Error found in climate modelling: Too many droughts predicted An international team of top boffins say that current climate models are based on faulty assumptions which lead them to predict more drought than will actually be the case. A storm is brewing (Mali, Sahel). Foto: F. Guichard & L. Kergoat, AMMA project, CNRS copyright. OK, the drought didn't turn up. Again At the moment, …
This didn't ought to provoke any particular ranting.
It's nothing to do with human contribution to global warming which seems to be the polarised issue.
This is about an entirely different piece of modelling and while LP might possibly want to keep the idea that models and predictions of negative effects arising from these models are often wrong in the forefront of people's minds there's nothing directly provocative in this article.
"It would seem that in one important respect at least, science to date has been predicting a future grimmer than will actually be the case."
This seems a really bold conclusion given the data presented - my guess is that changes like this will be slightly chaotic to the output of the model rather than linear as you suggest.
all that this shows is that a particular part of a model is wrong. Its not until the system as a whole is modeled that you can say what the overall implication is - I'd suspect that it will be extremely dependant upon the layout. At the extreme consider a ring shaped dry area encircling a damper area, this change to assumptions could presumably lead to the damp region being progressively dried out over a period of years. If it then turns out that the "damp" area is where we currently live and grow food thats not a good result.
For what its worth I'm personally of the opinion that most climate models are probably overstating the effects at present, however if you're going to report something like this please think about your conclusions. This shows part of a model is wrong - not what implications are on a systemic level.
Was going to post the exact same thing - all the study does is say that an assumption is wrong. No studies as yet have been made with corrected assumptions, ergo the statement "science to date has been predicting a future grimmer than will actually be the case" is inaccurate with current data.
I'm not saying it will prove inaccurate when models are updated, though.
"This seems a really bold conclusion given the data presented - my guess is that changes like this will be slightly chaotic to the output of the model rather than linear as you suggest. All that this shows is that a particular part of a model is wrong. Its not until the system as a whole is modeled that you can say what the overall implication is - I'd suspect that it will be extremely dependant upon the layout. "
If you are saying that changing the basic assumptions of the AGW model are not going to change the model's prediction then I agree with you completely... except that the reasons for the predictions remaining unchanged have *nothing* to do with science...
What I'm saying is that changing an assumption in a model this complex probably has an equal chance of making the prediction "better" or "worse", of course thats a global view.
At a small scale I suspect this change in assumptions will create local predictions of drought and flooding in different locations. The question will be are those currently the useful / productive areas of the planet?
Here's a relevant quote from the study's authors:
http://www.livescience.com/23128-dry-soils-more-rain.html
The researchers emphasize "it's important to recognize that we are comparing storm statistics between nearby places with the same climate," Taylor told OurAmazingPlanet. "We are not saying that rain is more likely in the Sahara than the Amazon Basin."
Moreover, "I should add that we can only see this signal when regions get quite dry, ruling out places like the United Kingdom," Taylor added.
Could it be because weather and climate are 2 completely different things? I can accurately predict that it will be colder in the winter than in the summer this year, next year and any year afterwards. That's climate.
Predicting where a particular rain cloud will go over the next few days based on satellite photos is much harder. This is weather. Weather predictions are nowadays amazingly accurate 3-4 days in advance and predict rain and sunshine with about an hour of accuracy.
"I can accurately predict that it will be colder in the winter than in the summer this year, next year and any year afterwards. That's climate."
That's climate, but it is not a climate prediction. It is a prediction that Earth will continue to orbit the sun. A climate prediction would put numbers on how much hotter or colder it will be down here on Earth. And yes it's different from weather, but so far we've no evidence that short term (a century or so) climate prediction is any easier than long-term (a month or so) weather prediction.
You could always ignore climatology and stick with astronomy and geology. In the medium term, you are probably safe to guess that Milankovic cycles will continue for the next million years or so. Longer than that, you are probably safe to assume that ocean circulation will be predominantly pole-to-pole rather than round-and-round (because continents don't shift too quickly) and therefore we're unlikely to return to the sort of climate seen at various points in the past which saw 20C at the poles. But these aren't climate predictions either.
Actually I am in the UK. Hint: predictions for the UK as a whole are not accurate for most people, watching the weather on the news is useless except for whole country predictions such as big storms or snow. Get predictions for where you actually live on BBC weather. And yes, it does rain pretty much when the forecast says it does, so I use it to decide whether to cycle to work or not.
