Guest Post by Willis Eschenbach
I’ve been ruminating on the continuing misunderstanding of my position that a governor is fundamentally different from simple feedback. People say things like “A governor is just a kind of feedback”. Well, yes, that’s true, and it is also true that a human being is “just a bag full of organic chemicals, minerals, and water“ … but if you want to analyze humans, that’s far from sufficient.
Similarly, a governor is a kind of feedback … but if you want to analyze it, you can’t assume it’s just simple feedback.
For starters, let me offer my definition of a governor. A “governor” is a control system that uses both positive and negative feedback to maintain some system variable near a “set point” value. A common example in our daily lives is the cruise control on your car. It increases or reduces fuel flow (positive and negative feedback) to maintain the vehicle speed near some pre-set value.
I want to illustrate why you can’t analyze a governed system the same way you analyze an ungoverned system. Suppose I have a car, and I start out from a standstill on level ground. As I gradually add more and more gas by slowly pushing down on the gas pedal, the vehicle speeds up. I record the speed and the instantaneous fuel flow, and I get a graph like Figure 1. As is the usual custom, I’ve graphed the independent variable (fuel use) on the horizontal X axis, and the dependent variable (speed) on the vertical Y axis.
Figure 1. An illustrative graph of automobile fuel use versus speed, with no cruise control. Yeah, yeah, I know the shape of the curve won’t be exactly like that … which is why this is an “illustrative example”. [UPDATE: an alert reader has pointed out that the speed is of course in miles per hour (MPH) and not miles per gallon (MPG) … I can’t be bothered to redo all the graphs, so please just make the appropriate mental substitution.)
Figure 1 shows that the vehicle speed is some kind of function of fuel use. It’s not a straight line because as you speed up, the air drag on the car slows it down. And the drag increases by something like the cube of the speed. So as we add more and more fuel, the effect of each added unit of fuel decreases. You can see that at sixty miles per hour, the car uses 2 gallons of gas per hour.
The takeaway point from this analysis is that in terms of causation, we can see that a change in fuel flow causes a change in speed.
Now, let’s get the car going sixty miles an hour on level ground, turn on the cruise control, and once again measure the speed and the gas. Then, suppose the car goes uphill. It will start to slow down. As soon as it does, the cruise control will react to the reduction in speed by increasing the gas flow to keep the speed near to 60 mph. And when the hill steepens, speed goes down a bit more, and in response the governor further increases the fuel use to keep the speed up.
Then we crest the hill and start down the other side. The car starts to increase speed, and when it gets going faster than 60 mph, in response the cruise control will reduce the fuel flow.
This leads to a very curious situation—vehicle speed goes up as the fuel use goes down, and speed goes down as the fuel use goes up. Figure 2 shows an illustrative graph of the situation .
Figure 2. An illustrative graph of fuel use versus speed, with a cruise control set for 60 MPH.
I’m sure you can see the problem. If we analyze this situation in the exact same way as we analyzed the situation without the governor, we come to the ludicrous conclusion that if we increase the fuel use, it will reduce the speed of the car.
So how can we understand this change? The key to analyzing this system is to understand that the governor (cruise control) reverses the causation in the system. Without the governor, as mentioned above, a change in fuel flow causes a change in speed.
On the other hand, with the cruise control engaged the exact opposite is true—a change in speed causes a change in fuel flow. And as a result of this reversal of causation, our previous analysis method is useless because it incorrectly assumes that a change in fuel flow causes a change in speed.
But wait, it gets worse. Suppose we start up the car from a standstill as in Figure 1, but then when we get up to 20 mph we set the cruise control for sixty mph. The car will continue to accelerate as in Figure 1, but only until the car gets up to sixty mph. When it gets there, it doesn’t speed up any more. Instead, it takes up the pattern shown in Figure 2. So the complete graph of the run looks like Figure 3:
Figure 3. An illustrative graph of fuel use versus speed, with a cruise control that is set to 60 MPH just after the car starts moving.
Here we see that in the blue part of the graph, the change in fuel use causes a change in speed … but once it gets up to the set point speed of 60 mph, the causation reverses, and now the red line shows that a change in speed causes a change in fuel use. Note that this reversal does not require any change in the governor settings. When the situation is far from the set point, the causation goes fuel –> speed. But once it reaches equilibrium, causation reverses such that speed –> fuel.
