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Note
titleERA-Interim production stopped on 31st August 2019

For ERA-Interim (1st January 1979 to 31st August 2019) access through the ECMWF Web API stopped on 01 June 2023

Its successor ERA5 is available from the Climate Data Store (CDS) (What are the changes from ERA-Interim to ERA5?) and users are strongly advised to migrate to ERA5 (How to download ERA5).

For those users who still need access to ERA-Interim after 01 June 2023, they can do so as per instructions below.


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Easy Heading Macro

Since October 25th 2017,  the time period you can select on the ECMWF Web User Interface for ERA-Interim is limited, namely for daily data to one month, and for monthly data to one year. The purpose of the ECMWF web user  interface is only to provide small sample datasets for evaluation. Data over longer time periods should not be downloaded through the web interface, but using the ECMWF WebAPI with Python scripts as described below.

Please note also that the web user interface does not list all available data. For listings of all available data please see the ECMWF archive catalogue (which allows you to browse through the entire ERA-Interim archive) and the respective ERA-Interim dataset documentation.

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Learn about ERA-Interim data

  1. Read What is ERA-Interim.
  2. Browse the ERA-Interim catalogue and make sure the data you are interested in is available in ERA-Interim. A demonstration (for ERA5 but the same principle applies for ERA-Interim) is available as part of the video tutorial below:

    Multimedia
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    Full Transcript (pdf)

  3. Read the ERA-Interim data documentation and take note of the parameters (fields) you want to use, and of the corresponding values for data type, stream, level type (surface, pressure levels, model levels, etc) base time and forecast steps.

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License agreement

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Read the Conditions of Use and accept the agreement

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3. Technical prerequisites

You need:

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here

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.

Browse and retrieve ERA-Interim data via the CDS API

Until further notice, access to ERA-Interim has now been enabled via the API of the Climate Data Store (CDS). The mechanism is very similar to that of ERA5-complete.

Data can only be retrieved in a programmatic way, via running a script. There is no possibility for interactive downloads.

Instructions can be found here.



Info

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). 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.

4. Set up your computer

This is to configure your computer to programmatically retrieve data from ECMWF. You only need to do this once, and only if you have never retrieved ECMWF data using Python before. For more information refer to Access ECMWF Public Datasets of ECMWF WebAPI.

1. Install the ECMWF WebAPI client library by running:

 

Code Block
languagebash
sudo pip install https://software.ecmwf.int/wiki/download/attachments/56664858/ecmwf-api-client-python.tgz

2. Get and install an ECMWF API key:

  1. Go to https://apps.ecmwf.int/auth/login/ to verify you are logged in. If you are not, log in with your ECMWF account details (as registered in step 2).

  2. Go to https://api.ecmwf.int/v1/key/ . You will see something like below:

 

Code Block
languagepy
{
    "url"   : "https://api.ecmwf.int/v1",
    "key"   : "XXXXXXXXXXXXXXXXXXXXXX",
    "email" : "john.smith@example.com"
}

3. Copy the bit with the curly brackets as shown above into a text file and save the file as $HOME/.ecmwfapirc (on Unix/Linux) or %USERPROFILE%\.ecmwfapirc (on Windows)

5. Run a test

This is to verify that your computer is set up correctly.

1. Copy the following Python script to a text file and save it, for example as 'my_ERA-Interim_test_script.py'

Code Block
languagepy
#!/usr/bin/env python
from ecmwfapi import ECMWFDataServer

server = ECMWFDataServer()
server.retrieve({
    "class": "ei",
    "dataset": "interim",
    "expver": "1",
    "stream": "oper",
    "type": "fc",
    "levtype": "sfc",
    "param": "167.128",
    "date": "2017-08-01/to/2017-08-31",
    "time": "00:00:00",
    "step": "3",
    "grid": "0.75/0.75",
    "target": "my_ERA5_test_file.grb",
 })

2. Run the script. On most computers you would do this by opening a command prompt and typing

Code Block
languagepy
python my_ERA-Interim_test_script.py

The test request will download data from ECMWF and save as file 'my_ERA-Interim_test_file.grb' in the directory you issued the command from.

Note that the data retrieval is not designed to be instant. The test request above usually takes a few minutes to complete, but depending on demand can take longer.

3. With your favourite GRIB file reader verify that you can read the file. If you are not familiar with GRIB please see What are GRIB files and How to read or decode a GRIB file

If you get an error message or the output is not as specified in to the Python script, most likely your computer setup is wrong, or you did not accept the ERA5 license, so please go back to the previous steps.

6. Create your data retrieval script

...

Change the "target": "CHANGEME", to the desired output path and file name, e.g. "data1.nc" or "./data/data1.grib". The default path is the current working directory.

Limitations:

  • You can have a maximum of three active requests at a time.
  • The maximum data volume is 20GB per request.
  • The maximum number of fields to be retrieved is 600,000 fields per request.

Note that the data retrieval is not designed to be instant. A larger request can take hours and even days to complete.

To retrieve 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. In most cases this means retrieving all the data you need for one month, then for the next month, and so on. See Retrieval efficiency pages.

7. Run your data retrieval script

On most computers you would do this by opening a command prompt and typing

Code Block
languagepy
python my_ERA-Interim_script_v1.py

This will retrieve the data as specified and download it as a single file to your computer into the current directory (or whichever "target" directory you specified).

For long running processes you can check the progress of your request in your job list.

8. Check results

Check that the data you downloaded meets your requirements.

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