Electron radiation belt data assimilation with an ensemble Kalman filter relying on the Salammbô code

Bourdarie, S.; Maget, Vincent

doi:10.5194/angeo-30-929-2012

Cited by 44 publications

(62 citation statements)

References 76 publications

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“…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. Recently, Bourdarie and Maget (2012) and Shprits et al (2013) reported data assimilation in 3-D radiation belt models.…”

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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“…However they are much more complex and difficult to manipulate confidently. Another advantage of the SVD based unfolding, is that it is complementary to filtered data assimilation in which SVD decomposition is also used to extract the best information from both data model [15].…”

Section: Discussionmentioning

confidence: 99%

“…We consequently describe in this section the adjustments of the driving parameters to optimize the unfolding. We based our settings strategy on a theoretical verification of the unfolding process, somehow comparable to twin experiments often used to validate the expected behavior of a data assimilation algorithm [15].…”

Section: Practical Implementation Of the Svd And Regularization Mmentioning

confidence: 99%

Unfolding JASON-2/ICARE-NG High-Energy Particles Measurements Using a Singular Value Decomposition Approach

Maget

Bourdarie

Lázaro

et al. 2014

IEEE Trans. Nucl. Sci.

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This paper presents an enhanced approach to extract as much as possible information from raw measurements of a given solid-state detector. Here we focus on the benefits of a singular value decomposition approach applied to the special case of the CNES-JASON 2 mission. It allows us to extract more information from the sensor than a more traditional technique. Refined differential fluxes instead of only coarse integral and differential ones are now obtained and to get an improved resolution for both protons (40-500 MeV) and electrons (825 keV to 8 MeV). Finally, thanks to the combination of all the information embedded into the different response functions of the ICARE-NG instrument, we are now able to: 1) estimate the uncertainty of our measurements, and 2) automatically filter contamination from both proton and electron in restored fluxes channels.

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“…The end goal of this in depth data analysis is to constrain the Salammbô electron data assimilation tool with pure electron data [6]. This is very important to ensure good performance of the analysis step of any data assimilation tool because one major hypothesis being the data are not biased.…”

Section: Discussionmentioning

confidence: 99%

In-depth analysis of SREM count rate measurements for future use in EnKF Salammbô data assimilation tool

Bourdarie

Lázaro

Nieminem

et al. 2013

2013 14th European Conference on Radiation and Its Effects on Components and Systems (RADECS)

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Electron radiation belt data assimilation with an ensemble Kalman filter relying on the Salammbô code

Cited by 44 publications

References 76 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

Unfolding JASON-2/ICARE-NG High-Energy Particles Measurements Using a Singular Value Decomposition Approach

In-depth analysis of SREM count rate measurements for future use in EnKF Salammbô data assimilation tool

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Electron radiation belt data assimilation with an ensemble Kalman filter relying on the Salammbô code

Cited by 44 publications

References 76 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

Unfolding JASON-2/ICARE-NG High-Energy Particles Measurements Using a Singular Value Decomposition Approach

In-depth analysis of SREM count rate measurements for future use in EnKF Salammb&#x00F4; data assimilation tool

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In-depth analysis of SREM count rate measurements for future use in EnKF Salammbô data assimilation tool