From Duke University, where they validate what we’ve been saying for quite some time: there’s a divergence between climate models and reality.
Global warming progressing at moderate rate, empirical data suggest
DURHAM, N.C. – A new study based on 1,000 years of temperature records suggests global warming is not progressing as fast as it would under the most severe emissions scenarios outlined by the Intergovernmental Panel on Climate Change (IPCC).
“Based on our analysis, a middle-of-the-road warming scenario is more likely, at least for now,” said Patrick T. Brown, a doctoral student in climatology at Duke University’s Nicholas School of the Environment. “But this could change.”
The Duke-led study shows that natural variability in surface temperatures — caused by interactions between the ocean and atmosphere, and other natural factors — can account for observed changes in the recent rates of warming from decade to decade.
The researchers say these “climate wiggles” can slow or speed the rate of warming from decade to decade, and accentuate or offset the effects of increases in greenhouse gas concentrations. If not properly explained and accounted for, they may skew the reliability of climate models and lead to over-interpretation of short-term temperature trends.
The research, published today in the peer-reviewed journal Scientific Reports, uses empirical data, rather than the more commonly used climate models, to estimate decade-to-decade variability.
“At any given time, we could start warming at a faster rate if greenhouse gas concentrations in the atmosphere increase without any offsetting changes in aerosol concentrations or natural variability,” said Wenhong Li, assistant professor of climate at Duke, who conducted the study with Brown.
The team examined whether climate models, such as those used by the IPCC, accurately account for natural chaotic variability that can occur in the rate of global warming as a result of interactions between the ocean and atmosphere, and other natural factors.
To test how accurate climate models are at accounting for variations in the rate of warming, Brown and Li, along with colleagues from San Jose State University and the USDA, created a new statistical model based on reconstructed empirical records of surface temperatures over the last 1,000 years.
“By comparing our model against theirs, we found that climate models largely get the ‘big picture’ right but seem to underestimate the magnitude of natural decade-to-decade climate wiggles,” Brown said. “Our model shows these wiggles can be big enough that they could have accounted for a reasonable portion of the accelerated warming we experienced from 1975 to 2000, as well as the reduced rate in warming that occurred from 2002 to 2013.”
Further comparative analysis of the models revealed another intriguing insight.
“Statistically, it’s pretty unlikely that an 11-year hiatus in warming, like the one we saw at the start of this century, would occur if the underlying human-caused warming was progressing at a rate as fast as the most severe IPCC projections,” Brown said. “Hiatus periods of 11 years or longer are more likely to occur under a middle-of-the-road scenario.”
Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
There’s no guarantee, however, that this rate of warming will remain steady in coming years, Li stressed. “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change.”
###
Eugene C. Cordero of San Jose State University and Steven A. Mauget of the USDA Agricultural Research Service in Lubbock, Texas, co-authored the new study with Brown and Li.
Funding came from the National Science Foundation (Faculty Early Career Development Program grant #ATM-0449996 and NSF grant #AGS-1147608) and the National Institutes of Health (#NIH-1R21AGO44294-01A1).
CITATION: “Comparing the Model-Simulated Global Warming Signal to Observations Using Empirical Estimates of Unforced Noise,” Patrick T. Brown, Wenhong Li, Eugene C. Cordero and Steven A. Mauget; Scientific Reports, April 21, 2015. DOI: 10.1038/srep09957
Full paper here: http://www.nature.com/srep/2015/150421/srep09957/full/srep09957.html
“Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
There’s no guarantee, however, that this rate of warming will remain steady in coming years, Li stressed. “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change.”
HUH?
The whole thing seems to be more of babble than scholarly here…..
sunsettommy,
lol. Well I feel somewhat better that I’m not the only one who has failed to help you understand the concept of internal variability.
Actually your internal variability argument is crap,as it doesn’t help your case in explaining why climate model projections,have continually run way above actual temperature data for 20 years now.
Internal variability is not presently predictable, yet demonstrably capable of inducing +/- 0.25 K deviations or more around the mean trend predicted by external forcings:
http://1.bp.blogspot.com/-oxFP6mUKqIY/VTWEdb3gJzI/AAAAAAAAAbU/YiRjFJ8Zb8M/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BForcings.png
Your evident lack of understanding and wilful refusal to allow someone like me to improve it does not make my argument crap.
Funny how it’s “internal variability” only when it suppresses warming.
During the last 30 years, there was no internal variability, all warming was the fault of CO2.
It still does not save the Chimps modeling temperature projection 100% failure rate. Skeptics have long pointed out this obvious reality,but people like YOU keep resisting the obvious, with bogus argument such as “internal Variability” claims.
The failure rate is the same whether you advance it or not.
The IPCC have made SPECIFIC temperature projections for EACH of the first two decades of at least .20C warming and actual temperature data says it is about ZERO,to slight cooling instead, for the first 13 plus years.
“For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios. Even if the concentrations of all greenhouse gases and aerosols had been kept constant at year 2000 levels, a further warming of about 0.1°C per decade would be expected.”
Warming of .2 C PER DECADE!
They left NO room for your stupid “internal Variability” argument.
Well someone just refuses to get on board:
http://wattsupwiththat.com/2015/02/24/are-climate-modelers-scientists/
Internal variability is not presently predictable and nor is external variability.
sunsettommy,
Yeah, in AR4. CMIP3 ran hotter than CMIP5, which the IPCC themselves say also runs hot. This is not news. I think it’s hilarious that you guys pretend otherwise.
It’s the IPCC’s argument, silly:
https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter11_FINAL.pdf
Climate scientists do not attempt or claim to predict the detailed future evolution of the weather over coming seasons, years or decades. There is, on the other hand, a sound scientific basis for supposing that aspects of climate can be predicted, albeit imprecisely, despite the butterfly effect. For example, increases in long-lived atmospheric greenhouse gas concentrations tend to increase surface temperature in future decades. Thus, information from the past can and does help predict future climate.
Some types of naturally occurring so-called ‘internal’ variability can—in theory at least—extend the capacity to predict future climate. Internal climatic variability arises from natural instabilities in the climate system. If such variability includes or causes extensive, long-lived, upper ocean temperature anomalies, this will drive changes in the overlying atmosphere, both locally and remotely. The El Niño-Southern Oscillation phenomenon is probably the most famous example of this kind of internal variability. Variability linked to the El Niño-Southern Oscillation unfolds in a partially predictable fashion. The butterfly effect is present, but it takes longer to strongly influence some of the variability linked to the El Nino-Southern Oscillation.
Here’s how you replied: http://wattsupwiththat.com/2015/04/18/too-many-wild-cards-in-the-climate-game/#comment-1911904
Your link is 78 pages long, I will ignore it,the same way you ignored the fact that ALL the short warming trends,going back to the 1850’s,fall in a very tight range, centering about .16C per decade.
I suspect your wilful ignorance goes a long way toward explaining your evident confusion above: HUH? The whole thing seems to be more of babble than scholarly here…..
I can only lead a horse to water ….
I wonder what the likelihood of a 20+ year hiatus is in their estimation because that’s where we’re headed.
@Brandon Gates
Could you please explain why the IPCC says as claim yet we are told that certainty is absolute and climate doom is around the corner unless we “ACT NOW”?
Here’s simple statistical evidence of internal variability:
http://www.phy.duke.edu/~rgb/Toft-CO2-PDO.jpg
This is a direct fit of HadCRUT4 back to 1850 against a smoothed estimate of CO_2 concentration that fairly precisely (as you can see) interpolates Mauna Loa data from the 1950’s to the present. Two “scenarios” are presented, one roughly equivalent to 9.5 and one roughly equivalent to 6.5. There is no lag in this fit — and no need for a lag — there is no evidence whatsoever of “uncommitted warming”. Note well that the best fit(s) have a total climate sensitivity of around 1.8 C per doubling of CO_2.
I offer no explanation for the empirical sinusoid with its period of 67 years and amplitude of 0.1 C, but it is in extremely good agreement with the assertions of Brown’s (no relation, and no I don’t work with them) paper. It is at least extremely plausible that between 0.2 and 0.25 C of the warming from 1970 to the present was the result of an entirely natural periodic climate oscillation that has persisted for the last 165 years (if we believe HadCRUT4 and its almost certainly far too optimistic error bars in the first place), an oscillation that also explains the so-called “hiatus” or “pause”.
When I use the term “explains” here, please understand that I’m using it in the sense of explanatory power in statistics. It means only that the curves I fit are in (very!) good agreement with the data. The log term, while semi-empirical, is pure physics and in decent empirical agreement with computed estimates of CO_2-only forcing. The sinusoid is simply there to emphasize a clearly visible feature of the data — although it has no immediate physical basis, there are a number of phenomena that could plausibly produce such a cycle, notably an apparently coherent progression of the decadal oscillations that we only poorly understand and cannot predict or explain.
Things that this fit leave little room for:
* Impact of aerosols. It suggests that the climate is almost completely independent of aerosols, either volcanic or otherwise. One cannot look at this fit or the data and guess where major volcanic eruptions occurred, and there is no functional dependence on aerosol concentration included in the fit itself. Other fits I’ve played with tend to confirm what Willis and others on this list have empirically argued for some time — aerosols are nearly irrelevant to the climate. A recent peer reviewed paper has concluded the same thing on the basis of much more careful study, and this alone means that the CMIP5 models almost without exception exaggerate warming because they are almost all based on strong cooling due to aerosols that permits an exaggerated ECS to CO_2 to fit the reference period (which as we can see above, just happens to have been selected during a period of warming augmented by a natural cyclic process, to doubly amplify the result).
* Lagged/uncommitted warming. There is no good reason to think that the climate is Markovian — there are without doubt relaxation processes that occur over decades to centuries (e.g. associated with the thermohaline circulation, which has timescales up to 1000 years in it). However, annual to decadal fluctuations are on the order of 0.1 to 0.2 C. Warm fluctuations push the climate past what should be “radiative balance” for any given CO_2 concentration on a regular basis. It is very difficult to imagine what causes the climate to supposedly regress to radiative imbalance when this occurs. To put it in mathematically understandable terms, if one has an overdamped system (like an overdamped harmonic oscillator or to be even more concrete, like a defective shock absorber in a car) and one bounces it around across its equilibrium point, it is difficult to see how the system would ever systematically/dynamically regress to some point other than that equilibrium point via some sort of “uncommitted oscillation”.
In a multi-reservoir non-Markovian model one can get all sorts of things including this sort of behavior, but those things necessarily require a much larger role for natural variability because much more of our current climate depends on details of past climate state, rolled through the multiple reservoirs. The additional explanatory power evident in the fits above when the periodic term is included suggest that there is lagged dynamics going on, but there isn’t a lot of reason that I can see or think of to think that it is exponential relaxation in the form of “uncommitted warming” and local radiative imbalance. Actually, the model strongly suggests that the Earth remains very close to radiative balance with short term regressive behavior but that there is considerable and significant complexity that arises from the natural multidecadal periods of the multiple reservoirs and switching around of coupled global circulation patterns in both the atmosphere and the ocean, none of which is captured by or predicted by the models (except by pure accident in some particular run with no discernible predictive value).
The one last feature of “interest” in HadCRUT4 is that there are a number of places where truly phenomenal heating or cooling have occurred without any human agency plausibly being the cause. Somewhere in the mid-1870’s global average temperatures apparently jumped by some 0.4-0.5 C in roughly five years. This jump is actually highly resolvable according to HadCRUT4’s own (probably too small) confidence intervals. It is the largest such jump in the record, although there are many five year jumps on the order of 0.3 to 0.4 C visible — early 1900’s, 1950’s, 1990’s. Some of these can be attributed to ENSO, and of course we have no real observational data for ENSO before the late 1800’s and early 1900’s when the phenomenon was first recognized and named. Periods where the climate is as stable as it has been since the 1997-1998 super-ENSO are actually rather rare in HadCRUT4 — perhaps a single stretch in the late 1940’s, a single stretch leading up to the huge jump in the 1860-1870’s. The super-ENSO jump itself was actually pretty modest compared to the historical record — neither “unprecedented” nor terribly interesting.
What the overall record clearly implies is that the climate can be disequilibrated from its long term presumptive radiative equilibrium trend by as much as 0.3 C at almost any time, and that it is usually disequilibrated by around 0.2 C from that trend (that is, it is more often off by that much than not). The width of significant excursions (either way) appears to be ballpark 5 years and AFAICT are not in particularly good agreement with e.g. ENSO’s period or the solar cycle etc as plausible driver, while at the same time they don’t look quite like simple noise.
