Supnithi, Pornchai

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Supnithi, Pornchai
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Supnithi, P.
Supnithi, Pomchai
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pornchai.su@kmitl.ac.th

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    Equatorial spread-F forecasting model with local factors using the long short-term memory network
    (2023-12-01)
    Thammavongsy, Phimmasone
    ;
    Supnithi, Pornchai
    ;
    Myint, Lin Min Min
    ;
    Hozumi, Kornyanat
    ;
    Lakanchanh, Donekeo
    The predictability of the nighttime equatorial spread-F (ESF) occurrences is essential to the ionospheric disturbance warning system. In this work, we propose ESF forecasting models using two deep learning techniques: artificial neural network (ANN) and long short-term memory (LSTM). The ANN and LSTM models are trained with the ionogram data from equinoctial months in 2008 to 2018 at Chumphon station (CPN), Thailand near the magnetic equator, where the ESF onset typically occurs, and they are tested with the ionogram data from 2019. These models are trained especially with new local input parameters such as vertical drift velocity of the F-layer height (Vd) and atmospheric gravity waves (AGW) collected at CPN station together with global parameters of solar and geomagnetic activity. We analyze the ESF forecasting models in terms of monthly probability, daily probability and occurrence, and diurnal predictions. The proposed LSTM model can achieve the 85.4% accuracy when the local parameters: Vd and AGW are utilized. The LSTM model outperforms the ANN, particularly in February, March, April, and October. The results show that the AGW parameter plays a significant role in improvements of the LSTM model during post-midnight. When compared to the IRI-2016 model, the proposed LSTM model can provide lower discrepancies from observational data. Graphical Abstract: [Figure not available: see fulltext.].
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    Total electron content observations by dense regional and worldwide international networks of GNSS
    (2018-06-01)
    Tsugawa, Takuya
    ;
    Nishioka, Michi
    ;
    Ishii, Mamoru
    ;
    Hozumi, Kornyanat
    ;
    Saito, Susumu
    Two-dimensional ionospheric total electron content (TEC) maps have been derived from ground-based Global Navigation Satellite System (GNSS) receiver networks and applied to studies of various ionospheric disturbances since the mid-1990s. For the purpose of monitoring and researching ionospheric conditions and ionospheric space weather phenomena, we have developed TEC maps of areas over Japan using the dense GNSS network, GNSS Earth Observation NETwork (GEONET), which consists of about 1300 stations and is operated by the Geospatial Information Authority of Japan (GSI). Currently, we are providing high-resolution, two-dimensional maps of absolute TEC, detrended TEC, rate of TEC change index (ROTI), and loss-of-lock on GPS signal over Japan on a real-time basis. Such high-resolution TEC maps using dense GNSS receiver networks are one of the most effective ways to observe, on a scale of several 100 km to 1000 km, ionospheric variations caused by traveling ionospheric disturbances and/or equatorial plasma bubbles, which can degrade single-frequency and differential GNSS positioning/navigation. We have collected all the available GNSS receiver data in the world to expand the TEC observation area. Currently, however, dense GNSS receiver networks are available in only limited areas, such as Japan, North America, and Europe. To expand the two-dimensional TEC observation with high resolution, we have conducted the Dense Regional and Worldwide International GNSS TEC observation (DRAWING-TEC) project, which is engaged in three activities: (1) standardizing GNSS-TEC data, (2) developing a new high-resolution TEC mapping technique, and (3) sharing the standardized TEC data or the information of GNSS receiver network. We have developed a new standardized TEC format, GNSS-TEC EXchange (GTEX), which is included in the Formatted Tables of ITU-R SG 3 Data-banks related to Recommendation ITU-R P.311. Sharing the GTEX TEC data would be easier than sharing the GPS/GNSS data among those in the international ionospheric researcher community. The DRAWING-TEC project would promote studies of medium-scale ionospheric variations and their effect on GNSS.
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    Identifying Geomagnetic Storms with Ionospheric Storm Scale for GNSS and Disaster Prevention
    (2020-03-01)
    Jamjareegulgarn, Punyawi
    ;
    Duangsuwan, Sarun
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    Supnithi, Pornchai
    ;
    Budtho, Jirapoom
    ;
    Tangtrakunphaisan, Udomsit
    This paper proposes an ionospheric storm scale (I-scale) for identifying the impact of geomagnetic or ionospheric storms in the Ionosphere for GNSS (global navigation satellite system) service and disaster prevention. The I-scale in this work is computed based on the observed foF2 at Chumphon station (10.72°N, 99.37°E) over equatorial latitude from January 2004 to July 2018. The results report that the severe geomagnetic storms, i.e., IP3 and IN3, seldom occur at Chumphon with the probabilities of 0.02% and 0.07%, respectively. The probability of quiet ionospheric condition is the maximum value of 70.73%. Meanwhile, the other I-scales sometimes occur and range from 0.60% to 13.97%. The benefits of the foF2-based I-scale are to indicate the violence level of geomagnetic storms and to announce the ionospheric irregularities in practice.
