Determining the Timing of Driver Influences on 1.8–3.5 MeV Electron Flux at Geosynchronous Orbit Using ARMAX Methodology and Stepwise Regression
dc.contributor.author | Simms, L. E. | |
dc.contributor.author | Engebretson, M. J. | |
dc.contributor.author | Reeves, G. D. | |
dc.date.accessioned | 2023-02-01T18:57:20Z | |
dc.date.available | 2024-02-01 13:57:18 | en |
dc.date.available | 2023-02-01T18:57:20Z | |
dc.date.issued | 2023-01 | |
dc.identifier.citation | Simms, L. E.; Engebretson, M. J.; Reeves, G. D. (2023). "Determining the Timing of Driver Influences on 1.8–3.5 MeV Electron Flux at Geosynchronous Orbit Using ARMAX Methodology and Stepwise Regression." Journal of Geophysical Research: Space Physics 128(1): n/a-n/a. | |
dc.identifier.issn | 2169-9380 | |
dc.identifier.issn | 2169-9402 | |
dc.identifier.uri | https://hdl.handle.net/2027.42/175744 | |
dc.description.abstract | Although lagged correlations have suggested influences of solar wind velocity (V) and number density (N), Bz, ultralow frequency (ULF) wave power, and substorms (as measured by the auroral electrojet (AE) index) on MeV electron flux at geosynchronous orbit over an impressive number of hours and days, a satellite’s diurnal cycle can inflate correlations, associations between drivers may produce spurious effects, and correlations between all previous time steps may create an appearance of additive influence over many hours. Autoregressive-moving average transfer function (ARMAX) multiple regressions incorporating previous hours simultaneously can eliminate cycles and assess the impact of parameters, at each hour, while others are controlled. ARMAX influences are an order of magnitude lower than correlations uncorrected for time behavior. Most influence occurs within a few hours, not the many hours suggested by correlation. A log transformation accounts for nonlinearities. Over all hours, solar wind velocity (V) and number density (N) show an initial negative impact, with longer term positive influences over the 9 (V) or 27 (N) hr. Bz is initially a positive influence, with a longer term (6 hr) negative effect. ULF waves impact flux in the first (positive) and second (negative) hour before the flux measurement, with further negative influences in the 12–24 hr before. AE (representing electron injection by substorms) shows only a short term (1 hr) positive influence. However, when only recovery and after-recovery storm periods are considered (using stepwise regression), there are positive influences of ULF waves, AE, and V, with negative influences of N and Bz.Plain Language SummaryThe influence of solar wind, waves, and substorms on high energy electrons at geosynchronous orbit can appear to occur over a number of hours and days. However, these long duration correlations may be due to diurnal cycles in satellite data, associations between the driving parameters, or correlations of each variable with itself over previous time steps. These extraneous correlations can be corrected for using autoregressive-moving average multiple regression models including previous hours simultaneously. Once these are controlled, the correlations between possible driving parameters and high energy electrons are both lower and influential only over a few hours.Key PointsAutoregressive-moving average transfer function models show drivers of relativistic electron flux are influential only within a few hours or a day of flux changesContrary to simple correlation findings, influences are lower in magnitude and act more immediatelyStepwise multiple regression shows less cumulative effects of drivers in after-storm periods than simple correlation would suggest | |
dc.publisher | OTexts, Heathmont | |
dc.publisher | Wiley Periodicals, Inc. | |
dc.subject.other | electron flux at geosynchronous orbit | |
dc.subject.other | ARMAX models | |
dc.subject.other | stepwise regression | |
dc.subject.other | ULF waves | |
dc.subject.other | substorms | |
dc.subject.other | solar wind and IMF drivers | |