To conclude, yes the climate is naturally highly variable. There is no question that “climate scale” global average temperature fluctuations as large as 0.5 C in as little as 5 years can and probably do occur within any interval longer than a couple of centuries (I could plot this out to demonstrate that the tail of the distribution extends at least that far with reasonable probability, but hopefully it is obvious from looking at the data). Given only fluctuations with the observed distribution, one probably cannot exclude the possibility that all of the “climate change” over the last 165 years is due to a mere random walk in an unbiased process of cumulative fluctuation — one has to assume that the physics pushes the system towards a rather narrow equilibrium to conclude otherwise, and I can see little reason or way to derive or even argue for a narrow equilibrium, especially given the large fluctuations observed and discussed above over multiple timescales. If the periodic variability is not due to actual periodic processes, it only makes this argument worse, because then we have to contend with multidecadal noise in our fluctuation spectrum and fluctuation-dissipation beats any assertion of computability/predictability in the system to pieces with a blunt instrument and leaves it free to drift all over the place from coincident noise with very little forced regression to an assumed narrow equilibrium “set point”.
All of this is useful in helping us understand why fitting the empirical timeseries produced by a non-stationary process, even producing a fit with high explanatory power, has little reliable predictive power. All we really learn by examining the fluctuations and apparently systematic variations visible in the fits above is that we are remarkably ignorant about the climate and that there is a lot going on that we cannot predict a priori or (if we are completely honest) explain a posteriori, more than enough to make future “prediction” of some climate trend via extrapolation of any sort of fit uncertain in the extreme. The fits and extrapolations in my figure above are plausible, but who would really be surprised if they were substantially incorrect? If we simply doubled the confidence intervals prior to (say) 1950, which IMO is a very conservative correction to HadCRUT4’s absolutely implausible assertion that contemporary temperature estimates are only twice as precise as those they claim for the 19th century then all bets are off! We could then drive a metaphorical truck through the space of plausible fit functions and still have excellent explanatory power. If we apply a single piece of obviously omitted correction for bias — HadCRUT4’s omission of UHI corrections likely to be on the order of at least tenths of a degree C from the 1800’s to the present — it makes profound changes to the estimated climate sensitivity of the best fit.
Brown’s paper is thus very useful, as he and his colleague have had the courage to assert publicly what is really rather obvious — natural variation is probably responsible for just under half of the total warming observed from the mid-1970’s to the present (with a big error bar, one large enough that it could easily be more than half). It sounds as though it made its assertion on the basis of the still-exaggerated prior estimates of climate sensitivity to aerosols, and this factor alone might well invert its conclusion from less than half to more than half.
In the end, though, it leaves us nearly as ignorant as we were beforehand. If my extremely simple model above that includes the periodic piece is “correct” (has some predictive value, which I do not assert) current temperatures are just under what they “should” be by around 0.1 C, and we might reasonably expect our next “random” five year fluctuations — when they resume, currently apparently suppressed — to regress the climate up by 0.1 to 0.3 C to the vicinity of the green line or just past it. and then remain close to that level (again within these 0.1 to 0.3 C fluctuations) for the next decade depending on what CO_2 does (but not strongly!) before going up rapidly as we approach the 2050’s. However, this assertion depends on a breathtaking list of assumptions (not the least of which is the presumptive accuracy of HadCRUT4!). Even so, this simple and physically motivated model — with or without the periodic piece — beats the hell out of CMIP5’s superaverage, and simply blows individual models or model runs away in the past, and is IMO at least as likely to be accurate in the future as the far more complex attempts to solve the coupled Navier-Stokes equations on a grid 30 orders of magnitude too coarse out decades to centuries into the future.
rgb
Brandon Gates,
The alarm bells dissapear when you argu “internal variability”, that argument produces ” no stink on the ball”. In order to scare children CAGW has used predictions…no?
Brute,
1) CO2 has a half-life in the atmosphere of ~40 years.
2) >90% of the retained solar energy due to GHG forcing has gone into the oceans.
Adds up to: what we’ve started will plausibly take centuries to stop.
I prefer not to be panicky about it, and don’t much care for your hyperbole. I don’t think it’s rational or responsible adult behaviour to look at something as uncertain as climate obviously is with a cavalier or mocking attitude.
owenvsthegenius,
I’m not big on scaring children, nor am I especially keen about motivating adults with fear. I do believe that identifying risks and communicating them is an appropriate role for science. I can’t parse the rest of your comment.
rgbatduke,
Hmm. Well I get better fits when I lag. IIRC 10 years really snaps things into shape. But that’s not how uncommitted warming is quantified in literature. Trenberth & Kiehl (2009) is more or less the gold standard AFAIK: http://journals.ametsoc.org/doi/pdf/10.1175/2008BAMS2634.1
I’m fairly sure you know of it already, I include it more for any silent third parties still reading this thread.
The usual suspects are AMO and/or PDO, but truly “understanding” those things is well above my paygrade. The length-of-day stuff I’ve been reading about lately is intriguing because the correlation to the residual of a CO2-only regression is spooky good AND looks like it might actually offer decades in advance predictability.
Completely agree.
I mostly agree, but with caveats. Much depends on what kind of prediction one is asking for, or is claiming has been made. If I thought the IPCC were claiming to be able to predict annual temperatures to within a tenth of a degree out to 2100, I would gladly relegate it to the pseudo-science bin because there is zero literature support for being able to do such a thing. Bounded estimates for decadal or longer periods of time out to 85 years are more defensible, but there a purely statistical model probably doesn’t cut it all by its lonesome.
In a more perfect world, T&K (2008) wouldn’t have had to torture the satellite data so much to tease out a signal with such ridiculous error bars, and we could do this with straight up 1st law accounting; flux in – flux out = known boundary forcings, initial conditions need not be so critical.
Yet, even that wouldn’t get rid of a vast number of other uncertainties about known and unknown non-linearities.
All of which raises my perennial question: why are so many folks so confident that we’ll be able to handle any changes, come what may? Massive uncertainty is the best argument I can think of to keep things within the realm of the familiar. IOW, “the models suck” mantra appears to have the exact opposite of what I’d consider a normal rational response to “we don’t know exactly what will happen” in this forum. Which I think is bizarre.
I am sure Brandon will explain this to all of us here:
“In panel a, the points show the CCSM4 anomaly projections of the AR5 Representative Concentration Pathways (RCP) 6.0 (green) and 8.5 (blue). The lines are the PWM emulations of the CCSM4 projections, made using the standard RCP forcings from Meinshausen. [2] The CCSM4 RCP forcings may not be identical to the Meinhausen RCP forcings. The shaded areas are the range of projections across all AR5 models (see AR5 Figure TS.15). The CCSM4 projections are in the upper range.
In panel b, the lines are the same two CCSM4 RCP projections. But now the shaded areas are the uncertainty envelopes resulting when ±4 Wm-2 CMIP5 long wave cloud forcing error is propagated through the projections in annual steps.
The uncertainty is so large because ±4 W m-2 of annual long wave cloud forcing error is ±114´ larger than the annual average 0.035 Wm-2 forcing increase of GHG emissions since 1979. Typical error bars for CMIP5 climate model projections are about ±14 C after 100 years and ±18 C after 150 years.
It’s immediately clear that climate models are unable to resolve any thermal effect of greenhouse gas emissions or tell us anything about future air temperatures. It’s impossible that climate models can ever have resolved an anthropogenic greenhouse signal; not now nor at any time in the past.
Propagation of errors through a calculation is a simple idea. It’s logically obvious. It’s critically important. It gets pounded into every single freshman physics, chemistry, and engineering student.”
http://wattsupwiththat.com/2015/02/24/are-climate-modelers-scientists/
sunsettommy,
Yah, that’s what empirical studies are for. Starting again, Harries et al. (2001):
https://workspace.imperial.ac.uk/physics/Public/spat/John/Increase%20in%20greenhouse%20forcing%20inferred%20from%20the%20outgoing%20longwave%20radiation%20spectra%20of%20the%20Earth%20in%201970%20and%201997.pdf
This time I’ll include a pretty picture:
http://www.skepticalscience.com/images/infrared_spectrum.jpg
It’s pretty bleedin’ obvious to me.
I hold that a rational person doing risk analysis would therefore argue for “no change” as the best policy. YMMV.
Changes in cloud cover (less cloud cover) also results in an increase in infrared red radiation. Curiously there has been a reduction in cloud cover during the period when warming occurred.
If the majority of the warming was due to a reduction in cloud cover rather than the increase in CO2 in the atmosphere, the warming would be reversible if the cloud cover where to increase, due to an abrupt slowdown in the solar cycle.
This is also a pretty picture. Does this picture support the assertion the planet is going to continue to not warm (‘pause’ in warm) or start cooling?
http://arctic.atmos.uiuc.edu/cryosphere/IMAGES/seaice.anomaly.antarctic.png
There are 342 warming events in the paleo climatic record (Antarctic peninsula ice core data, the Antarctic peninsula is outside of the Antarctic polar vortex and hence correlates with Southern Sea temperature rather than Antarctic ice sheet temperature, during the warming events the Southern sea warms and the Antarctic ice sheet cools which is exactly the same as was observed in the last 70 years) in the last 250,000 years with a mean time between warming events of 1400 years and 400 years (the period between events in the Southern hemisphere is the same as the period between warming events in the Northern hemisphere which provides support for the assertion that the cause of the cycle is solar magnetic cycle changes as that mechanism can affect both hemispheres simultaneously as opposed to internal climate mechanisms that are chaotic rather than periodic and that do not affect both hemispheres simultaneously.)
http://wattsupwiththat.files.wordpress.com/2012/09/davis-and-taylor-wuwt-submission.pdf
Curious that the cult of CAGW has not discussed the fact that the planet cyclically warms and cools, with the warming and cooling periods correlating with solar changes. Note the same high latitudinal regions warmed and then cooled in the past. (P.S. CO2 warming on the other hand should warm the tropics more than high latitudinal regions as the highest amount of long wave radiation is emitted to space in the tropics and of course CO2 is evenly distributed in the atmosphere. I guess no one in the IPCC noticed there has been almost no warming in the tropics.)
http://www.drroyspencer.com/wp-content/uploads/TMI-SST-MEI-adj-vs-CMIP5-20N-20S-thru-2015.png
http://www.drroyspencer.com/2013/02/tropical-ssts-since-1998-latest-climate-models-warm-3x-too-fast/
http://icecap.us/images/uploads/DOUGLASPAPER.pdf
A comparison of tropical temperature trends with model predictions
Brandon Gates
Could you please explain the ‘pretty pictures’ you’ve added. That is the strangest planck curve I’ve seen. Is it from a ‘dark universe’?
The troposphere was supposed to warm at least 1.5 times the surface. The troposphere is not warming period for close to two decades. 1998 was the warmest year. The surface warming does not drive global climate, especially UHI cities do not drive global warming,. ENSO is somewhat predictable. This article is a hot luke warmer. The emissions have been at level A the highest. Obama recently agreed to ensure that continues. The CAGW alarmist failed to predict how much the oceans would absorb. There is no sign of saturation. They over predicted the feedbacks, which the observations show to be largely negative.
If the AMO turns full negative, and the PDO also, and we get a large La Nina, we will see a step down the opposite of the 98 step up when we had a positive PDO, AMO, and very large El Nino.
Brandon, the Harries et al 2001 paper deals with the lowering of OLR at the 4 and 15 micron range, and was there to prove that CO2 had indeed introduced OLR at those wavelengths right? So, possibly, more heat is being retained by more CO2. Who disagrees with that?
The problem is that the retained heat doesn’t mean that there will be changes in atmospheric temperature because of, as you say natural forcing, and, of course feedbacks and sensitivity.
The pause kind of put the kibosh on all that, or at least it would have done in another scientific field. That there have been 63 explanations for the pause makes it clear that the scientific community don’t have a clue what has caused it, and nor will they if they persist in excluding the possibility that CO2 may retain heat but that doesn’t necessarily mean that this retained heat will lead to a rise in temperature (the “black swan” they should all be looking for).
Brandon
I can see how it was done , so no need to explain. I must add that I am underwhelmed by the milliwatt levels
geronimo,
Ask sunsettommy, he’s the one calling for “proof”.
The oceans are a massive heat sink, but they’re not infinite. If energy is retained in the system, it’s going to want to come out eventually, and that eventually will affect the atmosphere. It takes on the order of 2,000 years for the oceans to equilibrate. See ah, Bintanja (2008): ftp://ftp.ncdc.noaa.gov/pub/data/paleo/paleocean/by_contributor/bintanja2008/
Model study (with observational support), but the data give a pretty good idea of how ocean temps lag the surface. Also intersting, the ratio of atmosphere to ocean temps is about 5 to 1.
