Open Access
Issue |
J. Space Weather Space Clim.
Volume 12, 2022
|
|
---|---|---|
Article Number | 16 | |
Number of page(s) | 13 | |
DOI | https://doi.org/10.1051/swsc/2022011 | |
Published online | 16 May 2022 |
- Bilitza D. 2018. IRI the International Standard for the Ionosphere. Adv Radio Sci 16: 1–11. https://doi.org/10.5194/ars-16-1-2018. [CrossRef] [Google Scholar]
- Borries C, Berdermann J, Jakowski N, Wilken V. 2015. Ionospheric storms – A challenge for empirical forecast of the total electron content. J Geophys Res: Space Phys 120(4): 3175–3186. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2015JA020988, https://doi.org/10.1002/2015JA020988, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2015JA020988. [CrossRef] [Google Scholar]
- Burns AG, Killeen TL, Deng W, Carignan GR, Roble RG. 1995. Geomagnetic storm effects in the low- to middle-latitude upper thermosphere. J Geophys Res: Space Phys 100(A8): 14673–14691. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/94JA03232, https://doi.org/10.1029/94JA03232, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/94JA03232. [CrossRef] [Google Scholar]
- Chartier AT, Jackson DR, Mitchell CN. 2013. A comparison of the effects of initializing different thermosphere-ionosphere model fields on storm time plasma density forecasts. J Geophys Res: Space Phys 118(11): 7329–7337. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2013JA019034, https://doi.org/10.1002/2013JA019034, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2013JA019034. [CrossRef] [Google Scholar]
- Chartier AT, Matsuo T, Anderson JL, Collins N, Hoar TJ, Lu G, Mitchell CN, Coster AJ, Paxton LJ, Bust GS. 2016. Ionospheric data assimilation and forecasting during storms. J Geophys Res: Space Phys 121(1): 2014JA020,799. https://doi.org/10.1002/2014JA020799, URL http://onlinelibrary.wiley.com/doi/10.1002/2014JA020799/abstract. [Google Scholar]
- Codrescu MV, Fuller-Rowell TJ, Minter CF. 2004. An ensemble-type Kalman filter for neutral thermospheric composition during geomagnetic storms. Space Weather 2(11): S11,003. https://doi.org/10.1029/2004SW000088, URL http://onlinelibrary.wiley.com/doi/10.1029/2004SW000088/abstract. [Google Scholar]
- Codrescu MV, Fuller-Rowell TJ, Munteanu V, Minter CF, Millward GH. 2008. Validation of the coupled thermosphere ionosphere plasmasphere electrodynamics model: CTIPE-mass spectrometer incoherent scatter temperature comparison. Space Weather 6(9): S09,005. https://doi.org/10.1029/2007SW000364, URL http://onlinelibrary.wiley.com/doi/10.1029/2007SW000364/abstract. [Google Scholar]
- Codrescu MV, Fuller-Rowell TJ, Foster JC, Holt JM, Cariglia SJ. 2000. Electric field variability associated with the Millstone Hill electric field model. J Geophys Res: Space Phys 105(A3): 5265–5273. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/1999JA900463, https://doi.org/10.1029/1999JA900463, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/1999JA900463. [CrossRef] [Google Scholar]
- Codrescu MV, Negrea C, Fedrizzi M, Fuller-Rowell TJ, Dobin A, Jakowsky N, Khalsa H, Matsuo T, Maruyama N. 2012. A real-time run of the Coupled Thermosphere Ionosphere Plasmasphere electrodynamics (CTIPe) model. Space Weather 10(2): S02,001. 10.1029/2011SW000736, URL http://onlinelibrary.wiley.com/doi/10.1029/2011SW000736/abstract. [Google Scholar]
- Codrescu MV, Roble RG, Forbes JM. 1992. Interactive ionosphere modeling: A comparison between TIGCM and ionosonde data. J Geophys Res: Space Phys 97(A6): 8591–8600. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/91JA02807, https://doi.org/10.1029/91JA02807, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/91JA02807. [CrossRef] [Google Scholar]
- Codrescu SM, Codrescu MV, Fedrizzi M. 2018. An ensemble Kalman filter for the thermosphere-ionosphere. Space Weather 16(1): 57–68. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017SW001752, https://doi.org/10.1002/2017SW001752, URL https://agupubs.pericles-prod.literatumonline.com/doi/abs/10.1002/2017SW001752. [CrossRef] [Google Scholar]
