Posted by: Barry Bickmore | August 16, 2013

Dear Rich Trzupek, Here’s Why the Heartland Institute Creeps Us Out



Trzupek was so incensed because it was obvious to him that,















Dear Rich,










































MS. DONLEY:  An infant cannot leave a room.




THE CHAIRMAN:  That’s a bit of a misstatement, Father.






  1. All cults freak me out.

  2. Brilliant!

    This situation has got completely out of hand, and all because a small but powerful lobby hate the solution so much, that they’d rather deny the problem exists and try to control reality than acknowledge responsibility and act accordingly.

    Unfortunately, in the pursuit of trying to cover up the ‘uncoverupable’ reality, and as an admission of failure is an impossibility, those that dug themselves into the denial hole have dug so deep that they are forced to keep digging until the sides collapse. Perhaps then can we make progress as someone sweeps the remains into the bin.

    Some of the most egregious things in this whole charade of trying to discredit climate scientists and science in the futile attempt to find a means of justifying inaction, are:
    Damage to government by corrupting politics,
    Damage to society by confusing and misinforming the public,
    Politicization, leading to a greatly divided society along partisan lines,
    Coercion of mass media
    Corruption of education and the perception of scientific integrity.
    Unaffordable delays in tackling the problem.
    Continued degradation of the planet.

    Climate change and its mitigation is a global existential problem, and requires massive multi-partisan effort to try to get the genie back in the bottle, and we are well overdue. This is the greatest task that Humanity faces for this century and beyond.

    Those continuing to actively obstruct progress for short-term profit in implementing solutions are betraying younger and future generations the chance to enjoy a quality of life that we had, and this is a crime against humanity, if not life itself.

    I suppose we could always take Chairman Charles M. Harper’s advice to leave the planet if we don’t want to be exposed to the effects of climate change, but there’s an obvious problem with that.

  3. That was a brutal take down, richly deserved, of course, but you almost had me rooting for your victim as you flayed his thick skin away.


  4. Mann is/was putting forth a rather obvious strawman argument. It’s a dishonest tactic from a desperate man.

    • I’m not sure I understand how you’re using the term “straw man”. He was criticizing the quality of others’ arguments, not attributing any particular argument to them. It’s difficult to engage in straw man argumentation without creating a straw man.

      And why would he be desperate? Because some rubes who couldn’t do a principal components analysis to save their lives think he did something sneaky… to generate almost the exact same answer he would have gotten using other proxies and statistical methods? Please.

  5. Nice work, Barry. I think you nailed the problem with all supposed ‘scepticism’ regarding the consensus view that anthropogenic climate disruption is happening, significant, bad, and worth trying to fix:

    “And even if we know the theory isn’t quite right… we hang onto it until someone comes up with a “better” theory–one that explains more data, or at least explains the same data in a more simple and elegant manner”

    As Michael Mann has himself said (and I paraphrase): Without anthropogenic CO2 as the main driver of ongoing change (due to the radiative energy imbalance it is causing) it is impossible to explain the totality of post-industrial warming. Ipso facto, rejecting CO2 as the primary driver of change therefore explains less of the data not more of it.

  6. Trzupek writes: “I’ve interacted with a lot of people on the skeptical side of the aisle and they are – without exception – good, decent, sincere and well-meaning folks. That goes in particular for the folks at Heartland. People like Joe and Diane Bast, James Taylor, Jay Lehr, and Jim Lakely are the sorts of people you’d like to have as your neighbors.” Why, when I read this, am I reminded of some of those old-timey postcard from the South, where in the foreground you see a group of perfectly normal, perfectly nice looking people — friends and neighbors, no doubt — all smiling happily into the camera, while in the background you see a black man’s corpse hanging from a tree. The “nice people” of the Heartland Institute would gladly lynch Michael Mann, James Hansen — any reputable climate scientist, for that matter — if they thought doing so would protect fossil fuel company profits. Yessiryee, jes good country people!

    • One wonders which “good, decent, sincere and well-meaning folks” come up with a campaign that links the scientific consensus on global warming to mass murderers…

      It makes me doubt the ability to Trzupek to identify “good, decent, sincere and well-meaning folks”.

  7. > I can teach you how to code it in MATLAB (and maybe even Excel)

    Barry, that’s cruel… Microsoft is a nice “person” really, the kind you would like to have as a neighbour 😉

  8. “Even if the physics represented by the models were absolutely perfect, plugging those into a 3D grid where the boxes are kilometers across would lead inevitably to errors, especially in the short term. …the difference between short-term chaos and long-term predictability”

    Some insight into what might seem like a contradiction above.

