We discuss climate models a lot, and from the comments here and in other forums it’s clear that there remains a great deal of confusion about what climate models do and how their results should be interpreted. This post is designed to be a FAQ for climate model questions – of which a few are already given. If you have comments or other questions, ask them as concisely as possible in the comment section and if they are of enough interest, we’ll add them to the post so that we can have a resource for future discussions. (We would ask that you please focus on real questions that have real answers and, as always, avoid rhetorical excesses).
Part II is here.
Quick definitions:
- GCM – General Circulation Model (sometimes Global Climate Model) which includes the physics of the atmosphere and often the ocean, sea ice and land surface as well.
- Simulation – a single experiment with a GCM
- Initial Condition Ensemble – a set of simulations using a single GCM but with slight perturbations in the initial conditions. This is an attempt to average over chaotic behaviour in the weather.
- 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.
- Model weather – the path that any individual simulation will take has very different individual storms and wave patterns than any other simulation. The model weather is the part of the solution (usually high frequency and small scale) that is uncorrelated with another simulation in the same ensemble.
- Model climate – the part of the simulation that is robust and is the same in different ensemble members (usually these are long-term averages, statistics, and relationships between variables).
- Forcings – anything that is imposed from the outside that causes a model’s climate to change.
- Feedbacks – changes in the model that occur in response to the initial forcing that end up adding to (for positive feedbacks) or damping (negative feedbacks) the initial response. Classic examples are the amplifying ice-albedo feedback, or the damping long-wave radiative feedback.
Questions:
- What is the difference between a physics-based model and a statistical model?
Models in statistics or in many colloquial uses of the term often imply a simple relationship that is fitted to some observations. A linear regression line through a change of temperature with time, or a sinusoidal fit to the seasonal cycle for instance. More complicated fits are also possible (neural nets for instance). These statistical models are very efficient at encapsulating existing information concisely and as long as things don’t change much, they can provide reasonable predictions of future behaviour. However, they aren’t much good for predictions if you know the underlying system is changing in ways that might possibly affect how your original variables will interact.
Physics-based models on the other hand, try to capture the real physical cause of any relationship, which hopefully are understood at a deeper level. Since those fundamentals are not likely to change in the future, the anticipation of a successful prediction is higher. A classic example is Newton’s Law of motion, F=ma, which can be used in multiple contexts to give highly accurate results completely independently of the data Newton himself had on hand.
Climate models are fundamentally physics-based, but some of the small scale physics is only known empirically (for instance, the increase of evaporation as the wind increases). Thus statistical fits to the observed data are included in the climate model formulation, but these are only used for process-level parameterisations, not for trends in time.
- Are climate models just a fit to the trend in the global temperature data?
No. Much of the confusion concerning this point comes from a misunderstanding stemming from the point above. Model development actually does not use the trend data in tuning (see below). Instead, modellers work to improve the climatology of the model (the fit to the average conditions), and it’s intrinsic variability (such as the frequency and amplitude of tropical variability). The resulting model is pretty much used ‘as is’ in hindcast experiments for the 20th Century.
- Why are there ‘wiggles’ in the output?
GCMs perform calculations with timesteps of about 20 to 30 minutes so that they can capture the daily cycle and the progression of weather systems. As with weather forecasting models, the weather in a climate model is chaotic. Starting from a very similar (but not identical) state, a different simulation will ensue – with different weather, different storms, different wind patterns – i.e different wiggles. In control simulations, there are wiggles at almost all timescales – daily, monthly, yearly, decadally and longer – and modellers need to test very carefully how much of any change that happens because of a change in forcing is really associated with that forcing and how much might simply be due to the internal wiggles.
- What is robust in a climate projection and how can I tell?
Since every wiggle is not necessarily significant, modellers need to assess how robust particular model results are. They do this by seeing whether the same result is seen in other simulations, with other models, whether it makes physical sense and whether there is some evidence of similar things in the observational or paleo record. If that result is seen in multiple models and multiple simulations, it is likely to be a robust consequence of the underlying assumptions, or in other words, it probably isn’t due to any of the relatively arbitrary choices that mark the differences between different models. If the magnitude of the effect makes theoretical sense independent of these kinds of model, then that adds to it’s credibility, and if in fact this effect matches what is seen in observations, then that adds more. Robust results are therefore those that quantitatively match in all three domains. Examples are the warming of planet as a function of increasing greenhouse gases, or the change in water vapour with temperature. All models show basically the same behaviour that is in line with basic theory and observations. Examples of non-robust results are the changes in El Niño as a result of climate forcings, or the impact on hurricanes. In both of these cases, models produce very disparate results, the theory is not yet fully developed and observations are ambiguous.
- How have models changed over the years?
Initially (ca. 1975), GCMs were based purely on atmospheric processes – the winds, radiation, and with simplified clouds. By the mid-1980s, there were simple treatments of the upper ocean and sea ice, and clouds parameterisations started to get slightly more sophisticated. In the 1990s, fully coupled ocean-atmosphere models started to become available. This is when the first Coupled Model Intercomparison Project (CMIP) was started. This has subsequently seen two further iterations, the latest (CMIP3) being the database used in support of much of the model work in the IPCC AR4. Over that time, model simulations have become demonstrably more realistic (Reichler and Kim, 2008) as resolution has increased and parameterisations have become more sophisticated. Nowadays, models also include dynamic sea ice, aerosols and atmospheric chemistry modules. Issues like excessive ‘climate drift’ (the tendency for a coupled model to move away from the a state resembling the actual climate) which were problematic in the early days are now much minimised.
- What is tuning?