I fundamentally do not understand that claim. Seriously, it literally makes no sense to me — not because I’m stupid or uninformed, but rather because I’ve done my homework and most people who actually know me don’t think I’m a complete moron.
Basically, I think it’s preposterous that you think you know better than the thousands of domain experts who do this stuff for a living. Naked appeal to authority yes, but I’m tired of self-proclaimed experts thinking that because 63 aspects (times a zillion) of a fiendishly complex physical system are poorly understood that the rock-solid physics-based, lab-tested, observed directly from ground and space phenomenon that the entire kit and kaboodle is based on must also be poorly understood.
AGW is fundamentally a conservation of energy argument. If energy comes in and doesn’t go back out, things warm up. That much of it is dirt simple. Knowing exactly how and when that retained energy will manifest itself is the hard part. Don’t confuse lack of predictability with falsification of the underlying theory. My favourite example: earthquake predictability vs. plate tectonics.
Alex,
Converting to picowatts should yield up an impressively alarming number of goose eggs to the left of the decimal point.
Brandon shows up once again with his evasive replies to the obvious,that Chimps models are ALWAYS wrongs and have been for many years. He says:
“Yeah, in AR4. CMIP3 ran hotter than CMIP5, which the IPCC themselves say also runs hot. This is not news. I think it’s hilarious that you guys pretend otherwise.”
Nice to to know they were wrong in 2007 and still wrong today,yet YOU think I pretend differently?
I have KNOWN for years they are wrong, because I looked up the temperature data to see how well it matches up. They have always been waaay too high.
It has been over 13 years now,with ZERO warming, while the IPCC thought based on their scenarios,that it should have warmed about .35C by now.
Zero warming is very different from .35 C
To me that describes EPIC FAIL!
But YOU seem to think they are still wonderful,and defend them despite a 100% failure rate over the years. That indicate that you are seriously missing some rational thinking here.
Rational people have long dropped the Chimps models as credible models,since they have ZERO forecast skill to brag about.
The IPCC is now more confident in AR5 than it was in AR4 despite all the predictions being wrong.
This may seem strange. It needs explanation.
This is because predictions tested against reality are scientific evidence.
While AGW believers rely on faith. Reality is merely a challenge that strengthens them.
Coulda shoulda woulda.
So things might change; woud that ualify as cliate change.
And Mr Patrick Brwn, are you saying the whle thig couldtake nosedveas well.
I mean if you don’t have the faintest idea what is goin n and it might change anywy, then it could go dow instead of up clouldn’t it.
I hope you aren’t related to rgbatduke.
And shouldn’t the headline say it might be milder than the BEST case scenario, rather than the WORST case scenario ??
Worst case is it goes up 1o deg. C next year.
What a bunch of hooey !
Warming will change though. If the past is any indication, we will see about 15 to 20 more years of relative flatline (Negative PDO pushing down, CO2 pushing up), followed by a double-warming period similar to 1977-1998 (Positive PDO). Then 25-30 years more flatline (Negative PDO). Somewhere between 1+C and 2 C for ECS for doubling would be considered “surprise-free”. That’s what the data seems to be telling me. We may possibly double C)2, but we will never, ever redouble it. In the long run, the diminishing returns are in our favor.
Paint onto that whatever deltas you like. Drop in whatever factors please you. Maybe your result will be a model. Maybe it will be a bad model. But it will be a model that matches in with current data and trends better than CMIP5.
If the AMO turns full negative, and the PDO also, and we get a large La Nina, we will see a step down the opposite of the 98 step up when we had a positive PDO, AMO, and very large El Nino.
You forgot the AMO.
Yeah, I’m still trying to figure out when AGW became the null hypothesis.
when nature falsified their theory!
You need to be more skeptical sunsettommy.
The language of a pause of 11 years or more in the middle of the road scenario is an artifact found in few models. However, the pause is now 18 years and no model predicted that under any scenario even remotely close to what occurred.
It is probable that warming from CO2 emissions will amount to around 1.5degC or less for a doubling of the gas in the atmosphere. One has to keep in mind that the 3 deg figure was based upon the 17 year period of warming fingerprinted by Dr Ben Santer (80’s and 90’s) Only with that recent warming (in the year 2000) was there any evidence at all that warming would be so great. It was reinforced by the huge increase of CO2 emissions that occurred beginning with the decade of the 1970’s resulting in Santer’s analysis attributing to human sources and the claims that “natural variation” had been overridden.
Its easy to chart the warming pattern over 10 year trends. In this analysis warming occurred in time with the solar cycle. Peak 10 year trends would occur around solar maximums dropping to almost zero during solar minimums. Like clockwork the 10 year trends would bottom out to zero warming over 10 years near solar minimums and then hit somewhere between 2degC and 4degC at solar maximums. The AR3 prediction is an almost perfect fit to the most rapid 17 year warming period that could be found on the chart and just happened to run up to the study publication date deadline for AR3. This cherry picked low to high change in warming rates never had much science weight with me. Now its been falsified leaving no support except the models created out of that morass.
A chaotic statement might seem like babble to you but the climate may in fact be chaotic and as such a chaotic statement while not comfortable for you it might be factual.
Not sure why there is so much carping about this article. Their statements that “this could change” are pretty mild. The main point is that they are providing a critique of GCMs that could lead to their improvement. There was a Nature Geoscience by Bjorn Stephens the other day that says that maybe the iris effect is what is missing from GCMs. So, finally we are starting to get some attention to how poorly the models perform and trying to identify reasons why, rather than papers trying to say the hiatus did not really happen or trying to explain it away. Pointing out ways to improve the GCMs is a good thing. Many of the alarmist clap-trap that gets published takes the output/”projections” of the GCMs and uses it as input for
some other equally poor model projecting environmental or ecological effects. So, improved GCMs will hopefully lead to improved “crap” papers as well. Maybe someday they won’t be complete crap.
Yes, no kidding! Look what Wunderground published for Earth Day.
A whole series of articles, all predicting doom and gloom and all based on model output.
What a waste of time and resource.
Yirgach,
Look what Wunderground published for Earth Day.
and what liars they are:
http://www.wunderground.com/earth-day/earth-day-history/
They seem to imply that the Clean Air Act was passed after the first Earth Day in 1970.
The Clean Air Act became effective on December 17th 1963.
I hope their collective pants are on fire.
MarkW
On another WUWT thread I repeatedly attempted to get Brandon Gates to say what he means by “internal variability”. As he usually does, he provided much irrelevant waffle but no answer to the question.
My responses to his nonsense are here where I wrote
and here where I wrote
Mark W, It is clear that Brandon Gates is attempting to similarly pollute this thread with the same nonsense.
Richard
richardscourtney,
The concept of internal variability has been in literature since at least the late 1960s. Here’s an example from 1978 …
http://climate.envsci.rutgers.edu/pdf/RobockInternalExternalJAS1978.pdf
Internal variability was posited for the very reason that it was noted temperatures had been declining since the 1940s after having previously risen (as then estimated) about 1°C from 1880 to 1940. The introductory paragraph notes that previous studies mainly focused on external causes:
Various attempts to simulate this temperature record (Schneider and Mass, 1975; Pollack et at., 1976; Bryson and Dittberner, 1976) have all focused on external causes, such as volcanic dust, solar constant variations and anthropogenic effects. It is possible, however, that even in the absence of any external forcing a unique climate may not exist. Climate change may be a natural internal feature of the land-ocean-ice-atmosphere (climate) system.
I have a lot of trouble believing that most here would dispute the sentence I bolded for emphasis. Same for the very next sentence:
The theory of internal causation of climate change has been developed by Lorenz (1968, 1970, 1976). He suggested that climate change might just be the natural variations due to the complex nonlinear interactions among the various components of the climate system.
I’ve already shown you mine:
http://2.bp.blogspot.com/-sCuOxDdbiXo/VTb4ffCsPgI/AAAAAAAAAb8/cEgSwN3Dik8/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BInternal%2BVariability%2BNet.png
AMO and ENSO are well-documented phenomena, as is LOD, but its causal relationship to climate isn’t well-established. To me it looks promising.
How do YOU explain The Pause without invoking “magic”? Come now, don’t be shy — demonstrate your superior scientific understanding and knowledge.
Brandon Gates
I repeatedly asked you
On two threads you failed to answer either question and provided the waffle I have here reported instead.
Now, under pressure you have conducted your usual practice of copying&pasting something you don’t understand in attempt to pretend you have not been spouting nonsense.
You do NOT state what you mean by “internal variability” and the passages you quote do NOT provide definitions of it.
They each state – as I did with explanation on WUWT yesterday http://wattsupwiththat.com/2015/04/22/a-statistical-definition-of-the-hiatus-in-global-warming-using-nasa-giss-and-mlo-data/#comment-1914715 – that climate may vary with no force or process driving the change.
Brandon, I repeat to you
Please state what YOU mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.
I still await any answer to that from you because what you have written confirms my previous conclusion about your meaning of “internal variability”; i.e.
Clearly, what you call “internal variability” is an undefined excuse for all disagreements of the models with reality. In other words, your “internal variability” is magical mystery.
And you demonstrate that – as usual – you don’t understand what you have copied and pasted when you ask me
Your question demonstrate that almost everybody over the age of 5 years has superior scientific understanding and knowledge to you because only fools pretend knowledge they don’t have.
Nobody knows why global temperature has risen from the Little Ice Age (LIA), why that rise has stopped (i.e. the so-called ‘pause’, and if the ‘pause’ will end with warming or cooling. That is why there are nearly 70 possible explanations for the ‘pause’ published in the peer reviewed literature.
One explanation for these variations in global temperature was explained by me on WUWT yesterday (and I have linked to it in this post) and that explanation was also provided by you when you quoted
If the ‘pause’ is “natural variations due to the complex nonlinear interactions among the various components of the climate system” then the temperature rise before the ‘pause’ could have resulted from similar “interactions”.
Simply, the quotation you have provided does not explain what you mean by “natural variability but IT DOES DENY any need to invoke your superstitious belief that man-made effects caused the rises in global temperature during the twentieth century.
Richard
My link did not work.
Hopefully, this will
http://wattsupwiththat.com/2015/04/22/a-statistical-definition-of-the-hiatus-in-global-warming-using-nasa-giss-and-mlo-data/#comment-1914715
Richard
richardscourtney,
I replied to that query the first time. We’ll try it again: I don’t understand what you mean by “altering the empirical data”. The way I look at it, empirical data informs us about internal variabilities. Further, I see it as somewhat a nonsense question — internal variability is not something which switches on and off. We’re talking about a massive physical system here, which is constantly attempting to reach equilibrium. Due to its mass, it does not ever achieve equilibrium homogeneously, and it certainly doesn’t approach any sort of mean equilibrium in a neat and tidy fashion.
So, basically what you’re saying is that you don’t know.
I find it odd that someone who as much as just said “I don’t know why The Pause” would claim to speak for the entire body of literature on the topic.
Obviously. That was the whole point of the paper I cited. I requote: Climate change may be a natural internal feature of the land-ocean-ice-atmosphere (climate) system.
I thought the first bit I quoted made it quite clear: Various attempts to simulate this temperature record (Schneider and Mass, 1975; Pollack et at., 1976; Bryson and Dittberner, 1976) have all focused on external causes, such as volcanic dust, solar constant variations and anthropogenic effects. It is possible, however, that even in the absence of any external forcing a unique climate may not exist. Climate change may be a natural internal feature of the land-ocean-ice-atmosphere (climate) system.
IOW, “internal variaiblity” is a change in surface temperature not driven by external radiative effects. I cited two well documented examples, AMO and ENSO, both of which are driven by coupled ocean/atmospheric energy exchanges. So, once again, you have my definition and two well-known examples … and I note that you yourself cite NAO and ENSO.
Please explain why it necessarily follows that postulated effects of natural internal/external variability or forcings preclude any human influence on the system.
Brandon Gates
In response to my repeatedly asking you
Your latest evasion says to me
Even by your standards, that statement is daft.
You wrote
So, how do you know when your magical mystery of “internal variability” is causing measured temperatures to decline or to rise and by how much when – as you quote – ALL such rises and falls could be “the natural variations due to the complex nonlinear interactions among the various components of the climate system”?
Richard
PS And I know what I wrote yesterday to explain the implications of Lorenz’ work: I referred you to it and provided a link. So I refuse to grasp that ‘red herring’.
