1.week

Apologies for not keeping up with this blog as often as I'd like!
Unlike most high schools and universities in WA, my uni's midsem break only lasts a week.
So while everyone is still out partying, we UWA students are already back to that all-so-familiar lecture theatre and dodgy tutorial rooms.
It's quite common to hear students telling you they use their midsem breaks to catch up on lectures and assignments.
And they do mean it, really.
But something always gets in the way. Namely, procrastination.
Or in this semester's case, episode leaks of the fifth season of Game of Thrones.
And it isn't surprising how spending 5 hours watching those episodes can escalate to spending an entire week binge-watching on Netflix!

Figure 1. A cute little succulent plant I got from this year's EnviroFest.
I've always wanted a rock as a pet, but this is so much better. Its low-maintanence AND alive. Those blue and green gems are also irresistible! I keep it in my room now and water it weekly (because I'm just that busy forgetful).

Fortunately for me, I have not fell into the dark, inescapable world of TV-shows.
Don't get me wrong. I get hooked to things really easily.
But as long as I stay away from them, I should be relatively safe. Right? RIGHT!?
People might say I'm missing out but I'm not.
A perk of being hooked to things easily is that I'm also easily entertained.
YES, I admit I liked writing up my paper for a bunch of plants competing for nutrients!
As a result, midsem breaks usually find me in the library at uni. Churning away on a computer.
Although it has never happened to me yet, I think people around me are somewhat irritated by my keyboarding ethics (I type really loudly).
Fortunately for all library-goers, I wasn't at the uni library (much) this semester.

Figure 2. Over the Easter weekend, I also went for a film at my uni's open cinema, Somerville Auditorium.
The auditorium looked great; lighted up bright and surrounded by tall trees. And the pizza they sold was to die for!
It was my second time watching a film there. The films were curated as part of the Perth International Arts Festival.
My friend wanted to catch a German film called 'Phoenix'.

Earlier this year/late last year, I had decided to become more active and not type so much.
And that's how I got into volunteering TONS, all of which coincided with my break.
Somehow, I had the 'brilliant' idea to do volunteering work by day and work on assignments by night.
Well, you'll be happy to know that, just like 80% of uni students, assignments were neglected throughout the break!
Having the long Easter weekend prior to the break was also...not-so-ideal, because all public libraries were closed.
But by the end of the week, I might've been completely exhausted, with assignments still stacked in front of me; but it was some really great experience and I'm really appreciative of it.
tl;dr I'm happy because I procrastinated by volunteering.

Figure 3. More pictures of my daily coffee fix. Double it this time! Actually, it's not real coffee; but chai latte.
Fun fact: I seem to get some weird gastronomic activity going on after I drink coffee so it's best for me to stick to lattes from now on. Chai's perfect as it tastes exotic and spicy and not bitter. I clearly have an obsession going on with it! Unfortunately, chai lattes are also sold at a higher price at cafes (and they don't even use natural ingredients!).

Over the course of the week, I was at the citizen science project office, MicroBlitz.
Helping my manager send out loads of kits to MicroBlitzers (you should sign up too!).
I managed to eavesdrop on the agendas my manager was working on, which is great if I ever wanted to become more involved with the project.

Figure 4. A few weeks ago, MicroBlitz made an appearance at the local Caravan and Camping Show.
Of course, I was there to volunteer a bit of my time over the weekend. Unfortunately, we didn't get a very good spot.
But still, no one could escape our trademark 'lure them in with lollies' trick (which is what Australian call gummy candy. Weird...). Doing outreach work like these might eventually help me develop some better communication skills.
Plus, it's a great opportunity to get to know some of the other volunteers.