We are still a long way from being able to simulate the climate with a true first principles calculation. While many basic aspects of physics can be included (conservation of mass, energy etc.), many need to be approximated for reasons of efficiency or resolutions (i.e. the equations of motion need estimates of sub-gridscale turbulent effects, radiative transfer codes approximate the line-by-line calculations using band averaging), and still others are only known empirically (the formula for how fast clouds turn to rain for instance). With these approximations and empirical formulae, there is often a tunable parameter or two that can be varied in order to improve the match to whatever observations exist. Adjusting these values is described as tuning and falls into two categories. First, there is the tuning in a single formula in order for that formula to best match the observed values of that specific relationship. This happens most frequently when new parameterisations are being developed.
Secondly, there are tuning parameters that control aspects of the emergent system. Gravity wave drag parameters are not very constrained by data, and so are often tuned to improve the climatology of stratospheric zonal winds. The threshold relative humidity for making clouds is tuned often to get the most realistic cloud cover and global albedo. Surprisingly, there are very few of these (maybe a half dozen) that are used in adjusting the models to match the data. It is important to note that these exercises are done with the mean climate (including the seasonal cycle and some internal variability) – and once set they are kept fixed for any perturbation experiment.
- How are models evaluated?
The amount of data that is available for model evaluation is vast, but falls into a few clear categories. First, there is the climatological average (maybe for each month or season) of key observed fields like temperature, rainfall, winds and clouds. This is the zeroth order comparison to see whether the model is getting the basics reasonably correct. Next comes the variability in these basic fields – does the model have a realistic North Atlantic Oscillation, or ENSO, or MJO. These are harder to match (and indeed many models do not yet have realistic El Niños). More subtle are comparisons of relationships in the model and in the real world. This is useful for short data records (such as those retrieves by satellite) where there is a lot of weather noise one wouldn’t expect the model to capture. In those cases, looking at the relationship between temperatures and humidity, or cloudiness and aerosols can give insight into whether the model processes are realistic or not.
Then there are the tests of climate changes themselves: how does a model respond to the addition of aerosols in the stratosphere such as was seen in the Mt Pinatubo ‘natural experiment’? How does it respond over the whole of the 20th Century, or at the Maunder Minimum, or the mid-Holocene or the Last Glacial Maximum? In each case, there is usually sufficient data available to evaluate how well the model is doing.
- Are the models complete? That is, do they contain all the processes we know about?
No. While models contain a lot of physics, they don’t contain many small-scale processes that more specialised groups (of atmospheric chemists, or coastal oceanographers for instance) might worry about a lot. Mostly this is a question of scale (model grid boxes are too large for the details to be resolved), but sometimes it’s a matter of being uncertain how to include it (for instance, the impact of ocean eddies on tracers).
Additionally, many important bio-physical-chemical cycles (for the carbon fluxes, aerosols, ozone) are only just starting to be incorporated. Ice sheet and vegetation components are very much still under development.
- Do models have global warming built in?
No. If left to run on their own, the models will oscillate around a long-term mean that is the same regardless of what the initial conditions were. Given different drivers, volcanoes or CO2 say, they will warm or cool as a function of the basic physics of aerosols or the greenhouse effect.
- How do I write a paper that proves that models are wrong?
Much more simply than you might think since, of course, all models are indeed wrong (though some are useful – George Box). Showing a mismatch between the real world and the observational data is made much easier if you recall the signal-to-noise issue we mentioned above. As you go to smaller spatial and shorter temporal scales the amount of internal variability increases markedly and so the number of diagnostics which will be different to the expected values from the models will increase (in both directions of course). So pick a variable, restrict your analysis to a small part of the planet, and calculate some statistic over a short period of time and you’re done. If the models match through some fluke, make the space smaller, and use a shorter time period and eventually they won’t. Even if models get much better than they are now, this will always work – call it the RealClimate theory of persistence. Now, appropriate statistics can be used to see whether these mismatches are significant and not just the result of chance or cherry-picking, but a surprising number of papers don’t bother to check such things correctly. Getting people outside the, shall we say, more ‘excitable’ parts of the blogosphere to pay any attention is, unfortunately, a lot harder.
- Can GCMs predict the temperature and precipitation for my home?
No. There are often large variation in the temperature and precipitation statistics over short distances because the local climatic characteristics are affected by the local geography. The GCMs are designed to describe the most important large-scale features of the climate, such as the energy flow, the circulation, and the temperature in a grid-box volume (through physical laws of thermodynamics, the dynamics, and the ideal gas laws). A typical grid-box may have a horizontal area of ~100×100 km2, but the size has tended to reduce over the years as computers have increased in speed. The shape of the landscape (the details of mountains, coastline etc.) used in the models reflect the spatial resolution, hence the model will not have sufficient detail to describe local climate variation associated with local geographical features (e.g. mountains, valleys, lakes, etc.). However, it is possible to use a GCM to derive some information about the local climate through downscaling, as it is affected by both the local geography (a more or less given constant) as well as the large-scale atmospheric conditions. The results derived through downscaling can then be compared with local climate variables, and can be used for further (and more severe) assessments of the combination model-downscaling technique. This is however still an experimental technique.
- Can I use a climate model myself?
Yes! There is a project called EdGCM which has a nice interface and works with Windows and lets you try out a large number of tests. ClimatePrediction.Net has a climate model that runs as a screensaver in a coordinated set of simulations. GISS ModelE is available as a download for Unix-based machines and can be run on a normal desktop. NCAR CCSM is the US community model and is well-documented and freely available.
Stefano, #219.
So what made you not believe the scientific community?
Given we have no evidence of you ever believing them in the first place, how do we know you are telling the truth? See, we are acting skeptically. Just like you.