    Briefly.. In the short run, we might see the status quo (eg, small rises and falls.. like weather) with little ability to predict at any point in time if the temp will be higher or lower than the starting temp value. Meanwhile, in the long run, we are almost certain to see something clearly above the starting temp value (even though that precise value will still be unpredictable and mostly chaotic).

    Long version:

    Both the short and the long term are unpredictable in their range of oscillations if bounded; however, the long term oscillations weave around a fairly predictable rising moving average. So the short term presents, relative to the starting temp, no clear idea of a rise or a drop at a given point in time. In contrast, the long term shows that almost all cases consist of a rise from current temps since even the low range of possible temp values would be higher than the starting temperature thanks to the rising “average”.

    For example, the best science might predict and measure an oscillation spread of 1 C, while the long term prediction might be of on average 3 C gain. This would mean:

    — Short term: We might see a rise of +0.5 C down to a drop of -0.5 C. The average is near 0 (since we just started) and we have as much of a chance of going up as going down.
    — Long term: We might see a rise of +3.5 C down to a rise of +2.5 C. The average is 3C.

    As with short term, the unpredictability range of the long term is also 1C, but it’s much more predictable to expect a rise than a fall, when we compare to the starting temp. In fact, we expect a rise of at least 2 C in the long term (not too far from 100% certainty) more than we would expect to see any drop (or any rise, each at near 50%) in the short term case.

    Thus, there is a lot of predictability in the long term vs. in the short run, not in narrowing the bounds of error (they actually rise in the real modeling and is not depicted above), but in increasing greatly the odds of seeing a significant rise rather than a drop or even merely a small gain, when comparing to the starting temp.

    • All Finite Differential Equation solutions and every numerical solution to an integral are approximations based on taking a finite difference in what is modelled as a continuum of infinitesimals.

      But modelling the atmosphere as a continuous fluid is itself an approximation.

      Therefore the claims about the spacial resolution of models is weaselese of the highest order. EVERY physical law, EVERY statement EVER made by humans are, by that standard wrong.

      And when you define a word that widely, it ceases to have any meaning at all.

      Indeed a Single Column Model is enough to get the approximate outcome that we have seen.

      Hell, the observational network produces closely enough the same result if you pick stations 1500km apart. The weather is that homogenous laterally.

      THAT is how wrong the “Oh, your grid points are kilometers across!” is.

      • Hi Wow,

        I originally brought this topic up while discussing how surface temperature can vary chaotically in the short term because of changes in ocean circulation that are hard to predict. Making the grid smaller and knowing initial conditions more precisely would, indeed, make our El Niño forecasts more reliable. A single column model isn’t going to capture that kind of thing.

        Do you disagree with this?

        • It wouldn’t change the CO2e sensitivity much, though.

          As far as policy decisions go, we can’t go on “Lets hope we get El Ninos” (I forget which one does the cooling, it’s all greek to me…). They cycle for a reason.

          SCMs give the right ballpark CO2e sensitivity and the right imbalanced warming trend.

          When it comes to “Do we stop burning fossil fuels”, they were right enough to come to a policy decision.

          • I agree. Climate sensitivity is an “equilibrium” problem, which is a lot simpler to solve, and you don’t need to know the exact pathway for getting from one equilibrium state to another. Transient response (i.e., short-term changes in the system out of equilibrium) is a “kinetics” problem, and you DO need to know the exact pathways to predict that well. And while the speed of the change matters, whether we go up several degrees in 100 years or 150 years probably won’t make that much difference. In geological terms, either one is the blink of an eye.

            • Well, the kinetic solution is not as hard either, to give the transient response time. Harder, but still pretty decided.

              What doesn’t make a case, though, is transient response helps use ignore the climate change and sensitivity of the SCM.

              If the transient times are short, then the SCM is very close to an accurate measure of what we will see in climate change. So short transient times mean the SCM is accurate.

              Long transient times mean that the SCM is going to be wrong on the human timescale. HOWEVER, if the transient timescale is long, then given we have seen 0.8C warming in this short period (less than 60 years), then this proves that we’re going to see much much MUCH more warming.

              In the latter case, not only do we HAVE to stop IMMEDIATELY our additions to the problems, since each addition will be highly multiplied in the long term, we have to spend massive amounts of energy and effort removing and sequestering (and such sequestering will HAVE to be in addition to a zero emission scheme).

              The SCM being accurate is the better result for those who wish to avoid doing anything about the climate.

              And that means short response times.