How does this relate to the climate? Well, the underlying climate paradigm is that the forcing controls the temperature, such that a change in forcing causes a change in temperature.
On the other hand, I’ve proposed that there is a natural governing system regulating the temperature of the climate, a major part of which works as follows.
In the tropics, when it is warm, clouds form earlier and reflect away the sun to cut down the solar forcing. And when the tropics are cool, the clouds form later or not at all, which greatly increases the solar forcing.
What that means is that a change in temperature causes a change in forcing.
And that is why I say that the current method of analyzing the climate is totally incorrect, because it assumes the causation is going the opposite direction from what is actually occurring.
In closing, I can do no better than to post up this marvelous cartoon by Josh from five years ago showing my “Thundercloud” governor at work …
Best wishes to all,
w.
As Usual: If you disagree with someone, please quote the exact words you object to so that everyone can know both who you are addressing and just what it is that you disagree with.
This disagreement is a trivial semantics squabble.
The “It’s all negative feedback” folks are insisting that the governor always acts counter (thus negatiove feedback) to the second derivative (or acceleration) of the motion to keep the system near a set point. Willis is using the term “positive feedback” for the application of fuel to increase the velocity (first derivative) in the positive direction of motion. Since the vehicle is slowing this application of fuel is counter “or negative” to the now negative acceleration of the motion but it is positive, or still in the same direction as the velocity, Hence Willis’ use of the term “positive” feedback.
Pendants are tedious.
.
No, pedants are necessary.
If we do not agree what terms mean, we cannot communicate effectively.
If I tell you its OK to drive through red lights and stop at green because I am using the term red, as you would use green, and vice versa, we have a problem, Houston.
Engineers have been here before, and mapped and defined this territory. It is not down to anyone else to come charging in and redefine the vocabulary of it according to personal taste.
Because the discipline and the vocabulary allow for concise and precise statements. ‘It’s all just negative feedback’ is one such.
Once you have appreciated that that is in fact the correct statement, according to current engineering terminology, you can then access the whole body of what is known about negative feedback systems to help describe and understand the phenomenon.
If all people were engineers , you would be 100% correct . Clearly , all people are not engineers . These people may insist that their terminology is correct and yours is not … so how do we best communicate with them ?
(A problem engineers face ….daily ?..whether or not they realize it …(8>))
Bob wrote:
You don’t do it by completely breaking the conventions used throughout the field. Or are you suggesting that we re-educate every engineer and rewrite every textbook on the subject? Perhaps we can do the same with medicine and finance.
The only way to deal with it is to educate the non-engineer on the proper use of the terminology.
A forcing implies a temperature setpoint. The earth works to maintain that setpoint. That’s a governor—a governor that employs feedback to approach the setpoint.
If the temperature (read speed) exceeds the forcing-dictated setpoint, net top-of-the atmosphere downward radiation (read fuel use) decreases to reduce it. (Not that radiation imbalance is a different animal from forcing.) If the temperature exceeds the forcing-dictated setpoint, net top-of-the atmosphere radiation decreases. “This leads to a very curious situation”: as the temperature goes up the net radiation goes down.
In other words, we say potato, Mr. Eschenbach says potahto. Distinction without a difference. Let’s move on.
Well another way of looking at what he is saying is simply this.
“Systems with negative feedback can contain their own causes for change.”
In other words the climate changes all by itself. No need for radiative forcing from excess CO2 or anything. Given enough non linear feedback and time delay inherent in it, the climate will wobble around unpredictably even if the sun shines constantly and the CO2 never budges a single ppm.
The other way of saying this is this.
‘Observed climate change is fully consistent with no external forcing at all‘
Think about how much more radical that statement sounds than the original…
Excellent point!……. very minor addition to your summary statment.
‘Observed climate change is fully consistent with no change in external forcing at all‘
It’s difficult to explain to non-engineers (or at least those without a solid college level mathematics background) and especially anybody who hasn’t formally studied control theory how excessive delay in the response of any simple negative feedback system will cause oscillation about the set point of the system.
