It was just yesterday that we highlighted this unrealistic claim from CMIP5 models: Laughable modeling study claims: in the middle of ‘the pause’, ‘climate is starting to change faster’. Now it seems that there is a major flaw in how the CMIP5 models treat incoming solar radiation, causing up to 30 Watts per square meter of spurious variations. To give you an idea of just how much of an error that is, the radiative forcing claimed to exist from carbon dioxide increases is said to be about 1.68 watts per square meter, a value about 18 times smaller than the error in the CMIP5 models!
The HockeySchtick writes:
New paper finds large calculation errors of solar radiation at the top of the atmosphere in climate models
A new paper published in Geophysical Research Letters finds astonishingly large errors in the most widely used ‘state of the art’ climate models due to incorrect calculation of solar radiation and the solar zenith angle at the top of the atmosphere.
According to the authors,
Annual incident solar radiation at the top of atmosphere (TOA) should be independent of longitudes. However, in many Coupled Model Intercomparison Project phase 5 (CMIP5) models, we find that the incident radiation exhibited zonal oscillations, with up to 30 W/m2 of spurious variations. This feature can affect the interpretation of regional climate and diurnal variation of CMIP5 results.
Why wasn’t this astonishing, large error of basic astrophysical calculations caught billions of dollars ago, and how much has this error affected the results of all modeling studies in the past?
The paper adds to hundreds of others demonstrating major errors of basic physics inherent in the so-called ‘state of the art’ climate models, including violations of the second law of thermodynamics. In addition, even if the “parameterizations” (a fancy word for fudge factors) in the models were correct (and they are not), the grid size resolution of the models would have to be 1mm or less to properly simulate turbulent interactions and climate (the IPCC uses grid sizes of 50-100 kilometers, 6 orders of magnitude larger). As Dr. Chris Essex points out, a supercomputer would require longer than the age of the universe to run a single 10 year climate simulation at the required 1mm grid scale necessary to properly model the physics of climate.
The paper: On the Incident Solar Radiation in CMIP5 Models
Linjiong Zhou, Minghua Zhang, Qing Bao, and Yimin Liu1
Annual incident solar radiation at the top of atmosphere (TOA) should be independent of longitudes. However, in many Coupled Model Intercomparison Project phase 5 (CMIP5) models, we find that the incident radiation exhibited zonal oscillations, with up to 30 W/m2 of spurious variations. This feature can affect the interpretation of regional climate and diurnal variation of CMIP5 results. This oscillation is also found in the Community Earth System Model (CESM). We show that this feature is caused by temporal sampling errors in the calculation of the solar zenith angle. The sampling error can cause zonal oscillations of surface clear-sky net shortwave radiation of about 3 W/m2 when an hourly radiation time step is used, and 24 W/m2 when a 3-hour radiation time step is used.
Ouch. That’ll leave a mark.
[snip – no more Mosher drive-bys, make a point with a reference – mod]
Linking to the SI. ?
good moderation policy.
The reference IS the point for people who can read
I know I’d prefer a brief summary and a link.
Otherwise don’t bother.
The models measure incoming sun light for a flat earth?
?
Oh, you must be talking of the sharia compliant vision of the earth.
Oops!
But they are still adding fluxes which is not correct.
All models make one wrong assumption, that CO2 heats the atmosphere. There is no empirical data that shows it does.
How do you tangle longitude and TOA solar? That’s just nuts.
The sun doesn’t shine at night. (Simple answer to simple question)
The sun DOES shine at night. It shines constantly. It’s just that the Earth has rotated away from light strike!
It’s always 12 noon directly under the sun, isn’t it?
The models don’t like to wait until the sun has passed over the yardarm.
Douglas:
Patrick is correct. Furthermore. “Annual incident solar radiation” averages over all hours of all days, so the day-night distinction is superfluous.
He was being facetious.
That’s why the 49er fans planned their solar landing at night.
It’s always 12 noon directly under the sun, isn’t it?
==============
you’ve hit the nail on the head. In each time zone the sun is only overhead at noon for a single longitude. It is early or late for all others, because each time zone is typically 15 degrees of longitude – the distance the sun appears to travel in 1 hour.
It is this error, the temporal distance between your longitude and the actual longitude of the sun that could lead to an oscillation in the calculated TOA energy, depending on the size of your time slice and your relative position within the slice.
Quite silly actually of the model builders not to correct for this, but given the size of the grid they probably just assumed it would all wash out in the averaging. And since the models showed warming and they expected to see warming, they never bothered to look for errors. If it ain’t broke, don’t fix it.
The energy from incident radiation(the sun) does not average out. That nasty T^4 power in Stefan’s law plays heck with using averages to calculate heat and energy transfer. It’s not coincidence that thunderstorm strongly tend to form in the afternoon, shortly after the ground has absorbed all that heat from the sun. A model would have to integrate the heat input across a grid cell from sunrise to sunset to generate an accurate picture of the energy flow..
A given point has rotated away, not the whole Earth. How wide a strip and duration is noon, anyway? .0001°?
Nitpick: 100 km vs 1mm is 8 orders of magnitude, not 6.
It’s even worse than we thought !
That will undoubtedly be the response of Warmist pseudoscientists and their co-religionists.
8 OOM by distance. That’s 16 OOM by area and 24 OOM by volume. That’s a lot more opportunity for error. An error in the 24th digit would propagate. A numerical butterfly effect.
Ha. Ya got me!
They can just instruct their computers to calculate pi to 10^24 digits for all relevant calculations, thereby cancelling out the imprecision of their blunder with increased mathematical precision for pi.
Fast, Johan. Fast!
Thank you!
Another excuse coming
Hi Anthony –
Thank you for this new information.
This is another example of the deficiencies of these models. For a summary of others, please see our articles
Pielke Sr., R.A., R. Wilby, D. Niyogi, F. Hossain, K. Dairaku, J. Adegoke, G. Kallos, T. Seastedt, and K. Suding, 2012: Dealing with complexity and extreme events using a bottom-up, resource-based vulnerability perspective. Extreme Events and Natural Hazards: The Complexity Perspective Geophysical Monograph Series 196 © 2012. American Geophysical Union. All Rights Reserved. 10.1029/2011GM001086. http://pielkeclimatesci.files.wordpress.com/2012/10/r-3651.pdf
Preface to
Pielke Sr, R.A., Editor in Chief., 2013: Climate Vulnerability, Understanding and Addressing Threats to Essential Resources, 1st Edition. J. Adegoke, F. Hossain, G. Kallos, D. Niyoki, T. Seastedt, K. Suding, C. Wright, Eds., Academic Press, 1570 pp.
http://pielkeclimatesci.files.wordpress.com/2013/05/b-18preface.pdf
Best Regards
Roger Sr.
The hyperbole in the post requires some due diligence
http://onlinelibrary.wiley.com/store/10.1002/2015GL063239/asset/supinfo/grl52723-sup-0002-figs1.pdf?v=1&s=2c70ac93b0eed88d987977cfaf6813bb8bf69ed2
What’s the hyperbole? Can you explain.
Steve thanks for the input. It appears that Models don’t compensate for the Latitude angle at all. They model a flat circular earth instead of a sphere, that is why they all get 417 watts per square meter, when the poles should be receiving ZERO solar insolation..
You have shown exactly why models are completely nonphysical representations.
Genghis:
Quoting from post quoting the paper (my emphasis): “ANNUAL incident solar radiation at the top of atmosphere (TOA) should be independent of LONGITUDES.” so I’m not sure why you’re talking about Latitude angles.
From Mosher’s reference, it appears to me that some models show low variance with longitude, some others do much less well. I’m making some assumptions here, because the x- and y-axes are unlabeled. I also assume the chart titles identify various models.
I’m sorry, but I think solar input is a function of both latitude and longitude, as both have equal angles of incidents towards the “edge” of the earth “disk”.
What am I missing?
Steven
Every now and then (but not often enough to be valuable) you actually say something interesting, meaningful, and understandable.
The rest of the time it’s a couple lines of snark with (at best) a link to what may or may not be relevant.
This egotistical QED game is almost always misleading, usually obscure, not supported by any relation to your point.
You may (think you) understand it, but so what?
Genghis:
Even if the IPCC used a complex calculus formula with the function from zero to the max at the equator (whatever value they used) in total solar insolation, and adjusting for the time of day and angle of the sun from mid day, and then total sunlight at the other pole…. a very complex problem just to think about……… the current data still comes out wrong. Developing a fractal formula made much more sense. Especially in light of ocean, land, clouds, and ice and incident angle of sunlight relative to the earth.
If AND I DO MEAN IF, the IPCC’s number were correct, global runaway warming would already be a reality and not a prediction. We wouldn’t be debating about whether they were right or wrong, it would be obvious.
The error mode, when it occurs, is an almost exactly sinusoidal variation around the equator, with 3h or 1h period according to sampling. It will have no effect on total incoming radiation. The authors say it will have negligible effect on mean surface temperature.
“Now it seems that there is a major flaw in how the CMIP5 models treat incoming solar radiation, causing up to 30 Watts per square meter of spurious variations. To give you an idea of just how much of an error that is, the radiative forcing claimed to exist from carbon dioxide increases is said to be about 1.68 watts per square meter, a value about 18 times smaller than the error in the CMIP5 models!
