Lecture 1

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Past and Future Climate
Simulation
Dan Lunt
Lecture 1 – Introduction
 The course – overview
 An historical perspective
 The hierarchy of climate models
Aims and Objectives
(1) To introduce the concept of General Circulation Models and their
fundamental properties, strengths and weaknesses.
(2) To illustrate the use of GCMs in palaeoclimate studies, by focusing
on 3 key time periods.
(3) To illustrate the role of GCMs in future climate studies.
(4) To give hands-on experience of evaluating, analysing, and running
GCM simulations.
‘Learning Outcomes’
On successful completion, students will be able to:
(1) Describe the fundamental basis of GCMs;
(2) Discuss the limitations of GCM simulations and their interpretation;
(3) Critically assess previous studies which have used GCMs to understand
past climates;
(4) Evaluate predictions of future climate;
5) Run a simple GCM experiment.
Lectures
1) Introduction – history and the model hierarchy
2) General Circulation Models: dynamical core
3) General Circulation Models: parameterisations
4) Future Climate Modelling (1)
5) Future Climate Modelling (2)
6) Last Glacial Maximum Modelling
7) Pliocene Modelling
8) Eocene Modelling
Practical
Carry out an experiment of your choice with the GENIE-2 model
Assessment: write-up of your experiment in the
form of a ‘Climate of the Past’ paper
Detailed Timetable
The Earth System
Oldfield, p4
Historical Perspective….
Lewis Fry Richardson
1881-1953
First numerical
weather forecast,
~1917
Physically
unreasonable
– massive rise
in pressure
Due to lack of
filtering
“…Imagine a large hall like a theatre, except that the circles and galleries go right
round through the space usually occupied by the stage. The walls of this chamber
are painted to form a map of the globe. The ceiling represents the north polar
regions, England is in the gallery, the tropics in the upper circle, Australia on the
dress circle and the antarctic in the pit….
..A myriad computers are at work upon the weather of the part of the map where
each sits, but each computer attends only to one equation or part of an equation...
Compute nodes
Weather Prediction by
Numerical Process
1922
It carries a large pulpit on its top. In this sits the man in charge of the whole
theatre…. One of his duties is to maintain a uniform speed of progress in all parts of
the globe.…
Load balancer
Four senior clerks in the central pulpit are collecting the future weather as fast as it
is being computed, and despatching it by pneumatic carrier to a quiet room….
High speed interconnect
. There it will be coded and telephoned to the radio transmitting station. ….
Web portal
…Messengers carry piles of used computing forms down to a storehouse in the
cellar.
Tape archive
….Outside are playing fields, houses, mountains and lakes, for it was thought that
those who compute the weather should breathe of it freely.”
Air conditioning
Jule Gregory Charney
1917-1981
In 1950, the first realistic 24-hour
forecast was successfully
calculated on the ENIAC….
in about 24 hours
University of Bristol
supercomputer…Bluecrystal
Why Model Climate?
Understanding and Prediction
Climate
theory/understanding
Test
understanding
Climate observations
and monitoring
Model-data
agreement?
Application to prediction
of climate change,
mitigation etc.
Climate modelling
Hierarchy of models
More complex
Complex General
Circulation Models
(GCMs).
Include all physics.
Do not simulate all components of the
earth system, usually atmos, ocean, (veg).
Too slow to carry out transient
simulations or ensembles.
Carry out ‘snapshots’.
Earth-system Models of
Intermediate Complexity
(EMICs).
Conceptual/Box Models
Include some physics.
Include all components of earth-system.
Can carry out transient simulations and
snaphots.
Less complex
Include a few or no processes.
Can aid understanding.
Conceptual models: radiation balance
S
S
E
S
E
Solar energy, S, incident on
a planet is ~ constant.
Planet absorbs this energy.
It starts to heat up and emit
its own infra-red radiation
(heat), E = σT4
Planet heats up until E is
balanced by S. At this
point, the temperature is
Tbb
For our sun, and a planet at
the radius of the Earth,
Tbb= 6oC
Earth: T~10oC
If we know E, it is possible
to calculate the temperature,
T (T=(E/4σ)1/4)
S
In reality, planets do not
absorb all the sun’s energy
which his incident. A
fraction, α (the ‘albedo’), is
reflected.
αS
S
E
Planet heats up until S-αS
is balanced by E
αS
For our sun, and a planet at the radius of the Earth, and with Earth’s
albedo (~0.3), Tbb= -18oC
Earth: T ~ +14oC
What is going on?
The Earth has an atmosphere!
Some constituents of the atmosphere absorb the infra-red energy, E, emitted
by the Earth. The atmosphere itself warms up, and in turn emits radiation back
towards the surface, heating the surface. Energy balance is obtained with a
higher T - the ‘Greenhouse Effect’ (actually, a greenhouse works differently!).
S
αS
A
E
Atmosphere emits energy
A towards the surface.
Planet heats up until E+αS
is balanced by S+A
 For the Earth, the most important of these absorbing gases is water vapour!
Also CO2, N2O, CH4, CFCs.
More IR-absorbing gases => higher T !
Moisture complicates things – clouds etc.
