Guest Post by Willis Eschenbach
First, I would like to thank Dr. Meier of the National Snow and Ice Data Center (NSIDC) for answering the questions I had posed (and had given my own personal answers) in “Trust and Mistrust”. I found his replies to be both temperate and well-reasoned. Also, I appreciate the positive and considerate tone of most of those who commented on his reply. It is only through such a peaceful and temperate discussion that we can come to understand what the other side of the debate thinks.
Onwards to the questions, Dr. Meier’s answers, and my comments:
Question 1. Does the earth have a preferred temperature, which is actively maintained by the climate system?
Willis says that he “believes the answer is yes”. In science “belief” doesn’t have much standing beyond initial hypotheses. Scientists need to look for evidence to support or refute any such initial beliefs. So, does the earth have a preferred temperature? Well, there are certainly some self-regulating mechanisms that can keep temperatures reasonably stable at least over a certain range of climate forcings. However, this question doesn’t seem particularly relevant to the issue of climate change and anthropogenic global warming. The relevant question is: can the earth’s temperature change over a range that could significantly impact modern human society?
My comment: Since unfortunately so little attention has been given to this important question, my idea of how it works is indeed a hypothesis. Therefore, “belief” is appropriate. However, I have provided several kinds of evidence in support of the hypothesis at the post I cited in my original answer to this question, “The Thermostat Hypothesis”.
Next, Dr. Meier says that there are “some self-regulating mechanisms that can keep temperature reasonably stable at least over a certain range of climate forcings.” Unfortunately, he does not say what the mechanisms might be, at what timescale they operate, or what range of forcings they can handle.
However, he says that they can safely be ignored in favor of seeing what the small changes are, which doesn’t make sense to me. Before we start looking at what causes the small fluctuations in temperature that we are discussing (0.6°C/century), we should investigate the existence and mechanism of large-scale processes that regulate the temperature. If we are trying to understand a change in the temperature of a house, surely one of the first questions we would want answered is “does the house have a thermostat?” The same is true of the climate.
Question 2: Regarding human effects on climate, what is the null hypothesis?
I will agree with Willis here – at one level, the null hypothesis is that any climate changes are natural and without human influence. This isn’t controversial in the climate science community; I think every scientist would agree with this. However, this null hypothesis is fairly narrow in scope. I think there is actually a more fundamental null hypothesis, which I’ll call null hypothesis 2 (NH2): are the factors that controlled earth’s climate in the past the same factors that control it today and will continue to do so into the future? In other words are the processes that have affected climate (i.e., the forcings – the sun, volcanic eruptions, greenhouse gases, etc.) in the past affecting climate today and will they continue to do so in the future? A basic premise of any science with an historical aspect (e.g., geology, evolution, etc.) is that the past is the key to the future.
My Comment: I assume that Dr. Meier has temporarily overlooked the fact that a null hypothesis is a statement rather than a question. Thus, his Null Hypothesis 2 (NH2) should be:
NH2: The factors that controlled earth’s climate in the past are the same factors that control it today and will continue to do so into the future
However, this formulation has some serious problems. First, a null hypothesis must be capable of being falsified. My null hypothesis (NH1) could be falsified easily, by a showing that measurements of the modern climate are outside the historical values.
Dr. Meier’s NH2, on the other hand, extends into the future … how can we possibly falsify that?
Second, to determine if the factors that controlled the climate in the past are the same factors that control it now, we must know the factors that controlled climate in the past, and we must know the factors that control climate now. But that is exactly the subject being debated – what controls the climate? We don’t know the answer to that for the present, and we know even less about it for the past. So again, his NH2 is not falsifiable.
Finally, there is a more fundamental problem with NH2. The null hypothesis has to be the logical opposite of the alternate hypothesis, so that if one is true, the other must be false. My null hypothesis NH1 is that the currently observed climate variations are the result of natural variation. The opposite of my null hypothesis is the alternate hypothesis, that currently observed climate variations are the result of human-caused GHG increases.
However, what is the opposite of NH2, which states that the factors that controlled climate in the past are those that control climate today? The opposite of that is the alternate hypothesis that the factors that controlled climate in the past are not those that control climate today.
But I have never once, in this entire decades-long debate, heard anyone make the claim that some factors that affected climate in the past have stopped affecting the climate. As a result, NH2 is a straw man. It is the null hypothesis for an alternate hypothesis that no one is propounding.
Since it is not falsifiable, and since it is a straw man null hypothesis, Dr. Meier has not proposed a valid null hypothesis. As a result, his arguments that follow from that null hypothesis are not relevant.
Question 3: What observations tend to support or reject the null hypothesis?
Let me first address NH2. We have evidence that in the past the sun affected climate. And as expected we see the current climate respond to changes in solar energy. In the past we have evidence that volcanoes affected climate. And as expected we see the climate respond to volcanic eruptions (e.g., Mt. Pinatubo). And in the past we’ve seen climate change with greenhouse gases (GHGs). And as expected we are seeing indications that the climate is being affected by changing concentrations of GHGs, primarily CO2. In fact of the major climate drivers, the one changing most substantially over recent years is the greenhouse gas concentration. So what are the indications that climate is changing in response to forcing today as it has in the past? Here are a few:
1. Increasing concentrations of CO2 and other GHGs in the atmosphere
2. Rising temperatures at and near the surface
3. Cooling temperatures in the stratosphere (An expected effect of CO2-warming, but not other forcings)
4. Rising sea levels
5. Loss of Arctic sea ice, particularly multiyear ice
6. Loss of mass from the Greenland and Antarctic ice sheets
7. Recession of most mountain glaciers around the globe
8. Poleward expansion of plant and animal species
9. Ocean acidification (a result of some of the added CO2 being absorbed by the ocean)
It is possible that latter 8 points are completely unrelated to point 1, but I think one would be hard-pressed to say that the above argues against NH2.
My Comment: Saying “it is possible that the latter 8 points are completely unrelated to point 1” begs the question. It is possible that they are related, but that is the question at hand that we are trying to answer. If Dr. Meier thinks that they are related, he needs to establish causation, not just say it is “possible that [they] are completely unrelated”.
Whether his points argue for or against NH2 is not relevant, since NH2 is not falsifiable, and is a null hypothesis for a position no one is taking. In addition, they are presented as “indications that climate is changing in response to forcing today as it has in the past” … but it is a mix of statements about forcings, and responses to increasing warmth. So I don’t see how that applies to NH2 in any case.
Despite those problems, let me address them, one by one, starting with one without a number:
In the past we’ve seen climate change with greenhouse gases (GHGs): This cries out for a citation, but there is none. When did we see that, who showed it, what evidence is there to support it?
1. Increasing concentrations of CO2 and other GHGs in the atmosphere: Yes, GHGs are increasing. However, this says nothing either way about NH2.
2. Rising temperatures at and near the surface: Yes, temperatures generally have been rising, and they have been ever since the Little Ice Age in the mid 1600’s. But again, what does this have to do with NH2?
3. Cooling temperatures in the stratosphere (An expected effect of CO2-warming, but not other forcings): I would greatly appreciate a citation to the claim that this is an expected result of GHG forcing but not other forcings. Given our general lack of understanding of the climate, it would be a very difficult claim to establish.
For one of the reasons why it would be hard to establish, here is the actual change in the stratospheric temperatures:
Figure 1. UAH and RSS satellite measurements of stratospheric temperature. DATA SOURCES UAH, RSS
Now, how on earth (or off earth and in the stratosphere) is that an “expected effect” of increasing GHGs? Since recovering from the Pinatubo eruption stratospheric temperatures have been stable … which climate model projected that outcome? What theoretical calculations showed that flat-line response?
4. Rising sea levels: Sea levels have been rising since 1900. If GHGs were driving the rise, we would expect to see an acceleration in the rate of rise corresponding to the acceleration in the rise of GHGs. However, we have seen no such acceleration in the long-term, and we see deceleration in the short-term. Here are two long-term records. Fig.2 is from Church and White and Jevrejeva:
Figure 2. Church & White and Jevrejeva sea level records from tidal stations. Photo is of Dauphin Island Tidal Station. PHOTO SOURCE
There is good agreement between the Church & White and the Jevrejeva records. As they were calculated in different ways, this increases the confidence in the result. Note that, despite increasing CO2, there is no increase in the rate of sea level rise.
Next, we have a short-term but presumably more accurate sea level record from the TOPEX satellite. Fig. 3 shows that record:
Figure 3. Sea level record from the TOPEX satellite. Black line is the trend from 1993 to 2004, and is projected to 2007 in gray. Red line is the trend since 2004.
