Methodology of evaluating the science benefit of various satellite/sensor constellation orbital parameters to an assimilative data forecast model Article Swipe
R. L. Balthazor
,
M. G. McHarg
,
C. L. Enloe
,
Brandon A. Mueller
,
David J. Barnhart
,
Zachary W. Hoeffner
,
Robert W. Brown
,
L. Scherliess
,
Lance T. Wilhelm
·
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1002/2014rs005426
YOU?
·
· 2015
· Open Access
·
· DOI: https://doi.org/10.1002/2014rs005426
A methodology for evaluating the science benefit of adding space weather sensor data from a modest number of small satellites to the Utah State University Global Assimilation of Ionospheric Measurements—Full Physics (GAIM‐FP) model is presented. Three orbital scenarios are presented, two focusing on improved coverage of narrowly specified regions of interest, and one on global coverage of the ionosphere as a whole. An Observing System Simulation Experiment is used to obtain qualitative and quantitative results of the impact of the various orbital scenarios on the ionospheric specifications. A simulated “truth” run of the ionosphere is obtained from a first principle model of the ionosphere/plasmasphere model and used to generate global simulated Global Positioning Satellite total electron content (GPS‐TEC) data as well as in situ plasma density observations. Initially, only GPS data were assimilated by GAIM‐FP, and the results of this limited run were compared to the truth run. Next, the simulated in situ plasma densities corresponding to our three orbital scenarios were assimilated together with the GPS data, and the results were compared to both the truth run and the limited GPS‐TEC only GAIM‐FP run. These model simulations have shown that adding a constellation of small satellites/sensors in addition to global TEC inputs does indeed converge the GAIM‐FP model closer to truth in the situations described.
Related Topics
Concepts
TEC
Plasmasphere
Global Positioning System
Data assimilation
Constellation
Satellite
Ionosphere
Environmental science
Total electron content
International Reference Ionosphere
Remote sensing
Meteorology
Computer science
Space weather
Satellite constellation
Plasma
Geology
Geography
Physics
Geophysics
Magnetosphere
Telecommunications
Astronomy
Quantum mechanics
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/2014rs005426
- https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2014RS005426
- OA Status
- bronze
- Cited By
- 8
- References
- 20
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W1951856660
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W1951856660Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/2014rs005426Digital Object Identifier
- Title
-
Methodology of evaluating the science benefit of various satellite/sensor constellation orbital parameters to an assimilative data forecast modelWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2015Year of publication
- Publication date
-
2015-03-06Full publication date if available
- Authors
-
R. L. Balthazor, M. G. McHarg, C. L. Enloe, Brandon A. Mueller, David J. Barnhart, Zachary W. Hoeffner, Robert W. Brown, L. Scherliess, Lance T. WilhelmList of authors in order
- Landing page
-
https://doi.org/10.1002/2014rs005426Publisher landing page
- PDF URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2014RS005426Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2014RS005426Direct OA link when available
- Concepts
-
TEC, Plasmasphere, Global Positioning System, Data assimilation, Constellation, Satellite, Ionosphere, Environmental science, Total electron content, International Reference Ionosphere, Remote sensing, Meteorology, Computer science, Space weather, Satellite constellation, Plasma, Geology, Geography, Physics, Geophysics, Magnetosphere, Telecommunications, Astronomy, Quantum mechanicsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
8Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1, 2020: 1, 2019: 2, 2018: 1, 2016: 1Per-year citation counts (last 5 years)
- References (count)
-
20Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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