1. If you look at the SI you will see that only SOME of the CMIP5 models were examined.
2. If you look at the SI you will see that only SOME of this subset had the issue
3. If you look at those that did you will see that only SOME of them had ‘large errors”
4. If you look at the errors you wil see that it is not constant but sporatic.
5. comparing the effect of a sporatic forcing to a constant forcing is a hoot.
6. There is no secular component to the error
next
“Why wasn’t this astonishing, large error of basic astrophysical calculations caught billions of dollars ago, and how much has this error affected the results of all modeling studies in the past?
The paper adds to hundreds of others demonstrating major errors ”
1. astonishing? hardly.
2. Large? it depends.
3. Hundreds of other papers demonstrating major errors? like I said, requires due diligence.
Models are wrong. Hyperventilating in either defense of models or in attacking models.. is bad drama.
What Steven has referenced shows that the GCM’s average solar insolation to be 417 watts for every square meter for the entire Earth.
That means that every cell in the computers calculation for the high latitudes is off by at least 350 watts and every cell in the lower latitudes is off by at least 70 watts, simply based on the angle of incidence.
And furthermore because it is based on a non rotating earth it is off by up to 60 megajoules because of lack of computing the actual insolation. A 417 watt average is meaningless.
No wonder the GCM’s have no predictive power, they can’t even get the inputs correct.
Nick Stokes
March 10, 2015 at 2:12 pm
The authors say it will have negligible effect on mean surface temperature.
Isn’t the scientific method to do the correct calculation to see how it effects model evolution? What if there is a chaotic effect and it changes strange attractors? There is no way to know until you do it correctly.
Another drive-by.
Steven Mosher, ever more predictable, ever more boring.
Ghengis,
No. Just … no. See the main paper:
Fig. 1. Annual-mean incident solar radiation at the top of atmosphere from 8 climate models in CMIP5. The color scale has been adjusted to highlight the zonal variation in the tropics. The model names are in Table S1 of the Supplemental Materials. Units: W/m^2
By way of KNMI climate explorer, I report that the entire CMIP5 ensemble gives an annual average of 400 W/m^2 in the tropics (30N to 30S), vs. 340 W/m^2 for the entire globe.
Mosher writes “Models are wrong. Hyperventilating in either defense of models or in attacking models.. is bad drama.”
Yes and wrong models cant model climate change. They can model weather over the next few days. Parametrisation utterly kills models. It cant possibly be known the parameters vary as the climate changes. Modelling climate is many orders of magnitude harder than modelling weather.
Thanks for the links!
rpielke
March 10, 2015 at 9:14 am
Specify
DOY = Day-of-year (1 – 366 in leap years)
LAT = LAT (in radians)
ATF = Air attentuation (function of latitude and season, if in temperate latitudes)
0.75 if polar
The day and hour angle (for declination) = TAU =2*3.1415*(DOY+D9/24-1)/365 for any hour of the day
The declination (for the entire day) at 12:00
=0.006918-0.399912*COS(TAU)+0.070257*SIN(TAU)-0.006758*COS(2*(TAU))+0.000907*SIN(2*(TAU))-0.002697*COS(3*(TAU))+0.00148*SIN(3*(TAU))
The declination for every hour of the day
=0.006918-0.399912*COS(E9)+0.070257*SIN(E9)-0.006758*COS(2*(E9))+0.000907*SIN(2*(E9))-0.002697*COS(3*(E9))+0.00148*SIN(3*(E9))
Where cell E9 is the hour angle for that day (see above)
For each day-of-year, the TOA solar radiation (to within 1/2 watt/m^2 of SORCE measurements)
TOA=1362.36+46.142*(COS(0.0167299*(DOY)+0.03150896))
Over the year, the actual TOA radiation varies from 1408 watts/m^2 (January 5) to a low of 1315 watts/m^2 (July 5).
You now have a latitude, the actual TOA radiation for that day, and the declination for that hour of the day.
ANY day-of-year. Any latitude to any degree of accuracy desired. 1/100 km, 1/10 km, 10 km, 100 km, 1000 km, 1 deg, 0.1 degree, or whatever.
Get an hour angle HRA = =(RADIANS(D9-12)*15) for cell D9-D32 being 0 – 24 hours. Or whatever time interval is desired.
From those, you get a Solar Elevation Angle (SEA) in radians for each hour angle (also in radians) :
SEA =ASIN( (SIN(F9)*SIN(LAT)) +(COS(F9)*COS(LAT)*COS(G9)) )
for cells F9 and G9 being the declination angle and HRA angle for that particular hour. LAT was already defined in radians.
Note. Some users prefer Solar Zenith Angle SZA rather than SEA.
From Solar Elevation Angle for that hour, you get Air Mass (Kasten and Young, 1989; Kasten & Young, 1994, etc.)
AirMass = =IF(I9<0,0,(1/(COS(3.14159/2-H9)+0.50572*(6.07995+I9)^-1.6364)))
(Note, if the SEA is < 0.0 (the sun is below the horizon, the air mass = 0.0 and the sun has no radiation at that location at that hour. Uses Excel notation for cell H9 being the SEA (in radians))
=IF(I9<0,0,(ATF)^((J9))) for cell J9 = AirMass for that hour of the day.
(Note, if SEA < 0 (the sun is below the horizon, again, the attenuation = 0.0)
Direct radiation on that day at that latitude on a perpendicular surface to the sun's rays =
=TOA*K9 for cell K9 = the attenuation factor for that hour of the day.
Direct radiation on a flat surface depends on latitude.
Direct radiation on a flat surface =L9*SIN(H9)
for cell L9 = direct radiation on a perpendicular surfae and cell H9 being the SEA angle at that hour.
If a mountain slope, the GC Models ignore it.
The GC Models also ignore the effect of high altitude (less attenuation, cleaner air as well, less air mass).
the direct solar radiation is thus calculated in about 9 steps using single formulas at each step.
Diffuse radiation can be modeled as a function of air mass and direct radiation, or as a function of the Link turbidity factor, or as simple percentages of the potential direct radiation. Albedo of many common terrains and substances (particularly snow, soil, plants and water) is different between direct and diffuse radiation, so be careful at what is assumed and what is measured.
You can now calculate the albedo for the oceans based on the solar elevation angle for the ocean surface (which changes from 0.067 to 0.75 at low SEA angles) and the albedo for the land, sea ice, tundra, desert, and farm lands. None of which are "modeled" uniquely.
So, how could they screw this simple a function up? Because they knew the answer they wanted.
“the alleged radiative forcing from all man-made CO2 generated since 1750 is claimed by the IPCC to be 1.68 W/m2”
Let’s see, given the IPCC equation : (dT/dt) (C/year) = Forcing (W/m2) / 3.3
0.51 = 1.68 / 3.3
In other words the temperature of the atmosphere has risen over 5 degrees in the last 10 years.
I don’t see that in the temperature records, maybe that makes me a denier.
“a supercomputer would require longer than the age of the universe to run a single 10 year climate simulation at the required 1mm grid scale necessary to properly model the physics of climate.”
In other words, “All models are wrong. Some are useful.”
That one sentence underpins how little we really understand about “climate change.”
“That one sentence underpins how little we really understand about “climate change.”
Pretty much everything is understand about “climate change”, very little is know about actual climate…
Yikes, let’s try that again,
Pretty much everything is understood about “climate change”, very little is known about actual climate…
I think that is a bit of hyperbole, on two grounds. 1: they could use computers that are on the order of 100x what they are.secondly it only takes a matter of a day or so to do the calculations. 8 orders of Magnitude is 100 billion days ,and the Universe has been around some 3700 billion days. In about 30 years, this will be a reasonable amount of computing power as well.
The real difficulty would be creating sensors that could calculate to weather for each square centimeter. I doubt that will ever be possible.
Actually it’s 10^8 in one direction. (100 x 1000 meters x 1000 mm/meter) With three dimensions we have 24 orders of magnitude total. Admittedly we won’t need quite as many orders in the third dimension as the atmosphere isn’t really a full 100 km high unless you include the ionosphere. But it’s still far more than you’re talking about.
The science is not only unsettled but ludicrously wrong.
I believe the phrase is “not even wrong”. But we have known that about CAGW for a long time.
Too much incoming radiation in their models? Maybe they ran them in a microwave oven. 🙂
Ahh, it is the incoming solar radiation that they screwed up on.
That is truly breath taking stupidity. I can understand how trying to ‘calculate’ how much out going radiation there is could be challenging, but incoming radiation is known quite precisely.
The fact that the models were trying to derive a known constant and failing, tells me everything I need to know about the models.
Incoming radiation at the top of atmosphere is easy to measure but not at the surface.
No, incoming solar radiation at the top of the earths atmosphere is not a constant. Outgoing radiation at the sun’s surface is a near constant (it does vary, but not by much).
However, The earth’s orbit is elliptical, not circular, so the distance between the earth and the sun changes constantly. With the constant changes in distance come constant changes in the intensity of solar radiation at top of atmosphere.
As you get farther from the sun, the total amount of radiation stays the same, but it is evenly distributed over the surface of an ever larger sphere. The surface area of a sphere is 4PiR^2 so the decrease in intensity of solar radiation at any given point is quite rapid. This means that while variations in solar radiation at the sun’s surface are negligible, the variations at the top of the Earths atmosphere are quite significant.
No, No. I think somebody unplugged one of the cooling fans on their computer. That’s why their models run hot.
