Past and Future Climate Simulation

1
Past and Future Climate Simulation
Dan Lunt

• Lecture 1 Introduction
• The course overview
• An historical perspective
• The hierarchy of climate models

2
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.

3
Lectures

• Introduction history and the model hierarchy
• General Circulation Models dynamical core
• General Circulation Models parameterisations
• Future Climate Modelling (1)
• Future Climate Modelling (2)
• Last Glacial Maximum Modelling
• Pliocene Modelling
• Eocene Modelling

4
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
5
Detailed Timetable
6
The Earth System
7
Oldfield, p4
8
Historical Perspective.
Lewis Fry Richardson 1881-1953
First numerical weather forecast, 1917
9
Physically unreasonable massive rise in
pressure
Due to lack of filtering
10
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... 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. 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. .
There it will be coded and telephoned to the
radio transmitting station. . Messengers
carry piles of used computing forms down to a
storehouse in the cellar. .Outside are
playing fields, houses, mountains and lakes, for
it was thought that those who compute the weather
should breathe of it freely.
Compute nodes
Weather Prediction by Numerical Process 1922
Load balancer
High speed interconnect
Web portal
Tape archive
Air conditioning
11
In 1950, the first realistic 24-hour forecast was
successfully calculated on the ENIAC.
Jule Gregory Charney 1917-1981
in about 24 hours
12
University of Bristol supercomputerBluecrystal
13
Why Model Climate?
Understanding and Prediction
Climate theory/understanding
Test understanding
Model-data agreement?
Climate observations and monitoring
Climate modelling
Application to prediction of climate change,
mitigation etc.
14
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). Include some physics. Include all components of earth-system. Can carry out transient simulations and snaphots.
Conceptual/Box Models Include a few or no processes. Can aid understanding.
Less complex
15
Conceptual models radiation balance
Solar energy, S, incident on a planet is
constant.
S
S
Planet absorbs this energy. It starts to heat up
and emit its own infra-red radiation (heat), E
sT4
E
S
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 T10oC
E
If we know E, it is possible to calculate the
temperature, T (T(E/4s)1/4)
16
S
In reality, planets do not absorb all the suns
energy which his incident. A fraction, a (the
albedo), is reflected.
aS
S
Planet heats up until S-aS is balanced by E
aS
E
For our sun, and a planet at the radius of the
Earth, and with Earths albedo (0.3), Tbb
-18oC Earth T 14oC What is going on?
17

• 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!).
• For the Earth, the most important of these
  absorbing gases is water vapour! Also CO2, N2O,
  CH4, CFCs.
• More IR-absorbing gases gt higher T !
• Moisture complicates things clouds etc.

S
A
Atmosphere emits energy A towards the surface.
Planet heats up until EaS is balanced by SA
aS
E
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
18
Climate Feedback Parameter

• ? Ts ?F
• Y
• Y is the climate feedback parameter and has units
  of Wm-2K-1
• (Note that sometimes, ? Ts ??F, where ?
  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
19
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 lt 0
• Hence this feedback will reduce Yoverall. Most
  complex models predict that
• Ywv -1.5 Wm-2K-1 and so
• Yoverall Y(BBWV) 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

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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 lt 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

21
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(BBWVicecloud) 0.75 to 2.25 Wm-2K-1
• Hence the response to a doubling of CO2 is ? Ts
  5.3 to 1.8K

22
Daisy-World

• Simple Rules
• Bare grey soil has albedo 0.5
• White daisies have albedo 0.75
• All daisies reproduce according to
• 4) All daisies die at a constant rate

S
aS
E

• Solar energy, S, increases linearly, in a similar
  way to our own sun
• Experiments
• No Daisies
• Just White Daisies

Growth rate
5oC 22.5oC 40oC
Temperature
http//zool33.uni-graz.at/schmickl/models/daisywor
ld.html
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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?

24
Daisy-World

• Simple Rules
• Bare grey soil has albedo 0.5
• White daisies have albedo 0.75
• Black daisies have albedo 0.25
• All daisies reproduce according to
• and a factor that depends on the bare area
• 5) All daisies die at a constant rate

S
aS
E

• Solar energy, S, increases linearly, in a similar
  way to our own sun
• Experiments
• No Daisies
• Black and White Daisies, same albedo.
• Just Black Daisies
• Just White Daisies
• Black and White Daisies

Growth rate
5oC 22.5oC 40oC
Temperature
http//zool33.uni-graz.at/schmickl/models/daisywor
ld.html
25
Conceptual Models, e.g. Paillard.
Paillard, Nature, 391, 378-381, 1998.
Conceptual model leads to surprisingly good
results, but what is learnt about the system?
26
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
27
1990
1995
1995
1990
2001
2001
2007
2007
28
Surface Temperature observations
Surface Temperature HadCM3
How good are climate models?
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EMIC.
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For another EMIC, see CLIMBER
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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.