemble mean and spread. ERA5 is updated daily with a latency of about 5 days. In case that serious flaws are detected in this early release (called ERA5T), this data could be different from the final release 2 to 3 months later. In case that this occurs users are notified. The data set presented here is a regridded subset of the full ERA5 data set on native resolution. It is online on spinning disk, which should ensure fast and easy access. It should satisfy the requirements for most common applications. An overview of all ERA5 datasets can be found in this article. Information on access to ERA5 data on native resolution is provided in these guidelines. Data has been regridded to a regular lat-lon grid of 0.25 degrees for the reanalysis and 0.5 degrees for the uncertainty estimate (0.5 and 1 degree respectively for ocean waves). There are four main sub sets: hourly and monthly products, both on pressure levels (upper air fields) and single levels (atmospheric, ocean-wave and land surface quantities). The present entry is "ERA5 hourly data on single levels from 1940 to present".

i.e.

This data set contains gridded distributions of global anthropogenic and natural emissions. Natural and anthropogenic emissions of atmospheric pollutants and greenhouse gases are key drivers of the evolution of the composition of the atmosphere, so an accurate representation of them in forecast models of atmospheric composition is essential. CAMS compiles inventories of emission data that serve as input to its own forecast models, but which can also be used by other atmospheric chemical transport models. These inventories are based on a combination of existing data sets and new information, describing anthropogenic emissions from fossil fuel use on land, shipping, and aviation, and natural emissions from vegetation, soil, the ocean and termites. The anthropogenic emissions on land are further separated in specific activity sectors (e.g., power generation, road traffic, industry). The CAMS emission data sets provide good consistency between the emissions of greenhouse gases, reactive gases, and aerosol particles and their precursors. Because most inventory-based data sets are only available with a delay of several years, the CAMS emission inventories also extend these existing data sets forward in time by using the trends from the most recent available years, producing timely input data for real-time forecast models. Most of the data sets are updated once or twice per year adding the most recent year to the data record, while re-processing the original data record for consistency, when needed. This is reflected by the different version numbers.

ERA5 Monthly Aggregates - Latest Climate Reanalysis produced by ECMWF / Copernicus Climate Change Service

ERA5 is the fifth generation ECMWF atmospheric reanalysis of the global climate. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset. ERA5 replaces its predecessor, the ERA-Interim reanalysis.

ERA5 MONTHLY provides aggregated values for each month for seven ERA5 climate reanalysis parameters: 2m air temperature, 2m dewpoint temperature, total precipitation, mean sea level pressure, surface pressure, 10m u-component of wind and 10m v-component of wind. Additionally, monthly minimum and maximum air temperature at 2m has been calculated based on the hourly 2m air temperature data. Monthly total precipitation values are given as monthly sums. All other parameters are provided as monthly averages.

ERA5 data is available from 1979 to three months from real-time. More information and more ERA5 atmospheric parameters can be found at the Copernicus Climate Data Store (https://cds.climate.copernicus.eu/).

Provider's Note: Monthly aggregates have been calculated based on the ERA5 hourly values of each parameter.

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

Radiative forcing measures the imbalance in the Earth’s energy budget caused by a perturbation of the climate system, such as changes in atmospheric composition caused by human activities. RF is a useful predictor of globally-averaged temperature change, especially when rapid adjustments of atmospheric temperature and moisture profiles are taken into account. RF has therefore become a quantitative metric to compare the potential climate response to different perturbations. Increases in greenhouse gas concentrations over the industrial era exerted a positive RF, causing a gain of energy in the climate system. In contrast, concurrent changes in atmospheric aerosol concentrations are thought to exert a negative RF leading to a loss of energy. Products are quantified both in “all-sky” conditions, meaning that the radiative effects of clouds are included in the radiative transfer calculations, and in “clear-sky” conditions, which are computed by excluding clouds in the radiative transfer calculations. The upgrade from version 1.5 to 2 consists of an extension of the period by 2017-2018, the addition of an "effective radiative forcing" product and new ways to calculate the pre-industrial reference state for aerosols and cloud condensation nuclei. More details are given in the documentation section. New versions may be released in future as scientific methods develop, and existing versions may be extended with later years if data for the period is available from the CAMS reanalysis. Newer versions supercede old versions so it is always recommended to use the latest one. CAMS also produces distributions of aerosol optical depths, distinguishing natural from anthropogenic aerosols, which are a separate dataset. See "Related Data".

