KMITL

Permanent URI for this communityhttps://dspace.kmitl.ac.th/handle/123456789/1

Browse

Search Results

Now showing 1 - 7 of 7

Some of the metrics are blocked by your
consent settings
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.].
Some of the metrics are blocked by your
consent settings
Investigating the F2-layer peak height of IRI-2016 model at the equatorial station during the deepest solar activity for 70 years ago
(2023-01-01)
Jamjareegulgarn, Punyawi
;
Taugtragoonpaisan, Udomsit
;
Myint, Lin Min Min
;
Supnithi, Pornchai
The paper investigates the F2-layer peak height (hmF2) of IRI-2016 model at Sao Luis on the magnetic Equator in 2019. Since the deepest solar activity occurred surprisingly in year 2019 for 70 years ago, hence, the IRI-2016 model prediction should be investigated to know the anomalous ionosphere and the deviations between the observation and IRI prediction. The hmF2 is selected to be studied in this work. Our studied results show that the observed hmF2 and the three hmF2 models of IRI-2016 prediction generally show the similar variations only about 60% during this deepest solar activity and the variations of the four kinds of studied hmF2 values show the similar trends for all seasons, except June solstice. The diurnal variation of hmF2_Giro show three peaks for December solstice months and the equinoctial months, while they show four peaks amazingly in June solstice. The hmF2_SHU is the best option that can agree reasonably well to the observed hmF2 at Sao Luis, excluding the pre-sunrise hmF2 peak for all seasons and a very deep trough in June solstice.
Some of the metrics are blocked by your
consent settings
Positioning Comparison Using GIM, Klobuchar, and IRI-2016 Models During the Geomagnetic Storm in 2021
(2022-01-01)
Srisamoodkham, Worachai
;
Ansari, Kutubuddin
;
Jamjareegulgarn, Punyawi
This paper compares the positioning accuracy obtained from the GIM VTEC, the Klobuchar model, and the IRI-2016 model at Chiang Mai and DPT9 stations, Thailand, during an intense geomagnetic storm of 2021 (on May 12, 2021). The results show that the diurnal variation of the Klobuchar modeled VTECs show the same trend as that of the observed GIM VTECs with the same peaks and the maximum deviation of 22.5% at 05:00 UT. Meanwhile, the IRI2016-predicted VTECs show its peak at 07:00 UT and are not available obviously during 13:00–21:00 UT due to the impact of this intense geomagnetic storm. Most of the ionospheric delays obtained from the Klobuchar model underestimate those of the GIM VTEC, whereas they overestimate those of GIM VTEC during after midnight and pre-sunrise period. At both stations, the mean ionospheric range delays of the GIM VTEC are highest during daytime period while those of the IRI-2016 model are largest during nighttime period. The positioning errors at higher latitude (CHMA station) are larger than those at lower latitude (DPT9 station).
Some of the metrics are blocked by your
consent settings
Assessment of bottomside thickness parameters over magnetic equator and low latitudes during high solar activity of solar cycle 24
(2020-12-01)
Jamjareegulgarn, Punyawi
Bottomside thickness parameters of eight Digisonde stations over geomagnetic equator and low latitude regions have been investigated and compared with IRI model bottomside parameter during high solar activity (years 2013–2015) of the solar cycle 24. The studied years of each station rely on the GIRO data availability. The proposed B0 (B0_Pro) are computed by using the GIRO ionospheric data and the B0 expression in [16] with an average correction factor of “0.18733”. This average correction factor is derived from an average of 144 values of monthly average correction factors at eleven stations over geomagnetic equator and low latitude regions. The Results show that the seasonal variations of B0_Pro are in good agreements with those of B0_obs evidently as compared to B0_IRI at eight stations for all four seasons. For example, in the southern hemisphere, the absolute percentage distances between B0_Pro and B0_obs range from 13% to 33% with overall averages less than 26% and regional averages of 16.5%, but those between B0_IRI and B0_obs are higher. Moreover, the correlation coefficients between B0_Pro and B0_obs always are larger than 0.87 while excluding a lowest value of “0.7041”, but those between B0_IRI and B0_obs are lower. In the southern hemisphere, two remarkable features can always be reflected by B0_Pro for all studied stations. Meanwhile, in the northern hemisphere, the B0_Pro variations of each dip latitude has unique features at different locations, local times, and seasons. The inter-station differences of B0_Pro can be seen obviously in comparison with B0_IRI and described by the impacts of EEJ strength, vertical plasma drift, and PRE from local noontime to post-sunset periods. The remarkable findings from this present study may enhance the comprehension of bottomside variability and improve the IRI predictability in the future.
