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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
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
O3 = ozone layer a = aerosols js = jet stream
c = cloud i = ionosphere
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
O3 = ozone layer a = aerosols js = jet stream
c = cloud i = ionosphere
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
The Bastille Day Storm
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
The Bastille Day Storm
GCRs and SEPs
The Bastille Day Storm
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
The Bastille Day Storm
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
Regional & Seasonal 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
Regional & Seasonal 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
Global Cloud Cover Variation
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
Global Cloud Cover Variation
(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
Global Cloud Cover Variation
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
Permafrost Sea Level
Sun
Biosphere
El Niño
Albedo
Geological Effects
Greenhouse
LW SW
Albedo
Clouds
Climate
Volcanoes Man-Made
Cryosphere
Ocean
Permafrost Sea Level
Sun
Biosphere
El Niño
Albedo
Anthropogenic Effects
Greenhouse
LW SW
Albedo
Clouds
Climate
Volcanoes Man-Made
Cryosphere
Ocean
Permafrost Sea Level
Sun
Biosphere
El Niño
Albedo
Solar Influence
Greenhouse
LW SW
Albedo
Clouds
Climate
Volcanoes Man-Made
Cryosphere
Ocean
Permafrost Sea Level
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
Regional & Seasonal 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”
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
H. The Musick Booth
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
I. The Printing Booth
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
E. The Roast Beefe
Booth
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
N. The Boat drawne with
a Hors
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
Q. The Bull Baiting
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
figures”
C. The Tory Booth
“An exact and lively
mapp … with an
alphabetical explanation
of the most remarkable
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
Regional & Seasonal 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)
Krivova et al. (2007)
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
Krivova et al. (2007)
Lockwood et al. (2009)
Steinhilber et al. (2008)
Solar cycle means (Lockwood and Fröhlich, 2009)
Solar change and global mean
temperatures post-1985
PMOD data composite -Fröhlich (2009)
► sunspot number, R
► solar cycle length, L
► open solar magnetic flux, FS
► cosmic ray counts, C
► total solar irradiance, TSI
►GMAST anomaly, T
Climax n.m. data
Interplanetary data
Solar cycle means (Lockwood and Fröhlich, 2009)
Solar change and global mean
temperatures 1880-2001
► sunspot number,
R
► solar cycle length, L
► open solar magnetic flux, FS
► cosmic ray counts, C
► total solar irradiance, TSI
►GMAST anomaly, T
Solar cycle means (Lockwood and Fröhlich, 2009)
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
The Bastille Day Storm
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