My belief in Global Warming is getting shaky

[Overdog]

Originally Posted by Zythryn

...Again, no one has said the models are perfect. Infi and others have stated they are getting better.

You are making my point with this statement...

Please show how Grassl's criteria is wrong, or met, or conceed that the accuracy of the models remains a matter of opinion.

[InfiniteNow]

Originally Posted by Overdog

Please show how Grassl's criteria is wrong, or met, or conceed that the accuracy of the models remains a matter of opinion.

Would you care to explain to everyone why you think accuracy is a matter of opinion?


You seem to be equivocating "accuracy" with "acceptance of various levels of accuracy." As we all know, equivocation is a logical fallacy.



I've shown that the models are accurate, and I've shared countless links with real, verifiable, and specific data in support of my posts. I can't help but notice a definite asymmetry of effort going into our posts, and for you to suggest that I have not addressed your points is laughable.


I'm tired. It's been a long weekend with friends and family cooking and running errands. I spent several hours finishing a concrete project on my house, and redoing the drywall in my hallway, only to then install a set of french doors in the 100 degree Texas heat, and I still took the time to come here and respond to your challenges with vigor and well substantiated points.

It has become abundantly clear to me that there is nothing more I can say that will move you from the position whcih you have chosen to assume, with your heels dug deeply at the level of vague and abstract challenges to the concept of modelling, as opposed to specific addressable criticisms.

If your argument had any merit, you would have long ago supplied specific models suffering from the issues you describe. Instead, when questioned which specific models have problems, you pivot back to "All of them."


Since you deem all responses to your criticisms as "not relevant to your point," I suggest that the common theme is that it is your point itself which is without relevance.

[Overdog]

Originally Posted by InfiniteNow

Would you care to explain to everyone why you think accuracy is a matter of opinion?

Well, mainly because you have done absolutely nothing to refute it. You accused me of acedemic dishonesty for questioning the accuracy of the models. Now I have turned the tables on you, and frankly, your response has been pathetic. Your obstinate refusal to recognize that these models at the present, are merely "best guesses" is very revealing to me. You have not at all addressed the critisisms I have raised. I submit that the very accusation of academic dishonesty you directed at me applies equally to you.
[/Quote]

You seem to be equivocating "accuracy" with "acceptance of various levels of accuracy." As we all know, equivocation is a logical fallacy.

I'm not equivocating anything. I have stated my reasons for asserting that the accuracy of the models is a matter of opinion and you have done nothing to refute them, and you refuse to conceed that point. I am still waiting for you to do one or the other.

I've shown that the models are accurate, and I've shared countless links with real, verifiable, and specific data in support of my posts.

You have not shown that the models are accurate. You have said that they are "Damn close" and are "getting better". Bullshit. You have done everything you can to avoid addressing the issues I have raised.

I can't help but notice a definite asymmetry of effort going into our posts, and for you to suggest that I have not addressed your points is laughable.

Well that's your problem. Maybe you ought to think twice before you accuse people of academic dishonesty and hand waving.

I'm tired. It's been a long weekend with friends and family cooking and running errands. I spent several hours finishing a concrete project on my house, and redoing the drywall in my hallway, only to then install a set of french doors in the 100 degree Texas heat, and I still took the time to come here and respond to your challenges with vigor and well substantiated points.

Me too. Still, it's not an excuse. You need to tell me why Grassl's criteria is wrong, or show me how it is met, otherwise you are the one who is waving hands, not me.

It has become abundantly clear to me that there is nothing more I can say that will move you from the position whcih you have chosen to assume, with your heels dug deeply at the level of vague and abstract challenges to the concept of modelling, as opposed to specific addressable criticisms.

No, all you have to do is refute my points. Very simple. Refute them, and I will change my position.

If your argument had any merit, you would have long ago supplied specific models suffering from the issues you describe. Instead, when questioned which specific models have problems, you pivot back to "All of them."

This is a dodge that is indeed academically dishonest. I have given specific reasons for my position, and you have simply failed to refute them.

