A document by Michael Lockwood. Click on the document to view its contents.

A document by Michael Lockwood. Click on the document to view its contents.

A document by Michael Lockwood. Click on the document to view its contents.

A document by Michael Lockwood. Click on the document to view its contents.

Using 65,133 hourly averages of transpolar voltage Φ(PC) from observations made over 25 years by the SuperDARN radars, with simultaneous SML and interpolated am geomagnetic indices, we study their optimum interplanetary coupling functions. We find lags of 18, 31 and 45 min. for Φ_{PC}, am and SML respectively, and fit using a general coupling function with three free fit exponents. To converge to a fit, we need to average interplanetary parameters and then apply the exponent which is a widely-used approximation: we show how and why this is valid for all interplanetary parameters, except the factor quantifying the effect of the clock angle of the interplanetary magnetic field, sin^(d)(θ/2), which must be computed at high time resolution and then averaged. We demonstrate the effect of the exponent d on the distribution, and hence weighting, of samples and show d is best determined from the requirement that the coupling function is a linear predictor, which yields d of 2.50+/-0.10, 3.00+/-0.22 and 5.23+/-0.48 for Φ_{PC}, am and SML. To check for overfitting, fits are made to half the available data and tested against the other half. Ensembles of 1000 fits are used to study the effect of the number of samples on the distribution of errors in individual fits and on systematic biases in the ensemble means. We find only a weak dependence of solar wind density for Φ_{PC} and SML but a significant one for am. The optimum coupling functions are shown to be significantly different for Φ_{PC}, am and SML.

We use 214410 hourly observations of the transpolar voltage, ΦPC, from 25 years of observations by the SuperDARN radars, to confirm the central tenet of the Expanding-Contracting Polar Cap (ECPC) model of ionospheric convection that ΦPC responds to both dayside and nightside reconnection voltages (ΦD and ΦN). We show ΦPC increases at a fixed level of nightside auroral electrojet AL index with increasingly southward IMF (identifying the well-known effect of ΦD on ΦPC) but also with increasingly negative AL at a fixed southward IMF (identifying a distinct effect of ΦN on ΦPC ). We study the variation of ΦPC with time elapsed Δt since the IMF last pointed southward and show that low/large values occur when -AL is small/large. We have to allow for the fact that at lower numbers of radar echoes, ne , the matched potential re-analysis technique used to derive is influenced by the model used: this is done by a sensitivity study of the threshold of ne required. We show that for any threshold ΦPC falls to about 15kV for & Δt greater than about 15 hours giving an upper limit to the viscous-like voltage. It is shown that both ΦPC and -AL increase with increased solar wind dynamic pressure psw , but not as much as the mid-latitude geomagnetic range index am. We conclude psw increases both ΦD and ΦN through increasing the magnetic shear across the relevant current sheet but has a bigger effect on mid-latitude geomagnetic activity indices via the additional energy stored in the tail lobes.

Solar wind-magnetosphere coupling functions have been in use for almost 50 years. In that time, a very large number of formulations have been proposed. As they become increasingly subsumed into systems analysis and machine-learning studies of the magnetosphere, it is timely to establish best practice in their derivation and their limitations. This paper carried out a number of studies to establish some key points. Particular attention is paid to the best metric used to evaluate their performance and how it depends on the application for which the coupling function is intended.

Geometric modelling of Coronal Mass Ejections (CMEs) is a widely used tool for assessing their kinematic evolution. Furthermore, techniques based on geometric modelling, such as ELEvoHI, are being developed into forecast tools for space weather prediction. These models assume that solar wind structure does not affect the evolution of the CME, which is an unquantified source of uncertainty. We use a large number of Cone CME simulations with the HUXt solar wind model to quantify the scale of uncertainty introduced into geometric modelling and the ELEvoHI CME arrival times by solar wind structure. We produce a database of simulations, representing an average, a fast, and an extreme CME scenario, each independently propagating through 100 different ambient solar wind environments. Synthetic heliospheric imager observations of these simulations are then used with a range of geometric models to estimate the CME kinematics. The errors of geometric modelling depend on the location of the observer, but do not seem to depend on the CME scenario. In general, geometric models are biased towards predicting CME apex distances that are larger than the true value. For these CME scenarios, geometric modelling errors are minimised for an observer in the L5 region. Furthermore, geometric modelling errors increase with the level of solar wind structure in the path of the CME. The ELEvoHI arrival time errors are minimised for an observer in the L5 region, with mean absolute arrival time errors of 8.2±1.2h, 8.3±1.0h, and 5.8±0.9h for the average, fast, and extreme CME scenarios

We introduce the inductive effects of polar cap motions towards and way from the Sun into magnetospheric electrodynamics and show how this explains observed Universal Time variations in hemispheric geomagnetic indices. The large (and growing) hemispheric asymmetry in the offsets of the geomagnetic (dip or eccentric dipole) poles from Earth’s rotational axis means that the effect is not cancelled out in global indices. By adding this effect to that of the Russell-McPherron effect on solar wind-magnetosphere coupling, that of ionospheric conductivities, and that of the solar wind dynamic pressure and dipole tilt on the near-Earth tail lobe field and cross-tail current sheet, we are able to model the persistent “equinoctial” time-of-day/time-of-year pattern (with additional net Universal time variations) observed in the an, as and am geomagnetic indices since 1959. We discuss the implications for the longitudinal dependence of the effects of extreme space weather events