If only! The forecasts appear to be no better than guessing by sticking one's head in a cupboard. A few times they get a forecast of wind right and once recently we had some rain, more or less on forecast. Perhaps I live in a rainless bowl as some round here suggest. After a summer of record rain we are still wondering if the cracks in the garden will get much bigger and if we should try to fill them with sand or compost.
@Wilco1:"Get predictions for where you actually live on BBC weather."
Have they launched a new service? I haven't seen it, can you provide a link?
The service I've seen only provides hourly forecasts for the next 48 hours (and in my area you wouldn't believe how often those change between rain and sun some days), but then they expand the time interval to 3 hourly.
BBC weather forecasts for 3-5 days out *usually* change back and forth over the 3 days leading up to them. That is, the forecasters will issue 3 different forecasts in three days, for the fourth day. They aren't *that* accurate.
OTOH, the forecast for the next 12 hours is fairly accurate and you'll be OK planning your bike ride. Back on the first hand, simply travelling hours upwind and seeing what the weather is currently like there will probably give a pretty accurate forecast, without any profound understanding of meteorology. I don' t know (in percentage terms) how much better the computers are than the "12 hours upwind" methodology.
Yes, I get that they're different. But both processes of forecasting rely to a greater or lesser extent on models: that's where I see a parallel. Weather and climate predictions don't always deliver what the model said would happen or when it might happen.
Personally I'd like better weather forecasts. For society as a whole I'd like accurate climate modelling. It's why I said that I hoped that this result improves both.
Except.....
1) we can predict next weeks weather with remarkable accuracy
2) if you don't get that weather <> climate, please don't try and walk and chew gum at the same time.
I do however agree - this is the way science works, incremental improvements building on observations and fed into models that gradually get better at forecasting the future.
Alright, you're boring me now.
I see this trotted a LOT. Usually when there's some report showing that the Apocalypse is not about to occur tomorrow and that the New Gaians might in fact be spouting a religion rather than actually using the scientific method to study anything beyond their articles of faith.
What this means to the victim on the street is "that thing you thought we were talking about where there's floods and droughts and apocalypse and the weather KILLS YOU DEAD? It's not weather. It's a special magic thing called climate that you don't understand. But I understand it. I can bless you and save you from your sins. Give me thirty-five million pounds for a new wind farm or GAIA WILL BE ANGRY".
Wankers.
(Note - no opinion on whether the climate is changing due to human activity or indeed whether any alteration of human activity is required, sensible or not was made in this post. Only the assertion that all priests are scammers, Gaian as much as any other).
@Steve Knox -
I might. Joe Average shouldn't unless clear definitions are given, which they pretty much never are.
Usually Joe gets "the climate is getting warmer". Then he sees record cold winters. Then he's told "that's just weather, not climate you ignorant fool. Gaia will smite you!" which is not the behaviour of responsible scientists. Neither, incidentally, is RTFM - that's the behaviour of the smug geek. What Joe Public gets to listen to is a priesthood which condemns those who argue with it and threatens apocalypse unless it is placated with vast amounts of money.
Without a move to a) educate and b) genuinely debate - ie, stop calling people deniers and abusing their intellect - this situation can only worsen.
@Matthew 3:
Fill the sink with water. Drop in a spot of ink. Pull out the plug.
You'll have great difficulty saying whether the ink will make it to any particular spot or not but you can say with certainty that it will all go down the plug hole.
We can often say something useful about global behaviour of a system without being able to specify in detail the evolution of every point.
Climate modelling is about large-scale behaviour; weather, about more detailed behaviour.
So the news is "The climate model that we have been using to garner attention and government grants is really based off of a bunch of information that we padded to give us the results that we wanted and fundamentally flawed ideas on how the ecosystem works. Thus is it not representative of anything that will actually occur and more akin to a gigantic hole where the government can stuff a bunch of money to support green companies that they own stock in."
Well Duh. I'm a stoopid 'Merican and I know that.
"There's broad agreement on all sides of the environmental debate that climate change is occurring: and indeed that it always has been. Disagreement generally begins on exactly what it is that the future holds, who is responsible, and what is to be done.."
I added a li'l clarification there. I don't that anyone will object.
(And, appropriately, a little echo of tt. Lenin & Herzen there, no? кто виноват? и что делать? And we all know how *that* worked out. But then again they also thought they knew what the future held.)
