Guest Post by Willis Eschenbach
Well, this has been a circuitous journey. I started out to research volcanoes. First I got distracted by the question of model sensitivity, as I described in Model Climate Sensitivity Calculated Directly From Model Results. Then I was diverted by the question of smoothing of the Otto data, as I reported on in Volcanoes: Active, Inactive, and Retroactive. It’s like Mae West said, “I started out as Snow White … but then I drifted.” The good news is that in the process, I gained the understanding needed to direct my volcano research. Read the first of the links if you haven’t, it’s a prelude to this post.
Unlike the situation with say greenhouse gases, we actually can measure how much sunlight is lost when a volcano erupts. The volcano puts reflective sulfur dioxide into the air, reducing the sunlight hitting the ground. We’ve measured that reduction from a variety of volcanoes. So we have a reasonably good idea of the actual change in forcing. We can calculate the global reduction in sunlight from the actual observations … but unfortunately, despite the huge reductions in global forcing that volcanoes cause, the global temperature has steadfastly refused to cooperate. The temperature hasn’t changed much even with the largest of modern volcanoes.
Otto et al. used the HadCRUT4 dataset in their study, the latest incarnation from the Hadley Centre and the Climate Research Unit (CRU). So I’ll use the same data to demonstrate how the volcanoes falsify the climate models.
Figure 1. Monthly HadCRUT4 global surface air temperatures. The six largest modern volcanoes are indicated by the red dots.
This post will be in four parts: theory, investigation, conclusions, and a testable prediction.
THEORY
Volcanoes are often touted as a validation of the climate models. However, in my opinion they are quite the opposite—the response of the climate to volcanoes clearly demonstrates that the models are on the wrong path. As you may know, I’m neither a skeptic nor a global warming supporter. I am a climate heretic. The current climate paradigm says that the surface air temperature is a linear function of the “forcing”, which is the change in downwelling radiant energy at the top of the atmosphere . In other words, the current belief is that the climate can be modeled as a simple system, whose outputs (global average air temperatures) are a linear function of the SUM of all the various forcings from greenhouse gas changes, volcanoes, solar changes, aerosol changes, and the like. According to the theory, you simply take the total of all of the forcings, apply the magic formula, and your model predicts the future. Their canonical equation is:
Change in Temperature (∆T) = Change in Forcing (∆F) times Climate Sensitivity
In lieu of a more colorful term, let me say that’s highly unlikely. In my experience, complex natural systems are rarely that simply coupled from input to output. I say that after an eruption, the climate system actively responds to reductions in the incoming sunlight by altering various parts of the climate system to increase the amount of heat absorbed by other means. This rapidly brings the system back into equilibrium.
The climate modelers are right that volcanic eruptions form excellent natural experiments in how the climate system responds to the reduction in incoming sunlight. The current paradigm says that after a volcano, the temperature should vary proportionally to the forcing. I say that the temperature is regulated, not by the forcing, but by a host of overlapping natural emergent temperature control mechanisms, e.g. thunderstorms, the El Nino, the Pacific Decadal Oscillation, the timing of the onset of tropical clouds, and others. Changes in these and other natural regulatory phenomena quickly oppose any unusual rise or fall in temperature, and they work together to maintain the temperature very stably regardless of the differences in forcing.
So with the volcanoes, we can actually measure the changes in temperature. That will allow us to see which claim is correct—does the temperature really follow the forcings, or are there natural governing mechanisms that quickly act to bring temperatures back to normal after disturbances?
INVESTIGATION
In order to see the effects of the volcanoes, we can “stack” them. This means aligning the records of the time around the volcano so the eruptions occur at the same time in the stack. Then you express the variations as the anomaly around the temperature of the month of the eruption. It’s easier to see than describe, so Figure 2 shows the results.
Figure 2. Stacked records of the six major volcanoes. Individual records show from three years before to five years after each eruption. The anomalies are expressed as variations around the temperature of the month of the eruption. The black heavy line shows the average of the data. Black vertical lines show the standard error of the average.
The black line is the average of the stacked records, month by month. Is there a signal there? Well, there is a temperature drop starting about six months after the eruptions, with a maximum of a tenth of a degree. However, El Chichon is clearly an outlier in this regard. Without El Chichon, the signal gets about 50% stronger.
Figure 3. As in Figure 3, omitting the record for El Chichon.
Since I’m looking for the common response, and digging to find the signal, I will leave out El Chichón as an outlier.
But note the size of the temperature response. Even leaving out El Chichon, this is so small that it is not at all clear if the effect shown is even real. I do think it is real, just small, but in either case it’s a very wimpy response.
To properly judge the response, however, we need to compare it to the expected response under various scenarios. Figure 3 shows the same records, with the addition of the results from the average models from the Forster study, the results that the models were calculated to have on average, and the results if we assume a climate sensitivity of 3.0 W/m2 per doubling of CO2. Note that in all cases I’m referring the equilibrium climate sensitivity, not the transient climate response, which is smaller. I have used the lagged linear equation developed in my study of the Forster data (first cite above) to show the theoretical picture, as well as the model results.
Figure 4. Black line shows the average of the monthly Hadcrut temperatures. Blue line shows the average of the modeled annual temperatures from the 15 climate models in the Forster paper, as discussed here. The red line shows what the models would have shown if their sensitivity were 2.4°C per doubling of CO2, the value calculated from the Forster model results. Finally, the orange line shows the theoretical results for a sensitivity of 3°C per doubling. In the case of the red and orange lines, the time constant of the Forster models (2.9 years) was used with the specified sensitivity. Tau ( τ ) is the time constant. The sensitivity is the equilibrium climate sensitivity of the model, calculated at 1.3 times the transient climate response.
The theoretical responses are the result of running the lagged linear equation on just the volcanic forcings alone. This shows what the temperature change from those volcanic forcings will be for climate models using those values for the sensitivity (lambda) and the time constant (tau).
Now here, we see some very interesting things. First we have the model results in blue, which are the average of the fifteen Forster models’ output. The models get the first year about right. But after that, in the model and theoretical output, the temperature decreases until it bottoms out between two and three years after the eruption. Back in the real world, by contrast, the average observations bottom out by about one year, and have returned to above pre-eruption values within a year and a half. This is a very important finding. Notice that the models do well for the first year regardless of sensitivity. But after that, the natural restorative mechanisms take over and rapidly return the temperature to the pre-eruption values. The models are incapable of making that quick a turn, so their modeled temperatures continue falling.
Not only do the actual temperatures return to the pre-eruption value, but they rise above it before finally returning to the that temperature. This is the expected response from a governed, lagged system. In order to keep a lagged system in balance, if the system goes below the target value for a while, it need to go above that value for a while to restore the lost energy and get the system back where it started. I’ll return to this topic later in the post. This is an essential distinction between governors and feedbacks. Notice that once disturbed, the models will never return to the starting temperature. The best they can do is approach it asymptotically. The natural system, because it is governed, swings back shortly after the eruption and shoots above the starting temperature. See my post Overshoot and Undershoot for an earlier analysis and discussion of governors and how they work, and the expected shape of the signal.
The problem is that if you want to represent the volcanoes accurately, you need a tiny time constant and an equally tiny sensitivity. As you can see, the actual temperature response was both much smaller and much quicker than the model results.
This, of course, is the dilemma that the modelers have been trying to work around for years. If they set the sensitivity of their models high enough to show the (artificially augmented) CO2 signal, the post-eruption cooling comes out way, way too big. If they cut the sensitivity way, way down to 0.8° per doubling of CO2 … then the CO2 signal is trivially small.
Now, Figure 4 doesn’t look like it shows a whole lot of difference, particularly between the model results (blue line) and the observations. After all, they come back close to the observations after five years or so.
What can’t be seen in this type of analysis is the effect that the different results have on the total system energy. As I mentioned above, getting back to the same temperature isn’t enough. You need to restore the lost energy to the system as well. Here’s an example. Some varieties of plants need a certain amount of total heat over the growing season in order to mature. If you have ten days of cool weather, your garden doesn’t recover just because the temperature is now back to what it was before. The garden is still behind in the total heat it needs, the total energy added to the garden this season is lower than it would have been otherwise.
So after ten days of extra cool weather, your garden needs ten days of warm weather to catch up. Or perhaps five days of much warmer weather. The point is that it’s not enough to return the temperature to its previous value. We also need to return the total system energy to its previous value.
To measure this variation, we use “degree-days”. A degree-day is a day which is one degree above from some reference temperature. Ten degree-days could be five days that are two degrees warmer than usual, or two days that are five degrees warmer than usual. As in the example with the garden, degree-days accumulate over time, with warmer (positive) degree days offsetting cooler (negative) degree days. For the climate, the corresponding unit is a degree-month or a degree year. To convert monthly temperature into degree-months, you simply add each months temperature difference from the reference to the previous total. The record of degree-months, in other word, is simply the cumulative sum of the temperature differences from the date of the eruption.
What does such a chart measure? It measures how far the system is out of energetic balance. Obviously, after a volcano the system loses heat. The interesting thing is what happens after that, how far out of balance the system goes, and how quickly it returns. I’ve left the individual volcanoes off of this graph, and only shown the stack averages.
Figure 5. Cumulative record of degree-months of energy loss and recovery after the eruptions. Circles show the net energy loss in degree-months four years after the eruption.
Remember that I mentioned above that in a governed system, the overshoot above the original temperature is necessary to return the system to its previous condition. This overshoot is shown in Figure 3, where after the eruptions the temperatures rise above their original values. The observations show that the earth returned to its original temperature after 18 months. The results in Figure 5 show that it took a mere 48 months to regain the lost energy entirely. Figure 5 shows that the actual system quickly returned to the original energy condition, no harm no foul.
By contrast, the models take much larger swings in energy. After four years, the imbalance in the system is still increasing.
Now folks, look at the difference between what the actual system does (black line) and what happens when we model it with the IPCC sensitivity of 3° per doubling, or even the model results … I’m sorry, but the idea that you can model volcanic eruptions using the current paradigm simply doesn’t work. In a sane world, Figure 5 should sink the models without a trace, they are so very far from the reality.
We can calculate the average monthly energy shortage in the swing away from and back to the zero line by dividing the area under the curve by the time interval. Nature doesn’t like big swings, this kind of response that minimizes the disturbance is common in nature. Here are those results, the average energy deficit the system was running over the first four years.
Figure 6. Average energy deficit over the first four years after the eruption.
In this case, the models are showing an average energy deficit that is ten times that of the observations … and remember, at four years the actual climate is back to pre-eruption conditions, but the models’ deficit is still increasing, and will do so for several more years before starting back towards the line.
CONCLUSIONS
So what can we conclude from these surprising results?
The first and most important conclusion is that the climate doesn’t work the way that the climate paradigm states— it is clearly not a linear response to forcing. If it were linear, the results would look like the models. But the models are totally unable to replicate the rapid response to the volcanic forcings, which return to pre-existing temperatures in 18 months and restore the energy balance in 48 months. The models are not even close. Even with ridiculously small time constant and sensitivity, you can’t do it. The shape of the response is wrong.
I hold that this is because the models do not contain the natural emergent temperature-controlling phenomena that act in concert to return the system to the pre-catastrophic condition as soon as possible.
The second conclusion is that the observations clearly show the governed nature of the system. The swing of temperatures after the eruptions and the quick return of both temperature and energy levels to pre-eruption conditions shows the classic damped oscillations of a governed system. None of the models were even close to being able to do what the natural system does—shake off disturbances and return to pre-existing conditions in a very short time.
Third conclusion is that the existing paradigm, that the surface air temperature is a linear function of the forcing, is untenable. The volcanoes show that quite clearly.
There’s probably more, but that will do for the present.
TESTABLE PREDICTION
Now, we know that the drops in forcing from volcanoes are real, we’ve measured them. And we know that the changes in global temperature after eruptions are way tiny, a tenth of a degree or so. I say this is a result of the action of climate phenomena that oppose the cooling.
A corollary of this hypothesis is that although the signal may not be very detectable in the global temperature itself, for that very reason it should be detectable in the action of whatever phenomena act to oppose the volcanic cooling.
So that was my prediction, that if my theory were correct, we should see a volcanic signal in some other part of the climate system involved in governing the temperature. My first thought in this regard, of course, was the El Nino/La Nina pump that moves warm Pacific water from the tropics to the poles.
The snag with that one, of course, is that the usual indicator for El Nino is the temperature of a patch of tropical Pacific ocean called the Nino3.4 area. And unfortunately, good records of those temperatures go back to about the 1950s, which doesn’t cover three of the volcanoes.
A second option, then, was the SOI index, the Southern Oscillation Index. This is a very long-term index that measures the difference in the barometric pressures of Tahiti, and Darwin, Australia. It turns out that it is a passable proxy for the El Nino, but it’s a much broader index of Pacific-wide cycles. However, it has one huge advantage. Because it is based on pressure, it is not subject to the vagaries of thermometers. A barometer doesn’t care if you are indoors or out, or if the measurement location moves 50 feet. In addition, the instrumentation is very stable and accurate, and the records have been well maintained for a long time. So unlike temperature-based indices, the 1880 data is as accurate and valid as today’s data. This is a huge advantage … but it doesn’t capture the El Ninos all that well, which is why we use the Nino3.4 Index.
Fortunately, there’s a middle ground. This is the BEST index, which stands for the Bivariate ENSO Timeseries. It uses an average of the SOI and the Nino 3.4 data. Since the SOI has excellent data from start to finish, it kind of keeps the Nino3.4 data in line. This is important because the early Nino3.4 numbers are from reanalysis models in varying degrees at various times, so the SOI minimizes that inaccuracy and drift. Not the best, but the best we’ve got, I guess.
Once again, I wanted to look at the cumulative degree-months after the eruptions. If my theory were correct, I should see an increase in the heat contained in the Pacific Ocean after the eruptions. Figure 6, almost the last figure in this long odyssey, shows those results.
Figure 6. Cumulative index-months of the BEST index. Positive values indicate warmer conditions. Krakatoa is an obvious outlier, likely because it is way back at the start of the BEST data where the reconstruction contains drifts.
Although we only find a very small signal in the global temperatures, looking where the countervailing phenomena are reacting to neutralize the volcanic cooling shows a clearer signal of the volcanic forcing … in the form of the response that keeps the temperature from changing very much. When the reduction in sunlight occurs following an eruption, the Pacific starts storing up more energy.
And how does it do that? One major way is by changing the onset time of the tropical clouds. In the morning the tropics is clear, with clouds forming just before noon. But when it is cool, the clouds don’t form until later. This allows more heat to penetrate the ocean, increasing the heat content. A shift of an hour in the onset time of the tropical clouds can mean a difference of 500 watt-hours/m2, which averages over 24 hours to be about 20 W/m2 continuous … and that’s a lot of energy.
One crazy thing is that the system is almost invisible. I mean, who’s going to notice if on average the clouds are forming up a half hour earlier? Yet that can make a change of 10 W/m2 on a 24-hour basis in the energy reaching the surface, adds up to a lot of watt-hours …
So that’s it, that’s the whole story. Let me highlight the main points.
• Volcanic eruptions cause a large, measurable drop in the amount of solar energy entering the planet.
• Under the current climate paradigm that temperature is a slave to forcing with a climate sensitivity of 3 degrees per doubling of CO2, these should cause large, lingering swings in the planet’s temperature.
• Despite the significant size of these drops in forcing, we see only a tiny resulting signal in the global temperature.
• This gives us two stark choices.
A. Either the climate sensitivity is around half a degree per doubling of CO2, and the time constant is under a year, or
B. The current paradigm of climate sensitivity is wrong and forcings don’t determine surface temperature.
Based on the actual observations, I hold for the latter.
• The form (a damped oscillation) and speed of the climate’s response to eruptive forcing shows the action of a powerful natural governing system which regulates planetary temperatures.
• This system restores both the temperature and the energy content of the system to pre-existing conditions in a remarkably short time.
Now, as I said, I started out to do this volcano research and have been diverted into two other posts. I can’t tell you the hours I’ve spent thinking about and exploring and working over this analysis, or how overjoyed I am that it’s done. I don’t have a local church door to nail this thesis to, so I’ll nail it up on WUWT typos and all and go to bed. I think it is the most compelling evidence I’ve found to date that the basic climate paradigm of temperatures slavishly following the forcings is a huge misunderstanding at the core of current climate science … but I’m biased in the matter.
As always, with best wishes,
w.
APPENDICES
UNITS
Climate sensitivity is measured in one of two units. One is the increase in temperature per watt/m2 of additional forcing.
The other is the increase in temperature from a doubling of CO2. The doubling of CO2 is said to increase the forcing by 3.7 watts. So a sensitivity of say 2°C per doubling of CO2 converts to 2/3.7 = 0.54 °C per W/m2. Using the “per doubling” units doesn’t mean that the CO2 is going to double … it’s just a unit.
DATA
Let’s see, what did I use … OK, I just collated the Otto and Forster net radiative forcings, the Forster 15 model average temperature outputs, the GISS forcing data, and the dates of the eruptions into a single small spreadsheet, under a hundred k of data, it’s here.
METHOD
The method depends on the fact that I can closely emulate the output of either individual climate models, or the average output of the unruly mobs of models called “ensembles” using a simple lagged linear equation. The equation has two adjustable parameters, the time constant “tau” and the climate sensitivity lambda. Note that this is the transient sensitivity and not the equilibrium sensitivity. As you might imagine, because the earth takes time to warm, the short-term change in temperature is smaller than the final equilibrium change. The ratio between the two is fairly stable over time, at about 1.3 or so. I’ve used 1.3 in this paper, the exact value is not critical.
Using this lagged linear equation, then, I simply put in the list of forcings over time, and out comes the temperature predictions of the models. Here’s an example of this method used on the GISS volcanic forcing data:
Lambda (a measure of sensitivity) controls the amplitude, while tau controls how much the data gets “smeared” to the right on the graph. And sad to say, you can emulate any climate model, or the average of a bunch of models, with just that … see my previous posts referenced above for details about the method.
INDIVIDUAL RECORDS
Here are the most recent six eruptions, eruptions that caused large reductions in the amount of sunlight reaching the earth, with the date of the eruptions shown in red.
Even Krakatoa, which was supposed to be the cause of the “Year Without A Summer”, didn’t raise a ripple on the global scale.
That’s an amazing analysis Willis. As you say, the clearest evidence yet that the models not only don’t get the numbers right but don’t even get the form of response right. You should look to get this published.
Great post Willis. I think you’ve hit the nail squarely on the head. One possible point why Krakatoa creates a different effect (Fig 6) could be dust. Didn’t it throw up enough dust to create red sunsets in London for months after (a la Turner paintings)? Now i don’t know about the others in that respect and I guess it depends on the VEI.
Would dust and sulphur have different but synergistic effects? Does it depend on the height of the ejecta? Does it depend on the latitude of the volcano? Does this in turn affect how long the dust/sulphur stays in the system and how far and how fast it is spread around the globe?
These are just some of the questions forming in my head after reading this. I have seen discussions of such elsewhere and I’m sure you will have considered them. I love things that make me think. Thank you.
Like you say –
Often answers are right in front of us – for those who take the time to notice.
Willis’ analysis is very interesting. Thanks Willis.
It seems to show the impact of volcanoes is not at all large.
There aren’t a huge number of large volcanoes going off around
the world at the same time. They tend to be solitary phenomena.
Why should a volcano be considered to have much effect on the
global climate?
It’s a point source.
Some of its output may meander around the globe but not most
of it. It falls to the surface within a few hundreds of kilometers from
its source.
Does that which does stay airborne, mix evenly and permeate every
where or does it track according to prevailing winds/air-streams?
If the latter, then its impact can’t be anything but relatively minor.
We live in a gas medium.
We measure “surface” temperature at around 2 metres above the ground.
Any gas will rise when its temperature is increased.
No wonder there is hardly any change in measured temperatures after eruptions.
I’m about to light a big bon fire in the front paddock. I’ll be sitting around that fire with some friends eating and drinking. My side that’s facing the fire will be toasty warm, whilst the side away from the fire will be cool.
ALL the air that’s warmed by the fire will quickly rise and move away from me, to be replaced by cool air. A small, very local breeze will be created.
Even though my bon fire is about 2 metres in diametre (as much as my local council will allow) and not quite a metre high, it will generate some very high temperatures. However only a couple of metres away from the fire, there’ll be no difference in the air temperature at all. Any gas molecules warmed by the fire will quickly shoot up up and away.
We can not expect to measure an increase in the temperature of an unconstrained gas. It doesn’t “stand still” long enough for us to measure it.
“Either the climate sensitivity is around half a degree per doubling of CO2” This agrees with what Modtran derives. So I am going with A.
Love it! Willis, you have a talent for explaining your reasoning in clear, concise terms that just about anyone can understand. I don’t know if you are correct, but at least you have provided your argument and its underlying reasons simply.
Brilliant. Very convincing and clear. Well done. I’m convinced. Until a better explanation comes along I’m going to go with your one.
The next step then is to ask what CAN cause the climate to change if it is governed as you describe. Because as we all know climate can and does change. For example what could cause the LIA or the late 20th century warming if the system is indeed governed. A governed system is likely to be quite insensitive to changes in the input energy. To get it to change you would need something that “tweaks” the settings on the governor.
You suggest that the governor is the timing of daily cloud formation in the tropics. So the question becomes what could tweak the timing and speed at which clouds form each day in the tropics? Which brings us back to the solar wind and galactic cosmic rays. The difference under your theory of a governed system is that we understand now why the climate seems to be so sensitive to this change. Unlike other changes to forcing which have little effect this change turns the knob on the thermostat.
Willis,
“Their canonical equation is:
Change in Temperature (∆T) = Change in Forcing (∆F) times Climate Sensitivity
In lieu of a more colorful term, let me say that’s highly unlikely.”
Whose canonical equation? Could you give a reference? Certainly no GSM works that way.
Superficially, this seems pretty convincing. Thanks for the work that’s gone into this.
