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Title: Measurement and modeling of the refilling plasmasphere during 2001

Journal Article · · Journal of Geophysical Research. Space Physics
DOI:https://doi.org/10.1002/2015JA022126· OSTI ID:1246839
 [1];  [1];  [2];  [3];  [4];  [4]
  1. Naval Research Lab., Washington, DC (United States)
  2. Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
  3. Dartmouth College, Hanover, NH (United States)
  4. Univ. of Michigan, Ann Arbor, MI (United States)

Abstract The Naval Research Laboratory SAMI3 (Sami3 is Also a Model of the Ionosphere) and the RAM‐CPL (Ring current Atmosphere interaction Model‐Cold PLasma) codes are used to model observed plasmasphere dynamics during 25 November 2001 to 1 December 2001 and 1–5 February 2001. Model results compare well to plasmasphere observations of electron and mass densities. Comparison of model results to refilling data and to each other shows good agreement, generally within a factor of 2. We find that SAMI3 plasmaspheric refilling rates and ion densities are sensitive to the composition and temperature of the thermosphere and exosphere, and to photoelectron heating. Results also support our previous finding that the wind‐driven dynamo significantly impacts both refilling rates and plasmasphere dynamics during quiet periods.

Research Organization:
Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
Sponsoring Organization:
USDOE
Grant/Contract Number:
NNX10AQ60G; AGS1105790; AGS1265651; AC52-06NA25396
OSTI ID:
1246839
Alternate ID(s):
OSTI ID: 1402196
Report Number(s):
LA-UR-15-28753
Journal Information:
Journal of Geophysical Research. Space Physics, Vol. 165, Issue C; ISSN 2169-9380
Publisher:
American Geophysical UnionCopyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 13 works
Citation information provided by
Web of Science

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Cited By (2)

The Effect of Oxygen on the Limiting H + Flux in the Topside Ionosphere journal June 2019
A neural network model of three-dimensional dynamic electron density in the inner magnetosphere: Neural Network Model of Plasma Density journal September 2017

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