Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)-Reference-Cited by-同舟云学术

Space weather forecasting with a Multimodel Ensemble Prediction System (MEPS)

Published:2016-07 Issue:7 Volume:51 Page:1157-1165
ISSN:0048-6604
Container-title:Radio Science
language:en
Short-container-title:Radio Sci.

Author:

Schunk R. W.¹,Scherliess L.¹,Eccles V.¹,Gardner L. C.¹,Sojka J. J.¹,Zhu L.¹,Pi X.²,Mannucci A. J.²^ORCID,Butala M.²,Wilson B. D.²,Komjathy A.²,Wang C.³,Rosen G.³

Affiliation:

1. Center for Atmospheric and Space Sciences Utah State University Logan Utah USA

2. Jet Propulsion Laboratory California Institute of Technology Pasadena California USA

3. Department of Mathematics University of Southern California Los Angeles California USA

Funder

NSF

Publisher

American Geophysical Union (AGU)

Subject

Electrical and Electronic Engineering,General Earth and Planetary Sciences,Condensed Matter Physics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/2015RS005888

Reference36 articles.

1. Gardner L. C. R. W.Schunk L.Scherliess L.Zhu andJ. J.Sojka(2014a) Ionospheric reconstruction for various solar seasonal and geomagnetic conditions obtained from the Global Assimilation of Ionospheric Measurements—Gauss Markov (GAIM‐GM) model Proceedings of the Institute of Navigation International Technical Meeting San Diego Calif.

2. Global Assimilation of Ionospheric Measurements-Gauss Markov model: Improved specifications with multiple data types

3. COSMIC GPS Ionospheric Sensing and Space Weather

4. Data assimilation of ground GPS total electron content into a physics-based ionospheric model by use of the Kalman filter

5. Duration of an ionospheric data assimilation initialization of a coupled thermosphere-ionosphere model

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