Role of Averaging in Statistical Analysis of Solar Wind Data from the DSCOVR Spacecraft for the First Year of Operation

Abstract

The results from a statistical analysis of solar wind data obtained near the Earth’s orbit by the DSCOVR spacecraft for the period of one year starting August 2016 are discussed. The distribution of the solar wind temperature T for this period was bimodal and exhibited two maxima at 15 × 10³ and 190 × 10³ K (with a standard deviation of the same order of magnitude, respectively). This distribution can be represented as the sum of two lognormal distributions. The first peak of the T distribution is caused by the slow-cold wind component, the distributions of which over speed V and density n (varying in wide ranges) are also close to lognormal. This component covers slightly more than a quarter of the entire time period. A fast hot wind (the distribution maximum is at 310 × 10³ K) can be distinguished from the remainder; this component covers slightly less than a quarter of the period. Its T, V, and n distributions are also close to lognormal. The rest the wind, nearly half, exhibits a complex “jagged” distribution over speed and a double-peak distribution over density. The conclusion is that data averaging is of key importance in the classification of solar wind at the quantitative level. This is shown by the results of data averaging over a minute, hour, day, and week.