Should have been “Note that radiation imbalance is a different animal from forcing.”
I’m not celebrating yet, but offer my congrats. The otherwise tainted Wikipedia offers insight ranging from plain language for the lay person, to in-depth complex math for those who prefer abstract symbols, into control system theory in their “PID Control” article. Beware, their terminology isn’t perfect either.
One simple comment is all that was needed to point out Willis’ slight error in terminology. Any ADULT could make note of the issue and move on. All the extremely small people piling on here strike me as Antonio Salieri wanna be’s to Willis’ Mozart.
Please people, lets get back to the point of the article.
Actually, it’s BECAUSE Mike, Leo and others were willing to go into in depth description and the workings of control systems (a thing I know little about) that I now understand how Willis’ cloud governor theory could be right even though his use of terminology was wrong. Now if Willis can use this to rewrite his theory with the correct terminology and a good understanding of control system, his idea will be able to spread quickly among those who work with them.
Thanks Dave, that was the only reply so far and very valid and why doesn’t any one see that ? I have followed Willis and his observations of the Tropical thunderstorm and cloud formation as a typical day happens for years no. Maybe to some it was not filled with graphs, journals and eons of data. To me it had the most important thing.
Logic!
Dang, should have read” Thanks Dave, that was the only reply so far I agree with”.
When I think of governors I think of limiting devices. When growing up in NY state, our school bus had a governor that limited the speed of the bus to 50 mph, in college at a factory, the centrifuges had governors on them. In these example, control would always be negative.
“What that means is that a change in temperature causes a change in forcing”
…
Your “model” is useless in explaining the advance and retreat of glaciers.
Someone wrote to me and asked me if I had written this on Anthony’s blog. A was astonished and had to answer “no.”
If that’s your authentic name, congratulations. If it isn’t, please pick another pseudonym. Thanks!
Brian G Valentine
Arlington, Virginia
US DOE & OAEE UMCP
Willis,
Keep up the good work.
Looks like you need to use smaller words and more verbosity to keep highly focused, but blinkered, folk on the reservation.
I view that your statements and meaning are clear.
……”for over speed, the governor applies a feedback negative, i.e. to slow down, the system,
……for under speed the governor applies a feedback positive, i.e. to speed up, the system”
“feedback positive to the speed” vs “positive feedback” in clear context?
On tropic climate, there is “a feedback that is negative to change”:
….when the temperature is higher than the set point, clouds form
….when the temperature is lower than the set point, few clouds form.
-> one is ” negative” to the temperature, and one is “positive” to the temperature.
Ignoring “negative to change” feedback in the “pursuit of money” is…..
Willis
Think you have missed the obvious. The control system (governor) didn’t changed, the feedback did. The hill is a negative feedback when the car is going up the hill (fighting gravity). The engine must overcome friction, wind resistance and gravity. But it becomes a positive feedback when the car tops the hill and starts down the other side (assisted by gravity). The engine + gravity must now over come only friction and wind resistance.
Look at your analysis again and see if that makes a difference.
Basic process control uses PID (Proportional, Intergral and Derivative), or some variation (P+I, P+D {rare} or P+I+D). More advanced algorithyms are used to address more extreme systems, such as highly exothermic processes. The typical cruise control on cars is P+I.
Systems dominated by positive feedbacks will eventually saturate at one extreme or the other. Systems dominated by negatived feedbacks will fluctuate within an envelope of acceptable conditions but rarely stay in a saturated state. Think about a bowl and a ball. If the bowl is upside down with the ball on top, once the ball goes over the edge, it will roll or fall to the table. If the bowl is right side up, the ball will roll around inside the bowl but will always eventually come back to the bottom. The ball will only leave the stable condition if acted upon an unusual outside forcing, such as a gamma ray burst that adds a great deal of energy to our contained climate system in a relatively short period of time.
Earth’s climate exhibits all the character traits of a system dominated by NEGATIVE feedbacks. The AGW crowd assume it is dominated by positive feedbacks. Although we have seen “Snowball Earth” twice in our geologic history, Earth’s climate has never displayed runaway warming even when CO2 concentrations reached 7,000 ppm. If it didn’t do it then, it sure as hell won’t do it at 400, 500 or even 1,000 ppm now.