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    A comparison of neural network-based predictions of foF2 with the IRI-2012 model at conjugate points in Southeast Asia
    (2017-06-15)
    Wichaipanich, Noraset
    ;
    Hozumi, Kornyanat
    ;
    Supnithi, Pornchai
    ;
    Tsugawa, Takuya
    This paper presents the development of Neural Network (NN) model for the prediction of the F2 layer critical frequency (foF2) at three ionosonde stations near the magnetic equator of Southeast Asia. Two of these stations including Chiang Mai (18.76°N, 98.93°E, dip angle 12.7°N) and Kototabang (0.2°S, 100.3°E, dip angle 10.1°S) are at the conjugate points while Chumphon (10.72°N, 99.37°E, dip angle 3.0°N) station is near the equator. To produce the model, the feed forward network with backpropagation algorithm is applied. The NN is trained with the daily hourly values of foF2 during 2004–2012, except 2009, and the selected input parameters, which affect the foF2 variability, include day number (DN), hour number (HR), solar zenith angle (C), geographic latitude (θ), magnetic inclination (I), magnetic declination (D) and angle of meridian (M) relative to the sub-solar point, the 7-day mean of F10.7 (F10.7_7), the 81-day mean of SSN (SSN_81) and the 2-day mean of Ap (Ap_2). The foF2 data of 2009 and 2013 are then used for testing the NN model during the foF2 interpolation and extrapolation, respectively. To examine the performance of the proposed NN, the root mean square error (RMSE) of the observed foF2, the proposed NN model and the IRI-2012 (CCIR and URSI options) model are compared. In general, the results show the same trends in foF2 variation between the models (NN and IRI-2012) and the observations in that they are higher during the day and lower at night. Besides, the results demonstrate that the proposed NN model can predict the foF2 values more closely during daytime than during nighttime as supported by the lower RMSE values during daytime (0.5 ≤ RMSE ≤ 1.0 for Chumphon and Kototabang, 0.7 ≤ RMSE ≤ 1.2 at Chiang Mai) and with the highest levels during nighttime (0.8 ≤ RMSE ≤ 1.5 for Chumphon and Kototabang, 1.2 ≤ RMSE ≤ 2.0 at Chiang Mai). Furthermore, the NN model predicts the foF2 values more accurately than the IRI model at the three sites on average, as clearly seen on the yearly RMSE averages. The RMSE values of NN model are lower than those of both CCIR and URSI options, and in terms of the yearly percentage improvements, the NN model gives improvement of around 10–15% in 2009 and 10% in 2013 for Chiang Mai, 20–25% in 2009 and 5–10% in 2013 for Chumphon, and around 18–25% in 2009 and 20–30% in 2013 at Kototabang. Although the NN model predicts the foF2 values closely to the observed data and produces more accurate prediction than the IRI models, in some cases, the IRI model performs better than the NN model. Hence, there is still room for further improvement of the proposed NN model.
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    Equatorial Plasma Bubble Detection by Support Vector Machine at Chumphon Station, Thailand
    (2022-01-01)
    Thanakulketsarat, Thananphat
    ;
    Supnithi, Pornchai
    ;
    Myint, Lin Min Min
    ;
    Hozumi, Kornyanat
    Equatorial Plasma Bubble (EPB) is a phenomenon in which depletion of plasma density occurs in the ionosphere particularly in the equatorial region. It can degrade the performances of the navigation system and satellite communication. In this work, we analyze EPB based on the very-high frequency (VHF) radar images at Chumphon station, Thailand. Then an EPB detection system using the support vector machine (SVM) technique is developed, and the accuracies of the systems using different kernels: linear kernel, the polynomial kernel, the radial basic functions kernel (RBF), and the sigmoid kernel are compared. Among the different kernels, we find that the RBF kernel gives the highest accuracy in prediction at 86.67 percent.
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    Penetration of the electric fields of the geomagnetic sudden commencement over the globe as observed with the HF Doppler sounders and magnetometers
    (2021-12-01)
    Kikuchi, Takashi
    ;
    Chum, Jaroslav
    ;
    Tomizawa, Ichiro
    ;
    Hashimoto, Kumiko K.
    ;
    Hosokawa, Keisuke
    Using the HF Doppler sounders at middle and low latitudes (Prague, Czech Republic; Tucuman, Argentina; Zhongli, Republic of China, and Sugadaira, Japan), we observed the electric fields of the geomagnetic sudden commencement (SC) propagating near-instantaneously (within 10 s) over the globe. We found that the electric fields of the preliminary impulse (PI) and main impulse (MI) of the SC are in opposite direction to each other and that the PI and MI electric fields are directed from the dusk to dawn and dawn to dusk, respectively, manifesting the nature of the curl-free potential electric field. We further found that the onset and peak of the PI electric field are simultaneous on the day and nightsides (0545, 1250, 1345 MLT) within the resolution of 10 s. With the magnetometer data, we confirmed the near-instantaneous development of the ionospheric currents from high latitudes to the equator and estimated the location of the field-aligned currents that supply the ionospheric currents. The global simultaneity of the electric and magnetic fields does not require the contribution of the magnetohydrodynamic waves in the magnetosphere nor in the F-region ionosphere. The global simultaneity and day–night asymmetry of the electric fields are explained with the ionospheric electric potentials transmitted at the speed of light by the TM<inf>0</inf> mode waves in the Earth-ionosphere waveguide.[Figure not available: see fulltext.]