As you can see, rather than increasing, the rate of sea level rise has dropped in recent years. And while it may well start to rise again, it is certainly not accelerating as the AGW hypothesis requires.
5. Loss of Arctic sea ice, particularly multiyear ice: As Dr. Meier would agree, the satellite record of Arctic ice is quite short, much shorter than the long-term changes in Arctic temperatures. The Arctic was as warm or warmer in the 1930s, and many records from that time attest to greatly reduced ice conditions. Both the Polyakov and the NORDKLIM records [see Update 10] show the time around 1979 as being about the bottom of the Arctic temperature swing, so reducing Arctic sea ice is to be expected since 1979. In addition, I was surprised that Dr. Meier did not mention the last three years, which have seen both increasing Arctic sea ice and increasing multiyear sea ice.
6. Loss of mass from the Greenland and Antarctic ice sheets: NASA reports that the GRACE satellite data shows the Antarctic and Greenland ice sheets to be losing a total of ~ 1,700 cubic km of ice per year. While this sounds large, this is about 0.005% of the total ice in the two sheets … I hardly see this as indicating anything but a confirmation that the earth has been warming for centuries, and is generally continuing to do so with the usual fits and starts. Since at the current rate of loss it will take about two hundred years to lose 1% of the ice, I don’t see this as a critical issue.
7. Recession of most mountain glaciers around the globe: According to the NSIDC, the excellent organization that Dr. Meier works for, there are about 100,000 glaciers on the planet. Again according to the NSIDC, we have measured the mass balance on 300 of them, and we have continuous records since 1960 for only 60 of them … so we have at least one record on 0.3% of the glaciers, and decent (although short) records on 0.1% of the glaciers. Given those percentages, “recession of most mountain glaciers” seems to be a bit of an overstatement of what scientific research actually has shown …
It is true that many of the glaciers we have measured have receded since the colder period of the 1960s when the records started. It is also true that some are advancing. Many of the known glaciers have been generally receding since sometime after the Little Ice Age in the 1600’s. Before that, they were advancing, so much so that in 1678 the village of Aletsch in Switzerland made a formal church vow to live virtuously if only the nearby advancing glacier would not over-run their village … a vow which they are now trying to recant as the glacier recedes. That dratted climate never stops changing.
All this shows is that when the earth cools, glaciers generally advance, and when it warms, they generally retreat. Surprising, huh? It says nothing about whether or not GHGs control the temperature.
8. Poleward expansion of plant and animal species: Animals and plants advance and retreat with the seasons and with the climate. In a time of general warming, like the last 300 years, we would expect them to move slightly polewards. However, care is required, because climate change is blamed for everything. For example, in this South African study (subscription required), they say (emphasis mine):
Evidence from the Northern Hemisphere and simple theoretical models both predict that climate change could force southern African birds to undergo poleward range shifts. We document the chronology and habitat use of 18 regionally indigenous bird species that colonised the extreme south-western corner of Africa after the late 1940s. This incorporates a period of almost four decades of observed regional warming in the Western Cape, South Africa. Observations of these colonisation events concur with a ‘climate change’ explanation, assuming extrapolation of Northern Hemisphere results and simplistic application of theory. However, on individual inspection, all bar one may be more parsimoniously explained by direct anthropogenic changes to the landscape than by the indirect effects of climate change. Indeed, no a priori predictions relating to climate change, such as colonisers being small and/or originating in nearby arid shrublands, were upheld.
9. Ocean acidification (a result of some of the added CO2 being absorbed by the ocean): Again, this appears to be happening, although we have very little in the way of data. If verified, this would indicate that atmospheric CO2 levels are rising … but we knew that already.
Overall, Dr. Meier’s points show that when the world warms we are likely to see various phenomena related to that warming. But that says nothing about his null hypothesis NH2, nor about my null hypothesis. None of them either support NH2 nor falsify NH2, as NH2 is a straw null hypothesis that cannot be falsified. They also say nothing about whether GHGs are currently causing unusual warming.
Next, Dr. Meier addresses NH1, my null hypothesis:
Of course none of the above says anything about human influence, so let’s now move on to Willis’ null hypothesis, call it null hypothesis 1 (NH1). Willis notes that modern temperatures are within historical bounds before any possible human influence and therefore claims there is no “fingerprint” of human effects on climate. This seems to be a reasonable conclusion at first glance. However, because of NH2, one can’t just naively look at temperature ranges. We need to think about the changes in temperatures in light of changes in forcings because NH2 tells us we should expect the climate to respond in a similar way to forcings as it has in the past. So we need to look at what forcings are causing the temperature changes and then determine whether if humans are responsible for any of those forcings. We’re seeing increasing concentrations of CO2 and other GHGs in the atmosphere. We know that humans are causing an increase in atmospheric GHGs through the burning of fossil fuels and other practices (e.g., deforestation) – see Question 6 below for more detail. NH2 tells us that we should expect warming and indeed we do, though there is a lot of short-term variation in climate that can make it difficult to see the long-term trends.
So we’re left with two possibilities:
1. NH2 is no longer valid. The processes that have governed the earth’s climate throughout its history have suddenly starting working in a very different way than in the past.
Or
2. NH1 is no longer valid. Humans are indeed having an effect on climate.
Both of these things may seem difficult to believe. The question I would ask is: which is more unbelievable?
This is a false dichotomy, created by using my real null hypothesis NH1, and Dr. Meier’s straw man null hypothesis NH2. Yes, both CO2 and temperatures rose over the 20th century … but correlation is not causation, and CO2 does not correlate any better with temperature than a straight line correlates with temperature. Next, Dr. Meier seems to think that NH1 and NH2 are somehow related, so that one or the other must be false. But both could easily be true. It could be true that the climate variations are natural (NH1), and also true that the historical forcings still apply (NH2). So his “one true / one false” duality is not valid.
At the end of the day, as Dr. Meier says himself, none of what he has said falsifies the null hypothesis NH1 that the observed climate changes are natural variations rather than human-caused. Since it is not falsified, we have nothing for the AGW hypothesis to explain. This is an important conclusion.
Skipping over some questions where we generally agree, we come to:
Question 6: How are humans affecting the climate?
Willis mentions two things: land use and black carbon. These are indeed two ways humans are affecting climate. He mentions that our understanding of these two forcings is low. This is true. In fact the uncertainties are of the same order of as the possible effects, which make it quite difficult to tell what the ultimate impact on global climate these will have. However, Willis fails to directly mention the one forcing that we actually have good knowledge about and for which the uncertainties are much smaller (relative to the magnitude of the forcing): greenhouse gases (GHGs). This is because GHGs are, along with the sun and volcanoes, a primary component that regulates the earth’s climate on a global scale.
My Comment: First, despite the IPCC claims, our knowledge of the effects of the GHGs is not as good as our knowledge of the effects of black carbon or deforestation. This is because we can actually measure the effects on the temperature of chopping down a forest. We can actually measure an amount of black carbon on snow, and see what difference it makes to the melting rate of the snow, and the temperature above the snow.
But we cannot make any such measurements for CO2. All of our numbers for the GHG forcings are based on climate models rather than measurements. The IPCC, and many scientists, give them great credence. I, and a number of scientists, do not.
Dr. Meier again:
It might be worth reviewing a few things:
1. Greenhouse gases warm the planet. This comes out of pretty basic radiative properties of the gases and has been known for well over 100 years.
My Comment: This is one of the most widely held misconceptions in the field. Here’s an example of the identical incorrect logical jump, from another field:
It is clear from the basic radiative properties that solar radiation warms what it hits. Therefore, if I walk out into the sunshine, my core body temperature will rise.
Clearly, the mere fact that a source is radiating does not mean that it will necessarily cause whatever the radiation strikes to warm up …
This is a crucial point, and one which is either overlooked or ignored by AGW proponents. Here’s another example. If your house has an air conditioner on a thermostat, despite the sun getting warmer and warmer as the day goes on, the house does not warm up. Again, we have a radiation source which does not cause what it strikes to warm up.
So yes, we know that CO2 is a greenhouse gas. And we know it will increase the forcing, although the amount is not well established.
But we absolutely do not know if that will cause the earth to warm over time. This is why my Question 1 above, about whether the Earth has a thermostat, is so important. If the earth has a thermostat, there are many basic assumptions that need to be reconsidered. I discuss this issue in detail at “The Unbearable Complexity of Climate”.
