Analytic modeling of recurrent Forbush decreases caused by corotating interaction regions

TL;DR

This paper develops an analytic convection-diffusion model based on the Fokker-Planck equation to explain recurrent Forbush decreases caused by corotating interaction regions, successfully matching long-term observational data.

Contribution

It introduces a simplified yet effective convection-diffusion model that explains RFD features, including over-recovery and secondary dips, based on solar wind and magnetic field effects.

Findings

The model accurately reproduces observed RFD profiles.

Enhanced convection and reduced diffusion are key to RFD signatures.

Good agreement with 27-rotation CIR observations.

Abstract

On scales of days, the galactic cosmic ray (GCR) flux is affected by coronal mass ejections and corotating interaction regions (CIRs), causing so-called Forbush decreases and recurrent Forbush decreases (RFDs), respectively. We explain the properties and behavior of RFDs recorded at about 1 au that are caused by CIRs generated by solar wind high-speed streams (HSSs) that emanate from coronal holes. We employed a convection-diffusion GCR propagation model based on the Fokker-Planck equation and applied it to solar wind and interplanetary magnetic field properties at 1 au. Our analysis shows that the only two effects that are relevant for a plausible overall explanation of the observations are the enhanced convection effect caused by the increased velocity of the HSS and the reduced diffusion effect caused by the enhanced magnetic field and its fluctuations within the CIR and HSS structure. These two effects that we considered in the model are sufficient to explain not only the main signatures of RFDs, but also the sometimes observed "over-recovery" and secondary dips in RFD profiles. The explanation in terms of the convection-diffusion GCR propagation hypothesis is tested by applying our model to the observations of a long-lived CIR that recurred over 27 rotations in 2007-2008. Our analysis demonstrates a very good match of the model results and observations.