Global climate models (GCMs)
are used by regulatory agencies
and policy makers -- that's the
ONLY reason they are important.
GCMs have NOT been subject to
verification and validation, that is
the norm for engineering and science.
The models are NOT fit for the purpose
of identifying, with high confidence,
the proportion of 20th century warming
that was man made, versus natural.
That means GCMs are NOT fit
for the purpose of justifying
political policies to massively
change world energy systems.
GCMs have modules that model
the atmosphere, ocean, land surface,
sea ice and glaciers.
The atmospheric module simulates
winds, temperature, humidity and
atmospheric pressure, using complex
mathematical equations.
GCMs also include mathematical
equations describing the oceanic
circulation, how it transports heat,
and how the ocean exchanges
heat and moisture with the atmosphere.
Climate models include a land surface
sub-model that describes how vegetation,
soil, and snow or ice cover exchange
energy, and moisture, with the atmosphere.
GCMs also include sub-models
of sea ice and glacier ice.
GCMs divide the atmosphere,
oceans, and land into a
three-dimensional grid system.
The equations are calculated
for each cell in the grid –
repeatedly for each
of the time steps
that make up
the simulation period.
The number of cells
in the grid system
determines the
model's ‘resolution’.
Common resolutions for GCMs
are about 100–200 km
in the horizontal direction,
1 km vertically, and a
time-stepping resolution
typically of 30 min.
A doubling of resolution
requires about 10 times
more computing power,
which is not available at many
climate modeling centers.
Many important processes occur
on scales that are smaller than
the model resolution, such as
clouds and rainfall.
Sub-grid-scale processes
are represented using
‘parameterizations’,
which are simple formulas
that attempt to approximate
the actual processes.
These parameterizations
are ‘calibrated’ or ‘tuned’
to improve the comparison
of the climate model outputs
against historical climate data.
Climate scientists
don't like to admit
nearly every model
has been calibrated
precisely to 20th century
climate records.
The actual equations used in the
GCM computer codes are only
approximations of real life --
the real climate change processes
they represent are poorly understood,
or too complex to include in the model.
Parameterizations related to clouds
and precipitation are the most
challenging, responsible for
the biggest differences between
outputs of different GCMs.
There are more than 20 international
climate modeling groups contributing
climate model simulations to the
UN's IPCC assessment reports.
Many of individual groups contribute
simulations from several models.
Agreement between the
climate model simulations
and measured data,
does NOT imply
the model gets
the correct answer
for the right reasons.
Unfortunately,
only one model
seems to make
reasonable
predictions --
the Russian model.
The rest of the climate models
make wrong predictions,
falsifying their programming.
In real science, models that
make wrong predictions
are failed models, meaning
they are very expensive,
but worthless, computer games.
( The next article discusses
what climate models predict. )