Detrich, #198. Yes, but not if the theory supposed is “Well, it COULD happen”. I could transubstatiate and become a demi-god and no longer care what happens to mortals.
No idea how, nor even if it’s possible.
So I don’t bother to entertain the idea.
Now, do you have a theory that puts in stasis the GW for thirty years that isn’t “well, there could be one”? If you do, let us all know. Expect skepticism over it.
And make sure you explain what you’re doing properly.
Stefano (217), I agree with you that most of what scientists focus on is of interest to academics, but not necessarily relevant for policy. What is relevant for policy is the main thrust of the expected changes and their expected consequences; the details are in the realm of academics, not policy making.
You write “So what if you can say that the future will be a bit warmer and maybe a lot warmer?” If we take “the spread of possible future outcomes” in a business as usual scenario, then it’s fair to say that if it’s bad, it’s really bad, and if it’s good, it’s still pretty bad. In other words, the scientific details are not going to radically alter the needed policy response. As Herman Daly noted in a recent speech (http://www.climatepolicy.org/?p=65): “If you jump out of an airplane you need a crude parachute more than an accurate altimeter”. I commented on his speech on my blog (as did Michael Tobis on “init”).
Mark, please, let people post questions. They may not please you, they may have poor assumptions — but they’re not atypical of questions people ask. The thread here is dedicated to _collect_questions_.
Just smile and let them post their questions. Some will be useful here.
There are plenty of threads in which someone is wrong on the Internet.
How many components do the models have? How many different physical (or statistical) parameters are there?
Some of those parameters are probably known quite precisely. But others must be less precise. Are the models rerun with various plausible values for all these parameters?
re: #231, by John Mashey
many thanks for the link to your “old post”…IMHO, it should
be on the required reading list for all of us participating in
discussions of climate models
re #255
I think the answer to your question is yes; see here
http://www.climateprediction.net/index.php
Mark (#249, #250): Please note that I did not say I don’t know the answers. I said I am confused with your definitions, so I wanted to hear yours. So far you did a good job in representing incoherence in the jargon.
Regarding the question about “forcings” to be stupid: so, in your opinion it is clever to “explain” workings of climate in terms of “forcings” and “feedbacks” that you cannot even explain what they are, but it is stupid to ask questions about them?
The reason for all this confusion is that the climate is a system with tightly-coupled spatio-temporal state variables, each one affecting the other in a circular self-feeding way. What is stupid (as you phrased it) is to attempt to “explain” its behavior by slicing it into “forcings”, “amplifiers”, and “feedbacks”. These are all concepts from essentially one-dimensional electro-mechanical control theory, where these building blocks and signals are separated by design. This partitioning does not apply to dynamics of fluid. If you will attempt to justify the partitioning by invoking a difference in time scales, it will be still goofy because the system is strongly turbulent, and turbulent systems have CONTINUOUS spectrum of time “wiggles”, and there is no considerable time interval where you can “draw a line” and separate “statistical averaging” from “large scale dynamics”.
I hope that my comments would lead to more coherent answers to the FAQ, such that people would not hold their smiles (as compared to Hank’s sentiment in #254). Now I will follow your suggestion and leave. Thanks.
Re #225/#232/#234
Yes, each of those is a salutory reminder of the added burden of industrial human existence.
Respiration (“breathing”) is inherently net-neutral with respect to CO2, and if one considered the pre-industrial age, the planet could support a large fauna (including pre-industrial/pre-agricultural humankind) whose breathing merely returned CO2 into the atmosphere, previously ingested (as metabolites of carbohydrate) from plants which pulled this CO2 out of the atmosphere in the first place. The planet could in principle support a very large fauna, including humans, while maintaining net-neutrality with respect to CO2 production.
It’s only when deforestation and other land use changes made a net shift of carbon in the short term carbon cycle from plants back into the atmosphere, that humans began to make a net positive return of CO2 into the atmosphere (although deforestation is essentially reversible in principle), and it’s very true to point out that industrial scale animal husbandry with its high cost in fossil-fuel-derived energy does mean that what might otherwise be a relatively closed system of cycling CO2 from the atmosphere through plants and then animals and back to the atmosphere, does become net positive with respect to CO2 emissions.
But if one were able to maintain the large numbers of domesticated/food animals without using fossil fuels to power the farming systems, and didn’t make any further land use changes, then there would be no net positive CO2 emissions (there might still be net CH4 emissions, but presumably every CH4 would be released at the expense of CO2, since there’s nowhere else for the carbon to come from).
There is a very relevant point that respiration (“breathing”) is inherently net neutral and it’s only the added fossil fuel energy inputs that make a “naturally” net-neutral process “unnaturally” net-positive. So large numbers of humans needn’t necessarily be a net-burden on the planets resources….in fact the long term future of mankind requires that we deal with this issue of developing societies based on sustainable agricultural and industrial practices powered by renewable energy sources…
..in such a system of societies, humans (and their animals) could breathe to their hearts content knowing that their respiration makes no net contribution to CO2 emissions….an interesting question, though is what sort of a world human population might be supportable within net-carbon-neutral societies….
…but that’s not a question that relates to General Circulation Models I suspect!
OK, Hank, tell me how to answer your request without posting another reply!
:-P
The threads I have answered have fallen under three cases:
1) I can at least answer this one. The majority.
2) I’ve been asked a question. A large fraction.
3) Smartarsery. After a while when the brain cells of the poster seem not to be firing, this one may kick the thinking into gear. At least to the extent of returning the favour.
PS I would point you back to #211 for perusal. You post on a #3 tenant too.
PPS Does a thread only take one post every five minutes? No? Then how is this posting stopping others?
Stefano (#246) — I appreciate the warning that my remarks might be twisted to make a climate skeptic’s day.