The North America CORDEX (NA-CORDEX) dataset contains regional climate change scenario data and guide for North America, for use in impacts, decision-making, and climate science. This dataset contains output from ... regional climate models (RCMs) run over a domain covering most of North America using boundary conditions from global climate model (GCM) simulations in the CMIP5 archive. These simulations run from 1950 to 2100 with a spatial resolution of 0.22 degree (25km) or 0.44 degree (50km). This version of the data is the same as the AWS S3 version. It includes selected variables converted to the Zarr format from the original NetCDF. Only daily data are currently available; all daily data were mapped to the standard calendar.

The Country Trends in Major Air Pollutants data set is a framework of public-health-focused air quality indicators that quantifies over 200 countries' trends in exposure to Particulate Matter (PM2.5), Ozone (O3), Nitrogen Oxides (NOx), Sulfur Dioxide (SO2), Carbon Monoxide (CO), and Volatile Organic Compounds (VOCs). Pollutant concentration data are derived from the European Centre for Medium-Range Weather Forecasts (ECMWF) Atmospheric Composition Reanalysis 4 (EAC4) data sets, freely available from the Copernicus Atmospheric Monitoring Services' Atmospheric Data Store (https://ads.atmosphere.copernicus.eu). CIESIN's Gridded Population of the World, Version 4 (GPWv4): Population Count Adjusted to Match 2015 Revision of UN WPP Country Totals, Revision 11 was used in the population weighting algorithm.

Overview: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past.

Air temperature (2 m): Temperature of air at 2m above the surface of land, sea or in-land waters. 2m temperature is calculated by interpolating between the lowest model level and the Earth's surface, taking account of the atmospheric conditions.

Processing steps: The original hourly ERA5-Land data has been spatially enhanced from 0.1 degree to 30 arc seconds (approx. 1000 m) spatial resolution by image fusion with CHELSA data (V1.2) (https://chelsa-climate.org/). For each day we used the corresponding monthly long-term average of CHELSA. The aim was to use the fine spatial detail of CHELSA and at the same time preserve the general regional pattern and fine temporal detail of ERA5-Land. The steps included aggregation and enhancement, specifically: 1. spatially aggregate CHELSA to the resolution of ERA5-Land 2. calculate difference of ERA5-Land - aggregated CHELSA 3. interpolate differences with a Gaussian filter to 30 arc seconds 4. add the interpolated differences to CHELSA

The spatially enhanced daily ERA5-Land data has been aggregated on a weekly basis starting from Saturday for the time period 2016 - 2020. Data available is the weekly average of daily averages, the weekly minimum of daily minima and the weekly maximum of daily maxima of air temperature (2 m).

File naming: Average of daily average: era5_land_t2m_avg_weekly_YYYY_MM_DD.tif Max of daily max: era5_land_t2m_max_weekly_YYYY_MM_DD.tif Min of daily min: era5_land_t2m_min_weekly_YYYY_MM_DD.tif

The date in the file name determines the start day of the week (Saturday).

Pixel value: °C * 10 Example: Value 44 = 4.4 °C

The QML or SLD style files can be used for visualization of the temperature layers.

Coordinate reference system: ETRS89 / LAEA Europe (EPSG:3035) (EPSG:3035)

Spatial extent: north: 82:00:30N south: 18N west: 32:00:30W east: 70E

Spatial resolution: 1km

Temporal resolution: weekly

Time period: 01/01/2016 - 12/31/2020

Format: GeoTIFF

Representation type: Grid

Software used: GDAL 3.2.2 and GRASS GIS 8.0.0 (r.resamp.stats -w; r.relief)

Lineage: Dataset has been processed from original Copernicus Climate Data Store (ERA5-Land) data sources. As auxiliary data CHELSA climate data has been used.

