The WeatherPod: ECMWF’s Strategy 2021–2030

For the seventh episode of The WeatherPod, a programme produced for the Global Weather Enterprise Forum (GWE Fourm) Florence Rabier has been invited into the studio for this special extended episode ‘Forging a successful European partnership at ECMWF‘ devoted exclusively to ECMWF and the recent publication of its 10-year strategy 2021 to 2030 and the machine-learning roadmap.

https://www.gweforum.org/podcast/episode-7-forging-a-successful-european-partnership-at-ecmwf/#more-1503

ECMWF’s vision is to produce cutting‐edge science and world-leading weather predictions and monitoring of the Earth system in close collaboration with the members of the European Meteorological Infrastructure, for a safe and prosperous society. To achieve this vision, ECMWD has launched its strategy for 2021–2030
Areas of focus include:

• Overcoming both computational and scientific challenges to achieve ensemble forecasts at three- to four-kilometre resolution.
• Extracting maximum value from observations to produce an accurate analysis of the Earth system, consistent across its components.
• Developing next-generation models to produce high-resolution digital twins of the Earth.
• Increasing use of Cloud technologies to enable efficient use of data.
• Integrating global reanalyses and re-forecasts of weather and environmental hazards from 1950 onwards.
• Estimating and monitoring of CO₂ emissions.
• Contributing to the optimisation of the global observing system.
• Moving towards open data.

To address the computational challenges, artificial intelligence will play an important role. In particular, machine learning will become part of the whole numerical weather prediction and climate services workflow. ECMWF’s machine-learning roadmap for the next ten years identifies the challenges and provides potential solutions. Also it defines steps to channel the many distributed science and technology projects that study machine learning for weather and climate predictions into a coordinated effort. More information can be found at  https://www.ecmwf.int/en/elibrary/19877-machine-learning-ecmwf-roadmap-next-10-years.