            • Wow, I agree, but we can’t (for now) do much about the fact climate transients exist that might last for a while (I am working on a magic wand 😉 ). Take that argument and dumb it down a little if necessary but use it. It might help convince a few skeptics to do risk management a little more carefully.

      • >> EVERY physical law, EVERY statement EVER made by humans are, by that standard wrong.

        Yes, and this isn’t a worthless statement because it implies a different understanding of your tools.

        If you see them as models, you are naturally alert that you might be hitting a limitation in any given scenario. It also allows you to separate logical steps from modeling steps when considering their accuracy, and this is important when reviewing why you aren’t getting some expected or sensible answer.

        If you believe they are laws, you will not understand how a given model could possibly be unfit to address a particular problem and can get hung up asking the wrong question when the solution does not make sense. You might question data or math for far too long when you should perhaps be identifying assumptions of the model before wasting all of that time.

        You have greater insight to a problem if you call a cow a cow. Physical laws are approximations and assuming otherwise will impede your problem solving and troubleshooting.

        I am making a big deal of this because of my experiences in engineering. The more your problem domain deals in approximations, the more important this can be, I suspect.

        One example of a mental trap is that you can start to think the physical formulas imply something about the materials. That can lead you astray into wasting time whenever it is not true.

        People are imperfect and use lots of models without knowing their ins and outs and the ins and outs of high level math. When you get into a problem, you will have to waste time trying to better understand something. This is where not calling a model a model can cause you to waste a lot of time and get very frustrated.

        • And I know that you mean “wrong” as in “the earth is a sphere” wrong, not “The earth is flat” wrong (h/t to Arthur C Clark there).

          However, the import is that this dude and the deniers are using “the models are wrong” in the sense of “the earth is flat” wrong.

          YOU know it, I know it. But the deniers aren’t playing to the crowd any more, they’re playing to themselves, desperate to shore up the idea against any threat to have it changed.

          Lets stop knocking politely on the door. Lets knock the effing walls down. We can help them rebuild it later.

          • Everyone has patience limits. When I take time trying to explain something, I am usually learning in that conversation and I think I have a shot at winning over an honest skeptic. If I am wrong (ie, when I lose patience), I move on. Simple as that. Everyone has their style and reaches a different audience. Sometimes it really isn’t worth it for me, but sometimes it is. I can leave (with some trouble perhaps but) without ceding a point I still believe in. And I don’t have to defend the science perfectly. I ask if they have read a paper they want to discuss or I try to read their own ideas and critique accordingly. Most people denying the science don’t have a plausible alternative. It’s easier to shoot those down than it is for them to shoot down the actual science. I’m willing to end the game up by a few points. If they are honest, they know they are further away from closing the deal. If they are deniers, they very likely lost some points in the eyes of spectators if they really weren’t playing straight and making sense. If you can’t yield on a wrong point, you will be the one losing points in front of innocent bystanders, so that is why I try to be honest about model approximations. It really helps when used properly. It doesn’t help to keep calling a cow a goat when the masks have come off. [Admittedly, that mask usually doesn’t come off unless the other person has something of a sophisticated understanding.] Remember, if the other person is honest and is taking the time to try and follow an argument, they will appreciate honesty back. They may be smart enough to identify the cow in your logic and mock you for calling it a goat. As for many people just wanting to win in their denialism, it can be worth it to win 1 in 4 and tie or end up slightly ahead in the other 3. Anyway, my personality manages things this way. I tend to see a skeptical “me” on the other side of the argument, so I obviously can have a little patience to help my other self. I usually bite on a theory I am biased against only if I can understand it. I won’t be convinced more from someone being loud. You can’t wow me with a club, Wow. Maybe some people react well that way, but I don’t. I’m playing to my experiences and “expertise”. Whatever gave you a different idea about me, perhaps you will quote me.

      • >> But modelling the atmosphere as a continuous fluid is itself an approximation.

        Now, imagine how difficult it can get for you if you assume that approximation is a part of nature itself when solving a certain type of problem you are used to solving that way but which in this case will not be able to be solved until you test for the assumptions and attempt a quantum mechanics approach?

        If the problem is complex, you can waste much time to look everywhere at all sorts of data and question the integrity of everything except perhaps to make a few estimates or zone in on some data to test whether you should be using continuous fluid equations.

        We can follow logic in our minds from many different axiomatic starting points. If you set as axioms things that are not, you will come to doubt lots of the wrong things. Eg, if only a, b, or c can enter a room at one time and you wrongly believe to be true that a has entered, you will never consider the implications that b and c might be in the room or a not in it. For a complex problem, this sort of trip up can lead to a lot of unnecessary hair pulling.

