The height of the ionosphere/space transition is controlled in part by the amount of extreme ultraviolet energy emitted by the Sun and a somewhat contracted ionosphere could have been expected because C/NOFS was launched during a minimum in the 11-year cycle of solar activity. However, the size of the actual contraction caught investigators by surprise. (Credit: NASA/Goddard Space Flight Center)
ScienceDaily (Dec. 16, 2008) — Observations made by NASA instruments onboard an Air Force satellite have shown that the boundary between the Earth’s upper atmosphere and space has moved to extraordinarily low altitudes. These observations were made by the Coupled Ion Neutral Dynamics Investigation (CINDI) instrument suite, which was launched aboard the U.S. Air Force’s Communication/Navigation Outage Forecast System (C/NOFS) satellite on April 16, 2008.
The CINDI suite, which was built under the direction Principal Investigator Rod Heelis of the University of Texas at Dallas, includes both ion and neutral sensors and makes measurements of the variations in neutral and ion densities and drifts.
CINDI and C/NOFS were designed to study disturbances in Earth’s ionosphere that can result in a disruption of navigation and communication signals. The ionosphere is a gaseous envelope of electrically charged particles that surrounds our planet and it is important because Radar, radio waves, and global positioning system signals can be disrupted by ionospheric disturbances.
CINDI’s first discovery was, however, that the ionosphere was not where it had been expected to be. During the first months of CINDI operations the transition between the ionosphere and space was found to be at about 260 miles (420 km) altitude during the nighttime, barely rising above 500 miles (800 km) during the day. These altitudes were extraordinarily low compared with the more typical values of 400 miles (640 km) during the nighttime and 600 miles (960 km) during the day.
(h/t to Dan Lee)
From comments made by others I should define what I mean by ‘weather patterns’.
I do not mean simple local or regional variability as some have assumed.
Weather to me means the interplay of high and low pressure systems. Thus a shift in the average positions of those synoptic systems around the globe are as much ‘weather’ as the local or regional consequences of those shifts.
Any degree of persistence following a shift in the average positions becomes a shift in climate for the areas affected.
Thus a change in the Earth’s radiative energy balance dictates the size, position and persistence of those synoptic systems.
If the atmosphere is losing energy the jet streams move equatorward dragging the temperate zone lows and highs with them.
If the atmosphere is gaining energy the jet streams move poleward.
Either way the shift in global energy balance precedes and drives the changes which over time then affect the average atmospheric temperature.
“” Roger Carr (05:13:50) :
George E. Smith (17:58:19) “I apologise for forgetting that Kosciusco hill sometimes gets snow.”
And well you may apolgise, Sir! Kosciusco is a hillock. It is somewhat taller than I am, and even I have snow up top… Damnit.
(p.s. I also ripped the thermostat out of my ‘48 Holden to good effect; after it had done 125,000 miles.) “”
No offense intended Sir Roger; we of the shaky isles have to yank your chain occasionally. I have often wondered (OBSCON) if the fact that the land of Oz was such a low down place, has something to do with your lousy rainfall. There’s plenty of moisture coming off the ocean, but it just buzzes right across the whol dang place without hitting anything important.
Maybe you need to build some synthetic mountains out there in the ouback to encourage the clouds to climb to precipitation height.
George E. Smith (09:49:21) :
Dave, if the cold water is so effective at cooling the engine; then why does the engine heat up with the thermostat closed, when all that is in there when you start it is cold water ?
Simply because you transfer the heat generated by the engine is transferred to the water. A continuous supply of cold water would cool very effectively.
I will not even attempt to dispute that heat exchangers work more efficaciously with a higher temperature differential, because that is obvious.
That the IC engine works more efficiently at higher temperatures is indisputable also, which is why I maintain that the thermostat remains in effect until the beast has reached operating temperature.
Ideally we would operate IC engines at an even higher temperature but a cheap and plentiful coolant is not available to allow that.
DaveE.
“” Chris V (21:29:20) :
George E. Smith (17:58:19) said:
The REAL sun illuminates the spot at 1368 W/m^2; four times what NOAA claims, and the atmosphere reduces that down to 672 W/m^2 at the ground also 4 times what NOAA claims.