Outstanding analysis, Mr. Eschenbach, thank you very much.
Certainly Nick. Glad to help you with your obviously sincere hunt for enlightenment. I suggest you simply search for a definition of climate sensitivity. For example one can be found at http://en.wikipedia.org/wiki/Climate_sensitivity however you can find the same equation in plenty of places. Indeed anyone who uses climate sensitivity must define it and in doing so will write down an equation pretty much exactly like the one above. Oh it might be written in the form
Sensitivity = (∆T)/(∆F)
but I’m sure a clever guy like you can see that these are the same.
I was going to ask if you could work it backwards and derive sensitivity from it, but I guess you did and got a half degree.
A. Either the climate sensitivity is around half a degree per doubling of CO2, and the time constant is under a year,
or
B. The current paradigm of climate sensitivity is wrong and forcings don’t determine surface temperature.
I do think that the or needn’t be so exclusive and that or / and is valid. Myself, I go for and.
Very clearly explained as always. However, removing a data point (El Chichon) when all you have is 6 such data points, is a very serious decision. It’s not clear to me that El Chichon is that much of an outlier in Figure 2. It’s pretty much in the middle of the pack most of the time. Pinatubo is more consistently at the bottom, and Novarupta is low before the eruption and very high after. You say you’re dropping it because you’re “looking for a signal” but that’s the same reason Briffa uses for dropping out Khadyta River from Yamal.
So what happens if you leave El Chichon in? It weakens the “signal” to the point where one wonders if there is any signal at all. Then when you get to the stacked El Nino index (Figure 6), you drop out yet another volcano (Krakatoa). You’ve now dropped 33% of your data! Suppose you added El Chichon to this Figure 6–what would it look like? And then suppose you draw your black line using all the data–what would that look like? Not asking you to change your conclusions, but just provide all the data for your readers.
Reality can be a real swine when your pet theory is shown to be false.
Good post Willis.
Willis, I agree with you, the effect on temperature from these volcanos have been rather small. But the explanation via the BEST el Nino index looks strange to me (figure 6). The index starts increasing 18 months before the eruption. Is the index smoothed (3 years)?
Another detail, the “year without summer” occurred after the eruption of Tambora in 1815.
“Ian H says: May 25, 2013 at 2:36 am”
Ian,
Your Wiki reference says:
“For a coupled atmosphere-ocean global climate model the climate sensitivity is an emergent property: it is not a model parameter, but rather a result of a combination of model physics and parameters. By contrast, simpler energy-balance models may have climate sensitivity as an explicit parameter.
Δ T = λ RF”
A simpler model. That doesn’t make it a canonical equation.
In fact, if you look up the definitions of the various sensitivities, they relate to particular situations. Equilibrium response to a move from one fixed forcing to another. Or TCR, which mentions a period of seventy years. None entails a claim that Δ T is proportional to Δ F with constant factor.
Gregory and Forster 2008 do say something like that:
“Observations and AOGCM simulations of twentieth century climate change, and AOGCM experiments with steadily increasing radiative forcing F, indicate a linear relationship F = ρΔT, where ΔT is the global mean surface air temperature change and ρ a constant ‘‘climate resistance’’.”. But that’s an observation, not a presumption. They show the results, with scatter.
And when it comes to prediction, they say (6.2):
“If F = ρΔT holds, we can use ρ to make projections of ΔT given F.”
Doesn’t sound so canonical. They go on to describe some situations where ρ might be constant.
Great post, clever theory, but one small error.
for Krakatau read Tambora, much bigger bang and source of year without summer
Probably useful to subtract the 10-20 temperature year trend spanning each volcanic eruption, to better isolate the impact of the volcano. Perhaps also think about a second variable for size of volcano (obviously not all equal)
That said bravo. This is a very simple and powerful reproof for status quo climate modelling (at least of volcanos and aerosols), and will be hard to argue against. Worthy of an academic paper.
Another superb piece of work by Willis. When fully developed and refined, this simply screams out to be a peer-reviewed research paper in a science journal (if any real science journals are left).
I would tend to go for Willis’ first option. But in a sense it doesn’t matter too much: whether one option or the other is true, or both, the final result is the same: the warming caused by CO2 is very small and possibly negligible. This is also consistent with the lack of warming for almost two decades, the fact that almost half of the 20th century warming occurred when there wasn’t enough CO2 (1900 to 1945), and the evidence from the ice cores (CO2 follows the temperature and not the other way around).
One thought did occur, though. The whole thrust of these investigations is into the very largest eruptions, for obvious reasons. But volcanoes are erupting all the time and presumably more eruptions occur in some years compared to others, so a graph of eruption intensity (a bit like the ACE measurement for hurricanes) might have some structure over the years, as opposed to random noise. If so, could there be any correlation between mean volcanic activity and global climate. If so, this could provide more evidence on this question. It would also remove problems with small numbers of data points and the need to remove data points that look like outliers.
By the way, if anyone can give a link to any AVE data (Accumulated Volcanic Energy) I’d be very grateful.
Anyway, many thanks to Willis for an excellent, beautifully written and thought-provoking piece of research.
It does rather look like yet another dagger in the heart of AGW!
Chris
I think this is a strong challenge to the orthodoxy regarding climate sensitivity, but the posited correction mechanism doesn’t appear to cohere with the data shown. The claim is that “When the reduction in sunlight occurs following an eruption, the Pacific starts storing up more energy.” But the timing seems to challenge this assertion – in Figure 6 the change in the slope of the cumulative Best Index occurs about 20 months BEFORE the eruptions, and there is no change in slope around the time of the eruption. Is the implication that the Pacific starts storing energy in anticipation of the eruption, or have I misunderstood the proposed correction phenomenon (or its measurement)?
Willis,
“First we have the model results in blue, which are the average of the fifteen Forster models’ output.”
I’ve looked through your post, appendices, the spreadsheet, and Forster’s paper, and I still can’t work out what this means. Are they actually outputs from the models? Or are they outputs from your model of the models?
Nick Stokes says:
May 25, 2013 at 2:18 am
Willis,
“Their canonical equation is:
Change in Temperature (∆T) = Change in Forcing (∆F) times Climate Sensitivity
In lieu of a more colorful term, let me say that’s highly unlikely.”
Whose canonical equation? Could you give a reference? Certainly no GSM works that way.
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It doesn’t matter “how they work”, Nick, if that’s the result they give. Which it is. I believe there was a post here over the past week or so doing the sums on that so I won’t bother repeating them.
One of the first concepts taught in computer modelling is the “black box”. Essentially, any model can be replaced by any other model provided they both give the same output for the same inputs. If they do then they are “functionally equivalent” and it doesn’t matter in the least how they transform the input to the output.
It’s the principle used in many of the old “think of a number” tricks – which pre-date computers by a very long time. You get someone to choose a number (the input) and then ask them to do complicated maths with it (effectively running it through a model) over several stages. You can then tell them what the input was from their answer (the output). They work because all those complicated steps in your “model” can be replaced by a much simpler, but functionally equivalent, equation that you can do instantly in your head.
However the GCMs “work” internally, their (smoothed) output for any initial input forcing can be obtained using Change in Temperature (∆T) = Change in Forcing (∆F) times Climate Sensitivity, iterated over time.
Since we’re told not to worry about all those little wiggles of variablilty, because they’re just weather and it’s the long-term (smoothed) change that matters, the models are functionally equivalent to that cannonical equation.
Excellent article Willis. The response to volcanoes is what I’ve been saying for well over a year. Thanks for taking the effort to put all this into a coherent whole.
Full credit to you for your “governor” hypothesis and the mechanism, I think that is the key as you say. The system is governed by NON-linear feedbacks not the simplistic linear feedback that is behind all the models.
Excellent.
Delighted to see this challenge to the device at the heart of GCMs. I refer to that gift to the programmers involved of the use of ‘external forcing’ as a wheeze to step around the difficulties of actually modelling CO2 or aerosols or any of the other things on the list of ‘forcings’. Willis is focusing on the crude assumption also deployed – what he refers to as their canonical equation above. Even with it, the variability of the outputs, even from apparently pampered models, is very large indeed. Take it away, and suddenly the well from which so many grandiose prognostications about this that and the other would dry up, and many a would-be prophet would be deprived of fuel for their lucrative scaremongering.
Nick Stokes says: May 25, 2013 at 4:24 am
“Are they actually outputs from the models?”
I see now that they are the ones you digitized from the Otto et al paper; I couldn’t find the data in the Forster paper. Incidentally, I found a version of the Forster paper as published here.
In the middle of marking university entrance individual studies/investigations. I would not give this a good mark. There are lots of confounding factors not taken into account, for example: how long do the particles erupted into the atmosphere remain there? What criteria are used for selecting the eruptions (there were twelve VEI 5 or 6 eruptions in the 20th century)? 14 eruptions would have given a better sample. Are the results statistically significant?
What effect did the eruption of Mount Hudson have in such close temporal proximity to Mt Pinatubo (VEI 5+ and 6 respectively)? Can you unpick the effects of the two eruptions? How much material was erupted into the atmosphere at these eruptions and the other eruptions? Can we see local effects and how far do those effects extend?
The conclusion needs to have strong valid evidence to support it which appears to be missing. Because unsubstantiated assumptions are made in this post, the assertions remain speculative at best and most probably wrong. There will be those that pick that last sentence out for criticism so I shall answer it now. Firstly, taking a simple equation that models part of the behaviour of the climate system and showing it might be wrong does not invalidate all climate models. I believe there are 19 models referenced by the IPCC. Even if this equation is fundamental to them all, the evidence here does not invalidate it.
I know nothing of the author but I would suspect they have not used their full scientific training in the production of this short article. Had they done so, they would have spent a considerable time looking in detail at the possible confounding factors surrounding the global temperatures for each of these eruptions and those that were left out.
I might point out that different eruptions, and different types of volcanos, produce significantly different volumes of SO2. Pinatubo was in fact quite rich in the amount of SO2 spewed into the atmosphere for its relative size. There is also the issue of tropical versus arctic eruptions, eruptions in the arctic produce less effect on sunlight because the emitted S02 travels far less around the globe. Not sure if these effects your analyses.
There is a book ‘Eruptions that shook the world’ which gives a good summary of volcanism, and of course looks at many historical eruptions. There is some good stuff on investigations into eruptions which show up in the ice record, but where it is still not known which volcanoes caused them. Krakatoa appears to have a long history, as does the Pompeii area and a few in the Kurils.
Also, the ‘year without a summer’ was 1816 with Tambora in Sumbawa, not Krakatoa.
Having applauded the effort, now to point out some inaccuracies and short comings that I noted.
Excluding El Chicnon is a bit dubious. It is worth pointing out that it is the only one that does seem to show a possible cooling signal. It would be more instructive to look at why that is and whether it is simple confounded with some other independent effect that happened at about the same time.
Looking at LOD we see there is a change around El Chicnon. Is that a confirmation of a real volcanic cooling or witness to something else causing an “apparent” volcanic cooling?
http://climategrog.wordpress.com/?attachment_id=274
As I pointed out in your “spot the volcano” post last year, once clear effect of volcanoes is warmer winters. In fact if we split CRUTem4 into tropical and ex-tropical we can see this clearly for both Chichon and Pinatubo.
http://climategrog.wordpress.com/?attachment_id=270
There is a very strong warming due El Chicnon so don’t be too quick to regard it as an outlier.
Joe says: May 25, 2013 at 4:36 am
“However the GCMs “work” internally, their (smoothed) output for any initial input forcing can be obtained using Change in Temperature (ΔT) = Change in Forcing (ΔF) times Climate Sensitivity, iterated over time.”
That’s actually not true, and Willis has shown that it isn’t. In his version, ΔT is quite well approximated by an exponentially smoothed ΔF, with time constant of about three years. Considerably lagged.
Here’s what Otto et al say – it’s their eq 2:
“Both equations (1) and (2) assume constant linear feedbacks and (2) further assumes that the ratio of ΔQ to ΔT for the observed period is the same as that at year 70 of a simulation in which atmospheric CO2 levels increase at 1% per year, which is approximately the case over the past few decades if we exclude periods strongly affected by volcanic eruptions (see Supplementary Fig. S2).”
(my bold) – lot of caveats.
Now looking at SST, we see no notable effect in terms of warming / cooling but do see a reduced annual variation after Pinatubo causes a negative “anomaly” : warmer winters cooler summers for about three years. There is a slight dip but that process was already underway at least a year beforehand.
http://climategrog.wordpress.com/?attachment_id=271
This failure to account for existing trends is often the cause of false attribution of cooling to volcanoes. Some way is needed to remove this.
Your stacking idea is one crude way to hope that different periods will cancel out to reveal volcanic signal. This is good simple way to get a first look but you can’t start removing “outliers” otherwise you are open to selection bias.
Why are you using ECS to calculate a transient response ?!
The climate responds to volcanoes as if the feedbacks are actually negative versus the positive that is assumed in the global warming movement.
The climate responds as if the total of all feedbacks is negative 70% versus the 55% positive that global warming theory is based on.
@Nick Stokes
The Forster’s paper gives a 15-models mean for time from 1850 so I think Willis just did the with this output as for real temperatures when Figure 2. As for the red and yellow curves, he shows that the output of Foster models are quite the same as the one of a simple linear model in this article http://wattsupwiththat.com/2013/05/21/model-climate-sensitivity-calculated-directly-from-model-results/, so he surely did exactly that
“Degree days: What does such a chart measure? It measures how far the system is out of energetic balance. ”
No, that’s wrong. Temperature is a measure of heat (energy) . Degree.days is an integral of energy in some units like joule.second , it is not a measure of energy.
If a system comes back to the same temperature is has recovered to the same energy content.
The plot is still useful to look at differences in behaviour.
“Remember that I mentioned above that in a governed system, the overshoot above the original temperature is necessary to return the system to its previous condition. ”
Again you are misunderstanding the physics a bit here. This is the response of an “under-damped” system. An over-damped system will also return without overshoot but will return. Both are “governor” type systems with non-linear feedback.
It is NOT necessary to have overshoot to have a governor, but a bit of over shoot will recover quicker. Too much and it will show multiple oscillations before settling.
A linear negative feedback will NEVER come back it will settle to a new equilibrium with an exponential decay. GCMs responses only comes back up at all because of a) GHG and b) other +ve forcings which they have that produce a positive effect.
That does not alter your fundamental point but you need to better understand all this in order to avoid being dismissed.
Nick Stokes says:
May 25, 2013 at 4:56 am
Joe says: May 25, 2013 at 4:36 am
“However the GCMs “work” internally, their (smoothed) output for any initial input forcing can be obtained using Change in Temperature (ΔT) = Change in Forcing (ΔF) times Climate Sensitivity, iterated over time.”
That’s actually not true, and Willis has shown that it isn’t. In his version, ΔT is quite well approximated by an exponentially smoothed ΔF, with time constant of about three years. Considerably lagged.
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No, Willis showed that it’s quite well approximated using sensitivity and lag. The lag has no bearing on the magnitude of the response, only on its timing. So the fundamental formula is still as above, with the lag (as its name implies) simply delaying things slightly.
I’m sure you understand that really.
Nick.
You point out that sensitivity is computed in some models and an explicit parameter in some simpler models and claim that this somehow renders the equation non-canonical. A canonical equation is simply an equation that is so by definition. This equation is the defining equation for sensitivity so it is canonical. Are we going to end up arguing about the meaning of the word canonical? That seems to be a fairly pointless argument to have.
Any function can be locally approximated by a linear one (\cite{Newton}). If temperature is expressed as a function of forcing (of any kind) then it can be locally approximated by the linear equation Willis used. The real issue is whether or not climate models predict temperature as a function of forcing. I would be astonished to see you try to defend the position that climate models do not in general take the point of view that temperature is a function of forcing. In fact you have just told me that ” … AOGCM simulations of twentieth century climate change, and AOGCM experiments with steadily increasing radiative forcing F, indicate a linear relationship F = ρΔT, where ΔT is the global mean surface air temperature change and ρ a constant ‘‘climate resistance”. So clearly most do predict that temperature is a function of forcing.
If you want to argue the point I will concede that a GCM need not be limited to expressing temperature as a function of forcing. Indeed a GCM could even be tweaked to act according to the mechanism that Willis describes with the onset of cloud formation in the tropics having a strong temperature dependence so that it acts as a thermostat. Clouds are an admitted weakness of most GCMs. Perhaps Willis has the fix! Ponder that fact before putting too much faith in GCMs. There are far too many choices to be made in building such a thing and we can very easily make the elephant wiggle his trunk. Such models mostly tell us which way the builders of the model thought the trunk should go.
Willis: I see you’ve caught the volcano-ENSO bug. I’ve looked at that before, using NINO3.4 SST anomalies and the Extended Multivariate ENSO Index (MEI), but never published a post. I had also not looked at the old (GISST-based) version of the BEST ENSO index, which you used in this post, but I will say that the newer (HADSST2-based) version of the BEST ENSO index…
http://www.esrl.noaa.gov/psd/people/cathy.smith/best/enso.ts.1mn.txt
…is too noisy to be of value to you.
Of the others, the extended MEI…
http://www.esrl.noaa.gov/psd/enso/mei.ext/table.ext.html
…appears to show the best relationship. You may consider trying it in your analysis. The following are a series of graphs that compare the Extended MEI data to arbitrarily scaled (scaling factor = 10) GISS Aerosol Optical Depth data as our volcano proxy.
Mount Pinatubo preceded the El Niño, but El Niño conditions had been reached earlier in the year:
http://i44.tinypic.com/656ag9.jpg
El Chichon coincided with the El Niño:
http://i44.tinypic.com/14iophi.jpg
Mount Agung coincided with the El Niño:
http://i39.tinypic.com/116l17o.jpg
Novarupta doesn’t work (with all ENSO indices, BTW), but that eruption occurred at high latitudes:
http://i44.tinypic.com/33caz9k.jpg
The El Niño conditions preceded Santa Maria (with all ENSO indices), but the early start of that El Niño looks awkward:
http://i44.tinypic.com/auzfvs.jpg
There were minor El Niño conditions lagging Krakatoa:
http://i39.tinypic.com/6f35f4.jpg
I seem to recall reading papers that suggested that a volcanic eruption could initiate the downwelling Kelvin wave that starts an El Niño, and that seems to make sense.
In your post, you put the early portion of the SOI in a good light. However, the Tahiti portion of the SOI data is also questionable before 1935.
Before Trenberth’s alarmists days and before he was off looking for missing heat, he was well known for his ENSO research. In his 1997 “The Definition of El Niño”…
http://www.cgd.ucar.edu/cas/papers/clivar97/en.dfn.html
..Trenberth writes:
“Various versions of the SOI exist although, in recent years, most deal only with atmospheric pressures and usually only those at Darwin and Tahiti. In using the SOI based on just two stations, it must be recognized that there are many small scale and high frequency phenomena in the atmosphere, such as the Madden-Julian Oscillation, that can influence the pressures at stations involved in forming the SOI, but which do not reflect the Southern Oscillation itself. Accordingly, the SOI should only be used when monthly means are appropriately smoothed (Trenberth 1984, Trenberth and Hoar 1996a). For many years, Tahiti data were available only after 1935. Ropelewski and Jones (1987) outline an extension of the SOI prior to then using newly discovered Tahiti data, and they also discuss different ways of standardizing the data for use in the SOI. However, there are questions about the integrity of the Tahiti data prior to 1935 (Trenberth and Hoar 1996a), as the Tahiti-Darwin correlation is much lower in spite of strong evidence that the SO was present from other stations, and the noise level and variance in the early Tahiti data is higher than in the more recent period.”
Also, Willis, I was confused by something in your post. You wrote, “When the reduction in sunlight occurs following an eruption, the Pacific starts storing up more energy.”
Because the El Ninos are occurring at the same times as the volcanos, are you saying that an El Niño is causing the Pacific to store heat? The opposite is actually occurring.
“And how does it do that? One major way is by changing the onset time of the tropical clouds. In the morning the tropics is clear, with clouds forming just before noon. But when it is cool, the clouds don’t form until later. ”
Vegetation produces green leaf volatiles, GLVs, adding volatile organic compounds, VOCs, which form secondary, gas to particle, aerosols and so c.c.n. , cloud condensation nuclei.
The rate of this production is, I suspect, linked to the degree of ‘stress’ the biosphere is under at any given time. More heat, greater soil moisture deficit, more VOCs produces and equates to more cooling cloud formation. Conversely Cool conditions, less stress, less VOCs, less clouds formed.
http://crac.ucc.ie/downloads/presentations/portoroz_poster_trevorcarey.pdf
“A recent estimate of global SOA , secondary organic aerosol, production based on VOC fluxes indicated that there may be significant missing SOA precursors that are currently unknown (Goldstein and Galbally, 2007). The results obtained in this study indicate that GLVs may be an important part of this unidentified global source of SOA, which have been overlooked as a consequence of their volatile first generation oxidation products.”
Is this an example of the climate system actively responding to reductions in the incoming sunlight by altering cloud amounts via an overlooked mechanism of aerosol production and cloud formation by plants.
Willis,
I agree with you that B. is more likely. Try using a negative CO2 sensitivity and see what the models “predict”.
Now to reiterate a point I made on one of your other threads, where does this energy go once the governor has evacuated it from the tropical SST?
Firstly it goes to troposphere where is creates a slight warm spot ( but not the predicited hot-spot since they amplified the GHG with water vapour, but there is some small warmth in TMT ).
Then a large amount will end up radiated to space and the rest goes polewards. That atmospheric transport is fairly classic meteorology.
Now what happens at the pole?
So as not to deviate discussion from Willis’ important article, I’ll leave that for another day.
To be continued ….
Ian H says: May 25, 2013 at 5:23 am
“This equation is the defining equation for sensitivity so it is canonical.”
