Uncertainty in the climate response predictions to rising levels of Greenhouse gases

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Uncertainty in the climate response predictions
to rising levels of Greenhouse gases
PRINCE K. XAVIER
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Why are we concerned about CO2 and other
Greenhouse Gases?
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The history
In the nineteenth century various scientists
(such as Joseph Fourier) explained that the
atmosphere can, like an ordinary greenhouse,
retain energy radiated into it from outside. The
greenhouse analogy isn't very exact, but the name
certainly stuck. In the 1860s John Tyndall
explained that certain gases, including water
vapor and carbon dioxide (CO2), don't affect
visible light but absorb longer wavelength
radiation (infrared, heat).
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The actual process works like this Visible
incoming sunlight either gets reflected (for
example by clouds), or passes unhindered through
the atmosphere, and gets absorbed by the surface
of the Earth, thus heating it. The Earth
radiates heat from the surface back into the
atmosphere, where it can pass back into space, or
get reflected again, or, because it has now got a
longer wavelength than before, it can get
absorbed by the water vapour, carbon dioxide,
methane and other greenhouse gases which are
present in the atmosphere. As the water vapour/
methane/ carbon dioxide molecules absorb the
longwave radiation, they heat up, and in turn
re-radiate long wave radiation in all directions.
Some is lost to space, but some of it also gets
radiated back to the surface, again warming it.
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The Earth's annual radiation budget (W/m2)
Of the incoming radiation, 49 (168342) is
absorbed by the Earth's surface. That heat is
returned to the atmosphere in a variety of forms
(evaporation processes and thermal radiation, for
example). Most of this back-scattered heat is
absorbed by the atmosphere, which then re-emits
it both up and down. Some is lost to space, and
some stays in the Earth's climate system. This is
what drives the Greenhouse Effect Figure adapted
from Kiehl Trenberth, 1997.
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Without greenhouse gases, the average temperature
at the Earth's surface would reach only -17ºC,
approximately 33ºC colder than it actually is!
Now, what if the concentrations of these
insulating gases increase? We might expect
the process described above to intensify. In
fact, this is just what the Nobel Prize-winning
Swedish chemist Svante Arrhenius did in 1896. By
knowing how CO2 absorbs heat radiation from the
surface of the Earth, he calculated what would
happen if the amount of CO2 in the atmosphere
were doubled. He estimated that a doubling of CO2
would lead to an average global surface
temperature increase of 2 C. This is consistent
with modern predictions.
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The CO2 budget
Estimated average sources and sinks for the
1980ies in PgC per year. Fossil fuel burning and
landuse change act as sources, the vegetation and
the ocean as sinks. image by Elmar Uherek, data
from IPCC TAR 2001
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The global atmospheric concentration of CO2 in
parts per million (ppm) measured over the past
1000 years
and estimated for the next 100 years.
Source IPCC Third Assessment Report. The CO2
concentrations used in climateprediction.net
experiments 282ppm and 564ppm, are marked.
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Scientists are still uncertain exactly how the
Earth-climate system will respond to such changes
in carbon dioxide and other changes to the
composition of the atmosphere. Many atmospheric
models have predicted disastrous impacts of
increasing of CO2, but there are a lot of
uncertainty in the models This issue can be
addressed in a very systematic manner.
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The Unified Model
The atmospheric part of the model used by
climateprediction.net is the UK Met Office's
state-of-the-art Unified Model (the same model
that is used to produce every weather forecast on
British terrestrial television)
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Horizontal resolution - Grids
The resolution is 2.5 in latitude by 3.75 in
longitude.
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Vertical resolution - Levels
19 vertical levels, The top level is at about 30km
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Time steps
The basic time step is half an hour. The
dynamics (essentially the movement of the air)
needs to be calculated every half hour, but the
radiation (the balance of incoming and outgoing
energy) can be calculated less frequently.
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Parameterizations
For example, based on knowledge of the
temperature and humidity in a box, we must
estimate how much cloud and how much rain there
is in the box. We also need to know how much
dust (i.e. aerosol) is in the box, as raindrops
require a very small solid particle in the air to
form on. This process is called parameterizing.
There are many parameterization schemes in the
model, such as the scheme which calculates how
much cloud there is. Some of these schemes are
well-constrained by observations and are believed
to be quite reliable, but others are far less
well understood and we're not very sure about
them.
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Ocean Models and their interaction with the
atmosphere
Both a slab ocean model and a 'complete' ocean
model will be used in the climateprediction.net
experiment. Heat and water are passed between
the ocean and atmosphere, and these processes
must be represented as accurately as possible.
Also, the wind speed at the surface affects the
way that the top of the ocean is mixed and so how
rapidly it responds to changing atmospheric
temperatures. Since the scale of oceanic process
are smaller than the atmosphere, it needs a
higher resolution to resolve them and thus higher
computing capacity. As an alternative, a
simplified model called a "slab ocean is used,
which effectively just represents the top 50m of
the ocean, with none of the deep sea currents
which can transport a huge amount of heat, albeit
very very slowly. The effects of the currents
therefore need to be parameterized.
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Chaos, Ensembles and Probabilities
Is making an accurate weather forecast, or
climate prediction, a hopeless cause? NO!!! We
need to get an idea of all the possible ways the
atmosphere could develop, and what the
likelihood, or probability, of each possible way
is.
London temperature as predicted by 500 runs of a
GCM for a 5 day forecast
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Their idea is novel because, instead of using
many models, they use a single model, with
different combinations of parameters and initial
conditions. This will provide a better
understanding of the possible scenario that will
develop due to the increase in CO2, because they
explore all the possible ways the climate could
develop.
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A Unique experimental strategy

