Climate Policy

[Jester]

Now we have the "magic 8 ball" -- the computer. By developing models that predict what they want to predict, 'scientists' can sanctify their prejudices by running them through the sacrament of 'computer model'. The outcomes are theories that are taken to be infallible because they are ex cathedra -- emitted from the college of the infallible machine and sanctified by the papacy of pseudo science. The followers of that religion can then preach their gospel of imminent doom. By serving their beliefs as facts, they lead those that are ignorant to become misinformed. Instead of taking reasonable measures at a moderate pace in acknowledgment of their ignorance, the followers of the doom preachers propose extreme measures at a panicked pace from the arrogance of their misinformation.

It's really that bad?

-Jester

[--Pete]

Hi,

It's really that bad?

It really is.

In the wake of WW II and the mega research programs instituted then (the Manhattan project being the most renown, but others to develop jet engines, better ciphers, etc. also existed) it became the norm to expect government funding for research. Prior to that, research was mostly the pastime of people who were, for one reason or another, obsessed with knowledge. After that, it became, for many, a big business.

The people in charge of making those grants are not experts in the fields that they are funding -- they aren't completely ignorant, but they aren't active researchers, either. There is much more demand for research funding than there is funding available. To determine who gets the funding, the agencies need to evaluate the importance of the requests. So, if one researcher says "I'd like to be funded to study climatic change because it is cool" and another says "I'd like to be funded to study climatic change because it is taking us to the end of civilization as we know it", guess who gets funded?

Now, if two groups got funded because they each claimed that the end was imminent, and they each developed a model, one of which supported the doomsday scenario and the other which didn't, guess who gets an extension (hint, it's not the group who's report starts with "We were wrong.")

Then there is the fact that scientific computer models are seldom, if ever, written by people who are trained in computer fields. They are written by scientists who have picked up programming as an avocation. The papers generated by these models may be peer reviewed, but the models themselves very seldom are. At most, they are shared among the researchers in a field and some small degree of feedback is given. Usually, those obtaining copies of the code just want it to duplicate work that has been done and look at the code just enough to get it running on their system (often a non-trivial task if the code, like so many scientific codes, is written in a dialect of FORTRAN specific to one machine or class of machines). So misconceptions, poor assumptions, and downright errors are propagated. There is a standard analysis library that has known errors in it, but they are uncorrected so that present and future work will be comparable to that done in the past.

Finally, a model is often judged to be 'good' or 'bad' on the basis of what it predicts. But since there often isn't anything objective to compare it to, then it boils down to the subjective. The modeler often has a general idea of what he expects. If the model more or less gives him that, then it is good, otherwise it isn't. It appears that none of the climate models presently in existence can fully reproduce the *known* history of the planet. Why then believe them for the future?

I don't claim, nor think, that there is a big conspiracy. From my lifetime experience of modeling physical processes, I think that it is just a combination of the pressures of obtaining funding and the natural human inclination to become emotionally attached to our pet theories that leads to the situation we have. The field of climatology is exposed to political scrutiny that could lead to regulations, contracts, etc. And so, a conspiracy explanation is attractive. But look at the situation in cosmology, where there is no external pressures, and yet over the past fifty years various theories have been in vogue, and those researchers not subscribing to the theory du jour have had great difficulty in getting positions, funding, or even published.

Science is a nearly perfect system for obtaining knowledge, but it is conducted by imperfect people. In the long run, it works out. In the short, it is often dominated by personalities, prejudices, and expectations.

--Pete

[Kevin]

Science is a nearly perfect system for obtaining knowledge, but it is conducted by imperfect people. In the long run, it works out. In the short, it is often dominated by personalities, prejudices, and expectations.

Even Einstein would not accept the conclusions that his own equations drew, that the Universe was in fact expanding and not in a steady state. When it was pointed out he said something along the lines of "There is nothing wrong with your mathematics, but your physics is an abomination." So yep science, like pretty much everything else, is still dominated by people and the flaws that people have and you can pull examples from everywhere, to point that out.

I too have also had to "fight" the bad computer model. Trying to convince the person that his code was not doing what he thought it was, because fixing the coding errors meant that the model didn't produce the results he wanted, was not fun.