But it isn’t. If you look up the definitions for ECS and TCR, they are specific to notional experiments. ECS is the eventual equilibrium response to a prescribed step change in F, uniformly sustained. TCR postulates a 1% rise over 70 years (doubling). Neither of these implies this “canonical” equation. Or even linearity.
But the real point is, the sensitivities are after the fact summary statements descriptive of the system. No-one claims that their supposed constancy (if it is supposed) can be used as a general purpose predictor of temperature. That was the “canonical” equation cited. If it’s used that way, surely someone could cite someone doing it.
The Year without a summer was 1816 after Mt Tambora erupted – nothing to do with Krakatoa.
When you work in the real world with controlled processes and the PID controllers which keep the processes in control, you see strong evidence of bounce, lag and settling time which you refer to. Once the process is initiated, and the controller brought online to guide the process, there is always a deviation away from the control point in the opposite direction of the deviation which triggers a response from the controller. Dozens of companies make these PID controllers, there are even tunable control blocks programmed into commonly used PLC machine controls which take the place of the stand alone controllers.
http://wwwdsa.uqac.ca/~rbeguena/Systemes_Asservis/PID.pdf provides a very good overview on tuning PID controllers, and the discussion points out the effects of changes in tuning parameters on rise time (time from induced perturbation to hit 90% of steady state operating point) Overshoot (how much the tracked parameter deviates beyond the steady state operating point before returning to that point) and Settling Time, which is how long it takes for the process to regain stability after being perturbed.
One thing that practice in tuning these controllers teaches you is that the larger the quantity of the controlled substance is, the slower the responses to perturbation will be and the more stable the system itself will be. IE, a 10000 gallon aquarium at the local zoo will vary in temperature much less and a substantial change in its’ temperature will occur much more slowly than that of the 10 gallon aquarium sitting on it’s stand in your home.
It’s amazing to me how much stability there is in the climate of the earth, and how well the mechanisms work to perform, without human interference, the job that these PID controllers do under the direction of those tasked with keeping industrial processes (or even the temp in your home) under control, and how the climate does not oscillate totally out of control, producing either iceberg earth or barbecue earth.
Another thing your stacker plots show is that , on average, major eruptions happen at times when temperature have already been cooling for several years. This means that a part of the post eruption cooling would probably have happened anyway.
Those seeing cooling usually forget to account for that and incorrectly attribute it to the volacano.
This particularly true for Mt Pinatubo which in fact created no net cooling.
http://climategrog.wordpress.com/?attachment_id=270
http://climategrog.wordpress.com/?attachment_id=271
Forrest Mims III falls into this trap in his comments on your earlier thread. http://climategrog.wordpress.com/?attachment_id=270
His carefully monitored datasets could be useful here but he has not published yet so all we get are a few pics and his comments absent of even his own analysis.
Far be it from me to nit-pick over an article that Willis has put so much thought and time and intelligence into. I do have a few questions and observations, and maybe they will turn out to be irrelevant.
First, it would make sense to me that the chemical composition of the materials ejected from a volcano and thrown into the atmosphere would affect how the eruption affects the atmosphere and its ability to capture solar radiation. How much does that vary from volcano to volcano? Clearly some stuff that goes up will come down quickly, and some not so quickly, and chemical composition will be a relevant factor in identifying the difference.
A companion question is that of how high the ejected materials go. For major volcanic eruptions, this may be relatively constant, but I don’t know.
A second companion question is how much the latitude of a volcano matters in the apparent global distribution of its ejected gases and ash.
All that said, I find Willis’s explanation to be compelling, and the answers to these questions would only serve to refine the hypothesis, and maybe explain some of the differences between the selected volcanic eruptions.
Willis
Thanks for thought provoking comparisons. On first impressions, it clearly shows major physics missing in current global climate models. You provide a hypothesis. Now to see how well it holds up or if others improve on or complement it to further the science.
Re “but I’m biased in the matter.” No need to berate yourself. Put your best argument forward.
“Since I’m looking for the common response, and digging to find the signal, I will leave out El Chichón as an outlier.”
I think you need to remove that idea. It is not necessary, does not change the lack of cooling and is a clear case of selection bias.
Even with the full set of data there is a downward trend before the eruption and at the end : no downward trend and no net cooling. That sounds to me like volcanoes cause at net positive effect if anything.
In reality I think that net volcanic effect is indistinguishable from zero , the rest is natural variations that , on average, happen to be tending downwards when major eruptions happen.
Whether that is simple coincidence, in view of the very small sample of events , or indicates some correlation between cooling phases and the cause that triggers eruptions will likely remain beyond our understanding for a long time yet.
Anyway, I think if you correct some theoretic inaccuracies you have made a good summary of the lack of cooling that is a fundamental inaccuracy of current modelled behaviour.
Like I’ve been saying for a long time the incorrect model response to volcanism is pillar on which exaggerated CO2 forcing stands. Long over due that someone kicks it away. Congratulations on putting this together.
Here’s another one showing that cooling often precedes these events rather than being caused by them. Note, I’ve flipped stratosphere temps which works the other way.
http://climategrog.wordpress.com/?attachment_id=273
Not only do the actual temperatures return to the pre-eruption value, but they rise above it before finally returning to the that temperature. This is the expected response from a governed, lagged system.
=====================
We see this for example in the autopilot in boats. When the gain is turned up to quickly return to course, there is always an overshoot before the original course is resumed.
The climate models are behaving like an autopilot with the gain turned right down, so that if a wave (forcing) pushes the boat off course it will take a very long time to return to course. If a second wave hits before the boat is back on course, the boat goes even further off course. Thus, the climate models predict catastrophic warming – the boat will go dangerously off course in response to forcings.
However, in a boat where the gain is turned up, as we are seeing in the volcano response, then the boat quickly returns to course before a second wave can hit, and maintains a relatively stable course even in very large waves. There is no catastrophe if the gain on the course correction is high.
Anyone that has sailed small boats offshore in waves will be familiar with how this works. Overshoot is a result of the gain in the course correction mechanism. What Willis has shown is that there is evidence for a high level of gain in the temperature course correction in climate. The temperature response to volcanoes shows that the climate models are underestimating this gain.
I think Willis has hit the nail on the head. The volcano data shows that climate (temperature) does not act like a linear combination of the forcings. Rather it is more like an autopilot or pendulum. When a forcing pushes the temperature in one direction, the climate system works to oppose the forcing.
Nick, I think your comment about emergent properties is very telling. Since the models don’t come close to reality then clearly they are not capturing our reality sufficiently to be useful. Most likely due to the number of missing processes.
However, I agree with others that this study is based on too few events and the number of outliers is troubling. Also, it seemed the trend at the eruptions often was not changed by the eruption. While I happen to agree with your governor hypothesis, I think you need far more events to make sure your results are not just a random variation.
Thank you Willis for the brilliant post!
You found ways to look through the veil of the models. Indeed I find the current paradigm of climate models “forcings” to be in sorry need of revision.
Looking from the fence I have the gut feeling that a new generation of models should come using engineering standards of heat transfer, what I find sorely missing in climate models.
Judith Curry should be politely asked to concisely comment on this illustration of modeling “science” ignorance &/or deception:
http://wattsupwiththat.files.wordpress.com/2013/05/stacked-cumulative-modeled-observed-and-theoretical-temperatures.jpg
______
http://img829.imageshack.us/img829/2836/volcano911.png
http://judithcurry.com/2013/05/19/on-academics-abstraction-and-model-addiction/#comment-323490
Ian H says:
May 25, 2013 at 5:23 am
Such models mostly tell us which way the builders of the model thought the trunk should go.
============
Exactly. What models are best at predicting is what the model builders believe the future will be. If they didn’t – if the models didn’t return results in line with the model builders beliefs – the model builders would think the models were in error and change them.
To build models that can accurately predict the future requires very careful experimental design to eliminate human bias – something that is almost impossible to achieve. Even the best double blind experiments routinely show drift over time – indicating either that physical laws are not constant – or that bias is present even in double blind experiments. The problem is that no human being can accurately detect their own bias, because our bias affects our self-measurement.
The 259 trillion cubic miles of mostly molten rock beneath our thin cooled crust is not the result of gravity ‘compression’ heating or residual heat of origin, but is from decay of 700,000 cubic miles of fissionable material that is unevenly distributed within the molten mantle. This fissionable material is subject to varying solar and cosmic bombardments with varying degrees of protection by a varying magnetosphere. Individual nodes of fissionable material therefore have transient responses with regard to time and location. The ‘red dot’ eruption v temperature graphs in your concluding “Individual Records” plots show the random nature of these events. Volcanoes act as pressure relieve valves to temperatures that ‘sometimes’ correspond to ENSO input, and sometimes to the regional input of a local fissionable material node. A popcorn popper lid responds to variation in the base temperature input as well as the local kernel gas energy release. I strongly support your “B” hypothesis. Since the majority of Earth’s surface is covered with 310 million cubic miles of ocean, with half the mass per volume of land and a tiny fraction of the crust thickness, most of the volcanic activity is further dampened by ocean heat/particulate absorption. For more information on undersea activity see “Volcanic CO2” at the Timothy Casey, Geologist 1011 website. Casey’s post of the original Tyndall and Fourier material with after notes is a must read as well. Thank you Willis for discussing the ELEPHANT in the AGW room.
Fred Berple: The temperature response to volcanoes shows that the climate models are underestimating this gain.
No, the models do not model thunderstorms so they do not even have the mechanism. What they try (and fail) to do is create a time response hind-cast without having the correct mechanism.
You can always tweak a bad model to be about right over a fixed period but when the ratio of the forcing change (as happened post 2000) the tweak will not longer work. You need a new tweak to get roughly right again.
Now watch them tweak the parameters rather that fix the model.
@Paul Vaughan re contact: check back on the other thread if you haven’t already.
Greg Goodman says:
May 25, 2013 at 5:20 am
“Degree days: What does such a chart measure? It measures how far the system is out of energetic balance. ”
No, that’s wrong. Temperature is a measure of heat (energy) . Degree.days is an integral of energy in some units like joule.second , it is not a measure of energy.
If a system comes back to the same temperature is has recovered to the same energy content.
The plot is still useful to look at differences in behaviour.”
———————-
I think you are right about the oceans temperature being a measure of heat, but the atmosphere can have the same temperature with a different heat contents due to humidity differences.
Mann was onto this a while back:
http://www.nature.com/nature/journal/v426/n6964/abs/nature02101.html
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-3276.1
http://www.geotimes.org/feb04/NN_volcElNino.html
One major way is by changing the onset time of the tropical clouds. In the morning the tropics is clear, with clouds forming just before noon. But when it is cool, the clouds don’t form until later.
=======
This is the difference between “summer” and “winter” in the tropics. When the sun is on the opposite side of the equator from you (warm), you are in the dry season. If it is on the same side (hot), you are in the wet season. In the dry season the clouds form late in the day if at all and rarely bring rain. In the wet season the clouds form early in the day and often bring rain.
And if you have lived in the tropics, especially if you were originally from a cold climate, you know that the clouds are a very welcome relief in the “summer” because they give substantial relief from the heat. In the “winter” when the temperature is only “warm” the lack of clouds and rain makes the tropics ideal for vacations.
Thanks, Willis, a provocative article pointing to interesting facts to consider.
Yes, volcano-forcing air temperature data do show the workings of a self-regulated system.
After reading articles and comments on different sites for about month I have come to the conclusion: that the science is far from settled and that the models cannot accurately predict future climates. I’m afraid it’s just about governments using crisis justification to redistribute wealth from the folks to themselves. The energy cost pain index in Europe is a start to ending this con game.
• This system restores both the temperature and the energy content of the system to pre-existing conditions in a remarkably short time.
===============
The oceans (and earth itself) form a huge reservoir of energy. Even a small change in the rate of energy entering or leaving the oceans in response to a change in air temperature, as provided for by the change in tropical clouds, would be enough to quickly overpower any change in air temperatures.
What this suggests is that temperature is not a linear function of forcings. Rather, there are critical temperatures connected to the phase change of water (freezing, evaporation and condensation) that serve as attractors in the chaotic climate state, and global temperatures orbit these attractors in a chaotic fashion.
The forcings themselves have largely only temporary affects on the temperature, except when they perturb the orbits sufficiently to shift from one stable climate state to the next. Thus we see the pattern of ice ages and interglacials, with rapid transitions between the states.
If climate was in fact a linear combination of forcings, the shit between ice ages and interglacials would be gradual, reflecting the gradual change in forcings. But this is not what we see. The paleo climate records show that temperatures are relatively stable with rapid shifts between states. Which indicates a non-linear system, which can be described mathematically as a chaotic system orbiting attractors at different stable temperatures.
In effect our temperature (simplified) is a space-ship orbiting a moon called interglacial, which orbits the larger planet ice-age. So long as the forcings (our thrusters) all work randomly, opposing each other, we remain in orbit around interglacial. However, if the forcings (thrusters) align then we run the risk of being thrown out of orbit around interglacial and instead orbiting ice-age.
Right now, many of our thrusters are working in the cold direction to shift our orbit towards ice-age. They have been doing this for about 10 thousand years. The CO2 thruster however is working in the opposite direction, working to hold us in orbit around inter-glacial. Rather than being a bad thing, just maybe it will turn out to be what saves us from the next ice-age.
Very interesting Willis! I have several comments/questions.
1. I too wondered why use ECS instead of transient.
2. If you look at Fig. 2, it looks as though 3 of the 6 go positive and never really go negative after the eruption. This ties in to several other comments about different type of particulates giving different climate effects and ongoing ocean temp. trends simply continuing. In fact, in your average signal, you see this as there is no volcano signal within error which is kind of why you got rid of El Chicon, correct? Even with only five, the signal is almost non-existent when you consider your error bars.
3. And finally in Fig. 6, it looks as though the slope for 2-3 years before the eruption and 2-3 years after does not really change, which to me says there really is not a global effect due to most volcanoes. Just looked again and I will have to amend my statement to say that it shows that the parameter you are graphing on the y-axis shows no effect due to the volcanoes.
However, I like your ideas about tropical storms being governors and sending heat into space and the idea that changing the onset of tropical clouds by an hour or so can really have a huge effect. I would like to see more climate scientists looking at NEW ways of modeling the climate instead of using the same type of model to wrongly predict more things and usually more future calamities.
It is obvious that climate scientists have never studied governors. In biology, two clear examples concern compensatory growth. If a growing calf encounters a food shortage and can’t gain weight for a while, and then food is again available, it gains weight at a faster rate that normal until it recovers to normal. After grass is grazed or mowed, it regrows at a faster rate to recover what was lost. The total grass you mow on your lawn is more than if you had just left it alone and harvested it at the end of summer. The fact that longwave radiation is a 4th power of temperature provides one type of governor, and evaporation/precip processes and clouds others.
What amazes me is how these guys can point to something that does NOT match and call it proof of their model. Do they issue rose colored glasses when you get your Ph.D. in climate science?
Craig Loehle says: The fact that longwave radiation is a 4th power of temperature provides one type of governor, and evaporation/precip processes and clouds others.
With respect, that is a negative feedback not a governor. A step increase in forcing would result in a new equilibrium state under those feedbacks, not a return to the initial value.
I don’t think there is an El Nino response to volcanoes. The El Ninos that developed after El Chichon and Pinatubo were already well into development before the volcanoes.
Feb 1982 Pacific cross-section.
http://www.cpc.ncep.noaa.gov/products/GODAS/mnth_gif/xz/mnth.anom.xz.temp.0n.1982.02.gif
May 1991 cross-section.
http://www.cpc.ncep.noaa.gov/products/GODAS/mnth_gif/xz/mnth.anom.xz.temp.0n.1991.05.gif
Long monthly animation of these cross-sections.
http://www.cpc.ncep.noaa.gov/products/GODAS/mnth_gif/xz/movie.temp.0n.mon.gif
The mainstream doesn’t pay enough attention to circulation when thinking about aerosols.
Bill Illis says:
I don’t think there is an El Nino response to volcanoes. The El Ninos that developed after El Chichon and Pinatubo were already well into development before the volcanoes.
That’s an interesting point. I have also suggested several times the idea that El Nino cycle is a slow moving inertial tide in the thermocline. If that is the case the correlation with volcanism may be more than coincidental.
Bill Illis says: May 25, 2013 at 8:09 am
I don’t think there is an El Nino response to volcanoes.
Maybe not from the above….
“I don’t think there is an El Nino response to volcanoes.”
Common cause ?
BTW…the ‘other’ ELEPHANT in the AGW room is Thermal Mass. We are supposed to believe that 28 gigatons of human CO2 is the climate driver. To simply this analysis we will compare data with some approximations, as the magnitudes are so HUGE that exact relationships are trivial. If the 28 gigatons were pure Carbon at 125 lb/cu, then the human contribution would be less than 3 cubic miles….however….each CO2 molecule from combustion combines Carbon with O2 already in the air. Using atomic weights, Carbon = 12, Oxygen = 16, then the percentage by weight of Carbon in a CO2 molecule is 27%, so the human Carbon contribution would be 0.8 cubic miles. Mixing weights and volumes in not exact, but what is obvious is that this tiny portion of the tiny atmospheric mass, that is CO2, is trivial compared to the 259 trillion cubic miles mass of ‘solid’ Earth and the 310 million cubic miles of ocean.
Mass is one determinant in heat flow equations, which is modified by a coefficient known as Specific Heat. For air, this has an assigned value of 1.0, and CO2 has a derived value of 0.8, meaning that CO2 absorbs and RELEASES energy faster than air. Therefore, the tiny mass of atmospheric CO2 has it’s 0.8 cubic mile reduced relative to air to 0.64 cubic miles, but it gets worse. Water has a Specific Heat ~4.0 and Specific Heat by ratio of mass for all of the various elements on Earth far exceed the Specific Heat of water. A spec of dust on an elephants back MAY cause some solar reflection, it MAY absorb some solar energy and ‘warm’ a few cells in the epidermis, but dust does not drive an elephants body temperature.
This entire AHW farce only illustrates the desperate level of scientific illiteracy on Earth and the profound stupidity of government agenda driven Lysenko science. It also points to the need for interdisciplinary review of all science, with STRICT oversight for any ’emergent’ branches of science. Humanity cannot afford these frivolous waste of tax money and science education in the future. Stupidity is not sustainable.
On figure 5, the numbers -11, -13 and -17 on the graph seem misplaced.
Well done.
I’d suggest leaving El Chichon in the analysis — there is too little evidence of what the “real distribution” should be to call it an “outlier”.
Alternative language to “stacked” is “time-locked”. Recommendation: add the graph of the “time locked” increase in aerosol concentrations.
Thanks, Willis, for this global volcano trip!
Referring to the volcanic eruption of Pinatubo (VEI 6, in June 1991) followed by Cerro Hudson (VEI 5+, in August 1991) this double-eruption represented the strongest global volcanic impact since Tambora in 1815 (to which the “year without summer” is commonly attributed).
Very interesting to note is the apparent impact of stratospheric volcano-ash and SO2-aerosols on cosmic rays which appear severely reduced immediately after this event (see http://users.telenet.be/j.janssens/SC24web/CosmicRays.png)
This extremely narrow CR spike is clearly below the minimum of cosmic rays caused by the magnetic maximum of the 11year solar cycle at that time (see http://wattsupwiththat.files.wordpress.com/2012/07/image2.png)
If Svensmark theory is right, and cosmic rays really modulate low-cloud formation in the troposphere, an interesting scenario comes up:
A strong reduction of cosmic rays by stratospheric volcanic ash/aerosols consequently reduces cloud formation in the troposphere (=reduced albedo). This gets, for a short time of only a few weeks, more solar energy to land & oceans — buffering the upcoming negative volcanic forcings. Only several months after a big volcanic eruption (VEI>4), aerosols & fine-dust are globally dissipated in the stratosphere absorbing solar radiation and and starting to take their temperature toll — for maybe one or two years.
The relation of cosmic rays & cloud formation might be another independent temperature control mechanism adding to the ones that Willis mentioned — and all appear to be much more related to solar power than to CO2 … just my personal guess …
Carry on like this and best regards from chilly Munich/Germany!
Stefan Weiss
Krakatoa threw up dazzling red sunsets for years around the entire northern Hemisphere. Also, as pointed out by several readers, it was Tambora in 1816, that was allegedly associated with the
“Year Without A Summer” in the northeastern U.S.
Margaret Hardman says:
May 25, 2013 at 4:44 am
“.In the middle of marking university entrance individual studies/investigations. I would not give this a good mark. There are lots of confounding factors not taken into account, for example: how long do the particles erupted into the atmosphere remain there? What criteria are used for selecting the eruptions….etc….
Margaret, we’ve all had markers like you, who mark tougher on the smart ones. I suspect Einstein’s poor results in mathematics as a student may have partly been because of this. You seem to have missed the point that Willis has just graphed temps before and after the well known set of volcanic eruptions known to have sent aerosols into the stratosphere and noted that their overall effect after a few years has been zero, and remarkably the planet even worked overtime to make up the temporarily lost energy. This is an observation. Perhaps you can take issue with his suggestion that ENSO was somehow part of the rebound in temps associated with the eruptions, but not the observation itself. If Willis gets a low mark on this, what marks would you give to the bulk of climate scientists who certainly have it demonstrably wrong. Also, the last thing the climate scientists you probably admire would do is look into all the details on the behaviours of each eruption – they have an aversion to observation (they have to take such and homogenize and add stepped increases to disinfect them to get them to show their pre-supposed responses). While we are at it, why don’t you inform us of the characteristics of each eruption – volume, chemistry, etc. You could contribute this by way of rebuttal perhaps. Willis has written a thesis here in a number of hours only – you should read his “governor” thesis, It has been peer reviewed, and based on data and real world observations. God help our students.
Willis, I am not particularly sure why you need to bring in the cloud thermostat at this point. The heat capacity of the ocean is 1000 times greater than the atmosphere. With a volcanic perturbation, the ocean can take up the slack for quite some time. That is a change in the delta Q part of the ECS relationship that buffers or damps the atmospheric impact. The northern hemisphere “surface” air temperature drops more because the ocean/land surface area difference limits the rate of heat transfer.
