Long-Term Solar Activity Reconstruction:

Grand Minima and Maxima

Ilya Usoskin1, Sami K. Solanki2, Gennady Kovaltsov3

1 Sodankylä Geophysical Observatory, University of Oulu, Finland2 Max-Planck-Institut for Solar System Research, Katlenburg-Lindau, Germany

3 Ioffe Physical-Technical Institute, St.Petersburg, Russia

Solar activity variations: telescopic sunspot number record

• 11-year solar cycle (Christian Horrebow 1770s; Schwabe 1843)

• Variable amplitude/envelope (Gleissberg 1944);• Maunder minimum (Hivelius; Eddy 1976);• The contemporary level is high

0

50

100

150

1600 1700 1800 1900 2000

Gro

up s

unsp

ot n

umbe

r

Solar activity in the past

1E+01E+11E+21E+31E+41E+51E+6

Years before present

Electronic

Photographic data

Sunspot counts and drawings

Aurora sightings

Naked eye sunspot observations

Cosmogenic isotopes

Geomagnetic measurements

Proxy of SA: Cosmogenic isotopes

IMF, solar wind Cosmic Rays

Geomagneticfield

• Variable solar activity expands to the Heliosphere: solar wind, interplanetary magnetic field, interplanetary transients (CME, corotation regions), etc.• Galactic cosmic rays are modulated by IMF, magnetic inhomogeneities, solar wind;• Geomagnetic field partly shields the Earth (mid- and low-latitude regions) from incoming cosmic rays;• This process is well understood and can be properly modelled (Beer, Space Sci. Rev.,

2000; Usoskin et al., Phys. Rev. Lett., 2003; Solanki et al., Nature, 2004)

SN reconstruction from 14C or 10BeSunspot numbersSunspot numbers

e.g.e.g. ModelModel by Solanki by Solanki et al. et al. (2002)(2002)

SunspotSunspot number number open open magnmagn.. fluxflux

Heliospheric paramsHeliospheric params

e.g.e.g. ModelModel by by Usoskin et al. (Usoskin et al. (2002a)2002a)

ModulModul. strength . strength CR CR intensintens. variations. variationsCR intensityCR intensity

Deposition models, Deposition models, paleomagneticpaleomagnetic modelsmodels1010Be:Be: Webber & Higbie, Webber & Higbie, 1414C: C: UsoskinUsoskin & & KromerKromerBB⊕⊕::YangYang et al. (2000), et al. (2000), KorteKorte & Constable (2005)& Constable (2005)

CosmogenicCosmogenic isotopes isotopes UsoskinUsoskin et al. (2002b)et al. (2002b) in natural archivesin natural archivesSolanki et al. (2004) , Solanki et al. (2004) , UsoskinUsoskin et al. (2004, 2007) et al. (2004, 2007)

nonlinearnonlinear

nonlinearnonlinear

Sunspot number reconstructed from 14C

0

20

40

60

80

-10000 -9000 -8000 -7000 -6000 -5000 -4000

Sun

spot

num

ber

0

20

40

60

80

-4000 -3000 -2000 -1000 0 1000 2000

Years (-BC/AD)

Sun

spot

num

ber

Smoothed Sunspot number over 11400 yr

27 Grand minima19 Grand maximacan be identified.

Minima cover1880 yr ≈ 17% of timeMaxima cover1030 yr ≈ 9% of time

Solanki,. Usoskin, Kromer, Schüssler, Beer, Nature, 2004 Usoskin, Solanki & Kovaltsov, A&A, 2007

Sunspot number statistics

0 20 40 60 80 100

1

10

100

Max

Num

ber

per

bin

<Sunspot number>

Min

Red curve: best-fit normal distribution

Waiting time distribution

100 1000

1E-4

1E-3

Diff

eren

tial d

istr

ibut

ion

Interval length (Years)100 1000

1E-4

1E-3

0.01

wai

ting

time

dist

ribut

ion

Interval length (Years)

Grand minima Grand maxima

Closer to power law (red lines) than to exponential (dotted yellow lines) � waiting time tends to show clustering of Min and Max

Durations of Minima & Maxima

50 100 1500

2

4

6

Num

ber

per

bin

Duration (Years)

0 50 100 150 200

1E-3

0.01

Diff

eren

tial d

istr

ibut

ion

Duration (Years)

Grand minima Grand maxima

Maunder Spoerer

Quasi-Bimodal Exponential

Conclusions

�� The Sun spends 17% of the time in The Sun spends 17% of the time in grand minimagrand minima, 9% in , 9% in grand grand maximamaxima. Currently the Sun is in a grand maximum.. Currently the Sun is in a grand maximum.

�� Grand Grand minimaminima//maximamaxima are not due to longare not due to long--term cyclic variations term cyclic variations but rather to stochastic/chaotic processes. but rather to stochastic/chaotic processes.

�� Waiting time distribution of occurrence of Waiting time distribution of occurrence of grand minimagrand minima and and maximamaxima deviates from an exponential distribution deviates from an exponential distribution �� typical of typical of nonnon--Poisson processes with, e.g., selfPoisson processes with, e.g., self--organized criticality or organized criticality or processes related to accumulation and release of energy.processes related to accumulation and release of energy.

�� Grand minimaGrand minima can be classified into two different types: short can be classified into two different types: short minima of minima of Maunder typeMaunder type and long minima of and long minima of SpSpöörerrer typetype..

�� Duration of Duration of grand maximagrand maxima exponentially distributed exponentially distributed �� leaving a leaving a grand maximumgrand maximum is a random process, unlike for is a random process, unlike for grand minimagrand minima

Ti-44 activity:

measure-ments vs.

model

95%95%4.4 (11)4.4 (11)M05M05--AA

4%4%20.5 (11)20.5 (11)M05M05--MM

97%97%2.44 (8)2.44 (8)S04S04

98%98%7.55(17)7.55(17)GSNGSN

Confid. levelConfid. levelχχ2 2 (DoF)(DoF)ModelModel

3

4

5

6

7

8

9

1750 1800 1850 1900 1950 2000

44Ti a

ctiv

ity (dpm

/kg) GSN

S04

M05-A

M05-M

Ti-44

/kg

)

Preliminary Preliminary results!results!

New data are New data are currently being currently being finalized and finalized and

analyzedanalyzed