Solar cycle variations in the ionosphere of Mars as seen by multiple Mars Express data sets

<p>The loss of signal detection by the sub surface radars currently operational on Mars Express and Mars Reconnaissance Orbiter can be evidence of enhanced ionisation at lower altitudes in the Martian atmosphere as a result of solar energetic particles penetrating to these altitudes.&#160; The MARSIS instrument on Mars Express and SHARAD on MRO operate at different frequencies, with MARSIS up to 5 MHz and SHARAD between 10 and 20 MHZ.&#160; In addition MARSIS can operate in an additional mode as an Active Ionospheric Sounder, although here we focus only on the sub surface mode.&#160; We present an analysis of the data during the lifetimes of both instruments, extending from 2005 to 2018.&#160; Here we identify the radar blackouts as either total or partial and investigate their occurrence as a function of solar cycle.&#160; We find a clear solar cycle dependence with more events occurring during the solar maximum years, as expected.&#160; However, we also note the duration of events is often much longer than expected, in excess of several days, sometimes reaching 10 &#8211; 14 days.&#160; Investigation of other data sets, notably from the MAVEN SEP instrument complements the analysis.&#160; We finally compare our observations at Mars with similar observations at Earth.</p>

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On the Prediction of Solar Cycles

Solar Physics ◽

10.1007/s11207-020-01760-7 ◽

2021 ◽

Vol 296 (1) ◽

Author(s):

V. Courtillot ◽

F. Lopes ◽

J. L. Le Mouël

Keyword(s):

Solar Activity ◽

Solar Cycle ◽

Transfer Function ◽

Singular Spectrum Analysis ◽

Activity Cycle ◽

Solar Activity Cycle ◽

Planetary Motion ◽

Data Sets ◽

Solar Cycles ◽

Jovian Planets

AbstractThis article deals with the prediction of the upcoming solar activity cycle, Solar Cycle 25. We propose that astronomical ephemeris, specifically taken from the catalogs of aphelia of the four Jovian planets, could be drivers of variations in solar activity, represented by the series of sunspot numbers (SSN) from 1749 to 2020. We use singular spectrum analysis (SSA) to associate components with similar periods in the ephemeris and SSN. We determine the transfer function between the two data sets. We improve the match in successive steps: first with Jupiter only, then with the four Jovian planets and finally including commensurable periods of pairs and pairs of pairs of the Jovian planets (following Mörth and Schlamminger in Planetary Motion, Sunspots and Climate, Solar-Terrestrial Influences on Weather and Climate, 193, 1979). The transfer function can be applied to the ephemeris to predict future cycles. We test this with success using the “hindcast prediction” of Solar Cycles 21 to 24, using only data preceding these cycles, and by analyzing separately two 130 and 140 year-long halves of the original series. We conclude with a prediction of Solar Cycle 25 that can be compared to a dozen predictions by other authors: the maximum would occur in 2026.2 (± 1 yr) and reach an amplitude of 97.6 (± 7.8), similar to that of Solar Cycle 24, therefore sketching a new “Modern minimum”, following the Dalton and Gleissberg minima.

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Mars Under Primordial Solar Wind Conditions: Mars Express Observations of the Strongest CME Detected at Mars Under Solar Cycle #24 and its Impact on Atmospheric Ion Escape

Geophysical Research Letters ◽

10.1002/2017gl075446 ◽

2017 ◽

Vol 44 (21) ◽

Cited By ~ 9

Author(s):

Robin Ramstad ◽

Stas Barabash ◽

Yoshifumi Futaana ◽

Masatoshi Yamauchi ◽

Hans Nilsson ◽

...

Keyword(s):

Solar Wind ◽

Solar Cycle ◽

Mars Express ◽

Ion Escape ◽

Solar Cycle 24 ◽

Cycle 24

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Solar cycle variation of stratospheric ozone: Multiple regression analysis of long-term satellite data sets and comparisons with models

Journal of Geophysical Research Atmospheres ◽

10.1029/2006jd007107 ◽

2006 ◽

Vol 111 (D20) ◽

Cited By ~ 159

Author(s):

B. E. Soukharev ◽

L. L. Hood

Keyword(s):

Regression Analysis ◽

Solar Cycle ◽

Multiple Regression Analysis ◽

Multiple Regression ◽

Satellite Data ◽

Stratospheric Ozone ◽

Data Sets ◽

Solar Cycle Variation ◽

Cycle Variation

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Long-term evolution of sunspot magnetic fields

Proceedings of the International Astronomical Union ◽

10.1017/s1743921311015122 ◽

2010 ◽

Vol 6 (S273) ◽

pp. 126-133 ◽

Cited By ~ 12

Author(s):

Matthew J. Penn ◽

William Livingston

Keyword(s):

