Student Posters Repository

Data assimilation is a statistical method to estimate the state (and its time evolution) of a system by combining observation and numerical model simulation. Numerical weather forecasting technique has greatly improved since its first operational use in 1950s. Along with the exponential growth of computational resources and high-resolution observation data by remote sensing technology, the development of forecast models and data assimilation also play an important role. The effective parallelization of the computation is also crucially important for today's numerical weather forecasting in two different ways; domain decomposition and ensemble forecasting.