Open AccessRemoving Orbital Variations From Low Altitude Particle Data: Method and Application
Author(s) -
Green J. C.,
O’Brien T. P.,
Claudepierre S. G.,
Boyd A. J.
Publication year - 2021
Publication title -
space weather
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.254
H-Index - 56
ISSN - 1542-7390
DOI - 10.1029/2020sw002638
Subject(s) - geosynchronous orbit , altitude (triangle) , flux (metallurgy) , van allen radiation belt , satellite , environmental science , space weather , galileo (satellite navigation) , spacecraft , meteorology , atmospheric sciences , remote sensing , physics , geography , astronomy , magnetosphere , geometry , mathematics , materials science , plasma , quantum mechanics , metallurgy
Particle flux measurements from polar orbiting low altitude satellites provide a view of the near Earth radiation environment that is extremely valuable for science as well as space weather monitoring. Unlike, geosynchronous satellites that sample only a limited region of space ( L = ∼6.6), these low altitude satellites sample the extended radiation environment ( L = 1 to >10) at a relatively high time cadence (tens of minutes) that captures its global evolution. While these data are clearly useful, it is also challenging to work with because the particle flux measurements have large orbital variations related to the changing geographic location of the satellites. These orbital flux variations can sometimes obscure the time variations of interest for scientific study or space weather hazard awareness. Here, we describe and evaluate a method for removing these variations that is based on Statistical Asynchronous Regression. We demonstrate the utility and accuracy of the method by applying it to electron flux measurements from the NOAA POES and EUMetSat MetOp low altitude satellites.