The short version of that post is that “basic radiative properties” are far from enough to determine what will happen from increased forcing in a complex system such as the climate or the human body, or even in a simple system like an air-conditioned house.
2. Carbon dioxide is a greenhouse gas. This is has been also been known for well over 100 years. There are other greenhouse gases, e.g., methane, nitrous oxide, ozone, but carbon dioxide is the most widespread and longest-lived in the atmosphere so it is more relevant for long-term climate change.
My Comment: Agreed.
3. The concentration of CO2 is closely linked with temperature – CO2 and temperature rise or fall largely in concert with each other. This has been observed in ice cores from around the world with some records dating back over 800,000 years. Sometimes the CO2 rise lags the temperature rise, as seems to be the case in some of ice ages, but this simply means that CO2 didn’t initiate the rise (it is clear that solar forcing did) and was a feedback. But regardless, without CO2 you don’t get swings between ice ages and interglacial periods. To paraphrase Richard Alley, a colleague at Penn State: “the climate history of the earth makes no sense unless you consider CO2”.
My Comment: As temperatures warm and cool, the CO2 levels go up and down. We can see that in the ice core records. SInce CO2 lags temperature in the Vostok ice core records of these changes, this means that the CO2 is not the cause of temperature change. Instead, it is a result of the warming ocean giving off more CO2. So far, Dr. Meier and I totally agree.
He then says “sometimes the CO2 rise lags the temperature rise.” This is not borne out by the data, where the correlation with lagged CO2 is greater than with un-lagged CO2 for the entire dataset. This indicates that the lag is a phenomenon common to the entire time period of the data.
Then Dr. Meier makes the claim that the CO2 “was a feedback”. If this were true, once the CO2 started to rise or fall, we should see a change in the rate of temperature rise or fall. To my knowledge no one has ever mathematically demonstrated such a feedback-driven change in temperature rise or fall in the actual ice core data. In addition to searching the literature for such a demonstration, I have used a variety of mathematical methods to try to find such a lagged feedback effect in the data, without any success. So why does Dr. Meier say that CO2 is operating as a feedback?
Dr. Meier may not even realize it, but he has totally conflated reality and models. What Dr. Meier is trying to say is that “without CO2 the models don’t get swings between ice ages and interglacial periods.” And what Richard Alley has shown is that “the modelled version of the climate history of the earth makes no sense unless you consider CO2”. Neither of them are talking about reality, they are discussing model-ice on Model-world, not ice on the Earth.
This blurring of the line between reality and models is a recurring and very frustrating feature of the climate discussion. I’m talking about reality, and meanwhile, without saying so, Dr. Meier is discussing model results. This habit of climate scientists, of talking about models as if they were discussing reality, is very frustrating and impedes communication.
4. The amount of carbon dioxide (and other GHGs) has been increasing. This has been directly observed for over 50 years now. There is essentially no doubt as to the accuracy of these measurements.
My Comment: Agreed
5. The increase in CO2 is due to human emissions. There are two ways we know this. First, we know this simply through accounting – we can estimate how much CO2 is being emitted by our cars, coal plants, etc. and see if matches the observed increase in the atmosphere; indeed it does (after accounting for uptake from the oceans and biomass). Second, the carbon emitted by humans has a distinct chemical signature from natural carbon and we see that it is carbon with that human signature that is increasing and not the natural carbon.
My Comment: Agreed.
6. Given the above points and NH2, one expects the observed temperature rise is largely due to CO2 and that increasing CO2 concentrations will cause temperatures to continue to rise over the long-term. This was first discussed well over 50 years ago.
My Comment: We have no evidence (not model results but evidence) that at the current general temperature equilibrium, changes in GHG forcing affect the temperature. We have no evidence that they affected temperature in the transitions between glacial and interglacial periods. We have no evidence that there is a linear relationship between temperature and forcing, it may well be temperature dependent and asymptotically approach zero at equilibrium. Yes, as Dr. Meier points out, forcings affect temperature in those situations (and all others) in the models. But I’ve been programming computers for almost fifty years now, and I’ve written too many computer models and I know too much about computers to trust untested, unverified models that are tuned to reproduce the past. Too many parameters, too many degrees of freedom, too much error propagation, too little understanding of important processes, they have, as Kipling said, been “twisted by knaves to make a trap for fools”.
Question 7: How much of the post-1980 temperature change is due to humans?
Here Willis says we get into murky waters and that there is little scientific agreement. And indeed this is true when discussing the factors he’s chosen to focus on: land use and soot. This is because, as mentioned above, the magnitudes of these forcings are small and the uncertainties relatively large. But there is broad scientific agreement that human-emitted CO2 has significantly contributed to the temperature change.
My Comment: Post 1980, the temperatures rose, peaked in 1998, and have been basically level since then. While there is broad agreement on something like “CO2 contributes significantly”, how significantly did it contribute to the post 1998 period of basically no temperature change? The answer, presumably, is unknown. Some scientists see CO2 as a second order forcing, after land use/land cover change (LULCC) and black/brown carbon forcing, particularly for the Arctic. My point is that there is still ongoing scientific discussion on the question of how much each forcing might affect the climate, particularly given that the temperature hasn’t risen in the last decade.
Question 8: Does the evidence from the climate models show that humans are responsible for changes in the climate?
Willis answers by claiming that climate models don’t provide evidence and that evidence is observable and measurable data about the real world. To me evidence is any type of information that helps one draw conclusions about a given question. In legal trials, it is not only hard physical evidence that is admitted, but information such as the state of mind of the defendant, motive, memories of eyewitnesses, etc. Such “evidence” may not have the same veracity as hard physical evidence, such as DNA, but nonetheless it can be useful.
My Comment: I fear this answer makes no sense. Dr. Meier says evidence is “any type of information that helps one draw conclusions”. Many people are helped to draw conclusions by astrology. Does that make astrology evidence? The conclusions of some scientists are shaped by their religious beliefs. Does that make religious beliefs evidence? Hunches and intuition help scientists draw all kinds of conclusions … are they evidence?
I don’t think Dr. Meier really believes what he is saying here. For example, said that above that I think that the earth has a thermostat. The first thing that Dr. Meier said in response to that was “Scientists need to look for evidence to support or refute any such initial beliefs.”
I don’t think he was referring to astrology, or my state of mind, or the memories of eyewitnesses. I think he was talking about data, observations, facts to support my hypothesis. And that is what I have provided at the citation listed above, for the same reason that he asked – because science is based on evidence, data, facts, measurements, and not on states of mind. The modeller’s mantra says “All models are wrong … but some models are useful.” Yes, they are often useful, but they don’t produce evidence.
Regardless, let me first say that I’m a data person, so I’ve always been a bit skeptical of models myself. We certainly can’t trust them to provide information with complete confidence. It may surprise some people, but most modelers recognize this. However, note that in my response to question 6 above, I never mention models in discussing the “evidence” for the influence of human-emitted CO2 on climate. So avoiding semantic issues, let me say that climate models are useful (though far from perfect) tools to help us understand the evidence for human and other influence on climate. And as imperfect as they may, they are the best tool we have to predict the future.
My Comment: As anyone who has looked at a weather forecast for next weekend knows, some models may be the best tool we have and still be no better than flipping a coin.
As to whether the models are useful, we have some simple ways to determine whether a model is useful. One is to see if they can make falsifiable predictions of the future states of a given system. To date, the models have failed miserably at this test. The current hiatus in warming was not predicted by a single model that I know of. Even if the GHG forcing were overwhelmed by natural variations, according to the models the stratosphere should have continued to cool. It did not do so. They have not been able to forecast the trend in the numbers of hurricanes, despite making a host of claims after the recent single-year peak in hurricane numbers. The claim is often made that the models are not accurate in the short-term, but they are accurate in the long-term. I’m still waiting … how long a term does it take until their accuracy starts to show up? Twenty-six years? Fifty-three years? Where is the theory that tells us when they will start to be right?
Another way to judge a model’s usefulness is if it can identify missing factors in a system. The classic example is the discovery of Neptune based on what was missing in models of the solar system. But the climate models are assumed to already contain all the important forcings, so they cannot discover any possible missing forcings. What verified new facts have the models told us about the operation of the climate that we did not already know?
Another way to judge the models is to see if the results of various models agree or not. Figure 4 shows the amount of clouds by latitude from a number of climate models:
Figure 4. Cloud cover of the Earth by latitude, as shown by 31 climate models, from the AMIP study (1999). Black line is the observed cloudiness by latitude.
