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Sunday, June 9, 2019

Why Does Anyone Care About Global Climate Models ? Part 1

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. )