Speaker
Description
Data assimilation is a term used to describe various algorithms that help reconstruct the global state of evolution of the system from observations contaminated by noise. The most commo technique for the sequential data assimilation is called Kalman fileter ( Kalman 1960) produces sequential updates for the model forecasts using data. In this process the predictions of the physics based model are blended with observations from different sources and with different observational errors. This technique allows us to reconstract the previous state of the system, current state of the system, and also make very accurate predictions into the future as we can reconstruct the initial condition for the prediction. In this study we present reconstruction of the 4 years of radiation belts using the Versatile Electron Radiation Belt (VERB) code and Kalman Filtering. We also show a recent examples of the reanalysis of ring current electrons and discuss future applications this technique.