Actually many of the feedbacks happen to be positive. Negative feedbacks primarily slow down the speed of warming, but they cannot stop it (in the short term) due to being overwhelmed by our emissions. For example increased absorption of CO2 from the atmosphere by oceans and extra plant growth only removes 50% of the CO2 we emit. As the ocean heats up it can take on less CO2 - ie. effectively becomes a positive feedback. Other feedbacks such as water vapour can be both positive and negative, with the effects almost cancelling each other out.
Over many thousands of years, assuming humans have either stopped emitting CO2 or existing, negative feedbacks will eventually catch up and slowly stabilise the climate again. But that's not relevant, what matters is they are too weak to reverse the current warming trend over the next 100 years.
If climate mode as a whole was dominated by positive feedbacks, we'd see more stability, not less. It would enter a cold spell, and "stick" in an ice age. Some amount of warming, and the ice would melt rapidly, and we'd observe long ice-free (or ice-lite) interglacial periods. A primary mechanism for this would be ice cap albedo. Other mechanisms might be storage and release of methane in methane hydrate formations as the oceans cool and warm.
Whoops, that's what we see. And look what's melting in the Arctic.
Nice try at tying long term climate variations with positive and negative feedback loops. However, they are likely a result of periodic orbit fluctuations due to the gravitational effects of Jupiter. In fact, the variance would have been higher without the loops. Earth climate is at a dynamic equilibrium. It's fairly obvious that we're affecting that equilibrium. Possibly stressing it. And if that was what the global warmists claimed, then that would be fine and dandy. But it's not. The extraordinary claim is that we're about to break that equilibrium and that extraordinarily expensive and urgent measures are needed to prevent that. However, the corresponding extraordinary proof is somewhat lacking.
Ok, we now know the assumptions are wrong somewhere.
So amend the assumptions, load with the same data and rerun those predictions, if they still do not match reality, change and rerun until they do.
This does not mean fudge the input data to match your biases (smoothing a time series to get the hockey stick for instance!)
I understand the difficulty in designing a hypothetical model that seems to most resemble the observations of the climate. Humans are naturally very very good at spotting patterns in random behaviour however (we see faces in clouds all the time...). What I don't understand is how easily it seems that these scientists apply positive feedback, which we all know can only exists for a short period of time (unstable period) before a system falls into a stable (negative feedback) state. Thermodynamics, entropy, control theory, common sense... there are many approaches to this understanding. I don't deny the negative impact that humans are having on the planet, but for me each positive feedback mechanism I hear about discredits an otherwise sound scientific approach. If you must identify a positive feedback mechanism, at least consider the tipping point at which positive feedback can no longer be sustained (unless you have a design for a perpetual motion machine that can solve the worlds energy needs!)
The question is what do you call a short period? There is no doubt the climate will eventually stabilise itself (we won't see runaway warming), but it may take many thousands of years. In the meantime we have to live with it.
Also can you point us to a strong negative feedback machanism that will kick in shortly? So far there aren't any signs of strong negative feedbacks, but there are signs that the existing negative feedbacks (such as CO2 absorption by oceans, ice/snow coverage) are turning into positive feedbacks (as ocean temperature rises, it absorbs less CO2, and snow/ice coverage is declining fast, eg. arctic ice).
It's actually worse than that. The models use formulas that don't have have corresponding real world phenomena because using those formulas makes the data sort of work, where as using the formula you'd get from the real world phenomena produces an obviously bad result. A mathematician friend of mine who works in the field doesn't see a problem with this approach as long as the model produces reasonably accurate predictive results. I do because it indicates that while we may have maths that are helpful, we understand nothing about the way the system really works. To me it's the ancient Greeks being able to chart where the planets would be even though they put the Earth at the center of the universe and thought heavy objects fell faster than light ones. I wouldn't have as much of a problem with it if the people behind the models would admit as much and work at getting a better understanding of the real physics involved rather than heading off on a political jihad.
In terms of AGW if you sift through the hyperbole to the actual basics of the AGW proposition it works like this.
Lets define some variables.
We will lump all the things that affect climate into one generic lump, and call it K, for known variables and driver affecting climate.
So we observe that in the late 20th century, ΔT != f(ΔK).
That is temperature changes can not be accounted for by currently known variables.
