The Hockey Schtick brings this to our attention. It seems Dr. Roy Spencer was prescient with his observation:
“The most obvious way for warming to be caused naturally is for small, natural fluctuations in the circulation patterns of the atmosphere and ocean to result in a 1% or 2% decrease in global cloud cover. Clouds are the Earth’s sunshade, and if cloud cover changes for any reason, you have global warming — or global cooling.”
Readers might also recall that evidence has been found for Spencer’s 1-2% cloud fluctuation. Even the National Science Foundation recognizes the role of clouds is uncertain: NSF Releases Online, Multimedia Package Titled, “Clouds: The Wild Card of Climate Change”
WUWT readers may recall the recent paper by Suckling and Smith covered at WUWT: New paper: climate models short on ‘physics required for realistic simulation of the Earth system’
In the Suckling and Smith paper it was concluded that the models they reviewed just don’t have the physical processes of the dynamic and complex Earth captured yet. This paper by de Szoeke et al. published in the Journal of Climate finds that climate models grossly underestimate cooling of the Earth’s surface due to clouds by approximately 50%
According to the authors, “Coupled model intercomparison project (CMIP3) simulations of the climate of the 20th century show 40±20 W m−2 too little net cloud radiative cooling at the surface. Simulated clouds have correct radiative forcing when present, but models have ~50% too few clouds.“
Let that 40 watts/ square meter sink in a moment.
The 40 watts/ square meter underestimate of cooling from clouds is more than 10 times the alleged warming from a doubling of CO2 concentrations, which is said to be 3.7 watts/square meter according to the IPCC (AR4 Section 2.3.1)
So the cloud error in models is an order of magnitude greater than the forcing effect of Co2 claimed by the IPCC. That’s no small potatoes. The de Szoeke et al. paper also speaks to what Willis Eschenbach has been saying about clouds in the tropics.
Here is the paper:
Abstract:
Widespread stratocumulus clouds were observed on 9 transects from 7 research cruises to the southeastern tropical Pacific Ocean along 20°S, 75°-85°W in October-November 2001-2008. The nine transects sample a unique combination of synoptic and interannual variability affecting the clouds; their ensemble diagnoses longitude-vertical sections of the atmosphere, diurnal cycles of cloud properties and drizzle statistics, and the effect of stratocumulus clouds on surface radiation. Mean cloud fraction was 0.88 and 67% of 10-minute overhead cloud fraction observations were overcast. Clouds cleared in the afternoon (15 h local) to a minimum of fraction of 0.7. Precipitation radar found strong drizzle with reflectivity above 40 dBZ.
Cloud base heights rise with longitude from 1.0 km at 75°W to 1.2 km at 85°W in the mean, but the slope varies from cruise to cruise. Cloud base-lifting condensation level (CB-LCL) displacement, a measure of decoupling, increases westward. At night CB-LCL is 0-200 m, and increases 400 m from dawn to 16 h local time, before collapsing in the evening.
Despite zonal gradients in boundary layer and cloud vertical structure, surface radiation and cloud radiative forcing are relatively uniform in longitude. When present, clouds reduce solar radiation by 160 W m−2 and radiate 70 W m−2 more downward longwave radiation than clear skies. Coupled model intercomparison project (CMIP3) simulations of the climate of the 20th century show 40±20 W m−2 too little net cloud radiative cooling at the surface. Simulated clouds have correct radiative forcing when present, but models have ~50% too few clouds.
===============================================================
Given this order of magnitude blunder on clouds, it seems like an opportune time to plug Dr. Spencer’s book where he pointed out the 1-2% cloud forcing issue. Click to review and/or buy at Amazon.
Some most have forgotten to follow what’s known in real Science world….
Göran Frank, Experimental studies of the interaction of atmospheric aerosol particles with clouds and fogs, dissertation Lund University 2001, ISBN 91-7874-169-6
And here all this time I thought I was imagining that on those cloudy overcast nights it was not cooling off as much as on those bright cloudless evenings.
Yes, changes in cloud cover are the main cause of short-term fluctuations in global temperature. See Monckton of Brenchley (2010), Global brightening and climate sensitivity, Annual Proceedings, World Federation of Scientists. From 1983-2001 the naturally-occurring reduction in cloud cover possibly linked to the positive phase of the Pacific Decadal Oscillation caused close to 3 Watts per square meter of radiative forcing (the entire anthropogenic ghg forcing since 1750 was less than that). Late in 2001, according to the ISCCP dataset, the cloud cover returned to normal and there has been no global warming since.
Good point Rob, as well on warm, sunny day’s cloud’s move in and temps drop 10 degrees or more…also at CERN , new experiments have shown that the recent collapse of the solar winds allows more cosmic rays to penetrate our atmosphere and INCREASE cloud cover, therefore more cooling ahead
As all WUWT readers should know, it is not really about the science, it is about the conclusion and the unpalatable manipulations that can be achieved via these conclusions. All the “studies” that get trotted out are like the pathetic excuses habitual liars use to deflect attention from arguing the actual issue. Wait for the brush off. The liars behind the scenes will not want any attention for this article, so they will come out with another round of baseless BS as a diversion.
Bottom line- climate and weather are so complicated that we are unlikely to understand more than 40% of it. Claiming the science is settled is BS in the extreme. Really, the whole box of theories must be taken back to the drawing board since it is very clear the model MUST be incomplete as a parameter is missing.
Coming to a conclusion knowing important parameters have been omitted is scientific fraud.
“The 40 watts/ square meter underestimate of cooling from clouds …” — OP
So if the models were actually based on physics, and our best understanding of the inputs, they’d have been projecting that we’re well into the next ice age and need to step up coal burning exercises to stave off the encroaching glaciers.
Well, thank goodness for models based on physics. >_>
Clouds are just one of the components coupled into the neverending chicken-egg tail-chase. Getting a grip on constraints demands a broader perspective.
Henrik Svensmark’s The Chilling Stars suggests, IIRC, that similar increase in maritime stratus clouds would be enough change warming to cooling.
Lotsa of ways to say CO2 isn’t the demon gas some make it out to be.
A similar issue is the method of estimation of ocean reflectance/absorbtivity within climate models. Reflectance of sunlight is a complex phenomenon and is dependent on zenith angle, wind temperature, density, humidity, velocity and direction, and ocean surface tension, viscosity, salinity, and plankton content, I doubt that any factor other than zenith angle is used by the models. Anyone know?
“When present, clouds reduce solar radiation by 160 W m−2 and radiate 70 W m−2 more downward longwave radiation than clear skies, “.
The first part of the sentence makes sense, but it is hard to understand how either clouds or clear skies at a lower temperature than the surface or the atmosphere below can radiate anything downward..
[i]Let that 40 watts/ square meter sink in a moment.[/i]
I’m having trouble comprehending that figure. Could somebody convert it into Hiroshimas for me please?
“Let that 40 watts/ square meter sink in a moment.”
But with a little bit of thought. They are talking about a specific area. 20 °S and 10 ° of longitude. Just 7 cruises – we don’t know what time of year.
And the 40 W/m2 is an instantaneous variation in surface radiation balance. It isn’t loss to the planet, else we’d certainly have an ice age. There may be some extra albedo. But overall, the difference would mostly add to the large component of SW thermalized in the air rather than at the surface.
“When present, clouds reduce solar radiation by 160 W m-2 and radiate 70 W m-2 more downward longwave radiation than clear skies.”