Original ERA5-Land dataset license: https://cds.climate.copernicus.eu/api/v2/terms/static/licence-to-use-copernicus-products.pdf

CHELSA climatologies (V1.2): Data used: Karger D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E, Linder, H.P., Kessler, M. (2018): Data from: Climatologies at high resolution for the earth's land surface areas. Dryad digital repository. http://dx.doi.org/doi:10.5061/dryad.kd1d4 Original peer-reviewed publication: Karger, D.N., Conrad, O., Böhner, J., Kawohl, T., Kreft, H., Soria-Auza, R.W., Zimmermann, N.E., Linder, P., Kessler, M. (2017): Climatologies at high resolution for the Earth land surface areas. Scientific Data. 4 170122. https://doi.org/10.1038/sdata.2017.122

Other resources: https://data.mundialis.de/geonetwork/srv/eng/catalog.search#/metadata/601ea08c-0768-4af3-a8fa-7da25fb9125b

Processed by: mundialis GmbH & Co. KG, Germany (https://www.mundialis.de/)

Contact: mundialis GmbH & Co. KG, info@mundialis.de

Overview: 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. The ECV data products in this set have been estimated from climate reanalyses ERA-Interim and ERA5, and, depending on the source, may have been adjusted to account for biases and other known deficiencies. Data sources and adjustment methods used are described in the Product User Guide, as are various particulars such as the baseline periods used to calculate monthly climatologies and the corresponding anomalies. Sum of monthly precipitation: This variable is the accumulated liquid and frozen water, including rain and snow, that falls to the Earth's surface. It is the sum of large-scale precipitation (that precipitation which is generated by large-scale weather patterns, such as troughs and cold fronts) and convective precipitation (generated by convection which occurs when air at lower levels in the atmosphere is warmer and less dense than the air above, so it rises). Precipitation variables do not include fog, dew or the precipitation that evaporates in the atmosphere before it lands at the surface of the Earth. Spatial resolution: 0:15:00 (0.25°) Temporal resolution: monthly Temporal extent: 1979 - present Data unit: mm * 10 Data type: UInt32 CRS as EPSG: EPSG:4326 Processing time delay: one month

This dataset contains ERA5 initial release (ERA5t) surface level analysis parameter data from 10 member ensemble runs. ERA5t is the European Centre for Medium-Range Weather Forecasts (ECWMF) ERA5 reanalysis project initial release available upto 5 days behind the present data. CEDA will maintain a 6 month rolling archive of these data with overlap to the verified ERA5 data - see linked datasets on this record. Ensemble means and spreads were calculated from the ERA5t 10 member ensemble, run at a reduced resolution compared with the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation, for which these data have been produced to provide an uncertainty estimate. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record. See linked datasets for ensemble member and spread data. Note, ensemble standard deviation is often referred to as ensemble spread and is calculated as the standard deviation of the 10-members in the ensemble (i.e., including the control). It is not the sample standard deviation, and thus were calculated by dividing by 10 rather than 9 (N-1). See linked datasets for ensemble mean and ensemble spread data. The ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects. An initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed and, if required, amended before the full ERA5 release. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record.

This dataset, the International Comprehensive Ocean-Atmosphere Data Set (ICOADS), is the most widely-used freely available collection of surface marine observations, with over 455 million individual marine reports spanning 1662-2014-each containing the observations and metadata reported from a given ship, buoy, coastal platform, or oceanographic instrument, providing data for the construction of gridded analyses of sea surface temperature, estimates of air-sea interaction and other meteorological variables. ICOADS observations are assimilated into all major atmospheric, oceanic and coupled reanalyses, further widening its impact. R3.0 therefore includes changes designed to enable effective exchange of information describing data quality between ICOADS, reanalysis centres, data set developers, scientists and the public. These user-driven innovations include the assignment of a unique identifier (UID) to each marine report-to enable tracing of observations, linking with reports and improved data sharing. Other revisions and extensions of the ICOADS' International Maritime Meteorological Archive (IMMA) common data format incorporate new near-surface oceanographic data elements and cloud parameters. Many new input data sources have been assembled, and updates and improvements to existing data sources, or removal of erroneous data, made. The ICOADS Monthly Summaries Group (MSG) are designed to store both 1-degree, and 2-degree, latitude x longitude monthly summaries (the format also has the capability, unused at present, to store 0.5-degree data). MSG products are currently available covering the global domain (1-degree and/or 2-degree boxes) and an equatorial domain (1-degree), with 2-degree products available from 1800 forward and 1-degree products available only for 1960 forward. Six "groups" of variables make up MSG. The variables comprise the 19 variables that were produced for COADS Release 1 (groups 3-7) plus three additional variables that make up group 9: the cube of the wind speed, W**3, as well as the zonal and meridional contributions to the latent heat flux, U(QS-Q) and V(QS-Q).

