HR: 1330h
AN: SM43B-04    [Abstracts]
TI: Inner-Magnetospheric Data Assimilation With an Ensemble Kalman Filter
AU: * Naehr, S M
EM: naehr@rice.edu
AF: Rice University, MS 108, 6100 Main St., Houston, TX 77005 United States
AU: Toffoletto, F
EM: toffo@rice.edu
AF: Rice University, MS 108, 6100 Main St., Houston, TX 77005 United States
AB: The Ensemble Kalman Filter is a data assimilation technique that incorporates observational data into a physical model to estimate the state of a system, using Monte Carlo methods to estimate the model error statistics. The application of this technique to the inner-magnetospheric kilovolt plasma environment is explored in a series of identical twin experiments, using the Magnetospheric Specification Model (MSM) to represent the inner-magnetospheric state. Simulated IMAGE/HENA data is incorporated into the MSM, using a forward modeling algorithm to relate the observed ENA intensity to MSM variables. Results from experiments with different ensemble sizes, sampling strategies, and analysis schemes are presented, and the sensitivity of the assimilation to various sources of error is investigated.
DE: 2700 MAGNETOSPHERIC PHYSICS
DE: 2722 Forecasting
DE: 2730 Magnetosphere--inner
DE: 2753 Numerical modeling
SC: SPA-Magnetospheric Physics [SM]
MN: 2005 Joint Assembly