The two‐way relationship between ionospheric outflow and the ring current

Welling, D. T.; Jordanova, V. K.; Glocer, A.; Tóth, G.; Liemohn, Michael W.; Weimer, D. R.

doi:10.1002/2015ja021231

Cited by 37 publications

(31 citation statements)

References 118 publications

(168 reference statements)

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“…The stark difference in S Y M ‐ H predictions with and without the RCM component highlights the importance of the inner magnetosphere model in producing realistic ring current dynamics. The inner magnetosphere model can also, through coupling with the MHD solver, affect midtail currents to which S Y M ‐ H is sensitive, as evidenced by increased tail stretching in MHD models when coupling to an inner magnetosphere model is used (e.g., Pembroke et al, ; Welling et al, ). That SWMF predicts D s t (similar to S Y M ‐ H ) better when a ring current model is used has been shown previously in Rastätter et al ().…”

Section: Resultsmentioning

confidence: 99%

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

et al. 2017

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We simulated the entire month of January 2005 using the Space Weather Modeling Framework (SWMF) with observed solar wind data as input. We conducted this simulation with and without an inner magnetosphere model and tested two different grid resolutions. We evaluated the model's accuracy in predicting Kp, SYM‐H, AL, and cross‐polar cap potential (CPCP). We find that the model does an excellent job of predicting the SYM‐H index, with a root‐mean‐square error (RMSE) of 17–18 nT. Kp is predicted well during storm time conditions but overpredicted during quiet times by a margin of 1 to 1.7 Kp units. AL is predicted reasonably well on average, with an RMSE of 230–270 nT. However, the model reaches the largest negative AL values significantly less often than the observations. The model tended to overpredict CPCP, with RMSE values on the order of 46–48 kV. We found the results to be insensitive to grid resolution, with the exception of the rate of occurrence for strongly negative AL values. The use of the inner magnetosphere component, however, affected results significantly, with all quantities except CPCP improved notably when the inner magnetosphere model was on.

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Section: Resultsmentioning

confidence: 99%

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

et al. 2017

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“…An interesting consideration is the impact of the SWMF's inclusion of a ring current model may be having on these results. Inclusion of such a model has been show to strengthen the ring current and region‐2 Birkeland currents [ De Zeeuw et al , ; Welling et al , ]. It would be expected that these improvements would affect the midlatitude predictions most strongly but still play a role in higher latitude results.…”

Section: Discussionmentioning

confidence: 99%

Exploring predictive performance: A reanalysis of the geospace model transition challenge

et al. 2017

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The Pulkkinen et al. (2013) study evaluated the ability of five different geospace models to predict surface dB/dt as a function of upstream solar drivers. This was an important step in the assessment of research models for predicting and ultimately preventing the damaging effects of geomagnetically induced currents. Many questions remain concerning the capabilities of these models. This study presents a reanalysis of the Pulkkinen et al. (2013) results in an attempt to better understand the models' performance. The range of validity of the models is determined by examining the conditions corresponding to the empirical input data. It is found that the empirical conductance models on which global magnetohydrodynamic models rely are frequently used outside the limits of their input data. The prediction error for the models is sorted as a function of solar driving and geomagnetic activity. It is found that all models show a bias toward underprediction, especially during active times. These results have implications for future research aimed at improving operational forecast models.

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“…The ionospheric potential solver RIM is designated as a two-dimensional shell at the ionospheric height (∼110 km). The coupling between these codes, except for the dashed line between RAM-SCB and RIM, has been established in previous studies and meanwhile been validated through thorough comparisons with a variety of observations, including the global energy content Dst index, magnetic fields, field-aligned currents, and particle flux either at the boundary of codes or along certain satellites trajectories [Zaharia et al, 2010;Yu et al, 2014aYu et al, , 2015Welling et al, 2011Welling et al, , 2015. These data-model comparisons for this coupled modeling framework demonstrated its capability to reproduce many key features of the magnetosphere-ionosphere system.…”

Section: Methodsmentioning

confidence: 96%

“…The magnetic field required at the outer boundary of RAM‐SCB is provided by the empirical Tsyganenko model [ Tsyganenko , ], parameterized by Kp index. Since the magnetic field solver within RAM‐SCB represents the field with a set of Euler potential shells [ Zaharia et al , , ], it is difficult to construct the shells at the outer boundary with fields from other coupled code [ Welling et al , ].…”

Section: Methodsmentioning

confidence: 99%

A new ionospheric electron precipitation module coupled with RAM‐SCB within the geospace general circulation model

Jordanova

Ridley

et al. 2016

JGR Space Physics

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Electron precipitation down to the atmosphere due to wave‐particle scattering in the magnetosphere contributes significantly to the auroral ionospheric conductivity. In order to obtain the auroral conductivity in global MHD models that are incapable of capturing kinetic physics in the magnetosphere, MHD parameters are often used to estimate electron precipitation flux for the conductivity calculation. Such an MHD approach, however, lacks self‐consistency in representing the magnetosphere‐ionosphere coupling processes. In this study we improve the coupling processes in global models with a more physical method. We calculate the physics‐based electron precipitation from the ring current and map it to the ionospheric altitude for solving the ionospheric electrodynamics. In particular, we use the BATS‐R‐US (Block Adaptive Tree Scheme‐Roe type‐Upstream) MHD model coupled with the kinetic ring current model RAM‐SCB (Ring current‐Atmosphere interaction Model with Self‐Consistent Magnetic field (B)) that solves pitch angle‐dependent electron distribution functions, to study the global circulation dynamics during the 25–26 January 2013 storm event. Since the electron precipitation loss is mostly governed by wave‐particle resonant scattering in the magnetosphere, we further investigate two loss methods of specifying electron precipitation loss associated with wave‐particle interactions: (1) using pitch angle diffusion coefficients Dαα(E,α) determined from the quasi‐linear theory, with wave spectral and plasma density obtained from statistical observations (named as “diffusion coefficient method”) and (2) using electron lifetimes τ(E) independent on pitch angles inferred from the above diffusion coefficients (named as “lifetime method”). We found that both loss methods demonstrate similar temporal evolution of the trapped ring current electrons, indicating that the impact of using different kinds of loss rates is small on the trapped electron population. However, for the precipitated electrons, the lifetime method hardly captures any precipitation in the large L shell (i.e., 4 < L < 6.5) region, while the diffusion coefficient method produces much better agreement with NOAA/POES measurements, including the spatial distribution and temporal evolution of electron precipitation in the region from the premidnight through the dawn to the dayside. Further comparisons of the precipitation energy flux to DMSP observations indicates that the new physics‐based precipitation approach using diffusion coefficients for the ring current electron loss can explain the diffuse electron precipitation in the dawn sector, such as the enhanced precipitation flux at auroral latitudes and flux drop near the subauroral latitudes, but the traditional MHD approach largely overestimates the precipitation flux at lower latitudes.

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The two‐way relationship between ionospheric outflow and the ring current

Cited by 37 publications

References 118 publications

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

SWMF Global Magnetosphere Simulations of January 2005: Geomagnetic Indices and Cross‐Polar Cap Potential

Exploring predictive performance: A reanalysis of the geospace model transition challenge

A new ionospheric electron precipitation module coupled with RAM‐SCB within the geospace general circulation model

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