The Space Physics Environment Data Analysis System (SPEDAS)

Angelopoulos, V.; Cruce, P.; Drozdov, Alexander; Grimes, E. W.; Hatzigeorgiu, Nick; King, David A.; Larson, D. E.; Lewis, James W.; McTiernan, J. M.; Roberts, D. A.; Russell, Chuck; Hori, Tomoaki; Kasahara, Yoshiya; Kumamoto, Atsushi; Matsuoka, A.; Miyashita, Yukinaga; Miyoshi, Yoshizumi; Shinohara, I.; Teramoto, Masaaki; Faden, J.; Halford, A. J.; McCarthy, Michael; Millan, R. M.; Sample, J. G.; Smith, David M.; Woodger, L. A.; Masson, A.; Narock, Ayris; Asamura, Kazushi; Chang, T. F.; Chiang, Che‐Ming; Kazama, Y.; Keika, K.; Matsuda, Shoya; Segawa, Takehiko; Seki, K.; Motomizu, Shoji; Tam, Sunny Wing-Yee; Umemura, Norio; Wang, B. J.; Wang, S. Y.; Redmon, R. J.; Rodriguez, J. V.; Singer, H. J.; Vandegriff, J. D.; Abe, Shuji; Nosé, M.; Shinbori, Atsuki; Tanaka, Yoshimasa; Ueno, S.; Andersson, L.; Dunn, P.; Fowler, Christopher; Halekas, J. S.; Hara, Takuya; Harada, Yuki; Lee, C. O.; Lillis, R. J.; Mitchell, D. L.; Argall, M. R.; Bromund, K. R.; Burch, J. L.; Cohen, I. J.; Galloy, Michael; Giles, B. L.; Jaynes, A. N.; Contel, O. Le; Oka, M.; Phan, T. D.; Walsh, Brian M.; Westlake, J. H.; Wilder, F. D.; Bale, S. D.; Livi, R.; Pulupa, M.; Whittlesey, P. L.; DeWolfe, A. W.; Harter, B.; Lucas, Edson Mello; Auster, U.; Bonnell, J. W.; Cully, C. M.; Donovan, E.; Ergun, R. E.; Frey, H. U.; Jackel, B. J.; Keiling, A.; Korth, H.; McFadden, J. P.; Nishimura, Yoshihiro; Plaschke, Ferdinand; Robert, P.; Turner, D. L.; Weygand, J. M.; Candey, R. M.; Johnson, Russell D.; Kovalick, T. J.; Liu, M. H.; McGuire, R. E.; Breneman, A. W.; Kersten, K.; Schroeder, P.

doi:10.1007/s11214-018-0576-4

Cited by 370 publications

(362 citation statements)

References 43 publications

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“…THEMIS and OMNI data access and processing were done using the Space Physics Environment Data Analysis System (SPEDAS) version 3.1 (Angelopoulos et al, 2019). We acknowledge NASA contract NAS5-02099 for use of data from the THEMIS mission.…”

Section: Acknowledgmentsmentioning

confidence: 99%

A Statistical Study of Near‐Earth Magnetotail Evolution During Pseudosubstorms and Substorms With THEMIS Data

et al. 2020

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Pseudosubstorms (pseudobreakups) and substorms are similar phenomena. In terms of auroral morphology, however, the former are not accompanied by poleward expansion, while the latter are. To understand what causes this difference, we studied temporal and spatial development of the near-Earth magnetotail at X = −7 to −11R E around pseudosubstorm and substorm onsets, based on superposed epoch analysis of Time History of Events and Macroscale Interactions during Substorms (THEMIS) data. We find that the earthward flow begins to increase at X = −10 to −11R E just before onset and dipolarization for both pseudosubstorms and substorms, possibly due to near-Earth magnetic reconnection or the preceding relaxation of the thin current sheet in a tailward region, but the earthward flow is slower for pseudosubstorms than for substorms. Dipolarization, together with magnetic field fluctuation, is nearly the same at X = −8R E for both cases, but it is weaker at other distances for pseudosubstorms than for substorms. This result suggests that the current disruption related to dipolarization does not expand tailward and hence auroral poleward expansion does not occur for pseudosubstorms. Furthermore, the total pressure is larger at X = −8 to −11R E for several minutes before onset for substorms than for pseudosubstorms. The total pressure gradient increases more largely after onset for substorms than for pseudosubstorms. We suggest that these differences are important factors for determining whether ballooning instability causing current disruption grows in a wide area, that is, whether the initial action develops into a substorm or subsides as a pseudosubstorm.

