planetwater

Norm Costa recently published on 3 Quarks Daily his thoughts on “PSYCHOLOGICAL SCIENCE: MEASUREMENT, UNCERTAINTY, AND DETERMINISM” (part 1 and part 2).

A lot of his thoughts are mostly relevant to psychology, but I will try and extract some thoughts that are relevant to an environmental modeller. Mostly the thoughts that are relevant are related to measurement, error and uncertainty.

I do have a hard time on commenting on Costa’s thoughts, but I think they are well worth to be read and thought about!

Measurement

• a measurement is a comparison to a standard;
• standards do not last;
• I recently came across a funny unit: 1 knot, which is the velocity of a vessel which travels one minute of geographic latitude in one hour

Measurement of Precipitation

Photo by wfyurasko

Error

Costa does treat “error” not so much in a sense as in “measurement error”, but in terms of “what is research” and how do scientists deal with research and progress in research.

I like comparing scientific psychology with psychics because it dispels many false notions of science and makes room for psychology in the pantheon of science. For example:

• It dispels the notion that ‘real’ science is exact, objective, and dispassionate; Also, it blunts the objections of those who dismiss psychological science as inexact, subjective, and self-absorbed.
• It dispels the notion that there is such a thing as an exact science; Rather there are sciences that deal with relatively smaller errors of measurement (physics,) and others that deal with relatively larger errors of measurement (econometrics.) Psychology lies between the two in terms of the size of errors of measurement.
• Few scientists are objective and dispassionate in the absolute; Rather, science, by the way science is conducted, is self-correcting, in the long run, and keeps scientists on the straight and narrow.
• Scientists are not free of biases, preconceptions, misconceptions, and personal agendas; Rather, these can fuel the energy, motivation, and creativity of scientists.
• No scientific knowledge is absolute, unchanging, or final; Rather, all scientific knowledge is proximate and provisional, and only represents the best we can produce to this point in time. We can count on better data in the future superseding present-day knowledge.

Uncertainty

In his discussion on uncertainty, Costa talks quite a bit about Heisenberg’s uncertainty principle and how it relates to psychology. Here are two relevant passages:

For Heisenberg and all of quantum physics, UNCERTAINTY IS A PROPERTY OF NATURE. For scientific psychology, uncertainty is a function of the limitation of our measurement tools, not a property of nature.

Einstein’s view of the world was a deterministic one: Knowledge of an outcome is certain, provided all factors and antecedents are known. For quantum physics, outcomes are uncertain (probabilistic) because uncertainty is a property of nature, not a function of inadequate measuring. Einstein’s objection to this is captured in his famous statement, “God does not play dice.” In fact, God does play dice. God spends the whole damn day playing dice. Paradoxically, Einstein, the man who gave birth to quantum physics, could not accept Heisenberg’s ‘Uncertainty Principle’ and was forever bypassed by science and left to doter in the backwater of physics.

We were taught in environmental engineering undergrad-level that the first pictures of earth taken from space ignited an conditions on earth that allowed the seed of the environmental movement to prosper and grow in the 1970’s.

I just came across this movie, I have never seen something like it before, and I wonder what kind of conditions it might ignite.

This is the story of a designer, who worked at google. He explains how design at google is extremely data driven.

Yes, it’s true that a team at Google couldn’t decide between two blues, so they’re testing 41 shades between each blue to see which one performs better. I had a recent debate over whether a border should be 3, 4 or 5 pixels wide, and was asked to prove my case.

Picking up the google story, Scott Stevenson argues in this mini-pamphlet how important designers’ judgments in software design are.

How does this relate to planetwater.org or my work? I am obviously not mainly in software design. What I have done recently is I have been going through a lot of iterations of one problem with a master’s level student of mine. It has been a lot of fun at times and it has been frustrating at times. We could have tackled the problem by “just do it”. However, we took a lot of paths away from the main path, and we did learn a lot. Maybe it was not the most direct way, maybe we also created a lot of “failures”, maybe we could have been quicker. We did learn a lot, and our end-result is very good.

It remains, generally, that the boundary between design, statistics, environmental modelling, and even art is very interesting. It might be an art by itself. And dreaming is a big part of it.

Science is fun! It is fun, because things can emerge. Things that were not anticipated. It might be that the information of the things that eventually emerged has been there before you started, but you were not aware of it.

To this day things can emerge and there is no explanation. In these cases, experiments are not done to prove or to refute something, but because of fun. I am convinced this works in most fields. And it works even today, where it might seem that in some fields everything is found out. It works with “material experiments” such as this one where Frank Rietz played with glass beads. It can be in statistics, when you “play around” with a given data-set, and probably it can happen in any discipline. To a great deal, this is why I think science is fun!