I do agree that it really is as bad as you state, and in many fields. Civic centers have collapsed because people believe the computer models that were based on incorrect assumptions. I've seen a kiln exploded thanks to bad computer models. Sure not everything is bad, some of the stuff that is done, in the aerospace industry especially, when it comes to computer modeling is phenomenally helpful. But I don't trust most of the weather or climate models either. GIGO Garbage In = Garbage Out. If you have bad assumptions you are just feeding in garbage. For most of the theoretical sciences the lack of review of the modeling software is a major major issue and impediment to progress and the grant process is horrendous (I work at a University I get to see a lot of it 2nd or 3rd hand).

But again much of it boils down to people, as always. :)

[--Pete]

Hi,

Yeah. Those who have never been involved know not how bad it has become. Sometimes I think our scientific establishment has followed our judicial system in abandoning the truth for rules and games.

One minor nit:

GIGO Garbage In = Garbage Out.

That used to be the case, now it is 'Garbage In; Gospel Out' -- The Devil's DP Dictionary Stan Kelly-Bootle. :whistling:

--Pete

[Jester]

Finally, a model is often judged to be 'good' or 'bad' on the basis of what it predicts. But since there often isn't anything objective to compare it to, then it boils down to the subjective. The modeler often has a general idea of what he expects. If the model more or less gives him that, then it is good, otherwise it isn't. It appears that none of the climate models presently in existence can fully reproduce the *known* history of the planet. Why then believe them for the future?

Does hindcasting perform so poorly? My understanding, again self-admittedly inexpert, is that current models actually do quite well at predicting past temperature. Asking a single model to predict the entire global climate past is probably not possible or realistic, but doing things like predicting 20th century temperatures seems to yield solid results.

Is this based on your understanding from the late 1980s, plus having not heard of developments since? Or have you actually looked at the hindcasting skill of more current models? I'm afraid I'd be totally lost doing so, but my impression was obviously more positive than yours.

-Jester

[--Pete]

Hi,

Does hindcasting perform so poorly? My understanding, again self-admittedly inexpert, is that current models actually do quite well at predicting past temperature. Asking a single model to predict the entire global climate past is probably not possible or realistic, but doing things like predicting 20th century temperatures seems to yield solid results.

Is this based on your understanding from the late 1980s, plus having not heard of developments since? Or have you actually looked at the hindcasting skill of more current models? I'm afraid I'd be totally lost doing so, but my impression was obviously more positive than yours.

My ex-spurt-eas is from the late '80s and early '90s when, because of the collapse of the Soviet Union, my weapons group was looking for other fields to conquer. Since our forte was non-linear dynamic models, there was a lot of overlap, and we were very familiar with the general tool set. At that time, the climatic models were very poor. As an example, there were instances of non-linear air mass flow phenomena modeled using Fourier analysis. For the non-mathematicians out there, linearity is one of the prerequisites for Fourier analysis to be applicable.

In the late '90s, I revisited the field in conjunction with a satellite program we were developing. There had been some improvement of the models in the seven or so intervening years (and some of the code had actually been converted to C or C++ :rolleyes:) but the state of the art was not much different -- ad hoc models with enough adjustable parameters to predict an elephant if the modeler desired. Since then, my interest has been strictly that of an informed outsider. To paraphrase Will Rogers, all I knew is what I read in Science News. Furthermore, the past 4 years I've even let that slip quite a bit -- part of that time I did not have the ability to understand topics at that level, and much of the rest of that time I was too weak to care. It has only been in the past year, and especially the past four months, that I've had the mental and physical capacity to again take interest in scientific matters.

So, having thus established my (lack of) credentials, take what follows as you will.

I have not seen the most recent models. Nor have I seen any announcements of a major breakthrough in climatic models. Since there does exist an ongoing debate about the validity of the models used, I would expect any substantial improvements to be widely touted in support of the modeler's claims. That leads me to believe that the models are probably much the same as they were ten years ago -- which is to say, not that much different than they were thirty years ago when they were first able to 'predict' global warming.

Most of the existing models of ten years ago could do a sufficient job of postdicting any given historical period with an appropriate choice of parameters. The problem was that it would take a different set of parameters to postdict a different period. Thus, in essence, the models were little more than a curve fitting program. Each historic era was fit with one set of parameters, and then the next with another, and so on much like a cubic spline is used to fit experimental data. And just like a cubic spline does not 'explain' the data, neither did these models.

For a model to be valid, it does indeed need "to predict the entire global climate past". If it cannot, if it can only predict some eras but not others, then how are we to know that the coming era is one which it can predict? How can we know when we can use it and when we can't?

