Pointy-haired Climate Modeling (feat. Bonus Vintage Fred Pearce)

From Real Climate’s “FAQ on climate models“:

Multi-model Ensemble – a set of simulations from multiple models. Surprisingly, an average over these simulations gives a better match to climatological observations than any single model

And here’s the Dilbert strip of May 7, 2008:

Of course.

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Here’s another attempt at linking Dilbert to the climate change debate. And of course Scott Adams is not exactly your average RC fan.

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And now for the “Bonus Vintage Fred Pearce”, from a May 16, 2007 New Scientist article linked by Adams and penned by…Fred Pearce: “Climate myths: We can’t trust computer models”

Finally, the claim is sometimes made that if computer models were any good, people would be using them to predict the stock market. Well, they are!

A lot of trading in the financial markets is already carried out by computers. Many base their decisions on fairly simple algorithms designed to exploit tiny profit margins, but others rely on more sophisticated long-term models.

Major financial institutions are investing huge amounts in automated trading systems, the proportion of trading carried out by computers is growing rapidly and a few individuals have made a fortune from them. The smart money is being bet on computer models.

Smart money indeed.

Don’t Be Fooled By Another Non-Climate Satellite

The SMOS satellite is flying, and it will provide data for around three years. A “probe tracking global warming impact on water“? Not by a long shot (what are three years for climate??).

Remember to always read it all and carefully so.

Scientists rely heavily on computer models to project weather and climate patterns, and the additional data will make predictions more accurate.

SMOS “has long been awaited by climatologists who try to predict the long-term effects of today’s climate change,” said ESA’s director of Earth observations programme Volker Liebig in a communique. “The data collected will complement measurements already performed on the ground and at sea.”

As sadly usual, in climatology observations are subservient to models, rather than the other way around…

Finally, A Model That Does Exactly What It Says On The Tin

Or…”What Are Climate Models Good For”

“Instant climate model gears up – Simulation tool gives rapid feedback on implications of policy changes“, says “Nature News”.

What’s so good about it? Well, for once everybody should join in the celebration of a climate model that is presented for what it is (a policymaking tool for “negotiators to assess their national greenhouse-gas commitments ahead of December’s climate summit in Copenhagen“) rather than for what it is not (a scientific tool “used for a variety of purposes from study of the dynamics of the climate system to projections of future climate“, as rather naively claimed on Wikipedia).

Hooray for honesty and openness!

When Is A Climate Satellite Not Exactly A Climate Satellite?

I have just been at a beautiful presentantion at the British Interplanetary Society in London, by Jessica Housden of EADS-Astrium about the upcoming ESA “EarthCARE” satellite (beautiful especially to us engineering boffins that is).

Designing a Spacecraft to Observe Climate Change

Understanding of the atmosphere is a continual process, with scientists all over the world endeavouring to determine how our atmosphere works and how it is changing. One such mission, EarthCARE, will be observing several processes which will help scientists. How will this be done and how will the spacecraft work?

Jessica Housden is a systems engineer for the EarthCARE mission, which will observe water content and aerosol distribution in the atmosphere.

Ms Housden said that EarthCARE, designed to look at clouds and aerosols, will be up there for 4 years from around 2013 (don’t bet your house on that though…there’s lots to learn before it can actually fly).

Upon hearing that I suddenly realised something confirmed during the Q&A session later: the climate-change EarthCARE satellite is not exactly a satellite to study the climate.

For a start, 4 years are way too short a time to see what climate is doing, let alone to see it changing.

You see, EarthCARE is a climate-change satellite. Its measurements will be used to (surprise, surprise!) help climate modellers improve their models (as everybody knows, clouds have been particularly badly modelled up to now).

After all, that’s what it “says on the tin” (“Spacecraft to observe Climate Change“, not “Climate“). Nothing to fault EADS-Astrium for…still, I suspect in the upcoming future one will have to be careful about this apparently minute distinctions.

What about the Climate then? Well, EarthCARE would be a good starting point. For example one of its instruments is designed to measure incoming and outgoing fluxes, thereby answering many of the questions we still have about the planetary energy budget.

