Influence of solar activity variations on the day-to-day NmE variability during geomagnetically quiet conditions according to the ground-based Dourbes ionosonde data

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Abstract

A study of day-to-day variations in the statistical characteristics of the ionospheric E layer electron number density NmE for each month in the year under geomagnetically quiet conditions at low and middle solar activity was carried out according to the hourly ground-based Dourbes ionosonde measurements of the ionospheric E layer critical frequency during the time periods from 1957 to 2023. The NmE statistical parameters under calculations are the mathematical expectation NmEE, the most probable NmEMP, the arithmetical mean monthly median NmEMED, the standard deviations sE, sMP, sMED, and the variation coefficients CVE, CVMP, and CVMED of NmE relative to NmEE, NmEMP, and NmEMED, respectively. It was shown that the value of NmEE provides the best description of a set of observations of NmE by one parameter due to the lower day-to-day variability of NmE compared to NmEMP or NmEMED. It was proven for the first time that the transition from low to middle solar activity leads to significant changes in the day-to-day variability of NmE with the longest periods of increases and decreases in the studied variability in March and December, respectively.

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About the authors

A. V. Pavlov

Pushkov Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation of Russian Academy of Sciences

Author for correspondence.
Email: pavlov@izmiran.ru
Russian Federation, Moscow, Troitsk

N. M. Pavlova

Pushkov Institute of Terrestrial Magnetism, Ionosphere, and Radio Wave Propagation of Russian Academy of Sciences

