Patterns of F2-layer variability

Rishbeth, H.; Mendillo, M.

doi:10.1016/s1364-6826(01)00036-0

Cited by 504 publications

(442 citation statements)

References 34 publications

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“…It should be noted that the mid-latitude ionosphere exhibits considerable day-to-day variability in NmF2 during geomagnetically quiet conditions under similar solar activity conditions at all local times for each month (Forbes et al, 2000;Rishbeth and Mendillo, 2001). The origins of this ionospheric variability are discussed in detail by Forbes et al (2000) and Rishbeth and Mendillo (2001).…”

Section: Statistical Study Of the Nmf2 Winter Anomaly: Results And DImentioning

confidence: 99%

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Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study

Павлов

Павлова

2009

Ann. Geophys.

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Abstract. We present a statistical study of variations in the F2-layer peak electron density, NmF2, and altitude, hmF2, over the Argentine Islands ionosonde. The critical frequencies, foF2, and, foE, of the F2 and E-layers, and the propagation factor, M(3000)F2, measured by the ionosonde during the 1957-1959 and 1962-1995 time periods were used in the statistical analysis to determine the values of NmF2 and hmF2. The probabilities to observe maximum and minimum values of NmF2 and hmF2 in a diurnal variation of the electron density are calculated. Our study shows that the main part of the maximum diurnal values of NmF2 is observed in a time sector close to midnight in November, December, January, and February exhibiting the anomalous diurnal variations of NmF2. Another anomalous feature of the diurnal variations of NmF2 exhibited during November, December, and January when the minimum diurnal value of NmF2 is mainly located close to the noon sector. These anomalous diurnal variations of NmF2 are found to be during both geomagnetically quiet and disturbed conditions. Anomalous features are not found in the diurnal variations of hmF2. The statistical study of the NmF2 winter anomaly phenomena over the Argentine Islands ionosonde was carried out. The variations in a maximum daytime value, R, of a ratio of a geomagnetically quiet daytime winter NmF2 to a geomagnetically quiet daytime summer NmF2 taken at a given UT and for approximately the same level of solar activity were studied. The conditional probability of the occurrence of R in an interval of R, the most frequent value of R, the mean expected value of R, and the conditional probability to observe the F2-region winter anomaly during a daytime period were calculated for low, moderate, and high solar activity. The calCorrespondence to: A. V. Pavlov (pavlov@izmiran.ru) culations show that the mean expected value of R and the occurrence frequency of the F2-region winter anomaly increase with increasing solar activity.

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Section: Statistical Study Of the Nmf2 Winter Anomaly: Results And DImentioning

confidence: 99%

“…The origins of this ionospheric variability are discussed in detail by Forbes et al (2000) and Rishbeth and Mendillo (2001). This day-today variability of NmF2 results in a variability of r, and the statistical methods are required to be used in the study of the NmF2 winter anomaly.…”

Section: Statistical Study Of the Nmf2 Winter Anomaly: Results And DImentioning

confidence: 99%

Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study

Павлов

Павлова

2009

Ann. Geophys.

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“…On top of this regular, well behaved mean state of the ionosphere, there exist considerable daily variations under both quiet and disturbed geomagnetic conditions. For instance, Rishbeth and Mendillo (2001) found that for medium solar activity the fluctuations of the ionospheric peak electron density (NmF2) have a standard deviation of 20% in the daytime and 33% at night time. Forbes, Palo, and Zhang (2000), using data from over 100 ionosonde stations, showed that under very quiet conditions (Kp < 1), the standard deviation or 1-σ variability of NmF2 around the mean was about 25 -35% at high frequencies (periods of a few hours to 1 to 2 days) and about 15 -20% at low frequencies (periods of 2 -30 days) at all latitudes.…”

Section: Introductionmentioning

confidence: 99%

“…Forbes, Palo, and Zhang (2000), using data from over 100 ionosonde stations, showed that under very quiet conditions (Kp < 1), the standard deviation or 1-σ variability of NmF2 around the mean was about 25 -35% at high frequencies (periods of a few hours to 1 to 2 days) and about 15 -20% at low frequencies (periods of 2 -30 days) at all latitudes. Rishbeth and Mendillo (2001) and many others have suggested that the causes of this ionospheric variability are external: variations in solar EUV and X-ray fluxes (solar radiation), changes in solar-wind and interplanetary-magnetic-field (IMF) conditions (geomagnetic), and large-scale lower-atmospheric waves (meteorological). They found that the "solar-radiation" component is a minor contributor to the ionospheric daily variability, a conclusion that is consistent with that of Forbes, Palo, and Zhang (2000).…”

