ECMWF Code for Earth is an innovation programme run by the European Centre for Medium-Range Weather Forecasts (ECMWF). Its aim is to drive innovation and open source developments in the Earth sciences community - supporting developments in weather and climate, the two Copernicus services (Copernicus Climate Change Service and Copernicus Atmosphere Monitoring Service) and Destination Earth.

Since 2018, each summer, up to ten developer teams work together with experienced mentors from ECMWF and partner organisations on innovative projects. These projects are related to the broad scope of activities at ECMWF, including data science, weather, climate or other earth sciences, visualisation and more.

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Congratulations to the ten teams that have been selected to be part of Code for Earth 2023:

Browse through the Code for Earth challenges, ask questions and together with the mentors, tailor your proposal. Submit your proposal by 12 April 2023.

The selected Code for Earth 2023 project teams will be announced on 27 Apr 2023.

The four-month long coding period starts on 02 May 2023 and ends on 31 August 2023. During this time, the selected teams will work with their Code for Earth mentors. These are experts in earth sciences like weather, climate and climate change, atmosphere and air quality or in technology areas like AI/ML, cloud computing, applied data science or open source software development.

The Code for Earth day is a celebratory completion of the programme. This year the event will be hosted at the ECMWF's data centre in Bologna, Italy. Teams will be invited to present their project results.

Successfully completed projects will receive a €5,000 stipend.

• Code for Earth Frequently Asked Questions
• Code for Earth Terms & Conditions
• Follow Code for Earth on Twitter, LinkedIn and YouTube
• Read a summary of ECMWF Summer of Weather Code 2022 on the ECMWF Science Blog: ECMWF Summer of Weather Code 2022
• ECMWF Newsletter: Summer of Weather Code becomes Code for Earth
• Learn the most recent developments concerning machine learning in weather and climate from the Massive Open Online Course (MOOC) on Machine Learning in Weather and Climate