But you’d need a constellation of EarthCAREs for proper climate research, perhaps 5 or 6, if only to observe a particular spot more than once a month. And you’d need also a steady supply, to have enough of them up there despite the relatively-short 4-year lifetime.

There Is No Evidence

From Icecap why Global Warming Clearinghouse, here’s an intro to “There is no evidence” by Dr David Evans:

Let’s break down the case for human-caused global warming logically:

1) There is plenty of evidence that global warming has been occurring recently.
2) There is ample evidence that carbon emissions causes warming and that the level of atmospheric carbon dioxide is increasing.
3) But there is no evidence that carbon dioxide emissions are the main cause of the recent global warming.

The alarmists focus you entirely on the first two points, to distract you from the third. The public is increasingly aware of this misdirection. Yes, every emitted molecule of carbon dioxide (CO2) causes some warming – but the crucial question is how much warming do the CO2 emissions cause? If atmospheric CO2 levels doubled, would temperatures rise by 0.1, 1.0, or by 10.0C?

We go through the usual “evidence” offered by alarmists, and show that in each case either it:

• Is not evidence about what causes global warming. Proof that global warming occurred is not proof that CO2 was mainly responsible.
• Is not empirical evidence; that is, it is not independent of theory. In particular models are theory, not evidence.
• Says nothing about how much the temperature would rise for a given rise in CO2 levels.

[…]  If they just had some evidence of (3) they could just tell us what it was and end the debate.

[…] Typical Alarmist Offerings of “Evidence”: Polar Bears, Glaciers, Arctic Melt, Antarctic Ice Shelves, Storms, Droughts, Fires, Malaria, Snow Melt on Mt Kilimanjaro, Rising Sea Levels, Ocean Warming, Urban Heat Island Effect. Although each of these issues may say something about whether or not global warming is or was occurring, none of them say anything about the causes of global warming. It would make no difference to these issues if the recent global warming was caused by CO2 or by aliens heating the planet with ray guns.[…] Often the assumption takes the form that nearly all the temperature rises since the start of industrialization are due to CO2 rises, or that there are no other possible significant causes of global warming.

Computer Models are Evidence
Computer models consist solely of a large number of calculations that, individually, you could do on a hand-held calculator. So models are theoretical, and cannot form part of any evidence.

Computer Models Incorporate a Lot of Sound Empirical Science
Yes they do. The climate models contain some well-established science that has been verified by empirical observations. But they also contain a myriad of:
• implicit and explicit assumptions
• omissions
• guesses
• gross approximations.

A single mistake in any one of these can invalidate the climate models. Typical engineering models that mimic reality closely contain no untested assumptions, material omissions, guesses, or gross approximations. They are the result of mature understanding of the reality being modelled, and have been tested ad nauseum in a wide range of circumstances. On the other hand, climate science is in its infancy, individual models routinely fail most tests, the climate models are riddled with untested assumptions and guesses, they approximate the atmosphere with cells a hundred kilometres square and hundreds of meters high, and they do not even attempt to model individual cloud formations or any feature smaller than the cell size. Don’t let the word “model” fool you into thinking climate models are better than they are.

Richard S Courtney: Temperatures, Climate Models…And The Human Brain

(This is part of a private message from Richard S Courtney, answering a third person’s question: “what fundamental principles of thermodynamic, radiative forcing or radiation balance are in conditions to explain the fall of latest global temperatures observed by University of Alabama in Huntsville?”

Published with Richard’s permission)

I look at the records of global temperature and I see a series of cycles that are overlayed on each other. For example,

1. There seems to be an apparent ~900 year oscillation that caused the Roman Warm Period (RWP), then the Dark Age Cool Period (DACP), then the Medieval Warm Period (MWP), then the Little Ice Age (LIA), and the present warm period (PWP).

2. There seems to be an apparent ~60 year oscillation that caused cooling to ~1910, then warming to ~1940, then cooling to ~1970, then warming to ~2000, then cooling since.

So, has the warming from the LIA stopped or not? That cannot be known because the pattern of past global temperature fluctuations suggests that the existing cooling phase of the ~60 year cycle is opposing any such warming. And that cooling phase can be anticipated to end around 2030 when it can be anticipated that then either

(a) warming from the LIA will continue until we reach temperatures similar to those of the MWP

or

(b) cooling will set in until we reach temperatures similar to those of the LIA.