As long as there is debate over the models and parameters needed to postdict the existing data, so long will the models be useless to predict the future. From what I've seen published, that debate still runs hot. I'd love to go to a climatologist convention and see how many "my honorable colleague is a damned fool" arguments break out. Hell, I'd even buy the pizza and beer.:)

--Pete

[eppie]

Hi,
It really is.

No it isn't

In the wake of WW II and the mega research programs instituted then (the Manhattan project being the most renown, but others to develop jet engines, better ciphers, etc. also existed) it became the norm to expect government funding for research. Prior to that, research was mostly the pastime of people who were, for one reason or another, obsessed with knowledge. After that, it became, for many, a big business.

First, you forget to mention the difference between the US/USSR and the rest of the world. And because climate research doesn't take place solely in the US you should note this difference. Government funding has always been a lot lower in europe for example. This has indeed mainly to do with the enormous available funds for defence research.
Research is not big business. Most professors could earn at least double if they would choose to go and work for a company. Do you really think all the most intelligent people work for banks? There is a large group of very smart people that stays at university.

The people in charge of making those grants are not experts in the fields that they are funding -- they aren't completely ignorant, but they aren't active researchers, either.

Many funding schemes use peers to choose between different applications.

There is much more demand for research funding than there is funding available. To determine who gets the funding, the agencies need to evaluate the importance of the requests. So, if one researcher says "I'd like to be funded to study climatic change because it is cool" and another says "I'd like to be funded to study climatic change because it is taking us to the end of civilization as we know it", guess who gets funded?

In the west there is much more funding than there is demand (if that would be possible:) ), we have lots of money, but not enough researchers. Our kids see quickly that they can make much more money when the do some simple job at a bank, become a lawyer or compete in a reality show that the amount of autochtonous teenagers that want to become scientists is very low. That's is why in the US and northern europe more than half of the PhD students are from other countries.



Scientific results are peer reviewed before being published, sometimes this reviewing does not happen correctly (I know from experience), strange things happen. But comparing climate research with people not believing Galileo when he said the earth was round, or Einstein when he was posing his theories is soemthing different. The scientific is (luckily) very large at the moment, and there is enough possibility to (when you have scientific proof) comment on results that you say are wrong. Climate scpetics have more than enough possibility to be heard.

Your way of thinking on this subject is also a kind of role reversal. Industry has always been an important source of funding for research, even government funding was often used for industrially interesting subjects. Especially after the first concerns about climate change were voiced, the 'sceptics' had much more funding.

Then there is the fact that scientific computer models are seldom, if ever, written by people who are trained in computer fields. They are written by scientists who have picked up programming as an avocation. The papers generated by these models may be peer reviewed, but the models themselves very seldom are. At most, they are shared among the researchers in a field and some small degree of feedback is given. Usually, those obtaining copies of the code just want it to duplicate work that has been done and look at the code just enough to get it running on their system (often a non-trivial task if the code, like so many scientific codes, is written in a dialect of FORTRAN specific to one machine or class of machines). So misconceptions, poor assumptions, and downright errors are propagated. There is a standard analysis library that has known errors in it, but they are uncorrected so that present and future work will be comparable to that done in the past.


Finally, a model is often judged to be 'good' or 'bad' on the basis of what it predicts. But since there often isn't anything objective to compare it to, then it boils down to the subjective. The modeler often has a general idea of what he expects. If the model more or less gives him that, then it is good, otherwise it isn't. It appears that none of the climate models presently in existence can fully reproduce the *known* history of the planet. Why then believe them for the future?

I have too little experience with modelling to comment on this.

I don't claim, nor think, that there is a big conspiracy. From my lifetime experience of modeling physical processes, I think that it is just a combination of the pressures of obtaining funding and the natural human inclination to become emotionally attached to our pet theories that leads to the situation we have. The field of climatology is exposed to political scrutiny that could lead to regulations, contracts, etc. And so, a conspiracy explanation is attractive. But look at the situation in cosmology, where there is no external pressures, and yet over the past fifty years various theories have been in vogue, and those researchers not subscribing to the theory du jour have had great difficulty in getting positions, funding, or even published.

Science is a nearly perfect system for obtaining knowledge, but it is conducted by imperfect people. In the long run, it works out. In the short, it is often dominated by personalities, prejudices, and expectations.

