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All issues Volume 9 (2019) J. Space Weather Space Clim., 9 (2019) A34 References
Open Access
Issue
J. Space Weather Space Clim.
Volume 9, 2019
Article Number A34
Number of page(s) 27
DOI https://doi.org/10.1051/swsc/2019030
Published online 26 September 2019
  • Arge CN, Henney CJ, Koller J, Compeau CR, Young S, MacKenzie D, Fay A, Harvey JW. 2010. Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model. Twelfth International Solar Wind Conference 1216: 343–346. DOI: 10.1063/1.3395870. [Google Scholar]
  • Arge CN, Henney CJ, Koller J, Toussaint WA, Harvey JW, Young S. 2011. Improving Data Drivers for Coronal and Solar Wind Models. In: 5th International Conference of Numerical Modeling of Space Plasma Flows (ASTRONUM 2010), Pogorelov NV, Audit E, Zank GP, (Eds.), vol. 444 of Astronomical Society of the Pacific Conference Series, p. 99. [Google Scholar]
  • Aseev NA, Shprits YY, Drozdov AY, Kellerman AC. 2016. Numerical applications of the advective–diffusive codes for the inner magnetosphere. Space Weather 14(11): 993–1010. DOI:10.1002/2016SW001484. [CrossRef] [Google Scholar]
  • Azizian N, Mazzuchi T, Sarkani S, Rico DF. 2011. A framework for evaluating technology readiness, system quality, and program performance of US DoD acquisitions. Sys Eng 14(4): 410–426. DOI: 10.1002/sys.20186. [CrossRef] [Google Scholar]
  • Baker DN, Allen JH, Kanekal SG, Reeves GD. 1998. Disturbed space environment may have been related to pager satellite failure. EOS Trans 79: 477–477. DOI: 10.1029/98EO00359. [CrossRef] [Google Scholar]
  • Baker DN, Balstad R, Bodeau JM, Cameron E, Fennel JF, et al. 2008. Severe Space Weather Events – Understanding Societal and Economic Impacts. A Workshop Report. The National Academies Press, National Research Council of the National Academies. DOI: 10.17226/12643. [Google Scholar]
  • Baker DN, Kanekal SG, Hoxie VC, Batiste S, Bolton M, et al. 2013. The Relativistic Electron-Proton Telescope (REPT) instrument on board the Radiation Belt Storm Probes (RBSP) spacecraft: Characterization of earth’s radiation belt high-energy particle populations. Space Sci Rev 179: 337–381. DOI: 10.1007/s11214-012-9950-9. [CrossRef] [Google Scholar]
  • Bellaire P. 2006. Community Coordinated Modeling Center 2005 Workshop Report. Space Weather 4(2). DOI: 10.1029/2005SW000206. [Google Scholar]
  • Béniguel Y, Hamel P. 2011. A global ionosphere scintillation propagation model for equatorial regions. J. Space Weather Space Clim 1(1): A04. DOI: 10.1051/swsc/2011004. [Google Scholar]
  • Beutier T, Boscher D. 1995. A three-dimensional analysis of the electron radiation belt by the Salammbô code. J Geophys Res (Space Phys) 100(A8): 14853–14862. DOI: 10.1029/94JA03066. [CrossRef] [Google Scholar]
  • Birn J, Drake JF, Shay MA, Rogers BN, Denton RE, et al. 2001. Geospace environmental modeling (GEM) magnetic reconnection challenge. J Geophys Res (Space Phys) 106(A3): 3715–3719. DOI: 10.1029/1999JA900449. [NASA ADS] [CrossRef] [Google Scholar]
  • Blake JB, Carranza PA, Claudepierre SG, Clemmons JH, Crain WR, et al. 2013. The magnetic electron ion spectrometer (MagEIS) instruments aboard the radiation belt storm probes (RBSP) spacecraft. Space Sci Rev 179: 383–421. DOI: 10.1007/s11214-013-9991-8. [CrossRef] [Google Scholar]