I’m sure this will be the lead story on all the major News outlets. They are always quick to publicize shortcomings of the global warming narrative. Does this mean we can have two more cycles of CO2 doubling before we get to the point we thought we were at? Maybe climate change was responsible for the error. It’s worse than we thought!
Burning all known fossil fuel resources would be inadequate to achieve one doubling of CO2 ppm.
Anyone remember the old joke, “we don’t test our software, that’s what users are for”?
That isn’t an old joke.. that is how we do it !
He has you there
there are three kinds of software errors:
1. the kind users know about
2. the kind developers know about
3. the kind no one knows about.
typically we only have budget for 1.
sometimes we sneak in a fix for 2.
we hope and pray 3 is small or we find a new job before someone discovers otherwise.
if your math is 18 times worse than the result your margin of error is gonna completely eclipse any “science” you’re attempting to do.
I’ve written this before
What margin of error? Modelers seldom, if ever, acknowledge the existence of error bars.
Perhaps I need to improve my reading skills but I didn’t see a sign (+ or -) on the “spurious variations. Can someone please clarify?
What appears to be happening is that the models are using the solar angle at the start of the time period to determine the incoming radiation over the entire segment. This will tend to reduce solar radiation up to noon and increase it after noon, depending on where the segments are centered.
So maybe the models are on Daylight Savings Time?
Good one Brain after all we do get more sunshine with daylight saving time. I willing to be half the population actual believe we get more sunshine in a day due to daylight saving time.
Maybe this explains why the models all run to the hot side?
Maybe not an “accidental” error?
And the net effect is ……. what?
The temperature adjustments are huge. Judith Curry seems to accept the Zeke explanation they are reasonable, i.e. their net effect is zero. Others disagree. What is done is less important than what happens as a result. Here, the presence but not the effect is noted. But only the effect is important.
We need at least a calculation of what the error does for the basic energy balance of the Earth on an annual level.
Orbital variations are already known, major, bigger than CO2 forcings and cancelled out by natural processes. I suspect this error will disappear into the general +/- of the models but we need to know with certainty before we get too excited.
@NavarreAggie said “In other words, “All models are wrong. Some are useful.”
Depends on who you are. I would posit that the ‘wrongest’ models are ‘mostest’ useful to the warmists.
Why wasn’t the James Hansen’s quantitative howler that Venus’s surface temperature , 225% the gray body temperature in its orbit — a greater solar gain than anything humanity has yet created , been universally repudiated decades ago ?
….. not to mention the Earth’s oceans boiling from positive water vapor feedback to anthropogenic CO2.
Because infinity is unattainable, something terminates the feedback at some point. By the evidence, quite early in the case of water vapor latent heat transactions.
Because why combine what scientists know about ideal gas laws in cosmology to anything here on Earth?
Doesn’t really have anything to do with gas laws because they have to do with change in pressure , not effectively steady state . The equilibrium temperature of a radiantly heated ball depends on the correlation of its absorption=emission spectrum with its sources and sinks . Pressure per se doesn’t enter the equations . It would be nice if it did . We could just fill up giant scuba tanks and use them as sources of perpetual heat .
the lapse rate is related to pressure through gravity. thus the bottom of mine shafts are hotter than the surface, not because they are closer to the center of the earth, but because we have an atmosphere.
the surface pressure of venus is 90 atmospheres. the equivalent of a very deep mine shaft.
Another example of increasingly active Chinese scientists rocking the boat of climate science orthodoxy. Good to see.
one group of communist counteracting another group communist because the self interest collide. what could be better then that.
Assuming (big if) that the errors cancel out, ie, total energy to earth is approx. correct. Still the spurious errors are not explained. I am next assuming they did not screw up the incident at the equatorial regions, I mean how do you screw this up? hence the variation is in the polar regions? Does this explain why the models predict massive warming on the polar regions? If you can’t melt the polar icecaps with correct incident solar radiation, then a little trigonometry trick fixes that. Hey, Mike did it for his stuff, we can too!
Please excuse me for being dense, but I thought Mr. Watts included an article a week or so ago, that stated that the radiative forcing for CO2 had been measured in Oklahoma and the north slope of Alaska to be 0.2 W/m2. Am I remembering wrong, or did I just not understand the article. Any help would be appreciated.
Dan Sage
Dan Sage:
.2 W/ m sq. per decade. Comments showed the interval of 2000-2010 was cherry picked and that figure was merely a measure of temperature differences between the start and the end of that decade.
Dan Sage, I think you are referring to, “Almost 30 years after Hansen’s 1988 “alarm” on global warming, a claim of confirmation on CO2 forcing”, February 25, 2015
There will be rationalizations…
Yes. Look upthread.
I really like the Radiative Forcing graph with the error bars / confidence intervals. The only component I am not able to figure out is “solar irradiance”? What anthro forcing is this trying to quantify? I’m sure it will be obvious after someone tells me… 🙂
The GC models were never intended to do anything except justify an ideology-based economic-political roadmap for the UN. By that metric, they have been somewhat successful. But science they are not.
How many ‘hiroshima equivalents’ is the error margin?
Oh, I second that! How fun it would be to turn the Hiroshima equivalents propaganda into measures of model error!
Paper is paywalled. SI is not. SI1 shows that the spurious longitudinal variation in some, not all models at the equator correlates in a statistically significant way with feedbacks including clouds and precipitation. SI2 shows that none of these are self cancelling (averaging out around the globe).
Indeed, by WE’s governor hypothesis, they are in continual operation to constrain heat accumulation at the tropics,
But the error would not be cumulative, so would not impact the trend.
Obliquity variability should not impact total annual TOA input into the climate system, but the actual impacts are significant.
But that variability is cumulative at the locations where it matters.
Spurious variation is not to be confused with consistent variation. Is the trend spurious and or are the outliers truncated via model interpretation or aggregation?
We do not know that without seeing the source and type of error.
If the error ‘let in’ more energy than was really there, that energy might be captured by another formula and retained inside the toy atmosphere.
I have always been unimpressed by the initial claim that there would appear a tropical hot spot 8-16km above the ground. When that was first mooted, there was no polar amplification. When measurements showed that there was no hotspot but one of the poles was warming, ‘polar amplification’ appeared from the models. Rather convenient.
What has always amazed me is that, like a monopole, polar amplification has a North but no South. Physics is more interesting than I thought.
The errors are accumulating, and that is the trend.
it would most certainly affect the variance and thus the standard error.
Fifty quatloos says that when it’s sorted out, the fixes make CAGW even worse than we thought!
They are no doubt even now writing the letter demanding that they need an even bigger computer.
But, but … wouldn’t that mean the models were even more usel … ahh, less accurate?
And we base energy policy on this type of output? No other place in society would this type of issue be tolerated.
Ask yourself why?
Just amazing.
Queue up Kraftwerk “The Model” metaphorically speaking 🙂
If you had said “on this type of model” I could have made witty comment about women’s fashion.
It might have been witty, but it would have been appropriate.
this whole thing reminds me more and more of a “Bugs Bunny” cartoon … cue the Acme climate computer 2000 and dial the results for Elmer…..”ahhhh what a maroon.” wish it were truly just for comedic affect rather than sucking productivity and wealth redistribution.
Cheers,
Joe
Here you go, direct from Bug’s mouth:
http://www.entertonement.com/clips/nsvdjzkfdz
Hear, hear!
Were you thinking of Drs Richard Betts and Tamsin Edwards when you wrote of “comedic effect” and “sucking productivity and wealth distribution”?
Reminded me of:
1) Richard Betts;
2) Crediton solar farms;
3) Tamsin Edwards on Twitter ( and how more women should have careers in science so they can be full-time tweeters. )
ossqss, “No other place in society would this type of issue be tolerated.”
You really need to read more widely. This very same problem exists in every “science guided” policy area in the western world, from climate to diet to health. The problem is not the scientists necessarily, but rather the non-scientists, especially lawyers and politicians, who jump on “scary” scenarios and set policy on a basis of expecting the catastrophically worst case, and making policy based upon the precautionary principle. Very little public policy makes any kind of sense, and in general the rule will be that the squeaky wheel will get the grease. That is how Prohibition was passed, how current governmental guidelines on diet were established, and why despite any scientific support silicone implants were banned. Anecdotes and scary scenarios (watch The Day After Tomorrow for climate example) are what drive policy, not science. All science offers is the “possibility.” Your average policy maker could careless about the quality of the science.
Hi,
In simple to understand terms… What does this mean…
Can I say the warming that shows up in the models is overstated by X and what we have actually observed is what we should go by..
The Earth will not be in flames in 2 or 5 or 10 years
Is that the takeaway…
I am NOT a SCIENTIST. But all of the fearmongering and alinsky tactics of the Alarmists led me to believe that they were hiding something (not in this instance)
While i have your attention the Earth could be warming because we are still coming out of an ice age 10,000 years ago. But for me it is the almost religious zealotry of the Alarmists that makes me uncomfortable…
/Soapbox off
Nope. We finished comming out of the Late Glacial Maximum about 10,000 years ago. The planet continued to warm for about another 2,000 years. The earth has been generally cooling for the last 8,000 years or so. The present is not the coolest moment in the late Holocene, but considering that the warming covers the rebound from the LIA, the present is still cooler than about the Roman Warm Period, which in turn was cooler than the warm period that preceded it.