--Pete

There is a small truth in here. But mainly (and I am not talking about you personally) it is a case of 'zoals de waard is vertrouwt hij zijn gasten' (the landlord trusts his guess, like the way he is).

Many people with no university experience think that scientist are a bunch of corrupt and lying people working for some government interest. Although, as I said, it is true that the peer review system is not perfect the scientific community is probably the most transparent part of society there is.

[weakwarrior]

For the non-mathematicians out there, linearity is one of the prerequisites for Fourier analysis to be applicable.

I'm not sure what you mean? First of all if a function is linear why would you model it - it's pretty easy to predict. Second of all, unless the linear function is horizontal (even easier to predict) you actually can't model it with a Fourier analysis since you need bounded variation (sines and cosines are periodic so they can't do this).

[weakwarrior]

For a model to be valid, it does indeed need "to predict the entire global climate past". If it cannot, if it can only predict some eras but not others, then how are we to know that the coming era is one which it can predict? How can we know when we can use it and when we can't?

Ignorant question: since all we want to know is how an increase in CO2 (without any other major global changes - like earthquakes or what not) affects global temperatures why wouldn't modelling what happened since the industrial revolution be sufficient? Has that ever happened before?

Edit: Stupid post. If the baseline is moving on the order of the current deviation it needs to be modelled very carefully.

[--Pete]

Hi,

I'm not sure what you mean? First of all if a function is linear . . .

Linear in math means a lot more than a straight line relationship between two quantities related by one variable.

Sorry, I've started to write a more detailed description a few times, but each time it became clear that I would have to go back and cover more material. To go from the concept of a straight line to that of an infinite linear vector space of functions (which is what the Fourier analysis is one example of) is to cover about seven years of math (seventh grade to junior year in a math/science/engineering curriculum). That is a lot more than I can do in a forum post. Perhaps by following the link above, and reading from there, you'll be able to get a better grasp on the subject. Again, sorry that I can be of so little help.

--Pete

[kandrathe]

Ignorant question: since all we want to know is how an increase in CO2 (without any other major global changes - like earthquakes or what not) affects global temperatures why wouldn't modeling what happened since the industrial revolution be sufficient? Has that ever happened before?

There are no stupid questions. I read recently, "Reality laughs at computer modeling when the underlying science is just hearsay."

My interpretation of the climate system on earth is that it is more like a marble in bowl, than it is like a marble on an upside down bowl. The models have added many positive feedback mechanisms, such as, As temperatures rise, more water evaporates into the atmosphere - the increased water vapor absorbs more heat, amplifying the warming. As ice melts, water and land are exposed which absorb heat more effectively than ice, again amplifying warming. Melting permafrost releases methane and carbon into the atmosphere. Warming oceans become less effective as carbon sinks. But, then again, if it were so fragile what happened all those other times in our history when the levels of CO2, and methane were much higher than they are now?

This is why even with catastrophic atmospheric change (snow ball earth, asteroid impacts, super volcanoes) it still eventually settles back to normal. The edges of the bowl are the feedback mechanisms which increase in response to a change in the normal. For example, I mentioned earlier that plants grow differently in a more CO2 rich environment using less H20, and absorbing more CO2 which they use to build thicker foliage. Eventually, just that change might sequester the man made additions. I think we understand pretty well (maybe) what moves the marble (being climate change) around the bowl, but I don't fully think we understand the nature of the bowl and what forces are out there that work to offset climate change.

In fact, I'd be much more worried about a looming ice age than I am about global warming. It will be very, very inconvenient to have to abandon, or put dikes around our low laying cities, but that is nothing compared to the ravages of a much colder earth. At least we can stay warm and will have plenty to eat. All animals and plants on Earth do much better in a warmer wetter climate than a frozen climate, although there will be some areas that will suffer as well. Although, in my recent exploration of Arizona energy, I was shocked to see how vibrant it's agriculture output was, and most of that through irrigation. If we can do that to a desert, then I have to believe that with abundant energy, nothing is impossible to humanity.

Humans should do better to prevent deforestation and promote a healthy vibrant environment, but I still feel warmer is better than frozen.

[--Pete]

Hi,

Ignorant question: since all we want to know is how an increase in CO2 (without any other major global changes - like earthquakes or what not) affects global temperatures why wouldn't modeling what happened since the industrial revolution be sufficient? Has that ever happened before?

