She's a Modeller

Over the course of my (short and to-be-completed) undergraduate studies, I've had the pleasure of meeting some really great scientists (No, I don't stalk my lecturers... well, actually... nevermind).

The point is, I've met quite a few climate scientists over the year.

Surprisingly (or not), they are all female. 

So, I guess there's a correlation between being female and studying the most controversial field in science (next to GM crops and vaccination).

Anyway, as a student, we are kinda expected to be a "Jack of all trades, Master of none".

That's why I have to study Earth Science, Communications, Biology, Ecology, Genetics, Statistics, Biodiversity Conservation etc in my degree. 

And this semester, it's my turn to try and tackle a unit called "The Climate System".

At the beginning, I was a little excited at the prospect of finally studying what my "scientist acquaintances" are doing/did in their PhD: Climate.

I guess I can finally understand the reasons they were interested in looking at the global climate.

My bubble sorta popped at my first lecture, when I realised the climate system, is mostly just about the atmosphere, which I do not particularly like. 

However, many students have done this and have lived to tell the tale, so I shall persevere.

For our first assignment, we had to write an essay... with some rather ambiguous instructions.

We could pick to write about one of two topics (Wow, is "two" going to be a recurring theme again in this post?):

1. If weather forecasts can only predict one week into the future, how can climate scientists predict the climate for the next 50 to 100 years!?
2. Write about the El Nino Southern Oscillation (ENSO) and bla bla bla...

People who hear me whine everyday would know how much I hate ENSO.

And therefore, I will not write about ENSO.

Which leaves with Climate Modelling *yay*.

To help me better structure my essay, I will once again blog about my assignment in order to gain a better understanding of...the structure.

So what is climate modelling?

It's (at its most basic form) human's attempt to create a virtual Earth.

We do this by applying mathematical equations that describe the laws and forces of nature.

So you'll get an equation for the conservation of energy, an equation of the laws of thermodynamics etc.

And so through the use of maths (UGH...), we can create/model the Earth's atmosphere, which is the biggest player in the climate system.

However, the atmosphere itself is highly complex. 

If we were to encompass ALL the elements and processes in the atmosphere, it would take our computers wayyyy too long to model the Earth. 

That's why we started with only a few factors. And as computer processors grew faster, we could put in even more factors (but still not all of them).

Of course, if the model was to look at the Earth as ONE big system, it would overload and explode.

Therefore, we have to split the atmosphere up into tiny boxes/grids (as shown in Figure 1). 

And then, in each of the boxes, we apply a whole set of the mathematical equations (mass, energy, thermodynamics).

At this scale, our computer can calculate everything going on in that box and come up with some answers (Oh, the temperature in Box 1 is 39°C).

It does this for every box in the model. And then the boxes communicate with each other.

Box 2 is 34°C, therefore heat will transfer from Box 1 (39°C) to Box 2.

[NOTE: I could be wrong with all the physics going on here. But hopefully my explanations will be sufficient for understanding how models work.]

With this, we have the Earth divided into boxes. 

Each box with has calculated values in them (using maths).

And then the boxes communicate their values with each other (using more maths).

Figure 1. Discretisation is the process of taking one continuous Earth and slicing it up into separate cubes/grids. This process helps simplify climate models enough to make them solvable (by computers).
Computers will take the equations in each cube and calculate them, communicating data with other cubes.
Taken from ETH Zurich.

If you're still keeping up, I am genuinely impressed.

Not because of the complex details of climate modelling, but because of my crap communicating skills.

Anyway, having the atmosphere representing the climate isn't enough.

The ocean is another major player (along with the biosphere, lithosphere and cryosphere).

Thus, scientists have made models of them too.

And what they did next is combine the atmosphere model, with the ocean model (and any other models they have).

So now, the tiny boxes in the model communicate with each other. 

And the models themselves communicate and exchange data with other models.

Because you know... the atmosphere interacts with other systems on Earth, vice versa.

By taking in more factors (the atmosphere, ocean, land, biology etc), we are getting closer to creating a 99.9% copy of the Earth.

Of course, we can't possibly hope to replicate the planet 100% (something I'll get into later).

But with more models at our hands, we can predict the climate pretty well, don't you think?

And as our computers get faster and faster, we can couple MORE models together and predict further into the future.

After the modelling run is complete, you'll get data about what your "virtual Earth" thinks might happen (which can be illustrated into Figure 2). 

With this, climate scientists publish their results, try to use this data to educate to public (but are hated for it) and inform policy makers (but are ignored by them).

Figure 2. A typical graph resulting from climate model data. Each pixel in the graph represents a box/grid that resulted from discretisation. If the cube size was smaller, we would get a more "smooth" picture and less obvious pixels. But doing so will dramatically increase processing time several folds. Taken from IMAGe.

As I promised myself to keep things light and simple, I will stop here. 

But I'll definitely get back to this topic in my next post.

The content of this blog post will form the first (of three) section of my essay.

I hope I communicated the science well enough.

And I also hope that I didn't make any mistakes with the science.

*Fingers crossed*

Listening to Chandelier - Glee Cast (Originally by Sia)

Modelling,

TK