- Evensen G. 1994. Sequential data assimilation with a nonlinear quasi-geostrophic model using Monte Carlo methods to forecast error statistics. J Geophys Res: Oceans 99(C5): 10143–10162. 10.1029/94JC00572, URL http://onlinelibrary.wiley.com/doi/10.1029/94JC00572/abstract. [CrossRef] [Google Scholar]
- Evensen G. 2003. The ensemble Kalman filter: Theoretical formulation and practical implementation. Ocean Dyn 53(4): 343–367. https://doi.org/10.1007/s10236-003-0036-9. [CrossRef] [Google Scholar]
- Fedrizzi M, Fuller-Rowell TJ, Codrescu MV. 2012. Global Joule heating index derived from thermospheric density physics-based modeling and observations. Space Weather 10(3): S03001, 1–13. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2011SW000724, https://doi.org/10.1029/2011SW000724, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2011SW000724. [Google Scholar]
- Fernandez-Gomez I, Fedrizzi M, Codrescu MV, Borries C, Fillion M, Fuller-Rowell TJ. 2019. On the difference between real-time and research simulations with CTIPe. Adv Space Res 64(10): 2077–2087. https://doi.org/10.1016/j.asr.2019.02.028, URL http://www.sciencedirect.com/science/article/pii/S0273117719301322. [CrossRef] [Google Scholar]
- Fuller-Rowell TJ, Rees D. 1980. A three-dimensional time-dependent global model of the thermosphere. J Atmos Sci 37(11): 2545–2567. https://doi.org/10.1175/1520-0469(1980)037<2545:ATDTDG>2.0.CO;2, URL https://doi.org/10.1175/1520-0469(1980)037<2545:ATDTDG>2.0.CO;2. [CrossRef] [Google Scholar]
- Fuller-Rowell TJ, Evans DS. 1987. Height-integrated Pedersen and Hall conductivity patterns inferred from the TIROS-NOAA satellite data. J Geophys Res: Space Phys 92(A7): 7606–7618. https://doi.org/10.1029/JA092iA07p07606, URL http://onlinelibrary.wiley.com/doi/10.1029/JA092iA07p07606/abstract. [CrossRef] [Google Scholar]
- Fuller-Rowell TJ, Codrescu MV, Moffett RJ, Quegan S. 1994. Response of the thermosphere and ionosphere to geomagnetic storms. J Geophys Res: Space Phys 99(A3): 3893–3914. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/93JA02015, https://doi.org/10.1029/93JA02015, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/93JA02015. [CrossRef] [Google Scholar]
- Fuller-Rowell TJ, Codrescu MV, Rishbeth H, Moffett RJ, Quegan S. 1996. On the seasonal response of the thermosphere and ionosphere to geomagnetic storms. J Geophys Res: Space Phys 101(A2): 2343–2353. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/95JA01614, https://doi.org/10.1029/95JA01614, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/95JA01614. [CrossRef] [Google Scholar]
- Fuller-Rowell TJ, Codrescu MV, Roble RG, Richmond AD. 1997. How does the thermosphere and ionosphere react to a geomagnetic storm? Wash DC Am Geophys Union Geophys Monogr Ser 98: 203–225. https://doi.org/10.1029/GM098p0203, URL http://adsabs.harvard.edu/abs/1997GMS....98..203F. [Google Scholar]
- Fuller-Rowell T, Araujo-Pradere E, Minter C, Codrescu M, Spencer P, Robertson D, Jacobson AR. 2006. US-TEC: A new data assimilation product from the Space Environment Center characterizing the ionospheric total electron content using real-time GPS data. Radio Sci 41(06): 1–8. https://doi.org/10.1029/2005RS003393. [Google Scholar]
- Hedin AE, Biondi MA, Burnside RG, Hernandez G, Johnson RM, et al. 1991. Revised global model of thermosphere winds using satellite and ground-based observations. Journal of Geophysical Research: Space Physics 96(A5): 7657–7688. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/91JA00251, https://doi.org/10.1029/91JA00251, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/91JA00251. [CrossRef] [Google Scholar]
- Heelis RA, Maute A. 2020. Challenges to understanding the Earth’s ionosphere and thermosphere. J Geophys Res: Space Phys 125(7): e2019JA027,497. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2019JA027497, https://doi.org/10.1029/2019JA027497, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2019JA027497. [CrossRef] [Google Scholar]