Global temperature is the problem since responses are not globally the same.
Regarding the cooling trends prior to large volcanic eruptions- Don’t many volcanoes exhibit increasing activity prior to the main blast? I don’t know how to quantify that relative to the main date of the volcano, but it’s worth thinking about. (It’s also been pointed out here many times that smoothing temperature records will create a dip in the record preceding the actual drop caused by the initial volcanic eruption, so there’s that confounding factor as well.)
It’s also difficult to know how much routine background vulcanism is occurring both above ground and under sea relative to the large noticeable eruptions. That would need to be quantified as well, wouldn’t it?
Interesting post Willis.
David Archibald says:
May 25, 2013 at 1:59 am
Thanks, David, but the question was rhetorical. The problem, in addition to the size of the response, is the shape of the response. You need the “S”-shaped response that goes up above the zero line, in order to restore the lost energy … and the models seem unable to do that. No surprise, that’s the sign of a governing mechanism, and the models are slaves to linearity.
w.
The current climate paradigm says that the surface air temperature is a linear function of the “forcing”
It says nothing of the sort. You are starting with a misunderstanding, and so based on the well known principle of GIGO, your conclusions are invalid.
Seems to me from looking at those temp charts during the various eruptions, that the climate is already heading in a particular direction. When the climate is heading cooler or has flatlined, the eruption adds a more distinct cooling signal. But when the climate is going warmer, it doesn’t really stop it from doing so, it just seems to slow the process, and temper the peak of the warming.
Nick Stokes says:
May 25, 2013 at 2:18 am
Willis,
“Their canonical equation is:
Change in Temperature (∆T) = Change in Forcing (∆F) times Climate Sensitivity
In lieu of a more colorful term, let me say that’s highly unlikely.”
Whose canonical equation? Could you give a reference? Certainly no GSM works that way.
Folks, if you don’t know him, let me introduce you to Nick Stokes, who once again isn’t following the storyline. In fact, Nick will disagree about anything, if you say blue, he’ll say red. He’s a jailhouse lawyer, and has never (to my knowledge) admitted he is wrong.
I gave you the citations in the head post, Nick. The most important is this one, which discusses the equation in detail in the comments. But if you want more, you could read my post “The Cold Equations“, or any of a host of other posts discussing the topic.
And while you are correct that “no GSM works that way (I assume you mean GCM), my posts have shown that they are functionally equivalent to just exactly that equation … I guess you weren’t paying attention.
Do try to keep up, dear boy … don’t worry, folks, Nick will be back soon with his unending chant of “wrong, wrong, you’re wrong” … nothing short of a tactical nuclear weapon can prevent Nick from exposing his ignorance.
w.
Gary Pearse 25 May @ 9.05am
God help you, I think you mean. I mark against agreed criteria and applying those criteria this effort would be marked low. To tell me that it was written in a few hours tells me plenty. To expect to overturn the efforts of hundreds of scientists over dozens of years with something put together in a day, without much in the way of references and without much consideration for confounding factors.
As for marking Einstein down. Try http://skeptics.stackexchange.com/questions/956/was-einstein-a-poor-student for some evidence that Einstein wasn’t marked down by his teachers. Follow the evidence, don’t buy the myth is the moral here. And before you say it, because I am afraid the responses are usually predictable on this site, I follow the evidence, the real, messy, complicated evidence, as do climate scientists.
And as a final remark, you trumpet peer review but I suspect you have an ambivalent attitude to peer review. It is a useful but imperfect tool, designed to ensure that quality science is published whether it is in agreement with what we currently believe is correct or not. It weeds out articles like the current one which would have been returned with a lengthy list of recommendations for improvement. If you could send me a link for the paper you refer to, including the title of the journal, I would be most grateful. Google doesn’t seem to be helpful.
Lance Wallace says:
May 25, 2013 at 2:50 am
As you can see from the figures, the removal of El Chichon made little difference, merely clarified the shape of the response, so I’m not clear what your issue is. And no, that’s not the same reason Briffa uses.
w.
I agree with the very first comment.
Willis rarely admits that he was wrong for one simple reason: he is rarely wrong. That is in stark contrast to Nick Stokes and the rest of the alarmist crowd, who can’t seem to understand that their endlessly repeated predictions of runaway global warming were flat wrong. Instead of admitting they were wrong, they alter their argument.
Now we are at the “climate change”, “global-warming-causes-cooling” stage of delusion. My question to Nick: how many more years of non-warming would it take for you to admit that your catastrophic AGW conjecture is wrong? Give me a number.
Nick Stokes says:
May 25, 2013 at 4:24 am
This is Nick at his finest, folks. He claims that he can’t understand whether I’m talking about … Nick, when I say the “average of the fifteen Forster models’ output”, I’m talking about the average of the output of the Forster models … is that so hard to understand? I discussed in my last post, which I cited above and you apparently didn’t read, exactly how I got the results by digitizing the Forster data … wake up and smell the coffee, Nick. Your nit-picking is boring, just makes you look dumb.
w.
Wilis: ” You need the “S”-shaped response that goes up above the zero line, in order to restore the lost energy … and the models seem unable to do that. No surprise, that’s the sign of a governing mechanism, and the models are slaves to linearity.”
You need the S shape to match the data but not to restore lost energy. Your degree.days idea is wrong (physical dimensions again will tell you that).
The “S” is typical of a governor but so would a slow rise to previous temps. It is the return that matters and that shows recovering lost energy.
I explained all that above in more detail , I suggest you read and take note.
It does not undo any of what you are saying here but it would be better if you understood the physics since you will not get the idea accepted if you retain mistakes like that.
Nice work.
Especially see my comments on over shoot and over damped systems.
Nick Stokes says:
May 25, 2013 at 4:42 am
No, Nick, that’s just more of your bafflegab to avoid admitting an error. I digitized them from the FORSTER PAPER, exactly as I cited and quoted in my last post. See Figure 2 of the Forster paper that you just cited, that’s what I reproduced at the top of my last post. That’s what I digitized, and that’s what you seem unable to see.
I hardly expect you to actually admit you have your head up your fundamental orifice, Nick, you’ve never done that before … but it is obvious to the rest of us.
Thanks for the published version of the paper, though, much appreciated.
w.
@Willis I sometimes wonder if Nick is on some sort of frequent obfuscator program, where he gets rewards based on the number of such comments he leaves. – Anthony
Margaret Hardman:
“I know nothing of the author but I would suspect they have not used their full scientific training in the production of this short article. Had they done so, they would have spent a considerable time looking in detail at the possible confounding factors surrounding the global temperatures for each of these eruptions and those that were left out.”‘
So this is the holier than though “educator” that pretends to know more than anyone else?
When you’re marking those exams, do you allow students to use “their” and “they” to refer to a single individual?
And, perhaps as a better indicator of Einstein’s experience with “educators” (and those who mark entrance exams), Wiki tell us “Einstein did however fail his first entrance exam into Federal Polytechnic School in 1895.”
http://en.wikipedia.org/wiki/List_of_common_misconceptions
If I were to use the same tactics as Ms/Dr/Professor/Schoolmarm Hardman, I might write” “I know nothing about this “eduactor”, but I suspect she has a bloated opinion of her own intellect.”
But I won’t.
Willis – THANKS.
This is the first post that includes the basic concepts that a good process control engineer knows and understands. The globe, like a Terrarium, or a boiler at a power plant – a closed system. Changes are effected as much by the lag of a factor/parameter as they are by the gain/attenuation of the parameters involved. This seems to have been missed in the General Theory of AGW (pun intended.) The perceived effects of a known change mat not be the only effect, they can as you have suggested cause a lead (early cloud formation) or a lag of the effects (clouds lasting longer) each of which also causes different imperceptible, unless analyzed carefully, effects.
In tuning the control systems during the startup phase of a new power plant, The operators quickly discovered how difficult it was to manually control the level of a feedwater heater, or boiler. For some operators it was near impossible. And all were amazed at how one seemingly insignificant subsystem could quickly put the plant into a rapid, un-recoverable, spiral to trip/shutdown. Anyone with any process control training should readily see that the Earth is doing a very good job of controlling it’s temperature, otherwise we would be in a constant stat of oscillations.
All volcanic activity is not created equal. The effect on the models or the climate due to this bit of information is really unknown to me. But at least it might be worth noting the fact. I worked at a solar furnace in NM previous to and after the El Chichon eruption and I observed a drop in normal fall “solar constant” readings by about 100 watts/m^2 at our site for several months. We measured solar “input” at the surface with an Eppley normal incident pyrheliometer (NIP) tracker. Normal readings during the fall were 900 to1000 w/m^2 depending on water vapor in the atmosphere (and fall days were usually very low in water vapor). The fall after El Chichon was clearly different with a decreasing value throughout the year that lasted about 6 months and then slowly increased back to normal by the end of the 12 month period after the eruption. El Chichon apparently blasted large amounts of dust and gas into the stratosphere so that upper winds circling the globe slowly distributed this material far and wide. Effects like this depend heavily on the location of the volcano and the weather conditions during the activity. Apparently volcanoes at higher latitudes do not have much of a global effect.
So the take away from this is that perhaps most volcanoes do not have global effects. They certainly may have regional or latitudinal ones but the limits of their effects must be gauged by the physical conditions involved in the activity (location, eruption characteristics [violence, ejecta, etc], winds, etc). Perhaps this is why taking all volcanoes into the mix will not produce more than noise at least taken from a global perspective. And perhaps a global decrease in incoming SW radiation from the sun may still not be enough to cause much more than a ripple in “force” (climate). However, if this is true of levels of 100 watts/m^2 why are we worried about a few watts/m^2 caused by CO2?
Just a data point in an always interesting Willis analytical exercise.
Maybe the next step is to sort volcanoes by latitude and magnitude to see if a better signal can be teased out?
Anthony Watts says:
May 25, 2013 at 10:26 am
@Willis I sometimes wonder if Nick is on some sort of frequent obfuscator program, where he gets rewards based on the number of such comments he leaves. – Anthony
It is true. The posts are amazingly described by: “some sort of frequent obfuscator program, where he gets rewards based on the number of such comments he leaves”
I had the same experience reading comments posted under the same nick some time ago comparing the way the UVA behaved towards two different FOI requests, one by a green organisation requesting info based of FOI for a skeptic scientists (Michaels), the other by ATI requesting for info based on FOI for M.Mann:
http://rankexploits.com/musings/2012/court-ruling-on-mannati-case/
It is amazing to see his “logic”. Whilst I do understand the discussion should be looked from both angles, is this way of obfuscation the best the alarmists are able to bring up? Is this all they can do?
Willis,
“I gave you the citations in the head post, Nick.”
Yes, I’m back. You have given a caricature of the modeller’s approach to relating temperature to forcing, saying:
“Their canonical equation is:
Change in Temperature (ΔT) = Change in Forcing (ΔF) times Climate Sensitivity
In lieu of a more colorful term, let me say that’s highly unlikely.”
and
“The current paradigm says that after a volcano, the temperature should vary proportionally to the forcing.”
Well, “canonical”, “current paradigm” – I’d expect you could actually quote scientists saying those things. Instead you just refer me to posts where you’re saying them.
I’ve gone through above what Forster et al say, and Otto et al, and it isn’t their paradigm. Otto specifically says that a proportional relation is not ot be expected after a volcano. So whose is it?
On the data question, you gave no source for the 15 Model average plotted in this post for post volcano periods. I looked for the numbers in all the places one might expect – no. So I asked. Then I looked through some of your earlier posts, and by checking the numbers from a spreadsheet there and this one, I saw that they matched. So I posted again to acknowledge that. But it would have helped if you had said here where they come from, since they are central to your post.
Margaret Hardman says:
My goodness, madam, this is the hastily assembled findings of work done when I’m not working at my day job in construction, research into what volcanoes can show us which is still ongoing as I write this. Basically, I’m offering you the opportunity to read my laboratory notebook as I’m working on the issues, and you complain that it’s not a finished scientific paper?
This is totally taken into account, in the creation of the forcing figures. The volcanic forcing data takes all of those issues into account, the scientists considered those questions when they produced the estimate of the global reduction in sunlight.
The criteria for selecting the eruptions is that I picked the obvious large peaks in the forcing estimates that were clearly identifiable from the record. If there had been seven peaks, I’d have chosen them. I was looking for the biggest volcanoes.
I see now that you are a true scholar, destined for the ivory tower … not one of those makes the slightest difference to my analysis. How would it make any change in my results if I knew how much material was erupted into the atmosphere, or what the local effect of volcanoes might be?
Also, the VEI (volcanic explosivity index) isn’t really the important factor. The issue is how much dust is injected into the stratosphere. An eruption can have a high VEI and not put much aerosols into the stratosphere, and a low VEI eruption can put lots of aerosols up there.
But all of these issues are taken into account by the folks who put together the estimate of the volcano forcings, how much material, for how long it was injected, how long it lasted, they’ve considered all of that. Your claim that I need to adjust for those issues just reveals your misunderstanding. If you think those are problems, go talk to the volcanic forcing guys.
Not sure what to say to that … I see that despite my efforts, you haven’t understood the problem with the models. I’ll continue to explain.
Ah, I see what part of it is. You haven’t understood about the equation I used to emulate the models.
First, the equation I used doesn’t “model part of the behaviour of the climate system”. It models the MODELS. It is an equation that is functionally equivalent to what the models do. The problem is that the equation DOESN’T model the climate system for beans.
Let me see if I can simplify this.
What I discovered in the course of my research is that the current generation of climate models are all bozos when it comes to estimating the global surface temperature. All they do is a simple lagged linear transformation of the input data. An example of the models at work is this figure from above:
The volcanic forcing, in W/m2, is the bottom blue line. The other lines represent examples of a family of curves that can be produced by the climate models. The dark blue line is the 19-model average used in the Forster study. All that the models are doing is that they are delaying and changing the size of the effect. That’s it.
The red line is kind of interesting. It’s the line that gives the best fit to the actual volcanic results. Note that it has a wholly unrealistic time constant of six months …
The main problem, however, is not in the size of the climate models’ response. It is in the shape of the response. Notice that not one of those model results ever showed a temperature that crosses the top line, that goes higher than the original conditions … but in order to quickly recover from a volcanic loss of sunlight, you need to go above the original temperature in order to restore the lost energy.
Second, does this “invalidate all climate models”? Well, to date I’ve analyzed the GISS and the CCSM3 individual models. Isaac Held independently did the same analysis on the CM2.1 model. And I did the analysis on the 19 models in the Forster analysis … and that’s about all the models I know about.
So at this point, the shoe is on the other foot. I’ve done my part. If you want to claim that there is a climate model out there whose outputs CAN’T be replicated by my simple equation, you’ll need to identify it …
Ah, my dear, you can’t know how unintentionally funny that is … let me point you to my post “It’s Not About Me“, you might find my scientific training interesting.
Let me see if I can explain my thesis simply.
A volcano causes a huge dip in the amount of sunlight reaching the earth. This is clearly shown in the model results as a large and long-lasting dip in temperature following an eruption, but but such a large and lasting fall does not actually occur in the real world.
We know the effect isn’t happening in the real world because I showed the combined effects of the volcanoes by averaging them to minimize confounding factors, and also because I showed the individual records. That gave me an average response along with a standard error.
Then I showed that in the real world, both the temperature and the system energy quickly returned to pre-eruption values. In the models, by contrast, while they do return to near pre-eruption temperature (albeit very slowly), the system energy is not restored for decades.
And not one of the issues that you raised make the slightest difference to those findings or conclusions, Margaret. How long the aerosols remain in the air, and whether Mt. Hudson did or didn’t, those are all accounted for in the shape of the volcanic forcing data.
Finally, and as gently as I can, I do have to say that more questions and less assertions might be in order for you …
w.
John M
May 25, 2013 at 10:17 am
Thank you for missing the point. I wondered how long it would take before the comments turned from substantive points to ad hominem assertions. I don’t rate myself highly intellectually but I’m also not stupid (though I don’t doubt many would debate that). My point in suggesting that Mr Eschenbach might have used more of his BA in psychology (yes, I googled him) to bring to bear his undoubted intellectual qualities and really investigated the issue, as befits anyone trying to produce something of true intellectual worth. It is not enough in science to produce a few colourful graphs without doing some true analysis on the data and seeing if there really is anything real going on or just something that fools the eye. I read the piece waiting for the real meat in this thin sandwich and it never arrived. If the purpose of this site is really to unravel the science (and politics) of climate change then it requires something more than the preceding article. It requires intellectual rigour. It requires proper quantification of all sorts of factors. Science doesn’t proceed on assertion. Remember what Richard Feynman said on the subject of delusion.
As for Einstein, it is true he failed his initial FPI entrance exam at 16, two years early and partly self taught. He failed because his non-science scores were insufficient, while scoring exceptionally in maths and natural science. See http://www.library.ethz.ch/en/Resources/Digital-collections/Einstein-Online/Youth-1879-1896 If you had read the wiki link rather than just cherry picking the phrases you wanted then you might have got the full picture. Einstein himself said he was no slouch at school. Applying two years ahead of time for higher education was clearly a gamble and it didn’t work. Didn’t make him a dullard.
This really needs to be broken down in to land/sea temps and tropical , extra-tropical.
This would be expected when looking for evidence for or against Willis’ TS regulator hypothesis
http://climategrog.wordpress.com/?attachment_id=270
Land shows temporary winter warming ex-tropics and a remarkable El Chichon tropical response.
http://climategrog.wordpress.com/?attachment_id=271
SST tropics is more stable than usual it seems certainly no drop. Score 1 for Willis.
ex-tropical , clear annual oscillation in the anomaly for three years after Pinotubo.
If we look at the sense we see this is because of a _reduced_ annual variation, again warmer winters but cooler end of summer.
ie Land : temporary warming
Sea : less annual variation.
NO cooling. score two for Willis.
Now if someone wants look at this with a GCM simulator , try putting volcanic forcing to zero, zero water vap. feedback, CO2x2 at its theoretical value and see what happens.
Zero volcanics is not accurate but it’s probably the best first stab to test this in a model that is not capable of creating tropical storms.
To our resident Mother Superior…
“Whoever undertakes to set himself up as judge in the field of truth and knowledge is shipwrecked by the laughter of the Gods.”
Willis Eschenbach
May 25, 2013 at 11:38 am
Thank you for patronising me. Most gallant of you.
I read your Brief Communications and the response. I also read your scientific autobiography. I stand by my comment that there are many omissions and if this is a work in progress it should be labelled as such at the beginning.
As for true scholar. Destined for an ivory tower. I refer you here
Well, they’ll choose a man for you to meet tonight
You’ll play the fool and learn how to walk through doors
How to enter into the gates of paradise
No, how to carry a burden too heavy to be yours
Yeah, from the stage they’ll be tryin’ to get water outa rocks
A whore will pass the hat, collect a hundred grand and say thanks
They like to take all this money from sin, build big universities to study in
Sing “Amazing Grace” all the way to the Swiss banks
But I’m sure this will be moderated out as irrelevant.
John M
May 25, 2013 at 12:03 pm
From your Mother Superior:
And if you don’t know where you’re going
Any road will take you there.
Expect a paper out soon copying you hypothesis and giving no attribution. Anyway, the models are wrong.
Ms. Dr. Prof. Hardman:
May I ask why you apply plural pronouns to individuals? I’m sure that, had you applied all the English language knowledge you have surely accumulated, you would not have made this mistake. Does your usage result from confusing grammatical gender with biological sex, perhaps? I know that some ideologues object to the fact that in English masculine & neuter gender use the same pronouns. Regrettably, I must grade your writing skill lowly.
I would add that the “scientists” whom you so esteem aren’t. Consensus “climate science” began unscientifically as CAGW, valuing modeling over actual observation collection, then, when nature refused to comply with their models, descended into anti-scientific advocacy as “climate change”. Your heroes don’t make testable predictions, but instead “projections”. When weather seems to support their anti-scientific scare-mongering & grant-gaining activism, then that’s “what climate change looks like”. When it doesn’t, then that’s not what it looks like.
After 30 years of looking, I’ve not found a shred of actual physical evidence in support of CAGW, but if you know of some, please enlighten me. Feynman would most certainly not approve of consensus methods, any more than Dyson does now, for instance. And that goes double for Karl Popper. Thanks.
—————————————————————————-
As several have noted, the “year without a summer” was 1816, after the explosive Tambora eruption, which was ten times as energetic as Krakatau, promptly killing about 92,000 people locally, IIRC, & many more around the world from famine & disease. It occurred during the depths of the Dalton Minimum, the last blast of the Little Ice Age, when crop failures were already common at higher latitudes. The massive clouds of ash & molecules which circled the earth however had at least one silver lining: the invention of the bicycle, due to dearth of horses after oats failed in Germany.
It was also during the Dalton (~1790-1830) that Sir William Herschel laid the groundwork (1801) of astroclimatology, a real science relying on physical data.
May I also second requests in the comments for the addition of more eruptions to the stack, & the inclusion of El Chichon? When the author has time. Tambora is a good example of an impending volcanic eruption to start adding ash & gases to the atmosphere for some time before the major event.
Willis Eschenbach says:
May 25, 2013 at 9:51 am
Lance Wallace says:
May 25, 2013 at 2:50 am
‘”Very clearly explained as always. However, removing a data point (El Chichon) when all you have is 6 such data points, is a very serious decision. It’s not clear to me that El Chichon is that much of an outlier in Figure 2. It’s pretty much in the middle of the pack most of the time. Pinatubo is more consistently at the bottom, and Novarupta is low before the eruption and very high after. You say you’re dropping it because you’re “looking for a signal” but that’s the same reason Briffa uses for dropping out Khadyta River from Yamal.”
As you can see from the figures, the removal of El Chichon made little difference, merely clarified the shape of the response, so I’m not clear what your issue is. And no, that’s not the same reason Briffa uses.’
