How the Model Works

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En provenance du cours de The University of Chicago

Global Warming II: Create Your Own Models in Python

34 notes

The University of Chicago

Global Warming II: Create Your Own Models in Python

34 notes

This class provides a series of Python programming exercises intended to explore the use of numerical modeling in the Earth system and climate sciences. The scientific background for these models is presented in a companion class, Global Warming I: The Science and Modeling of Climate Change. This class assumes that you are new to Python programming (and this is indeed a great way to learn Python!), but that you will be able to pick up an elementary knowledge of Python syntax from another class or from on-line tutorials.

À partir de la leçon

A Model of Climate Changes Today

Background for this model was presented in Part I of this class, Unit 9, The Perturbed Carbon Cycle.

How the Model Works5:17

Rencontrer les enseignants

David Archer
Professor
Geophysical Sciences

The near future climate model is intended to try to

capture some of the dynamics of what's going on the nowish,

this decade, this 100 years with rising CO2.

The radiative forcing that that imposes on the climate.

And then the time evolving planetary response to that

change in the energy balance.

[COUGH] So, the CO2 concentration in the atmosphere, we're sort of

decomposing into a natural constant amount that was there before we were.

And then an exponentially growing part that's due to the industrial activity.

So given the CO2 concentration, we can calculate the radiative

forcing from that, which is number in watts per square meter.

Which indicates how much the change in CO2 from the initial

value has changed the energy balance.

So, eventually the planet warms up and makes the energy balance go back to zero.

So, this radiative forcing is defined after you put the CO2 in the air,

but before the temperature has had a chance to change at all.

So the radiative forcing is directly,

linearly proportional to the equilibrium temperature change.

Now it could be that in reality the temperature change could be some more

complicated function of the radiative forcing.

But to at first approximation, one watt per square meter

radiative forcing gets you three-quarters of a degree of temperature change,

and that proportionality is the climate sensitivity.

There's uncertainty to that, of course.

So the equilibrium temperature then is the temperature

that the planet is relaxing to given enough time.

But there's a long, non-neglible time scale for how long it takes for

the planet to reach the equilibrium temperature.

So, if the equilibrium temperature were to just suddenly change like this,

the transient temperature kind of relax torted on some longer timescale.

So this transient temperature is the one that's actually is what's controlling our

weather.

My python version of the world without us code looks like

it's got some variables initialized at the beginning and

a bunch of lists that are initialized and get filled up in a series of for loops.

And if we run it.

This is the CO2 concentrations as a function of time.

So, here is the business as usual, exponential ramp up.

And then here is the world without us,

where the CO2 is sort of slowly declining as it dissolves in the ocean.

We changed the plot, Comment out that one.

Reveal that one.

We will see the radiative forcing that are driving everything.

So this is the radiative forcing for masking.

It is proportional to the rate of increase of CO2,

just kind of call it industrial activity.

And then this suddenly drops to 0 at the world without us,

because the smoke all gets cleaned out of the air and that happens quickly.

So, in the business as usual scenario, the masking

is assumed to just stay at this value.

And so the temperature, really the total radiative forcing

starts to go up faster due to the rising CO2 concentration.

Here is the radiative forcing for the world without us simulation,

so it's following the business as usual up to the present day.

And then when the CO2 sort of stops rising but declines slowly that's here.

And then you also get this extra boost because the masking

effect goes away quickly.

So what we'll see

If we plot the temperatures.

The blue is business as usual and the green is actually the world without us.

And you see that pulling away the masking cooling effect from the aerosols

results in a slight increase in temperature in spite of the fact that

people are no longer on the planet to be putting CO2 in the air.

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