Ionospheric effects of St. Patrick's storm over Asian Russia: 17–19 March 2015

Золотухина, Н. А.; Полех, Н. М.; Kurkin, V. I.; Rogov, D. D.; Романова, Елена; Челпанов, Максим

doi:10.1002/2016ja023180

Cited by 33 publications

(23 citation statements)

References 63 publications

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“…Further in Figure , despite the absence of ionospheric reflections/recordings (particularly between ~00:00 and 06:00 UT, 18 March 2018) at all ionosonde stations, IDA4D offers a more reasonable interpolation of the NmF2 values. During this storm, most midlatitude ionosonde stations reported recordings of sporadic E (e.g., Zolotukhina et al, ). Therefore, the absence of ionosonde measurements could have been due to absorption of ionosonde HF radio signals in the lower ionosphere.…”

Section: Ida4d During Geomagnetic Storm Daysmentioning

confidence: 99%

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

et al. 2019

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For the purpose of building a regional (bound 20–60°N in latitude and 110–160°E in longitude) ionospheric nowcast model, we investigated the performance of IDA4D (Ionospheric Data Assimilation Four‐Dimension) technique considering International Reference Ionosphere model as the background. The data utilized in assimilation were slant total electron content (STEC) from 27 ground GPS (Global Positioning System) receiver stations and NmF2 (ionospheric F2 peak density) from five ionosondes and COSMIC (Constellation Observing System for Meteorology, Ionosphere, and Climate) Data Analysis Archive Center. The period analyzed covered both geomagnetic quiet and disturbed days (15–18 March 2015). Assimilations were run under the following data combinations (cases): (1) GPS‐STEC's only; (2) GPS‐STEC's and NmF2's from five ionosondes; (3) only NmF2's from five ionosondes; and (4) GPS‐STEC's and NmF2's from both five ionosondes and COSMIC. Results showed that under case 1 the root‐mean‐square error (RMSE) in STEC reduced by 44% over the background International Reference Ionosphere values and on averaged over all ionosonde stations in the analysis RMSE values of foF2 (F2 layer critical frequency) reduced by 21%. Furthermore, foF2 RMSE values under Case 2 were 36% smaller than those under Case 1. Under Case 4, IDA4D performance improved even further in areas not covered by GPS and ionosonde measurements. Therefore, IDA4D is a potential candidate for regional ionosphere modeling that exhibits improved performance with assimilation of different data types.

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Section: Ida4d During Geomagnetic Storm Daysmentioning

confidence: 99%

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

et al. 2019

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“…As shown in Figure , the first Lyapunov exponents are corresponding for the quiet and disturbed periods of different years. For example, solar activity during 2008 was very low and geomagnetic field activity was quiet most of the time, while these variations clearly illustrate the typical F region response to severe geomagnetic storms with an initial positive phase during the daytime on 17 March 2015 followed by an extended negative phase persisting in both the daytime and night‐time ionosphere (Zolotukhina, ).…”

Section: Resultsmentioning

confidence: 97%

“…The geomagnetic storm began around 0500 UT on 17, and the maximum Dst index reached −223 nT. It consisted of short initial phase, two‐step main phase, and two‐step recovery phase (Zolotukhina et al, ) and was over on 25 March. Before the storm, there were 8 days of low and moderate geomagnetic activity.…”

Section: Resultsmentioning

confidence: 99%

“…One can note that it is not necessarily mean that all the noise has been eliminated from the original observation data set. Quiet days which mentioned above have low Dst values while storm periods have high Dst values during 14-20 March 2015, especially the maximum Dst index reach −223 nT in 17 March 2015 (Zolotukhina et al, 2017). The same process can be used for different observation periods and determined sampling intervals.…”

Section: Analysis For Measured Time Seriesmentioning

confidence: 99%

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An Adaptive Forecasting Method for Ionospheric Critical Frequency of F2 Layer