Willis, my “issue” is pretty clearly explained in the second sentence –when you have a very small number of data points, you must be extremely reluctant to remove even one. Note that at least four more commentators have made the same point, so tossing us all off with a non-reply like the above is not helpful. Had you included the second paragraph of my comment, you might have seen more clearly what my issue was, since I pointed out that you again removed a second data point (Krakatoa), reducing your total data from 6 to 4 points!
Your reason for removing both of these was the same–they were “outliers”. But outliers as identified by you, with no preexisting criteria for the definition (e.g., >3SD out). Unless there is a really good reason for removing outliers other than that they don’t agree with other data, we should all avoid the temptation. And once again you state that removing El Chichon merely “clarified the shape of the response.” This is exactly my issue! You don’t really know the shape of the response beforehand, so how do you know the data without El Chichon is closer to the truth. Please tell me exactly how this differs from Briffa removing Khadyta River. He has a “response” in mind and Khadyta River was an outlier, so he got rid of it. (Briffa here is a proxy for multiple examples one can find in the climate “scientists” bag of tricks.)
I would ask again that you restore El Chichon to your Figure 6 so we can see all the data.
Margaret Hardman says:
“I stand by my comment that there are many omissions and if this is a work in progress it should be labelled as such at the beginning.”
Everything in science is a work in progress.
Nick Stokes says:
May 25, 2013 at 11:21 am
Nick,
I take it that you have a strong faith in the “canonized” IPPC “scripture”. It must hurt to question your faith.
Margaret Hardman
You demonstrate a considerable lack of humility for someone who has shown little evidence of understanding, or even reading, the recent posts by Mr Eschenbach. While that is obviously your prerogative on a site where comments are very largely unmoderated (unlike the warmist sites) I and I’m sure many others would have much more respect for your position if you actually did did the science and post your results in the comments section so we can all understand what it is you are saying. I’m sure valid results will be welcomed, so let’s all see how good you really are.
PS: I might add that Richard Feynman’s sister Joan, a former NASA astrophysicist, studies the effect of the sun on climate change. She is a real scientist, unlike consensus gate-keepers Hansen, Jones, Mann, et al. out to suppress the truth for personal & political gain.
Just to be fair to everyone lets see SH SST
http://climategrog.wordpress.com/?attachment_id=275
Margaret Hardman = Susan Anderson (artist, poet & astroturfer)
Anyone not familiar should check out Dot Earth.
Re. work in progress, Willis can correct me if wrong, but IMO one reason he posted his paper here was in order to obtain peer review more exacting than the pal review in which The Team engages. The more scathing the better, if cogent.
Margaret, if I may call you that, I’m sure we would all benefit from your detailed review of all or parts of Willis’ research effort, bringing to bear all the science you’ve studied and practiced. I for one look forward to it eagerly.
Awesome Willis!
I can’t help but think a unified theory of climate is forthcoming.
I’m not sure you’re taking the analysis out far enough I time. I’m just not convinced the magnitude of the 1998 El Niño wasn’t influenced by the 1991 Mt. Pinatubo eruption considering the very long lag times ocean circulations could potentially impart and it seems every graph I see touting about how well the models correlate (once they adjusted after the fact once they knew what answer they needed) with observations after the eruption stop @ 1996. It just looks like a big “S” overcorrection like one might expect from a damped oscillating system to me.
http://www.drroyspencer.com/latest-global-temperatures/
http://wattsupwiththat.com/2010/12/29/prediction-is-hard-especially-of-the-future/
Figure 5:
http://wattsupwiththat.com/2013/02/28/cmip5-model-data-comparison-satellite-era-sea-surface-temperature-anomalies/
If the gentleman has ability, he is magnanimous, generous, tolerant, and straightforward, through which he opens the way to instruct others.
Xun Zi
A true gentleman is one who is never unintentionally rude.”
Wilde, Oscar
I think that starts to describe Willis Eschenbach.
Thank you for your knowledge, wisdom, and not least of all, your patience.
Using my high tech equipment. I didn’t notice much the summer of 1991, when Pinatubo blew, but did notice a difference the next summer.
My high tech equipment was tomato plants. The summer of 1992 saw only about 8 fruits turn red, and every window sill in the house be loaded with green tomatoes the night of the first frost (which was early that autumn, as I recall.)
Of course, it is much easier to blame a volcano on the other side of the planet than it is to blame my own gardening.
Willis –
Your work showed that smoothing caused the cooling event in temperatures to start BEFORE the volcanic eruption. Is this the case with Antarctic ice core temperature data vs CO2 measurements, possibly because the two datasets are not the same statistically?
Greg Goodman says:
May 25, 2013 at 5:05 am
I’m not. I’m calculating the ECS from the transient response.
Thanks,
w.
Willis says: “I say that the temperature is regulated, not by the forcing, but by a host of overlapping natural emergent temperature control mechanisms, e.g. thunderstorms, the El Nino, the Pacific Decadal Oscillation, the timing of the onset of tropical clouds, and others. Changes in these and other natural regulatory phenomena quickly oppose any unusual rise or fall in temperature, and they work together to maintain the temperature very stably regardless of the differences in forcing.”
If that statement were true, why does the “regulator” break down so badly in the Paleo record?
JP
Willis – I happen to think that all that talk about volcanic forcing of global temperature is bullshit. As far as I can see the amount of real cooling is of the same order of magnitude as ordinary cloudiness variations and cannot be distinguished from that. I grant you that there are supervolcanos like Yellowstone whose eruptions have had colossal effects but ordinary stratovolcanos just don’t do that. Furthermore, all temperature dips in the global temperature curve that have been classified as volcanic cooling are nothing more than ordinary La Ninas, misidentified as volcanic cooling because they just happened to occur at a time when cooling subsequent to an eruption was expected. This is possible because the entire global temperature curve is a concatenation of El Nino peaks and their adjacent La Nina valleys. Since ENSO and volcanism are not in phase an eruption can coincide with any part of the ENSO system, and its nearness to a La Nina valley is determinant of how it is classified. As a result, there is no correlation between the reported strength of an eruption and the degree of this alleged cooling attributed to it. And don’t forget the total absence of cooling after important eruptions that may also occur and which has volcanologists scratching their heads. In this category are both Novarupta and El Chichon. Novarupta as you know was the strongest eruption of the twentieth century. This has gone so far now that it is built into climate models like the one you show in your lagged conversion bullshit figure. As a result, some scientists now are trying to use it to try to explain the unexplainable. Take Müller, for example. His global temperature curve goes back to 1750, more than any other curve. In one of the articles descring it by Rohde (Rohde et al., Geoinfor Geostat: An Overview 2012) there is a perfect example of this. In the late eighteenth and early nineteenth century they discovered that their temperature curve dipped strongly down but there were no volcanos nearby. They simply assumed that there had to be some undiscovered volcanos around to cause that cooling so they put them into their model. In their figure 5 they give the full temperature curve back to 1750, with 95 % confidence interval shown. Then they produce a simulated curve with volcanic sulfate emissions used to show that these dips could be volcanic coolings.That is a red curve laid on top of the data. It is not very accurate for any part of the data but they think it explains something. But this is doubly stupid. First they have been duped into believing that dips like that are always produced by volcanic cooling even if there is no volcano in sight. And secondly their temperature curve shows that these dips are part of a very interesting new phenomenon they are too stupid to notice. Namely, they are part of an oscillation that started before the beginning of their temperature record and continued for more than a century before subsiding. To be precise, the observable oscillation began in 1775, had a period of 25 years, had a continuously decreasing amplitude, and its amplitude became zero after 1900. If you know what a graph of an exponentially decreasing vibration looks like, this is it. It stares you in the face in their figure 5. I put it down to a cataclysmic event prior to the beginning of their temperature record but beyond this there are no clues. Identifying its source is obviously of great interest for climate theory and climate history but I doubt that the warmists will let go of any of their “climate research” billions to do actual climate research.
Arno Arrak says: To be precise, the observable oscillation began in 1775, had a period of 25 years, had a continuously decreasing amplitude, and its amplitude became zero after 1900.
That is also the pattern you get when two oscillations of similar frequencies interfere with each other. I found a similar pattern in artic ice coverage that I resolved as amplitude modulation of an internal 2 year oscillation by a 12.85 year oscillation that is also found in N. Atlantic SST.
http://climategrog.wordpress.com/?attachment_id=216
It’s best to avoid being too dogmatic about such trivial observation as you make before have done some thorough investigation.
Re your 2nd Figure 6 (you have two), the stacked El Nino index, as others have noted it is unconvincing because the positive slopes precede the eruptions. The usual Gaia hypothesis treats the solid planet as the stage, not the player. Your stacked El Nino index, if used causally, implies that the solid planet is itself a player because it prepares the biosphere for the upcoming eruption (which is “known” only to the solid planet). That would be a very strong interpretation of the Gaia hypothesis indeed.
John B
Bad luck. Try your guessing game again. I am she as you are she and we are altogether.
From your “Overshoot” article: http://wattsupwiththat.com/2010/11/29/28644/
Note that in response to changed forcings, the governor brings the value back to the desired equilibrium value. The governor does this by producing what is called “overshoot”.
===
Apparently Willis you have getting this wrong for a couple of years. The overshoot is not _how_ it brings the system back to the control value.
The presence of overshoot or not is simple a question of how much damping there is in the system. Critical damping is usually regarded as optimal, it is where control variable overshoots once but does not fall below again before settling. If it does it is called under-damped. if does not overshoot it is called under-damped.
These categories can also apply to simple negative feedback system returning to equilibrium after a temporary “forcing” change. It has nothing to do with whether is linear, non linear or a ‘governor’.
They key factor that determines whether is a governor is whether it returns or it finds a new equilibrium. In fact it will never come back to exactly the same point if a permatent change is made to the forcing, but it will be close. This is the non-linear bit that enables it to act as a governor.
Now I don’t expect you to take my word for it but there are enough keywords there for you to read up on it and verify for yourself.
“I’m not. I’m calculating the ECS from the transient response.”
Then my question would be : why are you calculating the ECS from the transient response?
“if does not overshoot it is called under-damped. ” Oops , typo, that over-damped.
Willis,
Just want to encourage remembrance that most governed systems have a limit from which they cannot recover without a complete breakdown, or large excursion beyond the ‘range’ . . perhaps an understanding of which would explain the onset/initiation of Ice Ages . . or an understanding of Ice Age onsets would support your conclusions.
Thanks for rocking the boat.
ed mister jones . What are the limits of Willis’ governor? Totally clear sky and totally cloudy tropics. Totally clear sky is a credible evolution and may be what allows the system to flip into a glacial period.
The other extreme is difficult to imagine ever happening. This would the other “tipping point” where the governor would breakdown and we see a algorian thermageddon.
Just at a guess , I’d say we could dig all our coal and burn it next year with out it needing to block all solar input into the tropics to correct the forcing.
It’s a good point to raise though.
next question is where does the heat go when it gets pumped into the troposphere by tropical storms. Some will get radiaited to space , the rest goes gets transported to higher latitudes via Hadley circulation. (Yeah Hadley as in Hadley Centre).
It is interesting to look at the length of the Arctic melting season in relation to the tropical SST Willis is considering as governor.
http://climategrog.wordpress.com/?attachment_id=276
atarsinc says:
May 25, 2013 at 1:48 pm
————————————–
Without invoking Goddess Gaia, it seems clear to me that Mother Earth is homeostatic. The rare runaway positive feedbacks in the climatic record are quickly (at least in geo-time) regulated. Possible exceptions are the Snowball Earth episodes, to the extent that they actually happened, when correction may have taken much longer than usual.
Your example of the inception of Pleistocene & future ice ages from interglacials, as now, is not IMO an instance of our planet’s self-regulating system breaking down but of moving into a new mode, during which the same processes still operate. In interglacials Earth maintains its average temperature (to the extent that global temperature is a valid concept), let’s say, around 15 degrees C, while in glacial mode it might be 5-10 C (actual figures don’t matter, as merely illustrative here). Of course there are periods of excursions below & above the average, as around Heinrich Events, which could count as a third & coldest mode, more extreme than the mean glacial phase climate.
Margaret Hardman says:
May 25, 2013 at 2:26 pm
John B
Bad luck. Try your guessing game again. I am she as you are she and we are altogether.
You are the egg-man?
One could also just look at the Transient Climate sensitivity here.
Let’s take the Pinatubo example where forcing was between -3.0 W/m2 to -4.0 W/m2 (the higher number is from other sources).
Temperatures declined between -0.3C to -0.4C.
Transient Climate Sensivity = 0.1C / W/m2.
Otto 2013 has it at = 1.3C / 3.7W/m2 = 0.35C / W/m2; The IPCC AR4 and AR5 has it at about 2.0C / 4.2 W/m2 = 0.48C / w/m2
So, Pinatubo was just 72% lower that the new lower ECS of Otto 2013 and 79% lower than the IPCC.
And then compared the the Equilibrium Climate Sensitivity of 0.81C / W/m2, it is only 88% lower.
So, 72%, 79%, 88% lower – take your pick.
The caption to Figure 4 says, “Blue line shows the average of the modeled annual temperatures from the 15 climate models in the Forster paper, as discussed here.”
Was there supposed to be a link at “here” to a posting on the Foster paper?
The Foster paper, Table 1 shows 19 models, not 15 models. I tried to replicate your blue line from the annual data, column 3 of your “Forcings and Models.xlsx” file. The average model temperature of the year after the 6 volcano eruptions was 1.23 Celsius less than the average model temperature of the year before each of the 6 eruptions. This is very different from your blue line where the 24 month value is only 0.3 C less than the 0 month value. How did you calculate the blue line?
The average climate sensitivity of the climate models used by the IPCC is 3°C per doubling, the orange line. Why is the climate sensitivity of the 15 models in the Foster paper, calculated at 2.4 C, so much lower?
The paragraph above Figure 4 says, “Figure 3 shows the same records, with the addition of the results from the average models from the Forster study, the results that the models were calculated to have on average, and the results if we assume a climate sensitivity of 3.0 W/m2 per doubling of CO2.” Correction: Change “Figure 3” to “Figure 4”.
milodonharlani says:
May 25, 2013 at 3:13 pm
Milo, I believe you’ve made my case. Probably better than I. JP
onlyme says:
May 25, 2013 at 5:46 am
When you work in the real world with controlled processes and the PID controllers which keep the processes in control, you see strong evidence of bounce, lag and settling time which you refer to.
Yes, the PID analogy is interesting. Let’s see what we have:
plank radiation is T^4 but with fairly small variation in tropical SST in relation to the absolute temperature in kelvin, it can be approximated as linear.
Now the radiation is W/m2 , ie a power term, this is equivalent to dT/dt, so we have a D for our PID.
The conditions that trigger tropical storms are a fairly fixed local temperature to set off the positive feedback that sets off the emergent phenomenon of TS. As long as there is a finite number of storms This will tend to ensure the long term average does not drift off. This was demonstrated by Willis’ degree.day plots. We have the I for our PID.
Evaporation (outside the storms) is proportional to the temperature so , if it is not too much of a gross simplification, we have the P for out PID.
Now I’m not sure that God rides a Harley , but he’s a damn good systems engineer.
clipe says:
May 25, 2013 at 3:14 pm
Margaret Hardman says:
May 25, 2013 at 2:26 pm
John B
Bad luck. Try your guessing game again. I am she as you are she and we are altogether.
“You are the egg-man?”
Walrus I’m thinking.
http://www.jabberwocky.com/carroll/pics/glass20.gif
The Walrus and The Carpenter
Lewis Carroll
(from Through the Looking-Glass and What Alice Found There, 1872)
The sun was shining on the sea,
Shining with all his might:
He did his very best to make
The billows smooth and bright–
And this was odd, because it was
The middle of the night.
The moon was shining sulkily,
Because she thought the sun
Had got no business to be there
After the day was done–
“It’s very rude of him,” she said,
“To come and spoil the fun!”
The sea was wet as wet could be,
The sands were dry as dry.
You could not see a cloud, because
No cloud was in the sky:
No birds were flying overhead–
There were no birds to fly.
The Walrus and the Carpenter
Were walking close at hand;
They wept like anything to see
Such quantities of sand:
“If this were only cleared away,”
They said, “it would be grand!”
“If seven maids with seven mops
Swept it for half a year.
Do you suppose,” the Walrus said,
“That they could get it clear?”
“I doubt it,” said the Carpenter,
And shed a bitter tear.
“O Oysters, come and walk with us!”
The Walrus did beseech.
“A pleasant walk, a pleasant talk,
Along the briny beach:
We cannot do with more than four,
To give a hand to each.”
The eldest Oyster looked at him,
But never a word he said:
The eldest Oyster winked his eye,
And shook his heavy head–
Meaning to say he did not choose
To leave the oyster-bed.
But four young Oysters hurried up,
All eager for the treat:
Their coats were brushed, their faces washed,
Their shoes were clean and neat–
And this was odd, because, you know,
They hadn’t any feet.
Four other Oysters followed them,
And yet another four;
And thick and fast they came at last,
And more, and more, and more–
All hopping through the frothy waves,
And scrambling to the shore.
The Walrus and the Carpenter
Walked on a mile or so,
And then they rested on a rock
Conveniently low:
And all the little Oysters stood
And waited in a row.
“The time has come,” the Walrus said,
“To talk of many things:
Of shoes–and ships–and sealing-wax–
Of cabbages–and kings–
And why the sea is boiling hot–
And whether pigs have wings.”
“But wait a bit,” the Oysters cried,
“Before we have our chat;
For some of us are out of breath,
And all of us are fat!”
“No hurry!” said the Carpenter.
They thanked him much for that.
“A loaf of bread,” the Walrus said,
“Is what we chiefly need:
Pepper and vinegar besides
Are very good indeed–
Now if you’re ready, Oysters dear,
We can begin to feed.”
“But not on us!” the Oysters cried,
Turning a little blue.
“After such kindness, that would be
A dismal thing to do!”
“The night is fine,” the Walrus said.
“Do you admire the view?
“It was so kind of you to come!
And you are very nice!”
The Carpenter said nothing but
“Cut us another slice:
I wish you were not quite so deaf–
I’ve had to ask you twice!”
“It seems a shame,” the Walrus said,
“To play them such a trick,
After we’ve brought them out so far,
And made them trot so quick!”
The Carpenter said nothing but
“The butter’s spread too thick!”
“I weep for you,” the Walrus said:
“I deeply sympathize.”
With sobs and tears he sorted out
Those of the largest size,
Holding his pocket-handkerchief
Before his streaming eyes.
“O Oysters,” said the Carpenter,
“You’ve had a pleasant run!
Shall we be trotting home again?’
But answer came there none–
And this was scarcely odd, because
They’d eaten every one.
Bill Illis says:
“The El Ninos that developed after El Chichon and Pinatubo were already well into development before the volcanoes.”
That’s the other external short term forcing agent at work:
http://omniweb.gsfc.nasa.gov/tmp/images/ret_13439.gif
http://omniweb.gsfc.nasa.gov/tmp/images/ret_13542.gif
accompanied by low land temp’s in winter 1981-82, and early 1991.
Bill Inis: Let’s take the Pinatubo example where forcing was between -3.0 W/m2 to -4.0 W/m2 (the higher number is from other sources).
Temperatures declined between -0.3C to -0.4C.
Where do you see that temp drop Bill?
I see about -0.18 K, of which some is attributable to a pre-existing downward trend.
give it a large half at 0.1K with a forcing of at least 0.3 that gives a transient response of 0.033 K/W/m2
/Basically, I’m offering you the opportunity to read my laboratory notebook as I’m working on the issues, and you complain that it’s not a finished scientific paper?/
I am probably too easily embarrassed. I would never publish my lab notebook! But that’s me! 😀
/I say that after an eruption, the climate system actively responds to reductions in the incoming sunlight by altering various parts of the climate system to increase the amount of heat absorbed by other means./
Actively? That pushes it a bit too far for my taste.
Sure, after a volcanic eruption, the ash and aerosols diminish surface temperatures by blocking sunlight reaching the earth’s surface. A temporary effect as both ash and aerosols get washed out over a couple of years.
But I see no need to posit an ‘actively’ responding climate system. First of all, if surface temps decrease so does outgoing radiation. Secondly, the lower temperature may result in growing of ice sheets and snow in polar regions which may ‘take out part of the cold’ for the surface temperatures for years to come. Third, there is lots of thermal inertia in the climate system, especially in the oceans. When the effects of the eruption start to linger the heat content of the oceans may quickly bring back the surface temperatures to near pre-eruption levels. Also, there is no accounting for ongoing other forcing effects in this analysis, as others have already mentioned.
Summarizing I don’t see any need yet for positing an effect of tropical cloud onset time. If you could show with data that this changed after volcanic eruptions, then I might consider it.
Margaret Hardman says:
May 25, 2013 at 4:44 am
In the middle of marking university entrance individual studies/investigations. I would not give this a good mark. There are lots of confounding factors not taken into account, for example: how long do the particles erupted into the atmosphere remain there? What criteria are used for selecting the eruptions (there were twelve VEI 5 or 6 eruptions in the 20th century)? 14 eruptions would have given a better sample. Are the results statistically significant?
What effect did the eruption of Mount Hudson have in such close temporal proximity to Mt Pinatubo (VEI 5+ and 6 respectively)? Can you unpick the effects of the two eruptions? How much material was erupted into the atmosphere at these eruptions and the other eruptions? Can we see local effects and how far do those effects extend?
The conclusion needs to have strong valid evidence to support it which appears to be missing. Because unsubstantiated assumptions are made in this post, the assertions remain speculative at best and most probably wrong. There will be those that pick that last sentence out for criticism so I shall answer it now. Firstly, taking a simple equation that models part of the behaviour of the climate system and showing it might be wrong does not invalidate all climate models. I believe there are 19 models referenced by the IPCC. Even if this equation is fundamental to them all, the evidence here does not invalidate it.