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Section: Acknowledgmentsmentioning

confidence: 99%

A Statistical Study of Near‐Earth Magnetotail Evolution During Pseudosubstorms and Substorms With THEMIS Data

et al. 2020

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“…AcknowledgmentsThis work was supported by NASA grants NNX17AL22G and 80NSSC18K0657, NSF grants PLR-1341359 and AGS-1737823, and AFOSR FA9559-16-1-0364. Data access and processing was done using SPEDAS V3.1; seeAngelopoulos et al (2019). Merrimack College gratefully acknowledges support from NSF awards 1716192 and 1742693.…”

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confidence: 99%

The 2‐D Structure of Foreshock‐Driven Field Line Resonances Observed by THEMIS Satellite and Ground‐Based Imager Conjunctions

et al. 2019

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Recent studies of Pc5‐band (150–600 s) ultralow frequency waves found that foreshock disturbances can be a driver of dayside compressional waves and field line resonance, which are two typical Pc5 wave modes in the dayside magnetosphere. However, it is difficult to find spatial structure of dayside Pc5 waves using a small number of satellites or ground magnetometers. This study determines 2‐D structure of dayside Pc5 waves and their driver by utilizing coordinated observations by the THEMIS satellites and the all‐sky imager at South Pole during two series of Pc5 waves on 29 June 2008. These Pc5 waves were found to be field line resonances (FLRs) and driven by foreshock disturbances. The ground‐based all‐sky imager at South Pole shows that periodic poleward moving arcs occurred simultaneously with the FLRs near the satellite footprints over ~3° latitude and had the same frequencies as FLRs. This indicates that they are the auroral signature of the FLRs. The azimuthal distribution of the FLRs in the magnetosphere and their north‐south width in the ionosphere were further determined in the 2‐D images. In the first case, the FLRs distribute symmetrically in the prenoon and postnoon regions with out‐of‐phase oscillation as the odd toroidal mode in the equatorial plane. In the second case, the azimuthal wavelengths of the 350–500 s and 300–450 s period waves were ~8.0 and ~5.2 Re in the equatorial plane. It also shows a fine azimuthal structure embedded in the large‐scale arcs, indicating that a high azimuthal wave number (m ~ 140) mode wave coupled with the low‐wave number FLRs.

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“…The algorithm was implemented through an IDL procedure, attached in the supporting information for this article and available from a GitHub repository (https://github.com/unh-mms-rogers/IDR_tail_search), leveraging the SPEDAS library (Angelopoulos et al, 2019) for loading and version control of all MMS data files. The procedure checks for each of the stages described above by way of conditional Boolean statements applied to each 3-min time series data segment.…”

Section: Algorithm Implementationmentioning

confidence: 99%

Numerical Algorithm for Detecting Ion Diffusion Regions in the Geomagnetic Tail With Applications to MMS Tail Season 1 May to 30 September 2017

2019

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We present a numerical algorithm to identify ion diffusion regions (IDRs) in the geomagnetic tail and test its applicability. We use five criteria applied in three stages. (i) correlated reversals (within 90 s) of Vx and Bz (at least 2 nT about 0; geocentric solar magnetospheric coordinates); (ii) detection of Hall electric and magnetic field signatures; and (iii) strong (≥10 mV/m) electric fields. While no criterion alone is necessary and sufficient, the approach does provide a robust, if conservative, list of IDRs. We use data from the Magnetospheric Multiscale (MMS) mission spacecraft during a 5‐month period (1 May to 30 September 2017) of near‐tail orbits. We find 148 events satisfying Step 1, 37 satisfying Steps 1 and 2, and 17 satisfying all 3, of which 12 are confirmed as IDRs. All IDRs were within the X‐range [−24, −15] RE and the majority occurred during traversals of a tailward moving X‐line. Eleven of 12 IDRs were on the duskside despite approximately equal residence time in the plasma sheet (56.5% dusk vs. 43.5% dawn). MMS could identify signatures of four quadrants of the Hall B‐structure in three events and three quadrants in seven events. The events we report commonly display Vx reversals greater than 400 km/s in magnitude, normal magnetic field reversals often >10 nT in magnitude, maximum DC | trueE→|, which are often well in excess of the threshold for Stage 3. Our results are then compared with the set of IDRs identified by visual examination from Cluster in the years 2000–2005.

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The Space Physics Environment Data Analysis System (SPEDAS)

Cited by 370 publications

References 43 publications

A Statistical Study of Near‐Earth Magnetotail Evolution During Pseudosubstorms and Substorms With THEMIS Data

A Statistical Study of Near‐Earth Magnetotail Evolution During Pseudosubstorms and Substorms With THEMIS Data

The 2‐D Structure of Foreshock‐Driven Field Line Resonances Observed by THEMIS Satellite and Ground‐Based Imager Conjunctions

Numerical Algorithm for Detecting Ion Diffusion Regions in the Geomagnetic Tail With Applications to MMS Tail Season 1 May to 30 September 2017

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