Articles | Volume 38, issue 6
https://doi.org/10.5194/angeo-38-1171-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/angeo-38-1171-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Regular paper
| 
10 Nov 2020
Regular paper |
| 10 Nov 2020
| 10 Nov 2020
Analysis of different propagation models for the estimation of the topside ionosphere and plasmasphere with an ensemble Kalman filter
Tatjana Gerzen
CORRESPONDING AUTHOR
Technical University Munich (TUM), Deutsches Geodätisches
Forschungsinstitut (DGFI), Arcisstraße 21, Munich, Germany
David Minkwitz
Airbus Defence and Space GmbH, Robert-Koch-Straße 1, Taufkirchen, Germany
Michael Schmidt
Technical University Munich (TUM), Deutsches Geodätisches
Forschungsinstitut (DGFI), Arcisstraße 21, Munich, Germany
Eren Erdogan
Technical University Munich (TUM), Deutsches Geodätisches
Forschungsinstitut (DGFI), Arcisstraße 21, Munich, Germany
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Tatjana Gerzen, Volker Wilken, David Minkwitz, Mainul M. Hoque, and Stefan Schlüter
Ann. Geophys., 35, 203–215, https://doi.org/10.5194/angeo-35-203-2017, https://doi.org/10.5194/angeo-35-203-2017, 2017
David Minkwitz, Karl Gerald van den Boogaart, Tatjana Gerzen, Mainul Hoque, and Manuel Hernández-Pajares
Ann. Geophys., 34, 999–1010, https://doi.org/10.5194/angeo-34-999-2016, https://doi.org/10.5194/angeo-34-999-2016, 2016
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We extend the kriging of the ionospheric electron density with slant total electron content (STEC) measurements based on a spatial covariance to kriging with a spatial–temporal covariance and develop a novel tomography approach by gradient-enhanced kriging assimilating STEC and F2 layer characteristics. The methods are cross-validated with independent measurements and point out the potential compensation for the often observed bias in the estimation of the F2 layer peak height.
T. Gerzen and D. Minkwitz
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The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The 3-D reconstruction of the ionosphere is one of the major tools to provide ionospheric corrections and to study physical processes in the ionosphere. In this paper, we introduce two reconstruction methods SMART and SMART+, and compare them to well-known reconstruction techniques ART and SART.
D. Minkwitz, K. G. van den Boogaart, T. Gerzen, and M. Hoque
Ann. Geophys., 33, 1071–1079, https://doi.org/10.5194/angeo-33-1071-2015, https://doi.org/10.5194/angeo-33-1071-2015, 2015
T. Gerzen, N. Jakowski, V. Wilken, and M. M. Hoque
Ann. Geophys., 31, 1241–1249, https://doi.org/10.5194/angeo-31-1241-2013, https://doi.org/10.5194/angeo-31-1241-2013, 2013
Andreas Goss, Michael Schmidt, Eren Erdogan, Barbara Görres, and Florian Seitz
Ann. Geophys., 37, 699–717, https://doi.org/10.5194/angeo-37-699-2019, https://doi.org/10.5194/angeo-37-699-2019, 2019
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This paper describes an approach to model VTEC solely from NRT GNSS observations by generating a multi-scale representation (MSR) based on B-splines. The unknown model parameters are estimated by means of a Kalman filter. A number of products are created which differ both in their spectral and temporal resolution. The validation studies show that the product with the highest resolution, based on NRT input data, is of higher accuracy than others used within the selected investigation time span.
Qing Liu, Michael Schmidt, Roland Pail, and Martin Willberg
Solid Earth Discuss., https://doi.org/10.5194/se-2019-60, https://doi.org/10.5194/se-2019-60, 2019
Preprint withdrawn
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Regularization is indispensable in regional gravity field modelling. In this paper, we propose two new approaches for the regularization parameter determination, which combine the L-curve method and variance component estimation (VCE). The performance of each method is studied for combining heterogeneous observations using spherical radial basis functions. The results show that our newly proposed methods are decent and stable for regularization parameter determination.
Chao Xiong, Hermann Lühr, Michael Schmidt, Mathis Bloßfeld, and Sergei Rudenko
Ann. Geophys., 36, 1141–1152, https://doi.org/10.5194/angeo-36-1141-2018, https://doi.org/10.5194/angeo-36-1141-2018, 2018
Eren Erdogan, Michael Schmidt, Florian Seitz, and Murat Durmaz
Ann. Geophys., 35, 263–277, https://doi.org/10.5194/angeo-35-263-2017, https://doi.org/10.5194/angeo-35-263-2017, 2017
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Although the number of terrestrial GNSS receivers is rapidly growing, the rather unevenly distributed observations do not allow the generation of high-resolution global ionosphere products. With the regionally enormous increase in GNSS data, the demands on near real-time products are growing very fast. Thus, a procedure for estimating the vertical total electron content based on B-spline representations and Kalman filtering was developed and validated by self-consistency check and altimetry.
