Challenges in Specifying and Predicting Space Weather
Abstract Physics‐based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same d...
Saved in:
| Main Authors: | , , , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Wiley
2021-02-01
|
| Series: | Space Weather |
| Online Access: | https://doi.org/10.1029/2019SW002404 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841536393570942976 |
|---|---|
| author | R. W. Schunk L. Scherliess V. Eccles L. C. Gardner J. J. Sojka L. Zhu X. Pi A. J. Mannucci A. Komjathy C. Wang G. Rosen |
| author_facet | R. W. Schunk L. Scherliess V. Eccles L. C. Gardner J. J. Sojka L. Zhu X. Pi A. J. Mannucci A. Komjathy C. Wang G. Rosen |
| author_sort | R. W. Schunk |
| collection | DOAJ |
| description | Abstract Physics‐based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same data are assimilated. In this study, we used our Multimodel Ensemble Prediction System (MEPS) of DA models to elucidate the similarities and differences in the individual DA model reconstructions of the mid‐low latitude ionosphere when the same data are assimilated. Ensemble model averages were also obtained. For this ensemble modeling study, we selected the quiet/storm period of 16 and 17 March 2013 (equinox, solar medium). Five data assimilation models and one physics‐based model were used to produce an ensemble mean output for Total Electron Content (TEC), ionospheric peak density (NmF2), and ionospheric peak height (hmF2) for latitudes less than 60° and all longitudes. The data assimilated included ground‐based Global Positioning Satellite TEC and topside plasma densities near 800 km altitude derived from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites. Both a simple average and a weighted average of the models were used in the ensemble averaging in order to determine if there was an improvement of the ensemble averages over the individual models. |
| format | Article |
| id | doaj-art-3178cc9fc2714405aec1300abab3303d |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2021-02-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-3178cc9fc2714405aec1300abab3303d2025-01-14T16:30:32ZengWileySpace Weather1542-73902021-02-01192n/an/a10.1029/2019SW002404Challenges in Specifying and Predicting Space WeatherR. W. Schunk0L. Scherliess1V. Eccles2L. C. Gardner3J. J. Sojka4L. Zhu5X. Pi6A. J. Mannucci7A. Komjathy8C. Wang9G. Rosen10Center for Atmospheric and Space Sciences Utah State University Logan UT USACenter for Atmospheric and Space Sciences Utah State University Logan UT USASpace Dynamics Laboratory Albuquerque NM USACenter for Atmospheric and Space Sciences Utah State University Logan UT USACenter for Atmospheric and Space Sciences Utah State University Logan UT USACenter for Atmospheric and Space Sciences Utah State University Logan UT USAJet Propulsion Laboratory California Institute of Technology Pasadena CA USAJet Propulsion Laboratory California Institute of Technology Pasadena CA USAJet Propulsion Laboratory California Institute of Technology Pasadena CA USADepartment of Mathematics University of Southern California CA Los Angeles USADepartment of Mathematics University of Southern California CA Los Angeles USAAbstract Physics‐based Data Assimilation (DA) has been shown to be a powerful technique for specifying and predicting space weather. However, it is also known that different data assimilation models simulating the same geophysical event can display different space weather features even if the same data are assimilated. In this study, we used our Multimodel Ensemble Prediction System (MEPS) of DA models to elucidate the similarities and differences in the individual DA model reconstructions of the mid‐low latitude ionosphere when the same data are assimilated. Ensemble model averages were also obtained. For this ensemble modeling study, we selected the quiet/storm period of 16 and 17 March 2013 (equinox, solar medium). Five data assimilation models and one physics‐based model were used to produce an ensemble mean output for Total Electron Content (TEC), ionospheric peak density (NmF2), and ionospheric peak height (hmF2) for latitudes less than 60° and all longitudes. The data assimilated included ground‐based Global Positioning Satellite TEC and topside plasma densities near 800 km altitude derived from the COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) satellites. Both a simple average and a weighted average of the models were used in the ensemble averaging in order to determine if there was an improvement of the ensemble averages over the individual models.https://doi.org/10.1029/2019SW002404 |
| spellingShingle | R. W. Schunk L. Scherliess V. Eccles L. C. Gardner J. J. Sojka L. Zhu X. Pi A. J. Mannucci A. Komjathy C. Wang G. Rosen Challenges in Specifying and Predicting Space Weather Space Weather |
| title | Challenges in Specifying and Predicting Space Weather |
| title_full | Challenges in Specifying and Predicting Space Weather |
| title_fullStr | Challenges in Specifying and Predicting Space Weather |
| title_full_unstemmed | Challenges in Specifying and Predicting Space Weather |
| title_short | Challenges in Specifying and Predicting Space Weather |
| title_sort | challenges in specifying and predicting space weather |
| url | https://doi.org/10.1029/2019SW002404 |
| work_keys_str_mv | AT rwschunk challengesinspecifyingandpredictingspaceweather AT lscherliess challengesinspecifyingandpredictingspaceweather AT veccles challengesinspecifyingandpredictingspaceweather AT lcgardner challengesinspecifyingandpredictingspaceweather AT jjsojka challengesinspecifyingandpredictingspaceweather AT lzhu challengesinspecifyingandpredictingspaceweather AT xpi challengesinspecifyingandpredictingspaceweather AT ajmannucci challengesinspecifyingandpredictingspaceweather AT akomjathy challengesinspecifyingandpredictingspaceweather AT cwang challengesinspecifyingandpredictingspaceweather AT grosen challengesinspecifyingandpredictingspaceweather |