For more information, section 1.2 of ‘The Physics of Atmospheres’, John T. Houghton or
Chapter 8 of ‘Fundamentals of Weather and Climate’, Robin McIlveen
Climate Feedback
Parameter
 Ts = F
Y
Y is the climate feedback parameter and has units of Wm-2K-1
(Note that sometimes,  Ts = λF, where λ = climate sensitivity parameter)
If the outgoing longwave radiation is the only process which changes
when temperature changes, then
YBB = 3.3 Wm-2K-1
It can also be shown that for a doubling in atmospheric CO2, F ≈ 4 Wm-2
Hence in the absence of any other feedbacks,  Ts = 4/3.3 = 1.2K
For descriptive discussion of feedbacks, see Global Warming by Houghton (p90 onwards)
For more quantitative discussion, see Climate Change IPCC (1990) p77 onwards
For more mathematical discussion, see Dynamical Paleoclimatology by Saltzman, p 139 onwards
Climate Feedbacks:
Water Vapour
 Ts = F
Y
Water vapour feedback: we know that a warmer atmosphere will hold
more water vapour and we also know that water vapour is a radiatively
active gas (RAG). Thus the changes in water vapour will amplify the
response. This is a positive feedback but (unfortunately corresponds to a
negative value of Y). i.e. Ywv < 0
Hence this feedback will reduce Yoverall. Most complex models predict that
Ywv ≈ -1.5 Wm-2K-1 and so
Yoverall = Y(BB+WV) = 3.3 – 1.5 = 1.8 Wm-2K-1
Hence if the response to a doubling of CO2 is  Ts = 4/1.8 = 2.2K
NOTE THAT THERE IS SOME ARGUMENT ABOUT THE MAGNITUDE
OF Ywv
Climate Feedbacks:
Ice Albedo
 Ts = F
Y
Ice Albedo feedback: in a warmer world, we would expect less
ice and snow and hence the surface albedo will decrease. This will
result in more solar energy being absorbed, thus further warming
climate. This is another example of positive feedback (Yice < 0).
Models typically predict that Yice ≈ -0.3 Wm-2K-1 and so
Yoverall = YBB + Ywv + Yice = 1.5 Wm-2K-1
Hence the response to a doubling of CO2 is  Ts = 4/1.5 = 2.7K
NOTE THAT THERE IS SOME ARGUMENT ABOUT THE
MAGNITUDE OF Yice
Climate Feedbacks:
Cloud Feedbacks
 Ts = F
Y
Cloud feedback: We do not know how cloud cover will change. In our
present climate, satellite observations suggest that the net effect of clouds
is to cool the climate system, but this does not tell us how they will respond
to a particular climate change scenario.
Clouds can influence the radiation budget by many ways:
– Total cloud amount
– Cloud height
– Cloud optical properties (cloud liquid water, droplet radius, fraction of ice
etc)
Currently we have no confidence in our estimates of the sign of Ycloud. As a
very rough approximation, Ycloud ≈ +/- 0.75 Wm-2K-1 (i.e. either a positive or
negative feedback) and so Y(BB+WV+ice+cloud) = 0.75 to 2.25 Wm-2K-1
Hence the response to a doubling of CO2 is  Ts = 5.3 to 1.8K
“Daisy-World”
Simple Rules:
αS
E
Solar energy, S, increases linearly, in a similar
way to our own sun
Experiments:
a)
No Daisies
b)
Just White Daisies
1)
‘Bare’ grey soil has albedo 0.5
2)
White daisies have albedo 0.75
3)
All daisies reproduce according to:
Growth rate
S
5oC
4)
http://zool33.uni-graz.at/schmickl/models/daisyworld.html
22.5oC
Temperature
40oC
All daisies die at a constant rate
(1) Initialisation parameters at low luminosity – predictions?
(2) Increase luminosity by hand – daisies appear
(3) Increase luminosity further – daisies die
(4) Show scenario with no daisies – why shape of graph?
(5) Prediction for white daisies and scenario?
“Daisy-World”
Simple Rules:
αS
E
Solar energy, S, increases linearly, in a similar
way to our own sun
Experiments:
a)
No Daisies
b)
Black and White Daisies, same albedo.
c)
Just Black Daisies
d)
Just White Daisies
e)
1)
‘Bare’ grey soil has albedo 0.5
2)
White daisies have albedo 0.75
3)
Black daisies have albedo 0.25
4)
All daisies reproduce according to:
Growth rate
S
5oC
40oC
and a factor that depends on the
‘bare’ area
Black and White Daisies
5)
http://zool33.uni-graz.at/schmickl/models/daisyworld.html
22.5oC
Temperature
All daisies die at a constant rate
Conceptual Models, e.g. Paillard.
Conceptual model leads to surprisingly good results,
but what is learnt about the system?
Paillard, Nature, 391, 378381, 1998.
Comprehensive Model
….(GCM, Earth System Model)
Newton's Laws of Motion
1st Law of Thermodynamics
Conservation of Mass and Moisture
Hydrostatic Balance
Ideal Gas Law
1990
1995
1990
1995
2001
2001
2007
2007
Surface Temperature: observations
Surface Temperature: HadCM3
How good are climate models?
EMIC….
For another EMIC, see CLIMBER…
Summary
• Range of climate models
• Each have their own strengths and weaknesses
• Simple models (EBM, EMICs) powerful tools for
helping our understanding
• But perhaps less relevant for future predictions
• Most complex models (GCMs) include detailed
representation of the physics of climate
• But, as we will see, still many approximations
• These climate models get used for prediction but
are they good enough?
• Palaeoclimate can test these models
• If data is good enough, and if we know the forcings.
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