Modeling of GPS total electron content over the African low-latitude region using empirical orthogonal functions

Andima, Geoffrey; Amabayo, Emirant B.; Jurua, Edward; Cilliers, Pierre J.

doi:10.5194/angeo-37-65-2019

Cited by 15 publications

(8 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…We adopted the method of singular value decomposition (SVD) to determine the EOF modes that explain most of the variability in the SH_set data [25]. The SH_set data matrix M was decomposed into left basis vectors U and right basis vectors V, and S is a matrix of singular values of M as M = USV T (8)…”

Section: Eof Methodsmentioning

confidence: 99%

“…The results show that the model can reproduce TEC better and reproduce well the dependence of mid-latitude trough on local time, season, solar cycle and geomagnetic activity. Andima, et al [25] established a TEC model for low-latitudes regions in Africa based on EOF and least square regression analysis. The results show that the error of EOF-based models in predicting Malindi's TEC is less than IRI-2016.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

Liu

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

Based on the ERA-5 meteorological data from 2015 to 2019, we establish the global tropospheric delay spherical harmonic (SH) coefficients set called the SH_set and develop the global tropospheric delay SH coefficients empirical model called EGtrop using the empirical orthogonal function (EOF) method and periodic functions. We apply tropospheric delay derived from IGS stations not involved in modeling as reference data for validating the dataset, and statistical results indicate that the global mean Bias of the SH_set is 0.08 cm, while the average global root mean square error (RMSE) is 2.61 cm, which meets the requirements of the tropospheric delay model applied in the wide-area augmentation system (WAAS), indicating the feasibility of the product strategy. The tropospheric delay calculated with global sounding station and tropospheric delay products of IGS stations in 2020 are employed to validate the new product model. It is verified that the EGtrop model has high accuracy with Bias and RMSE of −0.25 cm and 3.79 cm, respectively, with respect to the sounding station, and with Bias and RMSE of 0.42 cm and 3.65 cm, respectively, with respect to IGS products. The EGtrop model is applicable not only at the global scale but also at the regional scale and exhibits the advantage of local enhancement.

show abstract

Section: Eof Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

Liu

et al. 2021

Remote Sensing

View full text Add to dashboard Cite

show abstract

“…Andima et al [60] analyzed TEC trends for Malindi, Kenya (3.0° S, 40.2° E) for the period 1999-2017, and also for the African low latitude region, using GPS-derived TEC. Zonal bands of alternating stronger and weaker TEC trends are shown approximately parallel to the magnetic dipole equator.…”

Section: Ionosphere Total Electron Content (Tec)mentioning

confidence: 99%

Review of Long-Term Trends in the Equatorial Ionosphere Due the Geomagnetic Field Secular Variations and Its Relevance to Space Weather

et al. 2021

View full text Add to dashboard Cite

The Earth’s ionosphere presents long-term trends that have been of interest since a pioneering study in 1989 suggesting that greenhouse gases increasing due to anthropogenic activity will produce not only a troposphere global warming, but a cooling in the upper atmosphere as well. Since then, long-term changes in the upper atmosphere, and particularly in the ionosphere, have become a significant topic in global change studies with many results already published. There are also other ionospheric long-term change forcings of natural origin, such as the Earth’s magnetic field secular variation with very special characteristics at equatorial and low latitudes. The ionosphere, as a part of the space weather environment, plays a crucial role to the point that it could certainly be said that space weather cannot be understood without reference to it. In this work, theoretical and experimental results on equatorial and low-latitude ionospheric trends linked to the geomagnetic field secular variation are reviewed and analyzed. Controversies and gaps in existing knowledge are identified together with important areas for future study. These trends, although weak when compared to other ionospheric variations, are steady and may become significant in the future and important even now for long-term space weather forecasts.

show abstract

“…Given the predictability of the diurnal variation of TEC, deficiencies have varied with local time (LT), season, and latitude. After the release of IRI-2016 as the recent version, its performance in predicting TEC has attracted the attention of many researchers (Atici, 2018;Sharma et al, 2018;Tariku, 2018;Jiang et al, 2019). Most existing studies for ionospheric models aimed at the low and middle latitudes.…”

Section: Introductionmentioning

confidence: 99%

Global total electron content prediction performance assessment of the IRI-2016 model based on empirical orthogonal function decomposition

Zhou

et al. 2020

Ann. Geophys.

View full text Add to dashboard Cite

Abstract. In this study, the empirical orthogonal function (EOF) decomposition technique was utilized to analyze the similarities and differences of the spatiotemporal characteristics between the total electron content (TEC) of the International GNSS Service global ionospheric map (GIM) and that derived from the International Reference Ionosphere 2016 (IRI-2016) model in 2013. Results showed that the main spatial patterns and time-varying features of the data set have good consistency. The following four main spatiotemporal variation features can be extracted from both data sets through EOF decomposition: the variation with the geomagnetic latitude reflecting the daily averaged solar forcing, the diurnal and semidiurnal periodic changes with longitude due to local time, and the interhemispheric asymmetry caused by the annual variation of the inclination angle of the Earth's orbit. The differences between the spatial patterns represented by the EOF base functions of IRI-2016 and GIM TECs were analyzed by extracting the same time-varying coefficients. The deviations of the interhemispheric asymmetry component between the two data sets showed roughly equal values throughout the Southern or Northern Hemisphere, whereas those of the other spatial modes were mainly concentrated on the equatorial region. The differences of the time-varying characteristics between the IRI-2016 and GIM TECs were also compared by extracting the same EOF base functions. Although the EOF coefficients of the two data sets presented consistent seasonal variations, the magnitude of IRI-2016 TEC changes over time was less than that of GIM TEC. The diurnal variation of the daily averaged solar forcing component and the annual variation of the interhemispheric asymmetry component exhibited relatively large deviations between the two data sets. Considering the variance contribution of the different EOF components and their average relative deviations, both analyses showed that the daily averaged solar forcing and interhemispheric asymmetry components were the main factors for the deviation between the IRI-2016 and GIM TECs.

show abstract

Modeling of GPS total electron content over the African low-latitude region using empirical orthogonal functions

Cited by 15 publications

References 36 publications

Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

Empirical Orthogonal Function Analysis and Modeling of Global Tropospheric Delay Spherical Harmonic Coefficients

Review of Long-Term Trends in the Equatorial Ionosphere Due the Geomagnetic Field Secular Variations and Its Relevance to Space Weather

Global total electron content prediction performance assessment of the IRI-2016 model based on empirical orthogonal function decomposition

Contact Info

Product

Resources

About