        As always, it’s when you are exploring the gray areas where problems arise and you get stumped. While research scientists accustomed to modeling in different ways might be used to exploring gray areas, others (including many working on engineering problems) can easily do most of their work in safe environment solving many specific problems with canned solutions, and so never be able to solve some of the interesting “gray area” opportunities they get.

        And, really, if you don’t see this point, you may even bail out of a potential interesting career in science or other similar discipline. Lay people are more likely to miss this point, and part of this website’s goal is to address this task of bringing the science to lay people in a convincing fashion. You’ll need to be honest/precise about your tools to make them believable and lose “their” mysticism/misbehavior. In fact, I’m sure many a great paradox are based on the failure of most people to identify fundamental implicit assumptions.

        • You need to remember that these are grey areas.

          I.e. the basic shape is the black, the bits it is not is the white and that the grey area is the bit in between. The grey bit doesn’t define the situation better. It defines the uncertainty better.

          And we go with uncertainty every day.

          But when it comes to someone else paying the price or us paying it, there’s a hell of a lot of effort put into concentrating on the grey areas to avoid looking at the black and white parts.

  9. No matter your stance, unless you’re on one or other of the extreme ends AND ADMIT SO, then you can ALWAYS claim “there are extremes of either side”.

    Claims of this are either pointless or disingenuous, similar to the False Equivalency fallacy.

    Unless the activities of these extremes are being assessed and proven, the nod toward them is of no value whatsoever.

    • Wow, the point of the “nod” was that Trzupek was complaining about how extreme some environmentalists can get, and since there are always extremists regarding every issue, I signaled that I don’t see any point to defending them. I once saw a Nat. Geo. spread, for instance, on some wacko who wants us all to be riding sailboats around the world, and doing all kinds of things that would entail drastically reducing the population. Since I don’t favor killing off billions of people, and I think the vast majority agrees with me, I think of this guy as an “extremist,” and feel no compulsion to defend his views. I have better things to do.

      • Sometimes, though, the nod is no different from the enhanced interrogation technique where the intent isn’t really to get you to agree, it’s to get you talking.

        You then salami off the differences until you get the answer you want.

        And therefore there is a risk to giving a nod to someone who is not an honest broker. Worse, you accord the dishonest broker the camouflage of respectability (he can retreat or leave as implied that he himself is honest, incorrectly).

        So in a cost/benefit analysis, we have a cost. What is the benefit?

        You won’t be accorded any respect for giving the nod, you’re just going to be asked to give yet more nods.

        Your concession will not be acknowledged with a concession on their behalf. Their intent is NOT to find a consensus position, it’s to disprove yours in absence of being able to prove theirs.

        Your concession will not be remembered as indication that you have a valid opinion if that opinion does not shift to one they want you to hold.

        So there really isn’t any benefit to giving the nod. They sure as hell won’t give a nod back. The best you’ll get is a head-down rushing past as they whip the goalposts to a new location and a bluff “What? I was here all along!” faux innocence.

        Your nod needs context. The context is

        a) Where you stand on that spectrum
        b) Where you believe they stand on that spectrum

        Without that, you’re just complaining about strawmen at best.

        I like to tell people to consider a triangle of opinions.

        For every single one sitting on the extreme apex on the triangle, there are “two extremes” with other people standing on them.

        Without context, how is the assertion “There are idiots on the extremes of both sides” not plausibly described as being your extreme view on that triangle?

        False equivalence is also inevitable without context. If one side has a priest claiming a fatwah and the other side has New Atheists saying that religion is dangerous, there’s no really equivalence in the two extremes. But they are about the same “distance” in the theist/atheist spectrum, aren’t they?

        I understand that your intent is to give ground to reach the middle ground you are both at least equally unhappy about.

        The time for that passed 20-30 years ago. It’s far too late for someone to claim they’re unclear of the picture. Every line has been clear as day.

  10. Barry, I see you’re keeping the faith. Well, at least you’re consistent. Good luck–you’re going to need it. I don’t ever expect you to change your mind on the subject, despite the model mean to be below 2% confidence interval. That’s the realm of Santa Claus and tooth fairies and phrenology (go look it up). Some advice: the longer you hold on, the worse its going to be for your reputation. I’m curious, would you even be having this conversation if the world had warmed exactly as the models had predicted? Naw. Try being a doctor, where we are faced often with the very real cold hard truth of faulty predictions on a much shorter timescale. Cocky doctors don’t last long. But evidently cocky climate scientists do (well, at least for another ten years).