But this begs the question as to why such global temperature fluctuations occur. And I address that issue as follows.

The basic assumption used in the climate models is that change to climate is driven by change to radiative forcing. And it is very important to recognise that this assumption has not been demonstrated to be correct. Indeed, it is quite possible that there is no force or process causing climate to vary. I explain this as follows.

The climate system is seeking an equilibrium that it never achieves. The Earth obtains radiant energy from the Sun and radiates that energy back to space. The energy input to the system (from the Sun) may be constant (although some doubt that), but the rotation of the Earth and its orbit around the Sun ensure that the energy input/output is never in perfect equilbrium.

The climate system is an intermediary in the process of returning (most of) the energy to space (some energy is radiated from the Earth’s surface back to space). And the Northern and Southern hemispheres have different coverage by oceans. Therefore, as the year progresses the modulation of the energy input/output of the system varies. Hence, the system is always seeking equilibrium but never achieves it.

Such a varying system could be expected to exhibit oscillatory behaviour. And, importantly, the length of the oscillations could be harmonic effects which, therefore, have periodicity of several years. Of course, such harmonic oscillation would be a process that – at least in principle – is capable of evaluation.

However, there may be no process because the climate is a chaotic system. Therefore, observed oscillations such as ENSO, NAO, PDO and etc. could be observation of the system seeking its chaotic attractor(s) in response to its seeking equilibrium in a changing situation.

Very importantly, there is an apparent ~900 year oscillation that caused the Roman Warm Period (RWP), then the Dark Age Cool Period (DACP), then the Medieval Warm Period (MWP), then the Little Ice Age (LIA), and the present warm period (PWP). As I suggest above, all the observed rise of global temperature in the twentieth century could be recovery from the LIA that is similar to the recovery from the DACP to the MWP. And the ~900 year oscillation could be the chaotic climate system seeking its attractor(s). If so, then all global climate models and ‘attribution studies’ utilized by IPCC and CCSP are based on the false premise that there is a force or process causing climate to change when no such force or process exists.

But the assumption that climate change is driven by radiative forcing may be correct. If so, then it should be noted that it is still extremely improbable that – within the foreseeable future – the climate models could be developed to a state whereby they could provide reliable predictions. This is because the climate system is extremely complex. Indeed, the climate system is more complex than the human brain (the climate system has more interacting components – e.g. biological organisms – than the human brain has interacting components – e.g. neurones), and nobody claims to be able to construct a reliable predictive model of the human brain. It is pure hubris to assume that the climate models are sufficient emulations for them to be used as reliable predictors of future climate when they have no demonstrated forecasting skill.

So, my bottom line answer to a question that asks, “what fundamental principles of thermodynamic, radiative forcing or radiation balance are in conditions to explain the fall of latest global temperatures observed by University of Alabama in Huntsville ?” is

I don’t know because nobody can know, but I want to know.

And that is why I support attempts to quantify all the “fundamental principles” which you mention because that attempt affords the possibility of telling me what I want to know.

Stansted Climate Protest, or Why AGW Must Be Challenged

Major PR debacle for AGWers, one hopes, in today’s break-in at London’s Stansted Airport with thousands unable to leave for their expected destinations.

And it’s not just a matter of going home and rebook online: imagine how many pre-booked vacations have been ruined, family reunions postponed, business meetings cancelled, money wasted in giant taxi fares and expensive car parking, that will have to be paid again shortly.

Who would have guessed, of all people the climate protesters have prevented from flying a BBC journalist with plenty of AGW articles in his CV and a long-planned trip to Poznan to attend the UN climate talks. Is there a long, long ferry journey to Denmark in Mr Black’s future, one wonders?

Promises of bringing to protesters in front of a court of justice already abounds. However, in the recent past the UK Government has approved of apparently law-breaking climate-change protests, so I would’t bet anybody will be punished…

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Actually the Plane Stupid’s plain stupid initiative of today comes out handy to demonstrate why AGW has to be challenged by everybody with a sane mind: because it has been portrayed in so dire terms, that people of various critical ability will do who-knows-what excessive actions in its name.

