Propagation delay of solar wind discontinuities: Comparing different methods and evaluating the effect of wavelet denoising

Abstract

[1] We present a statistical study of the performance of three methods used to predict the propagation delay of solar wind structures. These methods are based on boundary normal estimations between the Advanced Composition Explorer (ACE) spacecraft orbiting the L1 libration point and the Cluster spacecraft near the Earth's magnetopause. The boundary normal estimation methods tested are the cross product method (CP), the minimum variance analysis of the magnetic field (MVAB), and the constrained minimum variance analysis (MVAB0). The estimated delay times are compared with the observed ones to obtain a quantitative measure of each method's accuracy. Boundary normal estimations of magnetic field structures embedded in the solar wind are known to be sensitive to small-scale fluctuations. Our study uses wavelet denoising to reduce the effect of these fluctuations. The influence of wavelet denoising on the performance of the three methods is also analyzed. We find that the free parameters of the three methods have to be adapted to each event in order to obtain accurate propagation delays. We also find that by using denoising parameters optimized to each event, 88% of our database of 356 events are estimated to arrive within˙2 min from the observed time delay with MVAB, 74% with CP, and 69% with the MVAB0 method. Our results show that wavelet denoising significantly improves the predictions of the propagation time delay of solar wind discontinuities.

Validation of an operational product to determine L1 to Earth propagation time delays

“…The standard method used by NOAA's Space Weather Forecast Office of assuming a flat plane propagation delay may continue to be the best option when accounting for simplicity and consistency in the observed results. Other methods, such as wavelet denoising [ Haaland et al ., ; Munteanu et al ., ], have shown promising results and future efforts could focus on evaluating how well such a technique works when implemented in a real‐time operational setting with a continuous stream of real‐time solar wind data.…”

“…Subsequently, various forms of the MVA technique [ Sonnerup and Scheible , ] have been used to compute the tilt of solar wind phase planes with respect to the Sun‐Earth line [ Weimer et al ., ; Bargatze et al ., ; Weimer and King , ; Mailyan et al ., ; Pulkkinen and Rastätter , ; Haaland et al ., ; Munteanu et al ., ]. Weimer et al .…”

On the Motion of the Heliospheric Magnetic Structure Through the Solar Wind Plasma

“…Knowledge about the movement of the heliospheric magnetic structure relative to the solar wind plasma can potentially lead to improvements in data-analysis schemes that advect upstream solar wind measurements to the Earth (Bargatze et al, 2005;Mailyan et al, 2008;Munteanu et al, 2013;Weimer et al, 2002Weimer et al, , 2003Weimer & King, 2008), critically used for magnetospheric physics and space weather. And note also that the velocity structure and plasma-properties structure of the heliosphere also moves with the magnetic structure.…”

Using a Numerical MHD Model to Improve Solar Wind Time Shifting

“…If only one monitor is available, methods such as the cross product method (Horbury et al, 2001), minimum variance analysis of the magnetic field (MVAB), constrained minimum variance analysis (MVAB-0; Sonnerup & Scheible, 1998), or even assuming a constant phase plane orientation (Jackel et al, 2013) can be used. There have been many studies comparing the effectiveness of various time-shifting methods (Cameron & Jackel, 2016;Cash et al, 2016;Mailyan et al, 2008;Munteanu et al, 2013). While Mailyan et al (2008), Munteanu et al (2013), and Cameron and Jackel (2016) found that MVAB-0 was the best performing time-shifting method, Cash et al (2016) concluded that the improvements were too minor for use in a real-time prediction capacity.…”