Section: Introductionmentioning

confidence: 99%

Ionospheric Day-to-Day Variability Around the Whole Heliosphere Interval in 2008

et al. 2011

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Ionospheric F2 peak electron densities (NmF2) measured at ten ionosonde stations have been analyzed to investigate ionospheric day-to-day variability around the Whole Heliosphere Interval (WHI) in 2008 (Day of Year (DOY) 50 -140). The ionosonde data showed that there was significant global day-to-day variability in NmF2. This variability had 5-, 7-, 9-, 11-, 13.5-, and 16 -21-day periodicities. At middle latitudes, the ionosphere appeared to respond directly to the solar-wind and interplanetary-magnetic-field (IMF) induced geomagnetic-activity forcing, with the day-to-day variability having the same periods as those in the solar-wind/IMF and geomagnetic activity. At the geomagnetic Equator, the ionosphere had a strong 7-day periodicity, corresponding to the same periodicity in the IMF B z component. In the equatorial anomaly region, the ionosphere showed more complicated day-to-day variability, dominated by the 9-day periodicity. In addition, there were also peri- odicities of 11 days and 16 -21 days in the ionosonde data at some stations. The ionosonde data were compared with the Coupled Magnetosphere Ionosphere Thermosphere (CMIT) simulations that were driven by the observed solar-wind and IMF data during the WHI. The CMIT simulations showed similar ionospheric daily variability seen in the data. They captured the positive and negative responses of the ionosphere at middle latitudes during the first corotating interaction region (CIR) event in the WHI. The response of the model to the second CIR event, however, was relatively weak.

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“…The other influences, were termed as meteorological to be originated from lower part of the atmosphere (Rishbeth & Mendillo 2001). Further, they (Zhao et al 2008a(Zhao et al , 2008b mention that the contribution of meteorological effect to the day-to-day variability is comparable to those attributed by geomagnetic activity.…”

Section: Correlation Coefficient Detailsmentioning

confidence: 99%

Removal of solar radiation effect based on nonlinear data processing technique for Seismo-Ionospheric Anomaly before few earthquakes

Yadav

Karia

Pathak

2015

Geomatics, Natural Hazards and Risk

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The study of ionospheric precursorsof earthquakehas gained interest among many researchers, specially the precursor obtained in terms of anomalous variation in total electron content (TEC). If earthquake occurs during a period of moderate to high solar activity, the TEC derived using global positioning system (GPS) measurements requires the elimination of solar effect so as to identify the precursory signature. This paperincludes multi-resolution time series technique to remove the nonlinear effect from solar radiation on GPS-based TEC. The technique is based on wavelet transform applicable to RINEX TEC data. This technique is used to remove nonlinear background solar effect from TEC prior to four different earthquakes (M > 6.0). Further in order to evaluate the extracted TEC, we obtain the correlation between the decomposed TEC A6 and measured solar index (F10.7) and extreme ultraviolet (EUV). A good correlation is obtained between decomposed TEC A6 and EUV for all the cases. This suggests that this technique is useful in removal of background solar effect for identifying earthquake precursor in TEC.

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Patterns of F2-layer variability

Cited by 504 publications

References 34 publications

Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study

Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study

Ionospheric Day-to-Day Variability Around the Whole Heliosphere Interval in 2008

Removal of solar radiation effect based on nonlinear data processing technique for Seismo-Ionospheric Anomaly before few earthquakes

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Patterns of F2-layer variability

Cited by 504 publications

References 34 publications

Anomalous variations of &lt;I&gt;Nm&lt;/I&gt;F2 over the Argentine Islands: a statistical study

Anomalous variations of &lt;I&gt;Nm&lt;/I&gt;F2 over the Argentine Islands: a statistical study

Ionospheric Day-to-Day Variability Around the Whole Heliosphere Interval in 2008

Removal of solar radiation effect based on nonlinear data processing technique for Seismo-Ionospheric Anomaly before few earthquakes

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Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study

Anomalous variations of <I>Nm</I>F2 over the Argentine Islands: a statistical study