global warming: salvaging fact from heaps of BS

[Edtharan]

Here in New Zealand, over the past few days, we have had the biggest snow dump for about 20 years. It has been incredibly cold! Brrrr. In the town of Christchurch, snow down to sea level which is almost unheard of.

Global Warming in not simply an increase in temperatures. Actually the name: Global Warming, is a bit of a misnomer (not well named). GW is all about there being more energy trapped within the Earth's Climate Systems (Atmosphere and Oceans). More energy can lead to increases in temperatures (so we will see them), but not all will necessarily go into heating the atmosphere and oceans.

 

Some will go into changing the weather patterns. This means that atmospheric currents will change. Warmer air from the poles might be shifted more north or south warming the higher latitudes. Or you might get air form the poles moving towards the equator which will create a decrease in temperatures in certain locations (not globally, but locally).

 

It might be due to global warming (without more data and a lot of research we can't say for sure) that NZ is experiencing a cold spell (it could also be due to local climatic conditions, but whether these are influenced by GW - and by how much - I can't actually say).

[iNow]

That's a good clarification, Edtharan. It's "global climate change," and one of the results is strange and more extreme weather events.

[D H]

It's "global climate change"

It's "global warming", not "global climate change". Calling it "global climate change" is moving the goalposts, not a good thing to do in science. Moreover, "global climate change" is too expansive a term. A new ice age would fall in the category of global climate change.

 

Calling it "global warming" is good science because it is a more focused concept and because that is what it really is: Whether the temperature at the surface of the Earth, when averaged over the year and around the globe, is increasing. The debate is over whether it is realm what the heck is causing it to occur, and what, if anything, should be done about it.

 

Global warming does not say anything about the amount of snowfall in Bum**** New Jersey, so arguing against global warming by claiming that Bum**** just got dumped on is a fallacious argument. Don't change the name just because some people twist the meaning!

[iNow]

It's "global warming", not "global climate change". Calling it "global climate change" is moving the goalposts, not a good thing to do in science. Moreover, "global climate change" is too expansive a term. A new ice age would fall in the category of global climate change.

 

Calling it "global warming" is good science because it is a more focused concept and because that is what it really is...

 

I can appreciate the point you are making, I just disagree. Not that wiki is the "end all, be all" of arguments, but see the below for why:

 

 

http://en.wikipedia.org/wiki/Global_warming

The term "global warming" refers to the warming in recent decades and its projected continuation, and implies a human influence.

[11]

[12]

The United Nations Framework Convention on Climate Change (UNFCCC) uses the term "climate change" for human-caused change, and "climate variability" for other changes.

[13]

. The term "climate change" recognizes that rising temperatures are not the only effect.

[14]

The term "anthropogenic global warming" (AGW) is sometimes used when focusing on human-induced changes.

[D H]

I can appreciate the point you are making, I just disagree.

 

Think of it this way. In persisting in calling it "global warming" you maintain the high ground. Those who refute global warming by claiming that Bumwhatever, New Jersey just had a cold winter are taking the low ground in the debate by reverting to fallacious arguments. In changing the name to "global climate change" you are appearing to move the goal posts and thus yielding the high ground to the critics. Not a good thing to do. Moreover, the term is still incorrect in terms of the alternate meaning of the word "global" because the climate in many places will stay unchanged.

 

Bottom line: Changing the name change doesn't buy anything and loses a lot. If the climate looks like a warm duck and quacks like a warm duck, call it a warm duck.

[iNow]

We're probably closer on this ideologically than it appears. I agree with the sentiment, but have tended to call it "climate change" NOT because I wanted to appease or yield to critics, but instead because warming is not the only thing we are experiencing. It's about more extreme climatic events (even though the overall trend is one of warming).

 

Again, I've been calling it climate change for years now, and it has nothing to do with idiots who don't understand the science.

 

 

Btw... Bum**** is in Missouri.

[SkepticLance]

The last few posts indicate the tendency for those who dislike my more sceptical approach to ignore most of what is said, and focus on, and distort what they can be bothered reading.