dc.title | Determining the Timing of Driver Influences on 1.8–3.5 MeV Electron Flux at Geosynchronous Orbit Using ARMAX Methodology and Stepwise Regression | |
dc.type | Article | |
dc.rights.robots | IndexNoFollow | |
dc.subject.hlbsecondlevel | Astronomy and Astrophysics | |
dc.subject.hlbtoplevel | Science | |
dc.description.peerreviewed | Peer Reviewed | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/175744/1/jgra57587_am.pdf | |
dc.description.bitstreamurl | http://deepblue.lib.umich.edu/bitstream/2027.42/175744/2/jgra57587.pdf | |
dc.identifier.doi | 10.1029/2022JA030963 | |
dc.identifier.source | Journal of Geophysical Research: Space Physics | |
dc.identifier.citedreference | Simms, L. E., Engebretson, M. J., Pilipenko, V., Reeves, G. D., & Clilverd, M. ( 2016 ). Empirical predictive models of daily relativistic electron flux at geostationary orbit: Multiple regression analysis. Journal of Geophysical Research: Space Physics, 121 ( 4 ), 3181 – 3197. https://doi.org/10.1002/2016JA022414 | |
dc.identifier.citedreference | Osmane, A., Savola, M., Kilpua, E., Koskinen, H., Borovsky, J. E., & Kalliokoski, M. ( 2022 ). Quantifying the non-linear dependence of energetic electron fluxes in the Earth’s radiation belts with radial diffusion drivers. Annales Geophysicae, 40 ( 1 ), 37 – 53. https://doi.org/10.5194/angeo-40-37-2022 | |
dc.identifier.citedreference | Pankratz, A. ( 1991 ). Forecasting with dynamic regression models (p. 386 ). John Wiley & Sons Inc. | |
dc.identifier.citedreference | Potapov, A. S. ( 2017 ). Relativistic electrons of the outer radiation belt and methods of their forecast (review). Solar-Terrestrial Physics, 3 ( 1 ), 57 – 72. https://doi.org/10.12737/article_58f9703837c248.84596315 | |
dc.identifier.citedreference | Reeves, G. D., Baker, D. N., Belian, R. D., Blake, J. B., Cayton, T. E., Fennell, J. F., et al. ( 1998 ). The global response of relativistic radiation belt electrons to the January 1997 magnetic cloud. Geophysical Research Letters, 25 ( 17 ), 3265 – 3268. https://doi.org/10.1029/98gl02509 | |
dc.identifier.citedreference | Reeves, G. D., Morley, S. K., Friedel, R. H. W., Henderson, M. G., Cayton, T. E., Cunningham, G., et al. ( 2011 ). On the relationship between relativistic electron flux and solar wind velocity: Paulikas and Blake revisited. Journal of Geophysical Research, 116 ( A2 ), A02213. https://doi.org/10.1029/2010JA015735 | |
dc.identifier.citedreference | Romanova, N., & Pilipenko, V. ( 2009 ). ULF wave indices to characterize the solar wind-magnetosphere interaction and relativistic electron dynamics. Acta Geophysica, 57 ( 1 ), 158 – 170. https://doi.org/10.2478/s11600-008-0064-4 | |
dc.identifier.citedreference | Rostoker, G., Skone, S., & Baker, D. N. ( 1998 ). On the origin of relativistic electrons in the magnetosphere associated with some geomagnetic storms. Geophysical Research Letters, 25 ( 19 ), 3701 – 3704. https://doi.org/10.1029/98gl02801 | |
dc.identifier.citedreference | Sakaguchi, K., Nagatsuma, T., Reeves, G. D., & Spence, H. E. ( 2015 ). Prediction of MeV electron fluxes throughout the outer radiation belt using multivariate autoregressive models. Space Weather, 13 ( 12 ), 853 – 867. https://doi.org/10.1002/2015SW001254 | |
dc.identifier.citedreference | Shprits, Y. Y., Thorne, R. M., Friedel, R., Reeves, G. D., Fennell, J., Baker, D. N., & Kanekal, S. G. ( 2006 ). Outward radial diffusion driven by losses at magnetopause. Journal of Geophysical Research, 111 ( A11 ), A11214. https://doi.org/10.1029/2006JA011657 | |
dc.identifier.citedreference | Simms, L., Engebretson, M., Clilverd, M., Rodger, C., Lessard, M., Gjerloev, J., & Reeves, G. ( 2018 ). A distributed lag autoregressive model of geostationary relativistic electron fluxes: Comparing the influences of waves, seed and source electrons, and solar wind inputs. Journal of Geophysical Research: Space Physics, 123 ( 5 ), 3646 – 3671. https://doi.org/10.1029/2017JA025002 | |
