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Uncertainty and Confidence in Climate Change Prediction
Dave Stainforth, Research Fellow, Atmospheric Physics, Oxford University.
Chief Scientist for Climateprediction.net
Climate Change Negotiators Meeting
Tuesday 29th August 2006
Environmental Change Institute
Oxford University
1. Climate change - a reality.
2. Predicting the future - climate models.
3. Confident predictions - putting
uncertainty bounds on climate forecasts.
Why Uncertainty Analysis Is Important
• Climate change is certainly a
problem.
• But predictions of future climate and
the impacts of climate are
problematic. They must be
probabilistic in nature (i.e include
uncertainty analyses) because overconfident or deterministic forecasts
will:
– lead to misdirected adaptation and
development planning, and
– undermine the credibility of
climate science.
Climate science must be clear on
what it is sure about and honest
about uncertainties.
That’s easier said than done.
The Microbe is so very small
You cannot make him out at all,
But many sanguine people hope
To see him through a microscope.
His jointed tongue that lies beneath
A hundred curious rows of teeth;
His seven tufted tails with lots
Of lovely pink and purple spots,
On each of which a pattern stands,
Composed of forty separate bands;
His eyebrows of a tender green;
All these have never yet been seenBut Scientists, who ought to know,
Assure us that they must be so….
Oh let us never, never doubt
What nobody is sure about.
Hilaire Belloc
What we are sure about: Climate Change on a Global Scale
“An increasing body of observations gives a collective picture of a warming world and other changes
in the climate system.”
“… most of the warming observed over the last 50 years is attributable to human activities.”
Climate Change 2001, The InterGovernmental Panel on Climate Change (IPCC) Third Assessment Report.
What we are sure about: A host of other observed changes
•
•
•
Widespread retreat of mountain glaciers.
Increase in freeze free season over many
mid and high latitude regions.
Increase in frequency of heavy
rainfall/snowfall events.
Changes in terrestrial ecosystems include:
• Earlier spring arrival time of animals or plants.
• Earlier breeding times.
• Shifts to higher elevations or latitudes.
• Changes in population densities.
What we are sure about: Concentrations of atmospheric carbon dioxide.
“Present CO2 concentrations have not been exceeded during the past 420,000 years and likely
not during the past 20 million years.”
Climate Change 2001, The InterGovernmental Panel on Climate Change (IPCC) Third Assessment Report.
Source: IPCC Third Assessment Report
What we are sure about: Anthropogenic emissions are part of the cause.
Natural emissions only:
All emissions:
Mankind’s emissions only:
What we are unsure about: What Happens Next.
For some global variables climate
models can simulate observed climate
change very well.
That gives us confidence that they can be
used to predict the future under a given
scenario for greenhouse gas emissions.
So We Can Use The Model To Forecast The Future?
That’s what people do.
A complex model of this sort gives lots of
regional details which would be invaluable for
planning. If it could be trusted.
•
•
•
The problem is that different models give different results; particularly at the regional /
seasonal level of detail.
There may be many many models which predict the recent past well but respond very
differently to changing levels of greenhouse gases.
Climate forecasts are intrinsically uncertain but by working with probabilistic forecasts
we can still extract confident predictions of some aspects of future climate.
E.g. An uncertainty range of 1.9-11.5°C change is a confidence that it isn’t under 1.9.
Climate Models: A Reminder
Climate Models are the principle tools
for climate prediction.
Most impacts studies are based on the
predictions of AOGCMS.
Complex, 3-dimensional, Atmosphere /Ocean
General Circulation Models (AOGCMs)
A Hierarchy of Climate Models
Ocean
Dimension
0
0
1
2
point EBM
box models
thermohaline
models (lat/z):
pulse response
models
Atmosphere
seesaw models
1
advectiondiffusion models
3
OGCM
deep ocean
models
EBM (lat)
–
ocean (lat/z) +
EBM (lat)
stat. dynam.
atm. + diffusive
ocean
ocean (lat/z) +
stat. dyn. atm
(lat/long)
AGCM + mixed
layer
ACGM + slab
ocean
rad.-conv.
model (z)
2
3
EBM (lat/long)
AGCM + SST
–
OCGM + EBM
(lat/long)
OCGM + QG
atm.
A/OGCM
Courtesy of Thomas Stocker, University of Bern.
Sources of Uncertainty
and How to Include Them In a Climate Forecast
•
Natural Variability:
The climate is chaotic with variations on
timescales from minutes to centuries.
Solution: Initial Condition Ensembles
•
Forcing uncertainty:
Changes due to factors external to the climate
system e.g. greenhouse gas emissions (natural
and anthropogenic), solar radiation etc.
Solution: Scenarios for possible futures.
•
Model uncertainty:
Different models could be as good at simulating
the past but give a different forecast for the
future?
Solution: Perturbed-Physics Ensembles
•
Model Inadequacy
Exploring Uncertainty: The Climateprediction.net Experiment
Initial Condition
Ensemble
Forcing Ensemble
•
Overall Grand
Ensemble
Standard model
set-up
Perturbed Physics
Ensemble
10000s
10s
Latest Statistics
• > 300,000 participants.
• > 24M years simulated.
• > 110,000 completed simulations.
(Each 45years of model time)
• 10000 years of computing time.
10s
•
•
•
•
To quantify uncertainty we need 100s of
thousands of simulations.
Impossible with super computers.
But possible with distributed computing.
At www.climateprediction.net people
can download the model to their PC.
Using the latest, complex model means
we can get regional detail as well as
global averages.
ClimatePrediction.net : What it looks like.
First Results in Terms of Climate Sensitivity
Climate sensitivity is defined as the equilibrium global mean surface
temperature change for a doubling of CO2 levels.
In 2001 the IPCC concluded that
the climate sensitivity was likely
to be between 1.5 and 4.5°C
Many studies have identified the
possibility of high sensitivities
(>6 °C).
Only now do we have the models
which show such a response.
So now we have the possibility of
predicting the range of possible
future behaviour on regional and
seasonal scales.
Source: Stainforth et al. Nature, 2005
First Results:
Regional Behaviour
From Stainforth et al. Nature. 2005
Regional Behaviour – European Rain and Snowfall
Mediterranean Basin
Northern Europe
Winter
Winter
Summer
Summer
Annual
Annual
From Stainforth et al., “Avoiding Dangerous Climate Change.
Conclusions
• The most comprehensive exploration of uncertainty in climate models has so
far shown that:
– There is no evidence that climate change could be less dramatic than suggested
by the IPCC Third Assessment Report.
– We can not yet rule out the possibility of extremely dramatic levels of climate
change, even at relatively low equivalent concentrations of CO2 e.g. 450ppm.
• Uncertainty bounds are essential for planning how society can adapt to the
changes ahead.
• Uncertainty and confidence are two sides of the same coin. We can be very
uncertain about some things but confident about others.
• There is a realistic possibility of probabilistic regional forecasts in the next
few years. And therefore probabilistic impacts assessments.
• Vulnerability to changes in climate may be as important to understanding
local consequences as detailed climate forecasts.