This is an odd statement, when you think about it. Clouds come in all shapes and sizes. Insolation varies a lot during the year. But no distribution quoted?
It has been obvious from the get-go that anthropogenic CO2 was not an important factor (if one at all) in explaining the changing climate on planet earth. It is nice to see that a few hardy men and women are still willing to practice science in spite of all the money and accolades flowing to those practicing mindless myth-making.
Very good article today. Thanks Anthony.
“we don’t know what time of year”
I see I was wrong there; the cruises were always in about November. An even narrower range of observations.
The paper is available here. They are basically trying to explain a known local SST discrepancy between models and measured SST. Models are known to overestimate in this particular region.
Nick Stokes
Models are known to overestimate in this particular region.
Any other known errors in the models, it’s only a model after all?
well they are consistent, pretty much everything the Team(TM IPCC) does biases the models high.
No highly alarming preprogrammed results results in no more funding.
Science was never more than a cloak for their naked ambition.
David, UK says:
November 29, 2013 at 1:21 pm
[i]Let that 40 watts/ square meter sink in a moment.[/i]
I’m having trouble comprehending that figure. Could somebody convert it into Hiroshimas for me please?
But of course….
It’s approximately 0.0000000000000000000000032128% of a Hiroshima per metre square per calender month. Approximately.
Henceforth to be annotated as Hiro’s.
I hope I have been of assistance..Have a nice day.
Dr Evil
Because of vertical structure and slant range cloud shadows cover more surface area than their footprint might suggest and because they move, they cannot be considered to be near the source of heat that created them.
But.. But… Energy budget! blah blah blah… Models show! blah blah blah… Tree rings! blah blah blah…
/ sarc
When, for example, a paper calculates that “0.5 +/- 0.2K out of the observed 0.6 +/- 0.2K global warming” over the past century comes from natural solar/GCR variation (Shaviv 2005), the primary observed mechanism is variation in cloud cover (and actually also in average cloud heights though with that usually less discussed).
Variation in albedo (including clouds) is the prime driver of changes in Earth’s climate on most relevant timescales.
Variation in cloud cover, temperature, glacial extent, cosmic ray flux, solar activity, and more all tie together for timeframes from recent decades to data centuries back, as illustrated in http://img176.imagevenue.com/img.php?image=81829_expanded_overview_122_424lo.jpg
But once that is seen, there is nothing left for CAGW to stand on.
Like the enormous tens of percent increase in plant productivity and water usage efficiency in going from pre-industrial to future levels of CO2, the large overall net cooling effect of white clouds is among the facts very deliberately not publicized by activists.
“Given this order of magnitude blunder on clouds, it seems like an opportune time to plug Dr. Spencer’s book where he pointed out the 1-2% cloud forcing issue.”
Indeed. And another publication of Dr. Spencer is also relevant:
http://www.drroyspencer.com/2011/05/indirect-solar-forcing-of-climate-by-galactic-cosmic-rays-an-observational-estimate/
When Dr. Spencer’s analysis of cloud variation under cosmic ray influence leads to him remarking:
“The results suggest that the total (direct + indirect) solar forcing is at least 3.5 times stronger than that due to changing solar irradiance alone”
… that is a ratio fitting the results of others like Dr. Shaviv and, for instance, a Dergachev et al 2004 paper which noted “Svensmark [1998] proved that a temperature change produced by the GCR effect on the clouds from 1975 to 1989 was 3-5 times greater than the temperature change caused by changes in the total solar irradiation.”
The next group who get the low bid U.N. contract to study Global Warming aka Climate Change aka CO2 kills should be required to do all the work out doors with no heating or cooling of the people involved in the data gathering. Seems that it is/would be important that this be done considering these prior did not get much real world experience while on the job. Junk in, junk out.
Sort of a control of the control group.
Thanks Nick,
It gets weary pointing out the obvious. 40 watts, 40 watts, 40 watts, is all they read and jump to conclusions. not very skeptical this crowd.. well selectively skeptical.
When the models are improved they will complain that the models are being fixed.
Something else new: 11/28/2013
Atlantic Meridional Overturning Circulation slowdown cooled the subtropical ocean
http://onlinelibrary.wiley.com/doi/10.1002/2013GL058464/abstract
Steven Mosher says:
November 29, 2013 at 2:54 pm
Thanks Nick,
It gets weary pointing out the obvious. 40 watts, 40 watts, 40 watts, is all they read and jump to conclusions. not very skeptical this crowd.. well selectively skeptical.
When the models are improved they will complain that the models are being fixed
==============================================================
Well, you didn’t disappoint.
What are chances the models will correctly reflect the clouds in the near future?
@ Steven Mosher says:
November 29, 2013 at 2:54 pm
The fact is the models were wrong. And those models were used to push an agenda which at the very least has lead to bad policies and a great waste of money, effort and time throughout the world – not to mention crashing some careers [for speaking out] along the way.
Statements like this “When the models are improved they will complain that the models are being fixed.” are both arrogant and misleading. Based on what has transpired, people have an inherent right to be skeptical of the credibility of any who attached themselves to this magnificent failed theory called CAGW.
It’s my belief the main driver for climate change is the difference in temperature of the ELECTRON in the troposphere paticals float around in a sea of electrons Look into the fairweather and foul weather electric fields and how they work in oposite direction . This process drives high and low pressure systems.Now wrap this process around Coulomb’s Law
I still suspect that a lot of the believed water vapor feedback is based on the change during the Pinatubo cooling, which I think ignored the effect of decreased direct SW radiation on water and moist surfaces (e.g. soil).
@Nick Stokes: “They are basically trying to explain a known local SST discrepancy between models and measured SST. Models are known to overestimate in this particular region.”
Ah, good then. Since it’s a known bad value they can correct it like TOBS, right?
Simulated clouds have correct radiative forcing when present, but models have ~50% too few clouds. — Right there in the OP
So yeh, yet another empty sophistry on your part. Don’t get me wrong, I deeply appreciate that your statements are so consistently false in a backwards fashion. It’s a good signpost to where the truth lies.
I think we should also acknowledge Willis’ work at the “small scale” of individual thunderstorms and how in aggregate they regulate temperature over the ocean.
Jquip says: November 29, 2013 at 3:34 pm
“Since it’s a known bad value they can correct it like TOBS, right?”
That’s not what they are doing. You should read the paper. It begins:
“Accurate simulation of tropical southeastern Pacific Ocean sea surface temperature (SST) is challenging for coupled general circulation models (GCMs; Mechoso et al. 1995; Davey et al. 2002; de Szoeke and Xie 2008). Warm errors of 2°C in SST are found at 20°S, 75°W in most of the Coupled Model Intercomparison Project phase 3 (CMIP3) models assessed by de Szoeke et al. (2010).”
So they made observations to find out, and ascertained that in that transect, in November, models are underestimating observed cloud.
Isn’t this how science should proceed?
Teddi says: “Statements like this “When the models are improved they will complain that the models are being fixed.” are both arrogant and misleading. Based on what has transpired, people have an inherent right to be skeptical of the credibility of any who attached themselves to this magnificent failed theory called CAGW.”
Sort of like being skeptical of cars because model T’s were so lame. But, at the time, they were the best that we had.
