Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS) Article Swipe
R. W. Schunk
,
L. Scherliess
,
J. V. Eccles
,
L. C. Gardner
,
J. J. Sojka
,
L. Zhu
,
Xiaoqing Pi
,
A. J. Mannucci
,
Mark D. Butala
,
Brian Wilson
,
A. Komjáthy
,
Chunming Wang
,
G. Rosen
·
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1002/2015rs005888
YOU?
·
· 2016
· Open Access
·
· DOI: https://doi.org/10.1002/2015rs005888
The goal of the Multimodel Ensemble Prediction System (MEPS) program is to improve space weather specification and forecasting with ensemble modeling. Space weather can have detrimental effects on a variety of civilian and military systems and operations, and many of the applications pertain to the ionosphere and upper atmosphere. Space weather can affect over‐the‐horizon radars, HF communications, surveying and navigation systems, surveillance, spacecraft charging, power grids, pipelines, and the Federal Aviation Administration (FAA's) Wide Area Augmentation System (WAAS). Because of its importance, numerous space weather forecasting approaches are being pursued, including those involving empirical, physics‐based, and data assimilation models. Clearly, if there are sufficient data, the data assimilation modeling approach is expected to be the most reliable, but different data assimilation models can produce different results. Therefore, like the meteorology community, we created a Multimodel Ensemble Prediction System (MEPS) for the Ionosphere‐Thermosphere‐Electrodynamics (ITE) system that is based on different data assimilation models. The MEPS ensemble is composed of seven physics‐based data assimilation models for the ionosphere, ionosphere‐plasmasphere, thermosphere, high‐latitude ionosphere‐electrodynamics, and middle to low latitude ionosphere‐electrodynamics. Hence, multiple data assimilation models can be used to describe each region. A selected storm event that was reconstructed with four different data assimilation models covering the middle and low latitude ionosphere is presented and discussed. In addition, the effect of different data types on the reconstructions is shown.
Related Topics
Concepts
Data assimilation
Space weather
Ionosphere
Meteorology
Ensemble forecasting
Thermosphere
Plasmasphere
Computer science
Numerical weather prediction
Weather forecasting
Environmental science
Spacecraft
Geography
Aerospace engineering
Physics
Geophysics
Magnetosphere
Quantum mechanics
Engineering
Plasma
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1002/2015rs005888
- https://agupubs.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2015RS005888
- OA Status
- bronze
- Cited By
- 32
- References
- 32
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2472528681
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W2472528681Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.1002/2015rs005888Digital Object Identifier
- Title
-
Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)Work title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2016Year of publication
- Publication date
-
2016-06-30Full publication date if available
- Authors
-
R. W. Schunk, L. Scherliess, J. V. Eccles, L. C. Gardner, J. J. Sojka, L. Zhu, Xiaoqing Pi, A. J. Mannucci, Mark D. Butala, Brian Wilson, A. Komjáthy, Chunming Wang, G. RosenList of authors in order
- Landing page
-
https://doi.org/10.1002/2015rs005888Publisher landing page
- PDF URL
-
https://agupubs.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2015RS005888Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
bronzeOpen access status per OpenAlex
- OA URL
-
https://agupubs.onlinelibrary.wiley.com/doi/pdfdirect/10.1002/2015RS005888Direct OA link when available
- Concepts
-
Data assimilation, Space weather, Ionosphere, Meteorology, Ensemble forecasting, Thermosphere, Plasmasphere, Computer science, Numerical weather prediction, Weather forecasting, Environmental science, Spacecraft, Geography, Aerospace engineering, Physics, Geophysics, Magnetosphere, Quantum mechanics, Engineering, PlasmaTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
32Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 3, 2023: 9, 2022: 6, 2021: 2, 2020: 3Per-year citation counts (last 5 years)
- References (count)
-
32Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
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