So we pick on one known unknown, CO2 gas concentration (lets call that C) and try
ΔT = f(ΔK) + f(ΔC).
Sadly this does not work either. The effect of CO2 is too small to account for observed ΔT!
Now at this point you have a known unknown . Your model does not work as it is. So you have two choices.
(I) introduce an unknown feedback term to multiply the effect of CO2. (lambda factor) giving you an equation of the form:- ΔT = f(ΔK) + λ f(ΔC). This is the essence of the IPCC model.
(ii) simply accept that there is in addition to carbon dioxide, something else (U for unknown) going on as well giving rise to climate changes, so we have : ΔT = f(ΔK) + f(ΔC) + f(ΔU).. This is the essence of say - Svensmark et al's hypotheses where cloud cover is modulated by cosmic rays etc etc.
There is an important point here. Both models assume an known unknown element. In the IPCC model its a feedback system - positive feedback as well. It is not clear whether in fact they don't make a rather logically absurd assumption here as well, because the lambda factor should multiply ANY climate change due to other effects. I.e. the proper IPCC equations should be of the form:
ΔT =λ( f(ΔK) + f(ΔC)).
The problem is that this leads to a very unstable climate - which is simply not borne out by the historical record.
In short the 'CO2 is not the whole story' models of Svensmark and co actually fit the data better.
So if you compare the two possible models you have the following broad conclusions from the IPCC
- most warming in the late 20th century was man made
- feedback only applies to carbon dioxide created warming. Or the historical records don't fit.
- the lambda factor necessary to make the data fit this model produces really scary climate change predictions, justifying massive expenditures on products Al Gore and his chums sell.
Whereas lumping the known unknowns into a separate function with NO overall positive feedback gives rather different conclusions
- most warming in the late 20th century was not man made
- climate change will happen independently of any human attempts to stop it
- there is no point spending money on products and technologies to make the attempt: better is to spend the money on dealing with it
- we can't say whether or not scary climate change is happening/will happen, or not.
Naturally enough the political movements and industries geared to taking your money and spending it on stuff that either doesn't work at all, or doesn't work well enough to make any real difference (but we have to make the attempt, right?) have a lot riding on the IPCC general equation form.
Feedback is essential to keep the green machine on track printing money.
THAT'S why everyone loves it. Nothing else produces scary warming. In fact the non lambda models tend to suggest that we are more likley to be about to enter a global cooling period with far more drastic impacts on human life.
I presume that is because your post had no actual information content in it. Do you seriously think you can make a claim about actual climate models based on your misunderstanding how they actually work?
I suggest you first read up on climate science and how modelling is actually done. Here is a good article describing the 23 models used in AR4, and a link to more papers about those models, including actual source code:
http://www.ipcc.ch/pdf/assessment-report/ar4/wg1/ar4-wg1-chapter8.pdf
http://www.easterbrook.ca/steve/?p=667
re itzman:
"So we pick on one known unknown, CO2 gas concentration (lets call that C) and try"
CO2 concentration, and it's forcing, is in no way unknown! It's a known known. Definitely.
"It is not clear whether in fact they don't make a rather logically absurd assumption here as well, because the lambda factor should multiply ANY climate change due to other effects. I.e. the proper IPCC equations should be of the form:
ΔT =λ( f(ΔK) + f(ΔC))."
The lambda factor does multiply ANY climate change due to other effects. That's the whole point of the concept. Climate sensitivity (λ) is measured in units C/wm-2. Anything that induces a forcing (wm-2) will produce a temperature range according to: ΔT = λ x F, precisely because things like albedo feedback and water vapor feedback will kick in response to a temperature change from whatever source.
And by the way the idea of a climate without feedbacks is complete nonsense. Albedo, water vapor and cloud feedback are known to exist. Any model that assumes feedbacks don't exist is simply wrong. Climate modellers didn't decide to arbitrarily add some "feedback term" to the models to fit the warming as you claim. They added feedbacks because they are known to exist, ie they HAD to add them.
"The problem is that this leads to a very unstable climate - which is simply not borne out by the historical record."
Yes I guess it would cause unstable behaviour where the climate might switch between two very different states in response to small orbital forcings. Perhaps we could cause these states "glacial" and "interglacial" periods....oh wait.
"In short the 'CO2 is not the whole story' models of Svensmark and co actually fit the data better."