I would like to thank Steven Mosher for reminding me how stupid I am while doing nothing to educate me. I would also like to thank Pippen, who makes me even more stupider just from reedng wut him dun sed.
Paul Vaughan
Thank you for the excellent link to Sidorenkov. It will take some time to read and understand it all, but it is a remarkable reference.
I can almost hear http://en.wikipedia.org/wiki/Slartibartfast saying: “Climate models don’t do clouds|”.
Pippen Kool says:
“Sort of like being skeptical of cars because model T’s were so lame. But, at the time, they were the best that we had.”
Argument by analogy is almost always a waste of breath but that’s just cretinous.
CliSci—Good enough for government work.
Sort of like being skeptical of cars because model T’s were so lame. But, at the time, they were the best that we had.
Great analogy. My Grandmother was always complaining that the Model T took their family to the butcher’s, rather than the baker’s on the next block.
After reading here for some time, like from 2006 or so can not remember for sure. Do post some.
Got an EE degree back in the 1960’s and it was not easy at all then. Used it all the way to the research and development operation at GD Ft. Worth Tx. on the F-111 terrain following radar.
Any how lots of info here and there are lots of good facts now on the net for all to see. This information and the East Anglia University together I am sure have reached Pres. Obama and the decision makers in the White House Executive part of the U.S. Government. Therefore I am sure as you all should be that they will do the right thing and follow the facts known by all who truly want to know.
We can rest easy tonight and in the days ahead knowing they will not follow the mis-information
from the likes of Michael Mann eta that will only cause great harm to our country and most of humanity world wide.
Lets all just get along and let one another feel good and let our emotions rule us all.
Sweet dreams, nite nite
(sarc)
As Spencer says, a few percentage of cloud cover change can cause climate changes of the magnitude of the observation via an albedo change.
See Figure 19 in
Scafetta, N. 2013. Discussion on climate oscillations: CMIP5 general circulation models versus a semi-empirical harmonic model based on astronomical cycles. Earth-Science Reviews 126, 321-357.
http://www.sciencedirect.com/science/article/pii/S0012825213001402
where it is observed a very good correction between the global surface temperature against variations in total global cloud cover since July 1983 (P(|r| ≥ |ro|) b 0.0005. The cloud data are from the International Satellite Cloud Climatology Project (ISCCP)).
Figure 20 of the same paper shows a comparison with the cosmic ray index.
Who knew shade was cooler?
We don’t understand clouds so the models are an order of magnitude off. The “best minds” of climate science have resolved the energy balance to 0.6 +/- 17 watts/m^2, and discuss it as a “budget”. In most disciplines and my years in chemical processes an order of magnitude uncertainty would negate the model I’m using. The uncertainty in the energy balance would be 0 in any process model/estimate I’ve ever been around. If I had ever proposed expensive changes based on schlock like that all I’d hear was the laughter as I started with my new employment with the State Employment Security Commission.
If I were a real scientist studying climate, I’d really be upset at by the charlatans who claim to be climate scientists and use stuff like this.
In IPCC’s AR reports, these scoundrels freely admit Climate models don’t model clouds well at all… (accidentally on purpose…)
Under any interpretation of the Scientific Method, CAGW already deserves to be thrown on the trash heap of failed hypotheses, with NO RSS warming trend since October 1996– despite 1/3rd of ALL manmade CO2 emissions since 1750 made over the last 17 years…
This, umm, cloud “misunderstanding” is the IPPC’s get-out-of-jail-free card, which “scientists” will play to the hilt when this CAGW scam crashes and burns within the next 5 years and they’re testifying in front of Parliamentary and Congressional CAGW hearings explaining how they could have been so wrong for so many years about this CAGW scam.
Joni Mitchell had our knowledge of clouds down pat.
http://songmeanings.com/songs/view/25181/
dalyplanet (November 29, 2013 at 4:12 pm) wrote:
“Thank you for the excellent link to Sidorenkov. It will take some time to read and understand it all, but it is a remarkable reference.”
You’re very welcome. It’s a very refreshing read.
It gives background for interpreting Dickey & Keppenne‘s (NASA JPL 1997) figure 3a&b, which has simple consequences.
Regards
Pippin really? That has to be the most disconnected analogy I ever….
So the warming anomaly, already carefully and egregiously overstated, is also swamped by major omissions and error sources in the models.
What could go wrong?
@ Mosher.
Uh … the Models are “fixed”. 😃
r murphy says:
“Pippin really? That has to be the most disconnected analogy I ever…”
Agreed, that is a really bad analogy.
Why?
Because models are not a hundred years old like a Model T; they are current, and extremely expensive, and they are still completely wrong!
After wasting more than a $BILLION every year since 2001 on these worthless models, they should either perform, or be trashed.
GCMs are always wrong for one simple reason: they are programmed with the assumption that CO2 causes rising temperatures, when in reality, it is ∆T that causes ∆CO2.
Start with a wrong assumption, and the conclusion is bound to be wrong.
dbstealey says: November 29, 2013 at 8:28 pm
“GCMs are always wrong for one simple reason: they are programmed with the assumption that CO2 causes rising temperatures, when in reality, it is ΔT that causes ΔCO2.”
You have no idea how they are programmed. No such assumption is made.
“Isn’t this how science should proceed?”
[Nick Stokes says: November 29, 2013 at 3:56 pm]
Indeed. Scientists, especially those pushing CAGW, should admit the “challenging” nature of the subject and explain to all the activist policy makers that clarity has not yet been achieved. Please spare us this sort of statement:
““ There is now, he said, “much more clarity.” It “is a scientific finding” that climate change is humanity’s fault. ”” [Ban Ki-moon, 2013, Warsaw]
See post here:
http://nofrakkingconsensus.com/2013/11/29/un-climate-fanatics/
Likening the model T to climate models is lame, a better comparison would be if Henry Ford had insisted against all evidence, prior to manufacture, that the model T would fly, operate under water and never be in an accident.
The models are fixed; this is the problem, a computer model does what the programmer instructs it to do, any programmer who pretends otherwise might need a new career.
Current climate models predict the future climate as well as scrying the future by studying the guts of small animals.
Nick Stokes;
You have no idea how they are programmed. No such assumption is made.
>>>>>>>>>>>>
ROFLMAO
Go ahead Nick. Explain how models don’t attribute increased forcing, an increased ERL, and increased surface temps to increasing CO2. Go ahead. Explain.
Real science should proceed. Political science should not be recognized as “Real science”.
davidmhoffer says: November 29, 2013 at 9:16 pm
“Explain how models don’t attribute increased forcing, an increased ERL, and increased surface temps to increasing CO2.”
I thought you might have some idea of how they are programmed, but apparently not. Models don’t attribute forcing to anything. They are supplied forcing as data. In the case of CO2, it enters as a GHG into the radiative model. There’s no assumption in the programming about how it affects surface temps. There’s only the measured absorption spectrum, which goes back 150 years to Tyndall.
I think it’s time for loudmouth experts on GCM programming to point to the part of a GCM program where such an assumption is made.
Nick Stokes;
In the case of CO2, it enters as a GHG into the radiative model. There’s no assumption in the programming about how it affects surface temps
>>>>>>>>>>>>>>>>>>
You’re playing with words. Technically what you said is correct. The assumptions made however, about how the radiative properties of CO2 play out in the system as a whole, result in increased surface temps. Just because this is arrived at via thousands of calculations attempting to model all the atmospheric processes rather than a direct calculation changes nothing. Pick any set of SRES scenarios you wish, and any model you wish, and the higher the CO2, the higher the temps the model will calculate based on the assumptions built into the system as a whole. Saying otherwise is just silly.
