Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers
Abstract During geomagnetic storms, the capabilities of current climate models in predicting ionospheric behavior are notably limited. A data assimilation tool, Estimating Model Parameters Reverse Engineering (EMPIRE), implements a Kalman filter to ingest electric density rate correcting the backgro...
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| Format: | Article |
| Language: | English |
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Wiley
2024-09-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2024SW003933 |
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| author | Jiahui Hu Sarah McDonald Alex Chartier Aurora López Rubio Seebany Datta‐Barua |
| author_facet | Jiahui Hu Sarah McDonald Alex Chartier Aurora López Rubio Seebany Datta‐Barua |
| author_sort | Jiahui Hu |
| collection | DOAJ |
| description | Abstract During geomagnetic storms, the capabilities of current climate models in predicting ionospheric behavior are notably limited. A data assimilation tool, Estimating Model Parameters Reverse Engineering (EMPIRE), implements a Kalman filter to ingest electric density rate correcting the background electric potential and neutral wind. For the baseline setup, or case (1), EMPIRE ingests electron density global map output from the Ionospheric Data Assimilation 4‐Dimensional (IDA4D) algorithm. In this work, a new augmentation method is evaluated in which ion drift measurements are also assimilated into EMPIRE. The ion drift measurements used in the new augmentation method are obtained from Super Dual Auroral Radar Network (SuperDARN) sites in the mid‐to‐high latitude region of the northern hemisphere. Cases (2) and (3) are set up for evaluating the impacts from ingesting different types of observations: SuperDARN fit and grid data, respectively. Six independent data sources are used as validation data sets to compare outcomes with or without ingesting ion drifts. One is the vector ion velocities derived from the Millstone Hill Incoherent Scatter Radar (MHISR) and a second is the vertical drift from Arecibo site. The other four are SuperDARN ion velocity grid data from Saskatoon, Kapuskasing, Christmas Valley West, and Hokkaido East. Results show improvements in performance at mid‐latitudes by augmenting electron density rates with 3D spatially distributed line‐of‐sight ion drift measurements, with negligible improvements to low and high latitude estimations. The lack of improvement at high‐latitudes is attributed to the increase in EMPIRE ion drift error poleward of 60° magnetic. |
| format | Article |
| id | doaj-art-277f37922f134f58ba26407f92a3510f |
| institution | Kabale University |
| issn | 1542-7390 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-277f37922f134f58ba26407f92a3510f2025-01-14T16:35:30ZengWileySpace Weather1542-73902024-09-01229n/an/a10.1029/2024SW003933Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma DriversJiahui Hu0Sarah McDonald1Alex Chartier2Aurora López Rubio3Seebany Datta‐Barua4Illinois Institute of Technology Chicago IL USANaval Research Laboratory Washington DC USAJohns Hopkins University Applied Physics Laboratory Laurel MD USAIllinois Institute of Technology Chicago IL USAIllinois Institute of Technology Chicago IL USAAbstract During geomagnetic storms, the capabilities of current climate models in predicting ionospheric behavior are notably limited. A data assimilation tool, Estimating Model Parameters Reverse Engineering (EMPIRE), implements a Kalman filter to ingest electric density rate correcting the background electric potential and neutral wind. For the baseline setup, or case (1), EMPIRE ingests electron density global map output from the Ionospheric Data Assimilation 4‐Dimensional (IDA4D) algorithm. In this work, a new augmentation method is evaluated in which ion drift measurements are also assimilated into EMPIRE. The ion drift measurements used in the new augmentation method are obtained from Super Dual Auroral Radar Network (SuperDARN) sites in the mid‐to‐high latitude region of the northern hemisphere. Cases (2) and (3) are set up for evaluating the impacts from ingesting different types of observations: SuperDARN fit and grid data, respectively. Six independent data sources are used as validation data sets to compare outcomes with or without ingesting ion drifts. One is the vector ion velocities derived from the Millstone Hill Incoherent Scatter Radar (MHISR) and a second is the vertical drift from Arecibo site. The other four are SuperDARN ion velocity grid data from Saskatoon, Kapuskasing, Christmas Valley West, and Hokkaido East. Results show improvements in performance at mid‐latitudes by augmenting electron density rates with 3D spatially distributed line‐of‐sight ion drift measurements, with negligible improvements to low and high latitude estimations. The lack of improvement at high‐latitudes is attributed to the increase in EMPIRE ion drift error poleward of 60° magnetic.https://doi.org/10.1029/2024SW003933data assimilationradar technologyspace weatherKalman filter |
| spellingShingle | Jiahui Hu Sarah McDonald Alex Chartier Aurora López Rubio Seebany Datta‐Barua Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers Space Weather data assimilation radar technology space weather Kalman filter |
| title | Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers |
| title_full | Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers |
| title_fullStr | Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers |
| title_full_unstemmed | Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers |
| title_short | Data Assimilation of Ion Drift Measurements for Estimation of Ionospheric Plasma Drivers |
| title_sort | data assimilation of ion drift measurements for estimation of ionospheric plasma drivers |
| topic | data assimilation radar technology space weather Kalman filter |
| url | https://doi.org/10.1029/2024SW003933 |
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