andModelling
Processes
CUBASCH, R.D. CESS
,rntributors:
Bretherton;H.Cattle; J.T. Houghton;J.F.B-Mitchell; D. Randall;E. Roeckner;
D . Woods;T. Yamanouchi.
(.ONTENTS
F.recutive
Summary
I I lntroduction
('limate System
I I The Atmosphere
l l The Ocean
l l The Cryosphere
l l The Biosphere
I -5 The Geosphere
I 6 Timescales
3.5.1.I Estimateof temperature
sensitivityto CO2
-75
75
75
16
77
77
7'7
77
: -l Cloud Feedback
77
11
78
78
79
Predictability of the Climate System
80
\tethods of Predicting Future Climate
< I The Palaeo-AnalogueMethod
80
83
Radiative Feedback Mechanisms
i. I Discussionof RadiativeFeedbackMechanisms
: l Water Vapour Feedback
: .1 Snow-iceAlbedo Feedback
changes
3.5.1.2 Construction
of the analoguepattems
3.5.2 AtmosphericGeneralCirculation Models
3.-5.2.
I Physicalparameterizations
3.5.2.2 Radiationand the effect of clouds
3.-5.2.3Sub grid-scaletransports
83
83
84
84
84
8-5
3.5.2.4 Land surfaceprocesses
8-5
3.5.2.5 Boundaryconditions
86
3.-5.3OceanModels
3.5.4 CarbonCycle Models
86
86
3.-5.5Chemical Models
3.5.6 Coupled Models of the Atmosphereand the Ocean
3.5.7 Use of Models
8'7
87
87
3.5.7.1 Equilibriumresponse
experiments
88
3.5.7.2 Time-dependent
response
experiments
88
3.6 lllustrative Equilibrium Experiments
88
3.7 Summary
89
References
90
I-XECUTIVESUMMARY
' ' ..rmate systemconsistsof the five components:
atmosphere
()Cean
for interactive land surface temperatureand soil moisture are also
usually included. Representationsof the other elements of the
climate system(land-ice,biosphere)are usually included as non-
cryosphere(ice)
interactivecomponents. The resolutionof thesemodels is as yet
hiosphere
too coarseto allow more than a limited regional interpretationof
geosphere
the results.
Unfortunately, even though this is crucial for climate change
'.rndamentalprocessdriving the global climate system is
- j by incoming short-wave solar radiation and cooling by
prediction,only a few models linking all the main componentsof
the climate systemin a comprehensiveway have beendeveloped.
. .. eve infrared radiation into space. The heating is strongest This is mainly due to a lack of computer resources,since a
rrcal latitudes,while cooling predominatesat the polar coupled systemhas to take the different timescalesof the sub.
-.:.\ of each winter hemisphere.The latitudinalgradientof
systemsinto account.An atmosphericgeneralcirculation model
: drives the large-scalecirculations in the atmosphereand
on its own can be integratedon currently availablecomputersfor
. \ean, thus providing the heat transfernecessaryto balance
.tcm.
':r\ facetsof the climate systemare not well understood,and
equilibrium response;when coupled to a global ocean model
(which needsmillenniato reachan equilibrium)the demandson
severalmodel decadesto give estimatesof the variability about its
. r r f i c a n t n u m b e r o f t h e u n c e r t a i n t i e si n m o d e l l i n g
-rheric, cryosphericand oceanicinteractionsare directly due
computer time are increasedby severalorders of magnitude.The
- :!'presentation
or knowledgeof interactiveclimate feedback
' jli\ms. Such feedback mechanismscan either amplify or
resolutionneededto make regionalpredictionsdemandscomputer
. -: the climate responseresulting from a given changeof
,:: torcing.
'rder to predict changesin the climate system, numerical
.' . have been developedwhich try to simulate the different
-.lk mechanismsand the interaction between the different
-. .nentsof the climate system.
inclusion of additional sub-systemsand the refinement of
speedsseveral orders of magnitude faster than is available on
currentmachines.
It should be noted that current simulationsof climate change
obtainedby incompletemodelsmay be expectedto be superseded
as soon as more complete models of the climate system become
available.
An alternativeto numerical model simulations is the palaeo-
:.ir most climate simulations have been carried out with
analoguemethod (the reconstructionof past climates).Although
:::;al AtmosphericGeneralCirculation Models (AGCMs)
. - have been developed or derived from weather forecast
its usefulnessfor climate prediction is questionedbecauseof
:... For investigationsof climate change due to increased
' ':or.lsegas concentrations,they have generally been run
:J with simple representationsof the upper ocean and, in
problemsinvolving data coverageand the validity of past climate
forcing compared with future scenarios, the method gives
valuable information about the possible spectrum of climate
changeand it provides information for the broadercalibration of
i iases, with more detailed, but low resolution, dynamical atmosphericcirculationmodels in different climate regimes.
: . of the ocean to its full depth. Relatively simple schemes
!' r ttc esses qnd M ode llinp
/J
: I Introduction
: aim of this section is to provide background
. rr'r\tandingof the climate system,to explain someof the
--nical terms used in climate research(i.e., what is a
-'-.rcnt and what is an equilibrium response),and to
--rrbe how climate change can be predicted. In the
:r'd spaceavailableto this Sectionit is impossibleto
-' more than a brief descriptionof the climate systemand
::c'diction. The discussionwill thereforebe limited to
' :rost relevantaspects.More detaileddescriptionare
-.:J in the referencesand in, for example, the books of
, -". {1975)and Houghton(ed) (1984).
". .cction has beendevotedto feedbackprocesseswhich
' riuce the non-linearitiesinto the climate system, and
" ' - r account for many of the difficulties in predicting
rtr'change.Climatemodelsand their technicaldetails
. .rirgg5ssdwhere relevantto subsequentSectionsof the
{ a,n. For more detailedinformation the readeris refened
-: book by Washingtonand Parkinson(1986).
' '
illustratesome of the difficulties and uncertainties
biosphere
geosphere
The fundamental processesdriving the global climate
systemare heatingby incoming short wave solar radiation
and the cooling by long-wave radiation into space.The
heating is strongestat tropical latitudes,while cooling
predominatesin the polar regionsduring the winter of each
hemisphere.The latitudinal gradient of heating drives the
atmosphereand oceancirculations;theseprovide the heat
transfernecessaryto balancethe system(seeSimmonsand
Bengtsson,1984).
3.2.1 The Atmosphere
The bulk of the incoming solar radiationis absorbednot by
the atmospherebut by the Earth'ssurface(soil, ocean,ice).
Evaporation of moisture and direct heating of the surface
generate a heat transfer between the surface and the
atmospherein the form of latent and sensible heat. The
atmospheretransportsthis heat meridionally,mainly via
" - r arise in climate changepredictions from numerical transientweather systemswith a timescaleof the order of
r i ' l : w e c o m p a r e r e s u l t s f r o m t w o i n d e p e n d e n t days.
The following processesare importantin determiningthe
rncal simulationsat the end of the Section.
behaviour of the atmospheric component of the climate
system:
j ('limate System
Turbulent transferof heat . momentum and moisture at
;limate system(see Figure 3.1) consistsof the five
the surfaceofthe Earth:
3)nents:
The surfacetype (i.e., its albedo),which determinesthe
proportionof incoming to reflectedsolar radiation.
atmosphere
Latent
heat release when water vapour condenses;
(rcean
clouds, which play an important role in reflecting
cryosphere
Changesof
solar radiation
ATMOSPHERE
terrestrial
radiation
H z O ,N z , O z , C O z , O s ,e t c
Aerosol
precipitation
atmosphere-land
coupling a t m o s p h e r e - i c ec o u p l i n g
BIOMASS
C h a n g e so f
' - r s g h e r i cc o m p o s i t i o n
SEA_ICE
.orpiing +
evaporation
heat exchange
windstress
atmosphere-ocean
coupling
C h a n g e so f l a n d f e a t u r e s ,
o r o g r a p h y ,v e g e t a t i o n ,
a l b e d o ,e t c .
OCEAN
EARTH
C h a n g e so f o c e a n b a s i n
s h a p e ,s a l i n i t y e t c .
f, :aure3.1: Schematicillustrationof the componentsof the coupled atmosphere-ocean-ice-land
climatic system.The full arrows are
-:plesof extemal processes,and the open arrows are examples of internal processesin climatic change (from Houghton,
1984).
