A solar-wind-driven empirical model of Pc3 wave activity at a mid-latitude location

In this paper we describe the development of two empirical models of Pc3 wave activity observed at a ground station. The models are tasked to predict pulsation intensity at Tihany, Hungary, from the OMNI solar wind data set at 5 min time resolution. One model is based on artificial neural networks and the other on multiple linear regression. Input parameters to the models are iteratively selected from a larger set of candidate inputs. The optimal set of inputs are solar wind speed, interplanetary magnetic field orientation (via cone angle), proton density and solar zenith angle (representing local time). Solar wind measurements are shifted in time with respect to Pc3 data to account for the propagation time of ULF perturbations from upstream of the bow shock. Both models achieve correlation of about 70 % between measured and predicted Pc3 wave intensity. The timescales at which the most important solar wind parameters influence pulsation intensity are calculated for the first time. We show that solar wind speed influences pulsation intensity at much longer timescales (about 2 days) than cone angle (about 1 h).