Improving dB/dt Forecasts with Advanced Conductance Models

Geomagnetically Induced Currents (GICs), an important aspect of space weather, are electric currents driven by space weather activity in the near-Earth space environment. These currents, if strong enough, can damage and/or potentially interrupt man-made technological systems such as pipelines, railway lines and high voltage electric power lines, drastically affecting those who depend on them. A significant challenge in the space weather community has been to develop systems that are able to accurately monitor and predict the response of the near-Earth space environment during space weather events. An initial effort to assess the performance of operationally-promising GIC models was presented by Pulkkinen et al. [2013]. While this study represents a landmark first-step towards numerical space weather forecasting, many questions remained concerning the models’ performance capabilities for different levels of geomagnetic activity. Investigations by Welling et al. [2017] raised concerns that the limited datasets used in developing the estimation techniques of the ionospheric conductance in the auroral region in these GIC models do not include any information during strong driving.

This work addresses the concerns raised in Welling et al. [2017], with the development of the new Conductance Model for Extreme Events (CMEE) within the Space Weather Modeling Framework (SWMF). CMEE has been developed using a year's worth of one-minute resolution output from Assimilative Maps of Ionosphere Electrodynamics (AMIE), including times of extreme driving of the solar wind-magnetosphere-ionosphere system. The model fits auroral conductance measurements against field aligned current (FAC) inputs using an inverse exponential empirical relationship. Conductance estimates during extreme driving are specifically included in these fits, by basing the endpoint of said fit on the 90% percentile of the conductance values in a given bin, such that the fitted curve extends to these extreme values and is not just limited to the median or mean conductance. CMEE is integrated as part of the Ridley Ionosphere Model (RIM), replacing the older legacy conductance model based off of a month's worth of data. In this study, the CMEE-RIM model has been coupled dynamically with the BATS-R-US magnetohydrodynamic (MHD) model, & the Rice Convection Model (RCM) of the ring current as part of the SWMF Geospace setup for GIC prediction, and is employed to simulate the 6 geomagnetic events studied in Pulkkinen et al. [2013]. Data-model comparisons are conducted for polar cap potentials and conductance patterns against ground-based and in-situ measurements. Results show significant improvements in ground-based dB/dt predictions, and dB estimations when validated against observations. Metrics are calculated to examine how the new model improves forecast skill. These results illustrate the current state of conductance modeling in GIC models, and the aptitude of this technology for operational use.