Meteorologist, former weather forecaster, now data analyst passionate about data visualisation and jupyter notebooks.
Reminder - The date and time of this sessions are placeholder due to the limitation of the conference software.
All Poster will be presented during the Poster Session from 6:30 to 8:00 on Thus 11th,
Citizens in every inhabited place on the planet are increasingly experiencing dramatic consequences of a changing climate. Also within Europe the adaptation gap between the multi-hazard climate risk and the risk management capability is growing. The EU project CLIMAAX (CLIMAte risk and vulnerability Assessment framework and toolboX) addresses this by providing financial, analytical and practical support to climate risk assessment community, allowing an improvement of regional climate and emergency risk management plans. The CLIMAAX Operational Toolbox will consist of existing and improved tools for data access, manipulation, processing, modelling and dissemination. The four main elements of the toolbox will be:
1) A wiki to serve as user guide with full description of the tools involved;
2) Jupyter notebook templates and examples of the workflows of case studies;
3) Access points to the models, data needed and tools for data manipulation and visualisation for the Climate Risk Assessment;
4) Access to computational and storage resources.
Jupyter ecosystem will be the heart of the CLIMAAX toolbox with Jupyter lab enabled for users and Jupyter books for wiki, documentation and templates.
The project will start in January 2023 and in this poster we will share first design and implementation of the toolbox.
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.