Coldest in ~8,200 years, is what we are:
http://www.oarval.org/Foster_20k.jpg
Graphic by Don J. Easterbrook
John,
“…tactics of the Alarmists led me to believe that they were hiding something…”
These days they are hiding from something.
Doug Proctor wrote “Judith Curry seems to accept the Zeke explanation they are reasonable, i.e. their net effect is zero.”
Compensating errors is not the same as accuracy. In the real world this type of mistake would get you a huge wrist slap, you might even be walking the beach afterwards.
Suppose the spurious fluctuations propagate?
It is very likely that the errors cancel each other out. I don’t think this finding is important. It would be, if the models were being used to predict regional climate. But that’s not the case. If a cell incorrectly receives 20W/m2 that should have been received by the neighbour cell instead, this is not even a change as significant as the move of a cloud from cell to cell. And models do not model clouds or general cloudiness properly.
As the case may be, is this the kind of error one would expect from ‘state of the art’ climate models ?
Yes, it is, given that the art is in an abysmally primitive state.
Cave art.
If, as I suggest below, the problem comes from sampling every three hours, then the peaks in the error would occur every 45 degrees of longitude. That’s sort of like adding heat to California and Florida while freezing the plains states. Hey, perhaps reality is tracking the models!
” 30 W/m2 of “spurious variations” from incorrect calculation … is up to 18 times larger than the total alleged CO2 forcing since 1750.”
Couple in proponents of Climate Change were using CMIP5 models to back Global Warming and what do we got?
We have proponents proving by way of this incorrect calculation – “It’s the Sun”.
Etruscan Adage: “Where bug (is), bugs (are).” This is probably not the only significant error in the models. Warmists will immediately counter this discovery with a devastating barrage of ad hominem arguments* and other such nonsense.
* E.g., “Psychological studies show that Deniers have homo sapiens tendencies.”
This is just another example of why I continue to push for an open , well factored and therefore understandable , APL language level planetary model , see , eg , http://cosy.com/y14/CoSyNL201410.html#Need .
Such modern notations are generally as or more succinct than those in traditional textbooks . But they have the enormous advantage of being efficiently executable on any scale hardware so anybody can “play around with” the concepts . For example , in http://Kx.com ‘s K , which is the greatest influence on my own ongoing work on 4th.CoSy a dot product is defined as
dot : +/ *. But unlike the typical definition ofdotas the sum across the products of corresponding elements of two lists , it will sum across arbitrary arrays of pairs of lists of arbitrary length . Thus that simple expression can compute the dot products of an entire spectral map of the planet with the solar spectrum or a Planck thermal spectrum at once . Mean planetary temperature is , of course , ultimately determined by our spectrum as seen from the outside .A rather detailed competitive model of the planet can be written in not more than a few pages of APL definitions — and again , run on anything from a smart phone to a super-computer .
There would be no place for stupidity or mendacity to hide for very long .
Bob,
Dude, write the app! Get it started and invite others Who Know to add, subtract, multiply and divide. It would be one of the great group learning experiences in history.
You might ping David Evans as a collaborator – he’s really good with F’s Ts.
It is interesting that all the CMIP5 and CESM models exhibit the same error. I’ve long suspected that the modelers all borrowed code from one another. This would explain why there is such conformity in their results. It isn’t that they are all very about the right answer, it’s that they are all wrong together because they all use the same faulty code.
Yes but if you put all the wrong ones together by averaging their output they are more accurate than reality and the UKMO can then accurately predict the movement of every weather front. /////////sarc off
…sharing code probably also makes it easier to test (well, test is a relative term) your model with other models…
Sorry, that should be “they all vary” not “they are all very”.
Don’t apologise. You were clear.
And you make vary important point.
Seriously, you do.
Agreed.
I have spent many weeks now poring over the assertions of astronomer Duncan Steel, cited by a posting on the thread about insolation and ice ages back in early February, that insolation and albedo are much more complicated topics than the climate modelers admit and the models may incorporate incorrectly; and I have found what he has said to be true. This particular problem appears to be a sort of aliasing error and a separate issue from Steel’s concerns, but how many climate change “shoes” might eventually drop?
The impact on Albedo during the ice ages from all that extra glacier, extra sea ice, decline in forest cover, rise in deserts, rise in grassland, increased land surface with higher albedo due to sea level decline and reduced cloud cover according to the theory, has been vastly understated by the climatologists.
The reduction in net solar forcing is four or five time higher than the climatologists use when they try to simulate the ice ages with a climate model. Remember they need to keep the CO2 forcing impact at a high level so they have to reduce the ice-Albedo impact to keep the numbers close to reality. Increased Albedo during the ice ages reduces net solar forcing by at least -12 W/m2 if you actually run the numbers versus the amount Hansen used of just -3.5 W/m2.
That makes what? Explanation 64 or 65 for The Pause? `The Models got it wrong.’
I saw this on a FaceBook post yesterday. My comment there:
From what I can glean from the abstract, the models compute the incoming ToA radiation once per time increment, either one hour or three hours. In three hours, on the equator at the equinoxes, the sun moves 45 degrees. In the course of the daylight, the elevation of the sun could be computed at 0, 45, 90, 45, and 0 degrees above the horizon at one point and 22.5 longitude degrees away, it would be computed at 22.5, 67.5, 67.5, and 22.5 degrees. In terms of full sun, that would be the sine of the sun’s altitude, or 0, 0.71, 1.0, 0.71, 0 (total 2.42) and 0.38, 0.92, 0.92, 0.38 (total 2.60), a 7.5% difference.
In 2009 Trenberth et al. revised the 1997 vesion of their famous energy budget diagram. Vincent Gray posted a discussion of the changes on ICECAP http://icecap.us/index.php/go/icing-the-hype/the_flat_earth/
Since each of the two diagrams – 1997 and 2009 – contain the best estimates by the best and brightest scientists in the universe, I figure that any changes between the two estimates are an indication of the actual uncertainty in our understanding of what the actual energy amounts are.
So I created a diagram of the energy budget changes between the 1997 and 2009 versions, and here it is: http://icecap.us/images/uploads/EnergyBudgetTFed3.jpg
Note that at the surface of the earth, the major components, such as sunlight and IR absorbed and reflected, are unknown to plus or minus 6 to 9 W/m2. That gives an uncertainty of 1.3 W/m2 for the net surface energy balance. That means it will be difficult to find “the radiative forcing claimed to exist from carbon dioxide increases is said to be about 1.68 W/m2”.
Also note that at the bottom of the energy budget charts there’s a “Net Absorbed 0.9 W/m2”, which is the excess heat that goes to warm the earth. The actual uncertainty of this number is +/- 1.3 W/m2, so the actual net absorbed in indistinguishable from zero. That tells us where Trenberth’s missing heat is. It’s in the statistical uncertainty of the energy budget, and likely does not exist.
Ouch.
There is a 2012 redo by Stephens et. al. TOA imbalance 0.6+/- 0.4. Surface imbalance 0.6+/- 17!
Implications for sensitivity explored in essay Sensitive Uncertainty.
Ouch indeed, especially considering where they got that 0.9 W/m2 of “missing heat”. There’s no way they could have calculated it from the input numbers – the individual amounts shown on their energy budget chart aren’t accurate enough to come up with a fraction of a Watt per meter squared. And since that 0.9 W/m2 is supposedly Infrared heating from GHG and not sunlight, the number must have been pulled from a warm dark place where the sun doesn’t shine.
Ouch!
The ‘Settled Science’ seems to be in greatly in flux….
Trenberth’s 342 W/m2 is a global average. http://earthobservatory.nasa.gov/Features/EnergyBalance/page3.php
The Earth’s climate is created by the fact that solar radiation is far more intense (per square meter) in the tropics than in the higher latitudes and also varies diurnally and by season. The climate is driven by heat balancing through various physical and radiative mechanisms (many of which are also incompletely modeled). It is not driven by a simplified global average.
IMO, the global average TOA radiation can be as misleading and subject to error as the global average temperature.
Perhaps like Lake Wobegon’s children, all climate models are above average…
Thanks, “Icing The Hype” is an important article.
Your sort of thinking appears almost satirical. Do you work for The Onion? What you say in effect is that there maybe large errors in our models, but they don’t amount to much on net because they probably cancel out–I give many students a ‘D’ when they calculate a correct value through large offsetting errors. Irving Langmuir noted that one sign of pathological science is a tendency toward ad hoc explanations of contrary observations. This looks pretty ad hoc to me.
Kevin, the most important thing is to get the total incoming energy right, and also right for a given latitude band. which seems to be done correctly. We are dealing with prediction of GLOBAL temperatures, not local temperatures. The error here presented may cause a given place to be slightly, very slightly, more cold or more hot than it should, because of receiving too little / too much sun. But there will be another place next to it which will be more hot or more cold because of receiving too much / too little. The average doesn’t change, Also keep in mind that it is not just the incoming solar energy that afects a cell’s temperature. If it were like that, Europe would be a much colder place than it currently is. It is not, because we also get heat from other sources, mainly, the gulf stream. So if a cell does not receive the right ammount of solar but the neighbour cell receives extra, you can be sure that there will be some exchange of energy between them.
Nylo,
Surely it’s just as important to get the outgoing energy right too?
And that depends on how hot the area the heat is in, is.
As that depends on how spread out the energy is getting the wrong cell is very significant.
