long-term solar change and solar influences on global and...

Mike Lockwood

(University of Reading,

& Space Science and Technology Department,

STFC/Rutherford Appleton Laboratory )

Long-term solar change and

solar influences on global

and regional climates

STFC Introductory Space Plasma Course, St. Andrews 31st August 2016

Solar Outputs

Global Effects

Regional & Seasonal Effects

Solar Variability:

Effects on Climate?

Solar Variability

The Future

Solar Outputs

weakly modulated (~0.1%) by

magnetic field in photosphere

Visible/IR

UV modulated (~1%) by magnetic fields threading the

lowest solar atmosphere (chromosphere)

EUV strongly modulated (~50%) by magnetic fields in the

solar atmosphere (corona)

X-Rays fully dependent on (modulated ~90%) by magnetic fields

in the solar atmosphere (corona)

Solar wind ~65% modulated over the solar magnetic cycle

Cosmic Rays ~20% - 40% modulated (at 10 - 1GeV) by solar

magnetic field irregularities in heliosphere

SEPs ~100% modulated by transient magnetic fields in solar

flares & ahead of interplanetary coronal mass ejections

visible IR

UV

EUV & X-rays

Energy generated in core by nuclear fusion Energy transfer across radiation zone (mainly by

gamma rays) takes 107 years

Energy transfer across convection zone by large

scale motions (takes several months) Photosphere emits visible and IR radiation Chromosphere emits UV radiation Corona emits EUV and X-ray radiation

CORE

RADIATIVE ZONE

ZONE CONVECTIVE

6104 K

Solar Temperatures & Emissions different wavelengths are emitted from different heights

6103 K

1.5106 K

1106 K

3106 K

Height above photosphere (km)

T

em

pera

ture

(K

)

0 2000 4000 6000 8000

106

105

104

“braiding” of magnetic field

by photospheric motions is

central to coronal heating

Visible UV EUV EUV X-Rays

Earth’s atmosphere

10-6

10-5

10-4

10-3

10-2

10-1

1

density (kg m-3)

100

80

60

40

20

0 -100 -80 -60 -40 -20 0 20 40 60

10-3

10-2

10-1

1

10

102

103

tropopause

stratopause

mesopause

stratosphere

mesosphere

thermosphere

altitude (km)

pressure

(mbar)

temperature (C)

O3

a

turbopause i

winter pole

summer pole

O3 = ozone layer a = aerosols js = jet stream

c = cloud i = ionosphere

troposphere c js

Electromagnetic solar inputs

10-6

10-5

10-4

10-3

10-2

10-1

1

density (kg m-3)

100

80

60

40

20

0 -100 -80 -60 -40 -20 0 20 40 60

10-3

10-2

10-1

1

10

102

103

tropopause

stratopause

mesopause

stratosphere

mesosphere

thermosphere

altitude (km)

pressure

(mbar)

temperature (C)

O3

a

turbopause

winter pole

summer pole



troposphere

Visible/IR UV EUV X-Rays

i

c js

The Sun’s e-m

radiation spectrum

Close to a 5770K

blackbody radiator

Emitted flux

F = Tsun4

1 and surface

temperature of Sun

TS = 5770K

Implications of

high CZ mass

0

log ( T / TC ) TC = T(r = 0)

-4

CZ

RZ

core

CZ contains ~31028kg (M

/60)

thermal timescale of the CZ as

a whole = timescale for its

warming or cooling, 105 yr

Switch off source at base of CZ

and in t = 100 yr, Tsun changes

by 1- exp(t/) = 0.001

F = Tsun4 so that

F/F = (Tsun/Tsun)4

= 0.9994 = 0.996

i.e. F changes by just 0.4%

3Mm

(0.004R

)

R

Corpuscular solar inputs

10-6

10-5

10-4

10-3

10-2

10-1

1

density (kg m-3)

100

80

60

40

20

0 -100 -80 -60 -40 -20 0 20 40 60

10-3

10-2

10-1

1

10

102

103

tropopause

stratopause

mesopause

stratosphere

mesosphere

thermosphere

altitude (km)

pressure

(mbar)

temperature (C)