Except Svensmark and co don't have a quantified mechanism. There's no "wm-2" value that's been calculated for any change in cosmic rays from physical principles. In any-case the biggest problem is that cosmic rays show no trend in the past 50 years so they CANT possibly explain the warming in the late 20th century.
On the otherhand the wm-2 value for rising CO2 is very big, much bigger than anything else that is known to be happening. Sure maybe scientists have missed something else with an even bigger forcing (although I doubt it, if it's big it should be obvious), but to assume that some unknown unknown exists and trumps what is known is both unfalsifiable and the height of wishful thinking. It just aint science.
The problem with that is not that feedback doesn't exist, its that it has to be overall negative, or the planet would be uninhabitable.
The standard excuse that water vapours is a positive feedback element is of course nonsense. The more the world gets hotter, the more the oceans generate water vapour, the bigger the thermal activity there is that carries that warmth into the stratosphere well above any greenhouse effects and the more it radiates into space, this cooling the planet.
"The problem with that is not that feedback doesn't exist, its that it has to be overall negative, or the planet would be uninhabitable."
Not true. The planet would be habitable even with positive feedback. Positive feedback means changes are amplified, not that they run away to infinity.
"The standard excuse that water vapours is a positive feedback element is of course nonsense. The more the world gets hotter, the more the oceans generate water vapour, the bigger the thermal activity there is that carries that warmth into the stratosphere well above any greenhouse effects and the more it radiates into space, this cooling the planet."
And which model shows that? The model in your head? Yes what a great argument, we should ignore all those models running on supercomputers and written by physicists and instead trust your imaginings about what happens.
"But unconstrained amplification takes you infinity. At some point, the feedback needs to go negative for the system to find a new stable point."
You are right, but in climate it's not unconstrained. Warming of the Earth itself results in more energy emitted into space which eventually balances out the forcing and the warming stops. The concept of climate sensitivity is the amount of warming necessary to bring the system back into a new stable point when a forcing is applied. The new stable point is an Earth with a different mean temperature, which is effectively by this equation:
dT (C) = Forcing (wm-2) x Sensitivity (C/wm-2)
The forcing from a doubling of CO2 is 3.7wm-2. Climate models find a sensitivity around 0.75C/wm-2 (+- a lot) so the expected stable point after a doubling of CO2 is about 2-4C warming. By climate models "finding" a sensitivity I mean the sensitivity is an emergent behavior of the models. The above equation is a simple fit to a more complicated pattern derived from models. It makes it easier to estimate how much warming a 1wm-2 increase in solar radiance will cause without having to run it through a model.
"In any-case the biggest problem is that cosmic rays show no trend in the past 50 years so they CANT possibly explain the warming in the late 20th century."
Simplistic.
Cosmic ray rates in and of themselves do not have to show a trend. Whatever can locally modulate them will do, or periodic changes in what they actually affect physically may change.
Fire a bowling ball at the pins every 30 seconds; never change this. Periodically alter the ball trajectory via obstacle placement, or periodically don't replace all of the pins. I guarantee that the pin knockdown count will be related to everything *but* the non-changing rate of firing the ball.
... that guessed that climate change models were imperfect and that doomsday is a bit further away than they forecast.
software (although the modelling is very complex) is only as good as the last bug (feature?)
perhaps they could factor in parameters for solar activity as well - it does affect the weather too (surprise!)
wait until they find out the long term atmospheric trends suggest (note suggest) that wind speeds in the northern hemisphere may decrease significantly by the 2030's - which leads us to wonder how will the wind turbines will generate power to pay for themselves.
Once again the people who build these models seemed to have though they had a simple element to deal with when they actually had a simplistic model for something this is actually (a bit more) complex.
I think the fact it has taken *five* decades to review *this* assumption speaks volumes for how systematically the modellers have accepted their models limitations and worked to eliminate them.
"fudge factors" are the universes way of telling you that you do not fully *understand* the system.
But it seems the bits the modellers *think* they understand in fact they do not.
Thumbs up for *starting* to look through the fine print, but *boy* has it taken a long time to get here.
I can only quote a renowned skeptic Robert G Brown on the quality of climate modelling
" If one tried to actually write “the” partial differential equation for the global climate system, it would be a set of coupled Navier-Stokes equations with unbelievably nasty nonlinear coupling terms — if one can actually include the physics of the water and carbon cycles in the N-S equations at all. It is, quite literally, the most difficult problem in mathematical physics we have ever attempted to solve or understand! Global Climate Models are children’s toys in comparison to the actual underlying complexity, especially when (as noted) the major drivers setting the baseline behavior are not well understood or quantitatively available. "
Then maybe we should stop trying to base world-wide policies on them at all, then.