Dr. Meier, if you think that any of those model results are evidence for the actual cloud cover by latitude, I fear that we have vastly different definitions of “evidence”. They are model results, and are not evidence of latitudinal cloud cover in even the most expansive conceivable definition of evidence. Models can be useful, but their results are not evidence of anything.
Question 9: Are the models capable of projecting climate changes for 100 years?
Based on Willis’ answer to Question 1, I’m surprised at his answer here. If the earth has a preferred temperature, which is actively maintained by the climate system, then it should be quite easy to project climate 100 years into the future. In Question 1, Willis proposed the type of well-behaved system that is well-suited for modeling.
My Comment: I see no theoretical reason that a complex chaotic system with a preferred temperature would be any simpler to model than a complex chaotic system without a preferred temperature. I have provided links in my Thermostat Hypothesis to two simple models of such a system, one by Bejan and one by Ou. However, I do not think that either of them produce evidence, or that either can project the climate a hundred years from now.
However, Willis claims that such a projection is not possible because climate must be more complex than weather. How can a more complex situation be modeled more easily and accurately than a simpler situation? Let me answer that with a couple more questions:
1. You are given the opportunity to bet on a coin flip. Heads you win a million dollars. Tails you die. You are assured that it is a completely fair and unbiased coin. Would you take the bet? I certainly wouldn’t, as much as it’d be nice to have a million dollars.
2. You are given the opportunity to bet on 10000 coin flips. If heads comes up between 4000 and 6000 times, you win a million dollars. If heads comes up less than 4000 or more than 6000 times, you die. Again, you are assured that the coin is completely fair and unbiased. Would you take this bet? I think I would.
But wait a minute? How is this possible? A single coin flip is far simpler than 10000 coin flips. …
I fear I don’t know where to start explaining the host of reasons why this doesn’t work as a metaphor for the difference between a weather model and a climate model, or as an explanation of how climate models could possibly project a hundred years out. But I’ll give it a shot.
Both weather and climate models are what are called “iterative models”. The model looks at the current state of the weather, and predicts what the weather will look like after the next time step (typically under an hour in modern models).
This type of model is very, very hard to get right, because the errors “propagate”. This means that if your calculation of the weather at one time step of the model is off a little, the next time step will likely be off a little more, and on ad infinitum. Error propagation of this type is an unavoidable feature of iterative models. It is one of the main reasons that weather models diverge from the actual weather over a very short period of time. This makes long-term forecasts very difficult.
Predicting the number of heads in 100 flips or a million flips, on the other hand, does not suffer from this problem. It is a simple and well understood statistical problem which can be solved with a single equation. In fact, the more flips, the less error you will find in the result. Ahhh, would that climate could so easily be reduced to a single equation …
Next, coin flips do not contain any variables. They are not affected by things such as humidity or temperature. It’s just the coin, period. That’s why we use them as a decision tool, because they are random, they are not dependent on variables. Weather models, by contrast, have a host of variables: temperature, humidity, barometric pressure, wind speed, wind direction, and many others. They are anything but random.
And while one coin flip has the same number of variables as a thousand coin flips (none), climate models must include a host of variables that can be neglected in weather models. These include variables like terrestrial biology, sea biology, ocean currents, variations in soil moisture, slow changes in ice cover, and lots of others. This makes climate models much more complex than weather models … and in iterative models, this means more sources of error.
Finally, both climate and weather are chaotic. This introduces a host of other problems into any attempt to model the climate or the weather.
As a result, the idea that climate models can project the climate a hundred years out because “a single coin flip is simpler than 10000 coin flips” is untrue, simplistic, and in no way a metaphor which would help us understand the problem with long-term climate model projections of the future.
Moving along, I find:
Question 13: Is the current peer-review system inadequate, and if so how can it be improved?
There is always room for improvement and Willis makes some good suggestions in this regard. Speaking only from my experience, the process works reasonably well (though not perfectly), quality papers eventually get published and bad papers that slip through the peer-review process and get published can be addressed by future papers.
My Comment: I love the idea that “quality papers eventually get published”. It just sounds so good. However, please read Ross McKitrick’s saga with his paper on Surface Temperatures, and Bishop Hill’s post on Caspar and the Jesus Paper, before you become too enamoured of the idea that the system is self-correcting and works in the end. A review of the CRU emails in this regard is in order as well.
From my own experience, I wrote a paper explaining the problems with a study by Michael Mann that had been published in Geophysical Research Letters (GRL). His study claimed that the best way to extend a smooth (Gaussian or otherwise) to the end of a series was to pad the end of the series by reflecting it around both the x and y axes. (This results in forcing the smooth through the last point of the series, which is absolutely the last thing you want to do).
The paper was rejected by GRL because one reviewer said I was too hard on poor Mike. So I set off to re-write it.
Within a few months, Mann published a new paper in GRL on the subject, incorporating my ideas as his own. Coincidence? You be the judge … I threw up my hands, my paper never got published. I think the present peer-review system sucks. The CRU emails contain hosts of references to this kind of scientific malfeasance, stacking peer-review panels with people who will give papers an easy pass, circulating papers like mine to other scientists, blackballing journals, and pressuring editors. We know it is happening, we have their emailed confessions.
Yes, I understand that Dr. Meier’s personal experience is different, and I respect that. But only looking at his own experience is a very restricted view of the situation. The repeated refusal of many climate scientists to go outside their own experience and honestly look at the scientific malfeasance going on in their own field is a constant source of amazement to me.
Question 14: Regarding climate, what action (if any) should we take at this point?
This is of course an economic and political question, not a scientific question, though the best scientific evidence we have can and should inform the answer. So far there isn’t any scientific evidence that refutes NH2 and we conclude that the processes that influenced climate in the past are doing so today and will continue to do so in the future. From this we conclude that humans are having an impact on climate and that this impact will become more significant in the future as we continue to increase GHGs in the atmosphere. Willis answers no and claims that the risks are too low to apply the precautionary principle. The basis for his answer, in practical terms, is his conclusion that NH2 is no longer valid because while GHGs have been a primary climate forcing throughout earth’s history, they are no longer having an impact. This could of course be true, but to me there doesn’t seem to be much evidence to support this idea. But then again, I’m a skeptic.
My Comment: First, NH2 is not falsifiable and is a straw null hypothesis. Second, I make no claim that the factors operating now did not operate in the past. I did not conclude that “NH2 is no longer valid because while GHGs have been a primary climate forcing throughout earth’s history, they are no longer having an impact” as Dr. Meier claims, and I am mystified that my words could be misunderstood in that way.
Also, I did not say that “the risks are too low to apply the precautionary principle”. I said “I disagree with those who say that the “precautionary principle” means that we should act now. I detail my reasons for this assertion at “Climate, Caution, and Precaution”. And nothing at that link says that the issue is that the “risks are too low”, I have no clue where Dr. Meier got that claim.
Regrettably, after explaining why he thinks that I’m wrong about what action to take, Dr. Meier does not say what action (if any) he thinks we should take.
Final Conclusions, in no particular order
1. Reading Dr. Meier’s answers to the questions has been very interesting and very productive for me. It has helped to identify where the discussion goes off the rails.
2. Understanding how the guy on the other side of the table sees the situation is valuable for everyone concerned.
3. Dr. Meier’s answers were well thought out and well expressed. He obviously has considered these matters in detail, answered honestly and fully, and taken the time to lay them out clearly.
4. As I didn’t discuss most of the questions where Dr. Meier and I were in basic agreement, it likely appears that I disagreed on almost all points. This is absolutely not the case.
5. I wish that Dr. Meier had included citations for his assertions. Not having them makes it harder to discuss his ideas.
6. I sincerely hope that I have not offended Dr. Meier. I am a reformed cowboy, but despite going to the cowboy reform meetings and following the twelve steps, sometimes the raw ranch kid shines through. I am passionate about these matters, and sometimes I overstep the bounds. I apologize for any sins of omission or sins of commission I may have committed, and I hope that Dr. Meier considers my words in the spirit of vigorous scientific debate.
7. Since the null hypothesis that the climate variations are natural has not been falsified, the AGW hypothesis is still a solution in search of a problem.
8. As I have found out more than once to my own cost, putting one’s ideas out on the web for people to find fault with is a daunting prospect, and one which may not always end well. I offer Dr. Meier my profound thanks and my respect for his courage and willingness to put his ideas on the firing line, as it is not an easy thing to do.





DeNihilist (10:16:11) : Mr. Pelto (is it Dr.?), {Willis you mention the recession of mountain glaciers, but then spend your time looking at the glacier mass balance data set……}
Is there any data from the previous warm period of 1930/40 that shows abatement of the glaciers comparable to the last 30 years?
