On Optimum Solar Wind‐Magnetosphere Coupling Functions for Transpolar Voltage and Planetary Geomagnetic Activity. Issue 12 (14th December 2021)

• Record Type: Journal Article
• Authors: Lockwood, Mike; McWilliams, Kathryn A.
• Is Part Of: Journal of geophysical research. Volume 126:Issue 12(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-12-14
• Subjects: solar wind‐magnetosphere coupling -- coupling functions -- distributions of interplanetary parameters -- effects of averaging -- origins of correlation noise; Magnetospheric physics -- Periodicals; Space environment -- Periodicals; Cosmic physics -- Periodicals; Planets -- Atmospheres -- Periodicals; Heliosphere (Astrophysics) -- Periodicals; Geophysics -- Periodicals; 523.01
• DOI: 10.1029/2021JA029946
• Languages: English
• ISSNs: 2169-9380

Abstract

Abstract: Using 65, 133 hourly averages of transpolar voltage ( Φ PC ) from observations made over 25 yr by the SuperDARN radars, with simultaneous SML and interpolated am geomagnetic indices, we study their optimum interplanetary coupling functions. We find mean 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, yielding d of 2.50 ± 0.10, 3.00 ± 0.22, and 5.20 ± 0.41 for Φ PC, am, and SML, respectively. To check for overfitting, fits are made to half the available data and tested against the other half. Ensembles of 1, 000 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 . Plain Language Summary: Coupling functions are mathematical combinations of measured variables observed in the solar wind, just before it impacts near‐Earth space. They are used to predict the effect that the solar wind will have (or, for retrospective studies, will have had) on the space‐weather environment of the Earth. There is a very wide variety of proposed optimum forms for coupling functions in the literature, some of which work better than others and we show which performs best depends on which terrestrial disturbance indicator we are trying to predict and on what timescale. We look at the validity of some commonly used assumptions made when compiling a coupling function and, using an unprecedentedly large data set of different types of terrestrial space weather disturbance indicator, we derive the optimum coupling functions and their statistical uncertainties. We show that that the required coupling functions are significantly different in the three cases. The results establish some important principles for the development of these coupling functions and show they need to be tailored to the specific space weather disturbance indicator, timescale, and activity level that they aim to predict. Key Points: Using a very large dataset we analyze the sources and effects of noise in correlation studies used to derive solar wind coupling functions We study effects of weighting by the distribution of samples which varies with the choice of interplanetary magnetic field orientation factor and averaging timescale The optimum coupling functions for transpolar voltage and a planetary geomagnetic activity index are significantly different