The number you cite for the REAL sun illumination (1368 W/m^2) is what hits the equator, at noon. It decreases towards the poles (because of the lower relative angle of the suns rays) and is zero on the night side of the earth. The total illumination hitting the earth is 1368 multiplied by the surface area of a circle with the radius of the earth.
The number NOAA gives is that total illumination, divided by the the entire surface area of the earth.
The surface area of a sphere is 4 pi r^2. The area of a circle is pi r^2. That is why the “real” numbers you cite are 4 times the NOAA numbers.
“”
I guess I just totally wasted my time even raising the issue.
So if you know what the real number is, perhaps you also know why NOAA doesn’t use it.
What good is a climate model if it isn’t a model of anything real ?
George E Smith, quoting Roger Carr says:
Yeah, I had to rip the thermostat out of my ’67 Holden just after Christmas ’79 on the way back to Canberra from Brisbane. Never really needed it after that.
“” Jeff Alberts (19:14:00) :
George E Smith wrote:
To me the question of local climate is somewhat irrelevent; the temperature will be somewhere between -90C and +60 C, measured on the ground, no matter where you go on earth (surface), and somehow humans have adapted to deal with that whole range
Actually we haven’t adapted. We change our surroundings to suit us instead of adapting to our surroundings. We put on a coat instead of growing one. We turn on the AC instead of evolving a better method of keeping cool. “”
Well each of us is different; no matter how much effort is expended trying to make us all the same. So you can adapt in whatever way you want; others will choose to do other things.
Just consider the absurdity of trying to “Adapt” to a change of just a half deg F over the last century; which has the whole planet in an uproar. A century ago we did everything so differently from now, who knows how uncomfortable we were with our lot.
As for me; my plan A for adaptation to the global warming of 0.5F is to do exactly nothing; it will be all gone before I was able to detect any improvement in my lot anyway.
George E. Smith (11:26:19) wrote:
So if you know what the real number is, perhaps you also know why NOAA doesn’t use it.
What good is a climate model if it isn’t a model of anything real ?
Maybe I wasn’t clear enough- both sets of numbers are correct; they are just in a slightly different form (think of it as something like the difference between pounds per square inch and pounds per square foot).
Most climate scientists use the NOAA “versions” because they are easier to use when calculating things like global forcings. You could use the 1368 number to calculate the forcings also; you’d just have to do an extra calculation or two.
I guess I just totally wasted my time even raising the issue.
Not at all- you just made a very simple and fundamental mistake. I am sure that lots and lots of meteorology undergrads have made the same mistake.
Of course, most of those meteorology student aren’t proposing their own “theory of climate”, either. Maybe you need to get a slightly better handle on the basics before you overturn the existing paradigm.
All the signs are here. Hint – I am not referring to any of Algore’s scenarios.
“” Chris V. (14:04:34) :
“Maybe I wasn’t clear enough- both sets of numbers are correct; they are just in a slightly different form (think of it as something like the difference between pounds per square inch and pounds per square foot).”
Well they are a little more different than that. One set of numbers is actually observable on a real planet; namely ours; the other set is fictional and not observable anywhere of interest to humans.
“Most climate scientists use the NOAA “versions” because they are easier to use when calculating things like global forcings. You could use the 1368 number to calculate the forcings also; you’d just have to do an extra calculation or two.”
Well I have a pretty good idea what some climate scientists do, and none of those that I know use a model that has 168 W/m^2 striking the south pole continuously even in the dead of winter midnight. while the same thing is striking the equatorial noonday tropics.
On the other hand Physicists use real units; not fictions like “forcings” and the other trappings of “meteorological undergraduates”. That way, they have a finite chance of understanding what really happens on a real planet.
“Not at all- you just made a very simple and fundamental mistake. I am sure that lots and lots of meteorology undergrads have made the same mistake. ”
Yes I certainly did; merely in assuming that “climate scientists “would understand ordinary high school Physics
“Of course, most of those meteorology student aren’t proposing their own “theory of climate”, either. Maybe you need to get a slightly better handle on the basics before you overturn the existing paradigm.”
Well you’re very charitable; actually I’m not proposing any theory of climate; because I don’t really have much interest in climate, since we can do nothing about it.