Yes:
“The stupefying pace of glacier melt in the 1940s” (GRL 12/2009)
The most recent studies by researchers at ETH Zurich show that in the 1940s Swiss glaciers were melting at an even-faster pace than at present. This is despite the fact that the temperatures in the 20th century were lower than in this century. Researchers see the main reason for this as the lower level of aerosol pollution in the atmosphere…
Huss points out that the strong glacier melt in the 1940s puts into question the assumption that the rate of glacier decline in recent years “has never been seen before”. “Nevertheless”, says the glaciologist, “this should not lead people to conclude that the current period of global warming is not really as big of a problem for the glaciers as previously assumed”. This is because it is not only the pace at which the Alpine glaciers are currently melting that is unusual, but the fact that this sharp decline has been unabated for 25 years now.
http://hockeyschtick.blogspot.com/2010/03/austrian-alps-glaciers-have-almost.html
Will (05:53:25), thanks for your contribution.
First, you say “My apologies if this is a very naive question.” For me, the only naive question is the one I don’t ask, because then I stay uninformed forever …
Can we place more confidence in the average of a model run with different initial states and different parameters? These are actually two different questions.
If we vary the initial states, we are investigating the sensitivity of the model’s responses to where the model starts. This gives us an idea of the variety of possible modeled outcomes.
If we vary the parameters, on the other hand, we are performing a sensitivity analysis of the settings of the model itself. This will show us how much the outcomes depend on the settings of the model’s dozens and dozens of dials.
Bear in mind that the parameters have been very, very carefully adjusted and tuned to get the model to agree with the historical temperature trend. Unfortunately, in a complex model this often throws other parts of the model way out of kilter. If you tune the model for temperature, some other aspect (say humidity or clouds or rainfall) will likely get worse.
The key to answering your question, however, is to note that none of this tells us anything about the variability of the trend line or the hourly temperatures in the real world. All they do is show us the variability of the trend line and the hourly temperatures in the model. And as Fig. 4 above clearly demonstrates, the two (whether averaged or not) are very different. Model results are not evidence about anything but the model itself.
Finally, I cannot emphasize enough that these models are tuned to reproduce the past. This means absolutely nothing about their predictive ability. It is very, very tempting to think that if a model is successful in reproducing past conditions it will be equally successful in forecasting future conditions. Nothing is further from the truth, particularly when modelling chaotic systems. A good example of such a system is the stock market.
But the stock market is unlike the climate, in that unsuccessful models get squashed like bugs. How many are left after that squashing? Well … none. Nobody can predict the markets. The difference is that stock market models have to actually perform, whereas climate models only need to impress the credulous and kinda sorta fit historical temperature patterns.
The climate modellers make the extraordinary claim that, although their models are no better than the stock market models in predicting tomorrows conditions, or next month’s conditions, they can forecast the climate a hundred years from now.
I see no theoretical reason to believe that is true. The claim is that the general trend of the climate over time is more predictable than the individual hours and days and months of weather over time. But since the general trend is just the average of the individual hours and days and months, if those are bad, then the trend will be equally bad. So where do the models get the enhanced accuracy at long timescales?
All the best, questions are good,
w.
Speaking of parameters, the models have dozens of them that they can adjust. This allows them to tune the models so that they can “hindcast” historical climate conditions. And they do a reasonable job of that hindcasting, as the modellers never tire of pointing out and demonstrating with impressive looking maps and graphs.
But should that impress us? In this regard, the following story by Freeman Dyson bears repeating:
So yes, the models “work”, just like Dyson’s results “worked”. And the models can hindcast fairly well … but with dozens of parameter, it would be a surprise if they couldn’t make the elephant wiggle its trunk. However, as the stock brokerage investment ads always say, “Past success is no guarantee of future performance” …
will,
I think the point, and I don’t even know if this has been posed as a research question, that if one makes an error in the calculations of a climate model, that error will propagate very quickly due to the huge amount of calculations involved in the simulations of climate models. Since the same equations are used for weather models and climate models, it’s good to know that we have the weather figured out for a few weeks before we start talking about years and years. This should be fairly clear if you have dealt with error analysis and propagation in your own work.
It is also the reason I have hard time believe ‘hindcasting’ because the error in reconstructed data is ill-conditioned (no well-controlled error measurements made on it) and, therefore, it is almost impossible to track how the error propagates in simulations of past climate. This is very similar to the snowball effect.
In seems that the standard for models of future climate is that they agree with each ‘fairly well’, which was one of the points that Dr. Meier made in his post.
I think when it comes to your point concerning time and space scaling, one must be very careful with one’s data. If forecasters had data on a one mile by one mile grid of the USA on a basis of every 30 seconds, I think they could provide very good models for the weather on the time scale of minutes. But because weather data does not have that kind of resolution, longer time scales are modeled with more predictive power and the ‘sweet spot’ is a couple days.
If you’re trying to model the climate with ill-conditioned proxy data, low resolution time series data, no data on feedbacks and ’empirical parameters’ based on some measurements of the real world that may or may not capture the variation of the desired quantity it can be hard going.
Given the complexity of a physical model of the climate with its interactions between the oceans, land and atmosphere, there very well be some averaging that helps the simulations. There is, unfortunately, no reason to believe this would happen a priori for the whole model simulation however.
The ultimate test is validity in the real world where, as Willis points out, weather models do pretty good for a couple days and climate models don’t work.
I understand your confusion, as I am continually confused by all this, because simple statistics seems to tell us that the more one averages, the better. But, as is the case in almost all research fields which I’m sure you know, climate science is not simple statistics.
Hope that helps.
Cheers.
Also regarding rates of glacier melt in past:
Greenland:
If you look at this graph in detail, you can see that the retreat in the period 1929-1953 (24 years) was faster than in 1953-2003 (50 years).
http://hockeyschtick.blogspot.com/2010/04/cooling-of-greenland-over-past-8000.html
Glacier melt is actually reflective of the climate thousands of years ago:
http://hockeyschtick.blogspot.com/2010/03/glaciers-science-and-nonsense.html
Thanks for the reply, Willis. I should mention that I have only taken a real interest in this since reading ‘The Hockey Stick Illusion’ last week, and was utterly appalled by the abuse of the scientific method documented therein (although a mathematician by training, I currently work in neuroimaging – a field which is also prone to play fast and loose with statistics from time to time, which bothers me greatly).
I’m still not convinced by your argument (although am quite willing to be corrected 🙂 The models which produce the weather forecast for the next several hours may predict ‘a likelihood of some showers’ and this will often turn out to be a good prediction (I need to take my umbrella with me) – however those same models are unlikely to be able to tell me if it is going to be raining from 2.07am until 2.13am, and then again at 2.37am for another 13 minutes. So they have produced a reasonably accurate model of the future weather over one time scale (hours) but not another (minutes). Could the same not be said to apply to climate models? Note, this is a different issue from whether model predictions should be treated as ‘facts’. But it seems to me that predicitive models can have their part to play in scientific enquiry – otherwise there would be little point in ever producing one in any branch of science.
Will (12:17:38) : I would be grateful if someone could supply some pointers to the literature so that I can learn more about why this claim is incorrect (that modelling trends requires first modelling the detail correctly).
It would only be necessary for you to refer to a decent statistics text book.
I’ll explain my objections/concerns as follows.
Suppose you have a random variable with standard deviation ‘Sd’. As it is a random variable, individual observations (the “random variates”) cannot be fully determined in advance. The future values of individula random variates can only be described in terms of probability distributions.
One further condition: I’ll assume we have carefully sampled the random variable for maximum information in each random variate- this means the unpredicable components in the random variates are statistically independent (each sample provides no information about the random component in the neighbouring sample). [Things tend to get more complicated if this condition is not met, but the additional complications do not alter the conclusion.]
Let’s say we’d like to predict futre values, but decide that individual random variates are too unpredictableide. This has been the case for “weather” predictions – for example, the Met Office withdrawing its quarterly forecasts.
It is claimed that we can turn to averaging random variates to gain improvements in predictability (climate versus weather).
For simplicity, lets say we choose to average 100 samples of the above random variable. On the conditions set out above and using only well established stastistical properties, any mean value we produce from 100 samples will also be random variate. The “standard error” (standard deviation) of this new random variate will be (Sd/10).
Does that mean the average is more predictable in some useful sense? I say it doesnt.