• Involvement of the general public!
• The climateprediction.net project comprises three
  separate experiments
• to explore the model used,
• to see how well the models replicate past
  climate and
• to finally produce a forecast for 21st century
  climate.
• Each model distributed is unique, and differs
  from all the others in three ways
• the initial conditions
• the attributes which force it to be in one
  particular climate state (such as solar activity
  and, of course, the composition of the
  atmosphere)
• the parameters which make up the actual model
  (such as the relationship between the number of
  raindrops in a cloud and how much it actually
  rains. There are 20 of them!).

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Calibration step(phase 1) 1810-1825 The
temperature of the surface of the ocean is
artificially held constant. The movement, or
flux, of heat, in or out of the ocean that is
required to keep the ocean at a constant
temperature is calculated. This is an easy
solution to having a very simple ocean in the
model, which cannot actually store heat in the
way that a real, deep, complex ocean can.
Pre-industrial CO2 step (phase 2-control)
1825-1840 This involves running the model for 15
years with the levels of CO2 in the model
atmosphere kept constant at pre-industrial
levels, 282ppm. Unlike phase 1, here the
temperature of the ocean surface is allowed to
vary, according to how much energy the ocean
receives and emits. Unless the atmosphere starts
doing something very different, and the energy
balance at the top of the atmosphere is changed,
the temperature of the whole atmosphere should
therefore stay the same. Double CO2 step (phase
3) 2050-2065 In this phase the levels of
greenhouse gases are doubled and the model is run
for a further 15 years. In a good model, the
atmosphere should adjust to this change in
forcing and eventually settle in a new stable,
equilibrium state (which may be the same, warmer
or cooler).
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The results will give an indication of what
combinations of parameters work (in terms of
producing an atmosphere that behaves in a similar
manner to reality and does not freeze or boil, or
oscillate in and out of ice ages on a timescale
of a couple of years). We will therefore be able
to use the results to guide our choice of
parameters in the main experiment. By comparing
the single and doubled CO2 steps, we can
calculate the climate sensitivity of the models -
this is the difference between the globally
averaged surface temperature in the model with
pre-industrial CO2 and in that with doubled CO2.
This is a useful indicator of how a climate model
behaves, although it is slightly artificial, as
of course carbon dioxide values in the atmosphere
do not remain constant for 15 years, but change
continuously.
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Visualize the model runs
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The change in globally averaged surface
temperature with time after carbon dioxide values
in the atmosphere are doubled
15 years of phase 3 from 2579 climateprediction.ne
t runs
127 30-year simulations completed by the Hadley
Centre on the Met Office's supercomputer.
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Climateprediction.net Results
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The response to parameter perturbations

• The processes have limited impact
• Ranges of parameters too small
• Mutual compensation of Multiple perturbations

The frequency distribution of simulated climate
sensitivity using all model versions all model
versions except those with perturbations to the
cloud-to-rain conversion threshold This
parameter limits climate sensitivity all model
versions except those with perturbations to the
entrainment coefficient This parameter enhances
climate sensitivity
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The range of sensitivities across different
versions of the same model is more than twice
that found in the GCMs used in the IPCC Third
Assessment Report The possibility of such high
sensitivities has been reported by studies using
observations to constrain this quantity But this
is the first time that GCMs have generated such
behaviour.
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Variations in the relative r.m.s.e. of model
versions
The unperturbed model is shown by the red
diamond. Model versions with only a single
parameter perturbed are highlighted by yellow
diamonds. The triangles show the CMIP II models
for which data are available HadCM3 (having the
same atmosphere as the unperturbed model but with
a dynamic ocean) is shown in red and the others
in blue.
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Linear prediction of climate sensitivity based on
summing the change in l for the relevant
single-parameter-perturbation model versions, to
estimate l when multiple perturbations are
combined. Error bars show the resulting
uncertainty ( one sigma) caused by the
combination of a number of Dl values where each l
has an uncertainty deduced from the
initial-condition ensembles having only a single
parameter perturbed. Linear predictions within
one sigma of the simulated value are shown in
green, between one and two sigma in black, and
above two sigma in red. Mean uncertainties in the
simulated value (two-sigma range, inferred from
the initial-condition ensembles) are shown at the
bottom for four regions of sensitivity (03, 36,
69, 912).
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Rainfall difference
Temp difference
Unperturbed (3.4K)
Low sensitivity (2.5K)
High sensitivity (10.5K)
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My comments!

• This paper does NOT represent any new scientific
  discovery, but
• Realization of such a grand ensemble of
  simulations utilizing the computing power and
  active involvement of the public is worth
  appreciating!
• The originality of this paper is that they use
  the same model perturbed in many possible ways
  (within the acceptable limits) to estimate the
  climate sensitivity to some specific parameters.
  This is better than using many models, perturbed
  in many ways!
• Policy makers cannot ignore even a 1 chance of
  getting extremes! So this study is a
  demonstration of all the possible ways the
  climate can evolve.

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Present scenario of CO2 emissions
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