Leaving out earthquakes, volcanic eruptions, meteor strikes, global war, etc., is fine. These things are not directly related although they can have their effects. But you can't leave out things like the melting of the polar icecaps, the loss of snow cover, the melting of the tundra, etc., because these are related effects. As a simple example (partially repeated from a previous post): CO2 warms the earth; the warmth causes the polar ice caps to melt; the melt is mostly fresh water which decreases the density of the North Atlantic; at this point we have a bifurcation in the model.

If the decrease in the density of the waters of the North Atlantic is sufficiently slow, then the Atlantic currents will not be greatly effected, and (ignoring other factors) heating will continue, possibly to the desert planet stage. Whether this scenario occurs depends on many factors and relationships, such as how fast the ice will melt, how fast the layers of different density and temperature will mix, etc. etc.

If the decrease in the density of the North Atlantic is sufficiently fast, then the Atlantic currents *may* stop (again, a complex problem in itself). If these currents stop, the higher latitudes will become cold. This will reduce the absolute water content of the air at those latitudes. If that reduction is sufficient to offset the increased CO2, then a positive feedback cooling cycle can start which will lead to a snow ball planet.

The point is that a cause (say CO2) has many different effects. Some of these effects form feedback loops, both positive and negative. So the effects then become causes in their own right.

Now, one might say, "If increased CO2 levels lead to either a desert planet or a snowball, why does it matter which? Either way we need to control it." But the point that's missed there is that it can lead to either extreme, or any point in between. If, as some climatologists think, earth's natural progression should be taking us into the next ice age, then artificial global warming might be a good thing. That may be, probably is, highly unlikely. But on the basis of what we've got and what we know, it cannot be ignored.

--Pete

[kandrathe]

If the temperature rise came first, and caused CO2 to start rising, it did so with remarkably close proximity in time to the start of the industrial revolution.

Here is a better explanation from Skeptical Science...

<blockquote>In fact, a study came out just a few weeks ago (Stott 2007) that confirms CO2 increases around 1000 years after temperature rise. This raises an important question - does temperature rise cause CO2 rise or the other way around? The answer is both.



The dominant signal in the temperature record (the white line in the above figure) is a 100,000 year cycle where long ice ages are broken by short warm periods called interglacials. This cycle coincides with a change in Earth's orbit as it evolves from a more circular orbit to a more elliptical orbit. When springtime insolation (incoming sunlight) increases in the southern hemisphere, this causes temperature to rise in the south. The warming is amplified as retreating Antarctic ice means less sunlight is reflected back into space.

As the southern oceans warm, they give up more CO2 to the atmosphere as the solubility of CO2 in water falls with rising temperature. The CO2 mixes through the atmosphere, amplifying and spreading the warming to the tropics and northern hemisphere. This is why warming in the southern hemisphere precedes warming in the northern hemisphere (Caillon 2003). This is confirmed by marine cores that show tropical temperatures lag southern warming by ~1000 years (Stott 2007). CO2 warming also explains how the relatively weak forcing from orbital cycles can bring the planet out of an ice age. </blockquote>So all this is not to say that anthropogenic CO2 is not an issue, but that there is a natural fluctuation of global temperature which results in increases of CO2 to which we've added more. The results of which, are as of yet uncertain, but may lead to increased warming (above natural cycle) by some measure. Geologically, the Earth is warming naturally as we are emerging from an ice age, but the human contribution of CO2 to the atmosphere is the risky science experiment to which we are all captive lab rats.

[kandrathe]

Sorry, I've started to write a more detailed description a few times, but each time it became clear that I would have to go back and cover more material.

Let me try.

Linear equations are what most people understand and perform from simple math to multivariate statistics and complex calculus. Most people know linear equations as polynomials such as Ax^3 + Bx^2 + Cx + D = 0, or x^3 + y^3 + z^3 = 0. There are very many analytical tools, such as Fourier transforms, which can be applied to linear equations. And, some of them can also be applied piece meal to partial derivatives of non-linear equations.

What is little studied, and only by aspiring math graduate students are the little yellow books (eg. support vector regression analysis) that delve into the wild unknowns of non-linear equations. A nonlinear system is any problem where the variables to be solved for, cannot be written as a linear combination of independent components. They are equations such as the Korteweg–de Vries equation -- , or as you can imagine in climate science the effect of ionizing radiation as it moves through a cloud of water vapor.