Of course for one to believe this article, one must agree that [there] has been global warming. This is a claim supported by the alarmists with the slight of hand tactics of changing past temperatures, elimination of rural reporting stations, flat out lying and the other underhanded methods they use. I deny their contention that the earth has warmed in the last two decades, and believe that we are now on the backside of the bell curve towards a period of cooling. Thus this article holds my attention only as the latest perfidity of psuedo science.
@Brandon Gates
My hyperbole? You are a lunatic.
The climate catastrophist alarm is ringing so loudly and has been doing so for so long that statements such as the one below are the new normal:
“2015 is a critical year for humanity. Our civilization has never faced such existential risks as those associated with global warming, biodiversity erosion and resource depletion.”
http://earthstatement.org/statement/
I cannot begin to imagine the degree of delusion it takes to blame people like me for words that clearly and unequivocally are being said by others.
Yeah, they said that tripe in year 2014,2013,2012,2011,2010 and so on for many years.
The world, is always in peril chorus, never stops.
Brute,
That’s what I wrote.
Sure, that statement is arguably emotionally overwrought in my subjective opinion. I personally consider humanity itself its own worst existential threat even without the most dire of postulated future AGW impacts.
Worth noting that they consider 2015 critical because of the Paris conference. I’ve previously cynically predicted that not much progress will be made. Hope springs eternal however.
I’m not exactly sure you’re qualified to diagnose my mental state. I applied “hyperbole” specifically to your statement: Could you please explain why the IPCC says as claim yet we are told that certainty is absolute and climate doom is around the corner unless we “ACT NOW”?
… which explicitly mentions the IPCC. Yet you answer with a statement from: http://earthstatement.org/statement/
Do you not recognize that those are two completely different entities? By the way, here again are my substantive answers to your question:
1) CO2 has a half-life in the atmosphere of ~40 years.
2) >90% of the retained solar energy due to GHG forcing has gone into the oceans.
Adds up to: what we’ve started will plausibly take centuries to stop.
Did you have a substantive response, or is amateur-hour psychoanalysis the best you can muster?
Mission creep isn’t just for the boys at NASA. The NIH has joined in the climate study funding biz.
Maybe if they pay enough, it will get warmer.
Paragraph 2: “But this could change.”
Really? Who knew climate could change?
The question isn’t whether the climate will change but in what direction. These people assume that when the climate changes again, it will get warmer. They leave no possibility for cooling. But what if it does? What will they blame it on then, “climate wiggles” caused by an increase in undetected aerosols or an extended pattern of unusual natural variability?
They’ll blame it on man. It’s deemed climate
changedisruption, thus any change either way is “bad”. Pretty f’ing ridiculous. Whatever it takes to keep the narrative going, the religion alive, and the gravy train rolling.they will just keep increasing the aerosol forcing in the models and put more blame on ‘natural variability’ as if it didnt exist before the magical co2 come on the scene-
sure, it may look a bit stupid making aerosol more and more able to reflect over time, but hey they get away with it now.
Who knew the earth was round?
Reblogged this on Public Secrets and commented:
Reality further diverges from the sacred models. Whatever will the hierophants of the Church of Anthropogenic Global Warming do?
Phineas,
” Whatever will the hierophants of the Church of Anthropogenic Global Warming do?”
” … the Church of Anthropogenic Global Warming do-do”
All sorted.
Auto
I have known for years that the warming rate, has been far less than what the IPCC,Dr. Hansen and other AGW believers have been pushing,simply by looking at the temperature data,compare it to the predictions/Projections made.
Yet you maintain that, “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change.” sounds like scholarly babble.
Maybe for people like you who needs to be told over and over, that temperature and climate changes over time,but scientists should not have to keep saying it over and over, what is obvious to kids.
It’s obvious to children that climate changes because climate scientists are the ones pointing it out to them …
http://upload.wikimedia.org/wikipedia/commons/5/53/MilankovitchCyclesOrbitandCores.png
… as well as providing explanations as to why. Would that some adults could give up their “climate changes (full stop)” magical thinking.
It was only a few years ago we were being told that CO2 was so strong that it completely swamped all other factors.
Brandon,
Please state the evidence which persuades you that:
1) the control knob on climate is CO2, ie that the predominant force driving global warming or “climate change” since c. 1950 has been man-made CO2,
and that:
2) this warming or change will lead to catastrophic consequences, justifying the war on coal, oil and natural gas.
Thanks.
Poor Brandon,who keeps thinking people needs to be told the obvious,over and over and over, that climate changes.
“Based on our analysis, a middle-of-the-road warming scenario is more likely, at least for now,” said Patrick T. Brown, a doctoral student in climatology at Duke University’s Nicholas School of the Environment. “But this could change.”
It sure could change….. only if Brandon doesn’t bring up his “internal Variability” claims into the front of it.
Meanwhile it is just another modeled scenario,of which has all been too common these days,especially when they are wrong at least 99.99% of the time.
How I wish they drop these overt reliance on making modeled scenarios,get back into the fields,collect actual data based on real materials, instead of computer generated models,that clearly lack demonstrated forecast skills. It is a waste of time chasing after reality, with generated,unverified mathematical exercise.
MarkW,
If you read a statement that didn’t include a time component as a qualifier, then you were likely misinformed. Far be it for you to provide a direct quote, of course.
Gloria Swansong,
I don’t personally subscribe to CO2 as THE climate control knob meme. A nuanced reading of primary literature shows it as a significant factor, but only one of many. For evidence supporting my beliefs, we can start with the plot I posted in this comment to sunsettommy: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913430
Between the radiative forcings — CO2, TSI (solar) and AOD (volcanic aerosols) — CO2 provides the best correlation to the long-term trend. That particular regression has CO2 and the Sun running neck-in neck until 1965 or so, at which point the TSI trend levelled off. Clearly the Sun has an effect (and this regression likely overstates it), but I find it impossible to argue that it has been the dominant forcing since 1950.
If you’ve got a better plausible physical mechanism to explain the post-1950 temperature rise, now would be your chance to offer it. Bonus points if you can show me a correlation which beats out CO2+TSI+AOD plus the modes of internal variability I’ve regressed for the entire 1880-2014 interval shown, a pretty tall order; R^2 for that regression is 0.85.
2) this warming or change will lead to catastrophic consequences, justifying the war on coal, oil and natural gas.
I don’t have any evidence from the future to provide you. Such a thing is not possible. My personal desire to replace fossil fuels with things like nuclear fission, geothermal and solar PV is based on a combination of near-term benefits combined with long-term risk assessments, only some of which are directly related to inferred hazards of a warming planet. The thing I’m most certain of is sea level rise, but that’s also my least concern. Near term benefits are reducing particulate pollution, reducing dependence on foreign suppliers and the associated geopolitical entanglements, and economic stimulus from the R&D and construction work involved effecting the transition.
I’m not much for “declaring war” on the industries which keep my lights on and my automobile moving. Please refrain from putting such words in my mouth. Thanks.
sunsettommy,
http://www.merriam-webster.com/dictionary/variable
variable
adjective:
a : able or apt to vary : subject to variation or changes (variable winds) (variable costs)
b : fickle, inconstant
So glad I could help.
Brandon Gates
April 21, 2015 at 5:09 pm
OK, so you don’t say “control knob”, but do say “dominant forcing” since 1950.
Your regression is not evidence. All the actual physical evidence in the world falsifies your baseless assertion.
The warming cycle in the early 20th century is no different from the warming cycle in the late 20th century. The cooling cycle from the late 1940s to ’70s occurred under rising CO2.
Please provide some actual evidence. Thanks.
If you foresee no catastrophic consequences to rising CO2, then why are you concerned about it? The models which you so admire predict catastrophically rising temperature and other evil consequences from more CO2. Why don’t you believe them?
If you favor nuclear and alternate power sources for other reasons, then why does alleged but evidence-free AGW alarm you?
Gloria Swansong,
Correct, that is how I most often see it described in literature.
I took stats. I know that correlation does not necessarily imply causation. It can, however provide a big hint.
Sorry, no. The evidence I’ve provided is entirely consistent with “my assertion”. Arrhenius predicted the radiative effect on surface temperature in 1896: http://www.globalwarmingart.com/images/1/18/Arrhenius.pdf
The main hypothesis: If the quantity of carbonic acid increases in geometric progression, the augmentation of the temperature will increase nearly in arithmetic progression.
The following formulae express that relationship:
http://upload.wikimedia.org/math/c/2/a/c2a0e92291f118a8258a19b8fa58bb07.png
http://upload.wikimedia.org/math/2/c/f/2cfca9ed59cb49f7b68570481ee87f53.png
He was wrong about the coefficients on the high side (6K/2xCO2), which he himself corrected in his 1906 paper (4K/2xCO2). Even that is seen as too high, the IPCC estimates currently range between 1.5-4.5 K/2xCO2, with 3 K still considered the most likely value even though AR5 didn’t go on record with it.
My estimate of internal variability …
http://2.bp.blogspot.com/-sCuOxDdbiXo/VTb4ffCsPgI/AAAAAAAAAb8/cEgSwN3Dik8/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BInternal%2BVariability%2BNet.png
… shows a contribution of -0.5 K over that interval, whereas I estimate that CO2 contributed +0.1. If you think the data say something different, it would please me a great deal if you showed your specific work as I have done.
I’ve already shown you mine. I told you in my first response to you that if you could provide a better explanation for the observed temperature increase since 1950 that then was your chance to do so. Your silence is resounding, not least because I’m now at a total loss as to what you consider “evidence” — and I’m not much one for doing others’ homework for them, or getting sent on “show me evidence, no that’s not evidence, show me evidence, no that’s not evidence” goose chases by people who are only going to reject everything I show them.
IOW, it’s your turn to show ME something which offers a better explanation than I’ve already provided. Capice?
I didn’t say I don’t foresee any deleterious consequences, and I’ve read about plenty. What I’m most confident about is sea level rise, but that’s my least concern. I don’t need to be convinced of catastrophic effects to have a concern about taking action in the present. I’m not an all or nothing black/white thinker. It drives me batty when people attempt to impose that mode of decision-making on me.
So far we’ve only been talking about AOGCMs. Yes, I do admire them, I think they’re incredible feats of scientific intellect and technical achievement given the scope of the system they’re attempting to simulate. But they just spit out numbers. Someone has to interpret them and decide based on their own expertise (and biases) what constitutes “catastrophic”. I reserve the right to disagree with expert opinion, but it’s not something I do lightly. The nightmarish “runaway warming” scenarios were something I was dubious of the first time I heard them, and I did reject that notion. Literature has proven me out on that, no serious investigator I know of thinks we’re headed for a Venus-like ocean boil-off.
OTOH, are we at or past the “tipping point” for “irreversible” WAIS collapse? How in the heck should I know? It isn’t my field. I think it’s plausible, but I wouldn’t stake my life on it.
You would do well to stop thinking for me; you’re terrible at it — I’m not alarmed. I’m concerned, yes. But mostly quite frustrated at what I consider slow to non-existent progress, and the fractious nature of the policy battle in the political arena. I blame both sides for this. Not quite equally mind, but I still have some sharp things to say about how the environmental left has shot themselves in the feet over the years on this issue.
“Evidence” is contested here, it’s bad form to include that as part of your “question”.
I don’t understand why my favouring of nuclear, geothermal and solar PV to fossil fuels precludes me from having concerns about AGW at the same time.
>”That particular regression has CO2 and the Sun running neck-in neck until 1965 or so, at which point the TSI trend levelled off. Clearly the Sun has an effect (and this regression likely overstates it), but I find it impossible to argue that it has been the dominant forcing since 1950.”
?w=773&h=620
TSI levelled off at the highest levels for about 11,000 yrs (the Holocene approx) according to Usoskin (2014):
Brandon Gates appears to be another thermodynamic illiterate (along with a bunch of IPCC solar specialists as Alec Rawls recounts here at WUWT) demanding an almost instantaneous atmospheric temperature response from energy input (solar) change in the sun => ocean => atmosphere(+space) system. It is considerably longer than that.
Kevin Trenberth in his essay ‘The Role of the Oceans in Climate’ states:
“An overall estimate of the delay in surface temperature response caused by the oceans is 10–100 years.”
http://www.oco.noaa.gov/roleofOcean.html
Recent study of the Antarctic (Zhao and Feng 2014) states:
“‘The millennial variation of SSN led that of T by 30–40 years.”
http://hockeyschtick.blogspot.co.nz/2014/11/new-paper-finds-strong-evidence-sun-has.html
So if we assume from PMOD that solar peaked 1986 and maintained that level through to 2005 and a 35 yr solar-temperature lag then we can expect the secular trend in temperature to peak around 2020 – 2040. Macias et al 2014 (see below) couldn’t grasp this either but at least they separated the oscillatory component from the secular trend and identified the deceleration in the latter (which immediately disqualifies CO2 as the driver).