Processesand Modellins 3
/o
incoming solar short-waveradiationand in absorbing
and emitting long-waveradiation;
The radiative cooling and heatingof the atmosphereby
CO2, water vapour,ozoneand other tracegases;
Aerosols(such as volcanic dust), the orbital parameters,
mountainrangesand the land-seadistribution.
Atmospheric processesare also influencedby a number
o f f e e d b a c k m e c h a n i s m sw h i c h i n v o l v e i n t e r a c t i o n s
betweenthe atmosphericprocessesthemselves(radiation
from the atmosphereinto the interior of the oceanby thc
physical pump mechanism (described in the previour
Section) caused by differences in the partial pressureof
carbon dioxide in the ocean and the lowest layers of thc
atmosphere. Furthermore the annual ventilation of thc
seasonalboundary layer from the surface mixed-layer
controls the efficiency of the biological pump by which
ocean plankton convert dissolved carbon dioxide into
particulatecarbon,which sinks into deep water. Thesetwo
pumps are responsiblefor extracting carbon dioxide from
the global carbon cycle for periods in excessof a hundred
years.The oceanbranchof the carboncycle involves a flur
of carbon dioxide from the air into the sea at locationr
where the surfacemixed layer has a partial pressureof CO1
lower than the atmosphereand vice versa.Mixed-layer
partial pressureof CO2 is depressedby enhancedsolubiliSin cold water and enhancedplankton productionduring the
spring bloom. The rate of gasexchangedependson the airseadifferencein partial pressureof CO2 and a coefficierr
and clouds, for example) and betweentheseprocessesand
the underlying surface. Such feedback mechanismsare
discussedin more detailin 3.3.1.
The problemsconcemingthe impactof humanactivities
on the greenhouseeffect has broadenedin scope from a
CO2 climate problem to a trace gas climate problem
(Ramanathanet al., 1987).The climatic effects of trace
gases are strongly governed by interactions between
chemistry,radiation and dynamics' The natureof the trace
gas radiative heating and the importance of chemical- which increaseswith wind sPeed.
radiativeinteractionshas beenalreadydiscussedin Section
The following processescontrol the the climate responsc
2.
of the ocean:
3.2.2 The Ocean
The oceanalso plays an essentialrole in the global climate
system.Over half of the solar radiationreachingthe Earth's
surfaceis first absorbedby the ocean,where it is storedand
redistributedby ocean currents before escaping to the
atmosphere,largely as latent heat of evaporation,but also
as long-wave radiation. The currents are driven by the
exchangeof momentum,heat and water betweenthe ocean
and atmosphere.They have a complicated horizontal and
vertical structure determined by the pattern of winds
blowing over the seaand the distributionof continentsand
submergedmountainranges.The vertical structureof the
oceancomprisesthree layers:
The SeasonalBoundary Layer, mixed annually from the
surface,is less than 100 metresdeep in the tropics
and reacheshundredsof metresin the sub-polarseas
(other than the North Pacific) and severalkilometres
in very small regionsof the polar seasin most years;
The Warm Water Sphere (permanentthermocline)'
ventilated(i. e., exchangingheat and gases)from the
seasonalboundarylayer, is pusheddown to depthsof
many hundreds of metres in gyres by the
convergenceof surface (Ekman) currents driven
directly by the wind; and
The Cold Water Sphere (deep ocean), which fills the
bottom 807oof the ocean'svolume, ventilated from
the seasonalboundarylayer in polar seas.
The ocean contains chemical and the biological
mechanismswhich are important in controlling carbon
dioxide in the climate svstem.Carbondioxide is transferred
The small-scale(of order 50 km) transienteddiesinsi&
the ocean influencethe structureof permanentgyrer
and streams and their interaction with submerged
mountain ranges. The eddies also control the
horizontal dispersionof chemicals(such as CO2f
dissolvedin seawater.
The small-scale(tens of kilometres)patchesof deep
winter convection in the polar seas and thc
northernmost Dart of the North Atlantic, w
transport heat and dissolved carbon dioxide belor
one kilometre into the deep reservoir of the
water sphere,and the slow currents which circu
the newly implantedwater aroundthe world ocean.
The more extensive mechanism of thermocl
ventilationby which someof the water in the su
mixed-layer flows from the seasonalboundary
into the warm water sphere reservoir of the
which extendsfor severalhundredsof metres
most of the ocean'ssurfacearea.
The global transport of heat, freshwater and dissol
chemicals carried by ocean currents which dictate
global distributions of temperature,salinity, sea
and chemicalsat the sea surface'Fluctuationsin
larse-scalecirculation have modulatedthesepa
over years and decades.They also control
regional variations in sea surface properties !v
affect climate at this scale.
The biological pump in the seasonalboundary layer
which microscopicplants and animals(the
consumesomeof the carbondioxide dissolvedin
seawaterand sequesterthe carbon in the deep
i' rttr-essesand Modelling
away from the short term (up to a hundred years)
interactionsbetweenoceanand atmosphere.
).-l The Cryosphere
'-' rerrestrialcryospherecan be classified as follows
i
r:r'rsteiner.
1984):
r
I
D
D
I
d
n
!r
E
al
D
bc
1r.
:'r'l
rjc
fft-'
F'J
t|. l
okc:
:f.r
h:. i.
f ..'r
influencethe global sealevel.
\lountain glaciersare a small part of the cryosphere.
They also representa freshwaterreservoirand can
thereforeinfluencethe sealevel. They are usedas an
importantdiagnostictool for climate changesince
they respond rapidly to changing environmental
conditions.
i'crmafrost affects surface ecosystems and river
discharges.It influencesthe thermohalinecirculation
of the ocean.
lr: ':. C
\ aln-
t\'.,'u
s,.tr r1l
atc thc
si'.r-lCt
; ir. ttr
tJllJ!-n1
f\'. lhC
,i :i t;h
interacting with the biosphere) and in underground
reservoirs,or transportedas run-off to different locations
where it might influence the oceancirculation, particularly
in high latitudes. The soil interactswith the atmosphereby
exchangesof gases,aerosolsand moisture, and these are
influencedby the soil type and the vegetation,which again
are strongly dependenton the soil wetness.Our present
knowledge about these strongly interactiveprocessesis
limited and will be the tarset of future research(seeSection
i c a s o n a l s n o w c o v e r , w h i c h r e s p o n d sr a p i d l y t o
atmosphericdynamics on timescalesof days and
Ionger. In a global context the seasonalheat storage I I ) .
in snow is small. The primary influence of the
cryospherecomes from the high albedo of snow 3.2.6 Timescales
coveredsurfaces.
While the atmospherereactsvery rapidly to changesin its
ir'a ice. which affectsclimate on time scalesof seasons forcing (on a timescaleof hours or days), the oceanreacts
and longer. This has a similar effect on the surface more slowly on timescalesranging from days (at the
heat balance as snow on land. It also tends to surfacelayer) to millennia in the greatestdepths.The ice
decouplethe oceanand atmosphere,since it inhibits cover reacts on timescalesof days for sea ice regions to
the exchangeof moisture and momentum. In some millennia for ice sheets.The land processesreact on
regions it influencesthe formation of deep water timescalesof days up to months,while the biospherereacts
massesby salt extrusionduring the freezingperiod on time scalesfrom hours (planktongrowth) to centuries
and by the generation of fresh water layers in the (tree-growth).
meltingperiod.
..c sheetsof Greenlandand the Antarctic, which can be
consideredas quasi-permanenttopographicfeatures. 3.3 Radiative Feedback Mechanisms
They contain 80o/oof the existing fresh water on the 3.3.1 Discussion of Radiative Feedback Mechanisms
globe, thereby acting as a long-term reservoir in the Many facetsof the climate systemare not well understood,
hydrologicalcycle. Any changein size will therefore and a significantnumberof the uncertaintiesin modelling
r. .::C
.rl ar
77
) 1 The Biosphere
. hiosphereon land and in the oceans(discussedabove)
:rols the magnitudeof the fluxes of severalgreenhouse
..'\. including COz and methane, between the
' ' ) \ p h e r e ,t h e o c e a n sa n d t h e l a n d . T h e p r o c e s s e s
'lved are sensitive to climatic and environmental
-trtions,so any changein the climate or the environment
: . increasesin the atmosphericabundanceof CO2) will
Jc'rrc€the atmospheric abundance of these gases. A
.,rleddescriptionof the feedbacksand their respective
:nitudescan be found in Section10.
atmospheric,cryospheric and oceanic interactions are
directly due to interactiveclimate feedbackmechanisms.
