The Mansurov effect: Statistical significance and the role of autocorrelation | Journal of Space Weather and Space Climate

Open Access

Issue		J. Space Weather Space Clim. Volume 12, 2022


Article Number		11
Number of page(s)		10
DOI		https://doi.org/10.1051/swsc/2022008
Published online		08 April 2022

Benjamini Y, Hochberg Y. 1995. Controlling the false discovery rate: A practical and powerful approach to multiple testing. J Roy Statist Soc: Ser B (Methodol) 57: 289–300. https://doi.org/10.1111/j.2517-6161.1995.tb02031.x. [Google Scholar]
Bretherton CS, Widmann M, Dymnikov VP, Wallace JM, Bladé I. 1999. The effective number of spatial degrees of freedom of a time-varying field. J Climate 12(7): 1990–2009. https://doi.org/10.1175/1520-0442(1999)012<1990:TENOSD>2.0.CO;2. [CrossRef] [Google Scholar]
Burns GB, Tinsley BA, French WJR, Troshichev OA, Frank-Kamenetsky AV. 2008. Atmospheric circuit influences on ground-level pressure in the Antarctic and Arctic. J Geophys Res 113: D15112. https://doi.org/10.1029/2007JD009618. [CrossRef] [Google Scholar]
Frank-Kamenetsky AV, Troshichev OA, Burns GB, Papitashvili VO. 2001. Variations of the atmospheric electric field in the near-pole region related to the interplanetary magnetic field. J Geophys Res 106: 179–190. https://doi.org/10.1029/2000JA900058. [CrossRef] [Google Scholar]
Frederick JE, Tinsley BA, Zhou L. 2019. Relationships between the solar wind magnetic field and ground-level longwave irradiance at high northern latitudes. J Atmos Sol-Terr Phys 193: 105063. https://doi.org/10.1016/j.jastp.2019.105063. [CrossRef] [Google Scholar]
Freeman MP, Lam MM. 2019. Regional, seasonal, and inter-annual variations of Antarctic and sub-Antarctic temperature anomalies related to the Mansurov effect. Environ Res Commun 1: 111007. https://doi.org/10.1088/2515-7620/ab4a84. [CrossRef] [Google Scholar]
Gonzalez ALC, Gonzalez WD. 1987. Periodicities in the interplanetary magnetic field polarity. J Geophys Res 92(A5): 4357–4375. https://doi.org/10.1029/JA092iA05p04357. [CrossRef] [Google Scholar]
Kabin K, Rankin R, Marchand R, Gombosi TI, Clauer CR, Ridley AJ, Papitashvili VO, DeZeeuwk DL. 2003. Dynamic response of Earth’s magnetosphere to B_y reversals. J Geophys Res 108: 1–13. https://doi.org/10.1029/2002JA009480. [Google Scholar]
Lam MM, Tinsley BA. 2016. Solar wind-atmospheric electricity cloud microphysics connections to weather and climate. J Atmos Sol-Terr Phys 149: 277–290. ISSN: 1364-6826. https://doi.org/10.1016/j.jastp.2015.10.019. [CrossRef] [Google Scholar]
Lam MM, Chisham G, Freeman MP. 2013. The interplanetary magnetic field influences mid-latitude surface atmospheric pressure. Environ Res Lett 8: 045001. https://doi.org/10.1088/1748-9326/8/4/045001. [CrossRef] [Google Scholar]
Lam MM, Chisham G, Freeman MP. 2014. Solar-wind-driven geopotential height anomalies originate in the Antarctic lower troposphere. Geophys Res Lett 41: 6509–6514. https://doi.org/10.1002/2014GL061421. [CrossRef] [Google Scholar]
Lam MM, Freeman M, Chisham G. 2018. IMF-driven change to the Antarctic tropospheric temperature due to the global atmospheric electric circuit. J Atmos Sol-Terr Phys 180: 148–152. https://doi.org/10.1016/j.jastp.2017.08.027. [CrossRef] [Google Scholar]
Mansurov SM, Mansurova LG, Mansurov GS, Mikhnevich VV, Visotsky AM. 1974. North-south asymmetry of geomagnetic and tropospheric events. J Atmos Terr Phys 36(11): 1957–1962. https://doi.org/10.1016/0021-9169(74)90182-2. [CrossRef] [Google Scholar]
Mooney P, Mulligan F, Fealy R. 2011. Comparison of ERA-40, ERA-Interim and NCEP/NCAR reanalysis data with observed surface air temperatures over Ireland. Int J Climatol 31: 545–557. https://doi.org/10.1002/joc.2098. [CrossRef] [Google Scholar]
Page DE. 1989. The interplanetary magnetic field and sea level polar atmospheric pressure. In: Workshop on mechanisms for tropospheric effects of solar variability and the quasi-Biennial oscillation, Avery SK, Tinsley BA (Eds.), University of Colorado, Boulder, CO, USA, 22 p. [Google Scholar]
Pettigrew ED, Shepherd SG, Ruohoniemi JM. 2010. Climatological patterns of high-latitude convection in the Northern and Southern hemispheres: Dipole tilt dependencies and interhemispheric comparisons. J Geophys Res 115: A07305. https://doi.org/10.1029/2009JA014956. [Google Scholar]
Rodgers JL, Nicewander AW. 1988. Thirteen ways to look at the correlation coefficient. Am Statist 42: 59–66. https://doi.org/10.1080/00031305.1988.10475524. [CrossRef] [Google Scholar]
Theiler J, Prichard D. 1996. Constrained-realization Monte-Carlo method for hypothesis testing. Phys D 94: 221–235. https://doi.org/10.1016/0167-2789(96)00050-4. [CrossRef] [Google Scholar]
Thejll P, Christiansen B, Gleisner H. 2003. On correlations between the North Atlantic Oscillation, geopotential heights, and geomagnetic activity. Geophys Res Lett 30: 1347. https://doi.org/10.1029/2002GL016598. [CrossRef] [Google Scholar]
Tinsley BA. 2000. Influence of solar wind on the global electric circuit, and inferred effects on cloud microphysics, temperature, and dynamics in the troposphere. Space Sci Rev 94: 231–258. https://doi.org/10.1023/A:1026775408875. [CrossRef] [Google Scholar]
Tinsley BA. 2008. The global atmospheric electric circuit and its effect on cloud microphysics. Rep Prog Phys 71: 66801–66831. https://doi.org/10.1088/0034-4885/71/6/066801. [CrossRef] [Google Scholar]
Tinsley BA, Zhou L, Wang L, Zhang L. 2020. Seasonal and solar wind sector duration influences on the correlation of high latitude clouds with ionospheric potential. J Geophys Res: Atmos 126: e2020JD034201. https://doi.org/10.1029/2020JD034201. [Google Scholar]
Wilks DS. 2016. “The stippling shows statistically significant grid points”: How research results are routinely overstated and over interpreted, and what to do about it. Bull Am Meteorol Soc 97: 2263–2273. https://doi.org/10.1175/BAMS-D-15-00267.1. [CrossRef] [Google Scholar]
Zhou L, Tinsley BA, Wang L, Burns GB. 2018. The zonal mean and regional tropospheric pressure responses to changes in ionospheric potential. J Atmos Sol-Terr Phys 171: 111–118. https://doi.org/10.1016/j.jastp.2017.07.010. [CrossRef] [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.