Obviously, as solar input to the planetary system reduces there will be a thermal lag until the reduction is evident in atmospheric temperature – but that’s not for a while yet.
See:
Macias D, Stips A, Garcia-Gorriz E (2014) Application of the Singular Spectrum Analysis Technique to Study the Recent Hiatus on the Global Surface Temperature Record. PLoS ONE 9(9): e107222. doi:10.1371/journal.pone.0107222
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107222#pone-0107222-g005
richardcfromnz,
I’m using an 11 year moving average for TSI, no lag. Longer than that doesn’t significantly improve the fit, and I’ve got data going back to 1600 CE.
You’ll note that the regression coefficient is 0.29, that’s W/m^2, which is unphysical — the highest it could possibly be is 0.25 due to geometry. However, since the planet’s albedo is ~0.3, 0.075 would be more realistic.
IOW, I’m overstating solar forcing by almost a factor of 4, which I don’t have a problem doing because the main point of this exercise was to quantify internal variability and all I needed as the starting point was a reasonable fit for the secular trend as a starting point.
… but I repeat myself, which IS somewhat illiterate …
Brandon Gates
April 21, 2015 at 6:58 pm
Almost any other possible forcing, or none, fits reality better than CO2. Random fluctuations work better. The hypothesis that CO2 has been the dominant forcing on climate since c. 1950 has, as I pointed out and you ignored, been repeatedly shown false. Rising CO2 “drove” cooling from the late 1940s to ’70s and has at best “driven” no increase in temperature since the late 1990s.
A possible forcing that matches genuinely observed temperature fluctuations much better than CO2, which is easy, since CO2 usually doesn’t match at all, is solar activity, such as magnetic flux and the time integral of changes in the spectral composition of TSI, combined with oceanic oscillations. This is for multidecadal, centennial and millennial scale climatic cycles. On the order of tens and hundreds of millennia, look to Milankovitch cycles, which also operate on the shorter time frames, but obviously with less effect..
The late 20th century warming is nothing in the least bit special, so requires no special explanation. The null hypothesis has never been rejected. The CAGW hypothesis has however been falsified over and over again, and is now in the process of being so again, thanks to the plateau or cooling currently ongoing.
If you want to see a really impressive warming cycle following a pronounced cooling, check out the early 18th century, whose warming was faster, ran up more and lasted longer than the measly late 20th century cycle.
Your meaningless regression analysis demonstrates precisely nothing.
The models are worse than worthless PsoS, a gigantic, counterproductive waste of resources better spent anywhere else or not spent. Policy makers’ relying on them have cost untold lives and treasure. They are crimes against humanity.
Again, if the only concern you can muster about possible man-made warming is sea level rise not in evidence, then why are you worried at all? So far and for any likely future, more CO2 has been a great boon to the planet’s life.
“So glad I could help.”
I was being sarcastic.
Which is why I responded in kind.
Brandon, a “nuanced reading of primary literature shows” that no one knows what CO2 emissions will do to the climate, if anything at all. Climate models have zero predictive value.
Pat Frank,
The above statement is nonsensical gibberish.
@ Brandon Gates…you are missing the Big Picture. You should take your great understanding and wealth of data to the IPCC and similar minded scientists. You are at the wrong web site. You could potentially become the next Hansen, the next Big Guy that warmists fawn upon. Go and show them where they are wrong with their models and long term perspective. Go to them and show them how to win the debate on catastrophic climate change. You could be on the front page of media sites all around the globe. Obama would certainly appoint such a man to high position. All Hail, Brandon. All Hail, Brandon.
I notice that Brandon, indicate that he is unaware of what Forecast Skill is.
Rational people would by now give up the always wrong Chimps models, go one with something better,but not Brandon who seems to think they will eventually develop to the point, that even Brandon, will stop saying they run too hot.
Too bad you will not live to year 2100 to find out……..
sunsettommy,
I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores.
Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.
goldminor,
No need. Most of what I know about what’s wrong with AOGCMs comes from what the modelling community itself has told me. I read stuff, see, from the people who actually do the work itself. It’s a little thing I consider part of being well-informed.
Oh jeez, I’m blushing. Ok look, first 10 people in the queue get an autograph. After that … you lot can piss right off.
“I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores.
Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.”
Ha ha ha…
There a difference between Accuracy and Skill?
Here is the AMS definition:
“Skill in forecasting (or skill score,[1] forecast skill, prediction skill) is a scaled representation of forecast error that relates the forecast accuracy of a particular forecast model to some reference model.”
http://en.wikipedia.org/wiki/Forecast_skill
You have been repeatedly shown that Chimps (ENSEMBLE) models have never been close to the observed temperature range. I have pointed out a disparity (that is growing) of .35C in just 13 plus years. On version after another comes out, they CONTINUE to be way off and too hot.
Chimps models have a proven record of lacking BOTH accuracy and skill in their models over time. They have NEVER been accurate or show predictive skill.
Maybe That IPCC 95% Certainty Was Correct After All
http://www.drroyspencer.com/2013/10/maybe-that-ipcc-95-certainty-was-correct-after-all/
Here he shows a run of 90 CHIMP5 plotted on a chart versus temperature to show they have no predictive value to build on since chimp5 is supposed to be an “improvement” on chimp3.
By now most rational people would abandon Chimp models, as they are junk.
A professional Meteorologist certainly understand this very well,you don’t.
sunsettommy,
Yeah, pretty much what I wrote. You quoted me directly: I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores. Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.
http://www.climatechange2013.org/images/figures/WGI_AR5_Fig9-8.jpg
See the thick RED line? That’s the model ensemble mean. See the thick BLACK line? That’s HADCRUT4. Do you see how the RED line crosses the BLACK line?
How can the RED line cross the BLACK line if they’ve “never been close” to each other?
Please for your own sake, schedule an visit to an ophthalmologist. You’re not safe to walk around, so be darn sure and have someone else drive you to the appointment.
Pat frank says, “Brandon, a “nuanced reading of primary literature shows” that no one knows what CO2 emissions will do to the climate, if anything at all. Climate models have zero predictive value.”
================================
I disagree Frank. The models are highly informative in the COSISTENCY OF THEIR WRONGNESS.
Simply greatly lowering the CS to harmless levels on centurion scales makes the CIMP 5 modeled mean far closer to reality. However, as the IPCC is a political body, and all the nuance arm waving in their reports are left out of their summaries for POLICY MAKERS, do not expect them to further lower the CS and TCR of their models to match observations. Science 101 is not their strong suit.
Nominations for the person who talks the most and says the least, anyone?
I can demonstrate that, Brandon. Quantitatively.
See my post on WUWT here; see my invited 2013 AGU meeting poster, here (2.9 MB pdf); see my thoroughly peer-reviewed Skeptic article here.
I’ve been trying to publish a full paper for two years over the incompetence of climate modeler reviews and editorial cowardice. When (if) it does get published, you’ll see the reality in full glory.
But consider this, generally: errors in W/m^2 made by CMIP5 models are orders of magnitude larger than the annual increase in GHG forcing. Do you know any way an error-prone model can resolve an effect orders of magnitude below its level of resolution?
The way you describe “skill score, Brandon, as “equivalent performance to the reference model” is a merely measure of inter-model variance and has nothing to do with predictive value.
David A, lowering the CS artificially in CMIP5 models in order to get them to match observations, as you suggest, is a tacit admission that they can’t predict anything.
There is more noise on this thread than in the average global temp signal, but not wishing to be left out Brandon Gates on April 21, 2015 at 9:10 pm I trust you saw the irony in using that particular fig from the IPCC to show how good the models are in sample (ie over the period they were tuned to). The panel at the side shows just how far the modeled absolute temps are from the actual.
Clearly a number of them are modeling worlds that are quite different from ours.
Brandon, you clearly underestimated Pat Frank – by using a flippant, throwaway line in a dismissive fashion. If you read his/her posts, you’ll see that he/she is more than a match for you. The worst thing you can do while conversing is to underestimate your opponent. I have often waded into forums with estuary English and a ‘what if’ approach on purpose, in order that those I will argue against underestimate me. You can then devastate them with a reasoned and logical position. It’s a tactic that works well.
Brandon Gates
You write
and
I refer everyone to my above post here where I copy my earlier refutations of your nonsensical twaddle including this refutation of your idiocy that I quote in this post.
I again copy this comment which is in my above linked post but was there copied from another WUWT thread where you previously spouted your untruths.
Brandon Gates, trolls like you ignore corrections because you know you are promoting falsehoods. But I am getting tired of your repeating the same irrational nonsense over and over again despite my explaining reality to you again and again.
Richard
Pat Frank,
Ok, read all that. From your WUWT article, I take it the crux of your argument is this:
Please explain why the uncertainty envelopes in Panel B start circa 2000 instead of 1850.
When I want to talk about inter-model variance, I’ll talk about inter-model variance. I wrote, and meant, skill score (SS) as in forecast (or hindcast) skill, calculated as follows:
http://upload.wikimedia.org/math/f/5/4/f5471a5bde0020f137c1a8690f5ce2fe.png
Where MSE is mean squared error:
http://upload.wikimedia.org/math/c/b/0/cb039e2292e9ab1cb2ae8e4ffbcb6579.png
A reference model used in a forecast skill calculation can be anything one chooses. Your “passive warming model” (PWM) is an example of something which could be used as a reference model, which is conceptually how I understand you have used it.
richardscourtney,
How does one “determine” a model’s “accuracies and precisions”?
I subscribe to the following philosphy of models: Remember that all models are wrong; the practical question is how wrong do they have to be to not be useful. ~George E. P. Box, Empirical Model-Building and Response Surfaces (1987), p. 74
I cannot make you accept it, nor “prove” that it is correct, so I shan’t attempt to do either.
Forecast (or hindcast) skill is a technical term which does indeed compare model output to empirical observation. However, a skill score as I am using the term here, necessarily includes comparison to a reference model which can be anything one chooses. The basic formula for skill is:
http://upload.wikimedia.org/math/f/5/4/f5471a5bde0020f137c1a8690f5ce2fe.png
Where MSE is mean squared error:
http://upload.wikimedia.org/math/c/b/0/cb039e2292e9ab1cb2ae8e4ffbcb6579.png
That’s not what I’m talking about when I write about forecast skill as defined above. It would please me if you didn’t insert your talking points into a discussion where they do not directly address my substantive arguments. Thanks.
Please show your work.
The Ghost Of Big Jim Cooley,
Interesting that you claim to know the outcome of the discussion even though it’s only just gotten underway.
HAS,
Not at all. The individual model runs are difficult to pick out in that plot, but the ensemble mean is quite faithful to multi-decadal trends. There are notable deviations in the hindcast, 1905 to 1945 for instance — the ensemble mean ran up to 0.25 K hot.
Why do you presume that the “actual” asbolute temperature estimates are accurate?
Brendon, bit of advice if you don’t understand something ask.
The panel on the right in the figure above that you copied and pasted here from Fig 9.8 of IPCC AR5 WG1 shows, to quote the caption that you left behind: “Inset: the global mean surface temperature for the reference period 1961–1990, for each individual model (colours), the CMIP5 multi-model mean (thick red), and the observations (thick black: Jones et al., 1999).”
Thus it has nothing to do with the “individual model runs .. in that plot”; or the “ensemble mean” (whatever that indicates) and “multi-decadal trends”; and don’t require me to worry about the accuracy of the absolute temperature estimate (there is only one, and as the caption says it comes from via Jones et al).
What it says is we are using models that model (in sample) the 1961-1990 global temperature over the range of 12.6-15.4 C in the case of CIMP5 and 13.2-18 C for EMIC.
If you don’t know what the problem with that is, think non-linearity in the climate, think phase changes, and think as I said before, how different a planet they are each modelling.
Simple, Brandon; the uncertainty envelopes start at 2000 instead of 1850, because I began propagating the error from 2000.
Starting the error propagation from 1850 produced such huge uncertainty bars that they defeated the illustrative purpose of the graphic. Starting the error propagation from a later date does nothing to invalidate the method.
The core demonstration of that graphic is that climate models project future air temperature merely by linear extrapolation of GHG forcing. That makes them vulnerable to linear propagation of error. There’s no way around that.