If 80% or more of the living species are threatened by humans, surely a terrorist attack will appear fully justified in many not-even-too-deranged-minds? People have been bombing each other for decades for far less than the well-being of the biosphere. One wished nonviolence figured more prominently in the Plane Stupid declarations.

Nothing is safe from “the threat of runaway climate change”, and no rights can be considered too important for AGWers to leave it untouched: our rights to move freely, to choose how to earn and how to spend our money, to plan for a holiday, to visit parents and other relatives abroad or even on the other side of the country, not to mention the right to think if not express the opinion that AGW is a big castle made of nothing like sand, they will all disappear sooner or later, if nobody tries to insert some sense in the climate discussion.

The strange bit is that even such an authoritative AGW group like the IPCC, and avowed catastrophiliacs such as Lord Stern, do not believe overdramatic actions are needed today, or tomorrow. Rather, they all advocate something to be done in the scale of decades.

And that is even more worrying: because in spite of what is actually meant by Stern, or by Al Gore, or by James Hansen or the UK Government,  at the end of the day their choice of words will always inspire simpletons to do something very very silly at airports and elsewhere; and Governments to curtail civil liberties in the name of the Greater Good That Could Not Have Been Portrayed Greater.

Perhaps more people will wake up one day to the fact that he transformation of society into a “Moral Police State” is the only way AGW  can be stopped, or so it is implied by those that portray it as the biggest challenge to humanity, a threat bigger than the terrorism, the source of everything wrong with the world today, the thing that will burn up the world to cinder, etc etc.

All statements, by the way, that rest on very weak foundations, because extraordinary claims need extraordinary evidence. And we don’t have it.

Financial Crisis to Climate Negotiators: DO NOT OVER-RELY ON MODELS!!!

The ongoing financial crisis can and will teach all of us many lessons, also in terms of climate and AGW. And no, I do not mean the rather naive made-up litany visible at ClimateProgress.

I refer to something much more profound, especially since there is now evidence that even the guys at RealClimate do not fully understand what they are dealing with, when they deal with climate models (even after loving models to death).

Consensus is in fact emerging about three advices that went missing during the build-up of the financial troubles:

• DO NOT OVER-RELY ON MODELS
• DO NOT JUST PUSH TOWARD EVER MORE COMPLEX MODELS
• BE SENSIBLE WHEN MANAGING RISK

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I have prepared a couple of quick lists from three recent articles on the business pages of the International Herald Tribune (full attributed quotes at the bottom of the blog; and yes, do keep in mind those are from analysts that are experts in their field indeed).

First, what went wrong. It’s evident that plenty of it directly related to the climate debate:

• Models gave a false sense of precision. They can now be seen as educated guess calculated to many decimal places. At the time, they appeared precise, and yet proceeded to ultimately demonstrate themselves as totally off base
• Until the crisis, the field (of financial risk modeling) enjoyed a halo of academic credibility
• In general, there was too much focus on quantitative issues and data and models. People did not know what to do with things that cannot generally modeled as a quantifiable risk
• Risk managers were also too busy with models and bringing up data that could not be absorbed by senior management
• Better modeling, more wisely applied, would have helped, but so would have common sense in senior management

Obviously, the danger lies in the fact that to confuse the model with the world is to embrace a future disaster, as humans (or the climate) do not just obey mathematical rules that can be modeled.

What should be done? I wish the negotiators in Poznan had the following list in mind:

• Understand that risk is a function of behavior more than of models
• Consider that risk management is about making big-picture choices, not just trying to prevent losses
• Acknowledge that risk may mean different things, like hazard, threat, gamble, chance, possibility, or opportunity
• Accept that models are useful as points of information. They shouldn’t drive risk tolerance and shouldn’t be used to tell anybody how to manage firms (or nations)

Models getting translated to the real world of company or national policy suffer indeed from a “chinese whispers syndrome”, with the original caveat-full expert statements awfully simplified and distorted for the benefit of the business directors (or national politicians).

At the end of the day, the problem is not the models. The models are tools, perhaps the devil’s but still just tools. The problem is putting all eggs in the models basket, in financial just as in AGW terms.