All we have done is to transform the problem from one of predicting a variable with standard deviation Sd, to predicting a different variable with standard deviation of (Sd/10). If Sd was intolerable for the underlying data, (Sd/10) will be no more tolerable for the 100-point mean.
We have added no useful information in moving from one prediction to the other. All we have done is to give ourselves a more slowly moving random variable. But we will also discover that trying to predict the 100-point mean to better than (Sd/10) is no easier than predicting the underlying random variate to better than Sd.
That’s the way I see it – on arguments of averaging, the climate can be no more predictiable than the weather, when we take into account the appropriate measures of variability.
Happy to hear other views.
maxwell (07:30:53)
Well, I would if I understood what it had to do with climate models. You say his point is:
This is not true. The confidence intervals for coin flipping are well established. The standard error of the average for a coin that is flipped N times is 0.5 / sqrt (N-1).
So we don’t have “more confidence in our model” if we flip a coin a hundred times rather than ten times. We have 100% confidence in our model in both cases. We know for sure that the standard error will be smaller if we flip more times. We have 100% confidence that our model can tell us what the standard error is if we tell it how many times we are flipping the coin.
But what on earth does this have to do with climate models? The standard error of flipping coins, whether ten or a thousand times, is well encapsulated in a single equation. We know in advance that we will come closer and closer to 50% heads as the number of flips increases, in a manner which is exactly predictable by a well-understood mathematical equation.
With climate models, unfortunately, we have no corresponding equation, understanding, or mathematical predictability. We don’t know whether it will get closer and closer to some value as the number of iterations increases. In fact, we don’t know if the process is stationary (wanders around some central value) or not, and indications are that it is not stationary.
Here is the central problem with his analogy, which makes it useless for our present purposes:
With coin flips, as the number of flips increases, our answer gets more accurate (smaller standard error).
On the contrary, with iterative models like climate models, as our number of interations increases, our answer gets less accurate.
That’s why predictions of weather models are no good beyond a few days, where predictions of coin flipping have less error the more times we flip.
So whether Dr. Meier’s point is true or not, and whether I understand it or not, is immaterial, because coin flipping has absolutely nothing to do with climate models.
Bob (Sceptical Redcoat) (09:25:12)
These days, I toss my ideas onto the electronic winds so that they may possibly take root wherever they fall. I’m not doing this to get credit (although I don’t mind getting credit). I’m doing this to get results. Use them as you wish.
As to whether I have been a cowboy or a fisherman, I have been both, along with many other trades. My CV is here, it’s the record of a life lived foolishly and furiously at the edge of the envelope. My motto has always been “Retire early … and often”. Not a path I’d counsel for most folks, but it has served me well.
bob (09:39:38)
My take on Dr. Meier’s NH2 was that he meant that the classes and kinds of factors that affect the climate (e.g., greenhouse gases, volcanic eruptions, changes in the sun) are the same now as they were in the past. I agree with that, with the proviso that we don’t know what many of those factors are/were.
Yes, we’ve added a couple new very minor GHGs to the mix, but I don’t think that was what he was referring to.
Steve in SC (09:40:19)
Steve, without commenting on whether or not you are correct, your style of argumentation doesn’t add to the discussion. If you think Dr. Meier is wrong, it doesn’t do anyone any good to just call BS, even if you are right.
Go out and read the scientific papers on the subject of the variations in carbon isotopes in fossil fuels and in the atmosphere. Familiarize yourself with the arguments both pro and con. Research the authorities. Run the numbers yourself, don’t trust anyone’s calculations. Find the citations that support your point of view. Use them to demonstrate, not claim but demonstrate, that what Dr. Meier said is wrong.
Until you do that, I fear you have not added anything to the discussion other than your vote … but science is not settled by a vote (no matter how many times we’re told that there is a “consensus”). It is settled by evidence and logic and math.
All the best,
w.
Willis (or anybody else with the skill),
like a true skeptic I went back to the source data and plotted my own graph for Figure 3. It raised a few questions I hope can be answered.
1) When I plot that data and add a linear trend to the whole data set I don’t see such a divergence in trends as is obvious from the article graph.
I’m using Excel so I don’t have Gaussian average (in fact I don’t know what a Gaussin average does to the data). The website the data is derived from tends to use smoothed data. What is the strength in using this averaging?
2) I’m also unsure that there is any strength in comparing the trend from 93-04 with the trend from 05-09. The trend is constantly changing over different time periods. For example 92-97 would show a lower trend than for the whole data set. I guess on the basis of that argument you could also ask the strength of the trend from 93-09. My question is are these short term flutuations in data really relevant?
3) Finally the colorado website seems to agree with Willis. They plot a graph with a linear trend and don’t mention anything about an increasing rate of sea level rise. I was wondering should the predicted increase in the rate of sea level rise be showing up in the present observed data or is this something that will only start appearing down the line? What do the models predict about significant, observable rate change rise?
I’ll answer my own question 3!!
This section of the IPCC contains the relevant info.
Climate Change 2007: Working Group I: The Physical Science Basis
Section 5.5.2.4 Interannual and Decadal Variability and Long-Term Changes in Sea Level
Quoting
“Interannual or longer variability is a major reason why no long-term acceleration of sea level has been identified using 20th-century data alone”
It seems nobody expects to see the increasing rate of sea level rise at the moment. Willis have you set up a straw man?
John Coleman (10:08:57)
Dr. Meier is a research scientist at the National Snow and Ice Data Center. His bio and publication list is here.
I am (inter alia, and lots of alia at that) an amateur scientist and independent climate researcher. My bio is here.
Some of my earlier writings are:
Underground Problems with Mann-Holes
An Analysis of the Topex Sea Level Record
Data Smoothing and Spurious Correlation
Can’t See the Signal For the Trees
The Thermostat Hypothesis
Tropical Tropospheric Amplification, an invitation to review this new paper
Why Copenhagen Will Achieve Nothing
The Steel Greenhouse
The people -vs- the CRU: Freedom of information, my okole…
When Results Go Bad …
The Smoking Gun At Darwin Zero
Willis: Reply to the Economist
Darwin Zero Before and After
The Unbearable Complexity of Climate
Climate, Caution, and Precaution
Where Are The Corpses?
Floating Islands
Congenital Climate Abnormalities
Fudged Fevers in the Frozen North
Judith, I love ya, but you’re way wrong …
Sense and Sensitivity
Himalayan Hijinks
Another Look at Climate Sensitivity
More on the National Geographic Decline
GISScapades
Skating on the Other Side of the Ice
Carbon Emissionaries
Trust and Mistrust
Conservamentalism
Global Radiation/Conduction/Evaporation Climate Model (Excel Spreadsheet)
Nature Magazine “Communications Arising” on Lake Tanganyika
E&E article on Tuvalu
E&E article on Svalbard
I have discussed these questions in a number of my writings. I would note in passing that there is almost never “proof” in science, other than in a mathematical sense. All we can do is falsify claims, we can never prove them.
Exaggeration, but I love it.
w.
Regarding CO2 and water and reradiation:
http://pubs.acs.org/subscribe/journals/ci/31/i11/html/11box.html
which references (worth your time to read):
http://pubs.acs.org/subscribe/journals/ci/31/special/may01_viewpoint.html
Dr. Robert Essenhigh later worked out the calculations for absorption and published here:
http://pubs.acs.org/doi/abs/10.1021/ef050276y
subscription required. (Libraries may have subscriptions. If anyone can slog through this and post a summary, I would appreciate it. I’d be willing to buy the paper myself, but I’m not sure my calculus skills are still up to the task.)
The main point he makes is that H2O gas accounts for ~80% of what we call the greenhouse effect, and CO2 accounts for essentially the rest.
Apparently RealClimate beat on Dr. E back in the day.
Dr. E had an MS student do this:
http://etd.ohiolink.edu/view.cgi?acc_num=osu1259613805
Study of Energy Balance Between Lower and Upper Atmosphere
I haven’t read the thesis yet.
How do you propose to prove that there is no proof, Willis?
@ur momisugly Willis Eschenbach (13:13:39) :
I see no theoretical reason to believe that is true. The claim is that the general trend of the climate over time is more predictable than the individual hours and days and months of weather over time. But since the general trend is just the average of the individual hours and days and months, if those are bad, then the trend will be equally bad. So where do the models get the enhanced accuracy at long timescales?
They do not get enhanced accuracy over longer timescales, they only get a higher probability of showing a result that is similar to reality, which some people seem to confuse with ‘correct’.
ctm – that list of Willis’ articles above should become a sidebar/context menu somewhere, rather than get lost in the eternity of comment threads.