  • Blanc M, Richmond A. 1980. The ionospheric disturbance dynamo. J Geophys Res (Space Phys) 85(A4): 1669–1686. DOI: 10.1029/JA085iA04p01669. [CrossRef] [Google Scholar]
  • Booker HG, Wells HW. 1938. Scattering of radio waves by the F-region of the ionosphere. Terr. Magn. Atmos. Elect. 43(3): 249–256. DOI: 10.1029/TE043i003p00249. [CrossRef] [Google Scholar]
  • Burrell AG, Halford A, Klenzing J, Stoneback RA, Morley SK, Annex AM, Laundal KM, Kellerman AC, Stansby D, Ma J. 2018. Snakes on a spaceship – an overview of python in heliophysics. J Geophys Res (Space Phys). 10384–10402. DOI: 10.1029/2018JA025877. [Google Scholar]
  • Caldwell B, McCarron E, Jonas S. 2017. An abridged history of federal involvement in space weather forecasting. Space Weather 15(10): 1222–1237. DOI: 10.1002/2017SW001626. [CrossRef] [Google Scholar]
  • Carter BA, Retterer JM, Yizengaw E, Groves K, Caton R, et al. 2014a. Geomagnetic control of equatorial plasma bubble activity modeled by the TIEGCM with Kp. Geophys Res Lett 41(15): 5331–5339. DOI: 10.1002/2014GL060953. [CrossRef] [Google Scholar]
  • Carter BA, Retterer JM, Yizengaw E, Wiens K, Wing S, et al. 2014b. Using solar wind data to predict daily GPS scintillation occurrence in the African and Asian low-latitude regions. Geophys Res Lett 41(23): 8176–8184. DOI: 10.1002/2014GL062203. [CrossRef] [Google Scholar]
  • Carter BA, Yizengaw E, Retterer JM, Francis M, Terkildsen M, Marshall R, Norman R, Zhang K. 2014c. An analysis of the quiet time day-to-day variability in the formation of postsunset equatorial plasma bubbles in the Southeast Asian region. J Geophys Res (Space Phys) 119(4): 3206–3223. DOI: 10.1002/2013JA019570. [CrossRef] [Google Scholar]
  • Cash MD, Biesecker DA, Pizzo V, de Koning CA, Millward G, Arge CN, Henney CJ, Odstrcil D. 2015. Ensemble modeling of the 23 July 2012 coronal mass ejection. Space Weather 13: 611–625. DOI: 10.1002/2015SW001232. [NASA ADS] [CrossRef] [Google Scholar]
  • Cassak PA, Emslie AG, Halford AJ, Baker DN, Spence HE, Avery SK, Fisk LA. 2017. Space physics and policy for contemporary society. J Geophys Res (Space Phys) 122(4): 4430–4435. DOI: 10.1002/2017JA024219. [CrossRef] [Google Scholar]
  • Chamberlin P, Woods T, Woods T, Eparvier FG. 2007. Flare Irradiance Spectral Model (FISM): Daily component algorithms and results. Space Weather 5(7): S07005. DOI: 10.1029/2007SW000316. [Google Scholar]
  • Cousins EDP, Matsuo T, Richmond AD. 2015. Mapping high-latitude ionospheric electrodynamics with SuperDARN and AMPERE. J Geophys Res (Space Phys) 120(7): 5854–5870. DOI: 10.1002/2014JA020463. [CrossRef] [Google Scholar]
  • Drozdov AY, Shprits YY, Orlova KG, Kellerman AC, Subbotin DA, Baker DN, Spence HE, Reeves GD. 2015. Energetic, relativistic, and ultra relativistic electrons: Comparison of long-term VERB code simulations with Van Allen Probes measurements. J Geophys Res (Space Phys) 120: 3574–3587. DOI: 10.1002/2014JA020637. [CrossRef] [Google Scholar]
  • Emmert JT, Lean J, Picone JM. 2010. Record-low thermospheric density during the 2008 solar minimum. Geophys Res Lett 37: L12102. DOI: 10.1029/2010GL043671. [NASA ADS] [CrossRef] [Google Scholar]
  • Ganushkina NY, Amariutei OA, Shprits YY, Liemohn MW. 2013. Transport of the plasma sheet electrons to the geostationary distances. J Geophys Res (Space Phys) 118(1): 82–98. DOI: 10.1029/2012JA017923. [CrossRef] [Google Scholar]