AGW is about “Control” and “Fear”, not about science!
Love your posts.
Bill
Sorry I am with the “It’s all negative feedback” and Engineers. You start using the term positive feedback and as they said you are describing a system that will go into runaway either to destruction or some other stable state. That is a system that has a tipping point that the climate catastrophe true believers will tell you about. A cruise control on a car should ideally contain no tipping unless it’s a jeep that has been hacked.
A governor operates purely by negative feedback, however in any real-world system a problem we encounter is that there is a measurable time lag between applying a corrective change and the the correction appearing at the output. Thus if the corrective change is applied too rapidly or to too large an extent, the result will be an overshoot, because the correction cannot be withdrawn fast enough to keep the output from exceeding the desired level. In extreme cases the output may keep on overshooting alternately above and below the required value, in a process termed ‘hunting.’
The simple cure for hunting is to make the governor’s responsiveness slower than that of the process it controls. (in the tried and tested principles of cowboy electronics, slap a honkin’ great capacitor across the input sensor lead) The problem with this approach is that it also makes the governor rather slow to respond to errors.
The proper solution is to design ‘lead/lag’ compensation which tailors the governor’s response to not only the amount of error but also to the rate at which the error is being corrected. Thus, a large static error will result in a large correction, a small and reducing error will be given only a very small correction. A small error which is reducing too rapidly may even be given a reverse correction so as to prevent an overshoot.
An interesting area of engineering, and one in which achieving excellent results is not a trivial exercise.
What Ian said.
it’s called phase and gain margin. You design the loop to cross unity gain at something other than 180deg phase shift or vice versa.
I’m not an engineer, so I don’t know what the actual definition of positive or negative feedback comes from, but I’ve always loved operational amplifiers (OA) and they work by taking some of the output of a system and feeding it back to an input of the OA. This can be done either at a positive feedback terminal or a negative one, and I think that’s what Mike and others are talking about. But for everyday people they’re worried about whether the voltage inputted to the OA is positive or negative. So the actual source of confusion is not which input the signal is entered at (I agree it will be the negative feedback input), but whether the signal entered is a positive or negative value.
BTW, I knew “OA” didn’t look quite right. The usual abbreviation is “Op-amp”. And if I recall correctly, “negative feedback input” is usually called the inverting input.
An interesting thing about control loops is that you cannot troubleshoot a closed loop system. Also, as long as a system is within its control range, you cannot see the limits of that control range. What are the limits of the control range on the climate system? You cannot know, unless you can drive the system out of the control limits. IF you do that, the system will drive to one side (high or low) extremely rapidly.
Additionally, in a dynamic system, the feedback path will appear nonsensical. It’s kind of like watching a craps game without knowing any of the rules… the feedback signal really doesn’t appear to make sense (if you even know how to observe it), because the error amplifier behavior will be unknown (unless it was previously quantified). Thus, you can’t understand what you’re seeing in the feedback path, because you do not have the cognitive ability to understand the signal even if you know what the error amplifier is doing. And this is on a simple first or second order system. That’s why control loops are described mathematically.
This is a classic troubleshooting problem. As my mentor used to hammer me (repeatedly) you must open the loop to troubleshoot it. This allows you to inject static stimulus and observe deviation from the closed loop performance. It allows you to measure the behavior of the individual sections.
In some closed loop systems you can “ping” the system with a known stimulus and observe response behavior which will tell you certain things, but I would not expect most academicians to understand those methods. This is one reason it is alternately entertaining and frustrating to watch “climate scientists” attempting to rediscover control theory.
Despite this, control loops are fairly trivial… (eh, well, it is painfully difficult to learn the theory), but are so well understood that a competent engineer can design one without much difficulty. So if you’ve designed it, you know what it’s doing and what the limits are by design.
To me the term governor does not sound appropriate for a natural process. A governor implies that it is there by design. It also implies that the system goes to a set point but history shows there is no set point.
I think looking at this system as being stable, neutral or unstable makes more sense. History again seems to show that the system is quite stable but it does move to different equilibrium points over time. The idea that the system might be unstable and will be sent off into terrible conditions at some tipping point seems hardly possible. The question then might be how stable is the system.