====

(original quotes)

(1) From In fallout from crisis, rethinking risk and human judgment, by Lynnley Browning; IHT, Wednesday, November 19, 2008

[…] to cope with uncertainty and “slippery slopes” […] “With this crisis, everybody is re-evaluating the concept of risk management,” said Richard Phillips, a professor of risk management and insurance at Georgia State University […]

The scrutiny goes beyond a dissection of the complex mathematical models created by financial engineering [and focuses] “on the overreliance on models,” said Carol Fox of the Risk and Insurance Management Society […]

Because nearly all risk-management models failed to predict or protect against the crisis, Fox said, insurers will increasingly view risk “more as a function of behavior than of models.”

Going forward, she said, insurers will use models “as a point of information, but it won’t drive risk tolerance” […].

“People have been managing the wrong risk […] ” said Peter Bernstein, a historian and the author of “Against the Odds: The Remarkable Story of Risk.” ”Risk management is about making choices, not preventing losses. […]

the financial crisis has made clear is that risk, and how one deals with it, can mean wildly different things to different companies, from gamble, hazard or chance to threat, possibility or opportunity. It can be a bucket of nasty things to be avoided, or a daring play. […]

It didn’t help matters that until the crisis, the field enjoyed a halo of academic credibility. “All these rocket scientists with Ph.D.s provided reassurance to decision makers and buyers,” said Paul Bracken, a professor of political science at Yale University.

[According to] Robert Merton, the Harvard Business School professor who received the Nobel in economic science in 1997 […] “A lot of it is straightforward things, like judgments made to accept ratings. We’ve got to get these financial engineers and quant types out of the banks and get sensible types in.” […]

“Our definition of risk became confused with obeying the law,” said Bill Sharon, chief executive of Sorms, a risk-management consulting firm. […]

Now, insurers are increasingly looking at risk management as a process applying […] to big-picture questions […].

After all, said Martin Grace, associate director of the Center for Risk Management and Insurance Research at Georgia State University, “you can have math models, but that doesn’t tell you how to manage the firm.”

(2) From When crisis hit, a global framework for limiting risk proved ineffective by Conrad de Aenlle, IHT, Wednesday, November 19, 2008

[…] Even if [The Basel II international accord on banking supervision] had been put into practice immediately, it might not have averted the crisis. Critics contend that the various models, formulas and equations used to determine asset quality provide a false sense of precision, leaving bankers and regulators with no clear idea of where they stand. The numbers that are derived amount to an educated guess calculated to umpteen decimal places.

“There has been too much focus on quantitative issues and data and models and a lack of understanding of what the main risks are in the business model,” said Peter Neu, a principal in Frankfurt for the Boston Consulting Group. “Risk managers are too busy with models and bringing up data that can’t be absorbed by senior management.”

A shortcoming of some models is that their risk projections come with a caveat that they are assumed to be accurate during normal market conditions. […]

(3) From Wall Street’s extreme sport: Financial engineering by Steve Lohr, IHT, November 5, 2008

“Complexity, transparency, liquidity and leverage have all played a huge role in this crisis,” said Leslie Rahl, president of Capital Market Risk Advisors, a risk-management consulting firm. “And these are things that are not generally modeled as a quantifiable risk.”

The miss by Wall Street analysts shows how models can be precise out to several decimal places, and yet be totally off base

The quantitative models typically have their origins in academia and often the physical sciences. In academia, the focus is on problems that can be solved, proved and published — not messy, intractable challenges. In science, the models derive from particle flows in a liquid or a gas, which conform to the neat, crisp laws of physics.

“To confuse the model with the world is to embrace a future disaster driven by the belief that humans obey mathematical rules.”

Better modeling, more wisely applied, would have helped, Lindsey said, but so would have common sense in senior management

The Pointlesseness of Climate Data

Brett Anderson of Accuweather links to a Nov 5, 2008 Earth Observatory article by Rebecca Lindsey, “Correcting Ocean Cooling“, examining how Josh Willis “determined that there were errors” in his “Recent Cooling of the Upper Ocean” work.