But the point was: It is wrong to suggest that real-world development-related policy decisions are routinely based on very precise predictions of future problems, and that we cannot act on climate change because the models do not meet these alleged standards.
And this is not to defensively whine that climate projections are no worse than many predictions in other fields. On the contrary, global warming is a problem for which the world is rather well equipped to make informed policy, thanks to the IPCC reviewing the best available scientific knowledge, and thanks to ensembles of hindcasting-capable models constrained by (real-world!) physics.
The observation that experts sometimes make “best estimates” for hand-waving reasons clearly has nothing to do with e. g. the range and most likely value for climate sensitivity in the IPCC 4AR, where pains have been taken to work out the probabilities from independent lines of evidence.
It has been very eloquently pointed out in this thread why one can and should act on these probabilities (especially, #34 Garry S-J and #253 Bart). But sure, the outcome could lie towards the less bad end of the range. Should skeptics therefore say with Dirty Harry, “Go ahead, make my day”? Well — “Ask yourself: Do you feel lucky?”
Bart wrote:
You write “So what if you can say that the future will be a bit warmer and maybe a lot warmer?” If we take “the spread of possible future outcomes” in a business as usual scenario, then it’s fair to say that if it’s bad, it’s really bad, and if it’s good, it’s still pretty bad. …. “If you jump out of an airplane you need a crude parachute more than an accurate altimeter”. I commented on his speech on my blog (as did Michael Tobis on “init”).
Well, earlier I was criticized for comparing climate change to a simple textbook problem, like how much fuel is needed to reach the airstrip. It was said that the reality of climate is much more complex. However, you’re now comparing the future scenarios to an equally simple textbook problem, that of needing a parachute to slow my descent from a plane. You refer to a simple scenario to reinforce the view that the decision to act is simple and obvious. Now either this whole business is simple or it is complex. Or am I missing something? (That’s not rhetorical, really, what am I missing?)
It is this disconnect between the public message about the simple need to take action on climate change, and in contrast what is understood by academics/professionals in the field regarding the complexity of the problem, that could turn into a major headache. Going back to our plane analogy, say I ask you whether we have enough fuel to reach the airstrip, and you reply that based on your projections, yes we do (even though you have poor data available re. our heading and position and fuel consumption and there is a slow leak somewhere that you’ve had to parametrize). So we carry on flying and crash short of the runway. How do you think I will feel when I turn to you and say, “but you said we would make it?”, and you come back with a reply similar to what Mark said, “well, the best laid schemes of mice and men go oft astray”. How will I feel? What will I think of you?
The public isn’t hearing “we project a spread of scenarios”, what the public is hearing is a confident unequivocal assertion. And that is what I’ve realised I have to stop believing. Had the public message been accurate and properly representative from the beginning, then this mess of time wasting arguments between “skeptics” and the science community would not have occurred, methinks.
Sorry that’s a bit long, but that’s pretty much all I wanted to say.
Alexi Tekhassi writes:
It’s a converging series, not a diverging series. 20 W/m^2 of feedback is all you get from 4 W/m^2 of forcing.
Rod B writes:
Rod, CO2 from breathing comes from carbon which has been eaten, which is from the biosphere, not from fossil fuels.
The above, “Carbon Capturing Rock”, was published in MIT’s Technology Review. Any thoughts?
Stefano, if a system is sufficiently complicated, you cannot expect a model to be a crystal ball. In fact we do not need a crystal ball to see the effects of climate change. They are occurring even now, with loss of many species (e.g. frogs and other animals in the cloud forests of Central America) and threats to many others (polar bears, seals…). So, we know that there will be threats. What we do not know is how all those threats will manifest–which are credible and which are not.
We do not look to models to predict the future, but rather to elucidate the physics–and the physics tells us what we need to avoid, what we need to mitigate and what we may be able to safely accommodate. Right now, you are saying that because the models (in your opinion) are not reliable, you reject the conclusions of the overwhelming majority of climate scientists. Yet, the models do not establish risk. The risks is inherent when we make serious changes that affect the infrastructure of human civilization. Rather the models are essential in limiting risk. So you might want to think twice before adopting too sanguine an attitude.
CM wrote:
But the point was: It is wrong to suggest that real-world development-related policy decisions are routinely based on very precise predictions of future problems, and that we cannot act on climate change because the models do not meet these alleged standards.
Well you can act, but which of the range of scenarios should you focus on? Do you focus more on adaption, or more towards prevention? If you can’t give the policy-makers a clear target, then action will be based more on political leanings. The less precise your forecasts, the more they will use their gut instincts, and their innate political view. You have a range of scenarios? Well, some politicians lean left and feel the government is there to protect people. Some politicians lean right and feel the individual should be unencumbered by legislation. Some people are very cautious, while others are heavy risk takers. Sometimes one group does better than the other, and sometimes it is the reverse. Adaption or prevention? Does one believe that tomorrow new technology will come along? Or that no new technology is forthcoming and we must cut cut cut and conserve? This is why I commented, rather harshly to be sure, that these projections don’t have real world application, at least in the sense of actually specifying clearly to governments what action they should take. Some people take the view that we shouldn’t do anything at all, and it can be quite hard to argue convincingly that they are wrong.
Sorry to be off topic but isn’t this;
http://www.guardian.co.uk/environment/2008/nov/09/miniature-nuclear-reactors-los-alamos
a solution to our problems?
Alex Tekhasski,
If you double CO2 with no other changes, then radiative forcing increases by about 4 W/m^2.
But there will be other changes, due to the consequent temperature increase: increased water vapor, reduced snow and ice cover, etc. So in the real world, if you double CO2 the net radiative forcing increases by about 20 W/m^2. The “extra” 16 W/m^2 is therefore called “feedback.”
