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Understanding the Systematic Errors of CHAMP Accelerometer-Derived Neutral Mass Density Data Using Data Assimilation

Kodikara, Timothy and Fernandez-Gomez, Isabel and Forootan, Ehsan and Tobiska, W. Kent and Borries, Claudia (2022) Understanding the Systematic Errors of CHAMP Accelerometer-Derived Neutral Mass Density Data Using Data Assimilation. 1st Workshop on Data Science for GNSS Remote Sensing, 13-15 Jun 2022, Potsdam, Germany.

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Official URL: https://www.d4g-2022.de/assets/kodikara_timothy_understanding_the_systematic_errors_of_champ.pdf

Abstract

Accelerometer-derived neutral mass density (NMD) is an important measurement of the variability in upper atmosphere and one of the widely used sources to calibrate and validate models associated with satellite orbit determination and prediction. It is a significant challenge to provide precise information about the true uncertainty of these NMD products. 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%. Our experiments demonstrate that DA significantly 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/186851/
Document Type:Conference or Workshop Item (Poster)
Title:Understanding the Systematic Errors of CHAMP Accelerometer-Derived Neutral Mass Density Data Using Data Assimilation
Authors:
AuthorsInstitution or Email of AuthorsAuthor's ORCID iD
Kodikara, TimothyTimothy.Kodikara (at) dlr.dehttps://orcid.org/0000-0003-4099-9966
Fernandez-Gomez, IsabelIsabel.FernandezGomez (at) dlr.dehttps://orcid.org/0000-0001-7623-9219
Forootan, Ehsanefo (at) plan.aau.dkhttps://orcid.org/0000-0003-3055-041X
Tobiska, W. Kentktobiska (at) spacenvironment.net Space Environment Technologies, Pacific Palisades, California, United Stateshttps://orcid.org/0000-0002-0415-8484
Borries, Claudiaclaudia.borries (at) dlr.dehttps://orcid.org/0000-0001-9948-3353
Date:13 June 2022
Refereed publication:No
Open Access:No
Gold Open Access:No
In SCOPUS:No
In ISI Web of Science:No
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:1st Workshop on Data Science for GNSS Remote Sensing
Event Location:Potsdam, Germany
Event Type:Workshop
Event Dates:13-15 Jun 2022
Organizer:https://www.d4g-2022.de/
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Earth Observation
DLR - Research theme (Project):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:28 Jun 2022 11:00
Last Modified:28 Jun 2022 11:00

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