Aargh. (15:45:20), you raise a good question:
Proof? Well, first I establish the null hypothesis:
There is proof in science.
Then since this is climate science, to falsify the null hypothesis, I merely need to quote from that well known scientific work, “The Treasure of the Sierra Madre”, viz:
Then I just say “Q.E.D.”, and go back to collecting my government grant to study the effect of climate change on Man-In-The-Moon marigolds …
Willis Eschenbach (21:28:38) :
“Well, if I knew what the “Animal House parade” was, I suppose that would make sense … and I also don’t understand what a “jigsaw piece” has to do with the image. But then I was born yesterday, what do I know?”
Sorry for the obscure reference Willis. The reference to the jig saw piece was more of a flashback to all those PowerPoint presentations I sat through that dealt with team building or management solutions. (Time actually stood still during those sessions.) It stems from my natural aversion to Microsoft Clipart. My therapist is helping me deal with it.
On the Willis Eschenbach and Walt Meyer climate debate
by Arno Arrak
I found the point counter point questions of Willis Eschenbach (March 31) and Walt Meyer (April 8) interesting and illuminating. Eschenbach says he wants to “…detail my own beliefs about the climate and how it works.” Meyer then provides, as best he can, “…the current thinking of most scientists working in the various aspects of climate science.” Reviewing these questions in my mind I realized how much misinformation is out there and how far from the truth current thinking is. Below I will try to correct that with comments as needed and will stay with the numbering of the questions. By their nature some questions require a direct response from me. My information is based on research I did for “What Warming?” now available on Amazon.com. Al Gore made me do it. Here we go.
Question 1: Does the earth have a preferred temperature which is actively maintained by the climate system?
This question smacks of Lovelock’s “Gaia” hypothesis. It is true that the “faint young sun” paradox has yet to be explained but I am not ready to go with either Willis or Lovelock on this. Walt Meyer is right that it is not relevant to the existence or otherwise of AGW.
Question 2: Regarding human effects on climate, what is the null hypothesis?
Both agree to a null hypothesis that any changes in climate are due to natural variations. But Walt Meyer adds null hypothesis 2 (NH2) which brings in a historical perspective, that the past is the key to the future.
Question 3: What observations tend to support or reject the null hypothesis?
Willis can’t find anything in the record that is in any way unusual or anomalous and rightly points out that the Medieval Warm period was both widespread and warmer than the present. I agree with him. But Walt Meyer steps up and gives us a grab-bag of climate lore to overthrow the null hypothesis. Some of these things are just plain wrong: Pinatubo, for instance, did not depress global temperature as he and others claim because its cooling was restricted to the stratosphere and never reached ground level. But James Hansen came out with a GISS climate model just for Pinatubo and promised to “…estimate the predicted global cooling on such practical matters as the severity of the coming Soviet winter and the dates of cherry blossoming next spring…” Intended, no doubt, for that year’s issue of the “Collective Farmers’ Almanac.” Walt goes on from there and states that “…we are seeing indications that the climate is being affected by changing concentrations of greenhouse gases, primarily CO2.” That is complete nonsense: concentration of a gas and its effect on temperature are two different things. To prove existence of greenhouse effect not just in the laboratory but in nature you must be able to demonstrate that partial pressure of carbon dioxide and air temperature change in parallel. If you cannot do that your hypothesis is false. And you must prove that it is actually happening now, today, and not in some geologic past. That is your obligation because IPCC says it is true and makes recommendations based upon it. I see no sign that it has happened anytime since 1978 when satellites first began to measure temperature. Nevertheless, believing IPCC to be correct, the EPA has declared CO2 to be a pollutant and Congress has gone crazy and passed a cap and trade law. I can demonstrate the complete falsity of this belief from climate data. We know from satellite and other sources that from 2002 to 2007 world temperatures did not change while CO2 partial pressure kept on increasing. On top of that a substantial cooling followed in 2007 which bottomed out in 2008. It is totally impossible to explain any of this by the greenhouse effect. Knowing that this spells trouble for their theory Keenlyside has come out with damage control. He claims that natural factors like the Gulf Stream may have interfered with warming but not to worry, warming will be back in fifteen years. Fifteen years? If non-carboniferous factors have been in charge of world temperature since 2002 and will continue to be so for the next fifteen years then that greenhouse theory of yours sure as hell isn’t working and you might as well get rid of it. Keenlyside is just fighting a rearguard action, promising that warming will be back to keep the faithful happy. But Walt still has eight more points to make after his greenhouse claims and he lists them. As he himself says, they may be completely unrelated to the GHG’s in the atmosphere and they are.
Question 4: Is the globe warming?
The question is overly broad because a time frame is not specified. I choose to limit the observational time frame to the satellite era for which reliable temperature measurements exist. Satellites measure Oxygen microwave emission line intensities from the lower troposphere which are thermally excited and hence a proxy for local air temperature. These are polar orbiting satellites that sample the entire globe uniformly and are not subject to site selection bias as all ground-based measurements are. The most recent global warming before the beginning of the satellite era lasted a century and brought us out of the Little Ice Age. It ended with the start of World War II. From that point on until 1998 the climate was stable or even cooled a bit and some speculation about a coming ice age was published. For the last twenty years of this period satellite records are also available. But those same twenty years are shown by NASA, NOAA, and the Met Office as a period of rising temperatures. How is this possible? Satellite record shows only a multi-year temperature oscillation, up and down by half a degree, but no rise until 1998 (Figure1.)
Figure 1. Data from two satellite systems – UAH (University of Alabama Huntsville) and RSS (Radiation Sensing Systems) – plotted on a common curve.
There are five such cycles within that twenty year period and they are not random but correlate with the ENSO system in the Pacific. This is very different from a steady warming. It is clear that there was no warming and that all three curves showing it are cooked. As in falsified. It is pure scientific fraud but in the middle of this period James Hansen gets up in front of the Senate and testifies that global warming has started and that carbon dioxide we are putting into the air is its cause. Their fake warming starts suddenly about 1977 but checking the Mauna Loa carbon dioxide curve does not show a corresponding increase in carbon dioxide that laws of physics require. Hence, both claims made by Hansen in 1988 are false. Nevertheless, his testimony sparked the establishment of the IPCC, which was in the planning stages, as well as the Kyoto and Copenhagen agendas that were to follow. And now consider this: without Hansen’s warming there was no greenhouse warming at all in the twentieth or the twenty-first centuries. Greenhouse warming has simply never been observed, then or since. This does not mean that there has not been any warming. Real warming did start when the 1998 super El Nino showed up. But its cause was not carbon dioxide in the air but a storm surge in the Indo-Pacific region that brought warm water of the Indo-Pacific Warm Pool to the start of the equatorial countercurrent near New Guinea. The countercurrent then carried it to South America where it spread out and caused the super El Nino we observed. That is the regular route of all El Ninos we get. The one-time global temperature increase from that super El Nino was a full degree Celsius, more than the recorded temperature increase of the entire twentieth century. Its left-over warm water was responsible for the twenty-first century high, a run of six warm years from 2002 to 2007. Most of them were among the top ten and collectively they made that decade the warmest on record. But temperature stagnated during this period while carbon dioxide kept going up at the rate it has been for the last fifty years. This drove the model-makers nuts who were feeding carbon dioxide into their models and expecting temperature increase from that. All that came to an end with a La Nina cooling in 2008 that Kevin Trenberth of CRU could not understand. It is actually simple: the La Nina signifies the resumption of the oscillatory climate of the eighties and nineties that NASA, NOAA, and the Met Office obliterated with their deception to get that late twentieth century warming on the books. From now on, look for an alternation of warm El Nino and cool La Nina periods like those that existed before 1998.
Question 5: Are humans responsible for global warming?
Both are wrong – humans are not warming the planet. As I pointed out above there is a criminal conspiracy pushing that lie that needs to be brought to justice.
Question 6: How are humans affecting the climate?
Both list greenhouse gases and other nonsense from literature, none of which are implicated for the simple reason that humans are not affecting the climate.
Question 7: How much of the post 1980 temperature change is due to human activities?
Walt: “…there is broad agreement that human-emitted CO2 has significantly contributed to temperature change.” Willis: ”…there is no indication that post 1980 temperature rise is in any way unusual.” I have already come down on this question but it is so important that we need to look at the details. You can find out what is going on by directly comparing satellite and land-based temperature curves. Let’s take, say, HadCRUT3 from the Met Office, and compare it to UAH MSU satellite data as in Figure 2.