How hard is that to understand?
Not hard at all. Unless of course you work very hard deliberately to confuse the issue. Your departure will not be mourned.
[Response: Sorry to be pedantic, but the 20 W/m2 extra LW absorption you end up with is not a ‘radiative forcing’. The radiative forcing is defined as the initial TOA imbalance – as the planet reacts, that imbalance decreases (close to exponentially) until (at equilibrium) it is zero. However, that equilibrium state – given the changes in water vapour, clouds and increases in surface temperature happens to absorb more LW than you started with. – gavin]
Gavin, I am sorry, but you have to be more pedantic. The “equilibrium state” cannot absorb more LW since, by the definition of equilibrium, the net absorption is zero, and insolation (corrected for albedo) is still the same. You must mean something else.
[Response: No I do not. Consider the amount of LW coming from the surface which is partially absorbed by the atmosphere (if there was no absorption, there would be no greenhouse effect). An immediate increase in CO2 increases that absorption and creates a TOA radiative imbalance by the same amount (4 W/m2 for 2xCO2). As you equilibriate, the planet warms (reducing the TOA imbalance) and water vapour increases, increasing the amount of surface LW absorbed in the atmosphere, but not adding to the TOA imbalance (though it does slow the equilibration). By the time you get to the end, there is more LW from the surface absorbed in the atmosphere (~20 W/m2) while the TOA imbalance ~ 0. In the absence of SW feedbacks, the outgoing LW at the TOA is the same as before, but that LW is coming from higher in the atmosphere. – gavin]
So Gavin where are you trying to take the models now? Being that great improvement has been made, what are you working on now?
Also, where do you think climate is going to take us in the next 50 years or so based upon the best analysis of the trends? I am curious to hear directly from a reliable source what we may need to better work on in regards to slowing down very much, potentially, catastrophic consequences. When one conisders the combination of fossil fuels, deforestation, 6.6 billion people breathing, plat life limits, (in some cases increased adaptation of course) some bad energy policy decisions in light of sophisticated applications of data, math etc… what do you propose humanity might want to do, in order to reverse or atleast slow down current trends related to AGW in conjunction with natural processes?
We are so quick as scientists, non experts, the lay public, some ill informed undergrads, ad infinitum, to argue in this blog, however, you as a first hand expert modeling paleoclimate and modern climate trends and obviously with a handle on chemistry and physics, also have a vested interest in our planet and though you do the modeling for a living, I do not doubt it has helped you gain inisghts and opened up your eyes to the complexity and current to future detriments and potentialities we all face as humanity.
I pose this question to Gavin as I see him reply to a wide variety and large number of posts, but any moderators of this site, feel free to comment, as I read your backgrounds, published works and books, it has been both a joy and educational journey.
Stefano,(in general to your various posts) first of all no one can predict the future with absolute clarity, this is akin to the crystal ball mentioned by another poster, relying upon Nostradamous like predictions or looking to the constellations for truths in and of themselves. What is interesting, first of all is the rigors of science are so poorly misunderstood by most people, even the very educated, and completely put into God like perspective by the ignorant. If I were to tell you that the last bathroom stall is the cleanest of all stalls statistically, that might change people’s reactions, most going to the last stall, which would change the outcomesm would it not? The same can be said about how we do not know precisely how warm the globe will get in 25, 50, 100, or 150 years, dynamics do change; the 1990’s was the height of recent population explosion, and even though the global population is rising steadily, the incline has decreases a bit; China, India, japan have issues with pollution, overcrowding, exponential GDP growth or decline, respectively. We do know the warming since the industrial revolution has occured and that isn due atleast in part to human activity and we know that the planet cannot withstand continual additional CO2 to the atmosphere; the math used, the data collected, the training involved in doing thism is enormous. Some scientists disagree on the magnitude of the AGW threat, but the threat is very real; Pink Flamingos become pink, cheifly in Africa, by eating plankton in a toxic water body; in Arsenic filled lakes aquatic life thrives; some plants adapt to CO2 and grow beyond other plants; some die, release CO2, and more burning adds to this issue; breathing by itself is well tolerated by the planet, but add all the positve feedbacks and we soone realize even in light of negative feedbacks overwhelms the system and we see a slow, but positive heat increase, if it were faster we would be in trouble now and if it were slower perhaps we would miss the seriousness of the situation; but we live in the here and now and what are we to do now and the immediate future to slow down AGW trends for the not so, and even more distant future?
Mark makes a lot of solid points Alexi. I do suggest continued reading of the data, I provided some of best (and longest) data published that can be found anywhere on the internet. Even if Mark did (and I am not suggesting he did) make minor errors, he has been extremely accurate all through this thread. No scientist has a hold on all data, and only a few have a hold on all the concepts, and we all grow tired at times and forget. The point that Mark hits home on is simple: AGW is a reality and clear and present danger. No one here or anywhere offers an argument, logic or solid data to indicate otherwise, you should keep that in mind; Anthony Watts needs a lecture on galvanized steel, material chemistry, and thermal expansion:) I am glad, however, you are reading the sites I pasted, I suggest you get a hold of the Global Climate Systems book as well, if you read every word, look at all the diagrams and can do all the math and do not misunderstand any of it, well, that will really get you on your way; I have read it over three dozen times and it is an excellent reference for us to get old and forget at times how to state something.
Rod B didn’t you hear about the thousands of US soldiers wh did no get paid during their occupation of Ira, came home and either were still not paid at all or only minimally and were refused tuition reimbursemen for college? Also, the clinical setting in the military was so underfunded since Vietnam that many shell shocked (PTSD) and otherwise mentall ill or traumatized soldiers are not getting the professional help they need.