They can either amplify or damp the climate response
resultingfrom a given climate forcing (Cessand Potter,
1 9 8 8 ) . F o r s i m p l i c i t y , e m p h a s i sw i l l h e r e b e d i r e c t e d
towards global-meanquantities,and the interpretation of
c l i m a t e c h a n g e a s a t w o - s t a g ep r o c e s s :f o r c i n g a n d
response.This has proved useful in interpretingclimate
feedback mechanismsin general circulation models. It
should, in fact, be emphasizedthat the conventional
concept of climate feedback applies only to global mean
quantitiesand to changesfrom one equilibrium climate to
another.
As discussedin Section2, the radiativeforcing of the
system,AQ, is evaluatedby holding all
surface-atmosphere
fixed, with G = 4 Wm-2 for an
parameters
other climate
instantaneousdoubling of atmosphericCO2. It readily
follows (Cess et al., 1989) that the change in surface
climate, expressedas the change in global-mean surface
temperatureATs, is relatedto the radiative forcing by ATs
= l" x AQ, where l, is the climate sensitivityparameter
T =
[. ,': br
l;ll ritrll I
lc .:r llE
:F \-c3tr
).5 The Geosphere
-' land processes play an important part in the
:rological cycle. These concern the amount of fresh
:!'r stored in the ground as soil moisture (thereby
AF/ATs - AS/ATs
where F and S denoterespectivelythe global-meanemitted
infrared and net downward solar fluxes at the Top Of the
I
78
Processesand Modelting 3
Atmosphere (TOA). Thus AF and AS are the climatechange TOA responsesto the radiative forcing AQ. An
increasein l" thus representsan increasedclimate change
due to a given radiativeforcing AQ (= AF - AQ).
The definition of radiative forcing requires some
clarification. Strictly speaking,it is defined as the change
in net downward radiative flux at the tropopause,so that
for an instantaneous
doubling of CO2 this is approximately
4 Wm-2 and constitutes the radiative heating of the
system.If the stratosphereis allowed
surface-troposphere
to respondto this forcing, while the climate parametersof
the surface-troposphere
system are held fixed, then this 4
Wm-2 flux change also applies at the top of the
atmosphere.It is in this context that radiative forcing is
usedin this section.
A doubling of atmosphericCO2 servesto illustrate the
use of l, for evaluating feedback mechanisms.Figure 3.2
s c h e m a t i c a l l yd e p i c t s t h e g l o b a l r a d i a t i o n b a l a n c e .
Averaged over the year and over the globe, there is 340
Wm-2 of incident solar radiation at the TOA. Of this,
roughly 30Vo,or 100 Wm-2, is reflectedby the surfaceatmospheresystem.Thus the climate system absorbs240
Wm-2 of solar radiation,so that under equilibrium
conditions it must emit 240 Wm-2 of infrared radiation.
The CO2 radiativeforcing constitutesa reductionin the
emitted infrared radiation, since this 4 Wm-2 forcing
represents
a heatingof the climate system.Thus the CO2
GlobalRadiation
Budget
|
doubling results in the climate system absorbing 4 Wm-2
more energythan it emits, and global warming then occurs
so as to increase the emitted radiation in order to reestablishthe Earth's radiation balance.If this warming
produced no change in the climate system other than
temperature,then the system would return to its original
radiation balance, with 240 Wm-2 both absorbed and
emitted. In this absenceof climate feedbackmechanisms.
AF/ATs = 3.3 Wm-2 K-1 (Cesset al., 1989) while AS/ATs
= 0, so that 1,= 0.3 Km2 W- l ' tt in turn follows that ATs =
), x AQ = l.2"C.If it were not for the fact that this warming
|
I
I
I
I
I
I
I
I
I
I
introducesnumerous interactivefeedback mechanisms.
I
then ATs = 1.2"C would be quite a robust global-mean
I
quantity. Unfortunately, such feedbacksintroduce con- I
siderableuncertaintiesinto ATs estimates.Three of the I
commonly discussedfeedbackmechanismsare described
I
i n t h ef o l l o w i n gs u b - s e c t i o n s .
I
3.3.2 WaterVapourFeedback
I
The best understoodfeedbackmechanismis water uapour
I
feedback,and this is intuitively easyto comprehend.For I
illustrativepurposesa doubling of atmosphericCO2 wifl
I
::il":ilJT:H*
.T;;:il"::ll::*il:i'i;tlI
j::,"^""?.'"T,lffi
ff:il:l?,
:1"1';,T,'l;;"
;J,H#.'
ilinTI"JH::
i:uffi:,.'.1'
il:lff:
;: I
(amprirvin*
a positive
|;:flJffii?;,,:u"'nt
I
#"""n"1&,:,ffi:
:J:,,
;TI
;TJ;;:,ff;i:
lncidentSolar
340 Wm-2
to quantify the temperaturedependenceof the water vapour I
t:::::Hilil::'-"T:T",::T;';T
ReflectedSolar
100 Wm-2
CLIMATESYSTEM
AbsorbedSolar
240 Wm'z
--sr.
\ - a
it.'\
\ \
Emittedlnfrared
240 Wm'z
Absorbed
Instantaneous
C02
elnr rhlina
wuvrrrrY
NewEquilibrium
with
no otherchanoe
Emitted
240wm-2 236Wm2
240Wm-2 240Wm'2
Figure 3.2: Schematicillustrationof the global radiationbudget
at the top of the atmosphere.
from thepriorvalueof 3.3Wm-2K-l to 2.3wm-2 r-1. I
This in turnincreases
l, from 0.3 Km2 W- I to O.+gKm2 I
I;:Ti+::'i:;:::Hn
:# Jffi::",f,il,^,
I
;tT:l,:iJI
il:'r#,
ffjT;:fi
ilJJH#:r#:i
I
:tJl"lT
ilt:,ff:il?,njT;lH.;
:J:;",l,H
I
i f;iJ:;T
:',i1,.'
Til'JIJH
ill ll;,i."ll+
HI
as appearswithin the expressionfor ),, this results io I
ilffffi1
snow-ice albedo feedback,by which a warme
lesssnowandicecover,
resulting
in a r"rrr"n"i,i,i;i*
I
Pro ce sses and M odellinc
79
^ rch in turn absorbsmore solarradiation.For simulations
s hich the carbon dioxide concentration of the
':rosphereis increased, general circulation models
- duce polar amplification of the warming in winter, and
. is at least partially ascribed to snow-ice albedo
:Jback. The real situation, however, is probably more
':rplex as, for example, the stability of the polar
'-:ospherein winter also plays a part. Illustrations of
,*-ice albedo feedback, as produced by general
'-ulation models,will be given in Section3.5. It should
' \)me in mind, however,that there is a needto diagnose
i
nature of this feedbackmechanismmore
\lnteractive
t.1 Cloud Feedback
-.Jbackmechanismsrelated to clouds are extremely
:rplex. To demonstratethis, it will be useful to first
' .ider the impact of clouds upon the presentclimate.
-:rmarizedin Table 3.1 are the radiative impacts of
rds upon the global climate system for annual mean
.:Jitions. Theseradiativeimpactsrefer to the effect of
"clear-sky"Earth; as will shortly be
,tls relative to a
.-ribed, this is termedcloud-radiativeforcing.
. hc'presenceof clouds heatsthe climate systemby 3l
"' ::-l throughreducingthe TOA infraredemission.Note
. .imilarity to trace-gasradiativeforcing, which is why
impact is referred to as cloud- radiative forcing.
rtrughcloudscontributeto the greenhousewarming of
:limate system,they alsoproducea coolingthroughthe
.:ction
and reductionin absorptionof solarradiation.As
.:t()nstrated
in Table 3.1, the latter processdominates
-': the former. so that the net effect of clouds on the
r l l g l o b a l c l i m a t e s y s t e mi s a l 3 W m - 2 r a d i a t i v e
, .rn,e.As discussedbelow with respectto cloud feedback
':rponents,cloud-radiativeforcing is an integratedeffect
. trned by cloud amount, cloud vertical distribution,
.rtl optical depth and possibly the cloud droplet
. : : i b u t i o n( W i g l e y ,1 9 8 9 ; C h a r l s oent a l , 1 9 8 7 ) .