dc.identifier.citedreference | Simms, L. E., Engebretson, M. J., Rodger, C. J., Gjerloev, J. W., & Reeves, G. D. ( 2019 ). Predicting lower band chorus with autoregressive-moving average transfer function (ARMAX) models. Journal of Geophysical Research: Space Physics, 124 ( 7 ), 5692 – 5708. https://doi.org/10.1029/2019JA026726 | |
dc.identifier.citedreference | Simms, L. E., Ganushkina, N. Y., van de Kamp, M., Liemohn, M. W., & Dubyagin, S. ( 2022 ). Using ARMAX models to determine the drivers of 40-150 keV GOES electron fluxes. Journal of Geophysical Research: Space Physics, 127 ( 9 ), e2022JA030538. https://doi.org/10.1029/2022JA030538 | |
dc.identifier.citedreference | Simms, L. E., Pilipenko, V. A., Engebretson, M. J., Reeves, G. D., Smith, A. J., & Clilverd, M. ( 2014 ). Prediction of relativistic electron flux following storms at geostationary orbit: Multiple regression analysis. Journal of Geophysical Research: Space Physics, 119 ( 9 ), 7297 – 7318. https://doi.org/10.1002/2014JA019955 | |
dc.identifier.citedreference | Simms, L. E., Engebretson, M. J., & Reeves, G. D. ( 2022 ). Removing diurnal signals and longer term trends from electron flux and ULF correlations: A comparison of spectral subtraction, simple differencing, and ARIMAX models. Journal of Geophysical Research: Space Physics, 127, 2. https://doi.org/10.1029/2021JA030021 | |
dc.identifier.citedreference | SPSS. ( 2020 ). IBM SPSS Statistics for Windows (version 27.0). IBM Corp. | |
dc.identifier.citedreference | Staples, F. A., Kellerman, A., Murphy, K. R., Rae, I. J., Sandhu, J. K., & Forsyth, C. ( 2022 ). Resolving magnetopause shadowing using multimission measurements of phase space density. Journal of Geophysical Research: Space Physics, 127 ( 2 ), e2021JA029298. https://doi.org/10.1029/2021JA029298 | |
dc.identifier.citedreference | Stepanov, N. A., Sergeev, V. A., Sormakov, D. A., Andreeva, V. A., Dubyagin, S. V., Ganushkina, N., et al. ( 2021 ). Superthermal proton and electron fluxes in the plasma sheet transition region and their dependence on solar wind parameters. Journal of Geophysical Research: Space Physics, 126 ( 4 ), e2020JA028580. https://doi.org/10.1029/2020JA028580 | |
dc.identifier.citedreference | Su, Y.-J., Quinn, J. M., Johnston, W. R., McCollough, J. P., & Starks, M. J. ( 2014 ). Specification of>2MeV electron flux as a function of local time and geomagnetic activity at geosynchronous orbit. Space Weather, 12 ( 7 ), 470 – 486. https://doi.org/10.1002/2014SW001069 | |
dc.identifier.citedreference | Summers, D., Ma, C., Meredith, N. P., Horne, R. B., Thorne, R. M., Heynderickx, D., & Anderson, R. R. ( 2002 ). Model of the energization of outer-zone electrons by whistler-mode chorus during the October 9, 1990 geomagnetic storm. Geophysical Research Letters, 29 ( 24 ), 27-1 – 27-4. https://doi.org/10.1029/2002GL016039 | |
dc.identifier.citedreference | Takahashi, K., & Ukhorskiy, A. Y. ( 2007 ). Solar wind control of Pc5 pulsation power at geosynchronous orbit. Journal of Geophysical Research, 112 ( A11 ), A11205. https://doi.org/10.1029/2007JA012483 | |
dc.identifier.citedreference | Tu, W., Xiang, Z., & Morley, S. K. ( 2019 ). Modeling the magnetopause shadowing loss during the June 2015 dropout event. Geophysical Research Letters, 46 ( 16 ), 9388 – 9396. https://doi.org/10.1029/2019GL084419 | |
dc.identifier.citedreference | Wing, S., Johnson, J. R., Camporeale, E., & Reeves, G. D. ( 2016 ). Information theoretical approach to discovering solar wind drivers of the outer radiation belt. Journal of Geophysical Research: Space Physics, 121 ( 10 ), 9378 – 9399. https://doi.org/10.1002/2016JA022711 | |
dc.identifier.citedreference | Wing, S., Johnson, J. R., Turner, D. L., Ukhorskiy, A. Y., & Boyd, A. J. ( 2022 ). Untangling the solar wind and magnetospheric drivers of the radiation belt electrons. Journal of Geophysical Research: Space Physics, 127 ( 4 ), e2021JA030246. https://doi.org/10.1029/2021JA030246 | |
