Verification of SpacePy's radial diffusion radiation belt model

Welling, D. T.; Koller, J.; Camporeale, Enrico

doi:10.5194/gmd-5-277-2012

Cited by 13 publications

(17 citation statements)

References 39 publications

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“…Application of this tool in the radiation belt has been demonstrated by Koller et al (2007) to understand the acceleration mechanisms missing from the 1-D radiation belt model but being accounted for by the assimilation technique. (A version of EnKF and the radial diffusion radiation model are available with SpacePy (Morley et al, 2010;Welling et al, 2012).) Schiller et al (2012) conducted a parametric study using the EnKF innovation vector to identify the source location and magnitude in the outer electron radiation belt.…”

Section: Y Yu Et Al: Radiation Belt Data Assimilationmentioning

confidence: 99%

Radiation belt data assimilation of a moderate storm event using a magnetic field configuration from the physics-based RAM-SCB model

Koller

Jordanova

et al. 2014

Ann. Geophys.

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Abstract. Data assimilation using Kalman filters provides an effective way of understanding both spatial and temporal variations in the outer electron radiation belt. Data assimilation is the combination of in situ observations and physical models, using appropriate error statistics to approximate the uncertainties in both the data and the model. The global magnetic field configuration is one essential element in determining the adiabatic invariants for the phase space density (PSD) data used for the radiation belt data assimilation. The lack of a suitable global magnetic field model with high accuracy is still a long-lasting problem. This paper employs a physics-based magnetic field configuration for the first time in a radiation belt data assimilation study for a moderate storm event on 19 December 2002. The magnetic field used in our study is the magnetically self-consistent inner magnetosphere model RAM-SCB, developed at Los Alamos National Laboratory (LANL). Furthermore, we apply a cubic spline interpolation method in converting the differential flux measurements within the energy spectrum, to obtain a more accurate PSD input for the data assimilation than the commonly used linear interpolation approach. Finally, the assimilation is done using an ensemble Kalman filter (EnKF), with a localized adaptive inflation (LAI) technique to appropriately account for model errors in the assimilation and improve the performance of the Kalman filter. The assimilative results are compared with results from another assimilation experiment using the Tsyganenko 2001S (T01S) magnetic field model, to examine the dependence on a magnetic field model. Results indicate that the data assimilations using different magnetic field models capture similar features in the radiation belt dynamics, including the temporal evolution of the electron PSD during a storm and the location of the PSD peak. The assimilated solution predicts the energy differential flux to a relatively good degree when compared with independent LANL-GEO in situ observations. A closer examination suggests that for the chosen storm event, the assimilation using the RAM-SCB predicts a better flux at most energy levels during storm recovery phase but is slightly worse in the storm main phase than the assimilation using the T01S model.

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Section: Y Yu Et Al: Radiation Belt Data Assimilationmentioning

confidence: 99%

Radiation belt data assimilation of a moderate storm event using a magnetic field configuration from the physics-based RAM-SCB model

Koller

Jordanova

et al. 2014

Ann. Geophys.

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“…The computational grid is of dimension n = 90 for the model domain 1 < L * < 10. The Crank‐Nicolson scheme is an implicit, unconditionally stable numerical method, which converges with any reasonable time step Δ t [ Welling et al , 2011]. The inner boundary condition at L * = 1 is fixed at zero, and the outer boundary condition is modeled with a strong loss term (timescale of a drift period) for L * > L max , the last closed drift shell.…”

Section: Radiation Belt Model and Observationsmentioning

confidence: 99%

Localized adaptive inflation in ensemble data assimilation for a radiation belt model

Godinez

Koller

2012

Space Weather

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In this work a one‐dimensional radial diffusion model for phase space density, together with observational satellite data, is used in an ensemble data assimilation with the purpose of accurately estimating Earth's radiation belt particle distribution. A particular concern in data assimilation for radiation belt models are model deficiencies, which can adversely impact the solution of the assimilation. To adequately address these deficiencies, a localized adaptive covariance inflation technique is implemented in the data assimilation to account for model uncertainty. Numerical results from identical‐twin experiments, where data is generated from the same model, as well as the assimilation of real observational data, are presented. The results show improvement in the predictive skill of the model solution due to the proper inclusion of model errors in the data assimilation.

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“…They attributed these unnatural features to inaccuracies in the calculations of the second invariant K. As a complement to this earlier work, we will show below that such differences are also induced by the calculation of the first adiabatic invariant from a given (E, 0 , L * ) according to the magnetic field model in use. The maximum available L * corresponding to the last closed drift-shell is calculated following the simple empirical estimation of Welling et al (2012) that gives L * max = 6.07 × 10 −5 Dst 2 + 0.0436 Dst + 9.37. In this case the initial and boundary conditions drive the model and are derived from the edges of the plots in Figure 2.…”

Section: Psd: Role Of the Magnetic Field On Psd Peaks 421 Explanatmentioning

confidence: 99%

On the Use of Different Magnetic Field Models for Simulating the Dynamics of the Outer Radiation Belt Electrons During the October 1990 Storm

Loridan

Ripoll

et al. 2019

JGR Space Physics

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During geomagnetic storms, the magnetic field in the outer belt is known to be significantly distorted by the solar wind, such that the outer belt dynamics can be greatly impacted by the magnetic field topology. In this context, we develop a reduced Fokker‐Planck code that includes the effects related to realistic magnetic field models (by using the existing dedicated LANLGeoMag library) through the steps of preprocessing, postprocessing, and, for the first time, during the computation of the reduced Fokker‐Planck diffusion equation itself. We perform the solutions of the reduced Fokker‐Planck equation in the framework of the geomagnetic storm that occurred from 9 October to 15 October 1990. With the use of Combined Release and Radiation Effects Satellite observations, the magnetic field model is shown to strongly affect the way of conciliating theory with observations (processing steps). More specifically, we explain analytically and numerically why the use of a dipole field can lead to misleading interpretations on the local enhancements (attributed to local acceleration) displayed by the electron distribution function, resulting in inaccurate simulations results at large L‐shells. The consideration of a realistic field does not produce any artificial peaks. With such corrected data sets, a great part of the dynamics can be described by radial transport and is thus better reproduced by the simulations. This crucial importance of the field geometry is further emphasized with the calculation of unidirectional, omnidirectional, and integral electron fluxes, and their accuracy is quantified thanks to dedicated metrics.

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Verification of SpacePy's radial diffusion radiation belt model

Cited by 13 publications

References 39 publications

Radiation belt data assimilation of a moderate storm event using a magnetic field configuration from the physics-based RAM-SCB model

Radiation belt data assimilation of a moderate storm event using a magnetic field configuration from the physics-based RAM-SCB model

Localized adaptive inflation in ensemble data assimilation for a radiation belt model

On the Use of Different Magnetic Field Models for Simulating the Dynamics of the Outer Radiation Belt Electrons During the October 1990 Storm

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