    • Hi Scott,

      So, if I understand you correctly, you’re saying that if models predict something should happen only 2% of the time, that means it should NEVER happen? As we found in our previous conversations, statistics isn’t your forte, my friend.

      • Barry, the only thing worse than being wrong is being irrelevant, which is what AGW is becoming. Question: at what point are you willing to say those three precious but oh so hard words: “I was wrong”? How many more years? Not that it matters, of course. The scoffers are compounding daily. AGW will become another blip in history that we’ll all look back and say, “what we’re they thinking?” You and WOW are doing your part holding up the scheme and there’s definitely something to be said about standing up for what you believe in. Keep at it Barry. It’s only going to get a lot tougher.

        • Hi Scott,

          Wow and I both brought up essentially the same point about what a 95% confidence interval means in this case. Specifically, in the simulations situations like the present trend only happen about 2% of the time. That means they sometimes happen, so why would that be some kind of deal-breaker? I don’t think you have an answer for this.

          Anyway, with respect to your other question, I think someone would have to show me that the estimates of equilibrium climate sensitivity based on paleo-proxy data are way off. I suppose that could happen–I just don’t consider it likely, given how many different ways we get about the same answer. If the equilibrium sensitivity estimates are about right, and the GCMs overestimate warming trends, then one or both of two things is probably happening.

          1. The models don’t get ocean circulation exactly right. We already know this is true, to some extent. If this is the main culprit, we can expect to reach the same point a bit more slowly than predicted.

          2. The models don’t have the effects of short-term forcings like aerosols exactly right. We already know this is a big uncertainty in the models, so this wouldn’t be a surprise, either. Once again, if this is the case, we would simply reach the same point a bit more slowly as we taper off fossil fuel use.

          • Ok, Barry, last comment. If I asked you ten years ago how much change you would get from doubling co2 what would you have said? What would Gavin or Phil or Mike said or the rest of the experts? 3c? 4c? Definitely not what we are currently getting. My point is, why should any of us trust you for laughing guys like Lindzen and spencer off the stage when after ten years they’re closer to observations than any of the orthodoxy. Can we all not just agree that maybe sensitivity is not as great as everyone once thought?. Humility goes a long way. Some gain it naturally, others have to confront it like the ground after falling off the cliff. Sometimes you can get to the right answer using the wrong process, but you can never get the wrong answer using the right process.

            • Are you saying Spencer is using the right process? Have you read Barry’s analysis of any of Spencer’s works? Can you explain to us how Spencer could possibly have been using the right process?

              In the time range of a decade to two, the temperature can do just about anything. Look at that BEST link from earlier (“summary-of-findings”). Short term natural variability dominates the small CO2 contribution.

              Again. Short term natural variability dominates the small CO2 contribution. [I feel like I am parroting Barry’s last comment.]

              If you want to argue that the model averages are wrong and need improvements, you have at least these two basic options, (a) argue against the physics and approximations used or (b) show that the actual temperature deviates from the 95% confidence range for way too long to likely be correct. The models they use are known to be wrong in the time span of only a decade or two.

              You may want to read the top most (earliest) comment I wrote and the link to the animation of a person walking a dog.

              If you reply, consider replying to my earlier comment with that animation.

              You may also want to clarify why it is that seeing the temperature go down after some years or stay near flat leads you to believe the scientists are wrong. See the dog animation above and you will see many cases of the path going down. That is normal because the earth is complex and the ocean depths cannot be warmed quickly by sunlight (which doesn’t reach it) so must be warmed across many years slowly by mixing warm waters with cool waters. This mixing will necessarily draw heat from the top warm layers. This is why the CO2 expected air warming lags. And because of how complex nature is, the lag is not even and smooth but results in periods of greater lag and periods of less lag. This is why you see the temp oscillate up and down across years even as the underlying average keeps going up.

        • You aren’t making sense. Barry and Wow are supporting the science that is widely acknowledged by academic institutions of higher learning and major scientific bodies.

          What support are you using to go against science?

          You are aware that the temp has done before generally what it is doing now and that if it didn’t something would be horribly wrong, right? Did you expect natural variability oscillations to disappear or be totally dwarfed by the CO2 effect? Thankfully, that hasn’t happened yet.

          If you didn’t catch Wow’s reference to the escalator, look it up (skepticalscience has some graphics).

          The current theories will be adjusted, but if you ask a skeptic about their theories and they actually can reply with something, there is a very good chance that theory is way off the mark. Science is looking for the best theory we can manage, not a bad one or a horrible one.

