A computationally optimized low‐dimensional nonlinear dynamical model of the magnetosphere‐ionosphere system called WINDMI is used to analyze two large geomagnetic storm events, 3–7 October 2000 and 15–24 April 2002. These two important storms share common features such as the passage of magnetic clouds, shock events from coronal mass ejections, triggered substorms, and intervals of sawtooth oscillations. The sawtooth oscillations resemble periodic substorms but occur in association with strong or building ring current populations and have injection regions that are unusually close to the Earth and unusually wide in magnetic local times (Henderson et al., 2006; Borovsky et al., 2007). The April 2002 event includes one of the best examples of sawtooth events ever observed. On 18 April 2002, sawtooth oscillations were clearly visible when solar wind conditions (IMF Bz, density, pressure) were relatively steady with a slowly varying Dst. In this study, WINDMI is used to model the 3–7 October 2000 and 15–24 April 2002 geomagnetic activity. WINDMI results are evaluated focusing on the sawtooth intervals and the overall prediction of the westward auroral electrojet (AL) index and Dst index. The input to the model is the dynamo driving voltage derived from the fluctuating solar wind plasma and the interplanetary magnetic field measured by the ACE satellite. The output of the model is a field‐aligned current proportional to the AL index and the energy stored in the ring current which is proportional to the Dst index. The model parameters are optimized using a genetic algorithm (GA) to obtain solutions that simultaneously have least mean square fit to the AL and Dst indices and also exhibit substorms of period 2–4 hours. The GA optimization results show that the model is able to predict the Dst index reliably and captures the timing and periodicity of the sawtooth signatures in the AL index reasonably well for both storm events.

[1] We use the WINDMI model of the nightside magnetosphere to investigate the contributions of ring current, magnetotail current, and magnetopause current on the observed two-phase decay of the Dst index. For the analysis, several geomagnetic events in the period 2000-2007 were identified, during which the interplanetary magnetic field (IMF B z ) turns northward during the early recovery phase of the storm. The Dst recovery rate for these events were first estimated for either of two possible periods: by assuming an initial fast decay phase or by assuming an overall decay for the entire duration of storm. The recovery rates were estimated by matching Dst and Dst* data against WINDMI model predictions. We consistently found an increase in the Dst recovery times when a shorter initial decay phase was chosen as compared to an overall decay phase, thus, confirming the observations of two-phase decay and indicating the possibility of contributions from faster initial decay mechanisms. We then modified the Dst index as estimated by the WINDMI model to include contributions from the cross-tail current and magnetopause currents. The modified Dst was then optimized for all the events. The optimized results correlate very well to the Dst dynamics and indicate that under northward IMF B z conditions and during the early recovery phase of a storm; contributions from the geotail currents to the fast initial decay of the Dst index are important, while the slower recovery of Dst in the later phases of the storm are due to the charge exchange dominated ring current decay.

[1] We evaluate the performance of three solar wind-magnetosphere coupling functions in training the physics-based WINDMI model on the 3-7 October 2000 geomagnetic storm and predicting the geomagnetic Dst and AL indices during the 15-24 April 2002 geomagnetic storm. The rectified solar wind electric field, a coupling function by Siscoe, and a recent formula proposed by Newell are evaluated. The Newell coupling function performed best in both the training and prediction phases for Dst prediction. The Siscoe formula performed best during the training phase in reproducing the AL faithfully and capturing storm time events. The rectified driver was discovered to be the best in overall performance during both training as well as prediction phases, even though the other two coupling functions outperform it in the training phase. The results indicate that multiple drivers need to be concurrently employed in space weather models to yield different possible levels of geomagnetic activity.

1] A low-dimensional, plasma physics-based, nonlinear dynamical model of the coupled magnetosphere-ionosphere system, called Real-Time Solar Wind Magnetosphere-Ionosphere System (WINDMI), is used to predict AL and Dst values approximately 1 h before geomagnetic substorm and storm event. Subsequently, every 10 min ground-based measurements compiled by World Data Center, Kyoto, are compared with model predictions (http://orion.ph.utexas.edu/$windmi/realtime/). WINDMI model runs are also available at the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov/). The performance of the Real-Time WINDMI model is quantitatively evaluated for 22 storm/substorm event predictions from February 2006 to August 2008. Three possible input solar wind-magnetosphere coupling functions are considered: the standard rectified coupling function, a function due to Siscoe, and a recent function due to Newell. Model AL and Dst predictions are validated using the average relative variance (ARV), correlation coefficient (COR), and root mean squared error (RMSE). The Newell input function yielded the best model AL predictions by all three measures (mean ARV, COR, and RMSE), followed by the rectified, then Siscoe input functions. Model AL predictions correlate at least 1 standard deviation better with the AL index data than a direct correlation between the input coupling functions and the AL index. The mean Dst ARV results show better prediction performance for the rectified input than the Siscoe and Newell inputs. The mean Dst COR and RMSE measures do not readily distinguish between the three input coupling functions.

[1] In this paper we investigate the role of different solar wind magnetosphere coupling functions on the Dst index calculated by the low-order nonlinear dynamical WINDMI model. In our previous work we have shown that the geotail current dynamics has a significant role in the two-phase decay of the Dst index. During that investigation we used the rectified solar wind electric field v x B z as a baseline for the simulations and analysis. Here we include an evaluation of four other coupling functions in addition to the rectified vB s . These coupling functions emphasize different physical mechanisms to explain the energy transfer into the magnetosphere due to solar wind velocity, dynamic pressure, magnetic field, and Mach number. One coupling function is due to Siscoe, another by Borovsky, and two by Newell. Our results indicate that for a majority of cases, at most only v x , B y , and B z are needed to sufficiently account for the supply of energy to the ring current and geotail current components that contribute to the Dst index. The more complex coupling functions sometimes perform extremely well on storm data sets but at other times do not reproduce the Dst index faithfully. The AL index was used as an additional constraint on the allowable geotail current dynamics and to further differentiate between coupling functions when the Dst performance was similar. The solar wind dynamic pressure contribution appears to be correctly accounted for through the calculation of the Dmp formula of Burton et al. (1975). The degree to which the B y component affects the Dst index is not entirely clear from our results, but in most cases its inclusion slightly overemphasizes the ring current contribution and slightly underemphasizes the geotail current contribution.