If you’re in one with a jet stream moving away from the equator the heat will spread out more than if it’s over a desert land cell.
Question: How many iterations before you’re model is worthless?
Answer: 1
Let us suppose that the current calculation methods mis-allocate the incoming radiation. The total is correct, but it is altered so that one area is modeled too warm and another area is modeled too cool. Remember that the radiative properties of an object are not based on the average temperature of the object, but on the sum of all the various small areas on the object. This means that a model with some areas too cool and some areas too warm will radiate more strongly than a model with temperatures which are more evenly distributed — even if the second model has the same average temperature. The CAGW crowd claims that the Earth is warmed by back radiation from extra CO2. If their models have the wrong numbers (too high) for the outgoing surface radiation, won’t they also have the wrong numbers (too high) for the CO2 back radiation?
Nylo
It is not as simple as ‘averaging’ because calculated heat loss from the over-warmed model spot has a non-linear response to a change of 1 degree. What you are saying is that the net enthalpy is the same but spread a little differently from reality.
The problem is while that may be true, it does not result in no difference in effective total heat because the hot spots are calculated to have cooled faster than they really did. Put in +28 W/m^2 extra heat into one cell and -28W into an adjacent cell. The combined energy is lost to space is larger that would be the case if the two were both at the average. The loss is minimised when the whole system is the same as the average. The loss is maximised by having all the available heat concentrated onto one spot.
The reasons for this are that space is below the lowest cell temperature and radiation is a function of T^4.
The models having this flaw will estimate that the heat left the system sooner, and because they are tuned to measurements, a fudge factor will have been entered. An incorrect fudge factor. I do not think this has anything to do with anyone’s ‘missing heat’, however. It is impossible to tell how the model outputs will be affected by it. Maybe they all react differently. But it is a lot of heat.
How many “local temperatures” do we need to calculated the “GLOBAL temperatures”?
The Earth being ‘spherical’, eventually the error will catch up with its offset.
I guess if we do a time average of glacier thickness on the great lakes in the USA then they are currently covered by a glacier 250 metres thick.
Kevin, the most important thing is to get the total incoming energy right
Climate models are inherently chaotic. It is very important to get the details as right as you can. “On average correct” can affect the flows. And the flows can affect the clouds. And the clouds can affect the flows.
Catching on yet? You don’t average Navier-Stokes.
Hi all,
I didn’t mean that having the wrong amount of solar at TOA for every cell cannot have an impact despite the average is kept correct. It probably has some impact. I just don’t think it is a BIG impact, and in fact, I think that the impact will be much smaller than getting the cloud cover of a particular cell slightly wrong. And current GCMs get the cloud cover at particular cells, not just wrong, but VERY wrong. And if cloud cover is wrong, then having the exact amount of solar energy at the top of the atmosphere or a 1% variation from the exact value at some places starts to become… irrelevant. Move a cloud a little bit, from a cell to the next one, and the energy entering the system will be correct again.
Comparing those 20 Watts to the 1.68 Watts of the CO2 forcing is sensationalist. One is a permanent forcing additional to existing ones and affecting every cell all the time, the other is a forcing that you take from here to put it there keeping the total the same. They cannot be compared.
From the paper it seems that the error may be limited to about 8 CMIP5 models, with 20 or so identified as not affected:
“It is seen that the distributions of radiative flux in many models (bcc-csm1-1, BNU-ESM, CanAM4, CCSM4, CESM1-CAM5, EC-EARTH, inmcm4, NorESM1-M) exhibit longitudinal oscillations. The same type of biases was also reported in some climate model in AMIP-2 in the dezonalized anomalies plot [Raschke et al., 2005]. This variation would not be visible in zonally averaged plots or in spatial plots when the color scale has a large range. Other CMIP5 models are found to exhibit little or no zonal oscillations (ACCESS1-0, ACCESS1-3, CMCC-CM, CNRM-CM5, CSIRO-Mk3-6-0, FGOALS-g2, FGOALS-s2, GFDL-CM3, GFDL-HIRAM-C180, GISS-E2-R, HadGEM2-A, IPSL-CM5A-LR, IPSL-CM5A-MR, IPSL-CM5B-LR, MIROC5, MPI-ESM-LR, MPI-ESM-MR, MRI-AGCM3-2H, MRI-AGCM3-2S, MRI-CGCM3.”
They propose a fix: “We applied a revised algorithm in the CESM that corrects the bias from both spatial and temporal sampling errors, guarantees energy conservation, and is easy to implement.”
As Rud says above, the impact for the 3-h averaging time is on clouds (about 2% in amount, which is not negligible, about 2 W/m^2), temperature (0.2K), and precipitation (0.5 mm/day).
Paper is available here:
https://dl.dropboxusercontent.com/u/75831381/zhou%20error%20in%20CMIP%20models%20solar%20zenith%20angle.pdf
Thanks for the paywall end around. Had not yet got around to looking myself.
I second that Lance, thank you.
Am I correct in understanding that the magnitude and sign of the (total) error is currently unknown? It may be huge or it may be in the noise?
Magnitude is on order of positive 2w/m^2 clouds plus whatever humidity feedback equates to 0.5mm rainfall.
Thanks!
This just proves we need to spend billions more on settled climate science to get it right. Fork it over™.
[You must use a legitimate email address to post here. ~mod.]
Sounds like one of those “adjustments.”
So will the IPCC be 99% certain now? /sarc….
The solar averaging error is repeated vertically as well as horizontally…
In other words the models model stacked flat bottomed boxes, which they call a grid system.
What is modeled is certainly a failed and stacked system..
“Stacked” is the right term.
..are you talking about indian internet trolls who get paid by blue-chip companies to fight for their right to use the atmosphere as a dumping ground for free??
[Reply: Are you an Indian internet troll paid to post here? If not, please use a legitimate email address. ~mod.]
“Rigged”?
It doesn’t matter if the error is large. We need extremes to get people to the middle ground.
The principle remains the same humans are to blame. ( favorite excuse #12 of leftist kooks).
Facts and other key discoveries after the fact do not matter with religions either.
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This reveals that substantial manipulation must have been required to get ‘reasonable’ results out of the models. Pampered is, I think, the appropriate word for them.They are not vehicles for discovery. Their core purpose seems to have been PR-support for fundraising and scaremongering. Part and parcel of the corruption of climate science for political ends.
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Exactly.
“Richard Bettsism” = “PR-support for fundraising and scaremongering”;
“Tamsin Edwardsism” = “Part and parcel of the corruption of climate science for political ends.”
Copyright Betts/Edwards 2015.
Well played, guys!
I would just advise people to be cautious in the conclusions they draw from this one paper — or one review article about it. Even if the apparent model error turns out to be real and pervasive, a separate inquiry is required to determine how — or even whether — it affects estimates of climate sensitivity and projections of future warming.
Marlo, waiting is good and I will wait for folk like Rud to report more. However we already know the IPCC models are GIGO, compared to the observations.
David and Marlo, final report from the front on this. WE did us all a favor by downloading top line CMIP5 for all 42 models (ensemble means, not the 107 individual runs) into Excel. Posted here IIRC 12/22/14. Others have since noted the the model ‘closest’ to observed GMST is number 31 (series 31 in Willis’ spreadsheet). I just went to KNMI to see which model. It is IPSL-CM5A-MR, which interestingly is one of the ones that does not contain the error.
It is not possible to speculate on sensitivity, since the Chinese authors only ran the atmospheric portion of CESM for 4 years in order to test their code correction. One would need at least a coupled slab ocean plus (traditionally) 150 years with and without the code fix to get that information.
Don’t think this is the biggest problem with CMIP5. Smallest in CMIP5 is 110km. Means subgrid processes like tropical convection cells have to be parameterized. That is unavoidable, and is the root cause for them running hot. See essays Models all the Way Down for illustrations of the issue, and essay Unsettling Science for Akasofu’s (IMO correct) understanding of the parameterization consequences. If Curry’s stadium wave or Tisdale’s PDO -AMO are close to correct (they are related, and are IMO), it is going to be a very embarassing AR6 WG1. Regards.
Rud states, ” Others have since noted the the model ‘closest’ to observed GMST is number 31 (series 31 in Willis’ spreadsheet). I just went to KNMI to see which model. It is IPSL-CM5A-MR, which interestingly is one of the ones that does not contain the error.
==========================================
Thanks. I have long been curious as to what was different about the model runs closest to the observed T.
My guess was that those few models were predicting less warming because they contained input parameters that would make the IPCC uncomfortable. It would appear to be basic science to want to know why those models have been more accurate, but I have yet to see details on this.
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The authors state that the error they identified would affect use of the models at regional levels (“This feature can affect the interpretation of regional climate and diurnal variation of CMIP5 results.”) So, the fact that the errors may approximately cancel out globally seems to me not to be the major thrust of the paper. It is that this mistake makes the models useless with regard to modifying them in the future with the goal of understanding regional climate changes. Right? I would be interested in Judith Curry’s basis for concluding the errors would approximately chancel out globally. The word “approximately” is a little disturbing when speaking about models that do not work very well. “Approximately” can also be applied to CO2 feedbacks (though I think “wild speculation” would be more accurate) and to estimating the role of clouds, which even the modelers admit is not handled well in current models. Even so, there are hundreds of papers that start with outputs from these models and use them as though they were actual data, which are then fed into other unvalidated models to predict that squirrels will become cannibals, dogs and cats will live together, and the dead will rise from the grave (h/t Ghostbusters, which includes my favorite line, “Back off man, I’m a scientist”) – with 99% certainty
The errors approximately cancel out globally which is why the models so accurately have projected the last 20 years or so of atmospheric temperature.
