1 - Introduction

This article describes how users can access the family of ERA5 datasets via the Climate Data Store (CDS) infrastructure.

ERA5 data can be downloaded through the CDS either via the CDS web interface or programmatically using the CDS API service.

Any data in the CDS catalogue can be accessed in these two ways. And since such data is kept online, access is usually fast. Some parts of the ERA5 dataset are only accessible through the CDS API service. An example is ERA5 model level data that resides in the ECMWF's MARS tape archive. The extraction of such data from tape can lead to significantly longer retrieval times than data that is available online.

Users are now able to check the status of the CDS queue. You will be able to view status of requests submitted by yourself (you need to log into the CDS) and other users: https://cds.climate.copernicus.eu/live/queue

2 - Prerequisites

3 - Downloading online ERA5 family data through the CDS web interface

  1. Go to the C3S climate data store (CDS).
  2. Type  'ERA5' in the search box.
  3. Follow the ERA5 dataset title link of interest (there will be many more hits).
  4. Currently there are eight online ERA5 and two ERA5-Land catalogue entries  


  5. Each of these dataset catalogue entries includes the following tabs:
  6. Go to the Download data tab to make your selection for ERA5 data retrieval. Using this web interface, you can:
  7. Click on the button Submit Form at the bottom right to submit your data request (you must be logged in and have accepted the terms and conditions before submitting your request).

  8. You will now be redirected to the Your requests page.

Once your request has been processed you can download the data by clicking the green Download button. You can check the Live status of your request .

4 - Download ERA5 family data through the CDS API

First: Install CDS API on your machine

  1. This is Python based.
  2. Install the CDS API:
  3. You are recommended to use the latest release of package CDS API.
  4. Run CDS API requests, either interactively or in batch mode.

In a small number of cases, users may experience some issues when requesting data from the CDS API. The most common issues are documented here.

Option A: Download ERA5 family data stored on CDS disks - FAST ACCESS

  1. Build a basic CDS API request.

  2. Refine your CDS API script for ERA5 data listed in CDS for optional post-processing.

To retrieve data efficiently using the CDS API please have a look at the efficiency tips section on CDS documentation.


When requesting ERA5 data from the CDS in NetCDF (web or CDS API), users should not request ERA5 reanalysis atmospheric data, wave data, and ensemble data in one request. This is because the data has different spatial grids, which can cause issues for the current grib to NetCDF converter and produce incorrect results.

Option B: Download ERA5 family data stored on MARS tape archive (no data selection can be made from the CDS download form) - SLOW ACCESS

Although some flavours of the ERA5 family data is not online in the CDS (i.e. not available through the interactive web download form), it is accessible through CDS API. This embraces ERA5-complete and ERA5.1-complete, which provide data in the 'raw' format as they were produced:

The ERA5-Land dataset at the native 9km octahedral grid is an exception and is not available via the CDS API protocol. However, all information is available online at the slightly reduced 0.1°x0.1° regular lat-lon grid (access via Option A, above).

Due to the vast volume of these datasets (currently about 10petabyte) these are not stored on spinning disk, but reside in the ECMWF's MARS tape archive, instead. Access to this data is in general much slower, except for the latest couple of months of ERA5-complete, which are also kept online.


Please be aware that there is an additional queueing system for downloading data from the ECMWF's MARS archive - expect several hours to several days for submitted requests to complete at this time. You can check the Live status of your request


You can discover the ERA5-complete structure (1940-present) and learn how to build a CDS API request by following these steps:

  1. Open the MARS ERA5 catalogue
  2. browse for discovery, and browse your way to the parameter level to build a request.

    • More information on the available streams, product types and levels is available in the ERA5 data documentation.
    • On the parameter level, use the left-mouse button and the shift key to select more than one field in one retrieval.
    • The MARS catalogue only shows data for the final quality controlled data that is made available 2-3 months in arrear. However, data is also available from preliminary timely updates up to 5 days behind real time, using the same retrieval structure.


    To retrieve MARS data efficiently (and get your data quicker!) you should retrieve all the data you need from one tape, then from the next tape, and so on.

    As a rule of thumb everything shown on one page at parameter level in the MARS ERA5 catalogue is grouped together on one tape

    • For analysis fields this is one month of data with respect to one particular level type (e.g. surface).
    • For forecast fields on model levels this is limited to one single day.


  3. Use the " View MARS request " feature - this will help you build your own CDS API Python script to retrieve the data through the CDS API.