I can believe Nick or I can believe the model results vs observed. Can’t believe both. Sorry, Nick – no room in the tent for faith-based warming.
AR4, Chapter 8 (Models and their evaluation) was very explicit: they acknowledged a poor understanding of clouds. It was at that moment that I suspected that all the stuff in the Summary for Policymakers was completely politically driven, unconnected to the science. This was confirmed by their further admission in Chapter 8 that the team did not have any idea how to evaluate a particular model for accuracy. My jaw hit the floor. I went back and re-read the SPM to see if there was any acknowledgement of the serious weakness of the models–there wasn’t any. That day, I lost all respect for the IPCC process.
For every future futuristic view from the models, we can all chorus
“only if the changing cloud cover doesn’t change.”
Nick Stokes says:
November 29, 2013 at 8:50 pm
You have no idea how they are programmed.
==========
they are programmed to predict what the model builders believe the future looks like. and when the models get the prediction wrong, the model builders change the model until the model gives the correct answer.
and how does the model builder know when the model has given the correct answer? when the model delivers the prediction the model builder believes to be correct for the future.
because if the models had predicted temperatures were going to flat-line in 2000, all the model builders would have seen this as an error, and would have adjusted the models until they showed rising temperatures.
that is why the models are hopeless at predicting the future. if the models actually showed us the future, unless that future was exactly what the model builders expected to see, they would assume the model was in error and needed to be fixed. and fix it they would, until it finally gave the “correct” answer.
Nick Stokes;
I think it’s time for loudmouth experts on GCM programming to point to the part of a GCM program where such an assumption is made.
>>>>>>>>>>>>>>>
And I think it is time for people like YOU to stop issuing such challenges. If you can produce a single model that produces anything BUT higher temperatures in response to higher CO2, then your argument would be substantiated. Not to mention that the WUWT readership would be giddy. As for pointing out WHERE in the models this assumption is made, you know well that’s a fool’s errand as the assumptions don’t exist in any once single place. In fact, tracing out all the pieces of code that wind up delivering an end result of higher temps for higher CO2 is near impossible for any single person to do. I think you know this very well. I reproduce below a comment from Dr Robert Brown from a a few threads ago which lays out the challenge and exposes your little trick for what it is. But bottom line is that we don’t need to perform the analysis you demand to prove dbstealey’s assertion. All we need do is run the models with different levels of CO2 of any of them, ANY of them, produce ANYTHING other than higher temps for higher CO2. Here is Dr Brown’s comment:
>>>>>>>>>>>
GCMs without any question contain all sorts of information on pressure, density, and temperature of the air parcels they manipulate. If you are interested in seeing what goes on in at least on GCM, there is an open source on (CAM 3) with online documentation here:
http://www.cesm.ucar.edu/models/atm-cam/docs/description/
This is not one of the most detailed GCMs, but it is one where you can download the actual source and look at it, with program documentation in hand on the side. One can fault the design (one can ALWAYS fault a design:-) in a number of places, but the assertion that they don’t handle elementary parameters like pressure, density, and temperature is simply not correct. Indeed, to fault this one has to get pretty specific — point to a particular place in section 4 where they do something wrong. The top article basically suggests that there may well be something seriously wrong in CAM 3′s (and other GCMs’) treatments of aerosols, cloud formation, and vertical transport based on actual measurements. I suggest equally specifically that there may be something wrong with using a discrete latitude/longitude grid, especially with comparatively weak or missing adaptivity (CAM 3 actually has a tiny bit of adaptivity in it to handle polar regions better) for the specific reason that radiation rates on thermally averaged cells will be strict lower bounds — not upper bounds — on the true rate, so that CAM 3 and any other GCM that assigns a single temperature to a comparatively large horizontal area (in any given slab or layer) will underestimate the cooling via the unblocked channels and underestimate the rate of radiative energy transport between slabs in the blocked layers (basically, overestimating the “radiative insulation” properties of any given slab) because more uniform temperatures lead to more warming with exactly the same insolation at all scales.
This is the game, if one wants to criticize the GCMs. One can perfectly legitimately point out that they aren’t working without specifying why, as that is a posterior conclusion based on comparison of their predictions and the actual data, but if one wishes to assert that they aren’t working for a specific reason, to be responsible one has to look at the actual code and see if the specific reason you suggest is implemented in the actual code in a way that is (or more properly, may be for some evidence-supported reason) incorrect. So it isn’t that GCMs don’t include the effects of latent heat transport — they obviously do (see “shallow/middle troposphere moist convection” in the CAM 3 documentation, for example). It MIGHT be that they don’t include it CORRECTLY.
It is an open question as to whether or not they are leaving some physics out entirely that ends up being important. The galactic cosmic ray hypothesis, for example, has some empirical support but it is so far not a slam dunk or sufficiently compelling to warrant inclusion in a model on anything other than a trial basis. It would actually be interesting to include it ON a trial basis — one can always insert provisional physics into a model just to test the model and see if it does better with it or without it, or if it gives the model additional explanatory power. This is itself a form of weak evidence, if it does. In a highly multivariate model, however, it is probably WEAK evidence because model predictions, especially of single outputs, are very probably highly covariate in the physical parameters, so that one can turn up CO_2 sensitivity and turn up the effect of aerosols at the same time and maintain good agreement with GASTA across some training set, but end up with highly disparate long-term predictions as eventually CO_2 continues increasing but aerosols don’t.
I suspect that it is this alone that is largely responsible for much of the error in the GCMs relative to the present — they’ve systematically exaggerated CO_2 sensitivity and maintained agreement with data across the 50′s through the 90′s by asserting a larger effect to pollution and volcanic aerosols, but as we moved past the fit region and CO_2 continued up with aerosols not increasing to match (and with volcanism if anything a bit diminished) the highest senstivity models have started to systematically diverge from the observed temperatures.
Is this indeed the explanation? Hard to say. There need not be ONE explanation. There is no doubt that GCMs contain both positive and negative forcing terms and achieve agreement by balancing them. There is little doubt that they assign quite different values to the effect of aerosols as there is no consensus value or model (and the top article shows how nonlinear any model must be to correctly account for all of the observable physics!) The sad truth is that while there is only one way for a program to be right there are countless ways for it to be wrong. Once a program has the complexity of something like CAM 3, not only are there countless ways for it to be wrong but they get to where no single human knows the entire code and few humans are willing to take even a major component of that code and monkey with it as you have to START by learning it all. It gets to be very “expensive” to make changes — one can spend most of a postdoctoral position just getting to understand what the existing code does and have little time to even THINK of making serious changes, retraining the code parameters, and then spending two years of CPU time running the program all over again to see if the changes don’t egregiously break the existing code and (perhaps) lead to some improvement.
I’ve downloaded and looked over the CAM 3 code. Sadly, however good or bad the code itself may be, the packaging of the code truly sucks. It would be a matter of weeks of work (for me) just to get it to BUILD, lest alone build and run on some small test program, and I’m a pretty damn good programmer (although I do hate Fortran, sigh:-). It just isn’t worth it — I have no grant for working on climate (so it is by definition a “hobby”, not a profession), I’m not getting paid to do it, I am getting paid to do a lot of other stuff that is very time consuming and have lots of other hobbies/projects that languish for lack of work on my part.