Tatjana Gerzen, Volker Wilken, David Minkwitz, Mainul M. Hoque, and Stefan Schlüter
Ann. Geophys., 35, 203–215, https://doi.org/10.5194/angeo-35-203-2017, https://doi.org/10.5194/angeo-35-203-2017, 2017
David Minkwitz, Karl Gerald van den Boogaart, Tatjana Gerzen, Mainul Hoque, and Manuel Hernández-Pajares
Ann. Geophys., 34, 999–1010, https://doi.org/10.5194/angeo-34-999-2016, https://doi.org/10.5194/angeo-34-999-2016, 2016
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We extend the kriging of the ionospheric electron density with slant total electron content (STEC) measurements based on a spatial covariance to kriging with a spatial–temporal covariance and develop a novel tomography approach by gradient-enhanced kriging assimilating STEC and F2 layer characteristics. The methods are cross-validated with independent measurements and point out the potential compensation for the often observed bias in the estimation of the F2 layer peak height.
T. Gerzen and D. Minkwitz
Ann. Geophys., 34, 97–115, https://doi.org/10.5194/angeo-34-97-2016, https://doi.org/10.5194/angeo-34-97-2016, 2016
Short summary
Short summary
The accuracy and availability of satellite-based applications like GNSS positioning and remote sensing crucially depends on the knowledge of the ionospheric electron density distribution. The 3-D reconstruction of the ionosphere is one of the major tools to provide ionospheric corrections and to study physical processes in the ionosphere. In this paper, we introduce two reconstruction methods SMART and SMART+, and compare them to well-known reconstruction techniques ART and SART.
D. Minkwitz, K. G. van den Boogaart, T. Gerzen, and M. Hoque
Ann. Geophys., 33, 1071–1079, https://doi.org/10.5194/angeo-33-1071-2015, https://doi.org/10.5194/angeo-33-1071-2015, 2015
M. Limberger, W. Liang, M. Schmidt, D. Dettmering, M. Hernández-Pajares, and U. Hugentobler
Ann. Geophys., 32, 1533–1545, https://doi.org/10.5194/angeo-32-1533-2014, https://doi.org/10.5194/angeo-32-1533-2014, 2014
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The determination of ionospheric key quantities such as the maximum electron density of the F2 layer, the corresponding F2 peak height and the F2 scale height are of high relevance in 4-D ionosphere modeling to provide information on the vertical structure of the electron density distribution. This paper discusses mathematical correlations between these parameters as derived from FORMOSAT-3/COSMIC radio occultations and regionally parameterized by means of polynomial B-splines.
M. Limberger, W. Liang, M. Schmidt, D. Dettmering, and U. Hugentobler
Ann. Geophys., 31, 2215–2227, https://doi.org/10.5194/angeo-31-2215-2013, https://doi.org/10.5194/angeo-31-2215-2013, 2013
T. Gerzen, N. Jakowski, V. Wilken, and M. M. Hoque
Ann. Geophys., 31, 1241–1249, https://doi.org/10.5194/angeo-31-1241-2013, https://doi.org/10.5194/angeo-31-1241-2013, 2013
Related subject area
Subject: Earth's ionosphere & aeronomy | Keywords: Modelling and forecasting
Modeling total electron content derived from radio occultation measurements by COSMIC satellites over the African region
The very low-frequency transmitter radio wave anomalies related to the 2010 Ms 7.1 Yushu earthquake observed by the DEMETER satellite and the possible mechanism
Comparison of quiet-time ionospheric total electron content from the IRI-2016 model and from gridded and station-level GPS observations
Performance of the IRI-2016 over Santa Maria, a Brazilian low-latitude station located in the central region of the South American Magnetic Anomaly (SAMA)
High-resolution vertical total electron content maps based on multi-scale B-spline representations
Validation and application of optimal ionospheric shell height model for single-site estimation of total electron content
Extending the coverage area of regional ionosphere maps using a support vector machine algorithm
Patrick Mungufeni, Sripathi Samireddipalle, Yenca Migoya-Orué, and Yong Ha Kim
Ann. Geophys., 38, 1203–1215, https://doi.org/10.5194/angeo-38-1203-2020, https://doi.org/10.5194/angeo-38-1203-2020, 2020
Short summary
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This study developed a model of total electron content (TEC) over the African region. The TEC data were derived from radio occultation measurements done by the Constellation Observing System for Meteorology, Ionosphere, and Climate (COSMIC) satellites. Data during geomagnetically quiet time for the years 2008–2011 and 2013–2017 were binned according to local time, seasons, solar flux level, geographic longitude, and dip latitude. Cubic B splines were used to fit the data for the model.