 

The primary part of my post (#200) was about a reference in New Scientist to the fact that the computer models missed the mark in Europe. Another example to show how unreliable they are. Instead, I saw my debate opponents ignoring the main point and focusing on a throw-away remark about weather variation. Is this because they are unable to respond to the main point?

 

Ho hum.

[D H]

The last few posts indicate the tendency for those who dislike my more sceptical approach to ignore most of what is said, and focus on, and distort what they can be bothered reading.

The issue about snow in NZ was answered. The New Scientist article will take a bit more work.

 

Just because someone doesn't respond immediately does not mean you won the point. It might mean that you provoked some thought. It might also mean that your post is number 200. Posts that are an integral multiple of 20 are stuck at the bottom of the page. The very next post starts a new page. People tend not to look back.

 

The last few posts were an interesting side track. For example, this has nothing to do with anything you said:

Btw... Bum**** is in Missouri.

Many states appear to have a town with this exact name. I searched for the exact phrase "Bum****, State" and got many hits for all the states I tried. Idaho seems to be the winner with over 1600 hits. Texas is second with 800+.

[iNow]

Many states appear to have a town with this exact name. I searched for the exact phrase "Bum****, State" and got many hits for all the states I tried. Idaho seems to be the winner with over 1600 hits. Texas is second with 800+.

 

Woo hoo! Go Texas!

 

 

 

The primary part of my post (#200) was about a reference in New Scientist to the fact that the computer models missed the mark in Europe. Another example to show how unreliable they are. Instead, I saw my debate opponents ignoring the main point and focusing on a throw-away remark about weather variation. Is this because they are unable to respond to the main point?

 

Ho hum? It could have something to do with the lack of relevance of your post, but okay. Let me try.

 

On the subject of models:

 

 

I would first ask that you name a specific model with problems so we might have a real scientific discussion. If you refuse to name a specific model, then you are lacking in academic and scientific integrity. You can make all of the abstract and high level claims you want, but until you name a specific model with accuracy problems, you are simply hand waving.

 

If you name specific models with issues, then we can discuss the margins of error and where that error resides. We can discuss problems in the models inputs, and to what extent those problems cause issues in the results (the outputs). We can even discuss ways to improve the models.

 

However, we cannot do any of that if you continue with your blanket claims and handwaving that models are not to be trusted.

 

 

 

Now, with a substantiated, pre-emptive, and well supported counter argument:

 

 

U. study substantiates computer models for global warming — Department of Meteorology

 

Computer models used to predict climate change are remarkably accurate when measured against actual weather, according to a new study by University of Utah meteorologists. The findings are expected to boost the role of such models in shaping public policy to confront the menacing specter of global warming, generally believed to be caused by rising concentrations of atmospheric carbon from fossil fuel-burning industries.

 

<...>

 

The University of Utah study results directly relate to this highly publicized report by showing that the models used for the IPCC paper have reached an unprecedented level of realism.

 

Another important aspect of the research is that climate models built in the U.S. are now some of the best models worldwide.

 

 

AMS Online Journals - How Well Do Coupled Models Simulate Today's Climate?

 

Information about climate and how it responds to increased greenhouse gas concentrations depends heavily on insight gained from numerical simulations by coupled climate models. The confidence placed in quantitative estimates of the rate and magnitude of future climate change is therefore strongly related to the quality of these models. In this study, we test the realism of several generations of coupled climate models, including those used for the 1995, 2001, and 2007 reports of the Intergovernmental Panel on Climate Change (IPCC). By validating against observations of present climate, we show that the coupled models have been steadily improving over time and that the best models are converging toward a level of accuracy that is similar to observation-based analyses of the atmosphere.

 

 

 

Also:

 

 

 

The above looks pretty accurate to me.

 

 

 

NOAA has a great site discussing some of the main points in this issue of model accuracy (which includes links to other information).