Porting a rather large Fortran program to C, organizing it so that it will automagically build across a range of platforms in both parallel and serial versions, replacing the lat/long tessellation with a scalable icosahedral tesselation, determining the granulation error in radiative transfer rates as a function of scale and estimates of per-cell spatiotemporal noise, correcting the aerosol, cloud, and vertical transport component (or somehow parameterizing it so that one can experiment with different rates based on empirical evidence as it comes in), adding an “optional” (parametric) component for GCR-modulated cloud nucleation rates, transforming the initialization data from lat/long to the icosahedral grid, fixing the single-slab ocean model to account for oceanic transport and more, better, figuring out how to correctly include projections of solar state (out as far as such projections themselves have some reasonable chance to be right) — I could spend the rest of my life working on this WITH A TEAM and a million dollars a year in grant money. A bit much too tackle for free and if I want to have a life of some sort on the side.
rgb
and how did the model builders know that the models were wrong to predict temperatures were going to flat-line in 2000, and therefore needed to be fixed? because CO2 levels were increasing and thus temperatures could not flat-line.
thus, the models were programmed to predict that rising CO2 levels would lead to rising temperatures, because that was the expectation of the model builders. formally this is known as the experimenter expectation effect.
unless experiments are designed very carefully, the experimenter always finds what they are looking for, because they search until they find the effect, and then stop searching. and by allowing the models to be adjustable, the act of adjustment is a form of search.
the model builders are searching for the correct parametric adjustment so that the models shows the future exactly what they believe it should show, which they use as confirmation to themselves that the model is adjusted correctly.
In a highly multivariate model…and the top article shows how nonlinear any model must be
=============
non-linear multivariate time series analysis as climate models are attempting to perform is beyond the ability of modern mathematics to solve by numerical methods, except in trivial cases. the non-linearity of the problem ensures that round off errors quickly overwhelm the solution, leading to a nonsense result.
the notion that model errors will “even out” over time, such that climate models will be more accurate the longer the forecast horizon, is a fundamental mathematical error. a misapplication of statistics. an example of why this does not work for forecasting the future is the inertial guidance system, as widely used before GPS.
An inertial guidance system predicts the future position of the vehicle based on sensor readings of various forcings and feedbacks. This prediction for the future is then fed into the vehicle steering controls such that the vehicle will maintain it future course. However, no matter how precise you make the system, it will drift.
The errors left and right of course, even though they are random and should by the law of large numbers even out to zero over time, in fact do not average out. The vehicle drifts off course, sometimes to the left, sometimes to the right, and the longer the vehicle stays on inertial guidance, the more likely it is to be off course.
This is completely contrary to the basic beliefs of climate modelling, that the model errors will cancel out over time, making long term forecast more accurate. Inertial guidance systems demonstrate that the problem is fundamental. you can reduce the error by making the equipment more precise, but no matter what you do, the error increases with time. the models will drift.
In local forecasts the mets talk about how relative humidity, cloud cover (or winter snow cover) and the sun will affect the next day’s local weather. I really don’t see how it’s such a revelation that it’s any different on a global scale. (Not once have I heard a local met discuss CO2 conditions as a factor.)
Martin Hertzberg says:
November 29, 2013 at 1:20 pm
“it is hard to understand how either clouds or clear skies at a lower temperature than the surface or the atmosphere below can radiate anything downward..”
Perhaps you are thinking of the 2nd law of thermodynamics, which is often described by “heat always flows from warmer objects to colder objects”. This is actually a simplification. A slightly better description (still not the best) is “Net heat flow is always from warmer objects to colder objects and rate of net heat flow is directly proportional to the temperature difference.”
Matter always radiates heat at a rate corresponding to its temperature. If the first description of the 2nd law was valid, a red dwarf star near a hotter yellow G star would have to cease radiating on the side toward the G star, or the G star would have to turn away the energy being radiated in its direction by the red dwarf. In actuality, the red dwarf radiates energy in all directions, some of which strikes the G star. Simultaneously, the G star is radiating a far greater amount of energy in all directions, some of which strikes the red dwarf. Since energy from the G star striking the red dwarf exceeds the energy from the red dwarf striking the G star, net heat flow is from the G star to the red dwarf.
In the case of a cloud overhead, the cloud is radiating in all directions, at a rate determined by its temperature, even towards the warmer ground below. Simultaneously, the ground is radiating at a rate determined by its temperature. Net heat flow is still from ground to cloud. The ground temperature drops at a rate determined by the difference in rate of heat flow from ground to cloud versus the lesser cloud to ground rate.
Since clouds are usually warmer than clear air due to heat of condensation, and because water absorbs IR strongly (mostly coming from the ground below), the ground receives more radiated heat from a cloudy sky than from clear air. This is why the temperature drops quicker on a clear night than on a cloudy night, even though the clouds are colder than the ground. This is as close as we can come to a real world green house effect.
Consider also that clouds could not be keeping the ground warmer (than it would be in their absence) by reducing either convective heat loss or conductive heat loss by the ground.
SR
dbsteely says: “Because models are not a hundred years old like a Model T; they are current, and extremely expensive, and they are still completely wrong!”
Stupid #1. Sorry. You, and many others here, are wrong. The models are getting better, each year, just like cars did, or spaceships did, or computers did. It’s the way that scienceny stuff works, and if you don’t like it, get over it. If you don’t understand the changes, either listen to those that do or go to school.
Stupid #2: “GCMs are always wrong for one simple reason: they are programmed with the assumption that CO2 causes rising temperatures, when in reality, it is ∆T that causes ∆CO2.”
Wow. You are living in your own little imaginary bubble land. Enjoy yourself and be happy.
!!! pop !!!
Nick Stokes’ world (and modeling career) is falling apart. At the end of the day it’s observations compared to “what if”, scenarios, story lines, projections, predictions that matter. So far 95% of the models are failing, and failing badly. If this carries on much longer the referee will have to blow the final whistle.
Nick, what will it take for your to re-assess AGW as stated by the IPCC AR5 on global surface temperatures? That is how science works as you say.
They are getting ‘better’ because they are coming down to the sceptics’ point of view – lower climate sensitivity. And you are right that is how science works, OBSERVATIONS. Thanks for coming over to the sceptic side.
Abstract
Between these conflicting tendencies, 12 projections show drier annual conditions by the 2060s and 13 show wetter. These results are obtained from sixteen global general circulation models downscaled with different combinations of dynamical methods……
http://journals.ametsoc.org/doi/abs/10.1175/JCLI-D-12-00766.1
Steve Reddish says:
“Perhaps you are thinking of the 2nd law of thermodynamics, which is often described by “heat always flows from warmer objects to colder objects”. This is actually a simplification. A slightly better description (still not the best) is “Net heat flow is always from warmer objects to colder objects and rate of net heat flow is directly proportional to the temperature difference.”
Yes ‘better ‘ would be to avoid calling radiation …..heat.
Electromagnetic radiation energy is correct.
Heat can be transformed into thermodynamic work so cooler to hotter radiation is not heat.
Generalized statements about the second law sometimes require further clarification for particular circumstances.
Take today’s local weather
Air temperature about 4C
Ground temperature about -2C
Sun not ‘up’ yet.
