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Using Data Assimilation to Understand the Systematic Errors in CHAMP Accelerometer-Derived Neutral Mass Density Data

Kodikara, Timothy and Fernandez-Gomez, Isabel and Forootan, Ehsan and Tobiska, W. Kent and Borries, Claudia (2021) Using Data Assimilation to Understand the Systematic Errors in CHAMP Accelerometer-Derived Neutral Mass Density Data. Earth and Space Science Open Archive. AGU 2021 Fall Meeting, 13-17 Dec 2021, Virtual. doi: 10.1002/essoar.10509636.2.

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Official URL: https://www.essoar.org/doi/10.1002/essoar.10509636.2

Abstract

Accelerometer-derived neutral mass density (NMD) is an important measurement of the variability in upper atmosphere and one of the widely used measurements to calibrate and validate models used for satellite orbit determination and prediction. Providing precise estimates of the true uncertainty of these NMD products is a challenging task but essential for the space weather and geodetic communities. Using multiple data assimilation (DA) experiments and robust statistical techniques, we investigate the uncertainty distribution of three different accelerometer-derived NMD products from the CHAMP satellite mission. Here, in three different DA experiments, we use an ensemble Kalman filter to drive a physics-based model with CHAMP in-situ electron density and temperature data as well as neutral wind estimates from an empirical model. Using a multi-model ensemble comprised of both physical and empirical models, we characterize the error variances among the different NMD products. Our results indicate considerable differences among the CHAMP data sets and also show a pronounced latitudinal dependency for the estimated error distributions. On average, the error estimates for NMD vary in the range 6.5–15.6% of the signal. Our experiments demonstrate that DA considerably enhances the capability of the physical model. We note that the generic strategies applied here may be useful and applicable to other space missions spanning over longer time periods.

Item URL in elib:https://elib.dlr.de/143401/
Document Type:Conference or Workshop Item (Speech)
Title:Using Data Assimilation to Understand the Systematic Errors in CHAMP Accelerometer-Derived Neutral Mass Density Data
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iDORCID Put Code
Kodikara, TimothyUNSPECIFIEDhttps://orcid.org/0000-0003-4099-9966UNSPECIFIED
Fernandez-Gomez, IsabelUNSPECIFIEDhttps://orcid.org/0000-0001-7623-9219UNSPECIFIED
Forootan, EhsanUNSPECIFIEDhttps://orcid.org/0000-0003-3055-041XUNSPECIFIED
Tobiska, W. KentUNSPECIFIEDhttps://orcid.org/0000-0002-0415-8484UNSPECIFIED
Borries, ClaudiaUNSPECIFIEDhttps://orcid.org/0000-0001-9948-3353UNSPECIFIED
Date:17 December 2021
Refereed publication:No
Open Access:Yes
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
DOI:10.1002/essoar.10509636.2
Publisher:Earth and Space Science Open Archive
Status:Published
Keywords:thermosphere accelerometer-derived neutral mass density, ionosphere electron/plasma density and temperature, neutral winds, data assimilation, CHAMP, TIE-GCM, HASDM, JB2008, NRLMSIS, uncertainty estimation
Event Title:AGU 2021 Fall Meeting
Event Location:Virtual
Event Type:international Conference
Event Dates:13-17 Dec 2021
Organizer:AGU [https://www.agu.org/Fall-Meeting]
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Communication, Navigation, Quantum Technology
DLR - Research area:Raumfahrt
DLR - Program:R KNQ - Communication, Navigation, Quantum Technology
DLR - Research theme (Project):R - Ionosphere, R - Solar-Terrestrial Physics SO
Location: Neustrelitz
Institutes and Institutions:Institute for Solar-Terrestrial Physics > Solar-Terrestrial Coupling Processes
Deposited By: Kodikara, Dr Timothy
Deposited On:24 Feb 2022 09:31
Last Modified:24 Feb 2022 09:31

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