/sarc
This clip applies sooooooo often to AGW ‘science’….
Maxwell Smart – Missed it by THAT much, Chief!
http://youtu.be/oPwrodxghrw
The more errors there are in the climate models of this sort, …
… the more fudge factors have to be built in to come close to the Earth’s actual climate.
Error 1 —> Fudge Factor 1
Error 2 —> Fudge Factor 2
…
And we are still waiting for them to come close
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Even if the total solar irradiance averages out, if the model put more sunlight to the polar regions, that would cause more warming in the polar regions than expected (and less in the equatorial region?). Per Willie, the T^4 nature of blackbody radiation implies that the average global temp must increase in order to maintain the correct energy balance.
For how many years have the models and observations been diverging? They have known something is wrong, and could have tweaked the model parameters to make things fit, starting with CO2 sensitivity, yet have stubbornly refused to do so. Does anyone really think this will change anything about how the models work, or how the model results are reported?
Of course not.
” All models are wrong, But some models are more useful in extracting money from the taxpayer than others..”
That’s what you are saying, isn’t it, Mosher?
That the error may actually cancel itself out seems pretty logical. If it didn’t, an error that large would have sent the models careening out of the realm of possibility long ago instead of diverging from observations by a few tenths of a degree.
That’s not what is important here. What is important is that a fundamental, obvious, glaring error exists in the models, and appears to be shared by them. Meaning that someone blew it a long time ago and subsequent modelers simply built their own variations atop a faulty foundation. The questions now arises, are there similar fundamental errors built into the foundation?
Had we discovered that someone designed, built, and flew a passenger jet, only to discover that half the engineers were working in standard and half in metric, and by some miracle these monstrous errors cancelled each out such that the planes flew anyway, what would we do? Say its OK because the errors cancelled each other out? Our ground every single plane until all the designs could be picked through to see what other errors might have been made and just not presented themselves yet?
I don’t think that is a good analogy in this case David,
because while those planes actually flew
these models do not accurately match with the observed data.
The shuttles actually flew until one day they didn’t. MH370 actually flew until one day it didn’t. When/if we find root cause of these disasters is a mistake which by some miracle evaded detection until now, we ground everything until we know exactly what went wrong and if it affects anything else in the fleet.
davidmhoffer March 10, 2015 at 3:23 pm
And when that happens every engineer who was ever involved prays to God, “Not me dear God, please.”
Two almost too stupid to believe observations about the error:
1) Nobody noticed the gross error to “settled science” because everything surrounding it is also crap; hardly anybody believes anything about CO2 forcing – even warmist evangelicals;
2) Here’s the really funny part: THIS WILL BE CLAIMED TO HAVE ABSOLUTELY NO IMPACT ON MODEL ACCURACY (Real data? We don’t need no real data!).
I don’t think this will affect model output too much when corrected. Given TSI at TOA is about 1400 W/m2, this is approximately 2% error. And if we look at all the models in absolute temperatures, the coldest reproduces historical record about 2 degrees celsius below the hottest one. 2% difference in TSI can’t do that much so it’s all up to fudge factors.
” 2% difference in TSI can’t do that much so it’s all up to fudge factors.”
===============================
You forgot the sarcasm” tag.
It is actually about 400 w/m2. The sun does not stand still at the zenith all the time you know. As a matter of fact this whole debacle is about miscalculating the zenith angle.
Claiming an error in climate models is a bit comical. They are supposed to show a linear, upward trend with some variation and built in noise. They do this perfectly. Can’t argue with good results!
BBBBBut, it does not affect the results.
Let me see if I have this right. If [insert climate observation of your choice here] is “consistent with the models,” it’s either blind luck or a miracle?
It will be interesting to see what the models do when they correct the errors.
It’s not to late to coddle the model … maybe ad some hoc …
🙂
+1
Verification of the numerical methods is always an excellent idea.
Verification of the numerical methods is always an excellent idea and always an extremely useful exercise. Evaluation of component models, especially those critical to the application of interest, at different time-step sizes must be handled very carefully. Loss of energy conservation, for example, can be introduced.
Those people who say, it’s a small error, won’t do much, should consider that climate models are iterative; and the small error accumulates (assuming it does not cancel out completely. I think it cannot cancel out completely as the sampling leads to a step function that is NOT noon-symmetrical.)
It should be noted that the entire variation in temperature this whole fiasco is about is on the order of the 4th decimal place , ~ 0.3% .
And in a chaotic model (climate models are INHERENTLY chaotic) that can lead you to a different strange attractor. i.e. the error propagates and amplifies. Of course it might not propagate and it could be damped. You have to run it to see.
Oh , gobbledygook . The only tipping point around is 0c And our temperature is determined by our spectral map with respect to the Sun . And we’ve passed thru these temperatures many times before .
Tell me ;what threshold you assert is going to radically change our spectrum altho it has never happened in billions of years .
Bob Armstrong says: March 10, 2015 at 9:51 pm
“Oh , gobbledygook .”
Not gobbledygook but Chaos Theory terms. Let’s avoid the term Strange Attractor and just say: By definition an iterative model with finite precision of a chaotic system MUST develop an exponentially growing deviation of its state vector from the state vector of the simulated system.
Based on this precision argument, we would normally assume the UNAVOIDABLE deviation in each step to be of the order of least significant bits in the number format used. 0.3 % is many orders of magnitude larger.
Given this HUGE error we can say that what the Climate Models simulated HAS NOTHING AT ALL TO DO WITH THE CLIMATE SYSTEM OF THE PLANET EARTH. They simulated a DIFFERENT system.
I apologize for being a bit derisive , but the chaos of weather and climate is rather irrelevant to the boogeyman of mean global temperature . Determining the averages over the sphere and the year is more akin to calculating the temperature of a volume of gas via gas laws than understanding the eddies within it . Climate and weather are much harder problems than determining the mean and I think one of the impediments to solving the mean is that climatologists are looking up thru the chaos of the weather rather than down from the outside looking at the persistent “color” patterns of the ball .
The mean temperature of the planet is determined by its spectral map as seen from the outside . The eddies are blurred by time into relatively stable densities .
By the way , I learned what math I know hanging around Bob Williams and the NU math department in the late ’70s . Rene Thom and Christopher Zeeman’s catastrophe theory , closely akin to chaos , were pervasive influences .
Bob Armstrong
March 11, 2015 at 9:03 am
“Climate and weather are much harder problems than determining the mean”
That’s why I mentioned the deviation in the state vectors, not the deviation in a simple metric like average temperature.
It is always a joy to me to watch the scientists arguing over 0.2 of this and 0.002 of that when for the majority of the time they are talking about we measured to the nearest 0.5. Then they argue about how much cloud there is. We don’t know. Argue about how much heat we receive. Its an oblate spheroid, it wobbles…the ice changes daily, the clouds by the minute, the albedo by the season…We don’t know. How much heat gets in and how much is reflected? We don’t know. It depends on ice and snow cover, golden corn or brown earth, thin or thick cloud, how much water vapour, how much soot. We don’t know. So they create computer models which combine all the things we don’t really know and out of the spout comes disaster…the end of the world.. catastrophe….and worst of all…it is all caused by humans……the models say so. Yup.. gonna believe that when I see Obama sprout wings and ascend into heaven on January 20th 2017.
Until then I am going to enjoy the gift of life, in the most productive period of our race.
++
Yes, it should have been caught billions of dollars ago. But it was not.
The question is what are we going to do about it?
Business as usual with the IPCC and their flawed models?
Thanks, Linjiong Zhou, Minghua Zhang, Qing Bao and Yimin Liu.
Regardless of whether or not scientists are wrong on global warming, the European Union is pursuing the correct energy policies even if they lead to higher prices. -European Union Climate Commissioner Connie Hedegaard
The huge bureaucracy to implement the solution has already been decided upon. The actual problem, whether it exists or not is of no consequence and dwelling on such trivialities only delays implementation.
“pursuing the correct energy policies
even ifbecause they lead to higher prices. -European Union Climate Commissioner Connie Hedegaard ”…only that the EU is now running out of road… fast…
Higher prices is a means to the end. If you listen to the speeches at the United Nation IPCC/UNFCCC galas, the big talk is not about the environment or science. The environment and science are tools to implement the goal and the bureaucracy.
“This is the first time in the history of mankind that we are setting ourselves the task of intentionally, within a defined period of time to change the economic development model that has been reigning for at least 150 years…”
– UNFCCC Executive Secretary Christiana Figueres
The environment, Science or even Climate ‘science’ is a side show for this circus. If there are errors in the calculations they will be replaced by something else. It does not matter, the conclusion is predetermined. There are no ‘gotchas’ or silver bullets.
‘major errors of basic physics inherent in the so-called ‘state of the art’ climate models,’
sorry this does not matter one bit . becasue their ‘value’ has little relation to their scientific worth , their ‘value’ is in the support they offer to ‘the cause ‘ and the ‘impact’ they have in the press.
Nice picture
But why is there no Troposheric Water Vapour? Considering how much water vapour there is in the atmosphere I understood this to be a GHG? And work probably both positively and negatively.