O3

a

turbopause

winter pole

summer pole



troposphere

Cosmic Rays SEPs Solar wind

i

c js

Tracking events from the

Sun to Earth using STEREO

A (“ahead”) B (“behind”) HI2-A HI1-A CA CB HI1-B HI2-B

HI2-A HI2-B

HI1-A HI1-B CA CB

B (“behind”) A (“ahead”)

Start of the Story: the associated flare

CME hit Earth on 14th July 2000

The Bastille Day Storm

Flare and SEPs Solar Terrestrial Physics Summer School

“Halo”

(Earthbound)

form most

easily seen in

C2 difference

movie ►

The Bastille Day Storm CME

seen by SoHO/Lasco C2 and C3 Coronographs

Tomographic reconstruction from interplanetary scintillations


CMEs seen by IPS

Ground-level

enhancement (GLE)

of solar energetic

particles seen

between Forbush

decreases of galactic

cosmic rays caused

by shielding by the

two CMEs

Here seen at

stations in both poles

(McMurdo and Thule)

Neutron Monitor counts

Forbush

decrease

caused

by 1st

CME

GLE Forbush

decrease

caused by

CME

associated

with GLE

nm

co

un

ts


GCRs and SEPs


SEP Proton Aurora – seen by Image FUV-SI12

Polar Cap NO

From SEP event of April 2002

► Northern hemisphere ► Southern hemisphere

TIMED observations of 5.3 m NO radiative fluxes (Wm2)

(Mlynczak et al., 2003)

Storm Event – SEP Ozone Depletion


Ozone Depletion (TOMS )

Energetic Particles

Galactic Cosmic Rays

Generated at the shock

fronts ahead of

supernovae

Protons up to iron ions,

travelling at close to

speed of light

Three shields protect us

on Earth’s surface:

The heliospheric field

Earth’s magnetic field

Earth’s atmosphere

Galactic Cosmic Ray Spectra

Galactic Cosmic Rays

The coronal

source flux is

dragged out

by the solar

wind flow to

give the

heliospheric

field which

shields Earth

from galactic

cosmic rays

Cosmic Rays Anticorrelation with

sunspot numbers

Sunspot Number

Huancauyo –

Hawaii neutron

monitor counts

(>13GV)

Climax neutron

monitor counts

(>3GV)

CMEs, CIRs, GCRs and SEPs

Both CME fronts and

CIRs shield Earth

from Galactic

Cosmic Rays by

scattering

Both CME fronts and

CIRs generate SEPs

Both CMEs and CIRs

are more common

and more extensive

at sunspot maximum

CME

CIR

Geomagnetic Shielding of GCRs

(Cut-off rigidity)

low rigidity

(e.g. 1 GV)

high rigidity

(e.g. 13GV)

Rigidity is a measure of

the extent to which cosmic

rays maintain their direction

of motion

It is measured in GV (v c,

nGV rigidity energy

nGeV)

Higher rigidity GCRs can

penetrate to lower

geomagnetic latitudes

minimum rigidity that can be seen at a magnetic latitude called

the “rigidity cut-off” (e.g.) for Hawaii and Huancayo 13GV for

Climax (Boulder) 3GV

At highest latitudes rigidity cut-off set by atmosphere at 1GV

Cosmic ray tracks in a bubble chamber

OCEANS

STRATOSPHERE (2/3)

GALACTIC COSMIC RAYS

BIOMASS

TROPOSPHERE (1/3)

ICE SHEETS

10Be + AEROSOL

( ~1 year) ( ~1 week)

14C • 1/2 = 5370 yr

• < qG > = 2

atoms cm-2s-1

10Be • 1/2 = 1.5×106 yr

• < qG > = 0.018

atoms cm-2s-1

14C & 10Be: spallation products from O, N & Ar

14C+014C0 ; 14C0+0H14C02+ H

Solar Output

Signals in Troposphere

at most, very small “bottom up”

signals reported in troposphere

Visible/IR

UV clear heating effects in statosphere (ozone layer) – may

have subtle “top down” effects on troposphere

EUV dominates thermosphere, no evidence nor credible

mechanism for coupling to the troposphere

X-Rays major effects in thermosphere, no evidence or credible

mechanism for for coupling to the troposphere

Solar wind same as for EUV and X-rays

Cosmic Rays proposed modulation of cloud cover: effect on surface

temperatures depends critically on cloud height

SEPs destroy ozone so may have similar effects to UV

Solar Outputs

Global Effects


Solar Variability:

Effects on Climate?