I know nothing of the author but I would suspect they have not used their full scientific training in the production of this short article. Had they done so, they would have spent a considerable time looking in detail at the possible confounding factors surrounding the global temperatures for each of these eruptions and those that were left out.
Margaret, your arguments are missing the point: Willis has shown that the respective models do a very poor work in modeling volcanic forcings for the respective data analyzed.
You may want to give examples that fit closer to reality or reasons why they might miss in these cases.
The conclusion is strongly supported by the data shown, your comment is missing the points made and is not supported by anything. You do not bring arguments to what has been presented or new facts. Your words like “unsubstantiated assumptions” are just empty words as long as you do not show which/where such assumptions have been made, (which you fail miserably).
Nobody took “a simple equation that models part of the behaviour of the climate system”. Please read the post and try to understand it before you post answers. Trying to show yourself clever and showing you did not understand the basics of what has been said is really a bad start.
Furthermore you continue to say that what has been presented does not invalidate the models.
However we see that the respective models did a very poor job in modeling the climate post eruptions, actually missed in all examples. Just stating that without arguments is useless.
What you do is then ad-hominem. Whom do you try to impress here with empty words?
@Nick Stokes
Well, “canonical”, “current paradigm” – I’d expect you could actually quote scientists saying those things. Instead you just refer me to posts where you’re saying them.
I’ve gone through above what Forster et al say, and Otto et al, and it isn’t their paradigm. Otto specifically says that a proportional relation is not ot be expected after a volcano. So whose is it?
Nick, stop arguing semantics. No-one cares (including you).
Has Willis actually correctly shown the response of the models to volcanoes or not? Yes or no?
If you can show that the models don’t work as Willis claims, then do so. Don’t talk of “paradigms” and who has says what when, but show us how they actually model the results of major eruptions.
You won’t do so, of course, because semantics aside, Willis is basically correct in how they work. Reduced forcings lead directly to a cooling effect that is never negated, but continues indefinitely. And you can’t handle that.
Willis,
As others have mentioned, that last sentence needs to be changed to reference Tambora which erupted for over a week in April 1815 helping to cause the Year Without A Summer in 1816. The wikipedia information says it was at least four times the blast of Krakatoa, which is a really huge.
The effects of Krakatoa, occurring in the more modern era of 1883, are well-known. In fact when I was a kid in the 50’s it was commonly associated with the legendary 1888 blizzards in NYC and vicinity. These days those effects are seldom mentioned but it has always stuck with me and now I automatically expect at least a 5-year window to notice after-effects of large blasts like that. I suppose the main factor is what latitude it occurs at and whether it sends enough particulates into the stratosphere. Consequently precipitation must also be directly related to these blasts as they would seem to be excellent seeders for creation of raindrops and snowflakes.
Interestingly, that linked wiki page has a table called “Selected Volcanic Eruptions” that includes Northern Hemisphere Summer Anomaly for the eruptions and what jumps out is how there were several consecutive dips in temperature and long gaps with no change:
Kuwae 1452 -0.5°C
Huaynaputina 1600 -0.8°C
Tambora 1815 -0.5°C
Krakatoa 1883 -0.3°C
Santa Maria 1902 (none)
Novarupta 1912 -0.4°C
Mt. St. Helens 1980 (none)
El Chichón 1982 (yes) <– but what?
Nevado del Ruiz 1985 (none)
Pinatubo 1991 -0.5°C
So pretty much the entire alleged warming delta is routinely matched by periodic eruptions which means that citing a normal temperature within 0.5°C is futile, and temperature consistency relies solely on the fact of whether one is in a long eruption-less dry-spell or not. Somewhere there must be a complete list of all known eruptions and temperature anomalies, if not there ought to be.
Margaret Hardman says:
May 25, 2013 at 2:26 pm
“John B
Bad luck. Try your guessing game again. I am she as you are she and we are altogether.”
I’m guessing… Rob Ford.
Blade
As with so many volcanic eruptions (1258 is another example) the temperature had already been declining sharply BEFORE the eruption and bounced back very strongly afterwards
http://www.metoffice.gov.uk/hadobs/hadcet/
So how much effect it had is debatable as temperatures were declining anyway, but any effect it might have had was short lived
tonyb
Margaret Hardman is…Margaret Hardman of Leeds University.
I claim my £50 prize
Tonyb
Mooloo says: May 25, 2013 at 4:18 pm
“You won’t do so, of course, because semantics aside, Willis is basically correct in how they work. Reduced forcings lead directly to a cooling effect that is never negated, but continues indefinitely. And you can’t handle that.”
That’s completely wrong. Here is the plot of the 19-model average. It recovers from every eruption. No indefinite cooling effect – it rises 1°C over the period.
“If you can show that the models don’t work as Willis claims, then do so.”
Well, Willis claims that they track a lagged forcing of averages, and they do. But so do real temperatures. And if you want to show a regression of ΔT against ΔF for real temperatures, then it’s Forster’s Fig 6B, which also shows how the relation breaks down for volcanoes. Fig 4b shows the same effect for model HADCM3. So this behaviour is not a black mark against models.
The issue of the “current paradigm” isn’t semantics. Willis has laid out his post systematically – theory, investigations, conclusions and prediction. And the theory section is based on this paradigm. And then, in the conclusions:
“The first and most important conclusion is that the climate doesn’t work the way that the climate paradigm states— it is clearly not a linear response to forcing. If it were linear, the results would look like the models.”
First and most important. But that isn’t the climate paradigm, and it’s not how models work. That’s relevant.
Your most interesting and compelling post yet, Willis. Well done.
@Dr. Stefan Weiss (May 25, 2013 at 8:42 am)
A stimulating comment. Thank you.
____
@Greg Goodman (May 25, 2013 at 7:06 am)
Busy month — will have to wait for opportunity to discuss at level more than superficial.
Best Regards.
Has there been any studies on effects of solar eclipses on temperatures? The calculation of reduced solar insolation can be highly accurately calculated in this case.
Nick Stokes says:
May 25, 2013 at 11:21 am
Nick, the models themselves use that exact formula, ∆T = λ ∆F. What do you think I’ve been talking about? I just got through showing that the average of the climate models can be almost perfectly replicated using THAT EXACT FORMULA in its normal lagged version … and now you ask who uses the formula? Pay attention much?
Now, when the outcome of the current group of climate models, both singly and en masse, can be replicated by a single formula, then I think I’m justified in calling it “canonical”.
You really do need to follow the bouncing ball a bit more closely, Nick.
w.
Margaret Hardman says:
May 25, 2013 at 11:40 am
Margaret, to date you have not found a single flaw in my analysis. Yes, you’ve suggested avenues for further investigation, but you haven’t found one damn thing wrong with my work itself. Oh, you made yourself look stupid by babbling about the aerosols and how long they stayed in the air, not realizing that that all of that has been taken care of in the creation of the forcing dataset.
And other than your ill-advised foray into aerosols, mostly what you’ve been is patronizing and offensive.
So I fear that you complaining that the attack is ad hominem misses the point. You haven’t given us one scrap of scientific anything to work over and discuss … so people will naturally turn the discussion to your bad manners, and I can hardly blame them. My first response to you was … well, I was very unhappy with your priggish prima donna stance. But I toned it down, and tried to fill the hole between your ears … but given this latest response, I fear the task may be beyond my abilities.
The game’s not over, but it is late in the game for you. If you have some real scientific comment on my study to make, I’d suggest you make it now, and loud and clear, and you might stand a chance of salvaging your reputation.
w.
PS—You entered into this discussion and opened with an ad hominem, that I had not used my “full scientific training in the production of this short article”. That says nothing about the science, Margaret. It is nothing but a personal attack on me.
So you can take your whining about mean people posting ad hominems about you, and place it gently up your fundamental orifice. I don’t care for your style in the slightest, and your latest bitching about exactly what you started by doing just confirms my earlier impressions.
Willis,
Nick, the models themselves use that exact formula, ∆T = λ ∆F.
Is it so hard to give a quote?
‘can be replicated by a single formula, then I think I’m justified in calling it “canonical”.’
But you called it their canonical equation. Whose?
The formula that you showed achieved replication wasn’t ∆T = λ ∆F. Lagged exponential smoothing makes a big difference.
John B says:
Margaret Hardman
You demonstrate a considerable lack of humility for someone who has shown little evidence of understanding, or even reading, the recent posts by Mr Eschenbach. While that is obviously your prerogative on a site where comments are very largely unmoderated (unlike the warmist sites) I and I’m sure many others would have much more respect for your position if you actually did the science and post your results in the comments section so we can all understand what it is you are saying. I’m sure valid results will be welcomed, so let’s all see how good you really are.
Repeated for effect.
And climatereason says:
Margaret Hardman is …Margaret Hardman of Leeds University.
One quality most university employees share is being insufferable. Margaret passes that test with flying colors. But I suppose she has to live with her fellow promoters of catastrophic AGW, so maybe she feels she has no choice. Witness what happened to Judith Curry when she actually gave an opinion that deviated slightly from the “evil carbon” narrative: ‘Heretic! Apostate! Burn the witch!’ It takes someone with real character to disagree with the reigning paradigm, no matter how much it has been deconstructed — and in this case, by the planet itself.
It is sad to see yet another university lemming march in lock-step with the prevailing egghead narrative. At what point did theese people stop thinking for themselves? Why have tenure, if they’re going to always be in agreement?
Margaret Hardman says:
May 25, 2013 at 12:05 pm
Margaret, you started out with a patronizing, unpleasant ad hominem attack on me. I was not the only one who found it patronizing. So I thought I’d see how you like it … not much fun, huh?
And once again, your “surety” turns out to be completely false … but I suppose that’s no surprise in your world.
Look, Margaret, you don’t want to get into a pissing contest with me. You came in riding on your high horse, letting us know that you grade other peoples work, as if that meant anything other than a pathetic attempt to impress. You proceeded to tell me I wasn’t working hard enough, wasn’t putting my scientific training to work … is that how your momma taught you to come into a room full of strangers, with an insult on your lips for the host?
l doubt she did … well, as a result of you showing up to grade us all, your work in this thread has been graded by all the folks here. By and large, you got a D. I haven’t heard one person defend you.
I started out with a C. Then it went to a D. After your last email, I’d give you an F simply for being too stupid to realize that you’ve lost badly and people are starting to snicker and laugh … but hey, that’s just me.
w.
Jimbo says:
May 25, 2013 at 12:21 pm
Curiously, I strongly hope that that happens. I realized long ago that I could accomplish almost anything if I didn’t care who got the credit …
w.
Willis, I want to focus on an astounding observation you have made about the data. But I want to draw attention to it by quibbling with a statement you made between Figure 4 and 5:
This is where you introduce the “degree-days” or “degree-months” concept. From first principles, I see no theoretical reason why any non-active system needs to restore the degree-months balance.
Through your insight in Figure 5, what is astonishing is that the data shows that the system does indeed return to a degree-month balance and does so quickly. Equally obvious is that the climate models do not behave this way and that the cold must linger on in models for years.
For the moment, forget the “Why?” “Degree-days” is a well known agricultural term. We have been conditioned to “know” that volcanic eruptions create “year-without-summers” and therefore volcanic eruptions must lengthen the time to bring in a crop and increasing the chance of crop failure by reducing the cumulative degree-days as a function of calendar date. This is what we have been taught. This is what we have confirmed from legend. This is what most of us would have assumed to happen. No surprise, the climate models behave according to legend.
In Figures 4 and 5 Willis shows us DATA that does not behave according to legend; doesn’t behave according to models; so it must not behave according to theory. Either Willis got the data in figure 5 wrong or the theory on which the models are built is wrong. Full stop. It is true from the data that we loose about 30 degree-days over 12 months. But the data show that we stop losing ground in the second year and make it back by year 4, while the models fall further behind. Who predicted this before looking at the data? In a sense, Figure 5 is as earth shaking a result a the Michelson-Morley experiment — an expected signal is not to be seen in the data.
It is only as extra credit that Willis proffers his expected response from a governed, lagged system hypothesis. Furthermore, the governor apparently does not govern just temperature, but governs something like a “degree-day” quantity. Profound! The system does not NEED to operate this way. That it DOES is the jewel Willis uncovered.
Thank you for the enlightening evening, Mr. Eschenbach.
Nick, the models themselves use that exact formula, ∆T = λ ∆F. What do you think I’ve been talking about? I just got through showing that the average of the climate models can be almost perfectly replicated using THAT EXACT FORMULA in its normal lagged version … and now you ask who uses the formula? Pay attention much?
###################
actually having been through ModelE’s source code I can tell you that they do not use that formula. Not in any way shape or form.
Not ModelE. Not the MITGCM. Not CCSM4.
None of them.
Not a single one.
Mosher,
The question is not whether the models use that actual code. I believe the argument was that you can replicate the model results using that code. Willis’ argument was that his code reverse engineered the models. The contention was functional equivalence.
Nick, Steven,
Are you just fiddling around here or what?
Also, ‘the average climate models can be almost perfectly replicated using THAT EXACT FORMULA’ makes me think Willis isn’t arguing anybody’s going to see that in the source code.
In almost all engineered control systems, which aim to keep some state variable (e.g. velocity, voltage, temperature) at a desired value as closely as possible, there is some sort of “integral action” in the control algorithm. This aspect of control integrates the deviation from the set point over time, providing a restoring effort due to the integral of the deviation, and not just the deviation itself. (The units of the integrated deviation are the quantity being controlled multiplied by time, e.g. “degree days”.) This action is necessary to maintain the system precisely at the set point even if there is a continual “disturbance” to the system, such as the gravitational load on a mass that you are trying to hold at a specific height.
If such a system is subject to a temporary disturbance, the integrator charges up in response so that the system can return to the set point even with the disturbance present. If the disturbance then disappears, the only way for the integrator to “discharge” is to have the system overshoot the set point so the error is of the other sign for a while.
Willis’ argument here is that the climate system is behaving more like an engineered control system with integral action (what he refers to as a governor) than as a system with simple proportional feedback. As far as I can tell, there is no mechanism, implicit or explicit, in any of the mainstream climate models that provides any kind of integrated restoring action, as opposed to simple proportional restoring action (which lessens, but does not eliminate, the deviation due to a constant disturbance, and will not overshoot on disappearance of the disturbance).
The responses to the temporary volcanic disturbances (from reduction of admitted solar radiation) that Willis shows are consistent with his argument, and should at least prompt some more analysis. Even if you don’t think that the integrated error value, in degree-days, is physically meaningful to you, you should at least consider the possibility of restoring actions proportional to it.
In the Appendix Data section there is a link to an Excel file “Forcings and Models.xlsx”. It shows in column E the “Forster Model Results” in Celsius. It shows the minimum temperature for the Kratatoa eruption as -1.68 C in 1884.
The Excel file “CHIP5 black box reconstruction.xlsx given at the bottom of the post “Model Climate Sensitivity Calculated Directly From Model Results” column D, “Modeled Temperature” shows the 1884 value as -0.23 C. As far as I can tell, both of these files is supposed to be the Forster model average temperature outputs. Why are they different?
Mark Bofill says: May 25, 2013 at 8:16 pm
“Also, ‘the average climate models can be almost perfectly replicated using THAT EXACT FORMULA’ “
Again, no. The formula Willis used was:
T(n+1) = T(n)+λ ∆F(n+1) * (1-exp(-1/τ)) + ΔT(n) exp( -∆T / τ )
Not at all the same. Apart from anything else, there is an extra parameter.τ.
Ken Gregory May 25, 2013 at 8:22 pm
“As far as I can tell, both of these files is supposed to be the Forster model average temperature outputs. Why are they different?”
Ken,
That’s one of the things that had me puzzled back here. But I found that col E, although headed “Foster Model Results (°C)” seem to be actually forcings. Col F seem to be the 19 model average temperatures. and I think are what was used.
Nick Stokes: Again, no. The formula Willis used was:
T(n+1) = T(n)+λ ∆F(n+1) * (1-exp(-1/τ)) + ΔT(n) exp( -∆T / τ )
Not at all the same. Apart from anything else, there is an extra parameter.τ.
Mark Bofill did not write that something was “the same”; he wrote that Willis’ formula almost perfectly replicated the model results. I have read all of your comments, and I can not find where you claim that Willis Eschenbach’s replicated climate model response actually has a significant amount of error — enough, say, that the visual impression conveyed by figure 5 is wrong. His “reverse engineering” of the climate model output has in the past been pretty accurate. He has a better model for the models, so the speak, than the models are for the climate data.
Margaret Hardman: There are lots of confounding factors not taken into account, for example: how long do the particles erupted into the atmosphere remain there?
That is a good question for a follow-up paper. It parallels my request that Willis provide a time-locked plot of the aerosol indices (if such are available.) That he has not done so yet does not undermine the point of the present post. If motivated, we are all free to follow up on this excellent post.
Thanks for the reply Nick. You said, “Col F seem to be the 19 model average temperatures”, but Column F is blank.
Column E of the “Forcings and Models.xlsx” labelled “Forster Model Results (°C)” has values identical to Column G of the file “CHIP5 black box reconstruction.xlsx” labelled “Ave. Model Forcing” in W’/m2.
Column B of “Forcings and Models.xlsx” is labeled “Forster Forcing W/m2″. The values are similar to the values in Column E, but not identical. Why are they different?
Column D of file “CHIP5 black box reconstruction.xlsx” is labeled “Modeled Temperature” which is likely the temperature used to create the blue curve of figure 4.
How are we supposed to make sense of this work when the columns in the spreadsheet is mislabeled?
Well I can tell you this, if baby Krackatoa erupts again, we will find out how long dusts stays in the atmosphere. From what I have studied, it can cool the climate for a number of years, and ruin crops sometimes a thousand and more miles away. After the Thera and Mt.Vesuvius explosions in or around 1628 BC, China’s temps plummeted and they had frosts form and kill summer crops. The sun was obliterated and they had a 7 year drought. Volcanoes are not to be underestimated, especially when they have remained dormant for a number of years and suddenly erupt, they are the most dangerous rather than continual minor eruptions, like Etna and Stromboli and the Hawaiian volcanoes. We have hot spots in South Australia and Victoria, and they rumble occasionally. Last eruption only 5,000 years ago, so it ain’t extinct.
I copied column D “Modeled Temperature” of the file “CHIP5 black box reconstruction.xlsx” into the “Forcings and Models.xlsx” file in Column G, and calculated the average temperatures of the years of the six volcanic eruptions, and the years before and after the eruptions to replicate the blue curve of Figure 4. The calculated temperatures from the Forster modeled temperatures are:
Year deg. C
-2 0.00
-1 0.00
0 -0.18
1 -0.35
2 -0.23
3 -0.10
4 -0.06
This is shown in column V of my file:
http://www.friendsofscience.org/assets/files/WillisE Forcings and Models.xlsx
This is not similar to blue curve of Figure 4, described as the average of the modeled annual temperatures from the 15 climate models in the Forster paper. As I mentioned in my previous comment, the Forster model average is of 19 models, not 15 models. The volcanoes did not erupt at the beginning of each year. Was some correction made to the annual modeled data to account for the actual month of eruption?
Willis, can you please provide the spreadsheet used to create Figure 4?
Ken.
“Column F is blank”
There is something strange here. In my version of “Forcings and Models.xlsx”, seen in Open Office, it is indeed blank. But when OO sees it as an ODS file, it is filled with the temperature values, which seem to be the right ones.
Ken,
Oops, my apologies. I think I may have pasted the numbers in the ods file myself.
I change the file name to replace the blanks with _ so the link should work.
http://www.friendsofscience.org/assets/files/WillisE_Forcings_and_Models.xlsx
Patrick Michaels and Paul Knappenberger writes about anti-information from the Canadian climate model, run by Andrew Weaver at the Canadian Centre for Climate Modelling and Analysis.
http://wattsupwiththat.com/2013/05/23/anti-information-in-climate-models/
The Canadian Climate Model forecast one of the most extreme warming for the 21st century of all models. They write, “The differences between the predictions and the observed temperatures were significantly greater (by a factor of two) than what one would get just applying random numbers.”
I made a plot from Climate Explorer, CMIP5, comparing the Canadian model to observations:
http://www.friendsofscience.org/assets/documents/FOS%20Essay/CanESM2.jpg
With the model forced matched to the HadCRUT observations during the 1960s, the discrepancy between the model and 2012 average temperature is 0.71 Celsius. The climate modelers headed by Dr. Weaver obviously have no clue about how the climate works.
Dr. Weaver has sued Dr. Tim Ball for making remarks about Dr. Weaver’s climate modeling skills.
“[Margaret Hardman] … you’ve lost badly and people are starting to snicker and laugh …”
[Eschenbach]
LOL. It’s worse than that. After awhile, whenever I saw her name “says…,” I just scrolled down, skimming as the text flowed by, and always coming away with the impression of a deeply troubled, prideful, person of average intelligence far out of her depth.
Well, Ms. Hardman, don’t feel too bad. I’m sure most of the scientists here do that with my posts, too.
But, I don’t pretend to be science-saavy.
I hope you can find a way to start being the REAL you. That is the only way you will ever be happy. Post something that allows your strengths to shine.
Love yourself, love who you ARE.
And then, I think you’ll find that others will love you, too.
Steven Mosher says:
May 25, 2013 at 7:51 pm
Having been through the Model E’s source code myself, I’ve never seen it there … but that wasn’t my meaning. Sorry for the lack of clarity. What I meant was that the Model E is functionally equivalent to that equation. As I have been saying over and over again in the last three posts, my meaning was that the Model E’s output can be replicated, to about 99% accuracy, by that simple equation. As can the others. They are all functionally equivalent to that equation.
The ModelE. The MITGCM. The CCSM4.
All of them.
Every single one.
But then you knew that was my meaning. After all, in what you quoted above I said:
So you knew or should have known that I was talking about functional equivalence and not actual appearance in the code.