\lthough clouds produce net cooling of the climate
.:c'm.this must not be construedas a possiblemeansof
file 3.1: Infrared, solar and net cloud-radiativeforcing
tF t. Theseare annual-meanvalues.
Infrared CRF
3l Wm-2
Solar CRF
- 44Wm-2
CRF
- 13 Wm-2
Net
offsetting global warming due to increasing greenhouse
gases.As discussedin detail by Cesset al. (1989),cloud
feedbackconstitutesthe change in net CRF associatedwith
a change in climate. Choosing a hypothetical example, if
climate warming caused by a doubling of CO2 were to
result in a changein net CRF from -13 Wm-2 to -l I Wm-2,
then this increasein net CRF of 2Wm-2 would amplify the
4 Wm-2 initial CO2 radiativeforcing and would so act as a
positivefeedbackmechanism.It is emphasizedthat this is a
hypothetical example, and there is no a priori meansof
determiningthe sign of cloud feedback.To emphasizethe
complexity of this feedbackmechanism,threecontributory
processesare summarizedas follows:
Cloud Amount: If cloud amountdecreasesbecauseof
global warming. as occurs in typical general
circulation model simulations,then this decrease
reducesthe infrared greenhouseeffect attributed to
clouds.Thus as the Earth warms it is able to emit
infrared radiation more efficiently, moderating the
warming and so acting as a negative climate
feedbackmechanism.But there is a relatedpositive
feedback;the solar radiationabsorbedby the climate
s y s t e m i n c r e a s e sb e c a u s et h e d i m i n i s h e d c l o u d
amountcausesa reductionof reflectedsolarradiation
by the atmosphere.There is no simple way of
appraisingthe sign of this feedbackcomponent.
of cloudswill
Cloud Altitude: A verticalredistribution
a l s o i n d u c e f e e d b a c k s .F o r e x a m p l e , i f g l o b a l
warming displacesa given cloud layer to a higher
a n d c o l d e r r e g i o n o f t h e a t m o s p h e r e t, h i s w i l l
producea positive feedbackbecausethe colder cloud
will emit less radiationand thus have an enhanced
greenhouseeffect.
Cloud Water Content: There has been considerable
r e c e n t s p e c u l a t i o nt h a t g l o b a l w a r m i n g c o u l d
increasecloud water content,thereby resulting in
brighter clouds and hence a negative component of
cloud feedback.Cess et al. (1989) have recently
s u g g e s t e dt h a t t h i s e x p l a n a t i o n i s p r o b a b l y a n
oversimplification. In one case, they demonstrated
that this negative solar feedback induces a
compensatingpositive infrared feedback.In a more
recent study they further indicate that in some
models the net effect might thereby be that of
positive feedback (see also Schlesinger and
Roeckner.1988.Roeckneret al.. 1987).
The abovediscussionclearly illustratesthe multitude of
complexities associatedwith cloud feedback, and the
uncertainties due to this feedback will further be
emphasizedin Section3.5. In that both cloud and snow-ice
albedo feedbacks are geographical in nature, then these
feedback mechanismscan only be addressedthrough the
numericalcirculationmodels.
use of three-dimensional
and Modelling 3
Processes
80
A number of statistical test have been devised to
of climate changesignals(v. Storch
The prediction of change in the climate system due to optimize the detection
"climate forecasting". In the &Zwiers, 1988;Zwiers, 1988;Hasselmann,1988;Santer
changesin the forcing is called
1990)(seeSection8).
climate system the slow components (for example the and Wigley,
of
Studies the completedchangefrom one mean stateto
oceanic circulation) are altered by the fast components(for
"equilibrium response"studies.Studies
e x a m p l e t h e a t m o s p h e r e ) ( H a s s e l m a n n , 1 9 76 ; anotherare called
of the climate change due to an
Mikolajewicz and Maier Reimer, 1990)' which again are of the time evolution
also be time dependent,are
might
which
forcing,
altered
influenced by the slow components'so that the complete
"transientresponse"experiments.
systemshowsa considerablevariancejust by an interaction called "weather
systems"in the oceanhave much smaller
The
of all componentsinvolved. This effect is an illustration of
"naturalvariability".
horizontal scales(less than one hundred kilometres) than in
the large-scalefeaturesof the world
Taking the climate systemas a whole, we note that some the atmosphereleaving
to be non-chaotic. The successof
elementsof the systemare chaotic,viewed on a century to ocean circulation
oceanographydepends on that fact.
millennium time scale, while other parts are remarkably classical dynamical
of transienttracersinto thc
penetration
the
of
Observations
stableon those time scales.The existenceof these (in the
ocean currents are stable
large-scale
the
that
show
time frame considered) stable components allows ocean
several decades. Palaeo-oceanographic
prediction of global change despite the existence of the over periods of
that the currents and gyres adjusted
chaotic elements.The chaotic elements of the climate evidence shows
age cycle. That evidenceand theoreticd
ice
to
the
system are the weather systemsin the atmosphereand in smoothly
understandingof the large-scaleoceancirculation suggestr
the ocean.
dealing,in the ocean,with a predictable
The weathersystemsin the atmospherehave such a large that we are indeed
least on timescalesof decades.The questionir
horizontalscalethat it is necessaryto treat the whole of the system,at
existence of predictability in the ocean
the
atmosphericcirculation as chaotic; neverthelessthere are whether
of the Earth'sclimate systemmakesthe systen
stable elementsin the atmosphereas witnessedby the component
predictable as a whole. However, this seems to be r
smooth seasonal cycle in such phenomena as the
working hypothesis, which receives somc
temperaturedistributionsover the continents'the monsoon, reasonable
the smooth transient responsesimulated\
storm tracks, inter-tropical convergence zone, etc. That support from
models (seeSection6).
ocean-atmosphere
stability gives us hope that the responseof the atmospheric coupled
climate (including the statisticsof the chaotic weather
systems)to greenhouseforcing will itself be stableand that
3.5 Methods Of Predicting Future Climate
the interactionsbetween the atmosphereand the other
have been taken to predict the futurt
elementsof the climate systemwill also be stable,even Two approaches
climate:
though the mechanisms of interaction depend on the
3.4 Predictability Of The Climate System
I
weathersYStems.
This leads to the common assumptionused in climate
prediction,that the climate systemis in equilibrium with its
forcing. That means,as long as its forcing is constantand
the slowly varying componentsalter only slightly in the
time scaleconsidered,the mean stateof the climate system
will be stableand that if thereis a changein the forcing, the
mean statewill changeuntil it is again in balancewith the
forcing. This stateis describedas an equilibrium state;the
transition between one mean and another mean state is
called a transientstate.
The time-scaleof the transitionperiod is determinedby
the adjustment time of the slowest climate system
component,i. e., the ocean. The stable("quasi stationary")
behaviourof the climate systemgives us the opportunityto
detect changes by taking time averages.Because the
intemal variability of the systemis so high, the averaging
interval has to be long comparedto the chaoticfluctuations
to detect a statisticallysignificant signal which can be
attributedto the externalforcing.
a)
b)
"analoguemethod", which tries to estimatefuturt
the
climate changefrom reconstructionsof past climater
using palaeo-climaticdata,
climate simulationswith numericalmodels (GCM sr
of the atmosphericgeneral circulation, which hart
been derived from weather forecast models. Thel
include representationsof the other elementsof thc
climate system (using ocean models' land surfac
models, etc).which have varying degreesof sopbistication. A comprehensive list of the modelr
employed and the researchgroups involved can be
found in Table 3.2(a)and (b).
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' Processesand Modellinp
t.-;.1 The Palaeo-Analogue Method
. :r: method has two distinct and rather independentparts.
:c first derives an estimate of global temperature
,.rritivity to atmosphericCO2 concentrationsbasedon
.:tmatesof CO2 concentrationsat varioustimes in the past
83
mean annual precipitation were reconstructedfor each of
the above three epochs (see Figures 1.3, 1.4 and 7.5).