There are ways to evaluate stability in physical systems and maybe this has been already done or tried with the climate.
Also a “governor” sound too political but the idea of natural stability seems far from a political concept. 🙂
Hi Erik,
Systems can have more than one stability point. Think of it like a rubber sheet with a couple of indentations in the sheet, the depth of which is related to the stability at that location (the deeper the indentation, the more stable at that point). So in a system like that, you can displace the current stability location given a large enough stimulus to push the thing over the hill into the next stability region. Then it will tend to stay near that until displaced again by a large enough input.
Gerry, very true but I would not expect that normal disturbances would push the climate into such a new stability point.
But even a relatively stable system, can have values move about the stability point depending on the disturbances and responses and even change the stability point as things are added and taken away from the system. Complicated for sure but not necessarily chaotic.
One of the few things I remember about Thermodynamic in university was that in general the final steady state conditions of a closed system were dependent on the net input/outputs to the system and were independent of any of the processes within the system. And I am not even sure I remember this correctly. 🙂
[snip -fake commenter using assumed name -mod]
Yes, the cruise control directly controls the throttle – for the purpose of controlling the fuel flow – for the ultimate purpose of controlling vehicle speed. To be consistent, you should not say the ECS computer controls the fuel flow either, as it actually only directly controls a certain voltage… If you allow yourself to say the ECS computer controls the fuel flow, you should allow Willis to say the cruise control controls the fuel flow.
SR
Confusing positive and negative feedback is as ridiculous as saying that when you drop something it will fall upwards because of gravity. Claiming that everything is right apart from the terminology does not help!
In my view the car analogy could be improved. Firstly, most people know about speedometers but to keep to a set point we do not need a speedometer. We just need to know whether we need more gas or less. So we need a meter with a centre zero.
Secondly, instead of using speed which has inbuilt notions of positive being faster and negative being slower it would be more educational to use steering. Our centre zero meter would indicate left or right. Maybe one would be positive in some sense but that would not be relevant.
The point would be to keep the meter at the zero (set) point, then, when you get blown off course to the right, the meter says “go left” so you steer left. The feedback itself is agnostic, it has no concept of positive or negative. The point is that you need to restore the centre zero meter back to zero – negating the change hence negative feedback.
OK, this is where this whole thread starts to make sense to me. Everything is negative feedback if it drifts from the setpoint. So there really is no such thing as positive feedback unless the goal of the setpoint is to “change the current state.”
Is this right give what you’ve just said?
And if it’s right then from a climate modeling standpoint there can be no positive or negative feedback, since the climate system has no given setpoint. All you can have is various processes that change at changing rates. So maybe it’s the use of the term “feedback” that is getting a lot of people hung up. Further, the notion of “regulation” doesn’t make a lot of sense to me either.
@MftMW: Following my steering example, imagine the wiring to the centre zero meter to be swapped over. So, if you were blown off course to the right the meter would say turn right. So rather than correcting the change you would be compounding it.
This is why positive feedback is “not sustainable” to coin a phrase. It is why people argue that whatever positive feedbacks there are in the earth system they have probably already been tripped sometime in the last 4.5 billion years.
explain night
When the sun goes around to the other side of the earth.
:slow clap:
To jump on the pedantic wagon 🙂 more technically when the observer side of the earth is turned away from the sun.
Steven Mosher August 2, 2015 at 7:55 am
Explain your comment.
w.
The problem with the ‘Governor’ affect is that it only applies to a portion of the system. The system is more like a bunch of cars going down the roads. Some of the cars are idling at stop lights, some are coasting to a stop, some are accelerating, most are going at a steady speed or stopped altogether.
If the supply of gasoline goes up, what happens to the average speed on the highways? That is similar to what happens if the supply of CO2 goes up, what happens to the average temperature.
OK maybe the critics would be happier if the article contained “…creates the illusion of…”
Then the graphs would be interesting without offending the engineers.