 

NOAA Overview - Modeling Climate

 

 

 

And here is a summary for a wider audience done in 2007 as part of a "responding to the denialists" toolkit:

 

Climate is too complex for accurate predictions - earth - 25 October 2007 - New Scientist Environment

 

 

 

And below is a whole swath of information specific to models and the challenges to them:

 

RealClimate - Articles on Climate Modelling

 

 

 

I also want to make something clear which may be missed by people out there who are still trying to wrap their heads around this modelling discussion.

 

Models don't predict the future.

 

They are not crystal balls. They are not strangely dressed stinky people at the carnival. They are not palm readers or tarot card sorters or tea leaf smokers.

 

No. That's not what they do.

 

 

They provide an accurate set of outputs given a set of inputs. They don't predict the future, they model it.

 

 

So, the models can tell us:

 

IF humanity does this₁, THEN that₁ will happen.

IF humanity does this₂, THEN that₂ will happen.

IF humanity does this₃, THEN that₃ will happen.

IF humanity does this_...n, THEN that_...n will happen.

 

 

Models cannot predict human behavior. We don't know what political changes will alter society and how we operate, however, models DO provide a series of if/then conditions. When those conditions are met, the models are extremely potent.

 

With modelling, we actually know much more than "just what will happen in the future." We actually know and gain visibility into the rich and expansive landscape of what might happen in the future if the actions of humans change. It's really very powerful.

 

 

So, if we double the amount of CO₂ we add to the atmosphere, then temperature will change this much.

If we triple the the amount of CO₂ we add to the atmosphere, then temperature will change that much.

If we reduce the amount of CO₂ we add to the atmosphere by half, then temperature will change this much...

 

 

 

I just thought that was worth mentioning, and may not have been clear earlier.

 

Models don't predict the future, they model it, and they run various scenarios as inputs to get a clear picture of what will happen if humanity continues with the status quo or makes some sort of changes (for better or worse)... and they do so with awe inspiring accuracy.

 

 

 

Again, I suggest you respond to my original inquiry and offer a specific model with issues of inaccuracy. Perhaps you can start here:

 

Links to climate models and/or climate modeling groups

 

 

You need to find a specific model, show it’s margin of error, and also how predominantly that one model among many is used in the field when doing this work and forming conclusions.

 

 

Until then, you’re still just waving your hands about and expecting us to take you seriously.

 

Handwaving - Wikipedia, the free encyclopedia

 

 

 

Continuing with my pre-emptive strike on your challenges to model accuracy, I advise you review these studies which examine that very issue:

 

Performance metrics for climate models

(http://www.atmos-chem-phys-discuss.net/8/10873/2008/acpd-8-10873-2008-print.pdf)

 

 

http://ams.allenpress.com/perlserv/?request=res-loc&uri=urn%3Aap%3Apdf%3Adoi%3A10.1175%2FBAMS-89-3-303

 

 

http://www.atmos-chem-phys-discuss.net/8/10873/2008/acpd-8-10873-2008.pdf

 

I also advise the reference sections of each.

 

 

 

 

Regarding the subject of model accuracy, the IPCC 4, 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.

 

 

 

In the IPCC report to which I linked, they defined their terms. I have attached below the two key tables from that report which address these "confidence levels."

 

Please note that these are calibrated "quantitatively," not "qualitatively," so issues of subjectivity and opinion never come into the mix:

 

 

 

 

 

So yeah, ho hum.

Edited July 8, 2008 by iNow
speeling

[SkepticLance]

To iNow

 

Congratulations. That was a very good rebuttal. Wrong, but still good.

 

Sadly I do not have the time to go through all your references, just as it is clear you have not made the time to read mine. It is also true that accuracy of models as assessed by the modellers is somewhat suspect. And this is essentially what you are posting.

 

I am showing specific details of model inaccuracies, and these are genuine and correct, regardless of what the IPCC people say about IPCC models.

[Edtharan]

It's "global warming", not "global climate change". Calling it "global climate change" is moving the goalposts, not a good thing to do in science.