And it is my quite sound grasp of “the basics” that convinces me that the existing “paradigm” of “climate theory” is a shameful caricature of science.
When your “existing paradigm” is capable of explaining the climate history we already know about; say for example the little ice age, and the mediaeval warming period; after all your models that can predict the future 100 years ahead, ought to be able to replicate the past which presumably was used to create them; then maybe I’ll start paying attention.
In the meantime; if the “climate science” field learned some very simple fundamentals themselves; like the general theory of sampled data systems; they might actually start measuring things that are meaningful, instead of palming off total garbage data, and equally garbage models as capable of predicting even the very next point to appear on their plots; with less than a 3:1 fudge factor.
We now have over ten years of demonstrated failure of the “existing paradigm” to meet its own chicken little scenarios.
By the way; why would “meteorolgy undergraduates” be studying climate?
George E. Smith: That’s a lot of words to attempt to cover up the fact that you are attempting to judge a field of science but have some extremely basic misunderstandings of the field (as Chris V. has illustrated). I think I will trust the judgement of the scientists in the field themselves…and reputable scientific bodies such as the National Academy of Sciences (as well as my own judgement as a physicist).
Fortunately, since we will soon have a President who seems to actually believe in using the best science available rather than distorting science to fit his ideology (as we had to contend with for the last 8 years), that will also hopefully the prevailing view in guiding our public policy.
George E. Smith (11:19:53) “…land of Oz was such a low down place, has something to do with your lousy rainfall. There’s plenty of moisture coming off the ocean, but it just buzzes right across the whol dang place without hitting anything important.”
Check the rainfall again, George. We are drowning in it right now. This has always been a land of droughts and flooding rains and is right on schedule.
Hey Roger,
I was in Melbourne Christmas of 2006, when you were having terrible droughts, and bush fires. My relatives were getting into the water tank thing to try and save more water for their needs. The day we flew out to Auckland again, the drought broke and they got rain to try out their new storage tanks. Glad you’re getting some relief; the smell of that bush fire smoke was pretty pungent.
George E. Smith,
Just wanted you to know how much your explanations of basic science are appreciated. Please keep it coming. You know you are hitting the mark when you have a physicist sputtering. I wonder why basics have been forgotten in the ivory towers academe?
Mike Bryant
Chris V. (14:04:34) :
and Joel Shore (17:56:40) :
As another physicist I agree with the exposition of George E. Smith (16:34:09) :.
What he was trying to explain is that there is no meaning in making a ball of the earth and equitably distributing the incoming sun energy because this model has no correspondence with the way the earth radiates away the heat.
The heat is lost much faster ( I think he says 12 times faster) from the tropics than from the north . A model that depends on isotropic input and output cannot represent the real earth conditions. There cannot be a one to one correspondence with real earth because of the different functional forms needed all over the globe.
Integrations are necessary which are not being done.
“” Chris V. (14:04:34) :
Joel Shore (17:56:40) : “”
Well with almost 140 posts so far, by all and sundry on this thread, the insightful contributions by two experts such as yourselves are greatly appreciated.
We amateurs are totally dependent on the helpful contributions you brought to this discussion.
From my perspective, it is gratifying to see remarks from folks like Mike Bryant and Anna V. above.
I don’t do this for a living; my employer is paying me to design stuff for them; they have only one test, and that is my stuff has to work or I get fired. While my computer is thinking for me, I’m able to pop into places like this and try to be helpful to anyone like Mike, and helping just one person to understand some things that are esoteric, yet within the grasp of any sensible person, makes it very worthwhile to me.
To know there are fellow Physicists like Anna out there to straighten me out when I goof up, is also much appreciated, since my academic days are half a century in the past, and I’ve probably forgotten more than I have remembered.
Well I probably could go to Google and bone up on some of this stuff, but then anybody else can already do that for themselves, so they don’t need me.
So I like to stay in the desert island mode; if I can’t figure it out with a stick on a sandy beach, with what is in my head, I’d rather tell people to go to the textbooks themselves.
Apart from that, I come here to learn myself; if I wasn’t learning from others here, I wouldn’t be here.
As for the numbers of words; is it better to drop a one liner with disciplinary jargon, only to draw blank stares, and more questions to be answered, or is better to try and be more complete, even at the risk of boring those fully schooled in the subject.
