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There is considerable evidence that current sheet scattering (CSS) plays an important role in isotropic boundary (IB) formation during quiet time. However, IB formation can also result from scattering by electromagnetic ion cyclotron waves, which are much more prevalent during storm time. The effectiveness of CSS can be estimated by the parameter, the ratio of the field line radius of curvature to the particle gyroradius. Using magnetohydrodynamic and empirical models, we estimated the parameterKassociated with storm time IB observations on the nightside. We used magnetic field observations from spacecraft in the magnetotail to estimate and correct for errors in theKvalues computed by the models. We find that the magnetohydrodynamic and empirical models produce fairly similar results without correction and that correction increases this similarity. Accounting for uncertainty in both the latitude of the IB and the threshold value ofKrequired for CSS, we found that 29–54% of the IB observations satisfied the criteria for CSS. We found no correlation between the correctedKand magnetic local time, which further supports the hypothesis that CSS played a significant role in forming the observed IBs.

Recent studies have found that even during quiet times, observed proton isotropic boundaries (IBs) are often projected to the region of high adiabaticity parameter (K≈30), whereis the ratio of magnetic field line radius of curvature to the particle gyroradius. This contradicts the accepted hypothesis that current sheet scattering (CSS) is the dominant mechanism of IB formation becauseK≈8 would be expected for this mechanism. We used magnetohydrodynamic simulations and empirical models to computeKfor 30‐keV proton IB observations within 3 hr of local midnight. We found that neither class of model reliably estimatesKunless supported by magnetic field observations in the current sheet. magnetohydrodynamic simulations produced higherKvalues than expected for CSS (K = 15–30), and empirical models gave lower values (K < 4). We obtained reliable estimates ofKby controlling for the accuracy of the normal component and the gradient of the radial component in the neutral sheet, using observations from three Time History of Events and Macroscale Interactions during Substorms satellites. For the first time, we demonstrated that both these variables should be taken into account for the accurate estimation of the curvature radius. This greatly reduced the spread ofKvalues, indicating that much of the previous spread was due to errors in the magnetic field but also that these errors can be controlled. Most of the corrected values fall within the expected range for CSS, supporting the hypothesis that the IB's were formed by CSS. Accounting for all model results, we obtain an average corrected value ofK = 6.0.

A new model validation and performance assessment tool is introduced, the sliding threshold of observation for numeric evaluation (STONE) curve. It is based on the relative operating characteristic (ROC) curve technique, but instead of sorting all observations in a categorical classification, the STONE tool uses the continuous nature of the observations. Rather than defining events in the observations and then sliding the threshold only in the classifier/model data set, the threshold is changed simultaneously for both the observational and model values, with the same threshold value for both data and model. This is only possible if the observations are continuous and the model output is in the same units and scale as the observations, that is, the model is trying to exactly reproduce the data. The STONE curve has several similarities with the ROC curve—plotting probability of detection against probability of false detection, ranging from the (1,1) corner for low thresholds to the (0,0) corner for high thresholds, and values above the zero‐intercept unity‐slope line indicating better than random predictive ability. The main difference is that the STONE curve can be nonmonotonic, doubling back in both thexandydirections. These ripples reveal asymmetries in the data‐model value pairs. This new technique is applied to modeling output of a common geomagnetic activity index as well as energetic electron fluxes in the Earth's inner magnetosphere. It is not limited to space physics applications but can be used for any scientific or engineering field where numerical models are used to reproduce observations.