          • I’m using my two eyes and a graph with predicted temp change from several models overlaid with another graph of actual temps and how awefully divergent they are.a third grader could figure out that something is wrong. If nap/pdo and La Niña are now so important (as opposed to just very recently when “man made changes will overwhelm natural fluctuations” and “nao/pdo isn’t nearly as important as AGW”), then why didn’t anyone (not one model predicted current data) pick up on that? If your models can’t even predict what will happen in the first 18 years, why on earth are we supposed to believe or trust that it will be accurate long term? Which hand is the pebble in? Right! (Not there) I mean left! Ha! Laughed off the stage!

            • Which graph? I hope it isn’t Roy Spencer’s and John Christy’s dishonest one.

              Also, since when did any of the scientists say that manmade changes will overwhelm natural fluctuations ON THE SCALE OF A FEW YEARS? I’ve always heard just the opposite.


              If we were burning 10X the CO2 as we currently are, that might overwhelm the lows of natural variability across 10-20 years so that perhaps we’d see no lower temp after 5 years or so. But today we can see lower temperatures after past 10 years sometimes but we expect not to see lower temps after say 30 years. One hundred years back, the CO2 level was much slower in rising and we could see lower temps even 50 years into the future. Does this make sense? See the BEST temp graph for examples in the 1800s where 50 years out we could find a lower temp, but since 1970, we have not had a year that could see a lower temp even 30 years out. That duration keeps getting smaller the faster CO2 rises.

              Let’s look at some numbers with an analogy to gaining and losing weight across days (as if the days were climate years).

              I start by exercising to lose 20 pounds but then the next day I relax and indulge on 20.1 pounds of food, water, etc. I repeat this cycle of losing 20 and then gaining 20.1, over and over.

              Day 0: start at 100 lbs
              Day 1: 80
              Day 2: 100.1
              Day 3: 80.1
              Day 4: 100.2
              Day 5: 80.2
              Day 6: 100.3
              Day 7: 80.3
              Day 8: 100.4

              Do you see how my weight goes up over time very slowly even though on a daily basis I fluctuate up and down wildly?

              OK, that is like the CO2 story of the 1800s. One year it might be very hot and the next year cold and the next year again hot, etc. After a log time (decades), we might notice a small average gain. That gain can hardly be seen throughout the 1800s, but it is there. You can just barely see it in the temperature graphs and in the CO2 graphs (I provided these 2 links earlier). Similarly, you can hardly see the average gain in the pattern above even after 100 days.

              At Day 100, I change. I lose 20 but gain 22.
              Day 100: 85
              Day 101: 107
              Day 102: 87
              Day 103: 109
              Day 104: 89
              Day 105: 111
              Day 106: 91
              Day 107: 113
              Day 108: 93
              Day 109: 115
              Day 110: 95
              Day 111: 117
              Day 112: 97
              Day 113: 119
              Day 114: 99
              Day 115: 121
              Day 116: 101
              Day 117: 123
              Day 118: 103
              Day 119: 125
              Day 120: 105
              Day 121: 127
              Day 122: 107

              We still see the same sort of thing, but now there is an upward movement that is faster and easier to see. This can be like the 1900s temperature. We still go up and down year to year but can be seen to gravitate up over time. Notice how Day 101 has 107 lbs as the weight while Day 108 has 93. See, we still see a drop in weight even 8 years out. However, on Day 122, we have 107 lbs also and never again will the weight ever go below 107. So we will in this case never see a drop in weight past about 22 days.

              Then I change on Day 200. I lose 20 but gain 30.
              Day 200: 185
              Day 201: 215
              Day 202: 195
              Day 203: 225
              Day 204: 205
              Day 205: 235
              Day 206: 215
              Day 207: 245
              Day 208: 225
              Day 209: 255
              Day 210: 235
              Day 211: 265

              How, the rate is very fast. This might be how it gets in the future with CO2. Notice on Day 201 I weigh 215 lbs, yet on day 204 I weigh 205 lbs. I was at a lower weight, even at this fast rate, even after 3 Days. However, beyond Day 204, we will never again see a lower weight than I had on Day 200. So at 4 days or more, we no longer dip as low as we had crested at the beginning.

              In other words, we bob and weave so that even as the average goes up and eventually overtakes the weaving and bobbing entirely, for a short time frame, the weaving/bobbing will overlap.

              So to see 2012 cooler than 1998 is OK, but we are nearing the point where we will “forever” be higher than 1998. For now though, we will see some years cooler than that very hot 1998.