Well the skilled can always change the station, but what of the others who may not even find guidance as to where to look for answers.
My guiding principle, is that ignorance is NOT a disease; we are all born with it. But stupidity has to be taught, and there are plenty of people willing and able to teach it.
For me, there are no stupid questions; except those that are never asked. My office door is always open; and if I want to learn from others I simply bust into THEIR offices.
So Chris and Joel; if you are quite satisfied with the state of your fields of science, then you don’t need this place; you’d probably be more comfortable among your peers.
Steady, anna (anna v | 23:50:26), that sounds most unsettling…
anna v and George:
The NOAA numbers come from a simple diagram showing the earths energy budget- incoming sunlight, radiated longwave, reflected sunlight, etc. Those numbers are perfectly appropriate when looking at the global energy budget and the NET climate forcings.
The computer models do not assume an equal solar forcing everywhere on the earth; the models calculate the solar forcing for individual latitude bands.
Arhennius did his calculations that way over a hundred years ago.
Well I’m not going to belabor the point, and waste a bunch more of Anthony’s space.
The NOAA budget chart gives 390 W/m^2 for the surface radiation; which corresponds very closely to the blackbody radiation rate for 15 deg C (59 F) which has been the typically cited “mean global surface temperature” at least in the public media for quite afew recent years, although it may be slightly lower these days. I’m not unhappy with taking BB rates as applying to the real world, since some 73% of the real world surface is ocean and oceans do radiate somewhat like ablack body; probably with an emissivity in the 97-98% range (based on Fresnel reflection losses)
The hottest air temperatures correspond to 1.75-1.8 times that rate, and probably the hottest surfaces reach 2.0 times that or more.
The lowest temperatures go below -120F, and at least anecdotal reports from Vostock go to -140 F (-90C). For those typical lows the radiation rate drops by about 6 times from the “Global average”, giving a typical range of about 10:1, and as much as 12:1 for the extremes.
If the radiation rate (radiant emittance) were linear with temperature, then using an average temperature, with an average radiation rate would still yield a correct total radiation number.
But the real system isn’t linear, and it is reasonable to expect it to follow something close to a fourth power law.
Anytime you have a cyclic function raised to some power greater than 1, the integral of that is always greater than what you get by simply integrating the average, and for a fourth power function it becomes significantly greater.
So a radiation total based on an average global temperature must underestimate the total radiant cooling of the earth.
Where I live the climate follows a pattern that it has followed for thousands or millions of years.
The solar blow torch goes around my location in a 24 hour cycle, and has always done so, so that the insolation is only positive for a portion of that 24 hour cycle, typically around a third, but that varies from place to place on earth, but everywhere outside the Arctic, and Antarctic circles sees that 24 hour cyclic insolation climate behavior. On top of that, the earth moves in its elliptical orbit, so the amount of insolation also goes through an annual cycle of about 365 days.
If you don’t integrate the actual cyclic variations in that clearly observable climate behavior not only over the 24 hour day but also over the 365 day year then you don’t get the correct total radiation for any point on the planet.
That also doesn’t take into account that on average about 50% of the total globe surface is covered by clouds, and those clouds typically come and go on time cycles that can be just a few minutes to hours or days, and if you only measure the minimum and the maximum temperature at any measuring location, for any day, then you get no information about the higher frequency cloud related changes in the solar insolation at surface level.
If you ignore the cloud variations (I’m told that the GCMs do ignore clouds), and if you measure the temperature twice a day at regular intervals (midday/midnight or somesuch), your best chance of getting a correct daily average temperature would be if the temperature curve were a pure sinusoidal function. Theoretically, you can recover the average temperature (for the day) in that case, but you cannot recover the cyclic variation during the day, because you are employing “critical sampling”.
Well unfortunately the daily temperature cycle is not sinusoidal, even in the cloudless case, because the heating and cooling rates don’t match, so the temperature signal contains frequency components at least twice the daily rate, and in that case, you are undersampling and it is theoretically impossible to recover even the average value of the temperature for the day, even with no clouds. If you can’t get even the correct average temperature for a single day, you certainly can’t get it for a whole year, and just throwing in the random cloud variations means you have no idea what the mean temperature or total insolation is for even a single day, at any point on the planet.