You wrote, “When I want to talk about inter-model variance, I’ll talk about inter-model variance”
Let’s remember what you actually did write, Brandon: “I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores. Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.
You clearly described “skill score” as inter-model variance – “performance to the reference model” — and equated that to predictive value. Side-stepping your own argument is not allowed.
In your equation, mean squared error is, in fact, the definition of variance. So, you have now denied that skill score means inter-model variance, and then redefined skill score to mean inter-model variance.
The PWM was used to demonstrate that climate models linearly extrapolate GHG forcing. It’s not a reference model, in your sense, at all.
Further, intermodel variance is no definition of error. Error is the difference between a model expectation value and the relevant observable. Inter-model variance, or your SS = 1-(MSE ratio), is no physical error metric and may have no particular physical relevance at all.
I believe Richard Courtney has told you this repeatedly. You should pay attention, because he’s right.
Brandon, you didn’t define MSE as referring to the difference between model output and observation until your reply to Richard Courtney.
Even so, your skill score is almost useless because it just defines how well one arbitrary model does relative to another arbitrary model. One can invert your relationship and get something equally meaningful, or substitue other reference models and have skill score migrate through all sorts of values. There’s no obvious point.
More relevantly, climate models are tuned. Their parameters are chosen to reproduce the target climate. Reproduction of the target climate observables then becomes an exercise in off-setting errors.
The difference statistics relative to observables then become almost meaningless, because reproduced target climate observables provide no guarantee that the model is reproducing the underlying physics. MSE then tells one nothing about the physical validity of the model. Under those conditions, skill scores impart nothing of physical interest.
All of climate modeling, these days, is mere wheel-spinning of that sort.
Pat Frank,
No? You wrote: Typical error bars for CMIP5 climate model projections are about ±14 C after 100 years and ±18 C after 150 years.
1850-2000 is a span of 151 years yes? So if you’d started the propagation at 1850, at the year 2000 the expected error would be ±18 C.
Please describe for the class what the actual error is as of the year 2000.
Putting words in my mouth isn’t either.
You don’t say. The key question is: variance from what?
It’s not my definition.
I said it could be used as one. And I contend that’s exactly how you’ve used it: http://www.skeptic.com/reading_room/a-climate-of-belief/
Along with the GCM projections, Figure 2a shows the trend from a very simple model, in which all that happens is passive greenhouse gas warming with no climate feedbacks at all. Nevertheless, for all its inherent simplicity, the passive warming line goes right through the middle of the GCM trend lines.
This result tells us that somehow the complex quintillion-watt feedbacks from the oceans, the atmosphere, the albedo, and the clouds all average out to approximately zero in the General Circulation Models. Apart from low intensity wiggles, the GCMs all predict little more than passive global warming.
Emphasis mine because, well, I believe it more or less torpedoes your main argument about physical error propagation in AOGCMs. That is … if it’s still floating after the first broadside I put into it above.
Is MSE a physical error metric by your definition or not? Again from your Skeptic.com article:
With that in mind, look again at the IPCC Legend for Figure SPM-5. It reports that the “[s]hading denotes the plus/minus one standard deviation range of individual model annual averages.” The lines on the Figure represent averages of the annual GCM projected temperatures. The Legend is saying that 68% of the time (one standard deviation), the projections of the models will fall within the shaded regions. It’s not saying that the shaded regions display the physical reliability of the projections. The shaded regions aren’t telling us anything about the physical uncertainty of temperature predictions. They’re telling us about the numerical instability of climate models. The message of the Legend is that climate models won’t produce exactly the same trend twice. They’re just guaranteed to get within the shadings 68% of the time.
Is that what you think I mean when I speak of skill scores as defined by these formulae?
http://upload.wikimedia.org/math/f/5/4/f5471a5bde0020f137c1a8690f5ce2fe.png
Where MSE is mean squared error:
http://upload.wikimedia.org/math/c/b/0/cb039e2292e9ab1cb2ae8e4ffbcb6579.png
I’ll hold my own counsel about whom I pay attention to. Thanks.
Just another couple of little contributions to the noise.
First, GCM runs under CIMP5 aren’t predictions, forecasts, etc. They are projections. They say given this model and these set of assumptions (eg RCPs) this will be the outcome.
The question of skill doesn’t arise in the sense that it seems to be being used here. The way to evaluate projections is usually to judge their accuracy, and this is typically done by using the actual values of the assumptions and seeing if given that how the results compare.
Second, data mining to find a correlation (say between temps and CO2) is fun, but it isn’t statistical analysis. Postulating physical relations and evaluating a model of them from time series requires: (1) postulation of the model in terms that makes sense physically and then embodying it in formal relationships; (2) a careful analysis of the series to ensure they are well behaved for the tools that are planned to be used for the analysis nd transforming them so the structure fits the physical model and the tools available for analysis; (3) analysis to deduce the structure/estimate parameters holding out data so you can do the final stage (4) testing the model out of sample.
The paper that is the subject of this post shows some of the complications in doing all this.
HAS
April 22, 2015 at 6:30 pm
Except to show that CO2 is not the control knob on climate, GCMs have less than no utility. Money spent on them is a prime example of waste, fraud and abuse by the government-academic-Green industrial complex.
The “projections” are sold as predictions in order to extort more moolah and try to frighten the citizenry into surrendering their liberty yet further to tyranny. Anyone participating in this hoax is complicit in mass murder and theft on the grandest of scales.
I hope that there will be a fearful reckoning, but doubt it, given complicity of media and regimes around the world in the anti-human conspiracy.
HAS,
Reading ahead, your contributions don’t look like noise to me at all.
Thank you for raising that point, I have alluded to the difference between a projection based on some set of future assumptions and a prediction based on initial conditions elsewhere; just haven’t specifically discussed it. I have learned the hard way that going there will often be seen as a semantic argument: http://wmbriggs.com/post/13252/
I gave that particular thread a miss because I just didn’t feel like incurring the brain damage.
In the context of discussing The Pause, I will stipulate that the assumed parameters in each scenario between 2006 and present in each RCP are so close to each other, and so close to observed values, that the prediction/projection distinction is effectively moot. Talking about GMST in 2100, different ball of wax: those ARE projections based on four different scenarios, each with their own set of assumptions, NOT predictions. They’re “what if” estimates.
Well, careful there. Judging accuracy implies that we have some actual observation to compare to. We can’t do that for a projection of GMST in 2100 because that’s 85 years from now.
That’s kind of a broad definition of data mining combined with a rather narrowish definition of statistical analysis in my book. I’d say the weakest link in my multiple regression analysis is the LOD time series because the plausible physical mechanism there is not well-established in literature. I only know of three researchers actively working on it, two have published but not in major journals. One, Vaughan Pratt at Stanford has done two AGU posters, and I believe he’s got a paper in the works. Everything else are off-the-shelf boilerplate climate parameters with well-documented characteristics, and in the case of CO2, very well-documented physical causality.
I agree. I have disclosed elsewhere that the regression coefficient on TSI of … what is it … 0.28 is not well-behaved in the sense that it’s completely unphysical. 0.25 is the highest it could possibly be due to the spherical geometry of the planet, multiply by Earth’s albedo of 0.3 and we get 0.075. In my haste, I neglected to mention we should multiply again by 0.8 (the canonical climate sensitivity parameter for any radiative forcing) which brings it down to 0.06. With the sensitivity parameter in there, that’s an equilibrium response, mind.
It turns out that if I use a trailing 12-month moving average instead of 132 months, the TSI regression coefficient drops to 0.0803, which is believable; however, it destroys the good fit in the rest of the model. I suspect one reason is that AMO and ENSO, which I also use, contain some component of solar variability over the 11 year cycle already.
I’m not trying to do publication-quality work here. This model is my own self-teaching tool, and I share it as a way of saying, “I’ve looked at this myself in a very back of napkin way, and it’s broadly consistent with what I’ve read about here [citation] in literature.”
Indeed. That’s one reason why I’m dubious of Dr. Frank’s strong conclusions. They mainly hinge on the variance between observed and modelled cloud fraction, I believe for the entire atmospheric column. From there he calculates a theoretical downward LWR flux from models and observations to come up with his +/-4 W/m^2. It’s no mystery to me why he hasn’t gotten that published, and no, it’s not because the modelling community doesn’t want to hear it:
http://link.springer.com/article/10.1007%2Fs00382-014-2158-9
http://www.atmos.washington.edu/socrates/presentations/SouthernOceanPresentations/Session3/Dolinar.pdf
I’m more inclined to believe that they really do want to hear about it, but from someone who demonstrates a tad bit more knowledge about the actual innards of an AOGCM. And it’s not like Dolinar, et al. have better news:
The multimodel ensemble mean CF (57.6 %) is, on average, underestimated by nearly 8 % (between 65°N/S) when compared to CERES–MODIS (CM) and ISCCP results while an even larger negative bias (17.1 %) exists compared to the CloudSat/CALIPSO results.
A structural bias like that is a far cry from a +/-4 W/m^2 essentially “random” error.
HAS,
Bit of advice by way of basic logic; if I completely don’t understand something, it might not occur to me to ask about it.
Yup, that’s what I understood you to be referring to.
Way ahead of where you apparently think I am: http://www.realclimate.org/index.php/archives/2014/12/absolute-temperatures-and-relative-anomalies/comment-page-1/#comment-621580
Brandon, I’m going to skip your gratuitous snark.
You wrote, “No? You wrote: Typical error bars for CMIP5 climate model projections are about ±14 C after 100 years and ±18 C after 150 years.
“1850-2000 is a span of 151 years yes? So if you’d started the propagation at 1850, at the year 2000 the expected error would be ±18 C.
“Please describe for the class what the actual error is as of the year 2000.”
You originally asked about the graphic, Brandon, i.e., “Please explain why the uncertainty envelopes in Panel B start circa 2000 instead of 1850.,” not about my entire analysis. Starting from 1850, the uncertainty at the year 2000 is (+/-)18 C, as I noted. Back of the class for you.
Note that the projections in the graphic go to 2150, a full 300 years after 1850. The 2150 uncertainty bars, propagated from an 1850 start, are about (+/-)25 C.
You wrote, “You don’t say. The key question is: variance from what?” In your original post, your “what” was a “reference model.” You made no mention at all of an observational standard. There was no reference of an observational standard in your follow-on post, either.
An observational reference appeared only in your third attempt, in reply after Richard Courtney brought up the need for an observational standard. Maybe you had that standard in mind, all along. But you never mentioned it until pressed.
You wrote, “I said [your PWM] could be used as [a reference model]. And I contend that’s exactly how you’ve used it:. You’d be wrong. Twice. First, the PWM is never represented as a model of climate. Therefore, it cannot by definition be used as a reference climate model. Second, I never used the PWM as a reference model in any “skill score” sense.
You wrote, “Emphasis mine because, well, I believe it more or less torpedoes your main argument about physical error propagation in AOGCMs.”
If you think the sentence you bolded has anything to do with error propagation as such, then you know nothing of the subject.
If you think it refers to using the PWM as a climate model, or as a “skill score” reference model, then you’re revealed as pretty clueless about the expressed logic.
The logic of that sentence is the PWM demonstrates that GCMs merely linearly extrapolate GHG forcing when projecting air temperature. Mere linear extrapolation means that all other effects must be taken to average out to zero impact. Ecce the bolded sentence, Brandon. How complex is that to figure out?
Consider paragraph 2 in the Supporting Information of the Skeptic article: “The passive warming model is derived in SI Sections 1 and 2. The goal was to test outputs of GCMs, and no claim is intended about the actual physical behavior of climate.”
There it is, stated outright, right at the beginning.
You didn’t think to consult the Supporting Information, did you. The PWM is presented as a GCM emulator, not as a climate model. It’s not usable as a reference model and was never used by me, ever, as a physical reference model. I would never advise anyone to use it as a reference model. It would be wrong to use it as a reference model. It was used to demonstrate how GCMs project air temperature; a GCM emulator.
Your supposed broadside is not only 180 degrees out, it’s not a broadside. It’s a misfire.
You wrote, “Is that what you think I mean when I speak of skill scores as defined by these formulae?”
As already noted, you did not reference MSE to an observational standard until your third post. What you mean now may have been what you meant in posts 1 and 2, but there’s no evidence to suggest that is the case. Because you were completely absent on what you meant; apart from reference model.
If you want to be understood a certain way, Brandon, then it would seem wise to fully explicate what you mean, wouldn’t it. You didn’t do that, however. No one here should have to spend any time deciding whether you meant something other than what you wrote.
Pay attention, or not, to what Richard Courtney wrote; whichever way you go, he will still have been correct.