Actually it is Global Climate Change, not Global Warming. It was originally called Global Warming decades ago.

 

The reason they called it global warming back then is that they didn't fully understand the processes involved. They knew that certain gasses (CO2, Methane, the greenhouse gasses) trapped heat in the Earth's atmosphere.

 

At the first level, they though that the atmosphere would just heat up (like in a greenhouse), however, what they now realise is that the Heat, does not have to stay as heat, it can go elsewhere. Not only that, they realised that it does not only have to stay in the atmosphere, they realised it can go into the ocean (and not only as heat).

 

But. The name Global Warming stuck because the Mass Media picked it out, and it sounded like a good catch phrase .

 

If it is scientists moving goal posts, then it is moving goal posts not put there by the scientists, but instead by the mass media (and you know how reliable the mass media is for scientific rigour ).

 

A new ice age would fall in the category of global climate change.

Surprisingly this is a possibility from increasing greenhouse gasses. Or at least in certain localities.

 

If the North Atlantic Current is slowed down or stopped by the addition of a lot of fresh water (less dense than sea water) from the melting of the Arctic and Greenland, then this will stop the influx of warm tropical water form the equator (due to the NAC) and plunge Europe into an ice age. If enough of Europe freezes and for long enough, then the reflection of sunlight from the Earth might be enough to cool the Earth, despite the extra greenhouse gasses and drive the temperature further down (and more of the Earth freezes increasing the reflection more in a positive feedback loop)

 

So yes, an Ice Age could be the result of "Warming" the Earth.

 

The climate systems (atmosphere and oceans) are complex non-linear systems. Small changes in a non-linear system can have dramatic and unexpected results. Just because it was called "Global Warming" decades ago by a handful of people and then that catch phrase was then picked up by the media and then they ran with it, does not mean that the "goal posts" that science actually has placed is the same as that thrust upon us by the media.

[JohnB]

Surely, both of our references cannot be correct, and one of us must win this argument. Either the intensity of storms has increased, or, it has not.

Perhaps we both can.

 

I just came across this. Briggs applies statistical analysis to the Storm/Hurricane figures. He finds;

The rate at which storms become hurricanes appears to have decreased, and the rate at which category 4+ storms evolved from hurricanes appears to have increased. Both of these results are also dependent on the starting year.

Not sure how this particular piece fits in the puzzle, but it would appear that frequency/intensity trends are reliant of the starting year chosen for the data.

 

So we can both be right depending on the data start years chosen in the papers we've read. (I can't help but get a gut feeling that this is also a very wrong state of affairs, it smells of someone, somewhere massaging the data.)

[iNow]

To iNow

 

Congratulations. That was a very good rebuttal. Wrong, but still good.

 

Sadly I do not have the time to go through all your references.

Ah... yes. A thorough, internally consistent, and well substantiated response from SkepticLance without any rhetoric or handwaving, as per usual.

 

 

I simply must concede my point with a powerful point like the one you've just made. Touche. You really left no stone unturned with that one.

 

 

 

It is also true that accuracy of models as assessed by the modellers is somewhat suspect. And this is essentially what you are posting.

Actually, no it's not. You should probably try reading the references before you comment on what they are and what they are not.

 

 

 

I am showing specific details of model inaccuracies,

There were no specific models referenced in your post. I just looked back to confirm this before I responded.

 

Simply saying that you were specific does not mean that you actually were.

 

 

and these are genuine and correct, regardless of what the IPCC people say about IPCC models.

Also, once you've actually bothered to read my post and the sources contained within, you will find that nearly every single reference I shared had nothing to do with the IPCC, so your suggestion of bias and ego protection is both unfounded and without merit. You (if you bother reading the post and references within) will see that the studies which I shared on model accuracy were conducted by other independent groups, as were the references in THEIR studies.

Edited July 8, 2008 by iNow
multiple post merged

[SkepticLance]

iNow

 

I do not know if you did the research yourself, or used someone else's. If you did it yourself, it must have taken you hours. That is why I said congratulations. It was an acknowledgement of the time and effort involved.