Solar Variability

The Future

Sunspots

Galileo

Galilei’s

sketches

Image from the Solar and Heliospheric

Observatory (SoHO) spacecraft

Sunspots Data Series IAU (International Astronomical Union)

press release #1508 (2015)

“The new record

has no significant

long-term upward

trend in solar

activity since 1700,

as was previously

indicated.”

(WRONG!)

“This suggests that

rising global

temperatures since

the industrial

revolution cannot

be attributed to

increased solar

activity. (RIGHT

FOR WRONG

REASONS!)

Sunspots Data Series Why new composite is wrong: daisy-chaining

calibration with bad linear regressions

B has lower visual acuity than A (telescope has lower resolution, less good-focus or

higher scattered light levels, or keenness of B’s eyesight or how conservative

he/she was in making the subjective decisions to define spots and spot groups, or

local atmospheric conditions less helpful (greater aerosol concentrations, more

mists or thin cloud). Assumption that RA = 0 when RB = 0 is wrong. Also effect on

B’s data worse at low solar activity – gives non linearity.

Open Solar Flux, FS

(Lockwood et al., ERL, 2010)

► best-fit open

solar flux, FS

Open Solar Flux, FS

(allowing for longitudinal structure in solar wind)

from geomagnetic data (Lockwood et al., 2009)

model (Vieira & Solanki, 2010)

from IMF data

► use both

range and

hourly mean

geomagnetic

data

► model

emergence

from sunspot

number with

two time

constants for

decay of

open flux

Millennial Variation composite (25-year means) from cosmogenic

isotopes 14C & 10Be by Steinhilber et al. (2008)

Year AD

So

lar

Mo

du

lati

on

Pa

ram

ete

r,

(MV

)

-6000 -4000 -2000 0 2000

1000

800

600

400

200

0

composite from Solanki et al., 2004; Vonmoos et al., 2006 & Muscheler et al., 2007

we are still within recent grand maximum

Solar Cycles

in sunspot group number, RG & 10Be abundance

Maunder

Minimum Dalton

Minimum

Total Solar Irradiance Observations Systematic errors and drifts

due to instrument degradation

To

tal S

ola

r Ir

rad

ian

ce

(W

m-2

)

1980 1984 1988 1992 1996 2000 2004 2008

ORIGINAL DATA

0.3%

1374

1370

1358

1366

1362

Solar Irradiance Composites Errors and drifts corrected

by intercalibration

To

tal S

ola

r Ir

rad

ian

ce

(W

m-2

)

PMOD Composite

ACRIM Composite

IRMB Composite

1980 1984 1988 1992 1996 2000 2004 2008

Total solar irradiance changes and

magnetic field emergence

Dark sunspots and bright

faculae are where magnetic

field threads the solar surface

Enhanced field B

blocks upward heat flux F

Gives temperatures:

Sunspot Darkening

B

Heat Flux F

Quiet Bright Spot Bright Quiet

Sun Ring P U P Ring Sun

Quiet Sun TQS 6050K

Bright ring TBR 6065K

Penumbra TP 5680K

Umbra TU 4240K

Photosphere

Convection Zone

Enhanced field raises magnetic pressure and depresses

thermal pressure NkBT

Facular Brightening The Bright Wall Model

N falls & the O = 2/3

contour is depressed by

z 50 km

flux tube small enough

for radiation from walls

to maintain internal

temperature T

bright walls most visible

at small for which Tf

6200 K

z

B B

F

< 250 km

Sunspot Darkening &

Facular Brightening

Photospheric magnetic

field magnetogram data

3-component TSI model using magnetogram data

Use model contrasts of umbrae, penumbrae and faculae CU, CP, and

CF (>0 for brightenings) as a function of position on disc and

wavelength (w.r.t quiet Sun, so CQS(,) = 0)

Contrasts independent of time t – the time dependence is all due to

that in the filling factors which are functions of and t, but not .