Estimates of the mean temperaturesover the Northern
Hemisphereexceededthe temperatureat the end of the preindustrialperiod (the l9th century) by approximately l" ,2"
r.l the corresponding global average temperatures,
, :rustedto allow for past changesin albedo and solar
'rrtaflt. In the secondpart regionalpatternsof climate are
-'-onstructedfor selected past epochs, and they are
- i.rrded as analoguesof future climates under enhanced
--ir'nhouseconditions. For a further discussionof the
,'rhod,seefor exampleBudyko and Izrael ( 1987).
and 3-4'C during the mid-Holocene,Eemian and Pliocene
respectively.These periods were chosen as analoguesof
future climate for 2000, 2025 and 2050 respectively.
Although the nature of the forcing during theseperiods
was probably different, the relative values of the mean
latitudinal temperaturechangein the Northem Hemisphere
for eachepochwere similar in eachcase(Figure 3.3). Note
howeverthat the observationalcoveragewas ratherlimited,
' I .I Estimate of' temperature sensitivity to CO2 c:hanges especiallyfor the Eemian when the land-baseddata came
''i'rc'are threestages(Budyko et al., 1987)
essentially from the Eastern Hemisphere (see Section
1.2.2). Conelationswere also calculatedbetweenestimated
determiningthe global mean changesfor pastpalaeo- temperatureanomalies for 12 regions of the Northern
c l i m a t e s . T h i s i s d o n e f o r f o u r p e r i o d s ( E a r l y Hemispherein each of the three epochs.Thesewere found
Pliocene,early and middle Miocene, Palaeocene- to be statisticallysignificant in most cases,despitethe
Eocene and the Cretaceous). The temperature limited quality and quantity of data in the earlierepochs.
obtained
changesare basedon isotopictemperatures
(
1
9
6
6
)
a n d m a p s d e r i v e db y S i n i t s y n
by Emiliani
(1965,1961)(seeBudyko, 1982).
subtracting the temperaturechange attributed to
changesin the solar constantwhich is assumedto
have increasedby 57o every billion years, and to gol 3
changesin surface albedo. A lo/o increasein solar
o)
c
constantis assumedto raise the global mean surface (u
-c
temperatureby l.4oC. The changesin albedo are o 2
derivedfrom the ratio of land to ocean,and each0.01
f
reductionin albedois assumedto have raisedglobal (E
m e a n t e m p e r a t u r eb y 2 ' C . T h e s e c o r r e c t i o n s q ' 1
a
contribute to between 25Vo and 507o of the total
E
o
change.
0
relatingthe residualwarming to the estimatedchange
10N
30N
50N
70N
. he CO2
i n a t m o s p h e r i c C O 2 c o n c e n t r a t i o n sT
Latitude
concentrationsare derived from a carbon cycle
model. The concentrationsduring the Eocene are
O
estimated to be more than five times greater than :,
present, and for the Cretaceousnine times greater q 3
(Budyko et al., 1987).On the otherhand Shackleton c
( 1985)arguedthat it is possibleto constrainthe total E()
CO2 in the ocean, and suggeststhat atmospheric a 2
f
CO2 concentrationswere unlikely to have beenmore
than double today'svalue.
O , I
o
I
o _ l
The result is a sensitivityof 3.0'C for a doubling of CO2,
:h a possiblerangeof * l"C, which is very similar to that
'r.rinedon the basisof numericalsimulations(Section5).
E
c)
F
0
Latitude
< I .2 Constructionof the analoguepatterns
rheir study,Budyko et al. (1987) usedthe mid-Holocene
' 6 kbp), the Last Interglacial (Eemian or Mikulino,l25
..p) and the Pliocene (3-4 mbp) as analoguesfor future
.mates.January,July and mean annualtemperatures,and
Figure 3.3: Relative surfaceair temperaturechangesin different
latitudesof the Northern Hemisphereduring the palaeo-climatic
warm epochs:(a) winter, (b) summer. Full line = Holocene;
Dashedline = last interslacial:Dash-dottedline = Pliocene.
Processesand Modeltinp 3
84
The considerable similarity between the temperature
anomaly maps for the three different epochssuggeststhat
the regional temperatureanomaly changes are, to a first
approximation, directly proportional to increasing mean
global temperature.If this is true, then the regional
distributions of surface air temperatureanomalies are
analogousto each other and the similarities betweenthese
maps also suggestthat the empirical methodsfor estimating
the spatial temperaturedistribution with global warming
may be relativelyrobusl.
Similarly, annual mean precipitationchangeshave been
reconstructed,though the patternsin the mid-Holocene
differ from those found for the other two periods (see
Section5.4, SectionI .2.2).
When reconstructionsof past climate conditions are
accurateand thorough,they can provide relatively reliable
estimatesof self-consistentspatial patterns of climatic
changes.Weaknessesin developingtheserelationshipscan
arisebecauseof uncertainlies
i)
ii)
iii)
pastclimates,
in reconstructing
in extendinglimited arealcoverageto globalscales,
in interpretingthe effectsof changingorographyand
iv)
equilibriumversusnon-equilibriumconditions,
in determiningthe relativeinfluencesof the various
factorsthat havecausedthe pastclimatic changes.
Figure 3.4: The model land-seamask for a typical climate model
(T21. ECHAM. afterCubaschet al. 1989)
prevent the solution from becoming numerically unstable.
the time step must be made smaller than a value that
dependson the speedof the fastestmoving disturbance
(wave),the the grid size(or smallestresolvedwavelength).
and the integrationmethod.
T h e s p a t i a l r e s o l u t i o no f G C M ' s i s c o n s t r a i n e df o r
practical reasonsby the speedand memory capacityof the
computer used to perform the numerical integrations.
Increasingthe resolutionnot only increasesthe memorl'
required(linearlyfor verticalresolution,quadraticallyfor
h o r i z o n t a l r e s o l u t i o n ) ,b u t a l s o g e n e r a l l y r e q u i r e s a
the
reductionin the integrationtime step.Consequentially,
3.5.2 Atmospheric General Circulation Models
with
increasing
rapidly
required
increases
time
computer
General circulation models are based on the physical
have a horizontalresolutionof
conservationlaws which describe the redistribution of resolution.Typical models
2 and 19 vertical levels.
m o m e n t u m , h e a t a n d w a t e r v a p o u r b y a t m o s p h e r i c 300 to 1000 km and between
to representlarge-scale
sufficient
These
resolutions
are
motions. All of these processesare formulated in the
"primitive" equations,which describethe behaviourof a f e a t u r e s o f t h e c l i m a t e , b u t a l l o w o n l y a l i m i t e d
the regionalscale.
fluid (air or water) on a rotating body (the Earth) under the interpretationof resultson
influenceof a differential heating(the temperaturecontrast
parameterizations
between equator and pole) causedby an external heat 3.5.2.I Physit'ul
limited
spatialresolution,GCM's do not (and
Due
to
their
source(the Sun). Thesegoverningequationsarenon-linear
resolution)resolve
partial differential equations,whose solution cannot be will not with any foreseeableincreaseof
p
r
o
c
e
s
s
e
s
i
m
p
o
r
t a n c et o c l i m a t e .
p
h
y
s
i
c
a
l
o
f
s
e
v
e
r
a
l
obtainedexcept by numericalmethods.Thesenumerical
these
sub grid-scale
effects
of
However,
the
statistical
methods subdivide the atmospherevertically into discrete
"carried"
have to be
the
GCM
processes
resolved
by
on
the
scales
and computed.
layers, wherein the variablesare
model by relating them to the
For each layer the horizontalvariationsof the predicted incorporated into the
(wind, temperature,humidity and
variables
resolved
scale
quantitiesare determinedeither at discretegrid points over
pressure)
Such a process is called
themselves.
surface
the Earth,as in grid point (finite difference)models,or by a
is
on both observationaland
finite number of prescribedmathematicalfunctions as in parametrization,and based
shows
the physical processes
studies.