dc.identifier.citedreference | Baker, D. N., Pulkkinen, T., Li, X., Kanekal, S., Ogilvie, K., Lepping, R., et al. ( 1998 ). A strong CME-related magnetic cloud interaction with the Earth’s magnetosphere: ISTP observations of rapid relativistic electron acceleration on May 15, 1997. Geophysical Research Letters, 25 ( 15 ), 2975 – 2978. https://doi.org/10.1029/98GL01134 | |
dc.identifier.citedreference | Balikhin, M. A., Boynton, R. J., Walker, S. N., Borovsky, J. E., Billings, S. A., & Wei, H. L. ( 2011 ). Using the NARMAX approach to model the evolution of energetic electrons fluxes at geostationary orbit. Geophysical Research Letters, 38 ( 18 ), L18105. https://doi.org/10.1029/2011GL048980 | |
dc.identifier.citedreference | Birn, J., Thomsen, M. F., Borovsky, J. E., Reeves, G. D., McComas, D. J., & Belian, R. D. ( 1997 ). Characteristic plasma properties during dispersionless substorm injections at geosynchronous orbit. Journal of Geophysical Research, 102 ( A2 ), 2309 – 2324. https://doi.org/10.1029/96JA02870 | |
dc.identifier.citedreference | Borovsky, J. E. ( 2017 ). Time-integral correlations of multiple variables with the relativistic-electron flux at geosynchronous orbit: The strong roles of substorm-injected electrons and the ion plasma sheet. Journal of Geophysical Research: Space Physics, 122 ( 12 ), 11961 – 11990. https://doi.org/10.1002/2017JA024476 | |
dc.identifier.citedreference | Borovsky, J. E., & Denton, M. H. ( 2014 ). Exploring the cross correlations and autocorrelations of the ULF indices and incorporating the ULF indices into the systems science of the solar wind-driven magnetosphere. Journal of Geophysical Research: Space Physics, 119 ( 6 ), 4307 – 4334. https://doi.org/10.1002/2014JA019876 | |
dc.identifier.citedreference | Boyd, A. J., Spence, H. E., Claudepierre, S. G., Fennell, J. F., Blake, J. B., Baker, D. N., et al. ( 2014 ). Quantifying the radiation belt seed population in the 17 March 2013 electron acceleration event. Geophysical Research Letters, 41 ( 7 ), 2275 – 2281. https://doi.org/10.1002/2014GL059626 | |
dc.identifier.citedreference | Boynton, R. J., Amariutei, O. A., Shprits, Y. Y., & Balikhin, M. A. ( 2019 ). The system science development of local time-dependent 40-keV electron flux models for geostationary orbit. Space Weather, 17 ( 6 ), 894 – 906. https://doi.org/10.1029/2018SW002128 | |
dc.identifier.citedreference | Boynton, R. J., Balikhin, M. A., Billings, S. A., Reeves, G. D., Ganushkina, N., Gedalin, M., et al. ( 2013 ). The analysis of electron fluxes at geosynchronous orbit employing a NARMAX approach. Journal of Geophysical Research: Space Physics, 118 ( 4 ), 1500 – 1513. https://doi.org/10.1002/jgra.50192 | |
dc.identifier.citedreference | Burton, R. K., McPherron, R. L., & Russell, C. T. ( 1975 ). An empirical relationship between interplanetary conditions and Dst. Journal of Geophysical Research, 80 ( 31 ), 4204 – 4214. https://doi.org/10.1029/JA080i031p04204 | |
dc.identifier.citedreference | Elkington, S. R., Hudson, M. K., & Chan, A. A. ( 2003 ). Resonant acceleration and diffusion of outer zone electrons in an asymmetric geomagnetic field. Journal of Geophysical Research, 108 ( A3 ), 1116. https://doi.org/10.1029/2001JA009202 | |
dc.identifier.citedreference | Friedel, R. H. W., Reeves, G. D., & Obara, T. ( 2002 ). Relativistic electron dynamics in the inner magnetosphere — A review. Journal of Atmospheric and Solar-Terrestrial Physics, 64 ( 2 ), 265 – 282. https://doi.org/10.1016/S1364-6826(01)00088-8 | |
dc.identifier.citedreference | Holm, S. ( 1979 ). A simple sequentially rejective multiple test procedure. Scandinavian Journal of Statistics, 6 ( 2 ), 65 – 70. https://doi.org/10.2307/4615733 | |
dc.identifier.citedreference | Hwang, J. A., Lee, D.-Y., Lyons, L. R., Smith, A. J., Zou, S., Min, K. W., et al. ( 2007 ). Statistical significance of association between whistler-mode chorus enhancements and enhanced convection periods during highspeed streams. Journal of Geophysical Research, 112 ( A9 ), A09213. https://doi.org/10.1029/2007JA012388 | |
