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Author: search.filters.author.Jamjareegulgarn, PunyawiSubject: search.filters.subject.Total electron content

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    Total electron content prediction using singular spectrum analysis and autoregressive moving average approach
    (2022-01-01)
    Dabbakuti, J. R.K.Kumar
    ;
    Yarrakula, Mallika
    ;
    Panda, Sampad Kumar
    ;
    Jamjareegulgarn, Punyawi
    ;
    Haq, Mohd Anul
    Continuous monitoring of ionospheric behavior and subsequent development or improvement of models for the prediction of its parameters with consistent accuracy remains an ongoing challenge. In this sense, an integrated approach by combining the signal extraction technique Singular Spectrum Analysis (SSA) with Autoregressive Moving Average (ARMA) is presented in this work to predict the ionospheric Total Electron Content (TEC) values that are responsible for causing ionospheric delays in the trans-ionospheric signal propagation associated with satellite-based communication, navigation, and timing applications. In general, SSA is a nonparametric spectral estimation procedure that decomposes the signals into interpretable and physically significant components. The observed TEC from two Global Positioning System (GPS) stations across the low latitude Saudi Arabian region are considered during the year 2017 that falls in the descending phase of solar cycle-24. The performance of the proposed hybrid model is evaluated by comparing with the sole estimation from the ARMA model and the observed GPS–TEC dataset for two different geomagnetic conditions: a) the regular geomagnetically quiet period of 15 to 29 December, 2017 (Ap < 24 and Dst > − 30 nT) and b) the geomagnetic storm period from 7 to 9 September, 2017 (Dst min = − 142 nT). The corresponding average Precision, Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) of the proposed SSA–ARMA model predictions are 1.79 TECU, 1.23 TECU, and 13.02%. In contrast, the respective values in the exclusive ARMA model are 2.01 TECU, 1.37 TECU, 14.42% at Oman station. The corresponding values for Magna station are 0.92 TECU, 0.61 TECU, and 10.76% (SSA–ARMA) and 1.01 TECU, 0.75 TECU, and 11.33% (ARMA). The results show an improved computational efficiency with minor improvement in the TEC predictions with the proposed SSA–ARMA method compared to the sole employment of the ARMA model by disregarding the extraneous components.
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    Empirical orthogonal function modelling of total electron content over Nepal and comparison with global ionospheric models
    (2020-12-01)
    Jamjareegulgarn, Punyawi
    ;
    Ansari, Kutubuddin
    ;
    Ameer, Afsheen
    This analysis uses 3 years hourly observations of total electron content (TEC) from 5 global positioning system (GPS) station across Nepal to analyze the spatial trend. For this purpose, empirical orthogonal function modeling is used to investigate the annual and monthly variation inside the country. Empirical orthogonal function base functions and associated coefficients of TEC variability over Nepal have been studied to establish the relationship between observed and modeled TEC values. Both the observed GPS TEC values and the empirical orthogonal function modeled TEC values are compared with the global ionospheric models (global ionospheric map and international reference ionosphere) TEC values. The study shows an hourly pattern of TEC variation in which the TEC rises from dawn, reaches the highest TEC values about 40 TEC units during the peak hours of the day, then decreases at evening at the lowest diurnal values about 5 TEC units. Monthly TEC values over all sites are higher during the march and April (about 38 TEC unit), while they are lower values during December and January (about 10 TEC unit). Although the correlation coefficients between the GPS TEC values and the global modeled TEC values are higher, while it becomes highest with empirical orthogonal function modeled TEC values for both cases of hourly and monthly variations. We examined the root mean square errors between observed and modeled TEC values at each site by using tailor correlation plots and found that they are lower in case of empirical orthogonal function model. Monthly residuals between observed and empirical orthogonal function modeled TEC values are always lower as compared to other global modeled TEC values. These kinds of comparative analysis in the present work indicate that empirical orthogonal function model by using global geomagnetic activity works very well and is capable of depicting TEC variations accurately.
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    A new expression for computing the bottomside thickness parameter and comparisons with the NeQuick and IRI-2012 models during declining phase of solar cycle 23 at equatorial latitude station, Chumphon, Thailand
    (2017-07-15)
    Jamjareegulgarn, Punyawi
    ;
    Supnithi, Pornchai
    ;
    Watthanasangmechai, Kornyanat
    ;
    Yokoyama, Tatsuhiro
    ;
    Tsugawa, Takuya
    This paper proposes a new expression for computing the bottomside thickness parameter at equatorial latitude station, Chumphon (10.72°N, 99.37°E), Thailand. Its diurnal variations from 2004 to 2006 at this location are then studied. The proposed expression is derived based on two experimental data sources: FMCW ionosonde and dual-frequency GPS system, and some expressions of the NeQuick 2 model. Hence, after both the bottomside thickness parameter computed by the proposed equation, B2bot_Pro, and the bottomside shape parameter (namely, B1_Pro in this work) are computed, the bottomside electron density and the height where the bottomside electron density drops down to be 24% of the NmF2 (namely, h0.24) can be computed and shown in this work using the analytical functions of the IRI model. Moreover, the diurnal variations of the B2bot_Pro are compared with those computed from the NeQuick model, B2bot_NeQ, and the predicted B0 of the IRI-2012 model with ABT-2009 and Bil-2000 options (namely, “B0_ABT” and “B0_Bil”, respectively). The averaged, minimum, and maximum values of percentage deviations among these bottomside thickness parameters are also computed and shown in this work. Our results show that the diurnal variations of B2bot_Pro at Chumphon station have the following patterns: they start to increase during nighttime to the first peaks during pre-sunrise hours, and then decrease abruptly to their minimum values during sunrise hours. Afterward, they increase again to reach the second peaks around local noontime and fall gradually to their starting times during 20–04 LT. The diurnal variations of B2bot_Pro follow generally the same trends as those of the B2bot_NeQ and the B0_ABT, except pre-sunrise hours. The pre-sunrise peaks and sunrise collapses in both the B2bot_NeQ and the B0_ABT can be found occasionally. On the other hand, the diurnal variations in B2bot_Pro differ from those in B0_Bil due to the flattened variation in B0_Bil and the pre-sunrise peaks as well as sunrise collapses in B0_Bil disappear. The pre-sunrise peaks of the B2bot_Pro at the Chumphon station are higher than those of the B2bot_NeQ, the B0_ABT, and the observed B0 at other regions. Furthermore, the percentage deviations between the B2bot_Pro and the B0_ABT (PD_B2B0ABT) are mostly lower than 30% for all seasons of the studied years, opposite to the other percentage deviations studied in this work. The proposed B2bot_Pro parameters in this work follow a similar trend to the B2bot_NeQ and the B0_ABT, but it is not conclusive that the proposed values are equivalent to them.