Email: pavlov@izmiran.ru
Russian Federation, Moscow, Troitsk

References

  1. Агекян Т.А. Основа теории ошибок для астрономов и физиков. М.: Наука, 148 с. 1968.
  2. Акасофу С.И. Полярные и магнитосферные суббури. М.: Мир, 316 с. 1971.
  3. Акасофу С.И., Чепмен С. Солнечно-земная физика. Ч. 1. М.: Мир, 384 с. 1974.
  4. Балдин К.В., Башлыков В.Н., Рукосуев А.В. Основы теории вероятностей и математической статистики. М.: ФЛИНТА, 489 с. 2016.
  5. Брюнелли Б.Е., Намгаладзе А.А. Физика ионосферы. М.: Наука, 527 с. 1988.
  6. Демидович Б.П., Марон И.А. Основы вычислительной математики. М.: Наука, 664 с. 1970.
  7. Дэйвид Г. Порядковые статистики. М.: Наука, 336 с. 1979.
  8. Кобзарь А.И. Прикладная математическая статистика. Для инженеров и научных работников. М.: ФИЗМАТЛИТ, 816 с. 2006.
  9. Кремер Н.Ш. Теория вероятностей и математическая статистика. М.: ЮНИТИ-ДАНА, 551 с. 2012.
  10. Мак-Кракен Д., Дорн У. Численные методы и программирование на ФОРТРАНе. М: Мир, 584 с. 1977.
  11. Павлов А.В., Павлова Н.М. Влияние рефракции солнечного излучения на зенитный угол и времена восхода и захода Солнца в атмосфере // Геомагнетизм и аэрономия. Т. 50. № 2. С. 228–233. 2010.
  12. Павлов А.В., Павлова Н.М. Сравнение измеренных ионозондом Москвы и вычисленных концентраций электронов максимума слоя E ионосферы в весенних условиях // Геомагнетизм и аэрономия. Т. 55. № 2. С. 247–257. 2015. https://doi.org/10.7868/S0016794015020145.
  13. Павлов А.В., Павлова Н.М. Зависимости от месяца года статистических характеристик NmE средних и низких широт в дневных геомагнито-спокойных условиях при низкой солнечной активности // Геомагнетизм и аэрономия. Т. 56. № 4. С. 431–436. 2016. https://doi.org/10.7868/S0016794016040167
  14. Павлов А.В., Павлова Н.М. Суточные вариации статистических характеристик изменчивости NmF2 по данным наземных ионозондов низких широт в геомагнито-спокойных условиях при низкой солнечной активности // Геомагнетизм и аэрономия. Т. 63. № 4. С. 429–440. 2023. https://doi.org/10.31857/S0016794022600685
  15. Пиггот В.П., Равер К. Руководство URSI по интерпретации и обработке ионограмм. М.: Наука, 342 с. 1978.
  16. Тейлор Д. Введение в теорию ошибок. М.: Мир, 272 с. 1985.
  17. Acebal A.O., Sojka J.J. A flare sensitive 3 h solar flux radio index for space weather applications // Space Weather. V. 9. № 7. ID S07004. 2011. https://doi.org/10.1029/2010SW000585
  18. Banks P.M., Kockarts G. Aeronomy. Part B. New York and London: Academic Press, 355 p. 1973.
  19. Chattamvelli R., Shanmugam R. Statistics for scientists and engineers. Hoboken, NJ: John Wiley & Sons Inc., 467 p. 2015.
  20. Durivage M.A. Practical engineering, process, and reliability statistics. Milwaukee, WA: ASQ Quality Press, 260 p. 2022.
  21. Gatti P.L. Probability theory and mathematical statistics for engineers. London and New York: Spon Press of Taylor & Francis Group, 356 p. 2005.
  22. Haldoupis C. Midlatitude sporadic E. A typical paradigm of atmosphere-ionosphere coupling // Space Sci. Rev. V. 168. № 1–4. P. 441–461. 2012. https://doi.org/10.1007/s11214-011-9786-8
  23. Hedin A.E. MSIS-86 thermospheric model // J. Geophys. Res. – Space. V. 92. № 5. P. 4649–4662. 1987. https://doi.org/10.1029/JA092iA05p04649
  24. Howell D.C. Statistical Methods for Psychology. Belmont, CA: Wadsworth Cengage Learning, 771 p. 2013.
  25. Krall J., Emmert J.T., Sassi F., McDonald S.E., Huba J.D. Day-to-day variability in the thermosphere and its impact on plasmasphere refilling // J. Geophys. Res. – Space. V. 121. № 7. P. 6889–6900. 2016. https://doi.org/10.1002/2015JA022328
  26. Liu H., Yamazaki J., Lei J. Day-to-day variability of the thermosphere and ionosphere / Upper atmosphere dynamics and energetics / Geophysical Monograph Series, 261 / Eds. W. Wang, Y. Zhang, L.J. Paxton / Space Physics and Aeronomy Collection. V. 4, Hoboken, NJ: John Wiley and Sons Inc. P. 275–300. 2021. https://doi.org/10.1002/9781119815631.ch15
  27. Manson J.E. The solar extreme ultraviolet between 30 and 205 Å on November 9, 1971, compared with previous measurements in this spectral region // J. Geophys. Res. V. 81. № 10. P. 1629–1635. 1976. https://doi.org/10.1029/JA081i010p01629
  28. Mendillo M. Day-to-day variability of the ionosphere / The Dynamical Ionosphere. A Systems Approach to Ionospheric Irregularity / Eds. M. Materassi, B. Forte, A.J. Coster, S. Skone, Amsterdam, The Netherlands: Elsevier. P. 7–11. 2021. https://doi.org/10.1016/B978-0-12-814782-5.00002-9
  29. Moore L., Mendillo M., Martinis C., Bailey S. Day-to-day variability of the E layer // J. Geophys. Res. – Space. V. 111. № 6. ID A06307. 2006. https://doi.org/10.1029/2005JA011448
  30. Nicolls M.J., Rodrigues F.S., Bust G.S. Global observations of E region plasma density morphology and variability // J. Geophys. Res. – Space. V. 117. № 1. ID A01305. 2012. https://doi.org/10.1029/2011JA017069
  31. Pavlov A.V. The role of vibrationally excited oxygen and nitrogen in the D and E regions of the ionosphere // Ann. Geophys. V. 12. № 10–11. P. 1085−1090. 1994. https://doi.org/10.1007/s00585-994-1085-1
  32. Pavlov A.V. Ion chemistry of the ionosphere at E- and F-region altitudes: A review // Surv. Geophys. V. 33. № 5. P. 1133–1172. 2012. https://doi.org/10.1007/s10712-012-9189-8
  33. Pavlov A.V., Pavlova N.M. Comparison of NmE measured by the Boulder ionosonde with model predictions near the spring equinox // J. Atmos. Sol.-Terr. Phy. V. 102. № 1. P. 39–47. 2013. https://doi.org/10.1016/j.jastp.2013.05.006
  34. Pavlov A.V., Pavlova N.M. Long-term monthly statistics of mid-latitudinal NmF2 in the northern geographic hemisphere during geomagnetically quiet and steadily low solar activity conditions // J. Atmos. Sol.-Terr. Phy. V. 142. № 5. P. 83–97. 2016. https://doi.org/10.1016/j.jastp.2016.03.001
  35. Pavlov A.V., Pavlova N.M. Long-term monthly statistics of the mid-latitude ionospheric E-layer peak electron density in the Northern geographic hemisphere during geomagnetically quiet and steadily low solar activity conditions // Ann. Geophys. – Italy. V. 60. № 2. ID A0327. 2017. https://doi.org/10.4401/ag-6969
  36. Pellinen-Wannberg A.K., Häggström I., Sánchez J.D.C., Plane J.M.C., Westman A. Strong E region ionization caused by the 1767 trail during the 2002 Leonids // J. Geophys. Res. – Space. V. 119. № 9. P. 7880–7888. 2014. https://doi.org/10.1002/2014JA020290
  37. Picone J.M., Hedin A.E., Drob D.P., Aikin A.C. NRLMSISE-00 empirical model of the atmosphere: statistical comparisons and scientific issues // J. Geophys. Res. – Space. V. 107. № 12. ID 1468. 2002. https://doi.org/10.1029/2002JA009430
  38. Ross S.M. Introduction to probability and statistics for engineers and scientists. Amsterdam: Elsevier Academic Press, 624 p. 2004.
  39. Rumsey D.J. Statistics II. Hoboken, NJ: John Wiley & Sons, Inc., 423 p. 2022.
  40. Richards P.G., Fennelly J.A., Torr D.G. EUVAC: A solar EUV flux model for aeronomical calculations // J. Geophys. Res. – Space. V. 99. № 5. P. 8981–8992. 1994. https://doi.org/10.1029/94JA00518
  41. Schunk R.W., Nagy A.F. Ionospheres. Physics, plasma physics, and chemistry. Cambridge, UK: Cambridge University Press, 628 p. 2009.
  42. Sengupta P.R. Solar X-ray control of the E-layer of the ionosphere // J. Atmos. Sol.-Terr. Phy. V. 32. № 7. P. 1273–1282. 1970. https://doi.org/10.1016/0021-9169(70)90057-7
  43. Sojka J.J., Jensen J.B., David M., Schunk R.W., Woods T., Eparvier F., Sulzer M.P., Gonzalez S.A., Eccles J.V. Ionospheric model-observation comparisons: E layer at Arecibo incorporation of SDO-EVE solar irradiances // J. Geophys. Res. – Space. V. 119. № 5. P. 3844−3856. 2014. https://doi.org/10.1002/2013JA019528
  44. Titterington D.M., Smith A.F.M., Makov U.E. Statistical analysis of finite mixture distributions. Chichester, UK: John Wiley & Sons Ltd., 243 p. 1985.
  45. Verma J.P., Verma P. Determining sample size and power in research studies. Singapore: Springer, 127 p. 2020. https://doi.org/10.1007/978-981-15-5204-5
  46. Whitehead J.D. Production and prediction of sporadic E // Rev. Geophys. V. 8. № 1. P. 65–144. 1970. https://doi.org/10.1029/RG008i001p00065