As to the equation, you were the one who posted that very equation in my last thread, saying “write this down”, and I took heed. So why are you now propping up Nick Stokes, of all people? Your post makes it sound like he’s right about the equation and that it’s made up somehow, that no one uses it.
Which as you well know as someone who just posted the equation, is a load of total and complete Nick Stokes bollocks.
w.
Nick Stokes says:
May 25, 2013 at 8:43 pm
Nick, that’s pedantic hogwash. Here is my exact statement, with my added emphasis:
You see the part there about the “normal lagged version”? That’s where the tau comes in. So yes, it is exactly as I said. THAT EXACT FORMULA in its normal lagged version. You can’t have a lagged version without a time constant of some sort.
Folks, you remember I warned you that Nick would do this. Pedantic nitpicking of the highest order is his specialty. He’s good at trying to tear things down, he’s ridiculously bad at actually identifying a real problem, and as for actually building something up and moving the conversation forwards?
I have no idea how good he is at that … never seen the man attempt it …
w.
Janice Moore
May 25, 2013 at 11:16 pm
I notice a trope, a meme if you like, that runs through all so-called skeptical blogs and forums (9/11 truthers, antivaxxers, etc) – sooner or later the discussion turns personal. I don’t know you. You don’t know me. You have no idea who I am and beyond a few little biographical details that I have given freely, you probably never will. However, you choose to analyse me, just as others chose to insult or patronise me. I pointed out earlier, on the basis of five data points, that Mr Eschenbach’s thesis is unlikely to overturn a real scientist’s views on the models used in understanding the Earth’s climate. I asked for the criteria – it seems he chose the biggest, although there is no explanation of what source the list came from. I got patronised in return by the author. Hardly the response of someone keen to get the truth out, I would have thought.
There are people better qualified than me to examine this article and find the flaws in it. But that is what science does, all the time. Scientists read these things, find fault, examine their assumptions and communicate these concerns so that the science can become better and tigher. I’ve read Eschenbach’s Brief Communcation Arising on O’Reilly et al’s paper on warming in Lake Tanganyika and the response. The former was measured and reference free (aside from the necessary reference to the original paper). The response was measured and fully referenced. My point is that real working scientists are open with their methods (cue long and tedious thing about Climategate, blah, blah, blah) and welcome scrutiny. Pseudoscientists and aspiring scientists do not always get this. There may be something in the work of Mr Eschenbach that should be taken seriously. In which case, he needs seriously to work on it to put it into the sort of shape that will be accepted by a proper journal and not posted on some blog or other, even one that hilariously wins awards for its science.
So I may be prideful, I may be of average intelligence but I’m not sure I descend to the level of name calling and amateur psychiatry. I’m quite happy as I am, thank you. I’m looking forward to a day of marking, gardening and, if time permits, educating myself just a little bit more. In the meantime, read on: http://blog.hotwhopper.com/2013/05/wondering-willis-volcanoes-and-dunning.html#comment-form
Willis,
“THAT EXACT FORMULA in its normal lagged version”
What’s the normal value of τ?
Why put EXACT in caps when it isn’t that at all?
But the thing is, as I said above, Lucia among others has shown that exponentially smoothed forcing can be fitted to measured surface temperatures too. It’s a big extension of the “paradigm”.
“Your post makes it sound like he’s right about the equation and that it’s made up somehow, that no one uses it.”
Well, you’ve said it is the “climate paradigm” and “their canonical equation”. All you need to do to fix that is quote someone using it that way. That just isn’t happening.
But I think Ken Gregory has a point. The reason why I was stuck early on trying to locate the model output data in the spreadsheet you posted is that it isn’t there.
Willis: “So you knew or should have known that I was talking about functional equivalence and not actual appearance in the code.”
Willis, just admit what you said is CAPS was not what you “meant”. It is not for other to “should know” , it is for you to state what you mean and if you make an error or express something badly just admit it rather than getting into long acrimonious discussions.
Your last post was am important demonstration of how close the model behaviours is to this trivial linear model. Just correct you text to say what you meant and then we can get back to real point of this thread.
Stephen Rasey : “It is only as extra credit that Willis proffers his expected response from a governed, lagged system hypothesis. Furthermore, the governor apparently does not govern just temperature, but governs something like a “degree-day” quantity. Profound! The system does not NEED to operate this way. That it DOES is the jewel Willis uncovered.”
Yes, I think this is another important feature that Willis has discovered. This goes _beyond_ his idea of a governor mechanism since a governor will just restore the controlled variable not it’s integral. I corrected him on this earlier but he has not responded to that comment.
Like all hypotheses I’m sure this one can be improved and hopefully Willis will look at the technical points I have raised, none of which undo his basic premise but should make it less prone to rejection because he got some details wrong.
I should clarify something I said earlier. Linear negative feedback will only cause overshoot in a system with inertia. Most mechanical damped spring systems like car shocks do this. Climate temps could possibly show inertia by setting masses or air or water in motion but I doubt we are seeing that here.
The key misunderstanding here is that overshoot is proof of a non linear governor. It is neither necessary to see that in a governed system nor it is proof of non-linear feedback.
The degree.day integration is an important find but this is not a feature of a governor either. The key feature of a governor is the return, not the overshoot.
Nick Stokes: “That’s completely wrong. Here is the plot of the 19-model average. It recovers from every eruption. No indefinite cooling effect – it rises 1°C over the period.”
Climate models do not “recover” from the eruption, they have other positive feedbacks , mainly GHG, bot also other small ones, which are positive.
This is KEY to what Willis has pointed out. The two are not the same.
What they have is exaggerated positive forcings which counteract the incorrect response to volcanism. This means they get _roughly_ the right global average response while both are present and go tit’s up when one or the other is missing : post 2000.
There is NO cooling in the real climate:
http://climategrog.wordpress.com/?attachment_id=270
http://climategrog.wordpress.com/?attachment_id=271
http://climategrog.wordpress.com/?attachment_id=275
All the modelled cooling does is coincide with the already happening downward trends that figure 4 shows , on average, coincide with the major eruptions.
The fact Willis showed in his previous post, that despite all the smoke and mirrors, the net response is _equivalent_ to a linear model verifies what I’ve just said. The models to not “recover” from eruptions, they just have equally incorrect positive forcings that compensate.
Me says: “The degree.day integration is an important find but this is not a feature of a governor either. The key feature of a governor is the return, not the overshoot.”
Since Willis has shown the degree.day integrator is kept constant , this means that the overshoot is stronger than that of an damped governor feedback. This comes back to the idea of a PID controller that I discussed in more detail earlier:
http://wattsupwiththat.com/2013/05/25/stacked-volcanoes-falsify-models/#comment-1316550
Thanks to “onlyme ” for bringing that up.
Willis, have another think about the degree.day integrator. This is a separate feature you have found and I think it is probably as significant a find as the governor. Possible more so.
Willis write “One crazy thing is that the system is almost invisible. I mean, who’s going to notice if on average the clouds are forming up a half hour earlier?”
Our best weather forecasting models (and I mean short term here) can predict storms but are limited to “late afternoon” or “morning” and cant resolve specific factors to give timings. They’re not going to be able to model changes such as increasingly earlier onsets because they simply dont have that resolution in their predictions.
I think your ideas of the earth’s climate being a governed system are intuitively satisfying and believe that they are almost certainly going to be important ideas to explore if we’re to understand our climate. I also believe there will be resistance to them because modellers know they cant model emergent properties with anything like the accuracy we’re going to need if we’re to understand CO2’s role in changes in the atmosphere.
Another slight correction Willis, you have often referred to what you are calculating as being a “lagged” response. However, there is not lag term in your equations. The deltaT is simply a course numerical integration method. dT=1 year is the integration step , not a lag.
You could do the same calculation with a one month integrations step and get the _same_ results, just with more resolution. This is not a lag in the response you are modelling which you appear to think it is.
Again, don’t get annoyed by all these corrections. You are basically right, making important discoveries and backing them up. I’m trying to reinforce your efforts by correcting them, not trying to knock what you’re doing.
best regards, Greg.
Timthetoolman: “I also believe there will be resistance to them because modellers know they cant model emergent properties with anything like the accuracy we’re going to need if we’re to understand CO2′s role in changes in the atmosphere.”
There are technical solutions to global resolution not being sufficient for storms. The resistance will come because of dogma, orthodoxy and the self-interest of maintaining alarm to maintain funding. Add a tint of political bias is you wish.
Greg writes “There are technical solutions to global resolution not being sufficient for storms. ”
Not for the problem of modelling changes to onset times, there aren’t. If you cant precisely model a storm’s initiation then you cant model changes to it either. This isn’t a problem like maintaining energy conservation where you can check the result.
Willis black box formula is actually an “exponential moving average”
https://en.wikipedia.org/wiki/Moving_average
No, I am not Margaret Hardman of Leeds University. I once worked in a university but resigned on the principle that it was introducing a course in pseudoscience (in this case homeopathy).
I don’t see any fundamental reason why modelling the basic physics on a local, high resolution grid, would not produce a storm. If SST is higher more would erupt or they would erupt earlier. You don’t model when they erupt you model the causes and watch.
Once a working model on a local scale can imitate something like real behaviour this could be used to as a basis for cloud parameters fed to GSMs. This kind of approach is used to when ice models of Arctic are linked in.
If modellers were to recognise this is one area where the current paradigm was producing fundamentally incorrect behaviour , they could attack the problem.
The current reluctance is because of the reasons I outlined, not technical impossibility. That does not scare them off trying to model the whole world form first principals , does it?
Greg Goodman says: May 26, 2013 at 2:20 am
Greg,
I think you’re trying to deduce a lot of dynamics from not many yearss data there.
But Ken G has raised the question of whether they are even right. And I get similar results to his. I averaged the 19 model average from Willis’ earlier spreadsheet (digitized) by calendar year. I took the five eruptions that Willis used – Ken took all 6. My results for 9 years were:
0.22 0.21 *0.15* -0.01 0.01 0.09 0.12 0.15 0.17
I’ve starred the eruption year. These are offset up from Ken’s, not sure why. But the pattern is the same. A smaller dip, not so different to Hadcrut, and a more rapid recovery. You might like to try yourself on that spreadsheet.
Margaret, do you realize the purpose of Eschenbach’s article is not talking about you? Presumably most of the readers would agree.
We noticed your complaints. You have been answered. Looks like quite enough.
Stephen Rasey says:
May 25, 2013 at 7:34 pm
“…From first principles, I see no theoretical reason why any non-active system needs to restore the degree-months balance…”
Hi Stephen – have a look at the ‘law’ of Maximum Entropy Production (MEP) and Spatiotemporal Chaos to get some insight into reasons why the balance gets restored.
@Margaret Hardman – Do some serious reading about the ideas of Sir Karl Raimund Popper before you sail into the fray about the post normal scientific mess which climate science has become. It’s also worth a look at the work of Khun, for balance, then making your own decision about the value of the scientific method currently being employed by academia and the worth of the IPCC climate reports.
Margaret Hardman says:
May 25, 2013 at 4:44 am
“The conclusion needs to have strong valid evidence to support it which appears to be missing. Because unsubstantiated assumptions are made in this post, the assertions remain speculative at best and most probably wrong. There will be those that pick that last sentence out for criticism so I shall answer it now. Firstly, taking a simple equation that models part of the behaviour of the climate system and showing it might be wrong does not invalidate all climate models. I believe there are 19 models referenced by the IPCC. Even if this equation is fundamental to them all, the evidence here does not invalidate it.”
Where is the “strong valid evidence” that supports any of the IPCC models? Do you just ASSUME they are valid? It seems so. You are strongly biassed. Show your evidence.
Jesus, about half this thread is now about one irrelevant comment. Everyone, DROP it , please.
We’re discussing volcano forcings , right?
People might be interested in this paper which is a detailed study of the response to Pinatubo. It looks at radiative fluxes and water vapor as well as LT temperature.
Nick: “I’ve starred the eruption year. These are offset up from Ken’s, not sure why. But the pattern is the same. A smaller dip, not so different to Hadcrut, and a more rapid recovery. You might like to try yourself on that spreadsheet.”
This looks to be rather a mess. 15 or 19 ? Yours and Ken’s having an offset, mislabelled columns?
There is something that needs clarifying here. Since all this comes from Willis’ xlsx files and his digitisation of Forster et al , hopefully he will be able to explain what is going on.
For me I have enough work to do on data to start trying to hindcast other people’s copy/paste errors. Hopefully those responsible can straighten this out.
I also think the real volcanic forcing is how much the surface solar radiation falls. And that is 3.0% to 4.0% for Pinatubo or 7.0 W/m2 to 10.0 W/m2.
The reduced OLR is a negative radiative feedback, not a forcing.
So,one can do the math all over using those numbers.
While there has been a great deal of obfuscation on this thread, the simple fact is that real-world experiments like volcanoes always turn out to have much less impact than global warming predicts with its forcing —-> forcings + feedbacks —-> temperature increase
Always.
Ken,
Unfortunately I couldn’t get to your spreadsheet – the link just went to FoS homepage.
I showed my results above – I realize now that you followed Willis in setting the eruption year (or near) average to zero, which explains the offset. They still don’t quite match, but that may be because I made no allowance for eruption month.
It would appear that any response lasting between 6 months (small eruption – like Iceland’s 2x years ago) to 18 months to 24 months (Pinatubo) would have to start explicitly with the year.month value.
Margaret Hardman says:
Well Margaret, you started your first post with an ad hominem against Willis by gas-bagging about his training and the mark he should be given, and you immediately turn your second post into another ad hom in which you ridicule his BA instead of considering his argument, so why on earth should John M not call you on it and give his reaction to the very personal and irrelevant remarks you made about Willis? You opened the door.
Nick Stokes says:
People might be interested in this paper which is a detailed study of the response to Pinatubo. It looks at radiative fluxes and water vapor as well as LT temperature
Yes, it is interesting. And yet more confirmation of my point about confounding pre-existing downward trends in temperature (and water vapour I can now add) with the effects of Pinatubo.
They blinker there temp data to start just before the the eruption and thus fail to notice that temps were falling ANYWAY.
http://climategrog.wordpress.com/?attachment_id=270
In view of rest of their paper this is very poor science. This invites an implicit and spurious assumption that temp and water vap. would have been flat except for occurrence of the eruption.
It is obvious once pointed out and demonstrably wrong if you look at the data. That does not necessarily mean their time constants are significantly wrong though.
They do also note the overshoot in TOA radiation budget which is in the sense of confirming Willis’ governor plus the fact it retains a small positive offset long after.
“The value then remains close to zero (or a very slight positive anomaly) for the remainder of the
timeseries.”
… and …
” This accords with Wielicki et al. [2002], who show that in the tropics the net flux departs from zero only for the duration of the SW anomaly, and tracks this anomaly quickly back to zero (and thereafter remains remarkably close to zero, at least within the ‘noise’ of the results). ”
Maybe with a little literature searching Willis may find published evidence of what he is proposing.
Thanks for pointing to a relevant starting point.
[“there temp data” ?? => “their temp data” perhaps? Mod.]
Nick, did you miss my comment of May 25, 2013 at 10:41 pm
I change the file name to replace the blanks with _ so the link should work.
http://www.friendsofscience.org/assets/files/WillisE_Forcings_and_Models.xlsx
It should be possible to measure whether volcanic eruptions cause a delay in tropical cloudiness.
If tropical clouds form later in the day then the earth’s albedo will decrease, as more solar radiation is absorbed by the ocean.
To measure the earth’s albedo, the brightness of the earthlit part of the moon can be used.
After a volcanic eruption the earthlit part of the moon should be less bright.
I think this would prove scenario B.
[“there temp data” ?? => “their temp data” perhaps? Mod.]
yes, the lack a preview facility on WP does reduce the possibility of spotting such typos. I corrected myself on that same fault few days back.
Thanks for the irrelevant knit-pick.
@Margaret Hardman,
Your comments are hilarious – please keep them coming!
@Willis:
Thanks for another fascinating analysis. No doubt having failed to do the work of validating their models themselves, the climate science community will be roundly applauding you and patting you on the back for your efforts and contribution to their understanding.
It’s funny that when criticised for models’ lack of ability to reproduce regional or specific phenomenological details of climate behaviour, their proponents jump up and down yelling “you’re failing to see the big picture!”, whilst pointing furiously to the exact type of linear ‘black box’ behaviour of the models that Willis has clearly explained – forcing goes in – global temperature comes out. Then, when he points out that even when treated as a simple black box, the models fail to reflect any kind of observed reality, the usual drones (Stokes et al) come out of the woodwork accusing him of failing to grasp the beautiful complexity of the great wizard’s mind. Which is it guys? Could it be the thing you’ve bought into is a load of utter balls; that even the models used for weather forecasting are the digital equivalent of an educated guess? Actually there are good arguments as to why a short term weather model could and should be more accurate than a climate model – more iterations of specific behaviour to go on. Also, why is it that you are able to nitpick trivial details of a post, yet you are unable to read clearly labelled links at the very top of a post that would answer all your questions (were they legitimate and not a crude attempt to kick up a load of dust).
***
Margaret Hardman says:
May 25, 2013 at 4:44 am
***
I get this black & white image of Ms Gulch riding her bike swiftly along a Kansas dirt road (cue scary music).
Margaret Hardman says:
May 25, 2013 at 4:44 am
“The conclusion needs to have strong valid evidence to support it which appears to be missing.”
=========
You are mistaken. Willis has presented observed, authoritative temperature data and compared this against the predicted response of climate models. The climate models fail to accurately describe observations. Under the scientific method this falsifies the models.
There is only one weakness that can be reasonably argued in what Willis has done, and to me this is a weak argument, because the weakness lies not in what Willis has done, but rather in the use of ensemble means in model forecasting.
Willis has used an equation that very closely approximates the ensemble mean of the climate models. This saves the significant cost and expense of running the climate models to extract the ensemble mean. An in doing so, Willis has exposed the flabby underbelly of climate models.
Climate models show is a limited range of what is possible. Some of what might happen. They then average these limited possibilities into an ensemble mean and claim that this matches the future. But this is a nonsense. The future is not an ensemble mean. Throw a pair of dice, the ensemble mean of your dice throw is 7. Does this mean that your throw must also be 7?
Thus, the weakness in Willi’s method in fact lies with the climate models and their use of the ensemble mean to represent the future. This simplifying assumption by climate science exposes the climate models to black box analysis and replication, as Willis has successfully done.
Margaret Hardman says:
May 26, 2013 at 12:42 am
I notice a trope, a meme if you like, that runs through all so-called skeptical blogs and forums (9/11 truthers, antivaxxers, etc) – sooner or later the discussion turns personal.
Dear Margaret, we have seen alarmists posting here. Some of them try to engage in constructive conversation but the bigger part is of trolls who come posting off-topic but on message posts.
http://bishophill.squarespace.com/blog/2010/3/19/josh-13.html
Now before becoming just another troll and spam the thread with nonsense please try to think a bit about what you know and what you do not know about global warming.
Do you know that the Met Office has revised significantly down its modeled predictions recently (silently without much noise about it?)
Do you know that the sensitivity that climate models use was suddenly reduced by 30%- something that skeptics say since years? The skeptics were right and your praised climate scientists consensus wrong?
http://joannenova.com.au/2013/05/major-30-reduction-in-modelers-estimates-of-climate-sensitivity-skeptics-were-right/
Do you know you insult all of us and including respected scientists like Ivar Giaever and Freeman Dyson putting skeptics in a basket with 9/11 truthers and so on? Of course you do.
Do you know this is the behavior of an intolerant cultist defending his religion who refuses to talk arguments but holds to his scripture?
As Ivar Giaever has already put it “Global warming is a new religion”:
http://hockeyschtick.blogspot.com.au/2012/07/nobel-prize-winning-physicist-explains.html
Please listen to him before posting another answer.
“Now before becoming just another troll and spam the thread with nonsense please …..”
The basic rule is DON’T FEED A TROLL.
You and others that keep bringing this irrelevance up are spamming this thread far more that the person you are so keen to criticise.
Enough !
Margaret Hardman says:
May 26, 2013 at 3:58 am
I once worked in a university but resigned on the principle that it was introducing a course in pseudoscience (in this case homeopathy).
=========
You got out just in time. They are now introducing all sorts of pseudoscience courses with the name “science” after them to confuse the gullible.
Similar to what happens in politics when countries that are not democratic use the word “democratic” in their name. No democracy has ever needed to use the word “democratic” in their name. Which would you consider more likely to be democratic? The “United States” or the “People’s Democratic Republic of the United States”?
Number 1 rule. Any “science” that needs to add the word “science” to their name is not.
@Tenuc at 4:19 am
have a look at the ‘law’ of Maximum Entropy Production (MEP) and Spatiotemporal Chaos to get some insight into reasons why the balance gets restored.
MEP and Chaos are hardly first principles of physics. They are non-unique explainations of observed phenomina. Many chaotic systems do not show quick returns to a baseline. Indeed, the hallmark of chaotic systems is the existance of multiple local stability points. Chaos is an argument that better describes the climate models.
Greg Goodman says:
May 26, 2013 at 1:39 am
Willis: “So you knew or should have known that I was talking about functional equivalence and not actual appearance in the code.”
Willis, just admit what you said is CAPS was not what you “meant”. It is not for other to “should know” , it is for you to state what you mean and if you make an error or express something badly just admit it rather than getting into long acrimonious discussions.
———————-
Yes. I think it’s good for all parties to be as clear as possible. I wasted time I’d rather not have spent under the assumption that Nick was pointing out an error of actual substance by digging through that other thread he referred me to, instead of the a statement of the obvious and the implication that Willis misspoke or spoke poorly in that spot; so I think it would also be helpful if critics would make their points more lucid.