Figure
3.5
theoretical
spectralmodels. The horizontal resolution of a typical
parameterized
and
their interactions.
in
a
typical
GCM,
atmosphericmodel usedfor climate studiesis illustratedby
its representationof land and seashown in Figure 3.4.
effectof clouds
The valuesof the predictedvariables(wind, temperature, 3 .5.2.2 Radiation and the
is possibly the mosl
radiation
parametrization
of
The
humidity, surfacepressure,rainfall etc.) for each layer
since it is
experiments,
for
climate
change
important
issue
(including the surface) and grid point (or mathematical
gases
greenhouse
of the
function) are determinedfrom the governing equation by through radiation that the effects
"marching" (integrating) forward in time in discrete time are transferred into the general circulation. A radiation
the radiative balanceof
steps starting from some given initial conditions. To parametrizationschemecalculates
[' rttc esses and M ode lling
85
many simulations. Climate experimentsrun without a
seasonalcycle are limited in scopeand their reliability for
climate change experiments is therefore doubtful. The
inclusionof the diumal cycle improvesthe realism of some
feedback mechanisms and therefore the quality of the
climate simulations.
I
3
3
C
3
d
$
d
c't
t{
la-\
)r\:
3.5.2.3 Sub grid-scaletransports
Most of the solar radiation absorbedby the climate system
is absorbedat the surface.This energy becomesavailable
for driving the atmosphericgeneralcirculation only after it
has been transferred to the atmosphere through the
planetary boundary layer (PBL), primarily by small-scale
P r e ci p r l a l i o n
Re-evaDoralion
turbulent and convectivefluxes of sensible.andlatent heat.
but also by net long-waveradiativeexchange.On the other
hand, the generalcirculation is slowed down by frictional
dissipationwhich basically takesplace in the PBL through
vertical transportof momentumby turbulenteddies.
In most GCMs the turbulentfluxes of heat,water vapour
and momentumat the surfaceare calculatedfrom empirical
"bulk
formulae" with stability dependent transfer
coefficients. The fluxes at the PBL top (at a fixed height
generally)are either neglectedor parametrizedfrom simple
mixed-layertheory. In GCMs that resolve the PBL, the
eddy diffusion approach is generally employed.
Considerableefforts are made to incorporateinto the PBL
parametrizationsthe effects of cloud, vegetationand sub
. gure 3.5: Theprocesses
parametrized
in a numerical
grid-scaleterrainheight.
. .pheremodel(ECMWF)andtheirinteraction.
Thethickness
Cumulus convectionin a vertically unstableatmosphere
' , rrrowsindicates
(from
of theinteraction
thestrength
is one of the main heat-producingmechanismsat scales
,:nton.1984)
which are unresolvablein GCMs. A common procedureis
to adjust the temperatureand water vapour profile to a
" ncoming solar radiation and the outgoing terrestrial conditionallystablestate(Moist ConvectiveAdjustment:
:-\\ave radiation and, as appropriate,the reflection, MCA). The secondclass of cumulus parameterizations
' ..ror and absorptionof thesefluxes in the atmosphere. often employed in GCMs is based on a "moisture
' -' 'rption and emissionare calculatedin severalbroad convergence"closure(KUO). Other GCMs use Penetrative
', -:ral bands(for reasonsof economy)taking into accounl Convection (PC) schemesto mix moist conditionally
,oncentration of different absorbersand emitters like unstable air from lower model layers with dry air aloft.
'. \\'atervapour,ozoneand aerosols.
The question of how sophisticatedconvective para:rr' sensitive part in any radiation scheme is the meterizations in GCMs need be. and how much the
. . -iation of the radiative effect of clouds. In early GCM
sensitivityof climate changeexperimentsdependson their
.::lrr€ntSclouds were prescribedusing observedcloud formulation,is still open.
rtologies (fixed cloud (FC) experiments),and were not
.-.'d to alter during the experimentswith (for example) 3.5.2.4 Land surfaceprocesses
.:ged CO2 concentration.Later schemescontained Another important parametrizationis the transfer of heat
. -.rctive cloud parametrizations of various soph- and water within the soil. for instancethe balancebetween
..rtion,but mostly basedon an estimateof the cloud evaporationand precipitation,snow melt, storageof water
rnt from the relative humidity (RH experiments). in the ground and river runoff. This parametrizationis of
. rhe most advancedschemescalculatethe variation of
extreme relevancefor climate changepredictions,since it
shows how local climates may changefrom humid to arid
...1optical properties by the cloud water content (CW
- ' r i m e n t s ) . C a p i t a l l e t t e r s i n b r a c k e t s i n d i c a t e and vice versadependingon global circulation changes. It
":r iationsusedin Table 3.2.(a)and 3.2.(b).
furthermore reflects, in some of the more sophisticated
.
:r' S€&Sofl&l
variation of the solar insolationis included schemes,the changesthat could occur through alterations
. nost all experiments,but a diurnal cycle is omitted in in surfacevesetationand land-use.
86
Most soil moistureschemesusedto dateare basedeither
"bucket" method or the force-restore
on the so-called
from
method. In the former case,soil moistureis available
moisture
the
all
When
layer'
soil
a singlereservoir,or thick
two
is used up, evaporationceases'In the latter method'
nearlayersof soil provide moisturefor evaporation'a thin'
and
precipitation
to
rapidly
responds
surface layer which
a
as
acting
layer
soil
evaporation, and a thick' deep
moisture
reservoir. If the surfacelayer dries out, deep soil
rates
is mostly unavailablefor evaporationand evaporation
p
r
e
s
e
n
c
eo f
t
h
e
i
n
fall to small values. However,
a
as
layer
vegetation,realistic models use the deep soil
sourceof moisturefor evapotranspiration'
At any given grid-point over land, a balancebetween
of
precipitation,evaporation'runoff and local accumulation
e
x
c
e
e
ds
soil moisture is evaluated'If precipitation
until
evaporation, then local accumulation will occur
and
assumed
is
runoff
saturationis achieved. After this'
runoff
this
of
the excesswater is removed' The availability
for in
as fresh-waterinput to the oceanhas been allowed
Most
oceanmodels only recently(Cubaschet al'' 1990)'
for
required
freshwater
models differ in the amount of
The
saturation,and few treat more than one soil type'
include
force-restoremethod has recentlybeenextendedto
(
1989)'
Planton
and
a rangeof soil typesby Noilham
and Modelling 3
Processes
of the
doesnot allow for the observedlags in heat storage
mixed-layer
of
Variations
upper ocean to be represented.
with
Olptn, oceanicheat flux convergence'and exchanges
storage
the deep ocean, which would entail an additional
well'
as
neglected
all
are
and redistribution of heat,
to
models
Attempts have been made to couple atmospheric
for
ocean models of intermediate complexity' Thus'
resolution
example,Hansenet al. (1988) have useda low
coupled
model
layer
mixed
atmosphericmodel run with a
dependent
diffusively to a deep oceanto simulatethe time
responseto a gradualincreasein tracegases'
3.5.3 Ocean Models
a
To simulate the role of the ocean more adequately'
developed
been
have
models
number of dynamical ocean
( B r y a n , 1 9 6 9 ; S e m t n e r ' 1 9 7 4 ;H a s s e l m a n n1' 9 8 2 ; C o x '
for
1984:Oberhuber,1989). The typical oceanmodel used
set
of
same
the
basically
climate simulations follows
the
defining
equationsas the atmosphereif the equation
water vapourbalanceis replacedby one describingsalinitr'
be
As with atmosphericGCMs, numerical solutionscan
and
techniques
obtained by applying finite difference
(i'e"
specifying appropriate surface boundary conditions
from
fluxes of heat, momentum and fresh-water)either
atmospheric
an
from
or
observations(uncoupledmode)
and
GCM (coupledmode' seeSection3'5'6)' The vertical
and
horizontal exchange of temperature, momentum
3.5.2.5 BoundarYconditions
it
is
equations'
model
the
of
salinity by diffusion or turbulenttransfersis parametrized'
To determinea unique solution
boundary
lower
and
The formation of sea-iceis generallytreatedas a purell
necessaryto specify a set of upper
thermodynamicprocess.However, some models already
conditions.Theseare:
and
include dynamical effects such as sea ice drift
at
c
u
r
r
e
nts
input of solarradiation(includingtemporalvariation)
o
c
e
a
n
a
n
d
w
i
n
d
s
deformation caused by
the toP of the atmosphere;
(Oberhuberet al., 1989).
