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>>Hello, my name is Derek Rosendahl
and I'm a Postdoctoral Research Scientist
with the South Central Climate Science Center.
Today we'll be discussing what a global climate model is
and how it works.
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Scientists use models to represent a number of things
such as objects, concepts or systems
in order to gain a better understanding of them.
But the term model can mean many different things.
From the physical model of a watershed
to examine the movement of sediment in a river,
to a statistical model of a relationship
between consumer's interest
and the type of vehicle they buy.
In the case of a global climate model,
we're referring to a numerical model
that runs on a powerful super computer.
The lines of the computer code
describe what scientists know
about the physical processes that occur
in the atmosphere, ocean, biosphere and land surface.
Fundamentally, these processes represent
how heat, moisture, momentum and chemicals
move across space and through time.
Imagine trying to simulate the continuous earth system
in a computer model.
Global climate models work
by dividing up the earth's atmosphere,
oceans, land and sea ice
into lots of three dimensional boxes or grid cells.
Modern global climate models
can have grid cells that are
50 miles square in the horizontal,
and that can go up to 90 levels in the atmosphere,
and down to 60 levels in the ocean.
Most common global climate simulations
begin at initial state resembling
the beginning of the 20th century,
and then respond over time to changes
in the earth's energy budget
by processes such as the amount of incoming solar radiation
or atmospheric concentrations
of greenhouse gases and aerosols.
Using the equations for the basic laws of physics,
fluid motion and chemistry,
variables such as temperature, precipitation,
wind, moisture and pressure are solved
with each of the grid cells
and are able to interact with each other
across space and time.
For example, the winds may be blowing colder air
into regions over several time steps
the temperature at a given grid point
would decrease because the computer calculates
where the wind field moves that colder air mass.
When we visualize the results
or output of these global climate models,
it is sometimes difficult to tell the difference
between the model output and actual measurements
from satellites, weather stations
or other observing systems.
That's how good today's global climate models are.
The current generation of global climate models
includes the physics that represent
how radiation is transmitted,
reflected and absorbed within the atmosphere
and at the earth's surface.
They represent clouds, rain and snow.
Evaporation of water from the oceans,
transpiration from plants,
the movement of water into the soil,
and ocean circulation around the globe.
They can generate tropical storms,
cold fronts, jet streams and trade winds.
They can also release sulfur dioxide
through volcanic eruptions
or absorb carbon dioxide in the oceans and forests.
Essentially, all of the major drivers of our climate system
are represented in the current generation
of global climate models.
Some processes are either too small in size
or too short in duration to be modeled well.
In these cases, simplified representations
of these processes called parameterizations are used.
Individual thunderstorms are one example
of these small scale phenomena.
In these cases, modelers represent the physical impacts
of these processes
such as the exchange of heat and moisture
between the small scale and the large scale.
Global climate models typically include
parameterizations for processes
such as small scale vertical motions or convection,
turbulence near the earth's surface,
development of cloud droplets,
raindrops and snowflakes.
And molecular interaction with solar
and terrestrial radiation.
Although global climate models have seen
significant improvements over the last few decades,
they still are not perfect.
No model can exactly reproduce our complex climate system.
There are still physical processes in our climate system
that scientists are trying to better understand,
and as they do so,
that knowledge will continue to be incorporated
into climate models.
When you think about the increasing complexity
of the represented processes
and the millions of grid points
needed to cover the earth's surface, atmosphere and oceans,
you realize that the computer power needed
to calculate thousands of equations
over hundreds of years is immense.
That is why global climate models
need to run on super computers.
In fact, we use some of the fastest computers in the world
to run our global climate models.
With all that needed computing power,
why do we even model the climate in this way?
The main reason is that we are trying to understand
how atmospheric processes and feedbacks
impact our climate system,
especially in areas where there are few measurements
such as in South America or Asia.
We also can learn about our climate system
by making changes in the model
and seeing how those changes affect the climate.
Since we only have one planet,
we can't learn about how our atmosphere works
by conducting lab experiments on it.
We must model it instead.
We also use climate models
to measure the influence humans have on our climate.
We do this by running the models
with and without man made greenhouse gas emissions
in what are called fingerprint studies.
And then compare the similarities
and differences in the results.
Finally and perhaps most importantly for decision makers
is that we can use climate models
to project what our future climate may be.
Global climate models are the most important tools
for showing us that our future climate depends
on the decisions we make today.
Without global climate models,
we would not be able to manage for our changing climate.