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Abstract We investigate the applicability and performance of the plasma physics based WINDMI model to the analysis and identification of substorm onsets. There are several substorm onset criteria that have been developed into event lists, either from auroral observations or from auroral electrojet features. Five of these substorm onset lists are available at the SuperMAG website. We analyze these lists, aggregate them and use the WINDMI model to assess the identified events, emphasizing the loading/unloading mechanism in substorm dynamics. The WINDMI model employs eight differential equations utilizing solar wind data measured at L1 by the ACE satellite as input to generate outputs such as the magnetotail current, the ring current and the field‐aligned currents (FACs). In particular, the WINDMI model current output represents the westward auroral electrojet, which is related to the substorm SML index. We analyze a decade of solar wind and substorm onset data from 1998 to 2007, encompassing 39,863 onsets. Our findings reveal a significant correlation, with WINDMI‐derived enhancements in FAC coinciding with the identified substorm events approximately 32% of the time. This suggests that a substantial proportion of substorms may be attributed to solar wind driving that results in the loading and unloading of energy in the magnetotail. 

Abstract Radiation Belt Storm Probes (RBSP) data show that seed electrons generated by sub‐storm injections play a role in amplifying chorus waves in the magnetosphere. The wave‐particle interaction leads to rapid heating and acceleration of electrons from 10's of keV to 10's of MeV energies. In this work, we examined the changes in the radiation belt during geomagnetic storm events by studying the RBSP REPT, solar wind, AL, SML, and Dst data in conjunction with the WINDMI model of the magnetosphere. The field‐aligned current output from the model is integrated to generate a proxy E index for various energy bands. These E indices track electron energization from 40 KeV to 20 MeV in the radiation belts. The indices are compared to RBSP data and GOES data. Our proxy indices correspond well to the energization data for electron energy bands between 1.8 and 7.7 MeV. Each E index has a unique empirical loss rate term (τ_L), an empirical time delay term (τ_D), and a gain value, that are fit to the observations. These empirical parameters were adjusted to examine the delay and charging rates associated with different energy bands. We observed that theτ_Landτ_Dvalues are clustered for each energy band.τ_Landτ_Dconsistently increase going from 1.8 to 7.7 MeV in electron energy fluxE_eand the dropout interval increases with increasing energy level. The average trend of Δτ_D/ΔE_ewas 4.1 hr/MeV and the average trend of Δτ_L/ΔE_ewas 2.82 hr/MeV. 

Abstract The total energy transfer from the solar wind to the magnetosphere is governed by the reconnection rate at the magnetosphere edges as the Z‐component of interplanetary magnetic field (IMFB_z) turns southward. The geomagnetic storm on 21–22 January 2005 is considered to be anomalous as the SYM‐H index that signifies the strength of ring current, decreases and had a sustained trough value of −101 nT lasting more than 6 hr under northward IMFB_zconditions. In this work, the standard WINDMI model is utilized to estimate the growth and decay of magnetospheric currents by using several solar wind‐magnetosphere coupling functions. However, it is found that the WINDMI model driven by any of these coupling functions is not fully able to explain the decrease of SYM‐H under northward IMFB_z. A dense plasma sheet along with signatures of a highly stretched magnetosphere was observed during this storm. The SYM‐H variations during the entire duration of the storm were only reproduced after modifying the WINDMI model to account for the effects of the dense plasma sheet. The limitations of directly driven models relying purely on the solar wind parameters and not accounting for the state of the magnetosphere are highlighted by this work. 

The SuperMAG magnetic index called the SML index characterizes variations in the Earth's magnetic field due to significant external geomagnetic activities resulting from substorms. This index serves as a crucial parameter for detecting substorm onsets, as utilized by several authors ([1]–[5]). The outputs from the low-order physics-based model WINDMI can also be employed to analyze substorm onsets. In this paper, we evaluate the outputs from the model against the aforementioned techniques to derive criteria for the field-aligned current (FAC) I 1 and its time derivative, both of which are outputs from the model. These criteria hold potential significance in predicting substorm onsets from solar wind data.