  • Ganushkina NY, Amariutei OA, Welling D, Heynderickx D. 2015. Nowcast model for low–energy electrons in the inner magnetosphere. Space Weather 13(1): 16–34. DOI: 10.1002/2014SW001098. [CrossRef] [Google Scholar]
  • Ganushkina NY, Liemohn MW, Amariutei OA, Pitchford D. 2014. Low–energy electrons (5–50 keV) in the inner magnetosphere. J Geophys Res (Space Phys) 119(1): 246–259. DOI: 10.1002/2013JA019304. [CrossRef] [Google Scholar]
  • Ganushkina NY, Liemohn MW, Pulkkinen TI. 2012. Storm-time ring current: Model-dependent results. Ann Geophys 30(1): 177–202. DOI: 10.5194/angeo-30-177-2012. [CrossRef] [Google Scholar]
  • Ganushkina NY, Pulkkinen TI, Bashkirov VF, Baker DN, Li X. 2001. Formation of intense nose structures. Geophys Res Lett 28(3): 491–494. DOI: 10.1029/2000GL011955. [CrossRef] [Google Scholar]
  • Ganushkina NY, Pulkkinen TI, Fritz T. 2005. Role of substorm-associated impulsive electric fields in the ring current development during storms. Ann Geophys 23(2): 579–591. DOI: 10.5194/angeo-23-579-2005. [CrossRef] [Google Scholar]
  • Ganushkina NY, Pulkkinen TI, Milillo A, Liemohn M. 2006. Evolution of the proton ring current energy distribution during 21–25 April 2001 storm. J Geophys Res (Space Phys) 111(A11). DOI: 10.1029/2006JA011609. [Google Scholar]
  • Ganushkina NY, Pulkkinen TI, Sergeev VA, Kubyshkina MV, Baker DN, Turner NE, et al. 2000. Entry of plasma sheet particles into the inner magnetosphere as observed by Polar/CAMMICE. J Geophys Res (Space Phys) 105(A11): 25205–25219. DOI: 10.1029/2000JA900062. [CrossRef] [Google Scholar]
  • Glauert SA, Horne RB. 2005. Calculation of pitch angle and energy diffusion coefficients with the PADIE code. J Geophys Res (Space Phys) 110(A4). DOI: 10.1029/2004JA010851. [Google Scholar]
  • Glocer A, Rastätter L, Kuznetsova M, Pulkkinen A, Singer HJ, et al. 2016. Community-wide validation of geospace model local K-index predictions to support model transition to operations. Space Weather 14(7): 469–480. DOI: 10.1002/2016SW001387. [CrossRef] [Google Scholar]
  • Gordeev E, Sergeev V, Honkonen I, Kuznetsova M, Rastätter L, Palmroth M, Janhunen P, Tóth G, Lyon J, Wiltberger M. 2015. Assessing the performance of community-available global MHD models using key system parameters and empirical relationships. Space Weather 13(12): 868–884. DOI: 10.1002/2015SW001307. [CrossRef] [Google Scholar]
  • Grubbs G, Michell R, Samara M, Hampton D, Hecht J, Solomon S, Jahn J-M. 2018. A comparative study of spectral auroral intensity predictions from multiple electron transport models. J Geophys Res (Space Phys) 123(1): 993–1005. DOI: 10.1002/2017JA025026. [CrossRef] [Google Scholar]
  • Henney CJ, Hock RA, Schooley AK, Toussaint WA, White SM, Arge CN. 2015. Forecasting solar extreme and far ultraviolet irradiance. Space Weather 13: 141–153. DOI: 10.1002/2014SW001118. [CrossRef] [Google Scholar]
  • Henney CJ, Toussaint WA, White SM, Arge CN. 2012. Forecasting F10.7 with solar magnetic flux transport modeling. Space Weather 10: S02011. DOI: 10.1029/2011SW000748. [NASA ADS] [CrossRef] [Google Scholar]
  • Hickmann KS, Godinez HC, Henney CJ, Arge CN. 2015. Data assimilation in the ADAPT photospheric flux transport model. Sol Phys 290: 1105–1118. DOI: 10.1007/s11207-015-0666-3. [Google Scholar]