The underfunding for proper body armor, helmets and other supplies is also well documented and reported on in addition suits being brought against the military and government.
Now we certainly need the military in all its facets, and the war economy does fund many workers, however, not since WWII have we seen such a post war economic and baby boom in this country; also with the pull backs in the Korean action, at the Peking river, we more than sealed our fate, needing to pull out of a country we did know eneough about geographically and we were flanked much like many of our wars and occupations; WWII was our last real success.
Giving money to the top, trickle down theory has far too many failings to be still considered a viable socio-politcal-economic solution.
Stefano, #267 you are correct. Yet this is ABSOLUTELY 100% the same with any other legislation. The only way around this is
a) lie. Tell people we’re certain when we aren’t to get the politicians to do the right thing. This is WRONG. And no scientist who wants to keep their reputation intact will consider it
b) sack politicians and let the scientists decide. This is wrong too because this is a democracy. If the balance of all those leaning MPs is an action that isn’t sufficient then people will suffer but this will be at the hands of those MP’s who operated on dogma rather than reason.
Any why should all this overt and explicit uncertainty be a skeptic’s dream? The error in the temperature rise could be 5DegC +/- 6DegC and a *denialist* would be over the moon, saying “see, it could be COOLING”. Because they aren’t sceptical, they WANT it not to be warming and so forget the other side: it could be 11DegC warmer. Trout die in water warmer than what?
A true skeptic is HAPPY to see +/-6 error not because it proves one point but it proves that there is still a lot to learn. But that doesn’t make a *skeptic* think there is nothing wrong and nothing to do. It makes a *denialist* do it because they want to be able to do nothing or at least the same stuff as they did before. ‘cos change is scary. If you’re currently well off, a change is likely to make you less well off. And when it comes to THEIR wealth, the worst case scenario is ALWAYS the one trotted out (“You’re going to have us all living in the stone age!!!!” ring any bells, people?).
Alexi #258.
Make the sun hotter. What happens on Earth? Temperature goes up. Permanently (unless the sun gets cooler, earth moves away, etc).
It FORCES a change in temperature on climatological timescales.
It is a climatological FORCING.
Pump CO2 up there? Warmer because the residence time is decades to millenia, a climatologically forced change.
FORCING.
In both cases the system CANNOT decide to do otherwise. The climate is forced to change in a simple way. It gets hotter if you increase, cooler if you decrease.
Forcing.
Now, pump water vapour into the air. What happens? It rains out. But that doesn’t take a climatological period to happen. So there is no forcing of the climate to change, the process itself is self-regulating on a climatological scale. NOT a forcing.
But, lets look at the sun getting hotter again. Say it gets 1degree hotter. A hotter atmosphere will hold more water, so any water that evaporates will be able to stay there (if it is small enough change to fit in the warmer air’s ability to hold it). But this causes it to be a little warmer again. Let’s say 1/2 a degree for each degree of change. So it makes it WARMER than just the one change you put in with the sun. It feeds back more warming than the simple system. A FEEDBACK.
Now, this extra water warms the air by 1/2 a degree. Doesn’t change the sun’s output. But this warmer air can hold another bit of water vapour. And so another 1/4 degree is added to the warming of the atmosphere. But that holds more water… etc. So it is a POSITIVE FEEDBACK (remember, we already have seen that absent sun warming, there’s no change in water content so water is not a forcing). So what is the eventual change? A sum of the infinite series 1/2+1/4+1/8+…1/inf. Which doesn’t total infinity, but +1.
So the Sun warmed the earth by its climatlologial FORCING 1 degree. The water vapour FEEDBACK increased the effect of the sun’s change to 2 degrees. The sun didn’t get hotter, but the positive feedback of water vapour in the atmosphere doubled it.
So now do you get it?
Probably not, but others not deliberately trying to “not get it” will.
Stefano (#262, 267), I can understand your irritation with people who oversimplify the science and downplay uncertainties in an unsound way. Their motives can be pure — effective, pedagogic communication of a serious public issue — and the balance is hard to strike. But it can boomerang badly if people conclude — wrongly — that the quality of the PR reflects on the quality of the underlying science. Still, the science is out there for skeptics to access if they are interested in knowledge, not point-scoring. The last IPPC WG1 report is nearly a thousand freely downloadable pages with spreads, uncertainties, and qualifications.
In any case, science does not determine policy. Politicians and the public legitimately differ over how to deal with the facts in the light of differing ideologies, values, and attitudes to risk. Even precise and unequivocal knowledge of future temperatures, if available, would not by itself dictate a precise and unequivocal course of action to governments — not even on basic strategic choices of prevention or adaptation. Narrowing down the uncertainties might help cut through excuses for inaction, but I think you are granting those excuses far more than the present state of knowledge warrants, too.
Stefano writes:
Yeah, the oil people, the coal people, the automobile people…
You should add a definition of “parameterization.” You use the term a lot but do not explain it.
Re posts #275 et seq.,
The willful ignorance–whether motivated by (short-term) self-interest, cupidity, or sheer crankery can be quite breathtaking (not to mention provocative.)
Reactions to the NSIDC “guest spot” on Watt’s Up? included, I swear to God, the argument that though alternate explanations for observed warming might lack evidentiary support, there could still exist evidence for “unspecified causes!” (“We don’t know what it is, but it is fully supported by the evidence!?”)
