Development of a data assimilation method using Ensamble Kalman Filter to improve initial conditions for numerical models

Fernando Arellano Guerrero*
Centro de Ciencias de la Atmósfera de la UNAM

It's evident that the initial conditions for the numerical weather prediction models is very important for the improvement of the forecast of meteorological events. In the case of tropical cyclones, the initial conditions have an important impact in the estimation of their trajectory and intensity. We are interested in the develop a new methodology for the improvement of the initial conditions for the Weather Research Model (WRF). The Observation System Simulation Experiments (OSSE) will be used to forecast the event of a tropical cyclone. As a reference, the data assimilation system GSI will be used to compare the simulations performed with our methodology.

*Preference: Poster