The local ground temperature will continue to drop despite the higher air temperature.
The ground being much more dense will radiate a much higher continuous flux than the downward thin radiative flux of the warmer air.
The spectral flux of the air has many gaps particularly around the atmospheric window of 10um.
The energy gain of the surface from conductive interaction with the air is insufficient to make much difference.
Net result is heat loss by land surface is greater than energy gain from atmosphere.
Mosher seems to consistently argue that the “science is not settled” and scientists are working constantly to improve their models and understanding. At least that is my understanding of his comments.
If so, good on him.
The fact that GCM’s don’t “do clouds” , but that clouds are an important variable has been know for a long time. I first became aware of this from a February, 1993, article in “R&D Magazine” titled “Climate Researchers Look to the Clouds.” That was 20 years ago, and only 5 years after Hansen’s 1988 paper.
A couple of quotes from that article:
“Satellite measurements have found that the actual-as opposed to modeled- net effect of clouds in the present climate is to cool the planet. The Earth Radiation Budget Experiment recorded, in April 1985, both SW and LW effects of clouds.
That month an average of 342 W/m^2 shone on the earth in the form of SW radiation- also know as sunlight. Clouds reflected about 45 W/m^2 of this energy, while trapping 31 W/m^2 in the form of LW radiation.”
and:
“All of these facts have led Veerabhadran Ramanathan, of the Scripps Institution of Oceanography, La Jolla, CA, to suggest that cirrus anvils might ‘act like a thermostat” over tropical oceans to arrest warming.”
I doubt that Willis had heard of Dr. Ramanathan when he proposed the something similar.
There are fundamental philosophical problems with modelling, that need attention:
“Everything simple is false. Everything which is complex is unusable.” (Paul Valéry)
The diminishing returns of map making were discovered long ago:
“We now use the country itself, as its own map, and I assure you it does nearly as well.” (Lewis Carroll)
No genuine scientific theory can hang its hat on a model. Claiming that we will understand the science of something when we can model it, is absurd. We might model it perfectly but not understand it. However, it is rational to assume that we will be able to model it, when we understand it! This type of science (Modelling for the truth!) is politicly motivated at the outset and intended to fail. The answer from the model will be “42”, then we will have to start all over, searching for the question 😉 The fundamental assumptions still have yet to be proved and no model, no matter how accurate, can reveal them. If you want an accurate process, look out the window!
Fun aside, just stop for a moment and really think what these models are attempting to do.
They seek to model global weather (Perhaps that should be climate;-) in order extrapolate the temperature in the future!
Big brahamic in-breath!
I’m a big believer in the power of computers but then that is just the point!
We pick Co2 to blame because it is the biggest economically and politically but unfortunately it is a bit player in the atmosphere*.
Occam might just have cut his own throat, to end the irrationality.
* With qualification, modellers would say: “Sure, he is a tiny man but he is piggybacking a giant and he’s the brains of the relationship” (Think master blaster from Beyond Thunderdome, Co2 (A gas) riding on the shoulders of H2O (A solid, liquid, gas that gets around in great evaporative machines and powerful precipitative heat exchangers called clouds! 😉
old engineer says:
November 30, 2013 at 4:21 am
That month an average of 342 W/m^2 shone on the earth in the form of SW radiation- also know as sunlight. Clouds reflected about 45 W/m^2 of this energy, while trapping 31 W/m^2 in the form of LW radiation.”
==================
which is opposite of the 3x positive feedback assume for increased water vapor. which is why the famous “hot spot” predicted by all climate models does not happen.
water in the atmosphere makes the day cooler and the night warmer. This is because water “blocks” radiation in both direction. It blocks energy from the sun reaching the earth, and blocks radiation from the surface reaching space. however the net effect is negative – not positive.
It is the negative feedback for water in the atmosphere that stabilizes the temperature of the earth, such that over the past 600 billion years the range of average temps has remained at about 16C +- 6C, regardless of CO2 levels.
The work of Dr Henrik Svensmark has been invaluable. People should watch the documentary titled “Svensmark: The Cloud Mystery” (2008) about his ground breaking research relating to the astonishing correlation between solar activity, galactic cosmic rays and cloud cover.
0.7C of the 3.0C per doubling proposition is based on a reduction in clouds as a feedback from the initial warming produced by CO2.
But let’s say, it is actually Zero feedback instead. The 3.0C per doubling falls to 2.3C.
Or let’s say the sign of the feedback is actually opposite. Now the 3.0C falls to 1.6C.
Or let’s say the feedback is a large negative instead. Now the 3.0C falls below 1.0C.
Is getting clouds right important?
Its the difference between little warming and large warming impacts so it is obviously very important to get it right.
But the simple fact is that we do not know which one of the above scenarios is right. We have no clue. The observational evidence is relatively scant and variously provides some evidence supporting all of the scenarios.
I have seen nothing in the models that deals with Dr. William Gray’s criticisms. The models do not handle the evaporative cooling associated with increased LWIR. It is this conversion of radiation energy to water vapor which then gets transported to the upper atmosphere that appears to be missing. The planet is covered by water and it is not just the oceans. We have lakes, ponds, rivers, puddles, dew, rain-soaked ground, ice, etc.. The 3.7 w/m2 is largely transformed into a slight increase in convective water vapor. The net result is slightly more rain and perhaps a small residual warming of .1 to .2 C per CO2 doubling.
When the models get this right they will need to reduce aerosol effect which is the other factor they have wrong in a major way. Of course, once this is done the future catastrophe will disappear so I’m not looking for any funding to be targeted to investigate these problems.
Steve Mosher says:
“When the models are improved they will complain that the models are being fixed.”
That’s absurd. Improved models would reflect the reality that CAGW is implausible. I doubt anyone here would complain about that.
In reply to: Nick Stokes says: November 29, 2013 at 1:22 pm “Let that 40 watts/ square meter sink in a moment.” But with a little bit of thought. They are talking about a specific area. 20 °S and 10 ° of longitude. Just 7 cruises – we don’t know what time of year. And the 40 W/m2 is an instantaneous variation in surface radiation balance. It isn’t loss to the planet, else we’d certainly have an ice age. There may be some extra albedo. But overall, the difference would mostly add to the large component of SW thermalized in the air rather than at the surface. “When present, clouds reduce solar radiation by 160 W m-2 and radiate 70 W m-2 more downward longwave radiation than clear skies.” This is an odd statement, when you think about it. Clouds come in all shapes and sizes. Insolation varies a lot during the year. But no distribution quoted?
William:
The observational evidence (there must be a physical explanation for all observations, as we all believe in physics not magic 101) is that there has been almost no warming except for warming at high latitudes (see Bob Tisdale’s graph and the paper on latitudinal analysis of the temperature anomaly predicted vs observed). The observational evidence of high latitude warming has been incorrectly called ‘polar’ amplification with the implication that some magic fairy amplifies CO2 warming in the polar regions. The Realclimate blog fails to point out that the same magic fairy apparently inhibits the CO2 warming in all regions of the planet except for high latitude regions so what is observed is not ‘polar’ amplification. Also it should be noted that there is now observed cooling of high latitude regions which indicate the phenomena is reversible which is rules out CO2 as the little warming lights using Gore’s analogue are always on if there is long wave radiation emitted to space.