              Oh, and note that every year after 1997 was hotter than 1997. That is because 1997 was a low temp year. Every year since 1997, we have been hotter than 1997. The idea that temp has not warmed is by cherry-picking 1998.

              Disclaimer, the climate doesn’t follow a nice even pattern like my weight gain/loss. Also, I would not ever never try that diet exercise regime we just examined, and neither should you.


              I think if you read and understood my first comment (animation with dog), you would not ask this question.

              If we look at the weight gain analogy I just posted, it’s as if the models are horrible at figuring out the bouncing sequence, but they are great at picking up on the average rise over time.

              Analogy 1:
              In engineering we see this all the time with low-pass filters. They catch the slowly rising “bias” in a signal really well but were not designed to figure out the fast up/down movements at the higher pitches. [See * below]

              Analogy 2:
              And most humans can tell if they hear notes being played that bounce around but generally move up towards a higher pitch (or down to a lower pitch) that the notes are moving up (or down). But most of us stink at being able to perfectly nail the actual frequency/note or to say if the note we heard 10 notes back was higher or lower.

              Analogy 3:
              As another example. Suppose you see someone who just started going up from your level on a slow rising glass elevator. You notice that as they rise slowly in the elevator they are moving their hands wildly in the air (animated speaker). Pretend you are the Hand Motion Climate Model and you have to predict the height of that person’s left hand at any given future second in time.

              A) You will almost surely be wrong for any given prediction.
              B) The person’s hand will drop and become closer to the planet’s surface on many occasions, sometimes being closer even 20 seconds out.
              B) You will easily realize that your predictions have to keep slowly going up.

              Even if a prediction for any given second is wrong, you will easily properly identify the general pattern of upward drift.

              Now, if the elevator were moving almost imperceptibly slow, that would be like the temperature during the 1800s. In the 1900s, the elevator is moving slow but faster for sure. It is scheduled to move even faster in the 2000s

              [*Of course, the climate is more complex than that engineering problem, but eventually scientists might do a decent job at also picking up the fast up/down just as does a common high-pass filter.]

        • Take a look at this graph.

          Look at the 1700-present period in contrast with the BEST temp graphs from the earlier link. Notice how the temp seems to oscillate a lot and returns mostly to the same level throughout the 1750-1800. In the 1800s there is a small upward shift. This matches the CO2 rise during that time. That shift further increases in the first 50 years of the 1900s. Again, showing consistency between the temp and CO2 rise. It is very significant in the last half of the 1900s. If you look at the current CO2 values, they continue to rise faster than linear, so, using that simple but extensive correlation and little other analysis, we can expect that the first 50 years of this century will have a net gain in temp that is greater than the change observed in the second half of the last century.

          Now, out of curiosity, do you have a theory that can match that record of historical temperatures?

          You have to have some super cock-belief to go against the world’s scientific bodies without at a minimum a formula or something that can match the historical record you see there similarly to what the climate scientist have achieved with their models. Certainly, Spencer hasn’t shown such a “formula”. The one he presented that Barry covered here was shown to be enormously out of reality when you walk it backwards in time.

          So do you have a competing theory for scientists to make use of that can make sense of the BEST temperature set? The scientists are waiting for that better theory, and you might be able to save them!

          Can you as a layperson write off the CO2 correlation?

        • doctorhastings, in case you aren’t sure and iirc, the equilibrium climate sensitivity is the value defined to reflect the climate’s long-term temperature response to CO2 levels.

          Now, when you change CO2 levels, the temp won’t change right away to the predicted value. One reason is because the oceans take a long time to warm because sunlight only enters the very top layers so ocean mixing must happen with the cooler waters below. This (and the changes in sunlight throughout the year) leads to yearly oscillatory weather patterns. Warming the ocean depths to near their final value takes many years.

          Barry is saying that our modeling of the ocean mixing is a cruder model than the air+sun models, so we may be wrong in predicting *how fast* the air will warm to its final value as predicted (mostly) by CO2 changes but we are more confident that it *will reach* that final value. The oceans essentially serve as an “ice cube” underneath the area the sun is warming. The sun will take longer to warm the air. We don’t understand that process, that transient response, nearly as well as we have confidence in the final “steady state” temperature level.

          Barry also stated that our understanding of the CO2-temperature response, which is more accurate (in the scientists opinion, and note the graphs I linked) than the ocean models, is considered more accurate in part because of many different types of studies of the earth’s history as found in various layers. It’s not just one path of analysis but several that roughly conclude the same response range to CO2 (ie, the same error range for the equilibrium climate sensitivity value).