Every pixel in the magnetogram for time t that falls on the visible disc is

then classified as either umbra, penumbra, facula or quiet Sun to derive

U, P, F. Limb darkening function is LD(,) and the quiet-Sun intensity

(free of all magnetic features) of the disc centre is IO

ITS(,t = (Rs2 / R1

2) IO LD(,) [ P(,t){CP(,)+1} +

U(,t){CU(,)+1} + F(,t){CF(,)+1} + {1-P(,t)-U(,t)-P(,t)} ]d

1

0

penumbrae

umbrae faculae quiet Sun

4-component model

(Solanki et al., 2003)

Total Solar

Irradiance

reconstructions

using 4

component

model

(“SATIRE”) with

magnetograms

for 1996-2002

from the MDI

satellite,

compared with

SoHO TSI data

Stellar Analogues:

The use of the S index

► S index is a measure of stellar flux in the Ca I H and

K lines (chromospheric emissions associated with

magnetic field threading the solar surface)

► related to facular brightening term in TSI by Lean et

al. (1992)

Stellar Analogues: The distribution of S index values

150

100

50

0 0.10 0.12 0.14 0.16 0.18 0.20 0.22

average S index, < S > ►

num

ber

of occurr

ences ►

1/3 non-cyclic stars

Sun’s Maunder minimum? 2/3 cyclic stars

present-day Sun?

► Baliunas &

Jastrow (1990).

Data from the Mt.

Wilson survey of

Sun-like stars.

► 74 “solar-type”

stars with B - V

colours in range

0.60–0.76

(0.95-1.10 MS).

← from 13 of the 74

(so a third is just 4)

Active

dynamo

Dormant

dynamo

Hoyt and Schatten used solar cycle length, L, Lean et al. and Lean used a combination of

sunspot number R and R11, Solanki and Flkigge use a combination of R and L, Lockwood and

Stamper used Fs. All use stellar analogue except Lockwood and Stamper

TSI Reconstructions

1600 1700 1800 1900 2000

Lean, 2000

Lean et al., 1995

1368

1366

1364

1362 Hoyt & Schatten, 1993

Solanki & Fligge 1999

Tota

l S

ola

r Ir

rad

iance (W

m-2

)

Stellar Analogues: Recent re-evaluation of distribution

100

0 0.13 0.15 0.17 0.19 0.21 0.23 0.25

S Index ►

150

50 num

ber

of occurr

ences ►

1/3 non-cyclic stars

(not bimodal)

2/3 cyclic stars

► Hall and

Lockwood (2004)

Lowell survey of

300 stars with

colours in the

same range as

adopted by B&J

(0.60 B-V 0.76)

TSI Reconstructions To

tal S

ola

r Ir

rad

ian

ce

(W

m-2

)

1600 1700 1800 1900 2000

1368

1366

1364

1362

Lockwood and Stamper, 1999

Hoyt & Schatten, 1993

Solanki & Fligge 1999

Foster, Lockwood, 2004

Lean, 2000

Lean et al., 1995

Wang et al., 2005

Krivova et al., 2007

The Sun’s e-m

radiation spectrum

Variability is low in

parts of spectrum

power is greatest

Variability is highest

in UV which is

absorbed in the

stratosphere

Solar UV data intercalibration (Lockwood, JGR, 2011)

► e.g. = 164.5nm

► data from different satellite and instruments

► note the “SOLSTICE gap” between the end of UARS/SOLSTICE data and start of SORCE/SOLSTICE data.

► UARS/SUSIM data not reliable at >205nm

UV O3 production

and heating

(Rozonov et al., 2008)

► Modelled effects of UV in

1nm bands over a solar cycle

based on Lean UV spectrum

model, SL()

(top) maximum to minimum temperature changes T

(bottom) maximum to minimum ozone density change [O3]

T

[O3]

Solar maximum-solar minimum

UV difference spectrum

(Harder et al, GRL, 2009, Haigh et al., 2010)

SORCE SIM

SORCE Solstice, Ss()

Krivova, SK()

Lean, SL()

► SS() / SL() 10

in the = 270nm -

300nm band (in

green)

► Supported by

satellite

observations of

change in O3

abundance

Solar Outputs

Global Effects


Solar Variability:

Effects on Climate?

