The European Centre for Medium-Range Weather Forecasts (ECMWF) focuses on enhancing weather forecasting accuracy for weeks, months, seasons, and annual predictions.
ECMWF uses reanalysis and data assimilation techniques to combine short-range forecasts with atmospheric observations from various sources like satellites, ground stations, and weather balloons.
Satellite measurements, such as those from the EarthCARE satellite, assist ECMWF in improving cloud, aerosol, and precipitation modeling.
ECMWF integrates new satellite data with modeling techniques to create more accurate forecasts and improve understanding of cloud physics.
Advanced supercomputers and diverse observational data streams support ECMWF's forecast accuracy improvements.
The ECMWF is involved in creating digital twins for weather-induced and geophysical extremes, as well as climate change adaptation, using enhanced modeling and data assimilation methods.
Digital twins incorporate sea, atmosphere, land, and other elements at a resolution currently unattainable and pave the way for advanced forecasting capabilities.
ECMWF's strategic emphasis on machine learning and AI aims to enhance data-driven methods alongside established physics-based modeling for better forecasting.
Innovation like the Artificial Intelligence Forecasting System (AIFS) and Probability of Fire model show ECMWF's progress in machine learning applications for forecasting.
As a mission-driven organization, ECMWF's work in atmospheric physics, environmental science, and big data contributes to societal and economic benefits through cutting-edge research and weather predictions.