Worse (or better?) this was received by several posters as a telling point. . . to me, sheerest psychopathology. Overall, the thread was characterized by a really extreme refusal to confront facts–but I’ve seen this in online debates before, as I suppose many of us have; you point out several lines of well-accepted research only to be told, once again, “there is no evidence.” Well–no evidence that the denialist likes. That’s why there is a discernible fashion to dismiss all surface records in favor of the UAH satellite data. (One debater told me it was “the only true way to measure the temperature.” I told him I live rather closer to sea level than to the tropopause.)
Stefano wrote: “Well you can act, but which of the range of scenarios should you focus on? Do you focus more on adaption, or more towards prevention?”
Actually, if you studied risk analysis, you would already know the answers to your questions. We are often asked to make policy or design products in the face of significant uncertainties. The constraints on the solution are engineering constraints: they have to work and they have to be economical.
If adaptation is the most effective and economical strategy, we adapt. If avoidance is the most effective and economical strategy, that’s our option. If our risk estimate cannot be bounded by the models (and here you have to take a “worst case” or WC at 90% confidence), then you have to adopt a two-pronged strategy: Do what you can to avoid the threat or to mitigate its consequences with reasonable effort and work to improve your models. Under no circumstances can you ignore a threat whose risk cannot be bounded. That’s where we are with climate.
The FAQ entitled “Are the models complete? That is, do they contain all the processes we know about?” needs to be either rectified or clarified. It does not mention large scale processes which are (1) under active study, (2) might explain 20th century warming and (3) are not included in the models. Indirect solar forcing and abrupt changes are two examples among many. If it be argued that we do not “know about” these processes enough to include them in the models then that should be explained. The distinction is that between computable knowledge and non-computable knowledge. The models are confined to the former, but climate science is presently awash with the latter. These are processes that are being investigated that we do not understand well enough to write computable equations for. There are many hypotheses and large scale change phenomena under investigation which are not reflected in the models. The models and the science are not co-extensive, for the science is much larger. The FAQ should make this clear.
David, check the definition — you can do this online; it’s clear. Try
http://www.google.com/search?q=define%3Aparameterization
You don’t need more than a pointer to a dictionary except when a field has its own peculiar and different definition for commonly used words.
Just as your “climatechangedebate” site uses familiar words undefined.
Theory says that the sun over the last 55 million years has gotten hotter. Despite the fact that the Earth hasn’t moved enough farther away to offset this, the earth is now cooler. Must be that pesky “etc”.
Ok, the largest reason is probably less water vapor in the air now. What? That’s a feedback, and I can’t count it? Then I might say it’s due to less carbon dioxide in the air, but that’s at least partially a feedback, too. Well, then maybe it’s continental drift, since at least I don’t see any way that could be a feedback.
This climate stuff is sure complicated, especially the “etc” part.
[Response: Since water vapour is largely a function of the planetary temperature it doesn’t drive that temperature in any real sense. Solutions to the ‘faint young sun’ paradox almost always involve the longer term changes in CO2 and CH4. But the relevance of this to the last century where we have a much better understanding of the relevant terms is very low. Climate is indeed complicated, and you don’t need to resort to a ‘gotcha’ style of blog commenting to have that acknowledged. – gavin]
the moeny denialists make will not matter if we keep going at the rate we are going; then when they concede they want to do dangerous things; carbon capture in the ground… forget about reducing actual emissions and alternative energy sources, let us just bury everything… sickening really. Also reading one paragraph of a climate report does not constitute reading and learning.
A nagging concern I have is that fossil fuels are effectively permanent CO2 draw down. I can’t see how any sizable part of these reserves would have naturally been reintroduced back in to the atmosphere.
We have now effectively put back a huge amount of carbon that would not have found its way back over the inter-glacial cycles. This is completely bucking the natural progression.
This probably means that we are in for big time warming no matter what we do.
On top of the GW effect the small addition of heat energy from using these fossil fuels probably stacks the equilibrium even more, although it’s only is a fraction of the equation.
Mark #275 “It makes a *denialist* do it because they want to be able to do nothing or at least the same stuff as they did before.”
There are many legit positions (pro and con) to take on any one of the concerns brought up by climate change. To take the most ridiculous comments out there and paint a stereotype is interesting and fun, but intellectually lazy.
And everyone (even the most responsible) wants to ‘do the same stuff they did before’ – do they not? If I were to take the position that mitigation money would be better spent elsewhere, I may not be totally correct, but it sure doesn’t make me a total ephing idiot. It doesn’t make me irresponsible. It doesn’t make me selfish, ignorant, or bought.
It may just mean my priorities are ever so slightly different than yours.
David Wojick, Maybe we should posit that warming could be caused by Keebler elves working overtime on their bake ovens in their hollow tree as well? ;-) If you can’t model how it works, it ain’t physics. If it ain’t physics, it doesn’t belong in the models. If it’s needed in the models, then the models would fail to reproduce observed trends. Since the models do reproduce trends pretty well, I don’t thinki we should be terribly concerned with missing physics.
Occams razor: I will not multiply causes.
[Response: … unnecessarily! If there are identified physics that the models are missing, people will endeavour to insert it. The problem is when the ‘physics’ is some uncertain correlation in noisy data. If Wojick is thinking about GCR-cloud connections, this is being done (it requires a full aerosol model including all the different modes of formation, accumulation, growth and impacts on clouds), but all estimates so far are that changes in ionisation makes only a negligible difference. This is of course completely independent of critiques of the statistical work put forward by some, and the plain fact that with no trends in GCR, it can’t be related to recent warming. – gavin]
What do you do when your model shows results that don’t match real world measurements, ie. the cooling of the planet rather than the predicted heating over the past 10 years?
Do you assume that the model is wrong?
Do you assume that the real world data are wrong and that the model is correct?