- Hinteregger HE, Fukui K, Gilson BR. 1981. Observational, reference and model data on solar EUV, from measurements on AE-E. Geophys Res Lett 8(11): 1147–1150. https://doi.org/10.1029/GL008i011p01147, URL http://onlinelibrary.wiley.com/doi/10.1029/GL008i011p01147/abstract. [CrossRef] [Google Scholar]
- Hsu C-T, Matsuo T, Wang W, Liu J-Y. 2014. Effects of inferring unobserved thermospheric and ionospheric state variables by using an Ensemble Kalman Filter on global ionospheric specification and forecasting. J Geophys Res: Space Phys 119(11): 2014JA020,390. https://doi.org/10.1002/2014JA020390, URL http://onlinelibrary.wiley.com/doi/10.1002/2014JA020390/abstract. [Google Scholar]
- Jakowski N, Mayer C, Hoque MM, Wilken V. 2011. Total electron content models and their use in ionosphere monitoring. Radio Sci 46(6):RS0D18, 1–11. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2010RS004620, https://doi.org/10.1029/2010RS004620, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2010RS004620. [CrossRef] [Google Scholar]
- Jee G, Lee H-B, Kim YH, Chung J-K, Cho J. 2010. Assessment of GPS global ionosphere maps (GIM) by comparison between CODE GIM and TOPEX/Jason TEC data: Ionospheric perspective: Assessment of GPS global ionosphere maps. J Geophys Res: Space Phys 115(A10): A10319, 1–11. https://doi.org/10.1029/2010JA015432, URL http://doi.wiley.com/10.1029/2010JA015432. [Google Scholar]
- Killeen TL, Burns AG, Azeem I, Cochran S, Roble RG. 1997. A theoretical analysis of the energy budget in the lower thermosphere. J Atmos Sol-Terr Phys 59(6): 675–689. https://doi.org/10.1016/S1364-6826(96)00114-9, URL http://www.sciencedirect.com/science/article/pii/S1364682696001149. [CrossRef] [Google Scholar]
- Manoj C, Maus S. 2012. A real-time forecast service for the ionospheric equatorial zonal electric field: Real-time zonal electric field. Space Weather 10(9): S090021–9. https://doi.org/10.1029/2012SW000825, URL http://doi.wiley.com/10.1029/2012SW000825. [Google Scholar]
- Mlynczak MG, Hunt LA, Russell JM, Marshall BT, Mertens CJ, Thompson RE. 2016. The global infrared energy budget of the thermosphere from 1947 to 2016 and implications for solar variability. Geophys Res Lett 43(23): 11,934–11,940. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2016GL070965, https://doi.org/10.1002/2016GL070965, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2016GL070965. [CrossRef] [Google Scholar]
- Morozov AV, Ridley AJ, Bernstein DS, Collins N, Hoar TJ, Anderson JL. 2013. Data assimilation and driver estimation for the global ionosphere-thermosphere model using the ensemble adjustment Kalman filter. J Atmos Sol-Terr Phys 104: 126–136. https://doi.org/10.1016/j.jastp.2013.08.016, URL http://www.sciencedirect.com/science/article/pii/S1364682613002289. [CrossRef] [Google Scholar]
- Nava B, Cosson P, Radicella SM. 2008. A new version of the NeQuick ionosphere electron density model. J Atmos Sol-Terr Phys 70(15): 1856–1862. https://doi.org/10.1016/j.jastp.2008.01.015, URL http://www.sciencedirect.com/science/article/pii/S1364682608000357. [CrossRef] [Google Scholar]
- Negrea C, Codrescu MV, Fuller-Rowell TJ. 2012. On the validation effort of the coupled thermosphere ionosphere plasmasphere electrodynamics model. Space Weather 10(8):S08010, 1–9. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2012SW000818, https://doi.org/10.1029/2012SW000818, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2012SW000818. [Google Scholar]
- Picone JM, Hedin AE, Drob DP, Aikin AC. 2002. NRLMSISE-00 empirical model of the atmosphere: Statistical comparisons and scientific issues. J Geophys Res: Space Phys 107(A12): SIA 15–1–SIA 15–16. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2002JA009430, https://doi.org/10.1029/2002JA009430, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2002JA009430. [Google Scholar]
