Knowability and No Ability in the Earth and Climate Sciences

Download 0.54 Mb.
Date conversion17.07.2018
Size0.54 Mb.
1   2   3   4   5   6   7   8   9   10   ...   17

In Class Discussion

Maybe we should identify what we value in science – what motivates us? . The truth? The search for the truth?

Can truth only be defined in simpler systems (or subsystems of complex systems)? If for the latter, then you can’t really know there is an absolute, or whether you are close to it, or whether you have just moved further away from it.
If you come up with a theory that predicts something suprising that is later confirmed, shouldn’t that be closer to the truth? If a theory is of a lower dimension compared with the scale of the problems is describeds/informs/solves, then should this be a sign you are closer to the truth?
Physics is where “truth” originates. Perhaps it isn’t possible to find truth beyond the microscale?
Disturbed that we don’t aknowledge/teach that good scientists have ignore evidence that their idea was wrong – that data contradicts it. But Sandy points out that data can be wrong --- or misinterpreted.
Perhaps we should not be after the ‘truth’, but we should be after ‘useful models’
Choice of domain of a problem is almost as important as the question you are asking.
Science: 1. body of knowledge; 2. process of building information; 3. culture (how; honesty; guarding against ego; ) and motivation (understanding).
Honesty is the root of good science. Doesn’t imply that you fundamentally believe that truth exists?

    1. Student Comments (delivered prior to class)

There was a whole lot to chew on in these reading, so I will concentrate

on a bit of what I got out of the Brush reading:

Brush dealt principally with the issues that arise when trying to educate

new scientists using science’s often not-so-pretty history. A dilemma

arises, because history shows that often those we hold up as “good

scientists” don’t practice “proper” scientific methods.

In many of Brush’s examples of this behavior, the scientist does not

abandon their theory when observations contradict it (they seem to be

abandoning Popper’s Falsifyibility).

-When the big-brains (Einstein, Maxwell, …) disregard empirical data in

favor of their favored theory are they truly being subjective and just

appealing to the aesthetics of their conceptualization of the problem or

following their intuition, or is there rational reasoning that gives them

some criteria for when a theory is better than the data?
-In some of these cases an old theory with some refuting observations (or

anomalies to be more gentle) was abandoned for a new one, even though the

new one had more refuting observations (or the old one explained the data

better). Can this be appropriate to do? What if the new theory has more

anomalies but is more far reaching..
-Should we allow grander and more unifying theories to get away with

having more anomalies before we reject them?

-Do we have to work with only one theory/paradigm at a time? Sometimes it

can be more productive to continue thinking about things in multiple ways

while we wait for the data to hash things out better. We can’t run an

experiment with long-term climate change, so we may not be able to

effectively distinguish between two theories until the climate runs its

course. What can we learn by thinking two ways at once?

-What is the best way to facilitate breakthroughs? Is it productive to

teach everyone to be skeptical of the current state of the science, and

willing to break away from current paradigms and perhaps ignore the a few

pesky experiments when they don’t agree with a beautiful theory? Should we

only teach this to a select few, and let everyone else be “problem

solvers”? Should we not teach such methods at all, and just let the

big-brains go there on their own.



here are some late night ramblings.
Ramblings on "explanation" and "causality" in the

context of a complex system:

Expressing an explanation is a linear process, whereas

a particular phenomenon in a complex system might

arise from within and depend fundamentally on the

interplay of many of its components, thus having no

ultimate cause except the nature of the system itself.

We recognize this when we talk about the "chicken and

egg" problem. In this situation, perhaps it is

pointless to try to determine "causality". This might

work only if we can assume the "cause" to proceed

independently from all other components of the system.

In a more typical case, an "explanation" might consist

in highlighting those interactions within the system

that are necessary for the phenomenon to occur (e.g.

air-sea interaction for ENSO).

Ramblings on a potential theory of climate:

In physics, the search for grand unified theories is

an attempt to reduce all the known laws to

consequences of a more fundamental one, whereas in

earth sciences we know the fundamental equations (e.g.

Navier-Stokes) and we try to get insights on their

consequences. A search for a "theory of climate" is

perhaps like knowing the details of how molecules

interact and trying to discover thermodynamics.

However, in climate, it is not obvious that we can

coarse-grain our models of climate enough that any

such theory becomes insensitive to details. in fact,

one of the characteristics of the climate system is

its high degree of organization and its multiple-scale

interactions. Should we hope for such an overarching

theory or should we look for ad hoc ones tailored to

different situations?



Still working my way through the models paper, so I'll just respond

briefly to the other two papers...

With the Brush and McComas articles coming to more or less opposite

conclusions about what students should be taught about how science

works, it seems like a more fundamental question ought to be answered:

why do we bother teaching science (to non-scientists) in the first

place? Why have fine arts majors taking Weather 101 or every

ninth-grader dissecting frogs and crayfish? A little clarity here

might make the choice between these two points of view a little

I found the suggestion of using a deliberately fictionalized history

of science in the classroom pretty disturbing.
What sustains the myths that McComas identifies? Does someone or some

community stand gain anything through their perpetuation?