Yeah. If you have water vapor in the model, it will completely wash out all the other factors. Which is why they left it out.
But reflected energy leaves the earth immediately!
And, reflected energy at low solar elevation angles is strongly dependent on solar elevation angles.
And, absorbed energy before the inbound short wave radiation even gets reflected (energy lost going through the atmosphere) is strongly dependent on the solar elevation angles as well.
So, they are calculated the basics of every albedo equation for every square meter of water on earth basically wrong.
Oh, and I see contrails get a mention, although the supposed effect seems to be about the same size as the ‘0’ reference line.
Whoops: climate modellers, already knowing the models are wrong since all models are, find their own errors and honestly publish them in primary literature. Why that is such a foreign concept for the proprietor — as well as so many denizens — of the “Best Science Website in the World” once again defies rational explanation.
Sorry, I musta missed something. Can you point me to the place where they say something to the effect of “we” found a problem with “our” models? I see some people studying OTHER people’s models and finding a problem with them. I don’t get the impression that these authors were themselves writing any of the models in CMIP5.
But feel free to edumacate me.
davidmhoffer,
Abstract from the present paper:
Abstract
Annual incident solar radiation at the top of atmosphere (TOA) should be independent of longitudes. However, in many Coupled Model Intercomparison Project phase 5 (CMIP5) models, we find that the incident radiation exhibited zonal oscillations, with up to 30 W/m2 of spurious variations. This feature can affect the interpretation of regional climate and diurnal variation of CMIP5 results. This oscillation is also found in the Community Earth System Model (CESM). We show that this feature is caused by temporal sampling errors in the calculation of the solar zenith angle. The sampling error can cause zonal oscillations of surface clear-sky net shortwave radiation of about 3 W/m2 when an hourly radiation time step is used, and 24 W/m2 when a 3-hour radiation time step is used.
Googling the lead author Linjiong Zhou yields a coupla’ hits, one of which is:
http://www.researchgate.net/publication/268821205_Global_energy_and_water_balance_Characteristics_from_finite-volume_atmospheric_model_of_the_IAPLASG_%28FAMIL1%29
ABSTRACT This paper documents version 1 of the Finite-volume Atmospheric Model of the IAP/LASG (FAMIL1), which has a flexible horizontal resolution up to a quarter of one degree. The model, currently running on the “Tianhe 1A” supercomputer, is the atmospheric component of the third-generation Flexible Global Ocean–Atmosphere–Land climate System model (FGOALS3) which will participate in the Coupled Model Intercomparison Project Phase 6 (CMIP6).
So yes, my read is: “we’ve found this spurious incident radiation problem in several current generation models” written by at least one person involved in writing the next generation models for CMIP6, and published in a reputable journal so that everyone working with CMIP5 knows there’s a potential issue, and that everyone working on CMIP6 is aware to not make the same mistake.
You were correct to ask for substantiation of my argument. I am happy to provide it.
davidmhoffer, PS:
From a preprint of the paper kindly chased down and provided by Lance Wallace upthread: https://dl.dropboxusercontent.com/u/75831381/zhou%20error%20in%20CMIP%20models%20solar%20zenith%20angle.pdf
The purpose of this short paper is to report this bias to inform users of CMIP5 results when interpreting the regional and diurnal variations of model results and to call for the attention of the relevant modeling groups to correct this bias in future simulations. We show that this unrealistic model behavior is caused by sampling errors in the radiation calculations, which are accounted for in some models but not in others. The impact of the bias on the simulation of atmospheric radiation and clouds is also presented.
Lance also notes that they found the problem in 8 current generation CMIP5 models:
Annual – mean incident solar radiation at TOA from 8 selected CMIP5 models is shown in Figure 1. In the figure, we amplified the color scale to highlight the spatial differences in the tropics . It is seen that the distributions of radiative flux in many models (bcc-csm1-1, BNU-ESM, CanAM4, CCSM4, CESM1-CAM5, EC-EARTH, inmcm4, NorESM1-M) exhibit longitudinal oscillations. The same type of biases was also reported in some climate model in AMIP-2 in the dezonalized anomalies plot [Raschke et al., 2005].
They also checked about 20 other CMIP5 models …
This variation would not be visible in zonally averaged plots or in spatial plots when the color scale has a large range. Other CMIP5 models are found to exhibit little or no zonal oscillations (ACCESS1-0, ACCESS1-3, CMCC-CM, CNRM-CM5, CSIRO-Mk3-6-0, FGOALS-g2, FGOALS-s2, GFDL-CM3, GFDL-HIRAM-C180, GISS-E2-R, HadGEM2-A, IPSL-CM5A-LR, IPSL-CM5A-MR, IPSL-CM5B-LR, MIROC5, MPI-ESM-LR, MPI-ESM-MR, MRI-AGCM3-2H, MRI-AGCM3-2S, MRI-CGCM3, see supplemental Figure S1 in the supporting document).
… and did not find the same error. Dunno what to tell you — that looks like good scientists doing what good scientists are supposed to do: identify error and communicate it so that everyone knows there’s a problem.
Dunno what to tell you — that looks like good scientists doing what good scientists are supposed to do: identify error and communicate it so that everyone knows there’s a problem.
= = = = = = = = = =
Brandon, don’t you mean “everyone except the general public“?
I can’t find any reports at the New York Times, Guardian, CNN, NBC, ABC, CBC, or any western media outlet (government or corporate), trying to inform their audience that “there’s a problem” with climate models.
Even the paper that claimed “snowfalls are now just a thing of the past” in 2000 has never revisited the issue to try to explain why they got it so horribly wrong.
http://www.metoffice.gov.uk/media/image/t/i/Satellite_UK_241210_mid.jpg
(UK, 2010)
But they did change their story in 2014 without batting an eyelid:
http://www.independent.co.uk/environment/climate-change/global-warming-will-make-our-winters-colder-9819825.html
Which “warming” model do you subscribe to: fire or ice?
Brandon Gates March 10, 2015 at 7:41 pm
Tx Brandon.
davidmhoffer, you’re welcome.
Khwarizmi,
Good point. I meant everyone who cares about such things to the point that they’d be looking for it, which does very likely preclude the majority of the general public.
Don’t you mean, “I think the models are garbage, and the fact that western media outlets don’t share my opinion is further evidence of massive fraud”?
That was the Guardian wasn’t it?
► I meant everyone who cares about such things to the point that they’d be looking for it, which does very likely preclude the majority of the general public.
The general public, without any question of consent, have to pay for all that pseudo-science that you care about so much. If it was question of consent, you could spend more time caring about the real world, instead of embarrassingly deficient toy versions of it that were specifically designed to freak you out.
► Don’t you mean, “I think the models are garbage, and the fact that western media outlets don’t share my opinion is further evidence of massive fraud”?
No, I don’t mean your version of what I said. I meant my version.
It is not mere opinion that the computer models of climate are “garbage,” as you put it. That’s why you can’t cite a single model that predicted the so-called “pause”, the expansion of Antarctic sea ice, or the record snowfalls in the northern hemisphere.
On the other hand, I can point to a pattern-matching model used by the United Nations Fisheries and Aquaculture Organization, that did successfully predict an end to “global warming” (their scare quotes, not mine), starting around 2005 with a shift to a dominance of a meridional circulation pattern:
http://www.fao.org/docrep/005/y2787e/y2787e03.htm
Incidentally, some climate scientologists and their followers today are peddling a new epicycle, in which that old meridional cooling pattern that we’ve been seeing of late is caused by “arctic amplification” shifting the jet stream, or some other ad hoc “garbage” that was made up on the spot today in order to explain away what you failed to predict yesterday:
http://www.washingtonpost.com/blogs/capital-weather-gang/wp/2014/02/20/scientists-dont-make-extreme-cold-centerpiece-of-global-warming-discussions/
I notice you didn’t answer my question about what model of global “warming” you subscribe to: fire or ice?
Thanks for the paper, Brandon, that’s a pretty basic error.
Khwarizmi,
I live in a republican democracy. YMMV.
It was sauce for the goose.
I don’t expect scientists to be omniscient, any more than the models they produce. Did your fish stocks model predict the expansion of Antarctic sea ice? Record snowfalls in the NH? Tide levels in New Jersey last week? The price of tea in China yesterday? I can do this all day.
Thing about models is: they’re always going to be wrong. How convenient for you.
The main objective of the study was to develop a predictive model based on the observable correlation between well-known climate indices and fish production, and forecast the dynamics of the main commercial fish stocks for 5–15 years ahead.
My emphasis. I’m not so sure you want to start talking about correlations.
It’s an intriguing theory – that recently has gotten legs: the melting Arctic – spurred by global warming – is causing the weather’s steering flow, the jet stream, to become more extreme … But more and more scientists are expressing reservations about this hypothesis, first proposed by Rutgers climate scientist Jennifer Francis and collaborators.
“It’s an interesting idea, but alternative observational analyses and simulations with climate models have not confirmed the hypothesis, and we do not view the theoretical arguments underlying it as compelling,” write five preeminent climate scientists (John Wallace, Isaac Held, David Thompson, Kevin Trenberth, and John Walsh) in a recent letter published in Science Magazine.
Elizabeth Barnes, an atmospheric scientists from Colorado State University, after an attempt to dismantle Francis’ theory last summer, published a second challenge in January.