Brandon
Yes, agreed, you might have not thought you didn’t understand. From your comments here I can see how that could arise.
I’m also not surprised you then go on to tell me you understood exactly what I was referring to having indulged in a complete non-sequitur in your previous response.
As you say to someone called Gavin in the comment you link to:
“Where can an avid but amateur hobbyist such as me go … “
That is indeed the question.
milodonharlani
The models are useful, more particularly for studying interrelationships in the climate which is what they first were developed for. The problem has been their overuse to understand future climate states.
Collectively they aren’t worth the amount that is being invested in them, and the immediate challenge is to reduce the number that are being developed and use the money so released for other things.
If you are in the US you could usefully lobby to reduce the amount going into modeling by 1/3 and only have one national team working on it. I’m pleased to say that where I live we don’t have a model – we worry about sensible things like reducing subsides on fossil fuels http://www.mfat.govt.nz/fffsr/
HAS,
“We fundamentally disagree, so you must not know anything” is not an atypical hypothesis.
Speaking in ambiguities is the oldest rhetorical trick in the book, and I’m fond of giving people who do it to me the run around. Truth is, and this you’ll never know for sure, is that I wasn’t exactly sure what you were driving at, but I did guess “wrong” on purpose because actually I consider my original response NOT a non sequitur — global absolute surface temperature is a highly uncertain estimate, one reason why anomalies are so popular.
That would be my one and only conversation with Gavin Schmidt. I spend most of my online time right here at WUWT or scouring data repositories for interesting numbers to play with. What’s your point?
Brandon Gates
Please try to pretend you are not an obscurantist idiot.
I have repeatedly written in this and other threads
THOSE ARE CLEAR STATEMENTS OF SCIENTIFIC MODELLING PRINCIPLES.
However, you have – at last – replied here but with (deliberate?) idiocy that begins
Brandon, if a model provides outputs that have no known associated estimate of their accuracy and precision then those outputs are meaningless because those outputs could be any of all values between -infinity and +infinity.
However, that was not my point. Measurements of reality provide indications that have determined accuracies and precisions. The model is wrong if the model’s predictions do not agree with the measurements to within the accuracies and precisions of the measurements.
Not content with that nonsense, your reply continues
Well if “all models are wrong” then they cannot be useful because their wrong results mislead. Of course, warmunists want to mislead so I can see why you subscribe to that mistaken “philosphy” (sic).
In reality, the usefulness of a model is a function of the model’s purpose. And the accuracy, precision and reliability of the model outputs determines if the model is ‘fit for purpose’.
However, you rely on a quote so I shall, too, and my quote is more cogent.
My quote is, “I’m smarter than the average bear” and is by Yogi Bear.
As you said to me about your quote, I cannot make you accept it, nor “prove” that it is correct, so I shan’t attempt to do either.
You continue with more idiocy by repeating your claim that forecast skill of a model is assessed by comparison with another model. No, Brandon, outside of any insane asylum a model of reality has its forecast skill assessed by comparing its forecasts to outcomes of reality and NOT other models.
Clearly, you don’t understand that forecast skill is about ability to make forecasts and is independent of inter-model comparisons.
You conclude by quoting my having said
then asking me
I DID “show [my] work”.
My statement you quote is the final sentence of the paragraph which explains it, and it is the conclusion from my “work”.
Brandon, please try to act like a grown up. It is galling to need to e.g. provide quotes from cartoon characters to demonstrate that your ‘arguments’ are merely untrue assertions.
Richard
richardscourtney,
I agree, with the the additional criterion that a model cannot be expected to deliver better results than its stated design parameters.
Ok good, now I understand better what you meant about accuracies and predictions. Thank you for elaborating.
It’s galling to be held to a higher standard of proof than the person making sweeping insinuations about my alleged dishonesty. How about you pony up a quantified estimate of CMIP5 performance relative to observational precision and accuracy, and thereby complete the question you’ve raised in the previous quote block? Please try to leave the chicken bones out of it this time.
Pat Frank,
I repeat: Please describe for the class what the actual error is as of the year 2000.
Um, ±18 C — the figure I stated — is the correct answer according to you.
It’s implicit in the term “forecast skill”, which sunsettommy introduced to the discussion in this post: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913570
I’ve been using his provided definition ever since because I happen to both understand and agree with the utility of calculating skill scores. I like quantified statements of wrongness, see? It’s something my high school chemistry teacher drilled into me, among many, many others. I think skill scores are particularly useful because they provide a comparative to some reference standard, which helps me make decisions.
Note my intentional change in terminology from “reference model” to “reference standard”. I consider those functionally equivalent terms; however, in the interest of disambiguating meaning, I’m content to use the latter term going forward.
HAS
April 22, 2015 at 11:23 pm
I agree with your sensible suggestion about reducing modeling expenditure & have indeed discussed with members of Congress & their staffs the possibility of shutting down GISS completely.
NCAR is another matter. CO is a swing state, so probably would be politically impossible, although I have raised the idea of shutting it down, too (it got its start because of availability of a supercomputer), & folding its legitimate operations into the National Snow & Ice Data Center, also in Boulder.
IMO it’s simply too early in the history of climatology realistically to model climate, so it’s all bound to be a waste. It reminds me of the money wasted early in the War on Cancer, when despite dollars thrown at the problem, the basic science just wasn’t ready yet.
Brandon Gates
In response to my line-by-line demolition of your childish and stupid twaddle you have written
I have made no “insinuations” (be they “sweeping” or otherwise) about your honesty.
I have objected to your thread bombing with posts which display idiocy, evasions, irrelevance and childish assertions.
Indeed, your daft posts indicate that you lack sufficient intellectual ability for those posts to have been generated by “dishonesty” and, therefore, I am convinced that you are as stupid as you proclaim yourself to be.
Richard
richardscourtney,
In my previous post I asked of you: How about you pony up a quantified estimate of CMIP5 performance relative to observational precision and accuracy, and thereby complete the question you’ve raised in the previous quote block?
You end your reply with:
I really must be a moron because for the life of me I cannot figure out how any of your response has anything to do whatsoever with the question I posed.
Brandon Gates
You ask me
I answer:
Total failure as predictive tools according to every metric.
But you don’t slither away that easily.
I yet again ask you
Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.
And I ask if you will confirm that all your failures to answer that request demonstrate
what you call “internal variability” is an undefined excuse for all disagreements of the models with reality. In other words, your “internal variability” is magical mystery.
Richard
richardscourtney,
That’s not a quantified estimate, just more empty rhetoric in the form of another sweeping assertion. A silly one as well. This subthread started out with you giving a somewhat reasonable criterion for model utility: that its predictions fall within the bounds of observational uncertainty. Now you’ve saddled yourself with an extraordinarily difficult burden of proof, namely that CMIP5 models fail according to every imaginable metric. Good luck substantiating that one.
Good grief, Courtney, it’s getting rather tedious having the same conversation with you in three different places. As of the time of your writing, my latest response to that question was found in this post: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1915532
The least I can say is that the conversation subsequent to that is progressing somewhat; as such I’m now off to address your response there.
Good morning.
Brandon, you wrote, “I repeat: Please describe for the class what the actual error is as of the year 2000.”
Your question is meaningless, Brandon. Propagation of error yields an uncertainty, not a physical error. I’m presuming physical error is what you mean by “error.” Back to the back of the class.
Here’s the real meaning of the (+/-)18 C uncertainty obtained when (+/-)4 W/m^2 average cloud forcing error is propagated from 1850: the GCM-projected year 2000 air temperature has no physical meaning.
That’s because the GCM-inherent theory-bias error means the underlying physical behavior is wrongly expressed within the model even if the projected air temperature itself is close to the observed temperature. And the reason for that last, Brandon, is that tuned models merely hide their internal error. They do not produce physically unique solutions, and so cannot produce predictions in any scientific sense of that word.
You wrote that you’ve “been using [sunsettommy’s] provided definition of forecast skill, and provided this link as evidence. Except the linked comment provides no definition, implicit or otherwise, of an observational standard. It appears, to haul your chestnuts out, you’re reduced to making things up.
So, we’re back to you having never mentioned an observational standard until your third post on forecast skill in reply to Richard Courtney. As noted previously.
You wrote, “I like quantified statements of wrongness, see? It’s something my high school chemistry teacher drilled into me, among many, many others,” which brings us back to the meaning your [1-MSE ratio] as forecast skill score.
Let me try and express it plainly: a tuned model, with its hidden and off-setting parameter errors and theory bias, can not produce a unique solution to the climate energy-state. It therefore does not make physically valid predictions.
This means that the usual error metric — data minus model expectation value — is a false metric when derived using a climate model. The reason should be obvious. Any given climate model expectation value is only one among the very many model expectation values inherently possible, but left unrealized and unexpressed.
Your MSE, the mean squared error, is therefore not an error at all, when derived from any climate model study. It’s instead the difference between a non-unique solution, chosen from a huge array of other possible expectation values but tendentiously produced by tuning, and an observation.
As climate model MSE is not a physical error in any scientific sense, your “forecast skill” is not the [1-MSE ratio] you offered. Instead, it’s [1-MSFE ratio], where FE is ‘fake error.’ It’s a standard of consensus climatology, to leave the telling “F” out of their presentations to make it all look more scientific.
Forecast skill score as used by climate modelers is just one more false indicator in their enormous armamentum of false precision metrics.
So you should have paid closer attention to what your high-school chemistry teacher tried to teach you. Error is only physical error when the comparative physical results are unique and accurate.
You wrote, “I’m content to use the latter [reference standard] term going forward.”
You’ve got nowhere left to go, Brandon. Your entire position has collapsed. You were wrong about the meaning of the PWM (it’s not, and never was, a reference model), you misinterpreted uncertainty as “error” in Figure 1 of my post showing climate modelers are not scientists, and you missed the fakery inherent in a “forecast skill score” that in fact does not include anything that can be called a physically meaningful forecast; at least not if one is interested in actual science.
You’ve got no forward to go to.
Richard C. Courtney writes, in reply to Brandon:
“You continue with more idiocy by repeating your claim that forecast skill of a model is assessed by comparison with another model. No, Brandon, outside of any insane asylum a model of reality has its forecast skill assessed by comparing its forecasts to outcomes of reality and NOT other models.”
I keep waiting for Brandon to figure out the obvious here, that to determine if a model can be validated,it FIRST has to have support from the subject,the model was written for,in this case temperature data from Satellites, a real world test.
I posted specific IPCC temperature modeling projection scenarios (good or bad in themselves),then posted the actual temperature data from HadCrut4 and RSS showing a very large disparity from what was modeled from what is actual for the time frame.
The 2007 IPCC Report quote:
“For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios. Even if the concentrations of all greenhouse gases and aerosols had been kept constant at year 2000 levels, a further warming of about 0.1°C per decade would be expected.”
A .30C warming per decade “would be expected”
First decade results from official temperature data:
http://www.woodfortrees.org/plot/hadcrut4gl/from:2001/to:2011/plot/hadcrut4gl/from:2001/to:2011/trend/plot/rss/from:2001/to:2011/plot/rss/from:2001/to:2011/trend
First decade result is about NO WARMING trend.
The 13 plus years:
http://www.woodfortrees.org/plot/hadcrut4gl/from:2001/to:2015.3/plot/hadcrut4gl/from:2001/to:2015.3/trend/plot/rss/from:2001/to:2015.3/plot/rss/from:2001/to:2015.3/trend
Adding three more years shows the same result,with some slight cooling indicated.
Instead of about .35C warming ,we see it is about .00C instead.
To me this is convincing evidence, that the projected temperature models, are worthless as the margin of failure rate is very large.
Since Brandon, himself has stated more than once that Chimps models runs too hot,therefore wrong, HE should have ended it right there and gone on leaving those failed models in his wake.
Pat Frank,
!!!!
Where’s the fire then?
Ah, it’s all the OTHER things they’ve tuned which are the actual problem.
Ok. How many different parameters are adjusted during such tuning exercises? How many of them inform your uncertainty estimates? Thus far, I’m only counting one: downwelling LW based on a theoretical calculation based on cloud fraction.
Pardon me for saying so, but your, um, analysis is beginning to look rather … er … incomplete. And you do realize you’ve been scooped, don’t you?
http://link.springer.com/article/10.1007%2Fs00382-014-2158-9
http://www.atmos.washington.edu/socrates/presentations/SouthernOceanPresentations/Session3/Dolinar.pdf
The multimodel ensemble mean CF (57.6 %) is, on average, underestimated by nearly 8 % (between 65°N/S) when compared to CERES–MODIS (CM) and ISCCP results while an even larger negative bias (17.1 %) exists compared to the CloudSat/CALIPSO results.