Shufan Zhao, XuHui Shen, Zeren Zhima, and Chen Zhou
Ann. Geophys., 38, 969–981, https://doi.org/10.5194/angeo-38-969-2020, https://doi.org/10.5194/angeo-38-969-2020, 2020
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We use satellite data to analyze precursory anomalies of the western China Ms 7.1 Yushu earthquake by analyzing the signal-to-noise ratio (SNR) and using the full-wave model to illustrate a possible mechanism for how the anomalies occurred. The results show that very low-frequency (VLF) radio wave SNR in the ionosphere decreased before the Yushu earthquake. The full-wave simulation results confirm that electron density variation in the lower ionosphere will affect VLF radio signal SNR.
Gizaw Mengistu Tsidu and Mulugeta Melaku Zegeye
Ann. Geophys., 38, 725–748, https://doi.org/10.5194/angeo-38-725-2020, https://doi.org/10.5194/angeo-38-725-2020, 2020
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The performance of the IRI-2016 model in simulating GPS-TEC is assessed based on various statistical tools during two distinct solar activity periods. In particular, the categorical metrics used in the study to assess the performance of the empirical and climatological IRI-2016 model at the margins of the TEC distribution reveal remarkable model skill in simulating the observed tails of the TEC distribution, which is much better than accurately simulating the observed climatology as designed.
Juliano Moro, Jiyao Xu, Clezio Marcos Denardini, Laysa Cristina Araújo Resende, Régia Pereira Silva, Sony Su Chen, Giorgio Arlan da Silva Picanço, Liu Zhengkuan, Hui Li, Chunxiao Yan, Chi Wang, and Nelson Jorge Schuch
Ann. Geophys., 38, 457–466, https://doi.org/10.5194/angeo-38-457-2020, https://doi.org/10.5194/angeo-38-457-2020, 2020
Short summary
Short summary
The monthly averages of the F2 critical frequency (foF2), its peak height (hmF2), and the E-region critical frequency (foE) acquired by the DPS4-D installed in Santa Maria, Brazil, is compared to the International Reference Ionosphere (IRI-2016) model predictions. It is important to test the performance of the IRI over Santa Maria because it is located in the SAMA, which is a region particularly important for high-frequency (HF) ground-to-satellite navigation signals.
Andreas Goss, Michael Schmidt, Eren Erdogan, Barbara Görres, and Florian Seitz
Ann. Geophys., 37, 699–717, https://doi.org/10.5194/angeo-37-699-2019, https://doi.org/10.5194/angeo-37-699-2019, 2019
Short summary
Short summary
This paper describes an approach to model VTEC solely from NRT GNSS observations by generating a multi-scale representation (MSR) based on B-splines. The unknown model parameters are estimated by means of a Kalman filter. A number of products are created which differ both in their spectral and temporal resolution. The validation studies show that the product with the highest resolution, based on NRT input data, is of higher accuracy than others used within the selected investigation time span.
Jiaqi Zhao and Chen Zhou
Ann. Geophys., 37, 263–271, https://doi.org/10.5194/angeo-37-263-2019, https://doi.org/10.5194/angeo-37-263-2019, 2019
Mingyu Kim and Jeongrae Kim
Ann. Geophys., 37, 77–87, https://doi.org/10.5194/angeo-37-77-2019, https://doi.org/10.5194/angeo-37-77-2019, 2019
Short summary
Short summary
Spatial extrapolation of an ionosphere TEC map was carried out using a SVM learning algorithm. There has been much research on the temporal extrapolation or prediction of TEC time series, but the spatial extrapolation has rarely been attempted. Some researchers have performed simultaneous extrapolation both in time and in spatial domains, but this research covers the spatial extrapolation only by using an inner TEC map. This spatial TEC extrapolation can be useful for small countries.
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Short summary
We focus on reconstructing the topside ionosphere and plasmasphere and assimilating the space-based Global Navigation Satellite System slant total electron content (STEC) measurements with an ensemble Kalman filter (EnKF). We present methods for realizing the propagation step without a physical model. We investigate the capability of our estimations to reconstruct independent STEC and electron density measurements. We compare the EnKF approach with SMART+ and the 3D ionosphere model NeQuick.
We focus on reconstructing the topside ionosphere and plasmasphere and assimilating the...