Andrew, the problem with engineers is that we are held accountable for our designs. Thus, we cannot just publish crap claiming it represents truth. This leads to a certain discipline of thinking and intolerance of sloppiness or (willful error, particularly politically driven willful error). By the way, none is harder on an engineer than his fellow engineers (and we all make mistakes btw). It’s still a field where respect is earned.
“Thus, we cannot just publish crap claiming it represents truth.”
Was not a swipe at Willis. I was thinking of climate scientists. Willis makes a real effort to understand things and publish thoughtful articles.
Willis is also usually willing to rethink something if an error is explained in a way that he can Grok, which I expect is why he’s been so quiet in this thread. Maybe reading up on control systems and PID like I’ve just been doing. Always fun to learn a new way of looking at the world. ^¿^
schitzree August 2, 2015 at 10:38 am Edit
Dear heavens, why are peoples’ speculations on my inner mental state and my actions often so far from reality? schitzree, I was “quiet in this thread” because I wrote it on six hours sleep in two days, and then I went to bed. And strange as it may seem, when I’m sleeping I’m usually “quiet” on all threads.
When I got up (late of course) I read the thread, saw my error, and I acknowledged it and corrected it immediately. So your unpleasant suppositions about me are all you, nothing to do with me. Which should lead you to reflect on whether you assuming the worst interpretation of my actions is something you might want to re-examine …
w.
A governor is a mechanism, circuit, or algorithm that uses feedback to maintain a certain output.
I think some further confusion exists regarding what these regulators do. For example, some regulators sense rate of change and respond. Others, notably older marine autopilots, sense a compass point and try to hold that. Rate systems can be used in marine autopilots but they also need a fixed reference (compass, magnetic or gyro) because there’s no point in reducing rate of change of heading through rudder angle if the heading walks off over time.
The automobile speed controller is necessarily imperfect in holding speed and that is because the error between actual speed and intended speed can never be reduced to zero. Zero error equates to no input change of throttle. So when going up a hill a car’s speed is necessarily less than desired because if it were not there would be no throttle input to compensate for the hill and the car would slow. In fact in vacuum powered throttle position actuators this happens in worn engines. The actuator opens the throttle, the manifold vacuum drops, the actuator can no no longer respond linearly, and the car slows to the point the transmission will downshift in a sudden lurch that both increases the manifold vacuum and causes the throttle position to go to the floorboard.
Humans get around this by intelligently applying appropriate throttle for the conditions, and people can anticipate because of complex inputs what will be needed for throttle under varying conditions (down hill, sharp corner). Humans also have access to braking which is not available to speed controllers.
Faulty nomenclature, otherwise all good…
Thanks, gymnosperm. While I understand why my error in nomenclature has people concerned, some folks like yourself are able to look past that.
w.
Willis,
A number of others have already made these points verbally, I’ll put them in the form of equations. Consider a simple energy balance model of the atmosphere (yes, this is oversimplified, I use it to illustrate the principle). We have
dH/dt = R
where H is the enthalpy of the system measured relative to some reference state and R is radiative imbalance. H can be written as a product of a suitably averaged heat capacity, C, and a suitably averaged temperature, T, measured relative to the same reference state as H. Since C is constant, our equation becomes
C*dT/dt = R.
Let’s suppose that the reason that R differs from zero is due to some exogenous change, like a change in the solar constant. We call that exogenous change the forcing, F. If the change happens instantaneously at time t=0, we have
C*dT/dt = F at t=0
But T now starts to change and that causes a change in the radiative balance. For small enough changes in T, we can assume a linear response. Then the change in R due to the change in T can be written as
delta_R = -lambda*T
where lambda is a constant and the minus sign is included to indicate that an increase in T causes a reduction in net incoming radiation (most directly via an increase in outgoing radiation); i.e., a negative feedback. Including this in our equation, we now have
C*dT/dt = F – lambda*T.
This is exactly analogous to your example, with T instead of speed and R instead of fuel use. Stepping on the gas (increasing F) increases T and R. But increasing T reduces R. Exactly the same reversal of sign as in your example. That is a general property of a negative feedback control system.
You wrote: “What that means is that a change in temperature causes a change in forcing”.
A change T causes a change in R. You could call that “forcing” if you like, but in that case you have to be careful to distinguish between the exogenous forcing, F, and the response forcing, lambda*T. You have not done so.