wi&
orographyand land seadistribution;
One of the problemsof simulating the oceanis the
fa
albedoof bare land;
range of time and length scalesinvolved' The models
and
time
largest
surfaceroughness;
the
only
climate sensitivitystudiesresolve
vegetationcharacteristics'
length scales(horizontal resolution:200 to 1000 km; tinr
2 to 20
scale:hours to 10,000years;vertical resolution:
The lower boundary over the sea is either prescribed
eddiesresolve
can
which
models,
levels). High resolution
from climatological data or' as this is not very appropriate
btr
1988)'
Chervin'
are now being tested(Semtnerand
by
for climate changeexperiments,it has to be calculated
be
cannot nr
are with the currently availablecomputerpower
an ocean model. As comprehensiveocean models
sufficiently long enoughto simulateclimate changes'
expensiveto run (seeSection3'5'3), the most commonly
is the
used ocean model coupled to atmospheremodels
"mixed-layer" model. This model describesthe uppermost 3.5.4 Carbon CYcIeModels
ocean arl
is The exchange of carbon dioxide between the
layer of the ocean where the oceanic temperature
to tht
equations
adding
by
simulated
as a atmospherecan be
relatively uniform with depth' It is frequentlymodelled
of gr
physics
the
gas
flux,
layer is oceancomponentfor the air-sea
simple slab for which a fixed depth of the mixed
in scr
buffering
the solubility, the chemistryof carbon dioxide
prescribedand the oceanic heat storageis calculated;
(Maier Reimer atJ
only water, and the biological pump
oceanicheat transportis either neglected'or is canied
the coupled ocean
of
extension
Hasselmann,1989). This
within the mixed layer, or is prescribedfrom climatology'
the frratmospheremodel will permit diagnosis of
Seaiceextentsaredeterminedinteractively,usuallywitha
ad
tionation of carbon dioxide between the atmosphere
variantof the thermodynamicseaice model due to Semtner
to thr
ocean in the last hundred years, and changes
(1916). Such an ocean model evidently has strong
respond
to
begins
ocean
the
fractionation in the future as
limitationsforstudiesofclimatechange,particularlyasit
87
Proc'esse
s and M odelling
,bal warming, in particularthrough changesin the ocean
rcd layer depth, which affects both the physical uptake
' carbon dioxide and the efficiency of the biological
.lp. The physical and chemical equations are well
':rblished,but more work is neededto establishequations
- the biological pump. The latter must parametrizethe
prohibit equilibrium being reachedexceptwith mixed-layer
models. Various asynchronouscoupling techniqueshave
been suggestedto acceleratethe convergenceof a coupled
model. However, the problem is far from being solvedand
can only really be tackledby using fastercomputers.
A second basic problem that arises through such
,loeicaldiversity, which variesregionally and seasonally coupling is "model drift". The coupled model normally
.i is likely to vary as the climate changes;ideally the drifts to a state that reflects the systematicerrors of each
must copewith suchchangeswithout respectivemodel componentbecauseeach sub-modelis no
-...rtions
themselves
::,rducingtoo many variables.Candidatesets of such longer constrained by prescribed observed fluxes at the
,i.ust biological equations"have been tested in one- ocean-atmosphereinterface. Therefore flux correction
':rcnsionalmodels and are now being used in ocean terms are sometimesintroduced to neutralize the climate
-, ulationmodelswith encouraging
results.It seemslikely drift and to obtain a realistic referenceclimate for climate
:: rhey will have to be incorporatedinto eddy-resolving changeexperiments(Sausenet al, 1988,Cubasch,l9tt9)
,.:rn circulationmodelsin orderto avoidbiasesdue to the (c.f. Section4.9). However,theseterms are additiveand do
:.hv growth of plankton. They will also have to pay not guaranteestability from further drift, They are also
:;ial attention to the seasonalboundary layer (the prescribedfrom present-dayconditionsand are not allowed
.rrsist'seuphotic zone) and its interaction with the to changewith alteredforcing from increasedCO2.
-:nanentthermocline in order to deal with nutrient and
Carboncycle modelshave alreadybeencoupledto ocean
' " o n d i o x i d e r e c i r c u l a t i o n .S u c h m o d e l s a r e c o m p - models,but coupling to an AGCM-OGCM has not yet been
.,:ropsllyexpensiveand completeglobalmodelsbasedon
. .c equationswill have to await the arrival of more
..c'rfulsupercomputers
later in the 1990s.Besidesthe
.,rgicalorganic carbon pump the biological calcium
-aonate counter pump and interactions between the
:.\iter and carbon sedimentpools must be considered.
'.1 resultswith modelswhich includethe organiccarbon
':rp with a sediment reservoirindicatethe importanceof
(Heinzeand Maier Reimer,1989).
. -. processes
..5 Chemical Models
-J to the increasingawarenessof the importanceof trace
.:. other than CO2 a number of researchgroups have
.. \tarted to develop models consideringthe chemical
Jractionsbetween a variety of trace gases and the
rral circulation (Pratheret al, 1987). At the time of
:rng,thesemodels have not yet beenusedin the models
.,ussedso far to estimatethe global climate change.It
bc interestingto see their impact on future climate
,rge modelling.
I
I
I
I
a
>
3-
a
T
T
<.6 Coupled Models of the Atmosphere qnd the Ocean
. -' to the dominating influenceof the ocean- atmosphere
. in the climate system, realistic climate change
:-crimentsrequireOGCM's and AGCM's to be coupled
--'ther by exchanginginformation about the sea surface
'rp!'rature,the ice cover, the total (latent ,sensibleand net
:*ave radiative) heat flux, the solar radiation and the
.J
SITCSS.
)ne basicproblem in the constructionof coupledmodels
-cs from the wide range of time scalesfrom about one
, ior the atmosphereto 1000 years for the deep ocean.
'rchronously coupled atmosphere-oceanmodels are
':L'melytime consuming,and limited computerresources
carriedout.
3.5.7 Use of Models
Despite their shortcomings,models provide a powerful
facility for studiesof climate and climate change.A review
( 1983).They are
of suchstudiesis containedin Schlesinger
investigations
of
the
sensitivity of
normally used for
climate to internaland externalfactorsand for predictionof
"control"
climate change by firstly carrying out a
integration with parametersset for presentday climate in
order to establisha referencemean model climatology and
the necessarystatisticson modelled climatic variability.
Thesecan both be verified againstthe observedclimate and
of the subsequently
usedfor examinationand assessment
modelled climate change. The climate change (perturbation)run is then carriedout by repeatingthe model run
with appropriatelychangedparameters(a doubling of CO2
for example) and the differencesbetween this and the
parallel control run examined.The difference betweenthe
control and the perturbed experiments is called the
"response".The significance of the responsemust be
assessed
againstthe model'snaturalvariability (determined
in the control run) using appropriatestatisticaltests.These
to be made (usually expressedin
enable an assessment
probabilities)
of the confidencethat the changes
terms of
obtainedrepresentan implied climatic change,rather than
simply a result of the naturalvariability of the model.
Typical integration times range from 5 to 100 years,
depending on the nature of the investigation. Until now,
most effort to study the responseto increasedlevels of
greenhousegas concentrationshas gone into determining
the equilibrium responseof climate to a doubling of CO2,
using atmosphericmodelscoupledto slab oceanmodels.A
comparatively small number of attemptshave been made to
Processesand Modelting 3
88
"transient" (i.e. time-dependent)climate
determine the
responseto anthropogenicforcing using coupled atmosphereand oceancirculationmodels.
3.5.7.1 Equilibrium responseexperlments
In an equilibrium responseexperiment both simulations,
i.e., the control experimentwith the presentamount of
atmospheric CO2 and the perturbation experiment with
doubled CO2, are run sufficiently long to achieve the
respectiveequilibrium climates. A review of such experimentsis given in Schlesingerand Mitchell (1987). For a
mixed-layer ocean the responsetime to reach equilibrium
amountsto severaldecades,which is feasiblewith present
day computers. For a fully coupled GCM the equilibrium
responsetime would be severalthousandyearsand cannot
be achievedwith presentday computers. A comprehensive
list of equilibrium responseexperimentscan be found in
1.0
c)
o
E
(g
-_
>
'6
c
c)
a
O Global
o Clear-sky
3 o
na
o
nA
a o o
.)