Solar Cycle ◽

Magnetic Fields ◽

Spectral Line ◽

Detailed Examination ◽

Temporal Variations ◽

Line Of Sight ◽

Data Sets ◽

Infrared Spectral ◽

Cycle 24 ◽

Synoptic Observations

AbstractIndependent of the normal solar cycle, a decrease in the sunspot magnetic field strength has been observed using the Zeeman-split 1564.8nm Fe I spectral line at the NSO Kitt Peak McMath-Pierce telescope. Corresponding changes in sunspot brightness and the strength of molecular absorption lines were also seen. This trend was seen to continue in observations of the first sunspots of the new solar Cycle 24, and extrapolating a linear fit to this trend would lead to only half the number of spots in Cycle 24 compared to Cycle 23, and imply virtually no sunspots in Cycle 25.We examined synoptic observations from the NSO Kitt Peak Vacuum Telescope and initially (with 4000 spots) found a change in sunspot brightness which roughly agreed with the infrared observations. A more detailed examination (with 13,000 spots) of both spot brightness and line-of-sight magnetic flux reveals that the relationship of the sunspot magnetic fields with spot brightness and size remain constant during the solar cycle. There are only small temporal variations in the spot brightness, size, and line-of-sight flux seen in this larger sample. Because of the apparent disagreement between the two data sets, we discuss how the infrared spectral line provides a uniquely direct measurement of the magnetic fields in sunspots.

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Simulating the atmospheric response to the 11-year solar cycle forcing with the UM-UKCA model: the role of detection method and natural variability

10.5194/acp-2018-129 ◽

2018 ◽

Cited By ~ 1

Author(s):

Ewa M. Bednarz ◽

Amanda C. Maycock ◽

Paul J. Telford ◽

Peter Braesicke ◽

N. Luke Abraham ◽

...

Keyword(s):

Solar Cycle ◽

Climate Model ◽

Detection Method ◽

Linear Regression Method ◽

Data Sets ◽

Atmospheric Response ◽

Atmospheric Variability ◽

Active Season ◽

Atmospheric Forcings

Abstract. The 11-year solar cycle forcing is recognised as a potentially important atmospheric forcing; however, there remain uncertainties in characterising the effects of the solar variability on the atmosphere from observations and models. Here we present the first detailed assessment of the atmospheric response to the 11-year solar cycle in the UM-UKCA chemistry-climate model using an ensemble of integrations over the recent past. Comparison of the model simulations is made with observations and reanalysis. Importantly, in contrast to the majority of previous studies of the solar cycle impacts, we pay particular attention to the role of detection method by comparing the results diagnosed using both a composite and a multiple linear regression method. We show that stratospheric solar responses diagnosed using both techniques largely agree with each other within the associated uncertainties; however, the results show that apparently different signals can be identified by the methods in the troposphere and in the tropical lower stratosphere. Lastly, we focus on the role of internal atmospheric variability on the detection of the 11-year solar responses by comparing the results diagnosed from individual model ensemble members (as opposed to those diagnosed from the full ensemble). We show overall agreement between the ensemble members in the tropical and mid-latitude mid-stratosphere-to-lower-mesosphere, but larger apparent differences at NH high latitudes during the dynamically active season. Our results highlight the need for long data sets for confident detection of solar cycle impacts in the atmosphere, as well as for more research on possible interdependence of the solar cycle forcing with other atmospheric forcings and processes (e.g. QBO, ENSO… etc.).

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A combined analysis of geomagnetic data and cosmic ray secondaries in the September 2017 space weather phenomena studies

10.5194/angeo-2018-111 ◽

2018 ◽

Cited By ~ 1

Author(s):

Roman Sidorov ◽

Anatoly Soloviev ◽

Alexei Gvishiani ◽

Viktor Getmanov ◽

Mioara Mandea ◽

...

Keyword(s):

Solar Cycle ◽

Characteristic Function ◽

Space Weather ◽

Solar Flares ◽

Geomagnetic Storms ◽

Cosmic Ray ◽

Electron Content ◽

Data Sets ◽

Total Electron ◽

Combined Analysis

Abstract. The September 2017 solar flares and the subsequent geomagnetic storms driven by the coronal mass ejections were recognized as the ones of the most powerful space weather events during the current solar cycle. The occurrence of the most powerful solar flares and magnetic storms during the declining phase of a solar cycle (including the current 24th cycle) is a well-known phenomenon. The purpose of this study is to better characterize these events by applying the generalized characteristic function approach for combined analysis of geomagnetic activity indices, total electron content data and secondary cosmic ray data from the muon hodoscope that contained Forbush decreases resulting from solar plasma impacts. The main advantage of this approach is the possibility of identification of low-amplitude specific features in the analyzed data sets, using data from several environmental sources. The data sets for the storm period on September 6–11, 2017, were standardized in a unified way to construct the generalized characteristic function representing the overall dynamics of the data sequence. The new developed technique can help to study various space weather effects and obtain new mutually supportive information on different phases of geomagnetic storm evolution, based on the geomagnetic and other environmental observations in the near-terrestrial space.