          OK, if the oceans are slowing things down, that doesn’t mean air temps won’t rise a whole lot but that it will take longer. However, if the oceans take a long time to warm, they take a long time to cool as well. So the lag time will increase, but we can’t avoid most of the eventual rise only postpone it. If we repent later on only when we have seen the temperatures rise a lot, it will be too late to avoid the further rises in the pipeline.

          Wow’s point earlier was closely related. The more wrong we are about how much the oceans slow the temp rise, the worse it likely will eventually be, and the actual climate sensitivity will more likely actually lie closer to the upper end of the error range.

          If you know the above already or can’t make sense of what I just said and understand Barry and Wow better, at least I tried. 🙂

          • Then why didn’t one blasted model not pick that up and predict it! Additionally, it’s only the deep oceans >700m picking it up? Youre killing me guys!

            • Before you were saying that the models predicted such a thing might happen 2% of the time. Now you’re saying that NOT ONE predicted it? I don’t think you have a clear idea what you’re talking about.

            • >> Then why didn’t one blasted model not pick that up and predict it!

              This was answered a moment ago in the reply listing 3 analogies.


              The models will tend to be more accurate (in relative percentage terms) with 100 years than with 10. They will tend to be more accurate with 10 than with 1.

              And they will be more accurate, regardless of time span, the faster CO2 rises and will be less accurate the slower CO2 rises.

              This is just like you and I trying to predict many years out the hand height of a person rising on an elevator. The faster the elevator rises and the longer time goes on, the more accurate we will be (offset error divided by total height).

              >> Additionally, it’s only the deep oceans >700m picking it up?

              The sun first warms the top. While the top is rising in temp, the lower water remains cold.

              Eventually, some of this cold water and warm water mix.

              The result is that the top layer of water cools for a little while in order that the lower layers warm.

              The air is much thinner than the ocean water, so the air’s temp also drops when the ocean surface drops enough.

              Despite this, the CO2 continues to allow a greater amount of total sunlight to strike the earth. This adds a slowly rising contribution to the air temperature all the while the air temperature continues to bounce around on cue with the mixing oceans.

        • Doctorhastings/. Let me guess, you’re a young earth Creationist as well, think that it’s about time these Darwinist dead-enders give it up, simply accept the fact that the earth is only six thousand years old and that Jesus frolicked with the dinosaurs. “Evolution? What a bunch of maroons! If you believe that stuff I’ve got a bridge I’d like to sell you . . . “

    • Going down the up escalator AGAIN, doctor? You REALLY need to see a psychiatrist for this problem you have.

      PS your claim of “2% below the confidence interval” is incoherent and means nothing. However, if you mean “outside the 95% confidence interval” two things someone intelligent would have understood.

      1) Its wrong in actual fact
      2) In a dataset of 120 years, any 10-15 year period can be expected to have a trend outside the stated 95% confidence limits for the entire trend 5% of the time whilst still actually being on-track.

  11. Paraphrase…

    >> Proof is … not for science…. Science works in … theories.

    Which makes it a completely unsuitable basis for dictating rules to vital industries such as energy.

    > Trzupek was so incensed because it was obvious to him that,

    >> Mann’s attempt to separate proof from science…

    I can understand being incensed. Science, as a community, has built up this expectation that they can make these bold declarations with authority. So we want proof… Which they don’t provide… You are right that it is an incorrect attitude because, as a society, we need to recognize the role of science.

    A trial and error discovery process with low rates of confidence and very little in the way of quality control compared to say, building bridges, airplanes, or space flight vehicles.

    Proof it does not provide.

    • Well, that’s not exactly a “paraphrase”. But, warts and all, science still has a good track record compared to other human endeavors, in my opinion. So if we can all agree that science doesn’t provide absolute proof, and it never will be able to, people like you are perfectly free to dismiss science because you think you have some infallible guide that you can infallibly interpret. And then the rest of us (i.e., the vast majority of people) can ignore you and try to make decisions based on the best information we have.

    • >> Which makes it a completely unsuitable basis for dictating rules to vital industries such as energy.

      Were you insinuating that it’s possible for energy designers/engineers to *prove* ahead of time (a) the day any “energy” machine stops working and exactly which of the machines were not going to be manufactured correctly at a plant?

      I think you are confused about the message of this article. Did you read it? Proof in the sense covered here refers to abstractions only (to models). It can’t be applied to physical results because of the potentially infinite number of unknows (many of which we don’t even know about) that take place in nature.


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