Now, sit back, and watch this, and be amazed! 🙂

Nobel Prize in Economics

update Thursday; October 29, 2009: here is an overview-article, “The Non-Tragedy of the Commons”. It deals like my post with Hardin’s paper, it includes additional references to Elinor Ostrom’s work, and it shows solutions how the commons can be managed well.

The Nobel Price in Economics has been awarded this year to Elinor Ostrom. Besides being the first woman who has been awarded the Nobel Price in economics, she is also the first environmental economist. The Nobel Committee explains its choice for her due to her research on “problems related to the use of commons such as fishing grounds, groundwater resources, forests and pastures”.

According to The Globe and Mail,

Dr. Ostrom’s research, and her celebrated publication, Governing the Commons, challenged the prevailing wisdom that the best way to manage something is to privatize it or regulate it.

I haven’t read any of her works, in fact I haven’t heard of hear until this morning. However, the reasoning of the Nobel committee reminded me of probably one of the top five scientific papers I have read in my university career, at a very unlikely place. I once took a course entitled “ecological engineering”, given by Allan Werker who now seems to be at a company called anoxkaldnes. In this course we spent quite some time reading and discussing the paper “The Tragedy of the Commons” by Garrett Hardin. Back then this article sparked some of the most vivid discussions I have ever had in an engineering class, including some interesting modelling exercises with BerkeleyMadonna.

Right Livelihood Award

On a related note and since it seems to be award-season, I want to point out that the right livelihood awards 2009 have been awarded to David Suzuki, René Ngongo, Alyn Ware, and Catherine Hamlin.

David Suzuki is an interesting person, has great speaking and writing skills, and has undertaken a lot of action in his life to make the world a better place. His autobiographyis a remarkable read.

Even more remarkable is a speech given by his daughter to the assembly of the UN. She’s known in YouTube as the “Girl who Silenced the UN for 5 Minutes”:

I promise to continue to post on correlation examples really soon!

Folks,

the response to the regression line post was straight out phenomenal and mind-blowing. In the next sequel, we will look at some real data. I had this planned for today, but unfortunately preparing for the NUPUS conference, at which I will take part next week, takes longer than anticipated. I promise I will post on monday again.

However, I do have a suggestion for your weekend (if you’re not planning to climb up any mountains or if you are sick at home): read this!

I just found out that “the economist” has a sequel of classic debates, on various topics. The debate I’m suggesting for you to read is entitled “The value of H2O” — This house believes that water, as a scarce resource, should be priced according to its market value. Defending the motion is Mr Stephen J. Hoffmann, who recently published a book which is called just like this blog (more about this really soon). The arguments against the motion are represented by Dr Vandana Shiva.

I’ve recently taken a short course with Jacob Bear (see my summaries of days 1, 2, 3, and 4). This short course is still very actively in my mind. Jacob Bear was such a great teacher, and learning with his guidance was highly enjoyable — the way it should be. Hence, I want to share some thoughts today, on what I think makes a great teacher. I think it doesn’t hurt to think about this topic a little bit, because in our daily live, especially in an academic environment, we tend to have a lot of “teachers”, because we tend to want to learn regularly.

There are a few basics. In order to be a good teacher, you have to know your subject. You have to really know it, ideally by heart (which happens automatically if you are prepared). Ideally you don’t want to teach topics which you are currently learning yourself. I think, ideally you want to teach a little less than what you actually know. This is not because you want to hide knowledge from your students, but this is because you can’t be as confident on things you are just learning as you can be with things you have dealt with and worked with for some time.

I think it does not hurt if you are doing some research in the field you’re teaching on. Some can mean that you are doing or have recently done research in this field, or it can mean that you’re actively following what’s going on in the field via literature or via discussions. The point is, you want to know what the research community is currently up to. Also, I think it doesn’t hurt if you have written something like an overview of a topic. Writing an overview help you tremendously in organizing ideas and additionally this writing could be of help for your students. You also should have good slides and talk well.

From Good to Great

But what makes a teacher better than a good teacher? During that short course, it seemed to me like the “tipping points”, the decisive factors were the “little things”, the things that don’t jump at you immediately. Particularly, these were three things related to the “style” of presentation. Usually, as an engineer, I would consider style important, but not the decisive factor between good and great. These three things were (1) that the teacher was getting to the point, (2) that he was consistent, and (3) that he used brilliant illustrations. I am going to explain what I mean by each of these three.