dc.identifier.citedreference | Hyndman, R. J., & Athanasopoulos, G. ( 2018 ). Forecasting: Principles and practice ( 2nd ed., p. 291 ). OTexts, Heathmont. | |
dc.identifier.citedreference | Jaynes, A. N., Ali, A. F., Elkington, S. R., Malaspina, D. M., Baker, D. N., Li, X., et al. ( 2018 ). Fast diffusion of ultrarelativistic electrons in the outer radiation belt: 17 March 2015 storm event. Geophysical Research Letters, 45 ( 20 ), 10874 – 10882. https://doi.org/10.1029/2018GL079786 | |
dc.identifier.citedreference | Jaynes, A. N., Baker, D. N., Singer, H. J., Rodriguez, J. V., Loto’aniu, T. M., Ali, A. F., et al. ( 2015 ). Source and seed populations for relativistic electrons: Their roles in radiation belt changes. Journal of Geophysical Research: Space Physics, 120 ( 9 ), 7240 – 7254. https://doi.org/10.1002/2015JA021234 | |
dc.identifier.citedreference | Kozyreva, O., Pilipenko, V., Engebretson, M. J., Yumoto, K., Watermann, J., & Romanova, N. ( 2007 ). In search of a new ULF wave index: Comparison of Pc5 power with dynamics of geostationary relativistic electrons. Planetary and Space Science, 55 ( 6 ), 755 – 769. https://doi.org/10.1016/j.pss.2006.03.013 | |
dc.identifier.citedreference | Lam, H.-L. ( 2004 ). On the prediction of relativistic electron fluence based on its relationship with geomagnetic activity over a solar cycle. Journal of Atmospheric and Solar-Terrestrial Physics, 66 ( 2004 ), 1703 – 1714. https://doi.org/10.1016/j.jastp.2004.08.002 | |
dc.identifier.citedreference | Loto’aniu, T. M., Singer, H. J., Waters, C. L., Angelopoulos, V., Mann, I. R., Elkington, S. R., & Bonnell, J. W. ( 2010 ). Relativistic electron loss due to ultralow frequency waves and enhanced outward radial diffusion. Journal of Geophysical Research, 115 ( A12 ), A12245. https://doi.org/10.1029/2010JA015755 | |
dc.identifier.citedreference | Lyatsky, W., & Khazanov, G. V. ( 2008 ). Effect of geomagnetic disturbances and solar wind density on relativistic electrons at geostationary orbit. Journal of Geophysical Research, 113 ( A8 ), A08224. https://doi.org/10.1029/2008JA013048 | |
dc.identifier.citedreference | Makridakis, S. G., Wheelwright, S. C., & Hyndman, R. J. ( 1998 ). Forecasting: Methods and applications ( 3rd ed., p. 652 ). John Wiley and Sons. | |
dc.identifier.citedreference | Mathie, R. A., & Mann, I. R. ( 2000 ). A correlation between extended intervals of ULF wave power and storm-time geosynchronous relativistic electron flux enhancements. Geophysical Research Letters, 27 ( 20 ), 3261 – 3264. https://doi.org/10.1029/2000GL003822 | |
dc.identifier.citedreference | MATLAB. ( 2021 ). MATLAB version: 9.11.0.1809720 (R2021b) Update 1. The MathWorks Inc. | |
dc.identifier.citedreference | Neter, J., Wasserman, W., & Kutner, M. ( 1985 ). Applied linear statistical models ( 2 nd ed., p. 112 ). Richard D. Irwin, Inc. | |
dc.identifier.citedreference | O’Brien, T. P., & McPherron, R. L. ( 2003 ). An empirical dynamic equation for energetic electrons at geosynchronous orbit. Journal of Geophysical Research, 108 ( A3 ), 1137. https://doi.org/10.1029/2002JA009324 | |
dc.identifier.citedreference | O’Brien, T. P., McPherron, R. L., Sornette, D., Reeves, G. D., Friedel, R., & Singer, H. J. ( 2001 ). Which magnetic storms produce relativistic electrons at geosynchronous orbit? Journal of Geophysical Research, 106 ( A8 ), 15533 – 15544. https://doi.org/10.1029/2001JA000052 | |
dc.working.doi | NO | en |
dc.owningcollname | Interdisciplinary and Peer-Reviewed |
Files in this item
Remediation of Harmful Language
The University of Michigan Library aims to describe library materials in a way that respects the people and communities who create, use, and are represented in our collections. Report harmful or offensive language in catalog records, finding aids, or elsewhere in our collections anonymously through our metadata feedback form. More information at Remediation of Harmful Language.
Accessibility
If you are unable to use this file in its current format, please select the Contact Us link and we can modify it to make it more accessible to you.