  • Hickmann KS, Godinez HC, Henney CJ, Arge CN. 2016. Scale-dependent data assimilation of solar photospheric magnetic field. 10th IFAC Symposium on Nonlinear Control Systems 49, 193–198. DOI: 10.1016/j.ifacol.2016.10.162. [Google Scholar]
  • Honkonen I, Rastätter L, Grocott A, Pulkkinen A, Palmroth M, Raeder J, Ridley AJ, Wiltberger M. 2013. On the performance of global magnetohydrodynamic models in the Earth’s magnetosphere. Space Weather 11(5): 313–326. DOI: 10.1002/swe.20055. [CrossRef] [Google Scholar]
  • Horne RB, Glauert SA, Meredith NP, Koskinen H, Vainio R, et al. 2013. Forecasting the Earth’s radiation belts and modelling solar energetic particle events: Recent results from SPACECAST. J Space Weather Space Clim 3: A20. DOI: 10.1051/swsc/2013042. [CrossRef] [Google Scholar]
  • Jordanova VK, Miyoshi YS, Zaharia S, Thomsen MF, Reeves GD, Evans DS, Mouikis CG, Fennell JF. 2006. Kinetic simulations of ring current evolution during the Geospace Environment Modeling challenge events. J Geophys Res (Space Phys) 111(A11). DOI: 10.1029/2006JA011644. [Google Scholar]
  • Kalman RE. 1960. A new approach to linear filtering and prediction problems. Trans ASME J Basic Eng 82(Series D): 35–45. [Google Scholar]
  • Kappenman JG. 2005. An overview of the impulsive geomagnetic field disturbances and power grid impacts associated with the violent Sun-Earth connection events of 29–31 October 2003 and a comparative evaluation with other contemporary storms. Space Weather 3(8). DOI: 10.1029/2004SW000128. [Google Scholar]
  • Kellerman AC, Shprits YY, Kondrashov D, Subbotin D, Makarevich RA, Donovan E, Nagai T. 2014. Three-dimensional data assimilation and reanalysis of radiation belt electrons: Observations of a four-zone structure using five spacecraft and the VERB code. J Geophys Res (Space Phys) 119(11): 8764–8783. DOI: 10.1002/2014JA020171. [CrossRef] [Google Scholar]
  • Kelley MC, Makela JJ, de La Beaujardière O, Retterer J. 2011. Convective ionospheric storms: A review. Rev Geophys 49(2): RG2003. DOI: 10.1029/2010RG000340. [CrossRef] [Google Scholar]
  • Kim K, Shprits Y, Subbotin D, Ni B. 2012. Relativistic radiation belt electron responses to GEM magnetic storms: Comparison of CRRES observations with 3-D VERB simulations. J Geophys Res (Space Phys) 117(A8). DOI: 10.1029/2011JA017460. [Google Scholar]
  • Klenzing J, Simões F, Ivanov S, Heelis RA, Bilitza D, Pfaff RF, Rowland DE. 2011. Topside equatorial ionospheric density and composition during and after extreme solar minimum. J Geophys Res (Space Phys) (1978–2012) 116(A12): A12330. DOI: 10.1029/2011JA017213. [Google Scholar]
  • Koons HC, Gorney DJ. 1988. Spacecraft environmental anomalies expert system: A status report. Aerosp. Rep. ATR88(9562)1. Aerosp. Corp., El Segundo, CA. [Google Scholar]
  • Lanzerotti LJ. 2015. Space weather strategy and action plan: The national program is rolled out. Space Weather 13(12): 824–825. DOI: 10.1002/2015SW001334. [CrossRef] [Google Scholar]
  • Linker JA, Caplan RM, Downs C, Lionello R, Riley P, Mikic Z, Henney CJ, Arge CN, Kim T, Pogorelov N. 2016. An empirically driven time-dependent model of the solar wind. J Phys Conf Ser 719: 012012. DOI: 10.1088/1742-6596/719/1/012012. [CrossRef] [Google Scholar]
  • Liu H, Bardeen CG, Foster BT, Lauritzen P, Liu J, et al. 2018. Development and validation of the whole atmosphere community climate model with thermosphere and ionosphere extension (WACCM-X 2.0). J Adv Model Earth Sys 10(2): 381–402. DOI: 10.1002/2017MS001232. [CrossRef] [Google Scholar]