 

I cannot afford the time myself to do full justice to all your references, since I have work to do. Thus I must confine myself to general comments.

 

First; Modellers have been working on global climate models for more than 20 years. There has been a long series of such models, each a bit better than the earlier one. Each time, they tweak the models to make them closer to historical trends. They have reached the stage where they are approaching a close similarity with those trends. If that were not so, we would have to throw our hands up in horror and say what utter morons modellers must be.

 

However, there is a very big difference between managing to tweak a model till it comes close to 20:20 hindsight, and actually modelling (or predicting) the future. The references I have been posting have been discussing that. The latest one (New Scientist) showed that models missed out on predicting, simulating, modelling what is happening in Europe.

 

I have previously showed the same for predictions of Arctic warming and ice melting, and for the lack of ability to use cloud formation correctly.

 

Second : Without taking the time to go through each and every one of your references, it seems to me that many consist of modellers and global warming climatologists telling modellers and global warming climatologists what a good job they have been doing.

[iNow]

Thank you for reminding me whey I shouldn't take you seriously, and why I shall just ignore you. I am appreciative of the reminder, Lance. I really am.

[SkepticLance]

In exactly the same way you ignore the references I post from reputable sources. Still, it's nice to see consistency.

[swansont]

The last few posts indicate the tendency for those who dislike my more sceptical approach to ignore most of what is said, and focus on, and distort what they can be bothered reading.

 

The primary part of my post (#200) was about a reference in New Scientist to the fact that the computer models missed the mark in Europe. Another example to show how unreliable they are. Instead, I saw my debate opponents ignoring the main point and focusing on a throw-away remark about weather variation. Is this because they are unable to respond to the main point?

 

Ho hum.

 

 

I think one of the issues here is that your approach is often not skeptical. You take pop-sci summaries at at full faith, and even though New Scientist isn't terrible, it's still pop-sci summaries. They don't always get it right, and when you then throw your own interpretations onto that, you can end up with a game of "whisper" where your conclusions don't always match up well with the science.

 

 

Post #200:

Another example of global warming predictions missing the mark.

 

http://environment.newscientist.com/...e-change_rss20

 

"Since 1980' date=' average air temperatures in Europe have risen 1 °C: much more than expected from greenhouse-gas warming alone"[/i']

 

I don't see how you draw that conclusion from the information presented. The warming is more than from GHG emissions, but that's not the only thing that affects temperature

 

"Aerosol concentrations dropped by up to 60 per cent over the 29-year period, while solar radiation rose by around 1 watt per square metre "

 

Aerosols are a separate forcing. And if you read the paper, like I did, you'll see that the 1 W/m^2 increase in solar is not due to the sun's output; that's the increase of what's getting through the atmosphere. Just FYI.

 

That authors do express surprise that the cloudiness didn't change much, but also state that they couldn't rule out other factors affecting this, i.e. cloudiness does not depend solely on aerosol concentrations.

 

Aerosols are an input to climate models, not a prediction of them. Since they don't say if this information went into the climate models — they aren't discussed, AFAICT, I don't see how you can draw any conclusion whatsoever about the validity of those models from this paper.

[iNow]

I just came across this. Briggs applies statistical analysis to the Storm/Hurricane figures. He finds

 

The rate at which storms become hurricanes appears to have decreased, and the rate at which category 4+ storms evolved from hurricanes appears to have increased. Both of these results are also dependent on the starting year.

 

<...>

 

So we can both be right depending on the data start years chosen in the papers we've read.

 

John, I've got to give you a lot of credit for finding this article. While I might be inclined to suggest that it supports my position more than yours, I'll follow your lead and agree that we are, to some degree, both correct on this specific topic.