“And that is why I say that the current method of analyzing the climate is totally incorrect, because it assumes the causation is going the opposite direction from what is actually occurring.”
No, you are totally incorrect since you have used forcing to mean two different things, without realizing it.
I suppose someone will respond to this by saying “but climate models have positive feedback”. I’ll explain that misunderstanding when the time come.
Mike M. (period) August 2, 2015 at 8:37 am
Thanks for the math, Mike. I am in total agreement with you except for the part above, where I’m not seeing the difference.
Exogenous forcing is composed of the solar input minus the cloud reflections.
Response forcing is is composed of the solar input minus the cloud reflection.
I’m not clear about the difference you are pointing to. Not saying you are wrong, just saying I don’t understand the difference you are pointing out between the two, since both seem to me to be the same phenomena.
Regards,
w.
Willis,
“Response forcing is is composed of the solar input minus the cloud reflection.”
The response forcing depends on T, so it certainly does not include the solar input. It could include cloud reflection if there is a T dependent cloud cover. But it will mainly be a change in IR emission.
Thanks for the clarification, Mike. You say:
I have demonstrated through several independent datasets that there is indeed T dependent cloud cover, one which is strong enough to drive the temperature down in the face of increasing TOA solar input.
Since the change in incoming solar due to T dependent cloud cover is typically on the order of hundreds of watts, while the change in IR emission is typically on the order of watts, I’m not sure why you say the response is “mainly” a change in IR emissions. What am I missing?
w.
Willis,
“Since the change in incoming solar due to T dependent cloud cover is typically on the order of hundreds of watts”
No way is that possible, at least if you mean the usual W/m^2. Average reflected solar from clouds is only about 45 to 50 W/m^2, variations due to global T change are not more than a fraction of that. In fact, there is no real evidence that the change is different from zero. Instantaneous, local variations in incoming solar might be very large, but you can not compare that to numbers that are averaged globally and annually.
“I’m not sure why you say the response is “mainly” a change in IR emissions. What am I missing?”
Anthropogenic forcing, F, is about 2.3 W/m^2 (for brevity, I am not going to bother with error bars) and the imbalance, R is about 0.5 W/m^2, so lambda*T is around 1.8 W/m^2. The “Planck response (Stephan-Boltzmann)” is about (0.85 K)*(3.3 W/m^2/K) = 2.8 W/m^2, so the other response (water vapor, lapse rate, albedo, cloud “feedbacks”) contribute combined about -1.0 W/m^2 (net positive). So the direct IR response seem to dominate.
Note: There are two ways that people use the term “feedback”. One includes the Planck response, in which case the feedbacks are net negative. The other refers only to the non-Planck responses, which are net positive. The first is the one that is consistent with the terminology being used here.
Mike M. (period) August 2, 2015 at 12:38 pm
Thanks, Mike, I think we may be talking about different things. I’m talking about the strength of the governor, which operates on a daily basis, not on an annual average basis. Here’s daily data from the TAO buoys:
As you can see, cloud variations easily can cut 100-200 W/m2 out of the incoming solar.
Regards,
w.
Willis I am glad to see you have responded to my many post on this subject to a varied degree with this article.
I am interested in solving the climate puzzle as you must be. This is why as I have suggested before I think it would be of value to have a subject about what possibilities or combination of factors can come about in such a way to over come the governor on the climate to a point which is strong enough to take the earth from an Inter- glacial state to a glacial state and vice versa.
Willis you must be thinking about this and I think it is a topic that would be very is worth while.
Salvatore Del Prete August 2, 2015 at 8:37 am
Since I’ve never seen a single post from you on this subject, your idea that I am “responding to” your posts is just your self-importance speaking …
w.
Is this really an issue?
Negative feedback attenuates deviations. Positive feedback amplifies deviations.
BTW, I posted this before, but here is some fun video feedback. I used to love playing with it.
We know the climate has a regulator of sorts but what we do not know are the influences which can overcome this regulator enough which allows the climate of the earth to vary enough to bring it into different climatic regimes although the extreme boundaries warm or cold do have a limit.
Why ? That is the question and it is elusive. Very elusive.