Development of Forecast Algorithm for Coronal Mass Ejection Speed and Arrival Time Based on Propagation Tracking by Interplanetary Scintillation g-Value

Abstract

We have developed an algorithm for tracking coronal mass ejection (CME) propagation that allows us to estimate CME speed and its arrival time at Earth. The algorithm may be used either to forecast the CME’s arrival on the day of the forecast or to update the CME tracking information for the next day’s forecast. In our case study, we successfully tracked CME propagation using the algorithm based on g-values of interplanetary scintillation (IPS) observation provided by the Institute for Space- Earth Environmental Research (ISEE). We were able to forecast the arrival time (Δt = 0.30 h) and speed (Δv = 20 km/s) of a CME event on October 2, 2000. From the CME-interplanetary CME (ICME) pairs provided by Cane & Richardson (2003), we selected 50 events to evaluate the algorithm’s forecast capability. Average errors for arrival time and speed were 11.14 h and 310 km/s, respectively. Results demonstrated that g-values obtained continuously from any single station observation were able to be used as a proxy for CME speed. Therefore, our algorithm may give stable daily forecasts of CME position and speed during propagation in the region of 0.2–1 AU using the IPS g-values, even if IPS velocity observations are insufficient. We expect that this algorithm may be widely accepted for use in space weather forecasting in the near future.

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“…With respect to a real-time CME event that happened on October 2, 2000, the developed algorithm predicted the propagation of three daily storms; the errors in arrival time and speed were 18 minutes and 20 km/s, respectively. This demonstrated that the g-values of IPS observations from the Institute for Space-Earth Environmental Research (ISEE) can be used to track the propagation of CMEs.Furthermore, statistical validation was carried out on 50 CME-ICME pair events, yielding an average error of 310 km/s for velocity and 11.14 h for arrival time[4].Kim & Chang[5] looked into the relationships between solar variability and teleconnection indices, which affect atmospheric circulation and the spatial distribution of the global pressure system, in order to investigate the potential role of the Sun in understanding natural climate change. Using teleconnection indices [Southern Oscillation Index (SOI), Arctic Oscillation (AO), Antarctic Oscillation (AAO), and Pacific-North American (PNA)], they have computed the normalized cross-correlations of the total sunspot area, total sunspot number, and the solar north-south asymmetry.Consequently, (1) El Niño episodes most likely happen three years after a solar maximum because the SOI index has an anti-correlated relationship with both solar activity and the solar north-south asymmetry, with a lag of approximately −3 years.…”