(both the 2007 correction and 2006 original are available at this link)

Brett explains that:

“After applying a correction, the historical record shows a relatively steady increase (ocean heat content) in line with what’s shown by climate models”

I am sorry but it does sound fishy that all the hard digging was done only because the data were too cool. One is left with the lingering feeling that no such an effort ever materializes for data that shows warming (talk about WARMING BIAS there…)

And in fact: taking the Earth Observatory article at face value, one can indeed figure out the real reason behind Willis’ revisiting of his original data. At the time of publication of the original article (2006):

Willis described the [original] results as a “speed bump” on the way to global warming

Apparently, he soon convinced himself his data was not right. In February 2007, Willis said to his wife:

“I think ocean cooling isn’t real”

Why? Because:

In fact, every body was telling me I was wrong

And what was Willis’ own “tipping point”?

It wasn’t until that next year of data came in that the cooling in the Atlantic became so large and so widespread that Willis accepted the cooling trend for what is was: an unambiguous sign that something in the observations was “clearly not right.”

In all likelihood, had the original data shown warming, and/or the “next year of data” shown widespread warming, few if anybody would have told Willing that he was “wrong“. Chances are he would not have re-analysed anything at all.

The real irony can be extracted from the end of the EO piece:

We need multiple, independent, overlapping sets of observations of climate processes from space and from the Earth’s surface so that we can create long-term climate records—and have confidence that they are accurate. We need theories about how the parts of the Earth system are related to each other so that we can make sense of observations. And we need models to help us see into the future.

But for years, Willis has been stressing that

Argo data show no warming in the upper ocean over the past four years, but this does not contradict the climate models

Now, obviously the corrected data do “not contradict the climate models” either.

And so it really does look like there is no need for “multiple, independent, overlapping sets of observations“. Any and every data is always unable to “contradict the climate models“.

Why do people still bother to measure anything related to climate when the end result is pre-ordained, one wonders.

Climate Models Are Correct (And Useless)

Climate models are correct indeed. Because, as Bill Clinton would love to say, it depends on what the definition of “correct” is.

In the real world, climate models cannot be falsified by a single observation (modelists say it’s “only weather”), or by a set of short-term observations (they call it “just a specific trajectory”).

In theory, one could wait a sufficient number of years in order to statistically check if the world has actually got warmer, but in practice models don’t include volcanoes, clouds, solar activity, etc: therefore, even if observations diverge from the models, all the modelists will do is find a “culprit” that can justify the discrepancy.

For the 1940-1970 cooling climate, they say “it was the aerosols”. Never mind that it could be a made-up story.

RealClimate’s own Gavin has said in the recent past, there is no interest in verifying if models are correct or not. Instead, the “right question” appears to be: “are there analyses that will be made over the next few years that will improve the evaluation of climate models?”

It should go without saying that in such a situations, models have no predictive capability beyond chance and they are for all intents and purposes useless.

Imagine modelling a human being as a heart pump with tubes coming in and out, and then when the patient dies of tuberculosis, having the superciliousness to state “the model is correct” instead of understanding that humans have a pulmonary system too (and a lot of other systems).

Kudos to RealClimate’s Honesty and Sincerity

And no, I am not being sarcastic.

It’s just that (finally!) there is a RC claim that can be compared to the real world; next to it, a good dose of outright sincerity (surely it must have been there before,  perhaps buried in the polemic…)

From What the IPCC models really say (May 12, 2008):

• Claims that GCMs project monotonic rises in temperature with increasing greenhouse gases are not valid. Natural variability does not disappear because there is a long term trend. The ensemble mean is monotonically increasing in the absence of large volcanoes, but this is the forced component of climate change, not a single realisation or anything that could happen in the real world.
• […]
• Over a twenty year period, you would be on stronger ground in arguing that a negative trend would be outside the 95% confidence limits of the expected trend (the one model run in the above ensemble suggests that would only happen ~2% of the time).

Note that even the fabled 20-year negative trend may still be interpreted as consistent with at least one model run.

But it’s a good step in the right direction: bringing back climate science from its forcings cage to the actual world…

Climate Change Detection/Attribution? Some Hope!