Supplementary files

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2. Fig. 1. Pk versus NmE at 12:00 UT (12:18 SLT) during low solar activity. Solid and dashed curves correspond to January and February (upper left panel), March and April (middle left panel), May and June (lower left panel), July and August (upper right panel), September and October (middle right panel), and November and December (lower right panel).

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3. Fig. 2. Pk dependence on NmE at 12:00 UT (12:18 SLT) at average solar activity. The correspondence of solid and dashed curves to months of the year is the same as in Fig. 1.

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4. Fig. 3. Diurnal variations of CVE (solid curves), CVMP (dashed curves) and CVMED (dashed curves) for January (upper left panel), February (middle left panel), March (lower left panel), April (upper right panel), May (middle right panel) and June (lower right panel) under low solar activity.

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5. Fig. 4. Diurnal variations of CVE (solid curves), CVMP (dotted curves) and CVMED (dashed curves) for July (upper left panel), August (middle left panel), September (lower left panel), October (upper right panel), November (middle right panel) and December (lower right panel) under low solar activity.

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6. Fig. 5. Diurnal variations of CVE (solid curves), CVMP (dashed curves) and CVMED (dashed curves) for January (upper left panel), February (middle left panel), March (lower left panel), April (upper right panel), May (middle right panel) and June (lower right panel) under average solar activity.

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7. Fig. 6. Diurnal variations of CVE (solid curves), CVMP (dashed curves) and CVMED (dashed curves) for July (upper left panel), August (middle left panel), September (lower left panel), October (upper right panel), November (middle right panel) and December (lower right panel) under average solar activity.

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8. Fig. 7. Daily variations of ∆ CVE in January, February and March (solid, dashed and dotted curves, respectively, in the upper left panel), in April, May and June (solid, dashed and dotted curves, respectively, in the lower left panel), in July, August and September (solid, dashed and dotted curves, respectively, in the upper right panel), in October, November and December (solid, dashed and dotted curves, respectively, in the lower right panel).

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