The crafty magic fairy also inhibits CO2 warming in the tropical troposphere at around 8km above the surface of the planet which is the region of the planet that according to the GCMs should experience the most amount of warming on the planet. (The CO2 mechanism in the lower troposphere is almost saturated according the models due to overlap of the water emission radiation bands and the CO2. Higher the troposphere there is less water so the CO2 warming should be more. The increased warming the higher regions of the troposphere would then warm the surface of the planet by increased long wave radiation.) The complete lack of warming expect in the high latitude regions is a paradox, as is the lack of warming the tropical troposphere at 8km.
Now as CO2 is eventually distributed in the atmosphere and the CO2 forcing is by theory proportional to long wave radiation that is emitted off to space, the lack of warming of the tropical troposphere and the complete lack of warming except for the high latitude regions requires a new mechanism that inhibits the CO2 mechanism higher in the atmosphere but not lower in the atmosphere. CO2 is a greenhouse gas, the laws of physics are correct, the problem is there is something different in the upper troposphere that is being missed in the radiation calculations. Support for this assertion is paleo climatic data that shows the planet has been significantly warmer than current for millions than years when CO2 levels where close to current and has been cold (ice sheets) for millions of years when CO2 levels where two to three times current (the lack of correlation of CO2 and temperature paradox).
http://bobtisdale.files.wordpress.com/2013/11/figure-72.png
http://arxiv.org/ftp/arxiv/papers/0809/0809.0581.pdf
“These effects do not have the signature associated with CO2 climate forcing. (William: This observation indicates something is fundamental incorrect with the IPCC models, likely negative feedback in the tropics due to increased or decreased planetary cloud cover to resist forcing). However, the data show a small underlying positive trend that is consistent with CO2 climate forcing with no-feedback. (William: This indicates a significant portion of the 20th century warming has due to something rather than CO2 forcing.)”
“These conclusions are contrary to the IPCC [2007] statement: “[M]ost of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations.”
http://wattsupwiththat.com/2013/07/16/about-that-missing-hot-spot/
http://icecap.us/images/uploads/DOUGLASPAPER.pdf
A comparison of tropical temperature trends with model predictions
I think the modelers need to focus on cloud-affected albedo equatorially outwards to the 45th parallel, maybe a bit beyond. Why? Because beyond that limit I think oceanic currents of warmed or cold water affect land temperature and ice trends, not clouds. The angle of the Sun just isn’t that great. Within the band of interest, clouds will determine the amount of solar IR penetrating into the oceans, thus significantly changing the amount of heat stored and eventually sent poleward. On the other hand it would be interesting to determine any affects outside this important equatorial band. I think extra-tropical clouds bring about noisy weather variation and the equatorial band drives decadal trends.
Leon0112 says:
November 30, 2013 at 3:51 am
Mosher seems to consistently argue that the “science is not settled” and scientists are working constantly to improve their models and understanding. At least that is my understanding of his comments.
If so, good on him.
======================================================
Well shucks !!
I’ll bet that 97 % of the skeptics agree that the science isn’t settled either.
As far as the “scientists” that are constantly improving their models and understanding, it ain’t working.
Maybe they are spending more time trying to get research grants and funding.
If you have followed this issue for anytime, you would know that it’s been suggested numerous times that the people doing the modeling have their input wrong, yet, they don’t change it.
Well, basically should models not first model based on the known albedo of the Earth?
http://www.bbso.njit.edu/science_may28.html
1. With certainty, increasing CO2 has been increasing plant growth/vegetation productivity on the planet.
http://www.climatecentral.org/news/study-finds-plant-growth-surges-as-co2-levels-rise-16094
“In the end, they teased out the carbon dioxide fertilization effect from all other influences and calculated that this could account for an 11 percent increase in global foliage since 1982.”
2. With certainty, plant transpiration contributes massive amount of water vapor to the global atmosphere.
http://ga.water.usgs.gov/edu/watercycletranspiration.html
“Studies have revealed that about 10 percent of the moisture found in the atmosphere is released by plants through transpiration.During a growing season, a leaf will transpire many times more water than its own weight. An acre of corn gives off about 3,000-4,000 gallons (11,400-15,100 liters) of water each day, and a large oak tree can transpire 40,000 gallons (151,000 liters) per year”
3. Massive amounts of ground water for irrigation and other needs is increasing soil moisture as well as evaporation. This also increases plant transpiration(combined as evapotranspiration from the soil/plant combination)
http://www.waterworld.com/articles/wwi/print/volume-25/issue-5/groundwater-development-flow-modeling/groundwater-depletion-linked-to-rising.html
“Large-scale groundwater extraction for irrigation, drinking water or industry has resulted in an annual rise in sea levels of approximately 0.8mm – this works out at one quarter of total annual sea-level rise”
4. Additional moisture contributions from the sources above are effecting the global climate. A powerful example on a small scale is the micro climate of the US Cornbelt during the growing season.
http://www.weather.com/outlook/weather-news/news/articles/evapotranspiration-corn-belt-humidity_2011-07-13
“Moreover, evapotranspiration is the gift that keeps on giving too. The high dew point values that evapotranspiration helps to produce are also one of the ingredients that fuels the development of thunderstorms. Those thunderstorms then go on to produce very heavy rainfall which consequently creates high soil moisture content and lush vegetation. The cycle repeats”
https://www2.ucar.edu/atmosnews/opinion/4997/corn-and-climate-sweaty-topic
“Computer models also take vegetation into account. As used by the National Weather Service, the Weather Research and Forecasting model—which divides the United States land area into rectangles roughly 7.5 miles (12 kilometers) on each side—incorporates daily satellite data on the greenness of the landscape within each rectangle (though not on specific plant types). The model then assesses how much water will enter the atmosphere via the vegetation in each grid box. Forecasters can adjust the resulting model guidance based on their knowledge of local planting patterns and crop behavior.”
5. The contribution of evapotranspiration(including ground water) on a planetary scale to atmospheric water vapor is enormous. This clearly would lead to more clouds.
6. To dial much of this into climate models, one would first have to fully acknowledge and give appropriate weighting to the enormous increase in vegetation on our planet from the benefits of CO2 fertilization.
I realize that H2O is a greenhouse gas and the theory behind that. However, in the real world, using just the above, the contribution is one that increases clouds and acts as a negative feedback. Note for example, that an air mass in the Cornbelt in July with dew points boosted 5 degrees from tightly packed corn plants, will have have a much lower LCL(lifting condensation level) so cumulus clouds will develop much earlier in the day……..cutting off sunshine sooner, starting thunderstorms earlier. This same process is taking place globally, though not to that extreme in most locations and does not always have that result(in a dry air mass).
I wonder how many people reading this post (aside from NIck Stokes) understood that the de Szoeke paper, published a year ago, was referring to a small area off the coast of South America along the Andes in October / November? It would not have been hard to write the post in a way that made that clear. Instead, editorial statements like this
give the false impression the paper was making a general statement that wasn’t confined to a particular location and time of year.
Wayne Delbeke says:
November 29, 2013 at 8:17 pm
@ Mosher.
Uh … the Models are “fixed”.
===========
Had my dog “fixed” and he can not produce anything valid either.
To clarify my thoughts about drivers of trends versus noise. The equatorial band of clouds allows or reflects various amounts of solar IR into the oceans. Because of the obvious long term variations seen in oceanic/atmospheric teleconnection conditions in this band and the amount of irradiance available to it as a straight-on hit to the ocean surface exposed to this IR in this band, it makes sense that long term trends world wide can be traced back to this important band. Outside of that band we have noisy jet stream weather systems that add noisy data to the underlying trend.