This dataset contains ERA5 surface level forecast parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record. Model and surface level analysis data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset. The ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects. An initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that "ERA5.1 is very close to ERA5 in the lower and middle troposphere." but users of data from this period should read the technical memo 859 for further details.

Contains data generated by the CAMS model (during a global reanalysis), used to train and evaluate the models presented in the following scientific article :

Dabrowski, Mennesson, Riedi, Djeraba "Semi-supervised GAN with sparse ground truth as Boundary Conditions" International Joint Conference on Neural Networks (2023)
https://ieeexplore.ieee.org/document/10191911

This data can be downloaded from the Copernicus Atmospheric Data Store (https://ads.atmosphere.copernicus.eu/#!/home), and is also hosted by the ICARE Data and Services Center (https://www.icare.univ-lille.fr/).

This dataset only contains the specific data collection used for the experiments presented in aforementioned article. It is only a portion of the data available from these two websites.

This dataset contains ERA5 model level analysis parameter data. ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record. Surface level analysis and forecast data to complement this dataset are also available. Data from a 10 member ensemble, run at lower spatial and temporal resolution, were also produced to provide an uncertainty estimate for the output from the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation producing data in this dataset. The ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects. An initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that "ERA5.1 is very close to ERA5 in the lower and middle troposphere." but users of data from this period should read the technical memo 859 for further details.

This dataset contains ERA5 surface level analysis parameter data ensemble means (see linked dataset for spreads). ERA5 is the 5th generation reanalysis project from the European Centre for Medium-Range Weather Forecasts (ECWMF) - see linked documentation for further details. The ensemble means and spreads are calculated from the ERA5 10 member ensemble, run at a reduced resolution compared with the single high resolution (hourly output at 31 km grid spacing) 'HRES' realisation, for which these data have been produced to provide an uncertainty estimate. This dataset contains a limited selection of all available variables and have been converted to netCDF from the original GRIB files held on the ECMWF system. They have also been translated onto a regular latitude-longitude grid during the extraction process from the ECMWF holdings. For a fuller set of variables please see the linked Copernicus Data Store (CDS) data tool, linked to from this record. Note, ensemble standard deviation is often referred to as ensemble spread and is calculated as the standard deviation of the 10-members in the ensemble (i.e., including the control). It is not the sample standard deviation, and thus were calculated by dividing by 10 rather than 9 (N-1). See linked datasets for ensemble member and ensemble mean data. The ERA5 global atmospheric reanalysis of the covers 1979 to 2 months behind the present month. This follows on from the ERA-15, ERA-40 rand ERA-interim re-analysis projects. An initial release of ERA5 data (ERA5t) is made roughly 5 days behind the present date. These will be subsequently reviewed ahead of being released by ECMWF as quality assured data within 3 months. CEDA holds a 6 month rolling copy of the latest ERA5t data. See related datasets linked to from this record. However, for the period 2000-2006 the initial ERA5 release was found to suffer from stratospheric temperature biases and so new runs to address this issue were performed resulting in the ERA5.1 release (see linked datasets). Note, though, that Simmons et al. 2020 (technical memo 859) report that "ERA5.1 is very close to ERA5 in the lower and middle troposphere." but users of data from this period should read the technical memo 859 for further details.

PLEASE NOTE. It is advised to use ds633.0, ERA5 Reanalysis (0.25 Degree Latitude-Longitude Grid) [https://rda.ucar.edu/datasets/ds633-0/].

ECMWF has announced that the Copernicus Climate Change Service (C3S) has begun the release of the ERA5 back extension data covering the period 1950-1978 on the Climate Data Store (CDS).

Although in many other respects the quality of this dataset is quite satisfactory, the current back extension appears to suffer from tropical cyclones that are sometimes unrealistically intense. This is in contrast with the ERA5 product from 1979 onwards (also available from the CDS and RDA ds633.0). For this reason the current release of the back extension is preliminary.

It is therefore available from separate CDS catalogue entries (hourly, monthly, single level and pressure levels), and this RDA dataset. Around the end of 2021 an updated version of the back extension is to be made available which will be added to the ERA5 catalogue entries that currently reach back to 1979. After an overlap period (the duration of which is not yet decided), the preliminary back extension will be deprecated.

The full back extension preliminary dataset is expected to be made available near the end of 2020/early 2021.