Solar Variability

The Future

Greenhouse

LW SW

Albedo

Clouds

Climate

Cosmic Rays & Clouds

Low cloud: Albedo

effect exceeds

greenhouse trapping

effect

High Cloud:

greenhouse trapping

effect exceeds albedo

effect

GCR fluxes fell over 1900-1985 so to contribute to warming

Earth, they would have to generate low altitude cloud (so

reduced albedo exceeds reduced greenhouse trapping)

% g

lob

al clo

ud c

over

an

om

aly

Global Cloud Cover Variation

3

2

1

0

-1

-2

-3

1985 1990 1995 2000 2005

(Svensmark, 1998)

ISCCP D2 low-altitude

cloud anomaly

N.B. 1- error in D2

dataset is about 2%

% g

lob

al clo

ud c

over

an

om

aly


3

2

1

0

-1

-2

-3

1985 1990 1995 2000 2005

(Marsh & Svensmark, 2003)

offset?

% g

lob

al clo

ud c

over

an

om

aly


(Gray et al., 2010) 3

2

1

0

-1

-2

-3

1985 1990 1995 2000 2005

New Evidence: Diffuse Fraction (DF)

► Intensity in direct sunlight = IDI

► Intensity in shade = ISH

► Diffuse fraction, DF = ISH / IDI

► Measured at a

number of sites since

the 1950s

Idi

Ish Idi

CLOUD

CLEAR SKY

ISH 0

DF = ISH / IDI 0

CLOUDY SKY (and/or aerosols)

ISH IDI

DF = ISH / IDI 1

Ish

detector

shield

0.65 0.70 0.75 0.80 0.85

Mean DF for C < 36 105 hr -1

Aberporth Aldergrove Beaufort Park Camborne Cambridge Eskdalemuir Jersey Kew Lerwick Stornaway

0.85

0.80

0.75

0.70

0.65

Mean D

F for

C

≥

36

10

5 h

r -1


Harrison and Stephenson, Proc Roy. Soc (2006)

Average DF for various

stations in UK since 1950’s

Sorted according to the

galactic cosmic ray flux

(>3GeV) at Climax, C

Mean DF for C > threshold

consistently exceeds mean DF

for C < threshold

Clouds

Climate

Climate System

Volcanoes Man-Made

Cryosphere

Ocean

Permafrost Sea Level

Sun

Biosphere

El Niño

Albedo

Greenhouse

LW SW

Albedo

Greenhouse

LW SW

Albedo

Clouds

Climate

Volcanoes Man-Made

Cryosphere

Ocean


Sun

Biosphere

El Niño

Albedo

Geological Effects

Greenhouse

LW SW

Albedo

Clouds

Climate

Volcanoes Man-Made

Cryosphere

Ocean


Sun

Biosphere

El Niño

Albedo

Anthropogenic Effects

Greenhouse

LW SW

Albedo

Clouds

Climate

Volcanoes Man-Made

Cryosphere

Ocean


Sun

Biosphere

El Niño

Albedo

Solar Influence

Greenhouse

LW SW

Albedo

Clouds

Climate

Volcanoes Man-Made

Cryosphere

Ocean


Sun

Biosphere

El Niño

Albedo

Short-Timescale Ocean Energy Exchange

Observed Global

Surface Air

Temperature

Anomaly, TOBS

ENS0 N3.4 index

Anomaly, E

Mean Optical

Depth (AOD) at

550 nm, V

Cosmic Ray

Counts at

Climax, C

Anthropogenic

forcing, A,

(greenhouse

gases, aerosols,&

land use change)

fit to

observed

GMAST

anomaly

obtained

using the

Nelder-

Mead

simplex

(direct

search)

method

(Lockwood, 2008)

1955 1965 1975 1985 1995 2005

Global Mean Air Surface Temperature

Observed, TOBS

Fitted, TFIT

Weighted

contributions

to best fit

variation, Tp

(uses Climax

GCR counts

to quantify

solar effect)

(updated from Lockwood, 2008)

Solar El Nino Volcanoes Anthro Total

20

15

10

5

0

-5

Tem

pe

ratu

re T

ren

d (

10

-3 K

yr

-1)

1987-present

using GCRs (C), r = 0.89

(Lockwood, 2008)

Solar Outputs

Global Effects


Solar Variability:

Effects on Climate?