It would be of interest to me to de-aggregate the data in this way and build models that are similarly de-aggregated to cut down on weather noise when we want to project a world trend, or focus on the noise when we want to project the weather.
Pippen Fool says, in response to my statement that…
“…in reality, it is ∆T that causes ∆CO2.”
I can conclusively show that statement is correct: See here. But Pippen, as usual, is making a simple [and wrong] assertion:
“Wow. You are living in your own little imaginary bubble land. Enjoy yourself and be happy.”
Ah, but the bubble is Pippen’s world. He refuses to admit that ∆T causes ∆CO2, when every empirical measurement validates that cause and effect relationship.
While there is no cause and effect showing that changes in CO2 are the cause of changes in temperature.
We’re discussing scientific facts here, Pippen, not your crazy Belief system. Unless you can produce scientific facts showing that changes in CO2 cause changes in global temperature, you lose the debate. Simple as that, no? If that conclusion is wrong, point out the error.
Leo: what are you suggesting? That this site would misrepresent a study’s findings?
Increased water vapour leading to more convective uplift is a major part of the negative system response to more IR in the atmosphere.
Any ‘extra’ IR left over after the hydrological cycle has done its work is dealt with by air parcel expansion at levels off the ground.
The resulting changes in density along the lapse rate slope change convection rates further to eliminate any such ‘extra’ IR for, overall, a full negative system response.
All we could see would be a miniscule change in air circulation too small to separate from solar and oceanic variations.
Models fail because they are modeling an idea, not scientific principles. The GCMs exist only to encourage the belief that something catastrophic can happen with regard to climate. That encouragement does not come from nature, so models are required. Unlike nature, models are compliant.
@claimsguy
What do you think that Leo is suggesting?
Stephen Wilde says:
“Increased water vapour leading to more convective uplift is a major part of the negative system response to more IR in the atmosphere.
Any ‘extra’ IR left over after the hydrological cycle has done its work is dealt with by air parcel expansion at levels off the ground.
The resulting changes in density along the lapse rate slope change convection rates further to eliminate any such ‘extra’ IR for, overall, a full negative system response.
All we could see would be a miniscule change in air circulation too small to separate from solar and oceanic variations”
I respectfully and strongly disagree based on personal observations of the effects on diurnal clouds in the United States Midwest/Cornbelt as an operational meteorologist the past 32 years.
@dp says:”Models fail because they are modeling an idea, not scientific principles. ”
I think this is not strictly true: I believe the models ARE modeling actual physics, at least to some degree. In any model of a complex system there are almost always simplifications: we use easier calculations when we think they won’t hurt, we make assumptions that certain factors will not interact, and we leave things out that we a priori think are not likely to affect the outcome.
Of course, this list I just gave opens the door to significant potential for error, especially with highly nonlinear systems.
In sum, a model can be based on scientific principles, yet still produce horrifically wrong results.
Clouds really make a conundrum don’t they? Water expands as it warms and expansion of a ‘gas’ causes cooling doesn’t it?Maybe that’s why clouds and ice are visible?You know, like change from translucent to opague?Water forms a visible crystalline structure when subjected to certain conditions?Clouds are formed in response to warming temp.? ice formed because of expansion?Atmosphere at altitude is….very cold, lift water molecules that high into the cold and the expansion becomes two fold or exponential(expanding from warmth and expanding from cold at the same time.Yeah .try modeling that–i can see why some modelers left that out, if they included that then we probably wouldn’t be discussing this.
http://en.wikipedia.org/wiki/File:Phase_diagram_of_water.svg
http://www.engineeringtoolbox.com/air-altitude-temperature-d_461.html
http://www.engineeringtoolbox.com/humid-air-ideal-gas-d_677.html
Who knows .i could be wrong or incomplete in my ‘comment science’ view
Thanks for the interesting articles and comments.
a missing reference link from my comment:
http://www.howstuffworks.com/dictionary/physics-terms/expansion-info.htm
thanks
Anthony,
Taken a few days for this.
If there isn’t a lot of difference between the models for long range and the models for weather and they don’t do clouds well
How the hell do the weather side do rain then?
You would think after 30 odd years of improvement, climate models would be well past the Model “T” range.
Nick Stokes says:
“You have no idea how they are programmed. No such assumption is made.”
On the contrary it is totally implicit.
The moment delta CO2 enters on the right hand side of any global warming equation and delta T on the left, you are implicitly making an assumption that no matter how small, CO2 influences temperature.
And the only question playing with the parameters can resolve, is ‘by how much’.
And as long as CO2 and temperature move upwards, the answer will always be ‘well rather a lot actually’.
If CO2 is NOT introduced on the right hand side of a model there is no AGW IN the model, full stop.
This is the heart of the fraud.
1/. Think of a quantity that is definitely and almost unequivocally man made.
2/. Find a presumed deleterious effect whose time series approximates to the same pattern
3/. Find a relevant theory (and these are a dime a dozen) to give a plausible linkage
4/. Introduce a multiplicative parameterisation to match the curve slopes (lambda)
5/. Project the model to give scary future effects.
6/. Misdirect the boffins (bullshit baffles brains) with discussions about the value of lambda (climate sensitivity) but never let them see the twin sleights of hand that made lambda a positive feedback factor rather than an independent variable, or let them question the inherent assumption in the model itself that deleterious effect is a function of whatever human activity you want to play politcs with, at all….
It is in the end all a load of COCC….
http://www.clarewind.org.uk/events-1.php?event=39
Mike Maguire says:
November 30, 2013 at 4:52 pm
Could you provide more detail please.
Those diurnal changes are solar induced so my description of the relative insignificance of any effect from GHGs remains correct.
Stephen you say: “Those diurnal changes are solar induced so my description of the relative insignificance of any effect from GHGs remains correct.”
How Stephen? Are you thinking along the lines of your expanded/retracted size of the troposphere due to solar change impacts at the stratosphere? A very weak argument. State your mechanism.
stephen,
A reduction in cloud height allows for more efficient cooling to space. Cumulus clouds forming from additional low level moisture have a cooling effect(high albedo of shortwave/solar radiation as you mentioned but also more effective longwave radiation) vs high level clouds that have a warming effect.
http://scitechdaily.com/earths-clouds-are-getting-lower-may-be-in-response-to-global-warming/
Researchers analyzed NASA satellite data from 2000 – 2010 and found that the global average cloud height declined by around one percent over the decade, or by around 100 to 130 feet.
Related to this, Richard Lindsen suggested that in a warming climate, convective clouds will increase in coverage in the tropics. The increased compensating subsidence causes warming and drying in the upper troposphere which allows more longwave radiation to escape to space.
“Does the Earth Have an Adaptive Infrared Iris?”
http://eaps.mit.edu/faculty/lindzen/adinfriris.pdf
Mosher writes “When the models are improved they will complain that the models are being fixed.”
“Fitted” is the word you should be using and the reason I will complain.
Apparantely, the role of the clouds was (finally) admitted in the lastet AR5 of the IPCC but then swept under the carpet:
http://notrickszone.com/2013/12/01/ipcc-finds-the-important-natural-climate-driver-solar-surface-radiation-intensity-but-then-ignores-and-buries-it/