Data assimilation is a technology that merges data from observations and models. It is a central tool in numerical weather prediction. The new method may speed up several applications of atmospheric sciences in future.
Viite: Antti Solonen, Tiangang Cui, Janne Hakkarainen, and Youssef Marzouk: On dimension reduction in Gaussian filters, Inverse Problems, Volume 32, Number 4, 2016.
The Finnish Meteorological Institute is a leading expert in meteorology, air quality, climate change, earth observation, marine and arctic research areas. FMI is in a unique position to study various themes of climate change in the Northern context.
High-quality observational data and research is utilized to develop services to benefit our everyday life. Visible examples are improvement of weather forecasts, development of new expert and warning services as well as applications of the newest research results.