Solar Variability

The Future

Regional Analysis

(Lean and Rind, 2008)

solar UV

heated equatorial

stratosphere

jet stream

mild westerlies blocked

cold north- easterlies

eddy refraction and/or

polar vortex changes

“Top-down” Solar Modulation

Atlantic blocking events

(Plelly and Hoskins, 2003)

► blocking events are large long-lived anticyclones which

disrupt easterly flow of storms, bifurcating the jet stream and,

in winter, causing cold winds from the east over Europe

Example at 12UT, 21 Sept, 1998: on the potential vorticity PV=2 surface

(a) 250-hPa geopotential height (b) potential temperature (K)

Blocking Intensity Indices

► Lejenäs and Økland (1983) required a region of easterly

winds and used Z(, o+/2)Z(, o/2) where Z is a

constant height geopotential, is the longitude and the

latitude

► Barriopedro et al. (2006,2008) used BI = 100

{[Z(o, o)/RC]1} where RC = {Z(o+, o) Z(o, o)} / 2

► Pelly and Hoskins (2006,2008)

used mean potential

temperature in the red and

green areas of the plot B =

(2/) d (2/) d

o+/2

o o

o/2

ERA-40 Analysis of Blocking Index

(change of terciles relative to whole set)

► sorted using open solar flux FS High/Low solar activity gives reduced/enhanced (up to 8%) blocking over east Atlantic and Europe (symmetric effect) Consistent and localised effect Grey area shows significance from Monte-Carlo technique > 95%

(Woollings et al, GRL.,2010)

ERA-40 Analysis of DJF temperatures &

circulation (difference of high and low tercile subsets)

► sorted using open solar flux FS Low solar activity gives lower surface temperatures in central England Effect much stronger in central Europe Analysis shows a distinct system to NAO

(Woollings et al, GRL.,2010; see also Barriopedro et al., JGR, 2008)

SEP effects in polar atmosphere?

Seppala et al. JGR – in press

difference in surface temperature T between high Ap

(>14) and low (Ap <14) years

years with major stratospheric warmings are excluded

agrees rather well with model predictions of effects of NOx

events in winter stratosphere transmitted to the troposphere

(e.g. Rozanov et al.)

► Northern hemisphere

Observed solar maximum-solar

minimum temperatures

► ECMWF ERA40 + operational reanalysis zonal means

Dark and light areas show 1% and 5% significance levels

(Frame and Gray, J.Clim.,2010)

Modelled solar maximum-solar

minimum temperatures

► Heating effect only

(no [O3] change)

(Ineson et al, Nature Geosci., 2011)

► HADGEM3rev1.1

GCM, 85 atmos and

42 ocean levels.

► Uses the SORCE

max-min UV spectrum

SS()

► Increased meridional temperature gradient increase in westerly flow

Modelled solar maximum-solar

minimum zonal wind speed

► Modelled

downward and

northward

propagation of

easterly wind

anomaly (by

Eliassen-Palm

flux divergence)

(Ineson et al, Nature Geosci., 2011)

► seen in

ERA40+ data

► c.f. Kodera

and Kuroda,

2002; Matthes

et al.,2006

January 2010

Maunder Minimum & the

“Little Ice Age”

a). Sunspot Number

b). Open Solar Flux

c). Reconstructed Northern Hemisphere Temperatures

MM

MM

LIA 1.0

0.5

0

-0.5 1700 1800 1900 2000

T

NH (C

)

January 1683

A Frost Fair on the

Thames in London.

The river froze in

central London

relatively frequently

during the Maunder

Minimum of sunspot

activity

Same scene – once

thought to be painted

by Jan (a.k.a.John)

Wycke (son of

Thomas), but now

generally listed as

“unknown artist”

“An exact and lively

mapp … with an

alphabetical explanation

of the most remarkable

figures”


mapp … with an



figures”

H. The Musick Booth


mapp … with an



figures”

I. The Printing Booth


mapp … with an



figures”

E. The Roast Beefe

Booth


mapp … with an



figures”

N. The Boat drawne with

a Hors


mapp … with an



figures”

Q. The Bull Baiting


mapp … with an



figures”

C. The Tory Booth


mapp … with an



figures”

Z. London Bridge

Central England

Temperature (CET)

Manley (1953,1974)

Parker et al (1992)

Monthly 1659 to present

Maintained by UKMO

Longest instrumental temperature record

in the world

Representative of a roughly triangular area

between Bristol, Lancashire & London

Central England

Temperature (CET)

Winter Means (DJF)

show upward drift

(linear) rate of rise

dTann/dt = 0.37 C c-1

Frost Fairs on the Thames

e.g. Winter 1683/4.

usually attributed to Dutch

artist Thomas Wijk who

died in 1677! N.B. notice how warm

the next year was!