“…the link between recent Arctic warming and increased Northern Hemisphere blocking is currently not supported by observations,” Barnes’ study concludes.
Your point?
Robert of Ottawa,
I can’t take credit, it was Lance’s doing upthread.
A feature is just a bug with seniority.
[You must use a legitimate email address to post here. ~mod.]
I am so glad that you have chosen to post here. Your comments are enlightening and very much appreciated.
Mr Gates the fact that models are wrong has been obvious for fifteen years, that is not the problem. The problem is that they have been used to spout fire and brimstone in a political manner causing untold expenditure on a non problem. Now we even have a pogrom against honest scientists in the run up to Paris this is why this fraud of climate models is so wrong. This is a religion for some in high places following these wrong climate models, they dictate to us on a fallacy.
wayne Job,
A non-problem yet.
If you’re talking about Grijalva’s fishing expedition, I think it was a stupid political stunt — typical opposition-party manuvering — and just plain wrong-headed. An across the board review would have been the better approach. Going after specific researchers set — no, reinforced — a bad precedent for academic freedom. All he’s done is strengthen the resolve of like-minded colleagues across his aisle
When someone cancels elections, I’ll complain with you about dictatorship. Worst I’ll go is democratic oligarchy. As for religion — what thread is this — oh yeah, scientists find an error in the models and publish it like they’re supposed to. You’re talking about politics by way of response. Funny how quickly the subject gets changed.
So, Brandon, if you’re so convinced of the honesty of your beloved warmist scientists, where are the announcements by the IPCC that all prognosis of a dangerously warmed world in 2100 must now be scrapped until a re-validation of the fixed model versions has taken place? (Which will take about 30 years)-
(Well I said re-validation, as if a validation of the buggy versions ever happened, but let’s play your “honest scientists” game here)
DirkH,
Not forthcoming any time soon according to my radar. CMIP6 is on the horizon after all. Why not scrapping the whole programme should be considered “dishonest” is a bizarre notion. If science, or indeed any human endeavor, were scrapped the first time it became apparrent that someone screwed up, we’d never get anything done.
I reiterate my view as first stated. The honest thing to do when identifying a mistake is to describe it in public so that others are aware of the error. I repeat my amazement that this is such a foreign concept so many people here.
Brandon;
as usual nothing but drivel.
“climate modellers, already knowing the models are wrong since all models are”
Funny isn’t how all the climate models are wrong in the same direction isn’t it.
Bob Boder,
Funny that you’re just repeating something you read somewhere without checking it. Much depends on how one determines “direction”. One way to do it is to take linear trends for each model over some period and compare that to observation over the same period. I did that for the first model member for each model from 1860-2014 and compared it to HADCRUT4. Exactly half of them are less than or equal to the HADCRUT4 trend, exactly half are greater. The overall ensemble IS biased hot, to the tune of 0.07 K/century.
An interesting article, but here’s the thing:
The models suffer from 2 fatal fundamental flaws (both of which were mentioned in the article).
1) The resolution is vastly too coarse to meaningfully model the circulation of air.
2) Some crucial phenomena are not even modeled, but instead are parameterized. And there is no way to know or demonstrate that the parameterization is correct. They can fiddle with the parameters to get the model output to match historical data over a given period of time, but that is really just a silly exercise, because there is no reason to believe that the time period they choose is any more representative than any other period.
My concern is that focusing on a particular error (such as the discussed error in the treatment of solar radiation) can give the impression that the models might be improved by fixing such errors. I prefer emphasizing that even if all such errors were fixed, the models’ intrinsic nature renders them incapable of providing information useful for the formulation of policy.
Yes, it is too soon to declare the models dead. If these relatively large variations are random in the model run, they may average out to some extent. A systematic error this large would have been obvious in the results.
IMHO the weakest link in the code are the assumptions of net positive feedback. This is very tricky, and a small error can make a very large difference. It is too tempting to adjust the feedback coefficients to obtain a “plausible” temperature increase over the next century.
And besides that, the story we are asked to believe is that we must keep our warming to less than 2 degrees, or disaster will ensue. Well, with positive feedbacks, and carbon dioxide supposedly resident for centuries, then are we not doomed in the next hundred years, even if we stay within the 2 degree budget for 2100?
I didn’t even know the CHIMP5 report was out!
This is a bit tangential, but I’ve always hated the use of the term “forcing” when it’s applied to phenomenon that don’t force anything in regard to the overall energy budget of Earth. To me, the only things that can correctly be called forcing are those things that add external energy into the climate system. These are few, and include electromagnetic energy from the sun and from space, atomic decay, and the energy from impacts. Those things are the only forcing factors. Everything else should be considered as buffering, which could further break down into storing and moving. Am I the only one who feels this way?
Boy , do I agree . Is this term forcing used in any other field ?
Let me see
dThis/dThatwithdThis/dThatgenerally proportional to the distance to some equilibrium . Forcings always sound like they are independent of how muchThisorThatthere is .Of course , I’m just an APL programer with some math and basic physics background .
This is also related to emissivity and absorptivity that apparently are not well understood by the modelers. The earth is not a black body and simply ‘estimating’ a number for absorptivity out of the air blows away any validity. aS (solar radiation at the ground) is not black body radiation – and varies with the elevation of the sun.
It has been some years since I looked at any model code, but when I did I found nothing to deal with the interplay of black body vs aS other than a fudge factor. .If one did real error analysis of the models, the true error bars would show exploding error bars as one goes into the future.
It also amazes me that so little is said about historical humidity numbers – that have changed as much as 50,000ppm. The huge increase in land under irrigation in the last 50 years apparently isn’t interesting to either side of the debate. The changes in humidity cause a real change in aS – a confounding variable.
All of the authors have appointments at Chinese institutions, as well as two affiliated with SUNY Stoney Brook.
Brandon – for the third time:
What model of global “warming” do you subscribe to?
Fire?
http://www.independent.co.uk/environment/snowfalls-are-now-just-a-thing-of-the-past-724017.html
or Ice?
http://www.independent.co.uk/environment/climate-change/global-warming-will-make-our-winters-colder-9819825.html
Please answer the question.
Khwarizmi,
I answered you already: neither. Certainly not in such absolute form as stated by the headlines, or by your contrived dichotomy. I subscribe to the view that predicting local weather years in advance is difficult and filled with uncertainty.
Actually is easy , in the winter it will get colder , in the summer warming and in the spring more rain.
Now predicting climate is much harder has show by the failure of your beloved models to do just that.
knr,
Climate is defined as the statistics of weather over some extended period of time. 30 years is common, but not set in stone.
Which do you think is “easier” to do?
1) Predicting the temperature in downtown Topeka exactly 30 years from today.
2) Predicting the 30 year mean temperature anomaly for the entire planet exactly 30 years from today.
First-year stats for dummies should inform your answer.
Contrary to your latest assertion, none of your previous replies included an answer to my question.
But thanks for at last furnishing an answer of sorts at 5.11pm, even if it provides no information about what kind of phenomena you would expect the real world to exhibit as a consequence of warming. That was clearly the point of my question; to find out if you would expect more ice and snow,as per The Independant in 2014, or less, as per The Independant in 2000.
I always expect warming, or heating, to produce less ice in the system, not more. You seem to think that the word “weather” means the answer must be “difficult and filled with uncertainty.”
So how long do you wait for the weather in your oven to clear before you have climate fit for cooking?
30 years?
► Thing about models is: they’re always going to be wrong. How convenient for you.
How inconvenient for you that the FAO pattern matching model was correct in predicting a meridional cooling pattern after 2005, while your agenda-ridden CO2-forced playthings got is so horribly wrong, as demonstrated repeatedly.
Khwarizmi,
Quoting the report again: The main objective of the study was to develop a predictive model based on the observable correlation between well-known climate indices and fish production, and forecast the dynamics of the main commercial fish stocks for 5–15 years ahead.
Since you subscribe models based on correlation, here’s 135 years of correlation between CO2 and temperature:
http://3.bp.blogspot.com/-fRV6ymzCb7A/VQCAQnsE63I/AAAAAAAAAYQ/SDw5lXjU4GA/s1600/CMIP5%2Bto%2BGISS%2BNov%2B2014%2B12mo%2BMA.png
A few weeks ago I watch a forecast of 1-3 inches of snow to come 5 days later, Sunday. When Sunday came, there was no snow at all. If two super weather computers can’t predict the weather 5 days ahead of time, how am I or anyone else going to begin to even remotely believe a computer generated prediction of climate 10, 20 or more years in advance?
“Why wasn’t this astonishing, large error of basic astrophysical calculations caught …”
Because the models were built to reinforce the hypothesis, not agree with observed data.
Just lucky then that none of the major models have this error, including:
ACCESS1-0, ACCESS1-3, CMCC-CM, CNRM-CM5, CSIRO-Mk3-6-0, FGOALS-g2, FGOALS-s2, GFDL-CM3, GFDL-HIRAM-C180, GISS-E2-R, HadGEM2-A, IPSL-CM5A-LR, IPSLCM5A-MR, IPSL-CM5B-LR, MIROC5, MPI-ESM-LR, MPI-ESM-MR, MRI-AGCM3-2H, MRI-AGCM3-2S, MRI-CGCM3
The only one that has the 30W error is a Russian one that no-ones heard of called inmcm4.