Using ground-level cosmic ray observations for automatically generating predictions of hazardous energetic particle levels

Abstract It is well known that in periods of great flare energetic particle (FEP) ground events, fluxes of energetic particles can be so big that memory of computers and other electronics in space may be damaged, and satellite and spacecraft operations can be seriously degraded. In these periods it is necessary to switch off some part of electronics for a few hours to protect computer memories. The problem is how to forecast exactly these dangerous phenomena. We show that exact forecasts can be made by using high-energy particles (few GeV/nucleon and higher) whose transportation from the Sun is characterized by much bigger diffusion coefficients than lower energy particles. High-energy particles arrive from the Sun much earlier (8–20 minutes after acceleration and escaping into solar wind) than the lower energy particles that damage electronics (about 30–60 minutes later). We describe here the principles and operation of automated programs “FEP-Search-1 min”, “FEP-Search-2 min”,and “FEPSearch-5 min”, developed and checked in the Emilio Segre' Observatory (ESO) of the Israel Cosmic Ray Center (2025 m above sea level, R c =10.8 GV). The determination of increasing flux is made by comparison with the intensity, averaged from 120 to 61 minutes, prior to the current one-minute data. For each minute of data the program “FEP-Search-1 min” is run. If the result is negative (no simultaneous increase in both channels of total intensity ≥ 2.5 σ 1 , where σ 1 is the standard deviation for one minute of observation in one channel [for ESO σ 1 =1.4 %), start the program “FEP-Search-2 min”, using two minute averages with σ 2 = σ 1 /√2, and so on. If any positive result is obtained, the “FEP-Search” programs check the next minute of data. If the result is again positive, automatically run the on-line the programs “FEP-Collect” and “FEP-Research” that determine the expected flux and spectrum and generate automatic alerts. These programs are described in Dorman and Zukerman (2001).