IGPP Seminar Series

Data assimilation research project at the Institute of Statistical Mathematics (ISM) and an application of the ensemble Kalman filter to an atmosphere-ocean coupled model

by Dr. Genta Ueno
The Institute of Statistical Mathematics

Abstract

Data assimilation is a novel methodology for estimating variables in complex systems such as geophysical phenomena by improving the initial and/or the boundary conditions and parameters of simulation models. Our group is studying the methodology and application of the sequential data assimilation, mainly the ensemble Kalman filter (EnKF) and the particle filter (PF). Our applied subjects are ENSO, tsumanis, ring currents and biological pathways. After a brief introduction of our group, we show an application of the EnKF and smoother to an intermediate atmosphere-ocean coupled model.
Tuesday, 27 February 2007
3853 Slichter Hall
Refreshments at 3:45 PM
Lecture at 4:00 PM