Twice aday temperature sampling is not adequate for determining the average temperature.
That problem pales into significance when you start looking at the spatial sampling.
I read somewhere that back around 1900 there were a total of 12 reporting weather stations in the arctic (north of +60 degrees). That number grew to the mid 80s at its peak, but then declined to somewhere in the 70s; and I’m guessing that occurred around the collapse of the soviet empire.
I have no idea how many reporting stations there are south of -60, but I doubt that it is much different.
Over the oceans which after all are 70% or so of the total surface, measurements are often reported from ships, and historically, such as back when Arrhenius was doing hsi thing 100 years ago, they threw a bucket over the side to gather water from some unknown depth in some unknown location. Since 2001, we have known that ocean water temperatures do not correlate with ocean air temperatures, and why would we expect them to since air over Hawaii today, may be over America in a few days. also the ocean currents meander, so even in the same GPS co-ordinates, you cannot depend on being in the same water.
So prior to about 1980 when those ocean buoy studies were begun, we don’t have any reliable oceanic lower tropospheric temperatures, for 70% of the globe; even whatever measurements Arrhenius was doing.
So maybe the climate community are satisfied with that situation; but there isn’t any mathematical support for the way they sample gl”global temperatures”.
And even if they could get the correct global average value, it still tells us nothing about the total radiative cooling or total global insolation.
That’s the only global energy problem that i’m interested in; I’ll leave it to others to worry about whether the Riviera will be comfortable next year.
As for the GHG “forcings” (IPCC swear word), I would be pleasantly surprised to find out that any of the GCMs consider local temperatures, and Wien Displacement of the IR spectrum in computing the local CO2 absorption of surface emitted IR radiation. In the polar regions with lower temperatures, the IR emission falls closer to the CO2 absorption band, but the lower atmospheric temperatures reduce the Doppler broadening of that band.
In the hottest tropic areas, the IR spectrum peak moves further away form the CO2 band, but the Doppler width is increased. I’m sure I could find all that accounted for in the Computer models of climate.
Of course it suits the IPCC to maintain that 3:1 fudge factor in all of their utterances, because they can then ask; what if this worst case was the real one ?
If their error margins were reduced, they might find their predictions were no longer scary enough to suit their political purposes.
And I’m outa here.
George-
I don’t know where you’ve gotten your ideas about climate modeling, but they are very wrong.
Here’s a great link about how climate models work:
http://www.climateprediction.net/science/cl-intro.php
FYI-
Climate models don’t treat the earth as a black body (as you seem to think?).
They DO include the effects of clouds.
They don’t plug in some global solar forcing from NOAAs energy budget; they calculate it at different latitudes.
They use short time steps (1/2 hour, for the particular model in my link), so they take into account daily variations.
And any errors there might be in the global temperature set are not really important, as far as the models are concerned. They are only used to set up the initial starting conditions- after that, the model determines it own temperature, based on the physics. After running the model for some number of model years, the initial temps that were input don’t even matter any more.
~snip~
George E. Smith says:
We are similar in that regard, as I also do not do this stuff for a living. Like you, I do computational work in a different area for a living and read (and comment) about climate science in my free time.
I do appreciate many aspects of your philosophy. I too like to figure things out for myself. However, I think that when one does that, it is important to do it with lots of humility and the understanding that if you don’t understand something that the experts in the field are saying or doing, it doesn’t necessarily mean they are wrong…It more likely is a lack of understanding on your side.
In fact, a while back, I ran into the exact same factor of four issue regarding the solar constant that you ran into above…i.e., I was looking at the variations in the solar constant over the solar cycle and not understanding why they weren’t considered more significant in comparison to other forcings, until I learned that one had to divide by a factor of four to account for the difference between the surface area of the earth and the pi*r^2 projected area as “seen from the sun” (and there is also an additional factor of 0.7 because of the earth’s albedo). However, it seems to me that when you run into something you don’t understand, you seem to assume the worst of the scientists…i.e. that they are doing it wrong. So, you think they are using the wrong forcing…or that they applying the forcing equally over the whole earth in the climate models, which as Chris V. pointed out is not the case.
