ANCHOR: Global Parametrized Ionospheric Data Assimilation
Abstract ANCHOR is a novel assimilative model developed at the U.S. Naval Research Laboratory, which was designed for rapid assimilative runs. ANCHOR uses recently developed PyIRI model for the background and for the formation of the background covariance matrix. It only takes a few minutes for ANCH...
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| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2024-07-01
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| Series: | Space Weather |
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| Online Access: | https://doi.org/10.1029/2023SW003803 |
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| author | Victoriya V. Forsythe Sarah E. McDonald Kenneth F. Dymond Bruce A. Fritz Angeline G. Burrell Katherine A. Zawdie Douglas P. Drob Meghan R. Burleigh Dustin A. Hickey Christopher A. Metzler David D. Kuhl Daniel Hodyss Joe H. Hughes |
| author_facet | Victoriya V. Forsythe Sarah E. McDonald Kenneth F. Dymond Bruce A. Fritz Angeline G. Burrell Katherine A. Zawdie Douglas P. Drob Meghan R. Burleigh Dustin A. Hickey Christopher A. Metzler David D. Kuhl Daniel Hodyss Joe H. Hughes |
| author_sort | Victoriya V. Forsythe |
| collection | DOAJ |
| description | Abstract ANCHOR is a novel assimilative model developed at the U.S. Naval Research Laboratory, which was designed for rapid assimilative runs. ANCHOR uses recently developed PyIRI model for the background and for the formation of the background covariance matrix. It only takes a few minutes for ANCHOR to complete the data assimilation (DA) for one day, including data pre‐processing and model set up. ANCHOR extracts ionospheric parameters from radio occultation (RO) and ionosonde data using PyIRI formalism and assimilates them as point measurements into maps of the background parameters using a Kalman Filter approach. This paper introduces the ANCHOR algorithm, discusses its coordinate system and background, explains the background covariance formation, discusses the extraction of the ionospheric parameters from the data and the assimilation process, and, finally, shows the results of the observing system simulation experiment with synthetic data simulated using the SAMI3 model. ANCHOR reduces the root mean square errors in the analysis by more than a half for all of the ionospheric parameters in comparison to the background. Finally, this paper discusses advantages and limitations of the parametrized ionospheric DA, highlighting the avenues for its future improvement. |
| format | Article |
| id | doaj-art-df1592a9f44743c1a5502b7dc3da17bd |
| institution | DOAJ |
| issn | 1542-7390 |
| language | English |
| publishDate | 2024-07-01 |
| publisher | Wiley |
| record_format | Article |
| series | Space Weather |
| spelling | doaj-art-df1592a9f44743c1a5502b7dc3da17bd2025-08-20T03:03:29ZengWileySpace Weather1542-73902024-07-01227n/an/a10.1029/2023SW003803ANCHOR: Global Parametrized Ionospheric Data AssimilationVictoriya V. Forsythe0Sarah E. McDonald1Kenneth F. Dymond2Bruce A. Fritz3Angeline G. Burrell4Katherine A. Zawdie5Douglas P. Drob6Meghan R. Burleigh7Dustin A. Hickey8Christopher A. Metzler9David D. Kuhl10Daniel Hodyss11Joe H. Hughes12U.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAU.S. Naval Research Laboratory Washington DC USAOrion Space Solutions Louisville CO USAAbstract ANCHOR is a novel assimilative model developed at the U.S. Naval Research Laboratory, which was designed for rapid assimilative runs. ANCHOR uses recently developed PyIRI model for the background and for the formation of the background covariance matrix. It only takes a few minutes for ANCHOR to complete the data assimilation (DA) for one day, including data pre‐processing and model set up. ANCHOR extracts ionospheric parameters from radio occultation (RO) and ionosonde data using PyIRI formalism and assimilates them as point measurements into maps of the background parameters using a Kalman Filter approach. This paper introduces the ANCHOR algorithm, discusses its coordinate system and background, explains the background covariance formation, discusses the extraction of the ionospheric parameters from the data and the assimilation process, and, finally, shows the results of the observing system simulation experiment with synthetic data simulated using the SAMI3 model. ANCHOR reduces the root mean square errors in the analysis by more than a half for all of the ionospheric parameters in comparison to the background. Finally, this paper discusses advantages and limitations of the parametrized ionospheric DA, highlighting the avenues for its future improvement.https://doi.org/10.1029/2023SW003803ionospheric data assimilationKalman FilterparametrizationPyIRIANCHORionosphere |
| spellingShingle | Victoriya V. Forsythe Sarah E. McDonald Kenneth F. Dymond Bruce A. Fritz Angeline G. Burrell Katherine A. Zawdie Douglas P. Drob Meghan R. Burleigh Dustin A. Hickey Christopher A. Metzler David D. Kuhl Daniel Hodyss Joe H. Hughes ANCHOR: Global Parametrized Ionospheric Data Assimilation Space Weather ionospheric data assimilation Kalman Filter parametrization PyIRI ANCHOR ionosphere |
| title | ANCHOR: Global Parametrized Ionospheric Data Assimilation |
| title_full | ANCHOR: Global Parametrized Ionospheric Data Assimilation |
| title_fullStr | ANCHOR: Global Parametrized Ionospheric Data Assimilation |
| title_full_unstemmed | ANCHOR: Global Parametrized Ionospheric Data Assimilation |
| title_short | ANCHOR: Global Parametrized Ionospheric Data Assimilation |
| title_sort | anchor global parametrized ionospheric data assimilation |
| topic | ionospheric data assimilation Kalman Filter parametrization PyIRI ANCHOR ionosphere |
| url | https://doi.org/10.1029/2023SW003803 |
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