The Ecmwf Software Strategy These software packages have been developed over many years, sometimes decades, and continue to provide a reliable service to ecmwf operations. as part of our constant drive for efficiency and improvement, ecmwf is reviewing its strategy and roadmap for these software packages. The european centre for medium range weather forecasts (ecmwf) has published a new ‘software strategy’, outlining its plans for the development of software outside the weather prediction process until 2027.
The Ecmwf Software Strategy The european centre for medium range weather forecasts (ecmwf) has released their software strategy out to 2027. from the highlights reel: following a decade of adopting an open source policy for part of our software stack, we are now further engaging with the community. 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. Ecmwf has embarked on a new strategy aiming 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 infras tructure, for a safe and prosperous society. Our software supports the primary purpose of ecmwf to continuously enhance our capabilities for medium range weather forecasting and the scalable provision of forecast products to our member states. scroll down to explore some of our guiding principles.
The Ecmwf Software Strategy Ecmwf has embarked on a new strategy aiming 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 infras tructure, for a safe and prosperous society. Our software supports the primary purpose of ecmwf to continuously enhance our capabilities for medium range weather forecasting and the scalable provision of forecast products to our member states. scroll down to explore some of our guiding principles. Discover the main ideas behind our new software strategy, outlining our plans for the open development of software outside the weather prediction process until 2027 ️ lnkd.in enfew5xt. Making the digital twins accessible and ai ready mathilde leuridan is a research software engineer at ecmwf. she works on parts of the digital twin engine, a central component of destine. the engine brings together the software infrastructure necessary for extreme scale simulations, data handling, data access and machine learning. Anemoi is the software engine behind the earth system modelling in the digital twins of destination earth, as well as ecmwf's data driven "aifs" global weather model. The destine platform team will attend the 5th ecmwf esa machine learning workshop, taking place in bologna, italy from 13 to 17 april 2026.
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