[Response: What the models show is discussed here. RIght now there is no clear discrepancy. If that changes then there are three things that would need to be examined – the models, the data, and how the comparison is being made (i.e. the relevance of the particular model experiment, and what variables are actually being compared). I can think of dozens of cases where the each of those factors ended up being at fault – and so presupposing that one must be the cause of all mis-matches is foolish. You just have to see. – gavin]
Michael, reread again. And don’t be so one sided: someone who is skeptical will look at 5+/-6 and go “That’s a big error bar”.
Only a denialist will go “See! It could be cooling!!!”.
Why?
A skeptic doesn’t believe the anti side either. A denialist wants any excuse to justify their presuppostion.
If you feel this is an unworthy stereotype, how about YOU explaining why that happens? NOTE: This HAS HAPPENED BEFORE.
Greg #284
“Theory says that the sun over the last 55 million years has gotten hotter. Despite the fact that the Earth hasn’t moved enough farther away to offset this, the earth is now cooler. Must be that pesky “etc”.”
Wow.
The denialist camp keep coming up with new ones. Well, we know it was warmer back when the sun was cooler. But higher CO2. So the “It used to be 400ppm and things were a-ok!!” is thereby nullified, barring any information from you.
And please tell me how much cooler it is when the peak was 2005 and last year was second..?
Now, how MUCH warmer is the sun over, say, the last 150 years? Is that enough? You just seem to want to say “The sun got hotter and that explains it”.
Well it doesn’t.
Please tell us how much hotter the sun got and how much that should heat the earth.
Dare ya.
PS Michael, see how someone is willing to take as gospel any fragment that may support the “It’s all a scam!” denialist dogma. Please explain why else that moonbat said what they did.
Ta.
re 287: “And everyone (even the most responsible) wants to ‘do the same stuff they did before’ – do they not? If I were to take the position that mitigation money would be better spent elsewhere, I may not be totally correct, but it sure doesn’t make me a total ephing idiot. It doesn’t make me irresponsible. It doesn’t make me selfish, ignorant, or bought.
It may just mean my priorities are ever so slightly different than yours.”
It depends upon the consideration you give to actual evidence. The context of the thread for #275 is consideration of those who *refuse* to consider it in a reasonably objective manner, of whom there are sadly many examples.
Stefano (262): The details of the science are complex, but the (policy-relevant) main thrust is relatively simple in comparison. Based on this main thrust the decision to act should indeed be simple and obvious. In my view there’s an inverse relationship between the degree of scientific detail and its policy relevance.
You seem to claim that the public message should have paid more attention to the details and the uncertainties; I think that the media (and many scientists when engaging in public communication) actually pay too much attention to those, at the cost of laying out the big picture of what we know. Moreover, the issue is more usefully framed in terms of risk rather than in terms of uncertainty. These two things could have gone a long way in preventing the “time wasting arguments between “skeptics” and the science community”. Canadian science writer Lydia Dotto has some good thoughts on this: http://www.thegreatwarming.com/stormwarning.html. I discussed the role of the media on my blog, http://ourchangingclimate.wordpress.com/2008/05/21/scientific-debate-and-the-media/.
Your plane analogy argues in favor of the precautionary principle: Better be safe than sorry when we risk missing the runway. I agree, both on your analogy and on the real-world example of dealing with the risk of dangerous climate change.
Ray Ladbury (288) Says:
10 November 2008 at 2:21 PM
“David Wojick, Maybe we should posit that warming could be caused by Keebler elves working overtime on their bake ovens in their hollow tree as well? If you can’t model how it works, it ain’t physics. If it ain’t physics, it doesn’t belong in the models. If it’s needed in the models, then the models would fail to reproduce observed trends.”
Both your claims are false, Ray. For example, we know that abrupt events occur, so they are physics. They are large enough to explain the observed warming. But we do not know the mechanism so we can’t model them. The fact that the models can be made to reproduce historical trends, to the extent they can which is not well, merely shows that the hypotheses embedded in the models are physically capable of explaining the trends, not that they do explain them. It is also necessary to rule out the competing hypotheses, and this has not been done. We are not talking about elves here, we are talking about phenomena and hypotheses that are being actively investigated within climate science.
David Wojick wrote: “There are many hypotheses and large scale change phenomena under investigation which are not reflected in the models.”
Such as, specifically, what?
Keep in mind that anthropogenic global warming is not a “hypothesis”. It is an empirically observed fact: human activities, principally the burning of fossil fuels, are in fact releasing large quantities of CO2 into the atmosphere. That anthropogenic increase of atmospheric CO2 is in fact causing the Earth system to retain more of the Sun’s heat. The Earth system is in fact getting warmer as a result. These are facts, not hypotheses. They are not derived from models. They are derived from actual empirical observations.
Whatever other unspecified “many hypotheses and large scale change phenomena” you may wish to “investigate” — or speculate about or hand-wave at — you have to deal with those facts.
What software programs are usually used in developing climate change models?
Have any of this models taken data from the 1900 and come up with the weather we are having today?
David you are in grave error. We know quite well most of the mechanisms.
It takes a long time for industry, organizations, institutions to change due to the vast complexity, but AGW and green house gases and their roles are known.
#292 ‘It depends upon the consideration you give to actual evidence. The context of the thread for #275 is consideration of those who *refuse* to consider it in a reasonably objective manner, of whom there are sadly many examples.’
Unfortunately Kevin, those who *refuse* are the group I am talking about. The vast majority – those who are voting on policy issues, talking to friends, arguing with thier kids’ elementary school teachers – do not grasp the science behind GCM’s, for instance. Most have to make life decisions based on non-scientific reasons.
There is a good reason we elect politicions and not scientists.
Green house gases do militate climate trends, not in dispute at all.