Climate change science/politics currently boils down to "We're all heading for disaster, use less plastic bags and change your bulbs for CFL - by the way, we have no idea if that's true or not". We have no idea what's happening, how much, or how to fix it if it is.
We could literally play this game for 10 thousands years and never see significant climate change and praise everyone who's ever used a Bag for Life for their work in overcoming climate change when actually it made zero difference whatsoever and they could have burned a million plastic bags a year each and never affected the climate - that's not to say it's "healthy", just that we have ZERO idea if it affects climate or not. Literally. Zero. Nothing. Nada.
Or we could just say "Damned if I know. Let's not form world economic policy around complete speculation and worry about bigger things that we *CAN* prove are detrimental and fix them now, like oil running out and the atmosphere being polluted rather than what might happen if an iceberg may/may not break off thousands of miles away within the next thousand years and potentially wipe us out / do nothing at all but provide us with some large ice cubes."
Hell, to me personally, I think we're better spending money at the moment looking for Earth-killing asteroids than anything directly related to solely climate change (which is a poor excuse to use when things like oil are running out and will be millions of times more devastating within my lifetime if left unchecked). We stand a better chance of spotting something that MIGHT wipe us out, prove whether or not it will before it comes, and still be around to say "I told you so" whichever outcome occurs.
Probably more like
"I don't know if it's a problem, I don't know if we can fix it if it is, and I don't know where to start. This however is obviously a problem, I know exactly what needs to be done, and I can do something about it"
As the OP said, there are many things of far more value that we could and should work on. And if we do work on something which as the OP says will have more devastating effects in our lifetime (eg oil running out) we may just see the whole climate problem disappear as well.
If the money that was spent (wasted?) on all this climate stuff was put into research in other areas (health, food production, clean energy.....) we'd probably be much closer to living carbon neutral lives.
If there actually is a climate problem.
(I don't know if there is. I do know that the global warming/climate change/whatever the hell it's called today crowd have damaged their credibility and I tend to doubt what they say, especially when I see the differences between what the climate is doing today and what we were told a few years ago it would be doing today!)
@itzman
For a while I thought I was the only one with this view of climate modelling. Non-linearities in the real world makes predictive modelling impossible over anything other than trivial timescales. I suppose one reason I came to my conclusion is that I have a PhD in non-linear computer modelling, but what the heck, in this area, everyone's an expert.
And just to be clear, I do not deny that humans have had an impact on the global climate. I posit that the climate models are bad at predictions - things could be a lot worse than is being predicted.
We should be planning for survival on a "do it anyway, it makes sense" basis.
Welcome to science, we're always learning more and more about the world. The fact that data gets reviewed and models get tweaked is a good thing.
Science has given us many things over the years and those who don't believe climate change should go live in an Amish community as if they don't believe in science they should not be allowed to gain any benefit from scientific discoveries. Just like those who oppose stem cell research should not have any benefit from that when they need it later in life.
If you want to predict climate x years ahead, first try going backwards x years, and check this against historical data. When you can "predict" backwards with an acceptable degree of accuracy, you then have the basis for going forwards. Until then you are just pissing in the wind.
This is already done - after all, climate scientists have only been doing this stuff for over 30 years... Predictions turn out to be quite accurate, and usually conservative (ie. predicting slightly lower warming than actually measured, or predicting sea ice to disappear more slowly than it currently is doing). This link gives a few examples:
http://www.skepticalscience.com/climate-models-intermediate.htm
Note that climate models will never be 100% perfect as you can't model every molecule in the atmosphere individually. However it is unlikely the predictions will change drastically as the models are made more accurate: the refinements are increasingly about the small details, not about the underlying physics which are well understood.
"Predictions turn out to be quite accurate, and usually conservative (ie. predicting slightly lower warming than actually measured, or predicting sea ice to disappear more slowly than it currently is doing)."
In which case either you (or the people who you've linked to) do not understand what the word "conservative" means in a *scientific* context.
A good "conservative" model in this context makes predictions that are slightly (IE at most 10s of %, rather than say 3x ) *worse* than real life.
So when you design things or base policy on them you know it will be OK as it will *always* be below prediction.