  • Mankins JC. 1995. Technology readiness levels. White Paper. Available at https://aiaa.kavi.com/apps/group_public/download.php/2212/TRLs_MankinsPaper_1995.pdf. [Google Scholar]
  • Mankins JC. 2009. Technology readiness assessments: A retrospective. Acta Astronaut 65(9): 1216–1223. DOI: 10.1016/j.actaastro.2009.03.058. [CrossRef] [Google Scholar]
  • Matéo-Vélez J, Sicard A, Payan D, Ganushkina N, Meredith NP, Sillanpää I. 2018. Spacecraft surface charging induced by severe environments at geosynchronous orbit. Space Weather 16(1): 89–106. DOI: 10.1002/2017SW001689. [CrossRef] [Google Scholar]
  • McGranaghan R, Knipp DJ, Matsuo T, Cousins E. 2016. Optimal interpolation analysis of high-latitude ionospheric Hall and Pedersen conductivities: Application to assimilative ionospheric electrodynamics reconstruction. J Geophys Res (Space Phys) 121(5): 4898–4923. DOI: 10.1002/2016JA022486. [CrossRef] [Google Scholar]
  • McGranaghan R, Knipp DJ, Matsuo T, Godinez H, Redmon RJ, Solomon SC, Morley SK. 2015. Modes of high-latitude auroral conductance variability derived from DMSP energetic electron precipitation observations: Empirical orthogonal function analysis. J Geophys Res (Space Phys) 120(12): 11013–11031. DOI: 10.1002/2015JA021828. [CrossRef] [Google Scholar]
  • Merkin VG, Lyon JG, Lario D, Arge CN, Henney CJ. 2016. Time-dependent magnetohydrodynamic simulations of the inner heliosphere. J Geophys Res (Space Physics) 121: 2866–2890. DOI: 10.1002/2015JA022200. [Google Scholar]
  • Meulenberg A Jr. 1976. Evidence for a new discharge mechanism for dielectrics in a plasma. Studies in Condensed Matter Physics 237–246. [Google Scholar]
  • NASA. 2015. Heliophyics living with a star program, 10-year vision beyond 2015. LWS website https://lwstrt.gsfc.nasa.gov/images/pdf/LWS_10YrVision_Oct2015_Final.pdf. [Google Scholar]
  • National Research Council. 2003. The sun to the earth and beyond: A decadal research strategy in solar and space physics. The National Academies Press, Washington, DC. ISBN 978-0-309-08509-0. DOI: 10.17226/10477. [Google Scholar]
  • National Research Council. 2013. Solar and space physics: A science for a technological society. The National Academies Press, Washington, DC. ISBN 978-0-309-16428-3. DOI: 10.17226/13060. [Google Scholar]
  • O’Brien TP. 2009. SEAES–GEO: A spacecraft environmental anomalies expert system for geosynchronous orbit. Space Weather 7(9). DOI: 10.1029/2009SW000473. [Google Scholar]
  • Olechowski A, Eppinger SD, Joglekar N. 2015. Technology readiness levels at 40: A study of state-of-the-art use, challenges, and opportunities. In: 2015 Portland International Conference on Management of Engineering And Technology (PICMET), IEEE. pp. 2084–2094. DOI: 10.1109/PICMET.2015.7273196. [Google Scholar]
  • Owens MJ, Spence HE, McGregor S, Hughes WJ, Quinn JM, Arge CN, Riley P, Linker J, Odstrcil D. 2008. Metrics for solar wind prediction models comparison of empirical, hybrid, and physics-based schemes with 8 years of L1 observations. Space Weather 6(8). DOI: 10.1029/2007SW000380. [Google Scholar]
  • Product of National Science and Technology Council. October 2015. National Space Weather Strategy. https://obamawhitehouse.archives.gov/sites/default/files/ostp/final-nationalspaceweatherstrategy-20151028.pdf [Google Scholar]