 

 

<but, of course, I'm MORE correct >

[SkepticLance]

Swansont said

 

"I don't see how you draw that conclusion from the information presented. The warming is more than from GHG emissions, but that's not the only thing that affects temperature"

 

Swansont

 

You have been involved in this debate for a long time. You should know by now that my explanation for why GCMs do not always get it right is the unknowns that crop up. GCM's underpredicted Arctic sea ice melt, and one explanation is an oceanic current that was not previously seen. They predicted Antarctic warming, whereas it cooled (over most of the continent) due to wind movements (one explanation) that were not expected.

 

In this example, an underprediction of Europe warming is now explained by aerosol reduction. In every case, something unknown changes the outcome, making the GCM prediction invalid.

 

I continue to maintain that we cannot trust model predictions (or modelling of future outcomes, as iNow would insist) for the same reason. There will likely be unknown factors altering outcomes in unpredictable directions for some time to come. We have no way to know what all oceanic currents are doing, or how the sun will fluctuate, or what volcanoes will erupt. Every unknown alters outcomes.

 

For this reason, models will continue to be unreliable in relation to what happens in the future.

[Edtharan]

However, there is a very big difference between managing to tweak a model till it comes close to 20:20 hindsight, and actually modelling (or predicting) the future. The references I have been posting have been discussing that. The latest one (New Scientist) showed that models missed out on predicting, simulating, modelling what is happening in Europe.

When they make hindsight predictions, what they do is start with the known climate details at a particular date. They don't use the data that lies ahead of that date (ie closer to today). They then use their model to make predictions based on that limited data set and then check how close they got with the data from the model.

 

Essentially what they are doing is seeing what their model would have predicted if it were available at some time in the past.

 

So, if a climate modeller from 100 years in the future time travelled back to our time and use the data we have now in their model on their computers, would you consider their model valid if it then predicted the climate over the next 100 years? Because, except for the time machine, this is what we are doing now with our models.

 

If that future modellers modelled data is considered valid, then so must our models data from hindsight modelling.

 

First; Modellers have been working on global climate models for more than 20 years. There has been a long series of such models, each a bit better than the earlier one. Each time, they tweak the models to make them closer to historical trends. They have reached the stage where they are approaching a close similarity with those trends. If that were not so, we would have to throw our hands up in horror and say what utter morons modellers must be.

In other words the models of today are better then they were years ago. So, what is your problem with them? If they are better at modelling the climate, then why not use them.

 

They predicted Antarctic warming, whereas it cooled (over most of the continent) due to wind movements (one explanation) that were not expected.

Ther eis a reason the are called global climate models and not location specific climate models.

[swansont]

Swansont said

 

"I don't see how you draw that conclusion from the information presented. The warming is more than from GHG emissions, but that's not the only thing that affects temperature"

 

Swansont

 

You have been involved in this debate for a long time. You should know by now that my explanation for why GCMs do not always get it right is the unknowns that crop up. GCM's underpredicted Arctic sea ice melt, and one explanation is an oceanic current that was not previously seen. They predicted Antarctic warming, whereas it cooled (over most of the continent) due to wind movements (one explanation) that were not expected.

 

In this example, an underprediction of Europe warming is now explained by aerosol reduction. In every case, something unknown changes the outcome, making the GCM prediction invalid.

 

I continue to maintain that we cannot trust model predictions (or modelling of future outcomes, as iNow would insist) for the same reason. There will likely be unknown factors altering outcomes in unpredictable directions for some time to come. We have no way to know what all oceanic currents are doing, or how the sun will fluctuate, or what volcanoes will erupt. Every unknown alters outcomes.

 

For this reason, models will continue to be unreliable in relation to what happens in the future.

 

 

Since there is little use in pursuing this, I will just note that you've avoided the issue of the reliability of your sources on which you base your "skepticism." This post also points to not acknowledging the difference between global and local in the model outcomes.

 

As far as models go, there a quote from George Box, "All models are wrong, but some are useful." You're focusing on the fact the models are wrong, i.e. imperfect. To an arbitrary level of precision and accuracy, as the quote says, they are and always will be. The question is, are they useful? That's the issue, I think, most others are discussing here.