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The 11-year solar cycle in current reanalyses: a (non)linear attribution study of the middle atmosphere

Atmospheric Chemistry and Physics ◽

10.5194/acp-15-6879-2015 ◽

2015 ◽

Vol 15 (12) ◽

pp. 6879-6895 ◽

Cited By ~ 16

Author(s):

A. Kuchar ◽

P. Sacha ◽

J. Miksovsky ◽

P. Pisoft

Keyword(s):

Solar Cycle ◽

Linear Regression ◽

Middle Atmosphere ◽

Polar Vortex ◽

Reanalysis Data ◽

Support Vector ◽

Data Sets ◽

Nonlinear Approach ◽

Hypothetical Mechanism ◽

Solar Signal

Abstract. This study focusses on the variability of temperature, ozone and circulation characteristics in the stratosphere and lower mesosphere with regard to the influence of the 11-year solar cycle. It is based on attribution analysis using multiple nonlinear techniques (support vector regression, neural networks) besides the multiple linear regression approach. The analysis was applied to several current reanalysis data sets for the 1979–2013 period, including MERRA, ERA-Interim and JRA-55, with the aim to compare how these types of data resolve especially the double-peaked solar response in temperature and ozone variables and the consequent changes induced by these anomalies. Equatorial temperature signals in the tropical stratosphere were found to be in qualitative agreement with previous attribution studies, although the agreement with observational results was incomplete, especially for JRA-55. The analysis also pointed to the solar signal in the ozone data sets (i.e. MERRA and ERA-Interim) not being consistent with the observed double-peaked ozone anomaly extracted from satellite measurements. The results obtained by linear regression were confirmed by the nonlinear approach through all data sets, suggesting that linear regression is a relevant tool to sufficiently resolve the solar signal in the middle atmosphere. The seasonal evolution of the solar response was also discussed in terms of dynamical causalities in the winter hemispheres. The hypothetical mechanism of a weaker Brewer–Dobson circulation at solar maxima was reviewed together with a discussion of polar vortex behaviour.

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Total electron content in the Martian atmosphere: A critical assessment of the Mars Express MARSIS data sets

Journal of Geophysical Research Space Physics ◽

10.1002/2014ja020630 ◽

2015 ◽

Vol 120 (3) ◽

pp. 2166-2182 ◽

Cited By ~ 15

Author(s):

B. Sánchez-Cano ◽

D. D. Morgan ◽

O. Witasse ◽

S. M. Radicella ◽

M. Herraiz ◽

...

Keyword(s):

Total Electron Content ◽

Martian Atmosphere ◽

Critical Assessment ◽

Electron Content ◽

Data Sets ◽

Total Electron ◽

Mars Express

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Temporal changes in the frequencies of the solar p-mode oscillations during solar cycle 23

Proceedings of the International Astronomical Union ◽

10.1017/s1743921311015614 ◽

2010 ◽

Vol 6 (S273) ◽

pp. 389-393 ◽

Cited By ~ 6

Author(s):

E J Rhodes ◽

J Reiter ◽

J Schou ◽

T Larson ◽

P Scherrer ◽

...

Keyword(s):

Solar Activity ◽

Solar Cycle ◽

Linear Regression ◽

Temporal Frequency ◽

Power Spectra ◽

Temporal Changes ◽

Data Sets ◽

Regression Analyses ◽

Frequency Shifts ◽

Solar Cycle 23

AbstractWe present a study of the temporal changes in the sensitivities of the frequencies of the solar p-mode oscillations to corresponding changes in the levels of solar activity during Solar Cycle 23. From MDI and GONG++ full-disk Dopplergram three-day time series obtained between 1996 and 2008 we have computed a total of 221 sets of m-averaged power spectra for spherical harmonic degrees ranging up to 1000. We have then fit these 284 sets of m-averaged power spectra using our WMLTP fitting code and both symmetric Lorentzian profiles for the peaks as well as the asymmetric profile of Nigam and Kosovichev to obtain 568 tables of p-mode parameters. We then inter-compared these 568 tables, and we performed linear regression analyses of the differences in p-mode frequencies, widths, amplitudes, and asymmetries as functions of the differences in as many as ten different solar activity indices. From the linear regression analyses that we performed on the frequency difference data sets, we have discovered a new signature of the frequency shifts of the p-modes. Specifically, we have discovered that the temporal shifts of the solar oscillation frequencies are positively correlated with the changes in solar activity below a limiting frequency. They then become anti-correlated with the changes in activity for a range of frequencies before once again becoming positively-correlated with the activity changes at very high frequencies. We have also discovered that the two frequencies where the sensitivities of the temporal frequency shifts change sign also change in phase with the average level of solar activity.

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