Ulric Lyons says:
May 25, 2013 at 7:11 am
Mann was onto this a while back:
http://www.nature.com/nature/journal/v426/n6964/abs/nature02101.html
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-3276.1
http://www.geotimes.org/feb04/NN_volcElNino.html
So Mann and a whole bunch of published authors are aware of and have documented this tendency for climate to actively compensate for such perturbations yet none of this is reflected in GCM type climate model behaviour.
Yet the IPCC is in the process of rolling out more of the same with an (incrementally) reduced climate sensitivity.
@Tenuc
Read Popper, Kuhn, Feyerabend, Lakagos, Nagel, Polanyi, Ayer and others on the philosophy of science but thanks for the recommendations. I still do not see how such a firm conclusion based on such a small sample size can be justified. The findings can be little more than tentative. There are 14 VEI 5 and 6 eruptions starting with Krakatoa. The selection criteria are woolly. The decision on which is an outlier or not and then to discard it has to be taken with extreme caution since there is a small sample.
Willis,
Your work here has given me some valuable insight. I’m always on the lookout for valid information as related to weather, as there seems to be a plethora of propaganda.
Donny Griffin/Lake City, FL
Ah so we get to discuss the article, cool.
I and several others have pointed out the selection bias. Willis replies that it does make any difference, so we seem agreed he had no need to do it. It is a technical error that he would do well to correct but will not change the effect he is highlighting.
I think the selection criterion is those events that are visible in the volcanic “forcing” data used in Forster et al, so may be look at that paper to see what was taken into account.
The stacking method is a bit crude since it is based on the assumption that any other variations will average out. This is indeed rather optimistic in view of the sample size. So having established what appears to be a relationship, this would justify a more rigorous investigation.
It also revealed that there is, on average, a downward trend in temps before the average eruption. This will give a false impression of a volcanic cooling effect if is not removed somehow. That is clearly a problem and part of the reason for the perceived volcanic cooling.
A next step could be to compensate for the average downward trend on the assumption that it would continue through the post eruption period. This is fictitious but probably less so than than assuming it would stop the moment of an eruption which is what is implicitly done by ignoring it as has been done so far in all studies I’ve have read.
I would at least serve to make the point and give an estimation of the size of the effect induced by ignoring it.
Greg, some of that downward trend prior to official dramatic eruption may be due to increased volcanic activity leading up to eruption. I would be careful about simply correcting it away, even if that was easy to do. It might be better to try to quantify it and see if it is also a recurrent pattern or just happenstance depending on timing of eruption relative to existing climate trends.
Margaret Hardman,
Dirk H says: “Where is the “strong valid evidence” that supports any of the IPCC models? Do you just ASSUME they are valid? It seems so. You are strongly biassed. Show your evidence.”
Yes, show your evidence, Margaret.
Global warming stopped at least sixteen years ago, despite the continuing rise of [harmless, beneficial] CO2.
Question: what would it take for you to admit that your belief in manmade global warming is wrong? How many more years of no warming would it take? Give us a number.
Another weakness of stacking is that one clear effect is warmer winters. As is seen here:
http://climategrog.wordpress.com/?attachment_id=270
Looking at figure4 we see several peaks at around 6 months and a notable one at around 3 months. That is Santa Maria.
Most eruptions seem to be in March-June , St M was in October. This highlights a problem that the winter warming and summer cooling of different volcanoes will be averaging each other out , thus reducing the true volcanic signal found by the stacking method.
So it is a good first approximation but a closer look at individual eruptions would be more accurate.
“Greg, some of that downward trend prior to official dramatic eruption may be due to increased volcanic activity leading up to eruption. ”
Mt Agung happened at a time when there was some general low level activity immediately preceding it. That one is not the reason for the average downward trend but it is a good point.
There is another event that appears to affect temperature on a much shorter scale. I have been watching the daily UAH temperature data for the last few years and noted it seems to rise immediately after a strong CME which lasts anywhere from a few days to a couple of weeks. Note the recent rise after a string of CMEs in early May as an example. Also, the CMEs do not need to point at the Earth. Since CMEs occur far more often than strong volcanic eruptions the chances for finding a spurious result are much lower.
If my unscientific observations have any merit then one might expect to see a response similar to what Willis has seen with volcanoes only in the opposite direction and much faster. I don’t have the time nor the relevant expertise but thought I’d mention it in case anyone did and was interested.
“Looking at figure4 we see several peaks at around 6 months and a notable one at around 3 months. That is Santa Maria. ”
Sorry , I meant figure 2.
It would be interesting to do the stacking but keeping calendar months aligned. I think the summer/winter effects would stand out quite clearly. Boost Jan/Feb dip Sept/Oct
Ken Gregory says: May 26, 2013 at 5:59 am
“Nick, did you miss my comment of May 25, 2013 at 10:41 pm”
Well, I missed its significance. Thanks. I downloaded the file and it looks correct. The numbers I gave above are the same as your col W. The slight discrepancy came because I subtracted the eruption year value to match Fig 4 – you subtracted the year before, which is probably more consistent.
Your graphs indeed show a quite different behavior of the model average from the blue curve in Fig 4. It means most of the discussion in this thread is based on wrong figures.
Ken Gregory says:
Nick, did you miss my comment of May 25, 2013 at 10:41 pm
I change the file name to replace the blanks with _ so the link should work.
http://www.friendsofscience.org/assets/files/WillisE_Forcings_and_Models.xlsx
Ken all the volcano columns are derived from col G , except El Chichon, which is based on col E.
Is that intentional , what’s it about?
Greg Goodman says:
“The key misunderstanding here is that overshoot is proof of a non linear governor.”
ENSO is more like a highly amplified negative feedback that over-compensates, which is very handy for moderating land temperature extremes.
I think the key misunderstanding here though is that Willis’ stacked temperature rise at 36+ months after the eruptions is just the next El Nino’s and has nothing to do with what follows the eruptions:
http://wattsupwiththat.files.wordpress.com/2013/05/stacked-temperatures-five-major-volcanic-eruptions.jpg
“The slight discrepancy came because I subtracted the eruption year value to match Fig 4 – you subtracted the year before, which is probably more consistent. ”
If you are comparing once per year data with monthly time series you’d be better to use the middle of the year as the plotting date for the yearly data not the first of January.
“ENSO is more like a highly amplified negative feedback that over-compensates, ”
Nice assertion, does anyone else say that?
“I think the key misunderstanding here though is that Willis’ stacked temperature rise at 36+ months after the eruptions is just the next El Nino’s and has nothing to do with what follows the eruptions”
So you’re saying volcanoes don’t cause El Nino , but they just happen to follow. That they have common cause? Pure coincidence ? What’s you point exactly.
If you have something to tell us about our “misunderstanding” please say clearly what you mean and back it up. Don’t just make assertions.
BTW the papers you linked talking about El Nino-like variations in Nino3.4 is another way of saying cooler SST two years after , warmer SST 6 years after. Pretty close to Willis is saying isn’t it?
@Greg Goodman
No I’m saying there is a Nino response to volcanic cooling, but the rise 3+yrs later on the graph are subsequent Nino’s that are unrelated to to the volcanic response. The odd one out is El Chichon which had a multi-year La Nina soon after, so the warming at 36 months looked stronger when Willis took that one out.
Greg Goodman says:
May 26, 2013 at 12:45 pm
Ken all the volcano columns are derived from col G , except El Chichon, which is based on col E.
Is that intentional , what’s it about?
Greg, thanks for finding that error. All volcanoe columns should reference col G. It is now fixed:
http://www.friendsofscience.org/assets/files/WillisE_Forcings_and_Models.xlsx
[They were originally referenced to col E, which was mislabeled as temperature. I had changed the reference to col G, which is the modelled temperature, but I missed the El Chichon column. Sorry about that!]
Now the graph of six volcanoes is only a little different from the graph of five volcanoes (which excludes El Chichon) in the spreadsheet. The five volcanoes modeled temperatures drop in the year after the eruptions to -0.22 C (relative to the year before the eruptions) and recovers to -0.09 C in the 4th year after the eruptions. In contrast, Willis’ Figure 4 shows the modeled temperatures drop in the year after the eruptions to -0.30 C and recovers to -0.15 C in the 4th year after the eruptions.
Ok, so we’re getting nearer, that shapes right. Now what’s going on with the number of models? Are you plotting the same thing?
@Greg Goodman: It would be interesting to do the stacking but keeping calendar months aligned.
You could do that, but I wouldn’t believe the results either way.
We just don’t have that many volcanos to work with to instill an average 3 month time-positional error. Furthermore, working with calendar months makes little difference when we have Northern and Southern Hemispheres in play and most are in the Tropics anyway.
Arranged North to South
(Indicates other eruptions that could conflate the study)
N.Temperate-Arctic
Novarupta, USA AK, 1912 Lat= +58.27 Alaska Penn. June 6, 1912 VE 6
(note:largest eruption in 20th century)
(Colima, MX. Lat=+19.15 N.Tropic Jan 20, 1913 VE 5)
N. Tropics:
El Chichon, MX Lat=+17.36 (N.Tropic) Cen Am April 3, 1982 VE 5
(Mt. St Helens, USA Lat=+46.20 (N.Hem) May 18, 1880 (pre-Chichon) , VE 5)
Pinatubo, Phil Lat=+15.13 (N.Tropic) Asia Pac June 15, 1991 VE 6
(Cerro Hudson, Chile Lat=-45.90 (S.Hem) Aug 12, 1991 VE 5 )
(also pointed out by Dr. Stefan Weiss )
Santa Maria, Guat. , 1902 Lat=+14.76 (N.Tropic) Cen. Am. Oct 27, 1902 VE 6
S. Tropics
Krakatoa, Indo. 1883 Lat=-6.10 (S.Tropic) Indo-Indean Aug 27, 1883
(Okataina, NZ Lat=-38.12 (S.Hem) June 10, 1886 VE 5)
Mt. Agung, Indo Lat= -8.34 (S.Tropic) Indo-Indean peak VE 5 on March 17, 1963, but a year long.
Tambora, Indo Lat.=-8.25 (S.Tropic) Indo-Indean April 10, 1815 VE 7
(“Year without Summer” 1916 NE USA.)
Arranged by Local Season.
El Chichon – N.Tropic, Spring (preceded by Mt. St.Helens, 23 months Spring)
Novarupta – N.Hem-Late Spring (followed by Colima, 6 months)
Pinatubo – N.Tropic, Late Spring (followed by Cerro Hudson, 2 months, S.Hem)
Mt. Agung, – S.Tropic, Late Summer (alone)
Santa Maria – N.Tropic, Autumn (alone)
Krakatoa – S.Tropic, Late Winter (followed by Okataina 35 months, S.Hem.)
Tambora – S.Tropic, Early Autumn (alone)
Grouped by Geographic Area of influence:
N.Am, N.Pac – Novarupta
Cen.Am-E.Pacific – el Chichon, Santa Maria
Asia-W.Pac: Pinatubo
Indo-Indian: Krakatoa, Mt. Agung, Tambora
Greg Goodman says:
Now what’s going on with the number of models?
Well, the caption to Fig. 4 says “Blue line shows the average of the modeled annual temperatures from the 15 climate models in the Forster paper, as discussed here.”, but I think the 15 is an error. It is 19 models. There is one and only one record of the Forster modeled temperatures. It is from the previous post
http://wattsupwiththat.com/2013/05/21/model-climate-sensitivity-calculated-directly-from-model-results/
Willis digitized the graph from the Forster paper. The link at the bottom of the post gives the data. The caption to Fig. 3 says, “The blue line shows the average hindcast temperature from 19 models in the the Forster data.” This agrees with Table 1 of the Forster paper, and the digitized data, copied into my spreadsheet, matches the graph from the Forster paper.
Again I’ve split this to see north/south tropics and extra-topical zones
http://climategrog.wordpress.com/?attachment_id=277
Temporary cooling visible in both NH and SH extra-tropics . NH ends very slightly lower ; SH equally the other way. On average, both hemispheres are cooling before the event.
NO long term cooling .
http://climategrog.wordpress.com/?attachment_id=278
one really evident feature is the warmer winter in tropical SH ; cooling min at 2y warm bump at 6y.
Don’t know that any of that would get past a test of statistical significance. Looks very much too close to usual ups and downs.
If you took out the established circa 2.5 year bumps that seem a regular feature the cooling/warming features are minimal.
NO long term cooling .
The post 6y averaged “nino-like” bump is similar to the pre-6y one.
So the main feature seems to be that eruptions are synchronised to the “internal” variations. The same thing that I remarked in Willis’ figure 2.
Oh and did I mention, NO long term cooling .
Ian H says:
May 25, 2013 at 2:18 am
The next step then is to ask what CAN cause the climate to change if it is governed as you describe. Because as we all know climate can and does change. For example what could cause the LIA or the late 20th century warming if the system is indeed governed. A governed system is likely to be quite insensitive to changes in the input energy. To get it to change you would need something that “tweaks” the settings on the governor.
I asked myself the same question a couple of years back, and concluded that climate change results from factors that affect the phase changes of water; aerosols, including organic carbon (cloud condensation, and precipitation suppression), black carbon (snow/ice albedo changes), and perhaps GCRs. Ignoring Milankovitch Cycles.
Which led me to look for evidence of century scale changes in aerosols and BC to account for the MWP and LIA. I didn’t find any, but that doesn’t mean such changes didn’t occur.
Those bumps are worrying me. I synchronise the data on volcanic events spanning a full century, take the average SST anomaly and I get a series of regular bumps of about 2.4 years duration that stretch both before and after then event.
In fact a lot of what is generally attributed to volcanic cooling is just the synchronisation to this cycle.
Another observation, the larger peaks are about 11 years apart and the eruptions are in the middle. Solar minimum ??
Willis Eschenbach:
Excellent work!
Ian H says: The next step then is to ask what CAN cause the climate to change if it is governed as you describe.
Best not to over simplify. Willis has put a good case for a governor type response to variations to insolation of the tropics. Despite the individual storms being very fast, It is not instant on the regional scale. Here we are discussing changes over six years.
There is also the question of where does the heat go when it is evacuated from the tropics. I commented on that above as well. It get shipped to upper troposphere were some escapes and Hadley circulation takes the rest to higher latitudes. Eventually probably to the polar regions.
Don’t forget higher latitudes don’t have the governor.
Also a governor will leave a small offset if the forcing is maintained. How much depends on the strength of the internal feedbacks involved. A governor may be good at controlling deviations of a degree or two and bring the system back to within a few tenths.
If we can trust the data we have and trust the trustees of the data , tropical NH has show a few tenths of warming and it seems linked to Arctic melting season.
http://climategrog.wordpress.com/?attachment_id=276
However the key point of this post is that volcanic forcing is neutralised as far as the data shows. And without that someone will have to cut the CO2 factor down to size to restore the energy budget.
<i.Don’t forget higher latitudes don’t have the governor.
I think its likely they do. I don’t see how tropical thunderstorms could rapidly respond to a high latitude eruption like Novarupta in Alaska.
In addition, I think the role of humidity in tropical thunderstorm formation, and all cloud formation, is more important, than I believe Willis does.
I also think the mechanism operates in the temperate to arctic zones, at least in summer. Decreased temperatures > decreased clouds > increased solar insolation > increased SSTs and surface temperatures > increased evaporation > increased humidity, and after some lag temperatures and clouds return to their equilibrium level.
However the key point of this post is that volcanic forcing is neutralised as far as the data shows. And without that someone will have to cut the CO2 factor down to size to restore the energy budget.
Agreed. I remarked to Willis a while back that solid empirical evidence showing the aerosol forcings (both volcanic and anthropogenic) are too high will force the modelers to bring down the CO2 forcing.
Philip Bradley says:
<i.Don’t forget higher latitudes don’t have the governor.
I think its likely they do. I don’t see how tropical thunderstorms could rapidly respond to a high latitude eruption like Novarupta in Alaska.
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Tropical storms react quickly to tropical SST. There will be other feedbacks in different regions, probably not governors though.
Novarupta was VE6 and the max "cooling" of the temperature anomaly in the tropics was in the winter of the first year whereas most warm this period, hit min in second year. This pattern is shared by Krakatoa which was also very powerful. The recovery max was at start of third year synchronised with the other events.
One of the very strange things that comes out of this stacking, when calendar months are aligned rather than strict delay from eruption date, is the 2.4 year patter. You can only see hints of it in individual events but it becomes very clear when averaging.
http://climategrog.wordpress.com/?attachment_id=278
Could it be accidental? It's a surprisingly clear pattern.
"Agreed. I remarked to Willis a while back that solid empirical evidence showing the aerosol forcings (both volcanic and anthropogenic) are too high will force the modelers to bring down the CO2 forcing."
I have also been making the point repeatedly. Thanks to Willis for picking up the ball.
“Stephen Rasey says:
May 26, 2013 at 8:06 am
@Tenuc at 4:19 am
have a look at the ‘law’ of Maximum Entropy Production (MEP) and Spatiotemporal Chaos to get some insight into reasons why the balance gets restored.
MEP and Chaos are hardly first principles of physics. They are non-unique explainations of observed phenomina. Many chaotic systems do not show quick returns to a baseline. Indeed, the hallmark of chaotic systems is the existance of multiple local stability points. Chaos is an argument that better describes the climate models.”
Are you thinking in anomalies or absolutes?
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More general comment about this article & discussion:
It’s interesting watching people slowly clue in to what Ulric Lyons & Tomas Milanovic said long ago. An insight about human nature may be that sometimes people need to discover things firsthand for themselves in order to appreciate and that once they have done so they may not recognize (or acknowledge) equivalence with what others have said in the past. I suppose that in some sense wheel reinvention is like an insurance policy that saves civilization from losing knowledge in the longer term. But it’s also comical to see Ulric not even acknowledged — very informative about the dimension of human nature known as stubborn pride. FWIW, Ulric: I acknowledge that you were there years ago.
Thank you, Willis, once again, for a masterpiece of logic. I wonder of someone could clarify something for me: At one point the text says that, after an eruption, there should be an increase in the heat contained in the ocean. I’m not quite sure how the physics of that would work, since, presumably, the cause of the temperature drop is reduced insolation. It seems to me that, were the ocean moderating the temperature drop, one would see an increase in the heat being _released_ by the ocean, and therefore a _decrease_ in the heat contained in the ocean.
I would be grateful if someone could help me with my gap in understanding. Thanks!
PV: “FWIW, Ulric: I acknowledge that you were there years ago.”
Ulric Lyons is not a name recognise other than the occasional terse comments here and probably Talkshop. Where did he get to years ago, what have we missed?
I have reviewed my NH tropical stack to try to assess any cooling beyond the circa 2.7 y cycle:
http://climategrog.wordpress.com/?attachment_id=278
To assess the any cooling: the range before eruptions is 0 to -0.2 K , in the following period between 0 and -0.25 . This gives an average drop of 0.025 degrees in the immediate aftermath. It is not obvious whether this is part of a slow long term decline, an initial drop and recovery or a permanent offset.
PS In any case it is an order of magnitude smaller than the 0.25 to 0.3 deg C usually attributed to these events.
Regardless of the statistics, SO2 just doesn’t seem reflective when you work with it regularly under the lights, nor does H2S. H2SO4 does have that weird shimmery character as an aerosol shared with other strong acids, but really, is atmospheric concentration high enough to invoke this? Methinks we are talking of the ability to coalesce droplets or aerosol H2O.
Having found a remarkable pseudo-cyclic pattern in the monthly aligned stack: http://climategrog.wordpress.com/?attachment_id=278
it occurred to me that Willis’ degree.day idea (in fact the cumulative distribution function) would provide a means of flattening out the ripple to look for residual change. Here is the the CDF of hadCRUT4 for southern hemisphere:
http://climategrog.wordpress.com/?attachment_id=280
In all these plots I have averaged calendar months so as to keep the seasonal alignment.
Firstly this confirms my original observation that, on average, there is a general downward trend _before_ the eruptions which must be taken into account when looking for a volcanic cooling signal.
It can be seen that the tropical storm “governor” not only maintains temperature but actually compensates for the number of degree.days . An equal number of warm days make up for those lost to the eruption.
In the temperate latitudes there is a loss of cumulated “degree.day” but this does not mean a net loss of temperature (beyond the existing downward trend).
The CDF being parallel to fitted line corresponds to return to the same temperature. Since it is roughly parallel 6 years after the eruptions, this marks zero net cooling.
Both plots warm after 6 years but this ( the already reported Nino-like events) seems to be due to a curious synchronisity between the years of major events and the stronger climate pulses at about E-5 and E+6 .
The bottom line on all this is that there is not discernible global cooling as a result of major stratospheric eruptions, contrary to the established wisdom.
This false idea has been mainly caused by the lack of recognition of an underlying downward trend in temperatures that is usually already established when these events occur.
I loved the article because it built a simple picture in my mind. We live on a water planet. If anything heats the atmosphere water evaporates, clouds form and cool the earth while convection transports heat to high altitudes where it can escape into space. If anything cools the atmosphere, clouds don’t form and more sunlight gets through to heat the earth and oceans and eventually the atmosphere. That’s a super simple system to keep the earth and atmosphere temperatures within a small range. Volcanoes are a convenient experiment that cool the earth so we can see if the earth and atmosphere respond as expected. Apparently they do. Very compelling.
Unfortunately I doubt that such a simple explanation can move the interests vested in the notion that a twang to the system by humans in the form of CO2 will break the guitar string and it will whip us to death. Oh well, it convinces me. I like simple.
Nick Stokes: People might be interested in …
Thanks for the link.
At any given time, there are 500 active magma fields on land, some 650,000 active seamounts, several million smaller oceanic vents, and a 47,000 mile long Mid-oceanic ridge, which acts like the largest volcano imaginable in terms of volume of lava and gases produced.
Human actvities don’t even compare.
if that were not enough, the average for carbonate rock and carbonate-cemented rock dissolution is roughly one inch per year. They cover 10% to 15% of the crust. Assuming standard H2CO5 in rainwater chemistry, approximately 800 billion tons of CO2 are produced by this, but 12.7 trillion tons of CO2 are removed by this.