  • Pulkkinen A, Bernabeu E, Thomson A, Viljanen A, Pirjola R, et al. 2017. Geomagnetically induced currents: Science, engineering, and applications readiness. Space Weather 15(7): 828–856. DOI: 10.1002/2016SW001501. [CrossRef] [Google Scholar]
  • Pulkkinen A, Rastätter L, Kuznetsova M, Singer H, Balch C, et al. 2013. Community-wide validation of geospace model ground magnetic field perturbation predictions to support model transition to operations. Space Weather 11(6): 369–385. DOI: 10.1002/swe.20056. [CrossRef] [Google Scholar]
  • Qian L, Burns AG, Emery BA, Foster B, Lu G, Maute A, Richmond AD, Roble RG, Solomon SC, Wang W. 2014. The NCAR TIE-GCM. In: Modeling the ionosphere-thermosphere system, Huba J, Schunk R, Khazanov G, (Eds.) John Wiley & Sons Ltd. pp. 73–83. [CrossRef] [Google Scholar]
  • Quinn J, Hughes J, Baker DN, Linker J, Lyon J, Solomon SC, Wiltberger M. 2009. Building and using coupled models for the space weather system: Lessons learned. Space Weather 7(5). DOI: 10.1029/2009SW000462. [Google Scholar]
  • Raeder J, Berchem J, Ashour-Abdalla M. 1998. The geospace environment modeling grand challenge: Results from a global geospace circulation model. J Geophys Res (Space Phys) 103(A7): 14787–14797. DOI: 10.1029/98JA00014. [CrossRef] [Google Scholar]
  • Rajesh PK, Lin CH, Chen CH, Lin JT, Matsuo T, Chou MY, Chen WH, Chang MT, You CF. 2017. Equatorial plasma bubble generation/inhibition during 2015 St. Patrick’s Day storm. Space Weather 15(9): 1141–1150. DOI: 10.1002/2017SW001641. [CrossRef] [Google Scholar]
  • Rastätter L, Kuznetsova MM, Glocer A, Welling D, Meng X, et al. 2013. Geospace environment modeling 2008–2009 challenge: Dst index. Space Weather 11(4): 187–205. DOI: 10.1002/swe.20036. [CrossRef] [Google Scholar]
  • Richmond AD, Kamide Y, Ahn BH, Akasofu SI, Alcaydé D, et al. 1988. Mapping electrodynamic features of the high-latitude ionosphere from localized observations: Combined incoherent-scatter radar and magnetometer measurements for January 18–19, 1984. J Geophys Res (Space Phys) 93(A6): 5760–5776. DOI: 10.1029/JA093iA06p05760. [CrossRef] [Google Scholar]
  • Roederer JG. 1970. Dynamics of geomagnetically trapped radiation, Springer Verlag, New York. [CrossRef] [Google Scholar]
  • Roederer JG. 1988. GEM: geospace environment modeling. Eos, Transactions American Geophysical Union 69(33): 786–787. DOI: 10.1029/88EO01064. [CrossRef] [Google Scholar]
  • Saiz E, Guerrero A, Cid C, Palacios J, Cerrato Y. 2016. Searching for Carrington-like events and their signatures and triggers. J Space Weather Space Clim 6: A6. DOI: 10.1051/swsc/2016001. [CrossRef] [Google Scholar]
  • Schulz M, Lanzerotti LJ. 1974. Particle diffusion in the radiation belts, Springer, Berlin. [CrossRef] [Google Scholar]
  • Secan JA, Bussey RM, Fremouw EJ, Basu S. 1995. An improved model of equatorial scintillation. Radio Sci 30(3): 607–617. DOI: 10.1029/94RS03172. [CrossRef] [Google Scholar]
  • Shim JS, Kuznetsova M, Rasttter L, Bilitza D, Butala M, et al. 2012. CEDAR electrodynamics thermosphere ionosphere (ETI) challenge for systematic assessment of ionosphere/thermosphere models: Electron density, neutral density, NmF2, and hmF2 using space based observations. Space Weather 10(10). DOI: 10.1029/2012SW000851. [Google Scholar]