The next day, I joined a bunch of other volunteers to do some building sustainability audits with Sustainable Energy Now.
A big reason why I did this was because environmental consultancy firms handle lots of these 'audits'.
I just had to find out for myself what these things were.
Auditing was pretty mundane but people tend to find ways to keep themselves entertained.
For me, it was spotting cool features in the faculty offices, getting myself acquainted with the building's architecture AND having a glimpse at the different offices our academics have.
I was definitely not disappointed with that last part.
Every room was different. And I'd say it reflects the occupant really well.
One of the room was full of books with only a single trail leading to their desk (also filled with books).
We also got academics with clothes, weird-smelling rooms, coffee machines (a big NO for energy efficiency, people!) and vintage clock collections (don't ask).
Having to go door-to-door asking academics if we could audit their rooms also gave me a different vibe.
I wasn't going in as a student begging for more marks on an assignment.
Maybe it's the way we communicated. But somehow, I felt like we were a bit more like equals in that situation.
Plus, we got free pizza and fair-trade dark chocolates.

Figure 5. A detailed map of the Social Science Building I got from SEN UWA to aid me in my auditing endeavours!
Unfortunately for us, most of the academics weren't in their office that day so we had the privilege of breaking in, looking at their stuff and sitting on their chairs. Contrary to what the map shows, the building is actually humongous; or really confusing, to say the least. Although we were only assigned to do half the building (and other major advantages), our group finished last!

On Thursday and Friday, I did some hands-on work with a PhD student from the School of Plant Biology.
His name's Kenny and he's doing research on plant-soil interactions, with a particular focus on nitrogen-fixing plants.
It sounds cool and all, but I didn't really get to do much.
A key thing to do in mind while doing research is that things are incredibly repetitive.
My job was to unload plants from their pots, wash the soil away, then remove the finer organic material (debris, twigs etc) from the roots.
And mind you, those are some really tangled up roots.
A single plant could take up to 30 minutes, depending on the soil conditions and species.
For two whole days, I've basically stuck to removing stuff from the roots.
It really hurts my eyes and my fingers get really tired from holding forceps all day long.
I think that might've been the closest I've ever been to experiencing Repetitive Strain Injury.
Don't try it!
But Kenny's great and really easy to talk to (I'm not, because I'm too busy trying not to screw up).
I got some really good tips and insight into the world of research.
Hopefully, all this networking will end up with doing some real lab-work, with fancy gizmos and whatnot.
Then again, even fancy gizmos get boring when you have to repeat a process a hundred times!

Figure 6. My volunteering with Kenny had me remove debris and other organic material from plant roots.
He was working with several species of plants, growing in different soil conditions. Depending on these two factors,
the root morphology might go from fairly clean to nightmarish-to-work-on levels.
To be honest, I'm not too quite sure what I'm doing or whether I'm even doing an OK job. Geez, I wouldn't want to be the reason his dataset looks out of whack! But I'm sure someone'll stop me if I'm not doing something right.
Did I mention I had to listen to Triple J for two whole days while working in the greenhouse? Pure torture.
I'm sorry, but they really aren't my cup of tea. 

I think that sums up what I did over the break.
I still remember what I was doing exactly a year from now.
My whole break was spent at the library writing up two papers.
I guess as you go through uni, you learn how to do your work more efficiently, like on the night before its due.
Because that's me right now! Like I said before, I was still facing piles of assignments at the end of the break.
Go me!
But totally no regrets.
It was great not being looked up in a library trying to vomit words for my reports.


Listening to The Days - Fast Forward Music (cover)

Back to school,

TK

Weather vs Climate

The question remains: If we're crap at accurately predicting weather for more than a week into the future, why are climate scientists so sure of their models' results?

The answer can be simple. And it can be extremely complicated.
So complicated that I'm not even sure if I'm sharing science or pseudo-science.
But I shall try my best to explain.
Climate does not equal weather.
In a way (but not so in a way), weather is a part of climate.
I heard a really useful analogy once (and hopefully my brain made the right connections).
Imagine an empty swimming pool.
You're dumping loads of water into the pool.
You measure how big the pool is; how much water you need; how quickly is the pool filling up; what would happen if you poured even more water in?
That's climate.
Then you see how many tiny ripples are produced; how many bubbles are produced; how does the water splash around?
That's weather.
In climate, you look at things on a larger, more macro scale.
But you really need to focus and look real close when it comes to weather.
That's why we're more confident at looking at the big picture (climate) and not sweating the little details (weather).
To be more specific, weather is everything happening in the atmosphere at any moment.
Climate is just a statistical average of the climate over a long long period of time (Ie: what's the average temperature of 2014?).