Curious situation on the website of the PCMDI – the “Program for Climate Model Diagnosis and Intercomparison”, at the Lawrence Livermore National Laboratory, with a stated mission:

to develop improved methods and tools for the diagnosis and intercomparison of general circulation models (GCMs) that simulate the global climate

Here’s what the PCMDI has to say about “devising robust statistical methods for climate-change detection/attribution“:

Coming soon…

That’s it.

Wow.

Sure.

Well, it looks like we will just have to be patient. We will be told how to detect and attribute climate change…one day, perhaps after some considerable amount of time will have ben spent in the frankly rather wasteful efforts of mostly comparing climate models to each other, rather than to the actual world.

p.s.: Applause to the PCMDI for their frankness:

The need for innovative analysis of GCM climate simulations is apparent, as increasingly more complex models are developed, while the disagreements among these simulations and relative to climate observations remain significant and poorly understood. The nature and causes of these disagreements must be accounted for in a systematic fashion in order to confidently use GCMs for simulation of putative global climate change.

Aristotle’s Climate Model

Greek philosopher Aristotle may have written the first treatise on Meteorology, around 350BC. He postulated the existence of five geographical zones: Frigid (one North, one South) by the poles, Torrid (North and South of the Equator) and Temperate (one North, one South) in-between the relative Frigid and Torrid zones.

Remarkably, that subdivision still holds. One of Aristotle’s ideas has not survived the test of time though: contrary to his thoughts, the Torrid Zone is not devoid of life and especially of human life due to excessive warmth.

And so we can say that Aristotle was totally wrong. Or was he?

Let’s perform some quick computations using modern readings and the world as known by ancient Greeks.

=================

Consider Alexandria and Aswan, in Egypt, the cities used by Eratosthenes of Cyrene to measure the accurately measure the size of the Earth (around a century after Aristotle’s time).

From the BBC Weather website, temperature statistics for both cities can be computed

Alexandria (31 degrees North):
Average monthly Min: 17.3C
Average monthly Max: 24.9C
Average yearly: 21.1C

Aswan (24 deg N):
Average monthly Min: 19.1C
Average monthly Max: 34.25C
Average yearly: 26.7C

Now, since we know there are 7 degrees of latitude between the two cities, we can compute at what rates temperatures increase going south from Alexandria to Aswan:

Temperature increase by degree of Latitude:
Average monthly Min: 0.26C/deg
Average monthly Max: 1.33C/deg
Average yearly: 0.798C/deg

What is the expected temperature at the Equator (Latitude: zero, thus 24 degrees south of Aswan), assuming those rates don’t vary (i.e. temperature trends can be modelled in linearly)?

Equator (zero deg):
Expected Average monthly Min: 25.5C
Expected Average monthly Max: 66.3C
Expected Average yearly: 45.85C

Look at those temperatures…if those were true, truly the Equator would be more or less uninhabitable.

Therefore: Aristotle’s idea of a “Torrid Zone” was not a philosophical fantasy, but a reasonably estimation compatible with what was known during ancient times.

=================

Of course we know the actual values are different. For example:

Kinshasa (4 deg N):
Average monthly Min: 20.7C
Average monthly Max: 30.4C
Average yearly: 25.5C

That makes Aristotle’s Climate Model wrong of an amount between 5C and 36C.

=================

So what are the lessons to take home?

(1) Climate models that appear perfectly reasonable today can be shown to be very, very wrong tomorrow

(2) Extending a trend means just making an estimation that can be way off reality, especially if the trend is presumed linear

(3) Temperature is NOT everything. Actual climate depends on a lot of other things.

At the Equator, like everywhere else on the planet.

Ocean Circulation May or May Not Weaken with Global Warming

Ocean circulation in a warming climate – J. R. Toggweiler & Joellen Russell
Nature 451, 286-288 (17 January 2008) | doi:10.1038/nature06590; Published online 16 January 2008
Abstract: Climate models predict that the ocean’s circulation will weaken in response to global warming, but the warming at the end of the last ice age suggests a different outcome.

And so AGW studies start resembling dieting advice. Whatever you like to eat, just wait long enough and some paper will say it’s good for you.

ps a more serious note: how much more exciting would climatology be, were it not poisoned by all the save-the-planet agitation!!