  • Shinagawa H, Jin H, Miyoshi Y, Fujiwara H, Yokoyama T, Otsuka Y. 2018. Daily and seasonal variations in the linear growth rate of the Rayleigh-Taylor instability in the ionosphere obtained with GAIA. Prog Earth Planet Sci 5(1): 16. DOI: 10.1186/s40645-018-0175-8. [CrossRef] [Google Scholar]
  • Shprits Y, Kellerman A, Kondrashov D, Subbotin D. 2013. Application of a new data operator-splitting data assimilation technique to the 3-D VERB diffusion code and CRRES measurements. Geophys Res Lett 40(19): 4998–5002. DOI: 10.1002/grl.50969. [CrossRef] [Google Scholar]
  • Solomon SC, Hays PB, Abreu VJ. 1988. The Auroral 6300 Å emission: observations and modeling. J Geophys Res 93(A9): 9867–9882. DOI: 10.1029/JA093iA09p09867. [CrossRef] [Google Scholar]
  • Solomon SC, Qian L, Burns AG. 2013. The anomalous ionosphere between solar cycles 23 and 24. J Geophys Res (Space Phys) 118(10): 6524–6535. DOI: 10.1002/jgra.50561. [CrossRef] [Google Scholar]
  • Spence H, Baker D, Burns A, Guild T, Huang C-L, Siscoe G, Weigel R. 2004. Center for integrated space weather modeling metrics plan and initial model validation results. J Atmos Sol Terr Phys 66(15): 1499–1507. DOI: 10.1016/j.jastp.2004.03.029. [Google Scholar]
  • Subbotin DA, Shprits YY. 2009. Three-dimensional modeling of the radiation belts using the Versatile Electron Radiation Belt (VERB) code. Space Weather 7(10). DOI: 10.1029/2008SW000452. [Google Scholar]
  • Subbotin DA, Shprits YY, Ni B. 2011. Long-term radiation belt simulation with the VERB 3-D code: Comparison with CRRES observations. J Geophys Res (Space Phys) 116(A12). DOI: 10.1029/2011JA017019. [Google Scholar]
  • Sultan PJ. 1996. Linear theory and modeling of the Rayleigh-Taylor instability leading to the occurrence of equatorial spread F. J Geophys Res (Space Phys) 101(A12): 26875–26891. DOI: 10.1029/96JA00682. [CrossRef] [Google Scholar]
  • Weinzierl M, Yeates AR, Mackay DH, Henney CJ, Arge CN. 2016. A new technique for the photospheric driving of non-potential solar coronal magnetic field simulations. Astrophys J 823: 55. DOI: 10.3847/0004-637X/823/1/55. [CrossRef] [Google Scholar]
  • Whalen JA. 2009. The linear dependence of GHz scintillation on electron density observed in the equatorial anomaly. Ann Geophys 27(4): 1755–1761. DOI: 10.5194/angeo-27-1755-2009. [CrossRef] [Google Scholar]
  • Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, et al. 2016. The FAIR Guiding Principles for scientific data management and stewardship. Scientific Data 3: 160018. EP. DOI: 10.1038/sdata.2016.18. [CrossRef] [PubMed] [Google Scholar]
  • Wing S, Johnson JR, Jen J, Meng C-I, Sibeck DG, Bechtold K, Freeman J, Costello K, Balikhin M, Takahashi K. 2005. Kp forecast models. J Geophys Res (Space Phys) 110(A4). DOI: 10.1029/2004JA010500. [Google Scholar]
  • Worden J, Harvey J. 2000. An evolving synoptic magnetic flux map and implications for the distribution of photospheric magnetic flux. Sol Phys 195: 247–268. DOI: 10.1023/A:1005272502885. [NASA ADS] [CrossRef] [Google Scholar]
  • Yokoyama T. 2017. A review on the numerical simulation of equatorial plasma bubbles toward scintillation evaluation and forecasting. Prog Earth Planet Sci 4(1): 37. DOI: 10.1186/s40645-017-0153-6. [CrossRef] [Google Scholar]

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