    #!/usr/bin/env python
    import cdsapi
    c = cdsapi.Client()
    c.retrieve('reanalysis-era5-complete', { # Requests follow MARS syntax
                                             # Keywords 'expver' and 'class' can be dropped. They are obsolete
                                             # since their values are imposed by 'reanalysis-era5-complete'
        'date'    : '2013-01-01',            # The hyphens can be omitted
        'levelist': '1/10/100/137',          # 1 is top level, 137 the lowest model level in ERA5. Use '/' to separate values.
        'levtype' : 'ml',
        'param'   : '130',                   # Full information at https://apps.ecmwf.int/codes/grib/param-db/
                                             # The native representation for temperature is spherical harmonics
        'stream'  : 'oper',                  # Denotes ERA5. Ensemble members are selected by 'enda'
        'time'    : '00/to/23/by/6',         # You can drop :00:00 and use MARS short-hand notation, instead of '00/06/12/18'
        'type'    : 'an',
    }, 'output')                             # Output file; in this example containing fields in grib format. Adapt as you wish.
    



  4. Tailor your request to
    1. re-grid to the desired regular lat-lon resolution
    2. convert to NetCDF (works for regular grids only, i.e., so you need to use the 'grid' keyword as well)
    3. select sub areas



      #!/usr/bin/env python
      import cdsapi
      c = cdsapi.Client()
      c.retrieve('reanalysis-era5-complete', { # Requests follow MARS syntax
                                               # Keywords 'expver' and 'class' can be dropped. They are obsolete
                                               # since their values are imposed by 'reanalysis-era5-complete'
          'date'    : '2013-01-01',            # The hyphens can be omitted
          'levelist': '1/10/100/137',          # 1 is top level, 137 the lowest model level in ERA5. Use '/' to separate values.
          'levtype' : 'ml',
          'param'   : '130',                   # Full information at https://apps.ecmwf.int/codes/grib/param-db/
                                               # The native representation for temperature is spherical harmonics
          'stream'  : 'oper',                  # Denotes ERA5. Ensemble members are selected by 'enda'
          'time'    : '00/to/23/by/6',         # You can drop :00:00 and use MARS short-hand notation, instead of '00/06/12/18'
          'type'    : 'an',
          'area'    : '80/-50/-25/0',          # North, West, South, East. Default: global
          'grid'    : '1.0/1.0',               # Latitude/longitude. Default: spherical harmonics or reduced Gaussian grid
          'format'  : 'netcdf',                # Output needs to be regular lat-lon, so only works in combination with 'grid'!
      }, 'ERA5-ml-temperature-subarea.nc')     # Output file. Adapt as you wish.
      



For ERA5.1-complete follow the same procedure as for era5-complete explained above, however:

Please read: Technical issue fixed on ERA5.1 CDS API

  1. edit the script to change:


    'reanalysis-era5-complete' to 'reanalysis-era5.1-complete'
    


data is only available for the years 2000-2006 inclusive - so make sure that your request dates are within this time period.



#!/usr/bin/env python
import cdsapi
c = cdsapi.Client()
c.retrieve('reanalysis-era5.1-complete', { # Please note the addition '.1' for ERA5.1!
                                           # Keywords 'expver' and 'class' can be dropped. They are obsolete
                                           # since their values are imposed by 'reanalysis-era5.1-complete'
    'date': '2005-01-01',                  # Valid range:  2000-01-01 to 2006-12-31. Always first of the month for monthly means
    'levelist': '50',                      # Pressure level at 50 hPa
    'levtype': 'pl',
    'param': '130.128',                    # Full information at https://apps.ecmwf.int/codes/grib/param-db/
    'stream': 'moda',                      # Monthly means (of Daily means).
    'type': 'an',
    'grid'    : '1.0/1.0',                 # Latitude/longitude grid resolution.
    'format'  : 'netcdf',                  # Output needs to be regular lat-lon, so only works in combination with 'grid'!
}, 'era5.1-temperature-monthly-mean.nc')





This document has been produced in the context of the Copernicus Climate Change Service (C3S).

The activities leading to these results have been contracted by the European Centre for Medium-Range Weather Forecasts, operator of C3S on behalf of the European Union (Delegation Agreement signed on 11/11/2014 and Contribution Agreement signed on 22/07/2021). All information in this document is provided "as is" and no guarantee or warranty is given that the information is fit for any particular purpose.

The users thereof use the information at their sole risk and liability. For the avoidance of all doubt , the European Commission and the European Centre for Medium - Range Weather Forecasts have no liability in respect of this document, which is merely representing the author's view.

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