Getting to the point means that the teacher knows at every instant where he wants to go, and what he needs to explain, successively, in order to get there. This implies that he also knows where he’s coming from, that he knows details on how he wants to explain a given thing (and how he does not want to explain that thing), and how things are related. If these relations are known and available to the teacher, this knowledge will almost automatically influence the language he uses. He knows what he wants to stress, and he will use his voice or other rhetorical features to point things out. Jacob Bear was the master of using repetitions. Generally, every single word had its weight, meant something special. He was very precise. But once in a while he would repeat something he just said, usually summarized and maybe with wording changed. By those repetitions he stressed the important things that he wanted his students to remember because they were the key building blocks necessary to understand what was about to come.

The second small thing I call “consistency”. During the entire four days of the course, whenever we talked about porosity, it was represented by the greek small-case letter “phi”. Every single time. This might require some extra time at the beginning, because you need to lay the foundations for your terminology, abbreviations, indexing conventions, mathematical formulations and symbols. However the rewards are worth the effort: as a student I didn’t have to think twice what phi in a given case meant. It was porosity. Always.

The third and final little thing are illustrations and sketches. They have to explain well what needs to be illustrated. That means they have to be concise [sic!] and well readable. Don’t get me wrong. They don’t have to be animated using fancy software. They don’t even have to be in colour. In fact, Jacob Bear just used chalk and the chalkboard. With a few lines he was able to illustrate exactly what needed to be illustrated. And that forgives slides that were sometimes not optimal. On the other hand, if you can explain something very well by words in a sentence, that might even be short, then do it! However, usually in an engineering-related field, a simple sketch can work a lot for you!

I don’t think using fancy media or animations alone make a great presentation. Sure, used wisely, they will not hurt. I don’t think age is critical. Sure, experience never hurts. However, for a good teacher to turn into a great teacher, he has to be able to get to the point, he needs to be consistent, and his illustrations need to be well made!

A colleague of mine pointed me to an extraordinary paper. It is funny, but there is much truth below the surface. It seems to be on hydrological modelling, but I think it is for anybody who deals with the analysis of complex systems.

The paper’s title is “The Hunting of the Hydrological Snark”, here is a link to the paper’s site at Wiley’s. The full reference is

V. Andréassian, N. Le Moine, T. Mathevet, J. Lerat, L. Berthet, and C. Perrin. The hunting of the hydrological snark. Hydrological Processes, 23:651–654, 2009.

The paper describes the steps required to hunt the hydrological “snark”, an “hypothetical, unknown and unseen monster”, which supposedly is a hydrological system, the hunt is a perfect model of the snark, and the hunting party the hydrological modellers. I’d highly recommend it for reading!

I’ve spent a fair bit of my time as a grad students trying to model groundwater systems. There have been long discussions on modelling and its philosophy. Today was a PhD defence of such a grad student. Typical thoughts afterwards tend to be “… if we only had more data… ” or “… if we only knew the underlying processes better and could describe them… ” or “… if we only had more computing power available… ” .

I think a key trait of an environmental modeller should be his or her awareness of the quality of the data and the limitations regarding the quality of the predictions of the model. So when I read the headline “Climate Models Trump Financial Models” I was a bit worried. Sure, climate change is a pressing problem, and there is a lot of effort put into improving climate models. However, for me as an environmental engineer it seems that global financial markets should be better understood than global warming. And if it’s only because finance has been around for longer than environmental engineering! 🙂

I had never put much thought into how financial models might work, so this article brought up an interesting point for me, even though I’m not quite sure what I think about it:

“Climate models are very complex but you more or less understand the basic physics or chemistry,” said Derman. “[Finance papers] look like physics but a lot of the similarity is syntactic more than semantic.”

For example, stock options are priced with the Black-Scholes model, which says that stock price movement can be seen to move like the random movements of particles suspended in a liquid, i.e. Brownian motion. But stock price models differ from particle models because they describe the aggregate actions of people.

I guess quite a few processes are modelled like Brownian Motion. Why not stock option pricing. This just means though that we don’t know the underlying processes of stock option pricing better, so we could model the pricing in a more deterministic way. Then I thought a bit and it occurred to me that if you asked me, I probably couldn’t explain to you what is going on in the financial world these days. Why are we having this crisis? What are the underlying processes? Then I found this wicked little movie that explains these processes:

The Crisis of Credit Visualized from Jonathan Jarvis on Vimeo.

Based on this video, this seems to be a fairly straight forward process… 🙂 But I agree, there is a human factor involved, which admittedly doesn’t make things easier. I wonder what would happen, if you would throw an environmental modeller, a psychologist, and a finance person into a room for a while!

It seems like Weird was on a roll writing about financial models: They also point out, that the length of the finger of a trader is an indication for his degree of success. For me, that seems a little far-fetched! However, there’s again one interesting thought:

But leading up to the crisis — and underlying public acceptance of the mistakes and wrongdoing that produced it — was a widespread belief in the fundamental rationality of free markets and economic behaviors. That assumption may need to be revisited.