Figure 2. UAH MSU satellite (red) and Met Office HadCRUT3 (blue) temperature curves compared. Observe how Met Office rising trend is achieved.
You notice right away that they start by cherry picking the El Nino peaks and then raising up the low La Nina temperatures in between. But this only works with the first four El Ninos. The fifth one is too low so it gets raised up bodily. The super El Nino is next and is gratefully incorporated even though it is non-carbonaceous in origin. The twenty-first century high, a run of warm years near the El Nino maximum, follows. But this is just not high enough for them so the entire right side of their graph gets raised up and floats above the satellite curve. NOAA is worse: while HadCRUT3 at least retains the greatly reduced La Nina valleys they stay with the peaks, jettison all low values in between, and raise up the twenty-first century high as well. NASA (Land-Ocean, from Hansen 2006) starts out exactly like Hadcrut3. But they don’t have the nerve to raise up peaks so these are all in place and so is the twenty-first century high. Only the super El Nino is off (too low) and their data point for 2005 is too high. In all cases the warming in the eighties and nineties has been manufactured by distortion from an originally horizontal and oscillating curve. What real warming there is comes from the super El Nino and its aftermath and is not carbonaceous. The answer to question 7 is thus: NONE AT ALL! This sustained and coordinated scientific fraud by guardians of global climate data is the only thing that presently holds up the claim that AGW is happening. Since it involves three organizations it is also a criminal conspiracy and should be internationally investigated. A climate Nuremberg perhaps?
Question 8: Does the evidence from climate models show that humans are responsible for changes in climate?
Walt has faith in models, Willis does not. Willis is correct – models are a Trojan horse for introducing secret bias and passing it off as a “scientific” fact. They consume huge amounts of supercomputer time that Uncle Sam pays for and produce worthless predictions expressing the prejudices of the modelers. But it did not start with climate models – the Club of Rome was first. They were concerned with the “predicament of mankind” and commissioned a world model from MIT to predict the future. It was published as “The Limits to Growth” by Meadows and Meadows in 1972. They predicted that the world would run out of oil in the nineties and that civilization would collapse in the twenty-first century. When this did not happen their true believers started to “update” it every ten years and may still be doing it for all I know. Pilkey and Pilkey-Jarvis have surveyed many such failed attempts to model natural processes, from predicting cod fishery yields, to environmental impact statements, climate forecasts, beach erosion problems, Yucca Mountain drainage, sea level rise, and more, and list their failure modes. Such models often involve approximations or guesstimates. They also may depend strongly on initial values which are poorly known but may have a strong influence on the outcome. Plus “adjustments” may be required to make them correspond to reality and these adjustments are nothing more than fudge factors. They are opaque to users and political pressure can be, and has been, exerted to get the “right” answer which is then passed off as a “scientific” fact. They have two words to describe all this: “Useless Arithmetic.”
Question 9: Are the models capable of projecting climate changes for 100 years?
Willis says “No.” but Walt fudges it for more than a page. His argument is statistical and verges on, but does not actually utilize, statistical mechanics. Statistical mechanics says that if there are millions of identical molecules the properties of the assembly converge on macroscopic observables. I cannot see this level of input uniformity in averaging climate data and have to reject his theory. And I don’t want to wait a hundred years either. But that won’t be necessary because the current models are all guaranteed to fail. For a starter, they are programmed to use the fake warming of the eighties and nineties as input to be extrapolated. And secondly, they all utilize atmospheric carbon dioxide to compute the greenhouse effect. Since there is no observable greenhouse effect they all spectacularly failed when the twenty-first century high and the 2008 cooling appeared. And since our future climate will be an oscillating climate similar to that of the eighties and nineties there is no hope that any of them can make any meaningful predictions from now on.
Question 10: Are current climate theories capable of explaining the observations?
Willis says no and he is right. Walt says yes if one includes the greenhouse gases. “Increasing greenhouse gases should result in increasing temperatures and that is what we have observed” he amplifies. This is incorrect. Only if temperature increases in step with CO2 concentration can we postulate a causal relationship, and this is not happening. Not only is the temperature not cooperating, it is positively contrarian when it decides to sit still as it did from 2002 to 2007, or decrease as it did in 2008 while CO2 kept increasing on its metalled ways of time past and time future.
Question 11: Is the science settled?
I have to say yes: science proves the absence of AGW.
Question 12: Is climate science a physical science?
Does it have to be a science? Why not call it a religion which it really is?
Question 13: Is the current peer-review system inadequate, and if so, how can it be improved?
The peer-review system is simply broken. No papers questioning the existence of anthropogenic global warming can be published. I know, for a year ago I submitted one to Science, Nature and PNAS and was turned down. I did not fail peer review, they simply did not dignify me with sending it out for peer review. No criticism, no explanation, no nothing. Wegman did a network analysis for the U.S. Congress and unearthed a tightly knit group of scientist that control publication. Climategate shows that they block publication of papers they do not like and threaten editors of journals who do not toe the line. The effectiveness of their grip on the system is shown by Naomi Oreskes who could not find any opposition to the “consensus” view in over nine hundred papers she surveyed.
Question 14: Regarding climate, what action (if any) should we take at this point?
The answer is simple: stop the insanity of fighting an imaginary danger. It is costly, irrational, and designed to destroy civilization as we know it. Let me give you some examples. The EU has declared that ten percent of its transport should use biofuels by 2020. I bet you did not know that this requires that seventy percent of its cropland should be devoted to producing nothing but biofuel. Grain prices are already sky high thanks to current projects and there have been food riots in poor countries as a result. For England this means using their entire present grain harvest for biofuel and requires her to import as much grain as she now grows. No one has any idea of where that grain will come from. Or take the windmills. Denmark is ahead of everyone in windmill land. But in 2002 they declared a moratorium on new windmill projects. Why? Because the wind does not blow steadily. They found that when the wind was light they had to buy expensive electricity from Germany. And when it was strong they had an excess on their hands. You cannot store it so they ended up selling it to Norway below their own cost. It was a lose-lose proposition and the Danish people are now paying the highest electricity rates in Europe. And if you think that windmills are carbon free think again. It turned out that because of the uncertainty of wind speeds the outputs of individual systems kept fluctuating and it was necessary to keep a conventional “spinning reserve” on hand to take up that unpredictable slack at a moment’s notice. They get approximately eight percent of their electricity from these windmills. The same amount of power could be supplied at far lower cost by just one conventional coal-fired power station. If the Waxman-Markey ever becomes law we are in for a whole lot of such irrational actions, all to fight a non-existent warming.
[Sorry – the figures did not come through in this format. AA]
7. Recession of most mountain glaciers around the globe
I know in recent years that it has been portrayed that nearly all glaciers are in retreat.
I came across The World Glacier Monitoring Service’s preliminary mass balance data for 2007/08 (the most recent year). It shows continuing overall mass loss from all monitored glaciers but interestingly about 1/3 advanced in that particular year.
http://www.geo.unizh.ch/wgms/mbb/sum08.html
Interesting graphs from Steve Goddard:
http://docs.google.com/View?id=ddw82wws_5998xrxhzhc
I’ll ask you straight up Willis.
Do you believe in the skill of RTE, radiative transfer equations, and what they tell us about how concentrations of various GHGs in the atmosphere govern the propagation of radiation.
Simple yes or no.
Willis Eischenbach says: So we don’t have “more confidence in our model” if we flip a coin a hundred times rather than ten times. We have 100% confidence in our model in both cases. We know for sure that the standard error will be smaller if we flip more times. We have 100% confidence that our model can tell us what the standard error is if we tell it how many times we are flipping the coin.
But what on earth does this have to do with climate models?
I may be way off here, but when I read Meier’s post, through the coin-toss stuff, into his “predictability feel-good” stuff, I assumed he was trying to build confidence, ala The Particle Physicists who use probability to define where an electron is at a point in space-time. He used a very simple, tangible, everyday system (coin-flip),showed how we can “feel good” about confidence intervals (indirectly), and then moved on to his climate models, begging us to “feel good” about their potential for predictability…the more we learn, the more likely they are to be taken seriously.
So, I don’t think he made a stretch at all, bridging the coin-flip with climate modeling.
I still happen to disagree with his conclusion, lol, based on everything else already commented here and elsewhere (climate models will NEVER be reliable predictors!), but I wish everyone would stop getting all “puffy-chested” about the coin-flip scenario. He used it as a thought-experiment, nothing more or less, get over it already.
I’ve gotten to the point that I don’t even bother reading posts when I find “Coin” in the initial scan. It’s boring. Move on.