Forbush Decrease Prediction Based on the Remote Solar Observations

TL;DR

This paper develops a probabilistic model using remote solar observations to forecast Forbush decreases caused by CMEs, enabling early prediction without reliance on spacecraft data.

Contribution

It introduces a new empirical probabilistic forecasting method for Forbush decreases based on remote solar observations and statistical analysis of CME/flare parameters.

Findings

The model can predict Forbush decrease magnitude ranges.

Forecast accuracy decreases with increased specificity.

Remote observations enable early, spacecraft-independent predictions.

Abstract

We employ remote observations of coronal mass ejections (CMEs) and the associated solar flares to forecast the CME-related Forbush decreases, i.e., short-term depressions in the galactic cosmic-ray flux. The relationship between the Forbush effect at the Earth and remote observations of CMEs and associated solar flares is studied via a statistical analysis. Relationships between Forbush decrease magnitude and several CME/flare parameters was found, namely the initial CME speed, apparent width, source position, associated solar-flare class and the effect of successive-CME occurrence. Based on the statistical analysis, remote solar observations are employed for a Forbush-decrease forecast. For that purpose, an empirical probabilistic model is constructed that uses selected remote solar observations of CME and associated solar flare as an input, and gives expected Forbush-decrease magnitude range as an output. The forecast method is evaluated using several verification measures, indicating that as the forecast tends to be more specific it is less reliable, which is its main drawback. However, the advantages of the method are that it provides early prediction, and that the input is not necessarily spacecraft-dependent.