Open thread—post away

I am moving over a series of questions asked on another blog. My statements are in italics, the questions are in regular type.

1. The latest IPCC report seems to have removed a large portion of quantitative predictions and just goes with “may increase”, “may cause bad things”, etc.

“Seems”? How about some specific examples? What basis for comparison was used to arrive at this determination? Word counts? What?

2. That’s not really a scientific statement. ( The latest IPCC report seems to have removed a large portion of quantitative predictions and just goes with “may increase”, “may cause bad things”, etc.)

Pick a paper from some field other than climatology which you trust. Count how many times it uses qualifiers such as “may”, “might”, “could” etc. Keep in mind that a good scientific study is honest about uncertainty.

3. Virtually all the predictions from the models were barely within the error margins or outside the margins.
Which predictions, when? Over what period of time? Are we talking the last 20 years here or something else? Which models? Were some closer than others? Why were some more off than others?

4. More extreme weather?
When were those predictions made? What were the specific predictions made? What period of time did they cover (ie, how far in the future did the predictions cover from the time they were made)?

5. Arctic ice melting–yes, but faster than the models predicted, so another fail.

And that falsifies CO2 warming how exactly? Think about what you just wrote — a predicted effect of warming happened faster than predicted, and that falsifies the theory that CO2 causes warming?

6. Some thought Arctic and Antarctic ice melts would mirror each other, but no, that didn’t happen.
Specifics, Sheri. Who said this? When did they say it? Are you talking Antarctic sea ice or land ice? (Two very different animals). Same question as previous: how does a failed prediction of a secondary effect of warming falisify the underlying theory behind the warming itself?

7. Lack of snow–some places, some not.
Which places? How far off were the predictions? When were the predictions made? Snowmelt is an effect of warming: how does a failed prediction of an effect of warming falsify the underlying theory behind the warming itself?

8. Species extinctions–nope.
Who made the predictions? When did they make them? Over what period of time were the predictions supposed to take place?

 

My responses (note that this is a holiday weekend and I will be away from my computer much of the time.  Answers when I have time.  Other readers feel free to jump in with answers.  Makes it more fun!)

Number 2:  Clarification.  Yes, papers do use the terms “may”, “might”, etc.  This is indicative that what is being studied is still not fully understood or researched.  It is not known with near certainty.   If the point of the comment was much of science is uncertain, yes, it certainly is.  Which is why we should not be making policies and pretending like we do have certainty.  Without actual numbers and data, there’s no objective measures of “may” “might”.  For something to be scientifically likely, one needs to know what the probability, using an actual number, is and how that probability was arrived at.  As I am  prone to repeat, “There may be unicorns”, but that’s not a scientific statement.  There are unicorns is scientific and only true if the scientist can produce a unicorn.  There is a 10% chance there are unicorns would require the data and method used to arrive at the 10% to be examined before one can accept the statement as accurate.  I can say “The earth may be going into an ice age” and that statement is true.  Let’s say we have calculated to probability thereof accurately and it’s 2%.  The statement “The earth may be going……” is still very true.  It’s just not very probable based on current data.  Science needs to be more quantitative about its “mays”.  After all, science is about rules, quantification, verification.   Philosophy is about “may”.  (I do not have the time right now to search for the requested papers—may be able to do so later.)  

Number 5:  Yes, the arctic melting faster than predicted does call into question the theory.  If I have a theory that it will rain tomorrow and then it rains today and not tomorrow, my theory was wrong.  It did rain, but not when I predicted it would.  If I predict there will be a first snow later than the average date of September 15th (made up date, by the way) and it snows September 12th, my theory was wrong.   Theories being true require that the predictions are accurate in both quantity and timing.  If the Arctic ice is melting faster, then either there is another factor at play or the calculations of warming are inaccurate.  I put this example in frequently because people grab onto things that show warming, but completely ignore the time predictions.  If the time predictions are wrong, then theory may be wrong and it certainly is of very little value since its predictions are not accurate over time.

I will return later with more on the questions.  Part of the problem with climate science is the lack of time periods over which things will take place.  It will get warmer is not really a useful statement without some idea of how hot and when it will happen.  It’s just a prediction of a vague outcome.  Unfortunately we see it all the time in climate science.  Examples coming soon.

 

Check out Climate4kids.  There are new posts about climate change written at children’s level.  Share it with kids you know.

Scientific Badger

Scientific Badger

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Time flies

It looks like I’ve been missing in action on this blog for quite sometime.  It’s summer and between mowing, gardening and spending time at the cabin, I can’t seem to keep up with the computer work.  I am posting a letter to the editor I recently sent to my newpaper in response to another letter that was printed.  Hope to get back to posting more soon!

In response to Matt Armstrong’s letter:

Consensus is formed on the basis of many things–money, politics, power. It may start out based on facts, but can digress at any point if a new factor outweighs the others. Climate science seems to have digressed.

Scientists since the mid-19th century have been examining CO2 and its effects on temperature. That just means it’s not a new idea, not a correct one. Newton studied alchemy.

Even the IPCC admits there’s a pause or slowing in temperature. Berkeley Earth put out a paper on it. One can call it a slowing down or a pause. However, models did not predict any such slowing in any of the projections. Models all showed a consistent rise.

The use of the term “denialist” is indicative of a person with a very, very weak case. People who know their ideas are valid present their case and let the data and methodology speak for itself.

In spite of claims to the contrary, models lack sufficient resolution to incorporate clouds, a very important greenhouse factor. So “parameterization” is done. You don’t know the value, so you just use a number to represent this. Values varying from model to model. Also, natural phenomena like El Nino and La Nina cannot be included in the models. The models the IPCC used and most climate modelers used showed far more warming than actually occurred, meaning the models have serious flaws. The latest IPCC document, in the science section, admitted that models cannot forecast with any degree of certainty: “ Projections of future climate change are not like weather forecasts. It is not possible to make deterministic, definitive predictions of how climate will evolve over the next century and beyond as it is with short- term weather forecasts.”