Wang

Feng

2020

Radio Science

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To achieve further improvements in quantitative predictability, a chaos-based adaptive forecasting method for the critical frequency of the F2 layer (f o F 2 ) is proposed for the development of an ionospheric forecasting technique for one hour ahead. This method has three new characteristics. (1) It is based on Volterra filters and it has a simplified structure with easy implementation.(2) Based only on past measured data, it can forecast f o F 2 values without the requirement for past or forecast values of any solar and geomagnetic indices. (3) It can achieve high forecast accuracy with a small training dataset of 27 days (one solar rotation period). Diurnal, seasonal, and annual comparisons of measured and forecasted f o F 2 values are presented to illustrate the applicability and suitability of the proposed method. Statistical results reveal that the f o F 2 values calculated using the proposed model are consistent with the trend of measurements irrespective of whether geomagnetic conditions are quiet or disturbed. The average RMSE and RRMSE values were 0.86 MHz and 17.36%, respectively, when using measured data from periods of past 27 days during 2008-2015. The proposed method has potential to forecast other ionospheric characteristic parameters, and that it could achieve satisfactory regional or global 1-hr forecasting if combined with a spatial reconstruction technique. Plain Language SummaryThe critical frequency of F2 layer of ionosphere (f o F 2 ) is a very important characteristic parameter in various civil and military applications. To achieve further improvements in quantitative predictability, a chaos-based adaptive forecasting method for f o F 2 is proposed for the development of an ionospheric forecasting technique for 1 hr ahead. This method has three advantages: simplified structure with easy implementation, high forecast accuracy with a small training dataset, and forecast without the requirement for any solar and geomagnetic indices. Comparisons between the measured and forecasting values of f o F 2 have shown the usability and appropriateness of the proposed method. Statistical results reveal that the f o F 2 calculated by the proposed model is consistent with the trend of the measurements whenever quiet and disturbed geomagnetic conditions. The average RMSE and RRMSE are 0.86 MHz and 17.36% using the past 27 days measured data during the year of 2008-2015. Moreover, the analysis results have proved the proposed method has the potential to forecasting any other ionospheric characteristic parameters and can achieve 1-hr forecasting for global by combining spatial reconstruction technique.

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“…Over the past two decades, studies of ionospheric disturbances and its monitoring have caught the attention of the scientific community (Pi et al, 1997;Afraimovich et al, 1998;Tsugawa et al, 2004;Hernández-Pajares et al, 2006;Ding et al, 2007;Trichtchenko et al, 2007;Bergeot et al, 2011;Tang et al, 2016;Yao et al, 2017;Zolotukhina at al., 2017). Stankov et al (2006) presented several case and statistical studies of ionospheric storm, which were clearly showing the generation and propagation of ionospheric disturbances.…”

Section: Introductionmentioning

confidence: 99%

Study of ionospheric disturbances over the China mid- and low-latitude region with GPS observations

Ning

Tanida

2018

Ann. Geophys.

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Abstract. Ionospheric disturbances constitute the main restriction factor for precise positioning techniques based on global positioning system (GPS) measurements. Simultaneously, GPS observations are widely used to determine ionospheric disturbances with total electron content (TEC). In this paper, we present an analysis of ionospheric disturbances over China mid-and low-latitude area before and during the magnetic storm on 17 March 2015. The work analyses the variation of magnetic indices, the amplitude of ionospheric irregularities observed with four arrays of GPS stations and the influence of geomagnetic storm on GPS positioning. The results show that significant ionospheric TEC disturbances occurred between 10:30 and 12:00 UT during the main phase of the large storm, and the static position reliability for this period are little affected by these disturbances. It is observed that the positive and negative disturbances propagate southward along the meridian from mid-latitude to low-latitude regions. The propagation velocity is from about 200 to 700 m s −1 and the amplitude of ionospheric disturbances is from about 0.2 to 0.9 TECU min −1 . Moreover, the position dilution of precession (PDOP) with static precise point positioning (PPP) on storm and quiet days is 1.8 and 0.9 cm, respectively. This study is based on the analysis of ionospheric variability with differential rate of vertical TEC (DROVT) and impact of ionospheric storm on positioning with technique of GPS PPP.

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Ionospheric effects of St. Patrick's storm over Asian Russia: 17–19 March 2015

Cited by 33 publications

References 63 publications

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

Assimilation of Multiple Data Types to a Regional Ionosphere Model With a 3D‐Var Algorithm (IDA4D)

An Adaptive Forecasting Method for Ionospheric Critical Frequency of F2 Layer

Study of ionospheric disturbances over the China mid- and low-latitude region with GPS observations

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