Data Assimilation With VERB Code Yuri Shprits1,2, Binbin Ni2, Dmitri Kondrashov1, Marianne Daae1,2, Michael Ghil1,2, Data provided by Tsugunobu Nagai3 , Reiner Friedel4, Yue Chen4, Geoff Reeves4 (1) Institute of Geophysics and Planetary Physics, UCLA (2) Department of Atmospheric and Oceanic Sciences, UCLA

Comparison of the radial diffusion model and observations, starting on 08/18/1990. Shprits et al., 2007

Kalman Filter Assume initial state and data and model errors Make a prediction of the state of the system and error covariance matrix, using model dynamics Compute Kalman gain and innovation vector K is the Kalman matrix and d is the difference between the observations and the forcast Compute updated error covariance matrix Update state vector using innovation vector

Reanalysis of the radiaton belt fluxes [Kondrashov et al, 2006 Shprits et al., 2007]

Reanalysis of PSD for various values of K [Shprits et al., 2007]

Skeptics' Questions Can we reconstruct synthetic observations, and how sensitive our results to the assumed parameters of the code? Can we independently reconstruct the dynamics of the radiation belts using two different satellite data on different orbits? How sensitive our results to the assumed magnetic field model? How sensitive are our results to the assumed boundary conditions?

Peaks in Phase Space Density seen in Akebono and CRRES reanalysis [Ni et al., 2009]

Data Assimilation Various Magnetic Field Models [Ni et al., 2007]

Sensitivity to the Assumed Boundary Condition [Daa et al., 2011]

Long Term Reanalysis [Shprits et al., 2011]

Statistical Analysis of PSD

Sudden and catastrophic dropouts in phase space density Reanalysis results show that drop outs in the radiation belt fluxes occur when the pressure pulse hits Earth magnetosphere. The correlation between pressure pulses and dropouts suggests that the primarily cause of drop outs in the outer portion of the radiation belts are losses to magnetopause or tail, followed by the outward radial diffusion. Solar wind parameters are reconstructed following method of [ Kondrashov, Shprits, and Ghil, 2010]

Sudden and catastrophic dropouts in phase space density The correlation between pressure pulses and dropouts suggests that the primarily cause of drop outs in the outer portion of the radiation belts are losses to magnetopause or tail, followed by the outward radial diffusion. 70% associated with a clear pressure pulse 22% associated with a smaller increaseiin SWDP or gradual increase in SWDP 8% relatively steady

Recent Publications Kondrashov, D. , Y. Shprits, M. Ghil, and R. Thorne (2007), A Kalman filter technique to estimate relativistic electron lifetimes in the outer radiation belt, J. Geophys. Res., 112, A10227, doi:10.1029/2007JA012583. Shprits, Y. , D. Kondrashov, Y. Chen, R. Thorne, M. Ghil, R. Friedel, and G. Reeves (2007), Reanalysis of relativistic radiation belt electron fluxes using CRRES satellite data, a radial diffusion model, and a Kalman filter, J. Geophys. Res., 112, A12216, doi:10.1029/2007JA012579. Ni, B. , Y. Shprits, R. Thorne, R. Friedel, and T. Nagai (2009), Reanalysis of relativistic radiation belt electron phase space density using multisatellite observations: Sensitivity to empirical magnetic field models, J. Geophys. Res., 114, A12208, doi:10.1029/2009JA014438. Ni, B. , Y. Shprits, T. Nagai, R. Thorne, Y. Chen, D. Kondrashov, and H.-J. Kim (2009), Reanalyses of the radiation belt electron phase space density using nearly equatorial CRRES and polar-orbiting Akebono satellite observations, J. Geophys. Res., 114, A05208, doi:10.1029/2008JA013933 Ni, B., Y. Shprits, M. Hartinger, V. Angelopoulos, X. Gu, and D. Larson (2011), Analysis of radiation belt energetic electron phase space density using THEMIS SST measurements: Cross-satellite calibration and a case study , J. Geophys. Res. , 116 , A03208, doi:10.1029/2010JA016104. Daa et al, (2011) Submitted to Advanced in Space Weather Shprits et al, (2011) Submitted to JGR.

Summary We have validated and verified reanalysis results by using synthetic data, comparing reanalysis produced with different satellites. We studied sensitivity of reanalysis to the assumed magnetic field mode, boundary conditions, and parameters of the code. Reanalysis using four spacecraft measurements can help understand dynamical evolution of the radiation belts. In particular using reanalysis we showed that the peak in PSD is correlated with the dynamics of the plasmasphere. We also showed that majority of the dropouts of the relativistic electrons occur simultaneously with increases in the solar wind dynamic pressure, indicating that loss to the magnetopause and the outward radial diffusion may be responsible for this flux dropouts. 3D data assimilation will allow to use a vast array of data. It will allow to globally assimilate data from satellites on different orbits, and will allow to utilize measurements of pitch-angle distributions and energy spectra.