- o
o . ! E ^\ '^ vo
o C o o "
n
o.4 5 o
o
o
o o "
6 7 B 9 1011121314151617
M o d e ln u m b e r
Table3.2(a).
rcsponseexperimcnt's
3.5.7.2 Time-dependent
for given CO2 increasesare
studies
response
Equilibrium
required as standardbenchmarkcalculationsfor model
intercomparison.The resultsmay be misleading,however,
if applied to actual climate change caused by man's
activities,becausethe atmosphericCO2 concentrationsdo
not changeabruptly but have beengrowing by about O.4Vo
per year. Moreover, the timing of the atmosphericresponse
dependscrucially on the oceanheat uptake which might
delay the CO2 inducedwarming by severaldecades.Thus,
not only have
for realisticclimate scenariocomputations,
the atmosphericprocessesto be simulated with some
fidelity but also the oceanicheat transportwhich is largely
governed by ocean dynamics. First experiments with
models have been
coupled dynamical atmosphere-ocean
performed (Table 3.2(b)) and will be discussedlater in
Section6.
3.6 lllustrative Equilibrium Experiments
In this sectionclimate sensitivityresults,as producedby a
large number of general circulation models, are summarizedfor two quite different climate change simulations.
The first refers to a simulation that was designed to
suppresssnow-icealbedofeedbackso as to concentrateon
the water vapour and cloud feedbacks.The secondconsists
of a summaryof global warming due to a CO2 doubling.
The first case,addressingonly water vapour and cloud
feedbacks,consistsof a perpetual July simulationin which
the climate was changedby imposing a 4'C perturbation on
the global sea surface temperaturewhile holding sea ice
fixed. Since a perpetual July simulation with a general
circ:ulationmodel results in very little snow cover in the
Northem Hemisphere,this effectively eliminatessnow-ice
albedo feedback.The details of this simulation are given by
Figure3.6: Summaryof theclear-skyandglobalsensitivity
models.
fbr l7 generalcirculation
parameters
Cesset al. ( 1989);the main point is that it was chosenso an
to minimize computer time and thus allow a large number
of modelling groups to participatein the intercomparison.
This procedureis in essencean inverse climate change
simulation.Ratherthan introducinga radiativeforcing into
the modelsand then lettingthe model climatesrespondlo
this forcing, the climate changewas insteadprescribedand
the models in turn produced their respectiveradiativc
forcings.
c l i m a t es e n s i t i v i t y
C e s se t a l . ( 1 9 8 9 )h a v e s u m m a r i z e d
parameters as produced by l4 atmospheric general
circulation models (most of them are referencedin Tablc
3.2(a)and 3.2(b).This number has since risen to ll
models, and their sensitivity parameters(1, as defined in
Section3.3.1)are summarizedin Figure 3.6. The importan
point here is that cloud effects were isolatedby separatell
averagingthe models' clear-sky TOA fluxes, so that lr
addition to evaluatingthe climate sensitivity parameterfc
the globe as a whole (filled circles in Figure 3.6)' it *t
also possible to evaluate the sensitivity parameterfor r
"clear-sky"Earth (opencircles).
equivalent
Note that the models are in remarkableagreementu'it
respect to the clear-sky sensitivity parameter,and thc
model-averagel" = 0.47 Km2W-l is consistentwith tha
discussionof water vapour feedback(Section3.3.2).fq
which it was suggestedthat l, = 0.48 Km2W-1. There ir"
however, a nearly threefold variation in the globd
sensitivityparameter,and since the clear-skysensitirin
parametersare in good agreement,then this implies trr
most of the disagreementscan be attributed to diffl
in cloud feedback.A more detaileddemonstrationof this
given by Cess et al. (1989). The important concl
.l Processesand Modellins
89
::om this intercomparisonare that the l7 models agreewell
.(rth an observational determination of water vapour
":r'dback,whereasimprovementsin the treatmentof cloud
':l'dback are needed if general
circulation models are
- timatelyto be usedas reliable climate predictions.
The second type of simulation refers to a doubling of
.:nospheric CO2, so that in proceedingfrom one equi"num climate to another, snow-ice albedo feedback is
. :Jitionally activatedin the generalcirculation models. It
.r:t be cautioned however, that cloud feedback in this
t of simulation should not be expectedto be similar to
:t tbr the perpetual July simulation. Furthermore, one
- ,uld anticipate interactive effects between cloud feed.- k and snow-icealbedofeedback.
'iummarizedin Table 3.2(a) are ATs results,as well as
: related changes in global precipitation, for CO2
:hling simulationsusing a numberof generalcirculation
rlc'ls. All modelsshow a significantincreasein global- rn temperature
which rangesfrom 1.9'C to 5.2'C. As in
" pcrpetualJuly simulations,cloud feedbackprobably
:,rducesa large uncertainty,althoughhere it is difficult
*uantifythis point.
\lost resultslie between3.5'C and 4.5"C, althoughthis
,,'\ not necessarilyimply that the correct value lies in this
. ic. Nor does it mean that two models with comparable
. r ' a l u e s l i k e w i s e p r o d u c e c o m p a r a b l ei n d i v i d u a l
.'.lback mechanisms. For example, consider the
, - . t h c r a l da n d M a n a b e( 1 9 8 8 ) a n d H a n s e ne t a l . ( 1 9 8 4 )
':ulationsfor which the respectiveATs valuesare 4.0'C
: l.l"C. Summarizedin Table 3.3 are their diagnosesof
: : r i d u a l f e e d b a c k m e c h a n i s m s .T h e s e t w o m o d e l s
.t'lled GFDL and GISS respectively)produce rather
':rlar warmings in the absenceof both cloud feedback
: \now-ice albedo feedback.The incorporationof cloud
..lback, however, demonstratesthat this is a stronger
:Jback in the GISS model, as is consistentwith the
'lc-tual July simulations.But curiously the additional
. 'rporationof snow-icealbedofeedbackcompensates
for
:ble 3.3: Comparison of ATs (oC)Jor the GFDL and
:S ntodels with the progressive addition of cloud and
" -ice feedbacks.
i:EDBACKS
GFDL
GISS
' 'cloud or snow-ice
t.7
2.0
.l. cloud
t A
; t- z
.l\ SnOW-lCe
4.0
1 a
their differences in cloud feedback. Thus, while the two
models produce comparableglobal warming, they do so for
quite different reasons.
It should be emphasizedthat Table 3.3 should not be
used to appraise the amplification factor due to cloud
feedback since feedbackmechanismsare interactive. For
example,from Table 3.3 the cloud feedbackamplifications
for the GFDL and GISS models might be inferred tobe 1.2
and 1.6respectively.But, theseare in the qbsenceof snowice albedo feedback. Conversely, if snow-ice albedo
feedback is incorporatedbefore cloud feedback, then the
respectiveamplification factors are 1.3 and 1.8. These
larger valuesare due to an amplification of cloud feedback
by snow-icealbedofeedback.
3.7 Summary
Many aspectsof the global climate system can now be
simulatedby numericalmodels.The feedbackprocesses
associatedwith theseaspectsare usually well represented,
but there appear to be considerabledifferences in the
strengthof the interactionof theseprocessesin simulations
using different models. Section 4 examines results from
variousmodels in more detail.
Unfortunately,even though this is crucial for climate
changeprediction,only a few modelslinking all the main
componentsof the climate systemin a comprehensiveway
have been developed.This is mainly due to a lack of
computerresources,sincea coupled systemhas to take the
different timescalesof the sub-systemsinto account,but
also the task requiresinterdisciplinarycooperation.
An atmosphericgeneralcirculationmodel on its own can
be integratedon currently available computersfor several
model decadesto give estimatesof the variability about its
equilibrium response;when coupled to a global ocean
model (which needsmillennia to reach an equilibrium) the
demandson computertime are increasedby severalorders
of magnitude. The inclusion of additionalsub-systemsand
a refinement of resolution needed to make regional
predictions demands computer speedsseveral orders of
magnitudefasterthan is availableon currentmachines.
We can only expect current simulations of climate
changeto be broadly accurateand the results obtained by
existing models may become obsolete as more complete
models of the climate system are used. Resultsfrom fully
coupled atmosphereoceanmodels are now beginning to
emerge;theseare given in Section6.
The palaeo-analogue
method,althoughof limited use for
detailed climate prediction (see Section5), nevertheless
gives valuable information about the spectrumof past and
future climate changesand providesdatafor the calibration
of circulation models in climate regimesdiffering from the
present. Results from these calibrations are shown in
Section4.
90
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