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- ecmwf-opendata ecmwf-opendata is a package to simplify the download of ECMWF open data. It implements a request-based interface to the dataset using ECMWF's MARS language to select meteorological fields, similar to the existing ecmwf-api-client Python package.
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These products are a subset of the full Catalogue of ECMWF Real-time Products and are based on the medium-range (high-resolution and ensemble) and seasonal forecast models. The data are released 1 hour after the real-time dissemination schedule.
- Use of Data Accessed Via This Service
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- ECMWF moves towards a policy
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- Use of Data Accessed Via This Service
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- Overview
- Installation
- Usage
- Options
- Methods
- Request keywords
- Examples
ecmwf-opendata is a package to simplify the download of ECMWF open data. It implements a request-based interface to the dataset using ECMWF's MARS language to select meteorological fields, similar to the existing ecmwf-api-client Python package.
A collection of Jupyter Notebooks that make use of that package is available here.
The ecmwf-opendata Python package can be installed from PyPI with:
$ pip install ecmwf-opendata
The example below will download the latest available 10-day forecast for the mean sea level pressure (msl) into a local file called data.grib2:
The constructor of the client object takes the following options:
where:
•source is either the name of server to contact or a fully qualified URL. Possible values are ecmwf to access ECMWF's servers, or azure to access data hosted on Microsoft's Azure. Default is ecmwf.
•beta is a boolean that indicates whether to access the beta or the production version of the dataset. Current only beta=True is supported.
•preserve_request_order. If this flag is set to True, the library will attempt to write the retrieved data into the target file in the order specified by the request. For example, if the request specifies param=[2t,msl] the library will ensure that the field 2t is first in the target file, while with param=[msl,2t], the field msl will be first. This also works across different keywords: ...,levelist=[500,100],param=[z,t],... will produce different output to ...,param=[z,t],levelist=[500,100],... If the flag is set to False, the library will sort the request to minimise the number of HTTP requests made to the server, leading to faster download speeds. Default is False.
•infer_stream_keyword. The stream keyword represents the ECMWF forecasting system that creates the data. Setting it properly requires knowledge of how ECMWF runs its operations. If this boolean is set to True, the library will try to infer the correct value for the stream keyword based on the rest of the request. Default is True.
The Client.retrieve() method takes request as input and will retrieve the corresponding data from the server and write them in the user's target file.
A request is a list of keyword/value pairs used to select the desired data. It is possible to specify a list of values for a given keyword.
The request can either be specified as a dictionary:
or directly as arguments to the retrieve() method:
The date and time keyword are used to select the date and time of the forecast run (see Date and time below). If date or both date and time are not specified, the library will query the server for the most recent matching data. The date and time of the downloaded forecast is returned by the retrieve() method.
may print 2022-01-23 00:00:00.
The supported keywords are:
•type: the type of data (compulsory, defaults to fc).
•stream: the forecast system (optional if unambiguous, compulsory otherwise). See the infer_stream_keyword above.
•date: the date at which the forecast starts.
•time: the time at which the forecast starts.
•step: the forecast time step in hours, or fcmonth, the time step in months for the seasonal forecast (compulsory, default to 0 and 1, respectively).
Download a single surface parameter at a single forecast step from ECMWF's 00UTC HRES forecast Download the tropical cyclone tracks from ECMWF's 00UTC HRES forecast
•The downloaded data are encoded in BUFR edition 4 •For the HRES Tropical Cyclone tracks at time=06 and time=18 use:
Download a single surface parameter at a single forecast step for all ensemble members from ECMWF's 12UTC 00UTC ENS forecast
•To download a single ensemble member, use the number keyword: number=1. •All of the odd numbered ensemble members use number=[num for num in range(1,51,2)]. •To download the control member, use type="cf".
Download the Tropical Cyclone tracks from ECMWF's 00UTC ENS forecast
The Tropical Cyclone tracks are identified by the keyword type="tf". •The downloaded data are encoded in BUFR edition 4 •For the ENS Tropical Cyclone tracks at time=06 and time=18 replace step=240 with step=144.
Apr 30, 2024 · ecmwf-opendata is a package to simplify the download of ECMWF open data. It implements a request-based interface to the dataset using ECMWF's MARS language to select meteorological fields, similar to the existing ecmwf-api-client Python package.
Jun 13, 2024 · Find out how to access ECMWF real-time open data. ECMWF has recently deployed an updated version of the IFS Open Data at 0.25 degrees, with additional parameters to enable limited area model and machine-learning initialisation. The existing 0.4 degree data will be deprecated in 3 months time.
Oct 7, 2020 · The EU Copernicus Earth observation programme, several elements of which are implemented by ECMWF, has operated a policy of free, open data since its inception. With many thousands of users, the programme offers a host of examples of the benefits that open data can bring.
As part of its strategy and ongoing commitment to open science, ECMWF has progressively moved towards an open data policy since 2018. The aim is to achieve a fully open data status by the end of 2026, and the final goal is to provide the complete ECMWF Real-time Catalogue under a CC-BY-4.0 licence with no Information Cost.
Description. These products are a subset of the ECMWF real-time forecast data and are made available to the public free of charge. They are based on the medium-range (high-resolution and ensemble) and seasonal forecast models. Products are available at 0.4 degrees resolution in GRIB2 format unless stated otherwise.