 

You also continue, as shown here, to not distinguish between model and input to the model. Yes, a major volcano may erupt, or the solar output could change. The models under discussion don't predict those events — that's not their function, and to judge the utility of the models on that basis is a strawman. You judge them on how well they give a result if you put the data for those events into them. A model that says that temperature will rise 3 ºC if CO2 doubles isn't predicting a doubling of CO2. Just like any computer program, GIGO. If a 60% reduction in aerosols wasn't entered, even a perfectly accurate model would give incorrect results, and there is nothing here that indicates whether or not this was the case. It's outside the scope of the inquiry.

 

It's also a strawman to just claim "unknowns" and dismiss models. The models here are still constrained to follow e.g. conservation of energy, and such constraints put a limit on how large unknown effects can be. It's how we know how much dark matter and dark energy are out there, even though they have never been detected directly. It's how the neutrino was discovered. A blanket dismissal, lacking specifics, is insufficient.

[JohnB]

<but, of course, I'm MORE correct >

Such modesty.

[SkepticLance]

Edtharan said

 

"Essentially what they are doing is seeing what their model would have predicted if it were available at some time in the past."

 

That's true, but still ignores many unknown factors. That's why they are called unknowns.

 

When the first models were set up, their accuracy was much less, since many factors were not well understood - there were more unknowns. Since then, models have improved, but recent reports still show serious errors due to other unknowns that keep appearing. The Arctic ice melt was a major one.

 

Even where modellers think they understand, often there are uncertainties. For example : there are several theories as to why the main bulk of Antarctica does not warm as they predicted. They do not understand the mechanism. That does not stop them applying a 'fudge' factor.

 

But if you do not fully understand mechanisms, how can you be sure that your model is accurate? You cannot, and predictions continue to be off, as shown by the various references I have put up.

[iNow]

Since then, models have improved, but recent reports still show serious errors due to other unknowns that keep appearing.

 

<...>

 

But if you do not fully understand mechanisms, how can you be sure that your model is accurate? You cannot, and predictions continue to be off, as shown by the various references I have put up.

 

For others who are not a poster by the name of skepticlance:

 

 

Performance metrics for climate models

(http://www.atmos-chem-phys-discuss.net/8/10873/2008/acpd-8-10873-2008-print.pdf)

 

 

http://ams.allenpress.com/perlserv/?request=res-loc&uri=urn%3Aap%3Apdf%3Adoi%3A10.1175%2FBAMS-89-3-303

 

 

http://www.atmos-chem-phys-discuss.net/8/10873/2008/acpd-8-10873-2008.pdf

 

I also advise the reference sections of each.

[SkepticLance]

To swansont

 

We seem to have crossed paths. I wrote my last post without seeing yours. We must have been putting them in together.

 

First : reliability of my references. If I post a reference from New Scientist, it is reliable in terms of fact. Interpretation, of course, is always debatable. My references are, like anyone else's, reliable if taken on those terms. I also have to say that I am always suspicious of debaters who fail to address points, but attack people or references instead. Sometimes that is a sign of a weak argument. If I post something from a biased political source, of course you can challenge it. However, my references have not been from that source.

 

Second : ," "All models are wrong, but some are useful." "

I could not agree more. However, accuracy also varies. Some astronomical models, for example, which are based on equations known to be accurate to umpteen decimal places, and have as inputs, facts that are likewise enormously accurate, may produce outcomes that are incredibly accurate. Global Climate Models do not fit this category.

 

Your comments about unknowns are right on the button. But it goes beyond volcanoes and solar output. As I have shown recently, it extends to oceanic currents that behave in unexpected ways, and to wind patterns that have unexpected effects (Antarctica), and to uncertainties in the formation of clouds. There are sure to be other unknowns that currently live up to their name, and which will show themselves in due course. The time may come when all significant unknowns are accounted for, and models perform close to flawlessly, but that is not today. I suspect that if you are honest with yourself, you will admit that you know this already.