If your model does not predict the Little Ice Age or the Medieval Warm Period then it isn't a useful model.
If you haven't tested the predictive capabilities of your model then you are not a scientist and "climate science" is not a science. So why are we spending Billions?
Another thing, if the earth is warming why aren't we measuring the temperature of the earth rather than the air?
Oh good - as the models don't generally have any problem simulating the little ice age , where we have some systematic observational data so have something to test against (the mwp is a bit harder as there aren't good observational data, so its harder to work out if the model is successful - but it still can be, and has been, done), and you will, therefore, have to accept that climate science does work.
And - we are measuring the temperature of the earth, and what do you know, it shows the same pattern of warming - you can even reconstruct paleo temperature by measuring temperature gradients, and knowing how fast heat propagates through rock, get estimates of past temperatures.
Backwards prediction is all fine and dandy, but what happens is that after a while you start tweaking your model to actually give good backwards prediction results. Or stated alternatively, you're effectively running a genetic algorithm where only models that do give good backward prediction survive. This is another form of "curve fitting". Thus by continuously using the same "validation" data, you're effectively using fitting the model to that data.
That still doesn't mean that they'll be any good with predicting was is going to happen. Interpolation is good, extrapolation is evil. Effectively fitting observed data to a model to obtain the "actual" forcing values becomes hazardous the more model parameters there are. The problem being that there may not be a unique solution and you can't determine beforehand whether the solution, "fitting", you've found is the correct one. (Most likely it isn't.)
Another thing to bear in mind is that many of the "constants" used in the model were obtained by fitting historic data to a model of some sort, the more data, the better the fit. Therefore models should be able to "predict" the past quite well since they are based on the historic data.
Unfortunately, only time will tell whether the models were/are correct/incorrect and by that time it may be too late.
Some excellent points.
I'd suggest a rational basis for a model would be basic physics (with *all* assumptions tested first) then expand out to start identifying the missing areas and start on actual physics and chemistry models of those, *not* using fudge factors.
How viable that is in the real world is debatable but I think fudge factors are just another facet of Dykstra's warning that premature optimization is the root of all evil.
"Then maybe we should stop trying to base world-wide policies on them at all, then."
RV Jones in "Instruments and Experiences" called that a "Doctrine of Impotence." Basically "We can't do it so let's not even look at what the *boundaries* of our ignorance are."
This is simply not an option because the *effects* of climate change (never mind what's causing them) are so *vast* on people and property that modelling to get some idea of the scale of the events *has* to be done. Insurance companies do flood modelling for example to decide what premiums they should set long term.
" it would be a set of coupled Navier-Stokes equations with unbelievably nasty nonlinear coupling terms "
It's quite instructive to see how aircraft, missile and space vehicle designers use tools that implement similar equations.
Publicly identify ranges of speed, temperature, pressure, altitude (and possibly ) body shape the tool is *known* to be reliable over, and at what point "all bets are off."
Publicly give the error bounds their tools results will have.
Run new tools (or upgraded versions) against *standard* problems whose correct results have been verified either in hardware or derived closed form equations, with results from other CFD programs as a last resort.
Warn where the tool uses *gross* simplifications of the physics. The classic being the 2 factor turbulence model, which *can* work pretty well but does not involve *any* of the underlying variables that are known to affect this.
Warn that the results need *careful* interpretation and *should* be checked against real life (in a wind tunnel or sub scale flight models).
A similar process also happens with the tools used for designing launch ascent trajectories and orbital paths.
The results have been *cautious* use of these tools and gradual *continued* improvement from a *trustworthy* base with *lots* of cross checking between tools and models and flight data or orbit observations.
There appears to have been no *systematic* review of any of the General Circulation Models. Either the "Science is settled(although in at least one case it was wrong)" or "We (IE the developers) know how to twiddle the fudge factors to make it produce the last few decades results. We'll just leave it on those settings and that's that," which is fine *unless* you have a very slowly changing factor that you just happen to have set a reasonable value of for *this* period.
Couple that with the software development practices described in the Harryreadme file of the CRU at East Anglia an you have a house of (punched?) cards.
Humans *have* altered the global climate on human timescales. CFCs and damage to and recovery of the Ozone layer bear that out. That *human* generated CO2 is a cause of *bigger* changes is an *extraordinary* claim and demands *extraordinary* evidence. The scales of these issues is so vast that GCM development *should* use our most reliable development methods and highest documentation standards.