Joel Shore and Chris V
I have looked a bit into the mechanics of the GCM and the assumptions and equations that enter into them. I will have a look at your link, too.
I have previously stated my criticism of these models on posts here. These models started as weather prediction models. We all know that weather can be predicted for a very few days, even though they have this grid over the globe and they use the appropriate equations on the boundaries of their grids and averages within the grids.
The reason the models fail after a few days are due to this: the solutions even of the differential equations they are using are highly non linear because that is the nature of coupled differential equations. Let us expand these solutions in a perturbation expansion, and even suppose that it converges. The first term of the expansion, the linear term is connected with the average, and usually the first terms of expansions fit quite adequately for the first steps of the variable, in this case time every 20 minutes. After some time, i.e. number of steps,( by observation for weather in 300 or 400 iterations), the higher terms come in force and spoil the fit and thus predictions are off.
Now when these models are taken over and used on different time scales, the same applies, and they have substituted a lot more averages in their ambitious expansion.
By observation we see that these solutions diverge after a very few years, for the same reason: the first order terms cannot stand in for the complete solution of highly divergent solutions of coupled nonlinear differential equations, even if one had all of them in.
In addition a lot of equations are missing as George is arguing.
The way other sciences are facing this problem (of highly nonlinear coupled differential equations) is with complexity and chaos theory and applications. There is a paper by Tsonis et al who have used neural nets to this effect and I think that this is the way climate modeling should go.
anna v: What you are stating is nothing new to climate scientists. They understand chaos and sensitivity to initial conditions and indeed they do see it in their models. I.e., if they perturb the initial conditions, then the model follows a different trend of ups-and-downs in the temperature. However, despite these differences, the predictions of how much the global temperature changes over a reasonable-length period due to a change in greenhouse gas forcing is robust to these perturbations in the initial conditions.
The technical distinction that is often made is that weather prediction is an initial value problem whereas predicting a change in climate in response to a forcing is a boundary value problem.
anna v (22:34:19) :
You seem to be moving the goal posts a bit. I didn’t say anything about whether the models were “right” or “wrong”. I was addressing your’s and George’s misconceptions about how the models work.
Saying that the models don’t deal with clouds correctly is one thing; saying that models completely ignore clouds is another!
I just think that anyone who wants to argue about the accuracy of the models needs to have at least a basic understanding of how they work.
When someone gets the fundamental basics completely wrong, it makes it difficult for me to take any of their arguments seriously.
Joel Shore,
Using chaos in the language and using chaos theory to calculate are two different and distinct issues.
In the IPCC reports where models are given with spaghetti graphs and large bands of
“errors” when you go to chapter 8, you see that these are not real errors, i.e. varying systematically the parameters and initial conditions to see how much the solutions are perturbed , but “educated estimates of what the errors are”, i.e depending on the modeler’s intuition.
I am too lazy to hunt again the exact chapter and verse where it is stated clearly In the last IPCC report that “no likelihood” has been developed yet for the models.
I am sure that the reason they have not been able to develop a likelihood function for these models is what I stated in my previous post: first order approximations (that the use of averages is), diverge strongly in systems of coupled non linear differential equations.
So the robustness depends on the intuition of the modelers and not on hard mathematics.
It is all done by sleight of hand and magic.
Anna V: If likelihoods are what you desire, various groups (such as Annan et al.) have done Bayesian likelihoods for the climate sensitivity based on climate models simulating various empirical climate changes in the past.
I think the reasons that the IPCC has stayed away from likelihood is:
(1) Their emissions scenarios about future evolution of society and how that affects energy use etc. are just that…scenarios. It is hard to ascribe likelihoods to such things.
(2) The models biggest source of error are not errors in integrating the equations but potential systematic errors of various sorts (the representation of clouds, …). In such cases, establishing likelihood functions is not really possible.
Science can rarely quantify uncertainty rigorously. What I think this really all comes down to is holding climate science to a different standard than other physical sciences simply because you don’t like the political / societal implications of its conclusions. As I have noted before, if quantum field theory had controversial implications, we would see QFT “skeptics” who would be asking us how we could believe a theory where you have to subtract quantities that are diverging to infinity to get a meaningful result!