After many years of research and technical preparation, the production of a new ECMWF climate reanalysis to replace ERA-Interim is in progress. ERA5 is the fifth generation of ECMWF atmospheric reanalyses of the global climate, which started with the FGGE reanalyses produced in the 1980s, followed by ERA-15, ERA-40 and most recently ERA-Interim. ERA5 will cover the period January 1950 to near real time.

ERA5 is produced using high-resolution forecasts (HRES) at 31 kilometer resolution (one fourth the spatial resolution of the operational model) and a 62 kilometer resolution ten member 4D-Var ensemble of data assimilation (EDA) in CY41r2 of ECMWF's Integrated Forecast System (IFS) with 137 hybrid sigma-pressure (model) levels in the vertical, up to a top level of 0.01 hPa. Atmospheric data on these levels are interpolated to 37 pressure levels (the same levels as in ERA-Interim). Surface or single level data are also available, containing 2D parameters such as precipitation, 2 meter temperature, top of atmosphere radiation and vertical integrals over the entire atmosphere. The IFS is coupled to a soil model, the parameters of which are also designated as surface parameters, and an ocean wave model. Generally, the data is available at an hourly frequency and consists of analyses and short (12 hour) forecasts, initialized twice daily from analyses at 06 and 18 UTC. Most analyses parameters are also available from the forecasts. There are a number of forecast parameters, e.g. mean rates and accumulations, that are not available from the analyses.

Improvements to ERA5, compared to ERA-Interim, include use of HadISST.2, reprocessed ECMWF climate data records (CDR), and implementation of RTTOV11 radiative transfer. Variational bias corrections have not only been applied to satellite radiances, but also ozone retrievals, aircraft observations, surface pressure, and radiosonde profiles.

DECS produces a CF 1.6 compliant netCDF-4/HDF5 version of ERA5 for the CISL RDA at NCAR. The netCDF-4/HDF5 version is the de facto RDA ERA5 online data format. The GRIB1 data format is also available online. There is a one-to-one correspondence between the netCDF-4/HDF5 and GRIB1 files, with as much GRIB1 metadata as possible incorporated into the attributes of the netCDF-4/HDF5 counterpart.

Overview: era5.copernicus: surface temperature daily averages from 2000 to 2020 resampled with CHELSA to 1 km resolution Traceability (lineage): The data sources used to generate this dataset are ERA5-Land hourly data from 1950 to present (Copernicus Climate Data Store) and CHELSA monthly climatologies. Scientific methodology: The methodology used for downscaling follows established procedures as used by e.g. Worldclim and CHELSA. Usability: The substantial improvement of the spatial resolution together with the high temporal resolution of one day further improve the usability of the original ERA5 Land time series product which is useful for all kind of land surface applications such as flood or drought forecasting. The temporal and spatial resolution of this dataset, the period covered in time, as well as the fixed grid used for the data distribution at any period enables decisions makers, businesses and individuals to access and use more accurate information on land states. Uncertainty quantification: The ERA5-Land dataset, as any other simulation, provides estimates which have some degree of uncertainty. Numerical models can only provide a more or less accurate representation of the real physical processes governing different components of the Earth System. In general, the uncertainty of model estimates grows as we go back in time, because the number of observations available to create a good quality atmospheric forcing is lower. ERA5-land parameter fields can currently be used in combination with the uncertainty of the equivalent ERA5 fields. Data validation approaches: Validation of the ERA5 Land ddataset against multiple in-situ datasets is presented in the reference paper (Muñoz-Sabater et al., 2021). Completeness: The dataset covers the entire Geo-harmonizer region as defined by the landmask raster dataset. However, some small islands might be missing if there are no data in the original ERA5 Land dataset. Consistency: ERA5-Land is a reanalysis dataset providing a consistent view of the evolution of land variables over several decades at an enhanced resolution compared to ERA5. ERA5-Land has been produced by replaying the land component of the ECMWF ERA5 climate reanalysis. Reanalysis combines model data with observations from across the world into a globally complete and consistent dataset using the laws of physics. Reanalysis produces data that goes several decades back in time, providing an accurate description of the climate of the past. Positional accuracy: 1 km spatial resolution Temporal accuracy: Daily maps for the years 2020-2020. Thematic accuracy: The raster values represent minimum, mean, and maximum daily surface temperature in degrees Celsius x 10.