Some of the metrics are blocked by your
consent settings
A New Method for Computing Ionogram-Based TEC Based on Digisonde data for Disaster Prevention
(2020-03-01)
Jamjareegulgarn, Punyawi
;
Duangsuwan, Sarun
;
Supnithi, Pornchai
;
Srisamoodkham, Worachai
This paper presents a new approach for calculating the ionogram-based total electron content so as to be applied alternatively for alarming and preventing the disasters, for example, earthquake, tsunami or other space objectives. The proposed ITEC is estimated using the analytical expression of NeQuick model, the autoscaled Digisonde data, and a new variable "m" of 1. The results are show that 1) the proposed B0 is close to the B0-obs of Digisonde compared to the B0-IRI and the B2bot of the NeQuick model, 2) the diurnal variation of B0-Pro is the same as that of B0-obs compared to those of B0-IRI and B2bot, 3) the proposed ITEC is also close to the ITEC of Digisonde and TEC-iri, excluding the observed GPS TEC, and 4) all of the studied TEC values behave similar diurnal variations. Since the proposed ITEC is based on the analytical functions, the improvement of TEC-B0-Pro can be conducted reliably in order to close to the GPS TEC possibly and apply it optionally to correct the positioning errors for GNSS and aviation systems.
Some of the metrics are blocked by your
consent settings
Improving the modeling of bottomside thickness parameters over midlatitudes and high latitudes
(2020-02-01)
Jamjareegulgarn, Punyawi
;
Supnithi, Pornchai
;
Kenpankho, Prasert
;
Wichaipanich, Noraset
;
Nayak, Chinmaya
This paper investigates bottomside thickness parameters at Digisonde stations over midlatitude and high latitude regions, and compares the diurnal, seasonal, and solar activity variations in 2014 and 2009. The geographic latitudes of high latitude considered in this work are located beyond ±60° and those of midlatitude are located between ±40° and ±60°. The IRI-modeled B0 with ABT-2009 option (B0_IRI) are also examined and compared with four kinds of the B0 values, i.e., the observed B0 (B0_obs) from GIRO, the computed B0 following to Jamjareegulgarn et al. (2017a) (B0_old), the calculated B0 with a correction factor regarding to Jamjareegulgarn et al. (2017b) (B0_new), and the B0 with an average correction factor (B0_new_c_av). The average correction factors are proposed additionally in this work so as to assist occasionally the experimental B0 nonexistence of Digisonde which are equal to 0.2658 and 0.2058 for midlatitudes and high latitudes, respectively. Results show that the diurnal variations of B0_new and B0_new_c_av are in a good agreement with those of B0_obs evidently compared with those of B0_IRI and B0_old at every station during the three seasons over high and middle latitudes. During the three seasons, the diurnal variations of B0_new_c_av show similar trends and are close to one another with the B0_obs and the B0_new with small deviations. The differences between the B0obs and the B0_new_c_av also show similar trends and are close to one another with those between the B0obs and the B0_new. In contrast, the B0_IRI with ABT-2009 option seems to predict the B0 values poorly during the three seasons at high latitudes and some seasons at midlatitudes. The proposed B0_new is useful for computing approximately the observed B0 and the ionogram-based total electron content (ITEC) of Digisonde, and the plasma scale height over midlatitudes and high latitudes.
Some of the metrics are blocked by your
consent settings
Spread-F prediction model for the equatorial Chumphon station, Thailand
(2020-01-01)
Thammavongsy, P.
;
Supnithi, P.
;
Phakphisut, W.
;
Hozumi, K.
;
Tsugawa, T.
This work proposes a range spread-F (RSF) prediction model using the neural network (NN) over the equatorial Chumphon (CPN) region in Thailand. The RSF model is constructed by using five input spaces including the diurnal variations, seasonal variations, geographic latitude, solar flux index (F10.7), and magnetic index (A<inf>p</inf>). The RSF NN model is trained with three years of RSF data during 2013 to 2015 from Chumphon (CPN) station (Latitude = 10.7°N, Longitude = 99.4°E) and the performance of the proposed RSF NN model is validated using the dataset of 2016. As a result, the RSF NN model achieves 98.3% accuracy of all correct predictions even with the limited available data. The results show that the proposed NN model yields a lower RSF probability than the actual observation by about 7.3%, but the overestimation of the proposed NN model is 2.5% in both the equinoxes and solstices. In addition, we discover that the IRI-2016 model mostly overestimates the RSF probability when compared with the actual observation for all seasons in 2016, particularly, in equinoctial months over Chumphon station.

KMITL

Browse

Filters

Settings

Sort By

Results per page

Search Results