As far as I can see, photos offer three advantages:

• You see through a different set of eyes. When I walk around with my camera up and running, I generally pay more attention to detail and to my surroundings. I turn around more often, and the landscape behind you tends to look differently than in front of you! Without a camera, I tend to miss that part.
• Photography helps your memory. If you have photographs from the past available, they help your brain by remembering how things were, or how things evolved over time. This can be very useful. Do you remember how the chairs in your cafeteria looked like or were arranged 6 months ago? If you have the chance of knowing or storing the information of where the photograph was taken, this is a piece of great additional information. Geotagging.
• Photography is art and as such is beautiful. This is if you are careful by some minimum amount when you create the photography.

Why am I writing about this? Two reasons: primarily I have been having a lot of fun with photography lately, and secondly photography has been proven to be highly useful in a medical case I have been involved with.

Before I went on that trip to Chile, I contemplated for a very long time about which camera to take. I wanted to take a camera, because this is the kind of trip you just don’t do on a regular basis.

I do have some photographic history, which lead to some standards. The history dates back to shooting Lego scenes with my neighbour in the grass of our garden when we were about 8 years old with some obscure Rollei camera. This is where I learned what shutter speed and aperture were. I had no idea about ISO back then. The second flourishing period of my photography past happened during my student-magazine days. I managed to acquire sufficient ads so we had enough money to purchase a Minolta 500si super. That was very thrilling. This was in the late 90s so our school had on the one hand a black and white digital scanner. But one which you had to drag manually over the piece of paper you wanted to scan, and it was only about 10cm wide. It was quite a mess, but very exciting when your picture showed up in Corel 3. On the other hand the school still had a lab, where we developed our b/w film and magnified it on paper. This was so cool. I clearly remember the first roll of film that I took out of its tiny little box. In the dark. And there were only two of us in the lab… 🙂

In the end it came down to the question DSLR or point and shoot. More flexibility and picture-quality on a DSLR versus portability on a long backpacking trip. Sony just had released a series of DSLRs on which I could use my old Minolta lenses. I made the decision against heavy weight. As I said, I had some standards, so I still wanted some manual control, so I bought the Panasonic Lumix DMC-FX500. And I have been very happy with it! It has a really great automatic program. It has both aperture and shutter priority. At the beginning I was not sure if the display at the back would be bright enough if it is really light out, but I have been happy with it. The only thing I am not overly happy with is the autofocus. At times it’s a little slow and at very few times it doesn’t focus what I want to focus. I also bought an Amod AGL 3080 GPS tracker, because I wanted to have access to the second advantage from the triplet above. This thing works really nice for its money and for what I wanted it for, for tagging the location of where a photo was taken. Only drawback here is that it goes through batteries quite quickly.

During the trip I had a lot of fun, and I have been using both camera and gps device quite extensively and happily. When I came back, I had about 2000 photographs and a few megabytes worth of gps logs. I was dawn back into daily life quite quickly, but since last weekend I had a new push to work on those pictures. I guess my general feeling was like this: Ok, I have this camera with which I am quite happy, but a DSLR would be a DSLR. I took all these pictures, I had looked through them, they seemed to be ok, but nothing too great, I thought. Then two things happened. I read a blog post, unfortunately I forgot where, saying that essentially every camera is the same, all have a shutter and a lense. So it depends largely on the photographer and what he or she makes out of the situation. On sunday the situation was sunny and snow was on the ground. I switched my camera to black and white mode, yes, back to the roots, baby! Admittedly, this was also inspired by some blog post. And we went on a walk and I took my camera. I guess these days this is called a “photowalk”. And it was a lot of fun!

Afterwards I had built enough desire to look at those pictures from Chile and those gps logs. So I came up with this workflow:

• Take the individual logs, process them, put them in google earth to see where I actually do have a log. This processing I do with a little python script which creates a simple kml file.
• Then I select the pictures which correspond to the location and time of the log file in Lightroom and drag them into HoudahGeo.
• I let HoudahGeo do its magic, check in GoogleEarth if the tagging is correct, and write the locations to the exif file
• I load the metadata back into Lightroom: while still having the pictures I geotagged selected I click under “Metadata” in the menu bar on “Read Metadata from File”.

During the process it is important to pay attention to the times. Before dragging the photos away from Lightroom it might be necessary to “Save Metadata on File” (cmd-S).

This little story made me very happy with photography, again! I have learned a lot about Lightroom and gps on the way! A really great resource for Lightroom has been Scott Kelby’s Lightroom 2 Book! Hopefully I can share some decent Chile pictures or that python script! 🙂