JupyterCon 2023

Using Jupyter ecosystem for more accessible open weather forecast data
05-12, 12:00–12:30 (Europe/Paris), Gaston Berger

The European Centre for Medium-Range Weather Forecasts (ECMWF) is an independent intergovernmental organisation which is producing and disseminating numerical weather and environmental predictions to national meteorological services and other users including commercial customers. As of recently, ECMWF has adopted an open data policy which is being implemented in phases from 2020 to 2026. The first phase included opening hundreds of web forecast charts and making archived data available under a Creative Commons (CC BY 4.0) open licence in 2020, followed by the production of open subset of real time medium range forecast in early 2022. The next steps in 2023 include releasing “Atmospheric Composition Support” dataset and seasonal forecast parameters currently available with 4 and 6 days delay through Copernicus CAMS and C3S programmes, without any delay.
This phased move towards free and open data represents a significant step towards more reproducible open science. However this can not be achieved by only opening the real time data. To realise the full potential of open data, it needs to be easily accessible and with the appropriate supporting information to allow users to derive information and integrate the data into their own research work or application workflows.
To facilitate this, the additional development work is being done. This work includes the design of an API to easily download the forecast data, and the development of open source Python libraries to process and visualise it. To help users understand how to retrieve and process ECMWF data using these libraries, a set of Jupyter notebooks is being created, each of them reproducing one open weather forecast chart from the downloading the data to the visualisation.
This talk will focus on Jupyter notebooks development, from the idea to realisation, through challenges and attempts for automation.

Meteorologist, former weather forecaster, now data analyst passionate about data visualisation and jupyter notebooks.

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