Sadly that does not seem to be the case.
There's a hierarchy of simplicity versus impact. Physics is simple, biology is extremely complicated. Physical processes can have a moderate impact, biological processes can (for example) change the entire composition of the Earth's atmosphere (oxygen, perhaps you've heard of it). Biology can be stronger than Physics - imagine if the oceans were poisoned and all life there died.
This error was in the basic physics. Imagine if (*) the models fail to include all possible biological feedback loops. The models would always be crude and incomplete (**).
Hints: * they do. ** they are.
Climate modeling is a weak science. This needs to be kept in mind. All science papers based on computer models shall be forced to end with one last word: "...Maybe."
Note: I'm still generally in favour of efficiency and reducing dependence on fossil fuels, especially coal. But I hate weak science dressed up as hard science. And then defending it by dragging the debate into the dark religious vocabulary world of "belief" and "skepticism". It's become a religious screaming match, especially from the moral majority. News flash - you need to continuously defend your science if it is to improve. Screaming "skeptic" is a Science Fail.
So if the scientists predicted 20 droughts with their previous methods and with the new methods we get 15 instead we're now OK? Nothing to worry about, eh?
Again, this is the typical AGW tactic of finding a seeming contradiction and then jumping all over it like it is way more important than it really is. The scientists creating these models are quite aware that they have had to make simplifying assumptions to make their models work. They try to make assumptions that don't effect the results, of course.
There is actual science going on here, so the models themselves are being evaluated to see if they can be improved. This happens all of the time, just in this case the suggestion is that the models are sometimes predicting too many droughts. Most of the predictions of climate science tend to underestimate the effects. So I wouldn't be surprised if other reviews finds all sorts of errors that underestimate things as well. None of this invalidates the results .. it just makes them better and furthers our understanding.
The issue here is that the camp that preach Global Warming is man made or man is contributing to global warming point to models like the one in this article. BUT, time and time again holes are found in these models. The very action of making an assumption, of which I bet there are many, means that you are incorporating a basis that is a risk to the model being correct. This is where I have a problem with all man made GW alarmist preachers, how can you trust these models?
How many times do we have to go through this process of data questioning planted by the major polluters? Time and again, they are proven wrong. It is about time to put the let on the doubter's assertions and shut them up for good. Having easy money from dirty fuel is good for them but bad for the rest of the people on the planet. Year after year we read reports of havoc on the planet from man made heat/cold waves....
"Fossil Fuel" tends to be dirty, that is true.
What to do about it.
I have x dollars spare. I can put that money into a) climate research or b) alternative fuel research.
One will give lots of fancy looking computer models which will scare people into demanding more money gets put into it, money which will be required to hide the many holes we simple humans will inevitably make in our models simply because we cannot understand something so complex. The other will give us clean fuel which will mean we're not emitting anywhere near as much carbon, which means that if our carbon emissions are affecting the climate in a bad way then that problem will also be solved.
And in the short term, we'll all be healthier, energy will (hopefully but sadly I doubt it!) be much cheaper, and we won't have to worry about the impact that running out of oil will have on the planet's populations (hint: it'll probably be much more devastating than any actual climate changes in the short(er) term - do you live in a city? Grow your own food? No? Think it'll be either as cheap or abundant if/when we run out of fossil fuels?)
Scientists with their deliberately imperfect models are just really rakin' in the dough making all of these scary claims about the climate. Last I saw they had even nicer houses than the CEO's of fossil fuel companies. A lot of them even own yachts.
It's hard to understand why they even bother to build equipment that actually attempts to measure things to make their reports. They could just use their largess to buy a bigger yacht instead. Or a trophy wife perhaps.
Not.
Before we allow advocates of "De-Growth" and "De-Peopling" to sacrifice the lives and prospects of Billions of our fellow humans in order to "Save the Planet", now may be a good time to admit that this is likely to prove a fraudulent, "Faustian" bargain built on misplaced fear.
History shows that ideological zealots and politicians calling for authoritarian measures to combat a looming danger are mendacious merchants of terror and oppression, and result in far greater misery than the dangers they point to in justification.
Whatever the merits of climate change with or without AGW, I fear the hazards of anti-human totalitarian rule far more!. At least Mother Nature is impartial and free from malice. Human ideologues are not!
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