Rob N
some ideas:
i like the concept of 'context of discovery' and 'context of justification' in terms of a broad stroke description of the scientific process. there are elements of this in every project. too much focus on 'justification' leaves the work dry. cook book science that does not lead to significant results/break throughs. too much 'discovery' or creativity without the solid foundation of 'justification' leads to sloppy research that has potential but is not respectable in the end because it has little predictive power.
brush also brings up the idea of honest scientists. this is important to the scientific method. it is the foundation of everything, i think. you have to be able to trust what someone is telling you. i guess this doesn't really fall under the 'definition of science'. but it is an essential part of the 'culture of science'.

error in one generation is a neglected truth in another...

scientific myth 16: scientists know what science is....
Hi Gerard and David,
Overall I like the discussion of the scientific method. Seems that the author also favors "falsifiability" as a way to distinguish science. However I do think it is taken a bit far by stating, "the only truly conclusive knowledge produced by science results when a notion is falsified". I feel like something 'being able to be falsifiable' is different than 'must be falsified'. It seems that the author is suggesting that scientists pose really specific questions in order to obtain results.
Another issue that cuts at how science (most things?) are taught is true

learning vs. memorization. The hardest thing to teach in science is that memorizing science facts doesn't mean you are thinking scientifically. The difficulty is that in some sectors it is necessary (anatomy for example). A bit off topic but Richard Feynman had a great essay on this. He uses the memorization of science facts and lack of true understanding to critique how science often ends up getting done later on (if I remember right). This seems to me an important issue that ties into all the issues relating to falsities of the scientific method as it is taught (or memorized!).

The question of "what is science?" still sits uneasy with me. A few points that come to mind:
- Instead of only being falsifiable, I guess I think of science as trying to answer a question for which the answer is at present unknown, but believed to exist, and can be explained by aspects of the nature which it resides in.
- Can we really classify science as cleanly as we used to, and still expect to? Are there too many scientists attacking too many specific scientific problems that don't lump nicely together?

- I'm not sure if this idea of "pre-science" really gets us anywhere. All sciences were "pre-science" at some point and just because all science isn't at the same state right now doesn't mean it is actually fair to compare them.

Models... I hope we still think they are useful by the end of the quarter, otherwise I might need to switch to comparative literature while I can!
So I was thinking:


We can pretty easily agree that not all scientists work the same way when they want to prove a theory.

But are there within the climate-scientist society some common methods which the scientists work from – probably not.

Then one should think that within each group say for example the paleo-proxy group there is a common method from which the scientist works from. Are we able to describe this method?


Is it possible to make some generalizations of what a scientist from the climate society has to come up with in order to convince his colleagues that his theory is correct?



Hans Christian
Week 3
Brush article

Myths of the nature of science

Models in Science
***How do we efficiently strive for the "truth"?

- Have impartiality, logical rigor, followed by experimental verification of hypotheses

- Have skepticism about established dogma ("A genius knows when to break the rules")

Many times, we disregard anomalies as noise. But what exactly is "noise"? And how do we decide if we can really ignore "noise" and have confidence that disregarding noise will not change the conclusions made?

A new theory arises that challenges previously made theory. Both new and old theories have their own inconsistencies (or uncertainties). When two theories compete for the truth, new theory often gets rejected, rather than the old theory (supposedly because the old theory is more plausible than the new theory.) But could there be cases where we unconsciously favor the old, existing theory over the new, radical theory just because we like conservative thinking? Is this habit hard to break?

We are rarely taught uncertainties of ideas in class. That's understandable for introductory classes, but what about graduate courses? Students aren't taught to check the validity of information provided in class, which might be a problem... (some examples include the thermohaline overturning circulation)
- Use models to answer questions in a simplified world

If the end result is good (match reality), but the theory behind the model is uncertain, how reliable is the model? The model almost becomes the object of study, rather than the question it was made to answer. This process is also informative.

From: James Booth

Date: Wed Apr 12, 2006 12:57:12 AM US/Pacific

To: gerard roe

Subject: Week 2 readings

Question related to _Models in Science_
In the last sentence of section 1.3,

'The resulting model then is an interpretation of the general law.'

In this implying that the general law is not a model?, did I miss this connection being drawn elsewhere in the reading?
Also, I like the separation of Aristotelian and Galilean idealizations. Would you say that most models in earth sciences fall in one category?
_Should History of Science be rated X_
He seems to prove that in some cases a subjectivity, or blind faith in a theory was partially responsible for continued study. For instance,

Maxwell continued to believe-in and study the kinetic theory of gases despite the experimental results that seemed to refute it. Is it worth looking deeper at the root of this subjectivity? Is that even possible?

Heisenberg's recollection of Einstien's assertion: 'It is the theory which decides what we can observe' sends my mind into a conspiratorial relm. Does the math theory lead us to an explanation which must be the one that we observe because the math theory and the observation techniques are both designed by human brains. This question might be better suited for the templars and National > Enquirer.
Jimmy Booth

1   2   3   4   5   6   7   8   9   10   ...   17

The database is protected by copyright © 2017
send message

    Main page