Since you deem all responses to your criticisms as "not relevant to your point," I suggest that the common theme is that it is your point itself which is without relevance.

I don't deem all responses to my criticisms as irrelavant, only those which do not address the specific issues or questions I have raised. I am still waiting for you to address them.

[Zythryn]

Originally Posted by Overdog

You are making my point with this statement...

Please show how Grassl's criteria is wrong, or met, or conceed that the accuracy of the models remains a matter of opinion.

Are you suggesting anyone said 'Climate models are perfect'??
If so, that is definately a strawman argument.
From my cursory glance at your posting, I would not say it is wrong. Just that it is not black and white.
Basically, if a model doesn't meet all of the criteria doesn't mean it has NO accuracy.
Also, would you be kind enough to link to Grassl's work?

[Overdog]

Originally Posted by Zythryn

Are you suggesting anyone said 'Climate models are perfect'??

Of course not.

From my cursory glance at your posting, I would not say it is wrong. Just that it is not black and white.

I'm not sure what you mean.

Basically, if a model doesn't meet all of the criteria doesn't mean it has NO accuracy.

I have been very careful not to make that claim. I am focusing in on a very fine point here, for a very specific reason. I think INow knows exactly why.

Also, would you be kind enough to link to Grassl's work?

I suggest you google it, thats what I would do.

[Zythryn]

My you are helpful.
Before asking I did google it. I got a photographer, a man who couldn't be identified for a number of years because he refused to speak, a business professor, an athelete a poet, and I stopped about there.
The professor is my most likely guess. However I could find nothing in the bio shown that indicated any corrallary such as you mention.

Originally Posted by overdog

I have been very careful not to make that claim.

You should be more careful in the future then. You have repeatedly called the models 'nothing more than prophesy'.
Since they have met part of your own arbitrary rules for validity, but not all four, I can only gather that if any model doesn't meet all 4 of your rules, then it holds no validity.

[Grains]

Originally Posted by modest

One small qualification that comes with this trend:



This is flat - completely flat - at least, I can't tell which way it's sloping. But, this is not the logarithmic trend line that has a curved line. That one slopes down to the very perceptive eye. The one depicted above is a straight line or linear trend and it comes out flat or level. This is not biased in any way - it's just a trend choice in Excel. The linear choice comes out completely flat and the logarithmic choice comes out ever so slightly angled down (and obviously curved).

Considering this thread, I'm sure there is a lot of fighting room in that, so let me stress one more time: this is just a choice of kinds of trendlines. There is no bias either way. Nevertheless, I think it's important to point this out as explicitly as possible considering what I had to go through to even get Grains to admit excel was making trends rather than averages. I think to be as descriptive and honest with this as possible is good.

I said this when I originally posted that pic, but I did not very clearly explicate in a way that would avoid future complications which I think I've now done.

Unfortunately this leave us in a position where both these statements are true:

• The last 10 years show no increase or decrease in temp
• The last 10 years show a decreasing temperature

Oh boy

~modest

Nice. You had a hard time getting it out of Grains????

The problem with your choice of trend line is the problem within itself. I just had to use you logarithmic trend line because I was proving the point to you that it was sloping down. Remember, when you told me to post proof or you were going to infract me. A logarithmic trendline is a best-fit curved line that is most useful when the rate of change in the data increases or decreases quickly and then levels out. Clearly this is not the case with our data and you should not have used a log trend line.

Because you have chosen to go with a log trend, it does act more like an average than anything else. I have posted the same chart with your trendline and an average line. You can see how the mimic each other and even overlap at certain times. Again, ***ALL*** trendlines run on this chart show a downward trend and you cannot manipulate it otherwise. A more accurate trendline representation would be to do a moving average and then trendlines within the major points of data on that. But I think the consensus no longer argues that the chart is not trending downward. And modest, that was the main point of the whole thing was trying to get you to see the downtrend not telling me it wasn't an average.

[InfiniteNow]

Originally Posted by Zythryn

Also, would you be kind enough to link to Grassl's work?

Since Overdog could not find the "kindness" to support his own position, I will assist.