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    Neural Network Prediction of Receiver Bias in Ionospheric Delay Computation
    (2022-01-01)
    Thu, Phyo C.
    ;
    Supnithi, Pornchai
    ;
    Min Myint, Lin Min
    ;
    Saito, Susumu
    ;
    Saekow, Apitep
    An important measure typically used to understand ionosphere properties and disturbances is total electron content (TEC). A typical approach to calculating the ionospheric TEC is by analyzing dual-frequency GPS data. Satellite and receiver biases are the primary discrepancies in TEC computation. In this work, we develop a neural network to predict the instrumental receiver bias based on slant TEC. The minimum standard deviation method is used to calculate the receiver bias. Neural network with two hidden layers is trained with datasets and then used to predict the receiver bias. The predicted receiver bias from the proposed neural network differs from the baseline method by about 10 to 20 percent.
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    Using Principal Component Analysis of Satellite and Ground Magnetic Data to Model the Equatorial Electrojet and Derive Its Tidal Composition
    (2022-09-01)
    Soares, Gabriel
    ;
    Yamazaki, Yosuke
    ;
    Morschhauser, Achim
    ;
    Matzka, Jürgen
    ;
    Pinheiro, Katia J.
    The intensity of the equatorial electrojet (EEJ) shows temporal and spatial variability that is not yet fully understood nor accurately modeled. Atmospheric solar tides are among the main drivers of this variability but determining different tidal components and their respective time series is challenging. It requires good temporal and spatial coverage with observations, which, previously could only be achieved by accumulating data over many years. Here, we propose a new technique for modeling the EEJ based on principal component analysis (PCA) of a hybrid ground-satellite geomagnetic data set. The proposed PCA-based model (PCEEJ) represents the observed EEJ better than the climatological EEJM-2 model, especially when there is good local time separation among the satellites involved. The amplitudes of various solar tidal modes are determined from PCEEJ based tidal equation fitting. This allows to evaluate interannual and intraannual changes of solar tidal signatures in the EEJ. On average, the obtained time series of migrating and nonmigrating tides agree with the average climatology available from earlier work. A comparison of tidal signatures in the EEJ with tides derived from neutral atmosphere temperature observations show a remarkable correlation for nonmigrating tides such as DE3, DE2, DE4, and SW4. The results indicate that it is possible to obtain a meaningful EEJ spectrum related to solar tides for a relatively short time interval of 70 days.
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    Assessment of GPS-TEC with the IRI-2016 model, the IRI-Plas model and GIM-TEC during low solar activity at KMITL, Thailand
    (2019-06-01)
    Udomchaibanjerd, Jumpon
    ;
    Supnithi, Pornchai
    ;
    Phakphisut, Watid
    ;
    Hozumi, Kornyanat
    ;
    Tsugawa, Takuya
    We have assessed the ionospheric total electron content (TEC) variations which derived from dual frequency GPS receivers (GPS-TEC) at the KMITL, Thailand, called KMIT station. Then, we study TEC variations during the quiet geomagnetic condition in the low solar cycle, 2008 which is the lowest solar activity of the 24<sup>th</sup> solar cycle. The GPS-TEC is compared with the TEC prediction by the IRI-Plas model, the IRI-2016 model and the Global Ionospheric Maps (GIMs) by the International GNSS Service (IGS). The International Reference Ionosphere (IRI-2016), International Reference Ionosphere extend plasmasphere (IRI-Plas) and Global Ionosphere Maps (GIM-TEC) are model predicted total electron content (TEC). Also, the IRI-Plas has the plasmasphere extension up to 20,000 km, closed to observation TEC from the global positioning system. The GPS-TEC underestimates the IRI-Plas and GIM-TEC in all seasons whereas the IRI-2016 overestimates the GPS-TEC except the IRI-2016 is comparable to the GPS-TEC between 20.00-24.00 UT.
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    Statistical analysis of high frequency radio parameters on St. Patrick's day in Thailand
    (2017-10-19)
    Thammavongsy, Phimmasone
    ;
    Supnithi, Pornchai
    ;
    Klinngam, Somjai
    ;
    Phakphisut, Watid
    ;
    Hozumi, Kornyanat
    The ionospheric irregularities on St. Patrick's day (17 March 2015) at Chiang Mai and Chumphon stations are affected by the strongest of the 24th solar storm cycle. The ionogram data in this research is obtained from the frequency modulated/carrier waves (FM/CW) ionosonde at Chiang Mai station and near the magnetic equator, namely, Chumphon station. The parameters in this research include the critical frequency of F2 layer, the virtual height of F layer, and the maximum height of F2 layer. Overall, we found that the ionosphere layer at Chiang Mai and Chumphon stations are disturbed by the geomagnetic storm. The result indicate that the radio frequency transmission is affected by geomagnetic storm at both stations and the observation differ from the median value is specified in part of the percentage of coefficient deviation.