Statistical investigation of hourly OMNI solar wind data

13Citations
Citations of this article
11Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Hourly OMNI solar wind data are sorted into categories reflecting membership of each data point to either slow or fast solar wind streams, or to either coronal mass ejection or corotating interaction region environments. The categorization is inspired by Yermolaev et al. (2009) and modified from there. Durations and coverage fractions of each category are investigated, together with their dependence on the solar activity cycle. The results are in line with physical expectations for the solar wind at 1 AU. A further analysis, treating hourly solar wind fluctuations as a constrained random walk process, is carried out independently for each solar wind category and discussed. The resulting step size distributions are found to be largely symmetric across zero, resembling a random walk deviation from a long-term average. This constrained random walk can in principle be used to fill gaps in the OMNI data and perform other OMNI data extrapolations. Copyright 2011 by the American Geophysical Union.

References Powered by Scopus

This article is free to access.

Get full text
Get full text

Cited by Powered by Scopus

Get full text
107Citations
36Readers

This article is free to access.

This article is free to access.

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Cite

CITATION STYLE

APA

Thatcher, L. J., & Müller, H. R. (2011). Statistical investigation of hourly OMNI solar wind data. Journal of Geophysical Research: Space Physics, 116(12). https://doi.org/10.1029/2011JA017027

Readers over time

‘12‘13‘14‘15‘17‘19‘2301234

Readers' Seniority

Tooltip

PhD / Post grad / Masters / Doc 4

40%

Professor / Associate Prof. 3

30%

Researcher 3

30%

Readers' Discipline

Tooltip

Physics and Astronomy 6

55%

Earth and Planetary Sciences 3

27%

Computer Science 1

9%

Engineering 1

9%

Save time finding and organizing research with Mendeley

Sign up for free
0