Frost Fairs on the Thames

The last one was

1813/14. Painted

by Luke Clenell

(1781 – 1840 )

Thames Freezing Over

N.B. in 1825 London

Bridge demolished –

acted as a salt water

barrage

plus embankment

increased flow rate

1963 Thames at

Windsor

Thames Freezing Over

Scatter Plots

r = 0.23 r = 0.25

Scatter Plots

FS = f

TDJF

n

Distribution tests for various f

Solar Outputs

Global Effects


Solar Variability:

Effects on Climate?

Solar Variability

The Future

Predictions for the future

“It is not important to predict the future, but

it is important to be prepared for it”

Pericles,

Athenian orator, statesman and general

c. 495 – 429 BC

“It is not important to know the future,

but to shape it”

Antoine de Saint Exupéry,

French writer and aviator

1900 - 1944

“Prediction is very hard — especially when

it’s about the future”

Niels Bohr

Danish Physicist

1885 – 1962

“Never make predictions — especially

about the future”

Lawrence Peter (Yogi) Berra

American Baseball Player, coach and author

1925 – Who also said “I never said half the things I really said."

"It ain't over ‘till it's over"

"When you come to a fork in the road, take it."

"It's like déjà vu all over again"

"Always go to other peoples' funerals, otherwise they won't come to yours."

“I don’t have nightmares about my team – you’ve got to be able to sleep before

you can have nightmares”

Millennial Variation composite (25-year means) from cosmogenic

isotopes by Steinhilber et al. (2008)

Year AD

So

lar

Mo

du

lati

on

Pa

ram

ete

r,

(MV

)

-6000 -4000 -2000 0 2000

1000

800

600

400

200

0

composite from Solanki et al., 2004; Vonmoos et al., 2006 & Muscheler et al., 2007

we are still within recent grand maximum

Superposed epoch study of the

end of grand maxima

time after end of grand maximum (yrs)

800

600

400

200

0

end of grand solar maximum

-80 -40 0 40 80

(24 events in 9000 yrs)

So

lar

Mo

du

lati

on

Pa

ram

ete

r,

(MV

)

Future TSI Variation?

using the

relationship of

TSI and GCRs

& relationship

between solar

cycle amplitude

and the mean

(Jones, Lockwood and Stott, JGR 2011)

Lean (2000)

Krivova et al. (2007)

Lean (2009)

Maximum 1 Mean -1 Minimum

GMAST Predictions – EBM tuned to

HadCM3

(Jones, Lockwood and Stott, JGR in press, 2011)

Lean (2000)


Lean (2009)

use B2 SRES

emissions scenario

no future volcanic

forcing

solar responses have

been scaled to match a

maximum possible

solar cycle amplitude of

0.1K.

Maximum 1 Mean -1 Minimum

Model predictions for future

► model, HadGEM2-CC

(carbon cycle)55, with CMIP5

forcings

► a ‘high top’ model with 60

vertical levels up to 84 km

► horizontal resolution 1.875

longitude 1.25 latitude.

► ocean resolution is 11,

increasing in the tropics to

0.30.3, & 40 vertical levels

► time varying ozone incudes

solar variation effect

(Ineson et al, Nature Comms 2015)

<TSI> = 1336.2 Wm-2, <UV SSI> = 27.4 Wm-2

Global change

(Ineson et al, Nature Comms 2015)

► 2050–2099 Annual mean

surface temperature response

► Difference in near-surface

temperature (in C) between

CTRL-8.5 and (top) EXPT-A and

(b) EXPT-B

► Solid white contours give 95%

confidence interval from Mann-

Witney (non-parametric) test.