- Proelss GW, von Zahn U. 1978. On the local time variation of atmospheric-ionospheric disturbances. In: Space Research XVIII; Proceedings of the Open Meetings of the Working Groups on Physical Sciences, Tel Aviv, Israel, June 7–18, 1977. (A79-13382 03-88) Pergamon Press, Ltd., Oxford, pp. 159–162. URL http://adsabs.harvard.edu/abs/1978spre.conf..159P. [Google Scholar]
- Richmond AD. 1989. Modeling the ionosphere wind dynamo: A review. Pure Appl Geophys 131(3): 413–435. https://doi.org/10.1007/BF00876837, URL https://doi.org/10.1007/BF00876837. [CrossRef] [Google Scholar]
- Roble RG. 1992. Global dynamic models of the Earth’s upper atmosphere. In: Astrodynamics 1991; Proceedings of the AAS/AIAA Astrodynamics Conference, Durango, CO, August 19–22, 1991. Pt. 3 (A92-43251 18-13). Univelt, Inc., San Diego, CA, pp. 2313–2328. URL http://adsabs.harvard.edu/abs/1992asdy.conf.2313R. [Google Scholar]
- Rockafellar RT, Wets RJ-B. 1998. Variational analysis. Grundlehren der mathematischen Wissenschaften. Springer-Verlag, Berlin Heidelberg. ISBN 978-3-540-62772-2. https://doi.org/10.1007/978-3-642-02431-3, URL https://www.springer.com/gp/book/9783540627722. [CrossRef] [Google Scholar]
- Sarris TE. 2019. Understanding the ionosphere thermosphere response to solar and magnetospheric drivers: Status, challenges and open issues. Philos Trans R Soc A: Math Phys Eng Sci 377(2148): 20180,101. Publisher: Royal Society, https://doi.org/10.1098/rsta.2018.0101, URL https://royalsocietypublishing.org/doi/10.1098/rsta.2018.0101. [Google Scholar]
- Schunk RW, Scherliess L, Sojka JJ, Thompson DC, Anderson DN, et al. 2004. Global assimilation of ionospheric measurements (GAIM). Radio Sci 39(1). _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1029/2002RS002794, https://doi.org/10.1029/2002RS002794, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1029/2002RS002794. [Google Scholar]
- Solomentsev DV, Khattatov BV, Codrescu MV, Titov AA, Yudin V, Khattatov VU. 2012. Ionosphere state and parameter estimation using the Ensemble Square Root Filter and the global three-dimensional first-principle model. Space Weather 10(7): S07,004. https://doi.org/10.1029/2012SW000777, URL http://onlinelibrary.wiley.com/doi/10.1029/2012SW000777/abstract. [Google Scholar]
- Spencer P, Robertson D, Mader G. 2004. Ionospheric data assimilation methods for geodetic applications. In: PLANS 2004. Position Location and Navigation Symposium (IEEE Cat. No.04CH37556), Monterey, CA, USA, 26–29 April 2004. IEEE, pp. 510–517. ISBN 978-0-7803-8416-3. https://doi.org/10.1109/PLANS.2004.1309036, URL http://ieeexplore.ieee.org/document/1309036/. [Google Scholar]
- Sutton E. 2011. Accelerometer-derived atmospheric densities from the CHAMP and GRACE satellites: Version 2.3. AFRL Technical Memo. DTIC# ADA537198. Virginia, USA: Defense Technical Information Center. URL https://drive.google.com/drive/folders/1RnnRCPqTJcmsfS13N8ukLF-72k4IfJOL. [CrossRef] [Google Scholar]
- Sutton EK. 2018. A new method of physics-based data assimilation for the quiet and disturbed thermosphere. Space Weather 16(6): 736–753. _eprint: https://agupubs.onlinelibrary.wiley.com/doi/pdf/10.1002/2017SW001785, https://doi.org/10.1002/2017SW001785, URL https://agupubs.onlinelibrary.wiley.com/doi/abs/10.1002/2017SW001785. [CrossRef] [Google Scholar]
- Tapley BD, Bettadpur S, Watkins M, Reigber C. 2004. The gravity recovery and climate experiment: Mission overview and early results. Geophys Res Lett 31(9): L09,607. https://doi.org/10.1029/2004GL019920, URL http://onlinelibrary.wiley.com/doi/10.1029/2004GL019920/abstract. [Google Scholar]
- Weimer DR. 2005. Improved ionospheric electrodynamic models and application to calculating Joule heating rates. J Geophys Res: Space Phys 110(A5): A05,306. https://doi.org/10.1029/2004JA010884, URL http://onlinelibrary.wiley.com/doi/10.1029/2004JA010884/abstract. [Google Scholar]
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.