He originally referred to Grassl's four criterion with a quote from this link:

Introduction to Physical Oceanography : Chapter 15 - Numerical Models - Assimilation Models

Which said:

Grassl (2000) lists four capabilities of a credible coupled general circulation model:

• Adequate representation of the present climate.
  
• Reproduction (within typical interannual and decades time-scale climate variability) of the changes since the start of the instrumental record for a given history of external forcing
  
• Reproduction of a different climate episode in the past as derived from paleoclimate records for given estimates of the history of external forcing
  
• Successful simulation of the gross features of an abrupt climate change event from the past.

Here is a link to that Grassl 2000 study, as well as its abstract:

Status and Improvements of Coupled General Circulation Models -- Grassl 288 (5473): 1991 -- Science

Coupled general circulation models (CGCMs) integrate our knowledge about atmospheric and oceanic circulation. Different versions of CGCMs are used to provide a better understanding of natural climate variability on interannual and decadal time scales, for extended weather forecasting, and for making seasonal climate scenario projections. They also help to reconstruct past climates, especially abrupt climate change processes. Model intercomparisons, new test data (mainly from satellites), more powerful computers, and parameterizations of atmospheric and oceanic processes have improved CGCM performance to such a degree that the model results are now used by many decision-makers, including governments. They are also fundamental for the detection and attribution of climate change.

[InfiniteNow]

I think it's worth noting that Grassl hasn't really contributed anything to the literature since 2000, nearly 9 years ago, nor has he spoken to the accuracy issue much since then.

He was, however, a reviewer on the IPCC 4, which states that:

There is considerable confidence that climate models provide credible quantitative estimates of future climate change, particularly at continental scales and above. This confidence comes from the foundation of the models in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes. Confidence in model estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). Over several decades of development, models have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases.

<...>

In summary, confidence in models comes from their physical basis, and their skill in representing observed climate and past climate changes. Models have proven to be extremely important tools for simulating and understanding climate, and there is
considerable confidence that they are able to provide credible quantitative estimates of future climate change, particularly at larger scales.

An additional note worth making, the improvements in our models since that 2000 time frame when Grassl published his paper are significant.

[Overdog]

Originally Posted by InfiniteNow

I think it's worth noting that Grassl hasn't really contributed anything to the literature since 2000, nearly 9 years ago, nor has he spoken to the accuracy issue much since then.

He was, however, a reviewer on the IPCC 4, which states that:

There is considerable confidence that climate models provide credible quantitative estimates of future climate change, particularly at continental scales and above. This confidence comes from the foundation of the models in accepted physical principles and from their ability to reproduce observed features of current climate and past climate changes. Confidence in model estimates is higher for some climate variables (e.g., temperature) than for others (e.g., precipitation). Over several decades of development, models have consistently provided a robust and unambiguous picture of significant climate warming in response to increasing greenhouse gases.

<...>

In summary, confidence in models comes from their physical basis, and their skill in representing observed climate and past climate changes. Models have proven to be extremely important tools for simulating and understanding climate, and there is
considerable confidence that they are able to provide credible quantitative estimates of future climate change, particularly at larger scales.

An additional note worth making, the improvements in our models since that 2000 time frame when Grassl published his paper are significant.

I can't tell if you are conceeding my point or not with this post.

On a scale of 1 to 100, exactly which number would "considerable confidence" corresponds to?

If you say 50, for example, then be prepared to show why it cannot possibly be 49, or 51, or else conceed that differences of opinion on the matter are legitimate!

I'm simply arguing that the accuracy of the models is not established fact, that differences of opinion regarding the accuracy are in fact legitimate, and that persons may have different opinions without being academically dishonest!

EDIT:
Is this an extremely academic point I'm trying to make here?
Yes it is, but it is precisely because it is a response to a charge of academic dishonesty.

Edit:
I would also like to add that I have learned from this discussion with INow, and my degree of confidence in the climate models is now greater than it was when I first entered into this discussion. I would be happy to discuss this, if we can move beyond the charge of academic dishonesty.