A lot of times (at least for me), I see the results of climate models in the form of temperature.
"Ohhhh if we keep emitting carbon dioxide, the temperature will increase by x amount."
Why don't they ever give us something more "weather forecast-y"? Like air circulation?
That's because air movement relies on the laws of Dynamics, something we don't fully understand yet.
However, what we do understand is the Law of Thermodynamics.
That's why we're more confident in predicting temperature, of all the variables to look at.
That's definitely a bonus.
We use what we know as an indicator of future climate, and rely less on something we're unsure of.
At least then we can call our results 'credible' and don't risk getting any 'risky' predictions.

Another way to look at this is through the problems that arise from predicting weather and climate.
As I've mentioned previously, after predicting at 5-7 days' worth of weather, Mr. Chaos Theory kicks in and we get predictions that might be very different from what will actually happen.
We can also call this 'high sensitivity to initial values'.
Our tools aren't accurate enough to provide measurements that will minimise this sensitivity.
If we have more accurate tools, maybe we could predict a month into the future before Mr. Chaos Theory screws us up.
This applies to weather, and not climate (according to some).
In the climate system, it's believed that if we create a realistic model environment, everything will 'work out in the end'.
At some point, no matter how crazy the system goes, it will reach an equilibrium, a stable state.
This realistic model environment includes things such as concentration of greenhouse gas in the atmosphere, amount of solar radiation we're receiving, the flow of air currents in the atmosphere etc.
If those values (we call them 'boundaries') are set to the same as our Earth, we can get a pretty accurate reading on things.
So weather prediction is a 'initial value' problem.
And climate prediction is a 'boundary value' problem.
These sort of problems are really opinion-driven.
Some people think that climate modelling is purely a 'boundary' problem.
But others, like my wonderful lecturer, think that it's a 'boundary' AND 'initial value' problem.
Geez, I hope I explained that well enough (and true enough).

It would be depressing to end this 'trilogy' on an uncertain note.
So I'll write about a simple, yet fairly effective solution scientists have developed.
It's called "Ensemble Modelling".
What you do is basically, run several models at the same time.
But with each of them, you use some slight different initial values.
At the end of it, you can see how the models reacted differently to the similar inputs.
If you graph that up, you'll get a range of possible outcomes (Figure 1).
And that's really helpful, because replicating the modelling run several times gives a sense of consistency to our results.
Depending on how you use ensembles, you can either test to see how consistent your models are, compared to others (by putting the same inputs in and observing what comes out); or how slight changes in input values can change the results (by using the same model but with slightly different inputs).
This simple, yet computationally mind-blowing, technique has enabled us to become more confident in our forecasting and it gives us a rough idea of how large our uncertainties are.
Thanks to this, we've been able to do weather predictions up to 10-14 days into the future (instead of 5-7).
This is only a small step in creating reliable climate models, but our innovations won't stop there.
We'll continue developing better techniques and stronger supercomputers.
And one day, we might actually be able to plan our fishing trips months in advance.

Figure 1. The model output from a ensemble modelling run. The different-coloured lines represent different climate models used in this process. Although every model produced different results, once we overlap them, we can actually observe a rough area of what the possible climate might be. After that, they calculate the mean of all these results (the thick black line). Ensembles also tell us how big our uncertainty is. The wider the coloured-band areas are, the more uncertain these projections will be. Image taken from RealClimate. 

And that concludes this 3-part blog post about my assignment: climate modelling.
Funny thing is, I've already submitted my assignment a week ago before writing this.
Let's just say, by the end of the week I can't be stuffed with writing a good essay anymore.
Besides, it's only worth 10%.
Now I have another paper to write. But I probably won't blog about it.
Just because it looks incredibly dry and boring.
Plus, I wouldn't know how to blog about it even if I tried.
Good news is, I'm already halfway through the semester.
Just a little (actually 50%) more!


Listening to Hey Ya! - Glee Cast

Back to Writing,

TK