► GMAST change 0.13 C for

EXPT-A & 0.12 C for EXPT-B (2

year’s offset in greenhouse gas

driven change)

EXPT-A CTRL-8.5

EXPT-B CTRL-8.5

•Winter NH change southward shift

of jet stream and decreased/increased)

blocking over southern/northern Europe

► Differences

between CTRL-8.5

& (top) EXPT-A,

(bottom) EXPT-B

for 2050 –2099

► negative

AO/NAO-like mean

sea-level pressure

pattern

► enhanced cooling

in north Eurasia

and eastern U.S.

► stronger effects

for EXPT-B

sea-level

pressure (hPa) precipitation

(mm day-1).

near-surface

temperature (C)

European Winter (DJF)

Temperature change

► Differences

relative to mean for

1971 –2000

► 33-year running

means

► shaded areas 1

standard error

► representative

concentration

pathway (RCP)

simulations using

HadGEM2-ES

model

CTRL-85

EXPT-A

EXPT-B

RCP4.5

Winter NH change: number of

frost days (daily mean AST < 0C)

(a) Difference between

CTRL-8.5 for 2050–2099

and 1971–2000

(b) Difference between

CTRL-8.5 & EXPT-A 2050–

2099

(c) Difference between

CTRL-8.5 & EXPT-B 2050–

2099

(white dots show areas with

>95% confidence level)

European Winter Temperature

Variablity

► Great year-to-year

variability about

trends in all cases

► Winter (December

to January) northern

European (10W–

40E, 48–75N)

near-surface

temperatures (in C)

for land points only

annual ensemble members of EXPT-A

(blue), EXPT-B (red) and CTRL-8.5 (black)

time to…

STOP!!!

but questions most welcome, now, over dinner, or down the pub after

► Earlier

reconstructions

based on tree-

ring data

► also now use

marine

sediment,

speleothem,

lacustrine, ice

cores, coral,

and historical

documents

Ensemble of 11 reconstructions

based on temperature proxy data

► Use the

median of the

11 for 1659-

1850

► use upper

and lower

deciles for

1659-1850,

Tmax and

Tmin to test for

effect of

reconstruction

Ensemble of 11 reconstructions

based on temperature proxy data

Tmax

Tmin

median T

Major SEP Events

From nitrates in polar ice sheets

► SEP (>30MeV) fluence from ice sheet data (McCracken, 2001)

► Open flux model from sunspot number (Solanki et al., 2000)

► Open flux derived from aa index (Lockwood et al., 1999)

1972 event Carrington flare

Maunder

minimum

ERA-40+ Re-analysis interval

► open solar flux

► F10.7 radio flux

► GCR modulation

parameter

► Total Solar

Irradiance (TSI)

(PMOD Composite)

Solar change and global mean

temperatures pre-1985

► sunspot number,

R

► solar cycle length, L

► open solar magnetic flux, FS

► cosmic ray counts, C

► total solar irradiance, TSI

►GMAST anomaly, T

(10Be – Climax data)

HADCrut3v


Lockwood et al. (2009)

Steinhilber et al. (2008)

Solar cycle means (Lockwood and Fröhlich, 2009)


temperatures post-1985

PMOD data composite -Fröhlich (2009)

► sunspot number, R





►GMAST anomaly, T

Climax n.m. data

Interplanetary data



temperatures 1880-2001

► sunspot number,

R





►GMAST anomaly, T


Ground-level

enhancement (GLE)

of solar energetic

particles seen

between Forbush

decreases of galactic

cosmic rays caused

by shielding by the

two CMEs

Here seen at

stations in both poles

(McMurdo and Thule)

Neutron Monitor counts

Forbush

decrease

caused

by 1st

CME

GLE Forbush

decrease

caused by

CME

associated

with GLE

nm

co

un

ts


GCRs and SEPs

Scatter Plots

TDJF =

FS

n

Distribution tests for various

Student’s t test of means (parametric); Mann-Whitney U

(Wilcoxon) test & Kolmogorov–Smirnov test of “medians”)

Recent

Data

► radial IMF,

|Br|

► sunspot

number, R

► Kp

geomagnetic

index

► PMOD

composite

of TSI

Recent

Data

► radial IMF,

|Br|

► sunspot

number, R

► Kp

geomagnetic

index

► PMOD

composite

of TSI

Space Age

Data

long-term solar change and solar influences on global and...

Documents