There is another problem with climate models. Only a comparatively very few individuals ever learn enough about non-linear equations to be able to understand them, know they are accurate, let alone model them in a computer. Even in todays universities, most undergraduates, and most graduate students will never learn any non-linear equations, let alone the mathematics needed to apply them to real world phenomena. Even then, since the equations are "chaotic" it is hard to insure they fit the behavior you are trying to model. I have much more confidence in actual experimentation, where observed phenomena either fit or do not fit the hypothetical prediction. Models may be useful in suggesting the parameters of experiments, although it is hard to set up a climate for experimentation.

[--Pete]

Hi,

Let me try.

Nice try:)

I have much more confidence in actual experimentation, . . .

So do I. But some things are too big (hurricanes), too small (quarks), too fast (shock fronts), or too slow (universes) to bring into the lab. Then you make a goulash of theory, experiment, and computer models and do your best. But the more you know and the more honest you are, the less you trust those results.

--Pete

[--Pete]

Hi,

There are no stupid questions.

Actually, that should read, "There's no such thing as a dumb question." and is a pun on the two meanings of 'dumb' -- 'mute' and 'stupid'. Obviously, a question that is not asked (i.e., remains mute) does not exist.

There are, indeed, many stupid questions -- not that his was one.

Also, 'ignorant' is not 'stupid'. And a question not asked in ignorance is not really a question. At best, it is rhetorical. More often, it is a cry for attention.

But, the philosophy forum is next door. This is debate, rant, and abuse. :whistling:

--Pete

[kandrathe]

Actually, that should read, "There's no such thing as a dumb question." and is a pun on the two meanings of 'dumb' -- 'mute' and 'stupid'. Obviously, a question that is not asked (i.e., remains mute) does not exist.

There are, indeed, many stupid questions -- not that his was one.

Also, 'ignorant' is not 'stupid'. And a question not asked in ignorance is not really a question. At best, it is rhetorical. More often, it is a cry for attention.

But, the philosophy forum is next door. This is debate, rant, and abuse. :whistling:

:lol: Yes. I bow to your description. While the lay wisdom is that the only stupid question is the one that remains unasked, I've been through many semesters of classes to see my fair share of questions that the press the limit. Not that this one did at all.

[kandrathe]

So do I. But some things are too big (hurricanes), too small (quarks), too fast (shock fronts), or too slow (universes) to bring into the lab. Then you make a goulash of theory, experiment, and computer models and do your best. But the more you know and the more honest you are, the less you trust those results.

With climate at least, we can see an event, like Mt. Saint Helen exploding, and then measure local atmospheric change and then observe how that effects the local and global climate. Then, you have studies, like contrails missing during 9-11, that seem like good opportunities to study change, but fail to factor in all the variables. The biggest problem is repeatability.

I thought this was a funny excerpt from the article; <blockquote> "After hearing the news, Dr Forster said it was every scientist's dream to win a Nobel Prize before adding: "It's perhaps a little deflating though, that one man and his PowerPoint show has as much influence as the decades of dedicated work by so many scientists."</blockquote>

[--Pete]

Hi,

. . . we can see an event, like Mt. Saint Helen exploding, . . .

I actually did see that event. Well, almost. I was living in Pullman, Washington at the time, and on May 18, 1980 nightfall came from the West in the late morning. It had many effects, from a severe shortage of beer, to a large number of February births the following year. Most of our research was shut down because we wrapped our electronics in plastic to protect them from the volcanic dust that got everywhere. A humorous point: Magi had been a student janitor at WSU and the Friday before the eruption had been her last day. As the ash settled all around us, she remarked that she was very happy that it would not be her problem:)

. . . and then measure local atmospheric change and then observe how that effects the local and global climate. . . . The biggest problem is repeatability.

I think that's a toss up. The inability to control the other parameters is also a major problem. Unlike a controlled lab experiment, the best that observation of natural phenomena permits is to find correlations.

I thought this was a funny excerpt from the article; . . .

My personal favorite is, "But people don't appreciate that most documents on climate change are based around an international consensus that involves hundreds of scientists and publications." I somehow don't think 'international consensus' is adequate.

--Pete

[weakwarrior]

There are, indeed, many stupid questions -- not that his was one.

My brother likes to tell his students there is no such things as a stupid question only a stupid student.