An 8-17% bias sounds like something that could throw a 150 year projection out of whack whereas a propagated (+/-)18 C theoretical uncertainty which leaves the projection itself almost dead center after 150 years of hindcast sounds more like …. zzzzzzzzzzzzzzz …. by comparison.
Funny how the truly bad news made it past peer review and into a reputable journal while you’re still jogging the blog circuit, innit.
Time for tale of the tape:
Brandon Gates
April 21, 2015 at 6:06 pm
Pat Frank,
Climate models have zero predictive value.
The above statement is nonsensical gibberish.
sunsettommy
April 21, 2015 at 7:21 pm
I notice that Brandon, indicate that he is unaware of what Forecast Skill is.
Rational people would by now give up the always wrong Chimps models, go one with something better,but not Brandon who seems to think they will eventually develop to the point, that even Brandon, will stop saying they run too hot.
Too bad you will not live to year 2100 to find out……..
Brandon Gates
April 21, 2015 at 7:30 pm
sunsettommy,
I notice that Brandon, indicate that he is unaware of what Forecast Skill is.
I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores.
Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.
sunsettommy
April 21, 2015 at 8:09 pm
“I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores.
Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.”
Ha ha ha…
There a difference between Accuracy and Skill?
Here is the AMS definition:
“Skill in forecasting (or skill score,[1] forecast skill, prediction skill) is a scaled representation of forecast error that relates the forecast accuracy of a particular forecast model to some reference model.”
http://en.wikipedia.org/wiki/Forecast_skill
In my very next post, April 21, 2015 at 9:10 pm, I replied: Yeah, pretty much what I wrote. You quoted me directly: I know that a skill score of zero indicates equivalent performance to the reference model. I also know that choice of reference model affects skill scores. Hence: no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.
Notes:
1) The first mention of “forecast skill” in this thread is: sunsettommy, April 21, 2015 at 7:21 pm, “I notice that Brandon, indicate that he is unaware of what Forecast Skill is.”
2) It is in the context of discussing your statement: “Climate models have zero predictive value.”
3) sunsettommy, not me, therefore introduced the concept of “forecast skill” to your statement.
4) Once again, the link to the wikipedia article on forecast skill reads in its entirety as follows:
Skill in forecasting (or skill score,[1] forecast skill, prediction skill) is a scaled representation of forecast error that relates the forecast accuracy of a particular forecast model to some reference model.
Mean squared error:
http://upload.wikimedia.org/math/c/b/0/cb039e2292e9ab1cb2ae8e4ffbcb6579.png
Forecast skill (SS):
http://upload.wikimedia.org/math/f/5/4/f5471a5bde0020f137c1a8690f5ce2fe.png
A perfect forecast results in a forecast skill of 1.0, a forecast with similar skill to the reference forecast would have a skill of 0.0, and a forecast which is less skillful than the reference forecast would have negative skill values.[2][3]
5) Reference [1] from the Wikipedia article links to the AMS glossary. They define skill this way: http://glossary.ametsoc.org/wiki/Skill
skill
A statistical evaluation of the accuracy of forecasts or the effectiveness of detection techniques.
Several simple formulations are commonly used in meteorology. The skill score (SS) is useful for evaluating predictions of temperatures, pressures, or the numerical values of other parameters. It compares a forecaster’s root-mean-squared or mean-absolute prediction errors, Ef, over a period of time, with those of a reference technique, Erefr, such as forecasts based entirely on climatology or persistence, which involve no analysis of synoptic weather conditions:
http://glossary.ametsoc.org/w/images/2/29/Ams2001glos-Se28.gif
If SS > 0, the forecaster or technique is deemed to possess some skill compared to the reference technique.
Emphasis added.
Please point out to me where any of my statements about forecast skill in this thread have been inconsistent with these definitions. Thank you.
All that is covered by the definitions which sunsettommy, not me, provided. Had either you or Richard bothered to review HIS link to the definition, I would not have had to enlighten either of you — he and I already knew what we were talking about. So nice of him to correct you himself when he was the one who brought forecast skill into it in the first place, isn’t it.
That should just about wrap up the discussion of skill scores.
End.
Brandon, your most recent post is so mindless, it’s almost not worth responding to it.
You wrote, “!!!! Where’s the fire then?” concerning the lack of physical meaning in a CMIP5 projection. Incredible. That is the fire, Brandon. That’s been the fire all along: GCM air temperature projections are physically meaningless.
Which, in turn, means that your appeals to GCM outputs as evidence here, and here, and especially here and here and here are physically meaningless.
You wrote, “Ah, it’s all the OTHER things they’ve tuned which are the actual problem.”, a complete substantive non-sequitur, followed by another one, “Ok. How many different parameters are adjusted during such tuning exercises?”
Think on this, Brandon: the 4 W/m^2 LWCF error I propagated is, all by itself, enough to show that CMIP5 climate models are predictively useless. LWCF error amounts to a lower limit of error. That lower limit is enough to prove the point. For the purposes of that analysis, what reason is there to find more sources of error? They won’t change the conclusion.
Your question has no substantive force. It’s like a debater responding with, “Oh, yeah?” to a fatal point. Nothing. Your question is clearly either: 1) an indication that you don’t at all know how to think about physical error, or; 2) you plain don’t know what we’re talking about.
You wrote, “How many of them inform your uncertainty estimates? Thus far, I’m only counting one: downwelling LW based on a theoretical calculation based on cloud fraction.”
It’s actually upwelling long wave. But in any case, LWCF error is not an adjusted parameter, Brandon. Nor is it a theoretical calculation. It’s the difference between the cloud fraction projected by CMIP5 models and the observed cloud fraction. That should have been clear, just on reading the title of reference [1] in my prior post about climate modeler incompetence concerning physical error.
You wrote, “Pardon me for saying so, but your, um, analysis is beginning to look rather … er … incomplete.”; an admission that you’re clueless.
You wrote, “And you do realize you’ve been scooped, don’t you?” linking to this paper.
That paper nowhere propagates physical error through GCM projections. How could it possibly scoop my result?
I know Jonathan Jiang, one of the authors, and have met him. He’s a nice guy. He sent me a preprint of that paper. He has also provided me with data. He was the scientist who invited me to present my poster (2.9 MB pdf) at the Fall 2013 AGU conference. You’re clueless again, Brandon.
You wrote, “An 8-17% bias sounds like something that could throw a 150 year projection out of whack…”
And so it could. Making entirely meritless all your references to GCM outputs as evidence. You’ve just defeated your own position, Brandon; a great own goal, here for all to see.
You continued, “ … whereas a propagated (+/-)18 C theoretical uncertainty which leaves the projection itself almost dead center after 150 years of hindcast sounds more like …. zzzzzzzzzzzzzzz …. by comparison.”
Thanks for another incredible, Brandon, showing everyone you think that a ~2 C projection result at the center of a (+/-)18 C uncertainty envelope actually has some physical meaning. Truly incredible.
Someone can correct me here, but I see your comment as evidence that both items, 1) and 2) above, are together the correct choice: you both have no idea how to think about physical error, and you’ve also no idea what we’re talking about.
You wrote, “Funny how the truly bad news made it past peer review and into a reputable journal while you’re still jogging the blog circuit, innit.”
Leave it to you to gather shadenfreude from the workings out of incompetent reviewers and frightened journal editors. The small-minded must take their joys where they can. Politics is their usual serving platter.
Here’s an idea that might be new to you: in science, the validity of an analysis depends only on its internal content. It depends in no way upon the opinions of those others nor, for that matter, on the mindless smirks of an opportunistic gloater.
You wrote, “Time for tale of the tape:” followed by lots of conversational blah about forecast skill. The issue, of course, was when you referred to an observational standard. You didn’t mention it at all until your response to Richard Courtney, no matter that you’re now trying to CYA by citing a Wiki article that you had neither cited nor mentioned in any of those earlier posts.
You wrote, “sunsettommy, not me, therefore introduced the concept of “forecast skill” to your statement.”
Here’s the original sunsettommy citation you posted to me, Brandon: [An observational standard is] implicit in the term “forecast skill”, which sunsettommy introduced to the discussion in this post: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913570
Go there yourself. There’s no definition of forecast skill in that post. Now you allow that, well, it was a different sunsettommy post. But that doesn’t matter does it. Because the point was when you referenced an observational standard. Nor is there any evidence in your subsequent posts about forecast skill, here and here, that you knew it included an observational standard for the reference model.
Further, your reply to sunsettommy, that “no predictive value (on the basis of a skill score) is nonsensical gibberish because it lacks key information about what model was used for the reference.” shows that you misunderstood my analysis from the start. Forecast skill score played no part in it. There was no reference model, nor was there any need for a reference model. Nor was the PWM ever used as a reference model. Clueless again.
You’re displaying the classic tactics of the sore loser of a debate: shifting your ground; misleading statements about what was said and when; inconsequential claims to distract focus; supposing errors where none exist; empty disparagements. It’s all there, Brandon.
Future climate.
Having presented evidence
that major changes in past climate
were associated with variations in the geometry
of the earth’s orbit, we should be
able to predict the trend of future climate.
Such forecasts must be qualified in
two ways. First, they apply only to the
natural component of future climatic
trends-and not to such anthropogenic
effects as those due to the burning of fossil
fuels. Second, they describe only the
long-term trends, because they are
linked to orbital variations with periods
of 20,000 years and longer. Climatic oscillations
at higher frequencies are not
predicted.
One approach to forecasting the natural
long-term climate trend is to estimate
the time constants of response necessary
to explain the observed phase relationships
between orbital variation and climatic
change, and then to use those time
constants in an exponential-response
model. When such a model is applied to
Vernekar’s (39) astronomical projections,
the results indicate that the longterm
trend over the next 20,000 years is
toward extensive Northern Hemisphere
glaciation and cooler climate (80).
http://www.es.ucsc.edu/~pkoch/EART_206/09-0303/Hays%20et%2076%20Science%20194-1121.pdf
Holy Cow the temperature is what it is so long as you aren’t hammering the data to make it fit a computer projection. Who could have guessed?
Would someone explain to me how climate models, with one big CO2 knob, can predict a 10 year hiatus when the CO2 is constantly rising?
John Rolin,
Basically they can’t yet, something I go blue in the face pointing out. Yet. It is being worked on:
http://www.nasa.gov/topics/earth/features/earth20110309.html
NASA Study Goes to Earth’s Core for Climate Insights
http://boole.stanford.edu/pratt.html
An Ekman Transport Mechanism for the Atlantic Multidecadal Oscillation (poster)
Dec. 16, 2014, Global Environmental Change poster session, American Geophysical Union Fall meeting 2014, San Francisco.
Multidecadal climate to within a millikelvin
Dec. 4, 2012, Global Environmental Change poster session, American Geophysical Union Fall meeting 2012, San Francisco.
http://contextearth.com/2014/11/18/paper-on-sloshing-model-for-enso/
https://tallbloke.wordpress.com/tag/ian-wilson/
The only work “they” need to do is to scrap the worse than worthless, GIGO climate models, since the GCMs are a gigantic waste of taxpayer dollars, and relying on their epically failed forecasts has done untold damage to the world’s economy and cost lives.
“They” can start modeling again in a few decades after more fundamental data have been collected.
Yet.
Surely that’s a typo. For now, lets just go with, “Basically they CAN’T.”
Gloria Swansong,
Ok, I’ll bite. Let’s start with the objective part of your question: tell me how much of the research budget goes toward AOGCMs and other types of models vs. what is spent on empirical research.
For the subjective portion of your opinion, please tell me how much more fundamental data you require:
http://climexp.knmi.nl
http://www.ncdc.noaa.gov/data-access/paleoclimatology-data/datasets
http://ceres.larc.nasa.gov/order_data.php
Those are the three I frequent the most. Gigabytes of data live on this laptop from those three, plus sheesh, 10 others at least.
Brandon,
My reply didn’t post. I’ll try again.
Whatever is spent on GCMs is too much.
Do you really not know what is not known but would need to be for modeling to have a chance to reflect reality, however dimly? At present the GCMs are repeatedly falsified cartoons that intentionally distort reality.
For starters, we need 30 more years of satellite, balloon and buoy data. We need de-adjusted, uncooked book “surface” records. We need more decades of SORCE or other solar observations.
Climatology is in its infancy, or perhaps just starting to walk, but was tragically retarded by 30 years of ideologically motivated gibberish.
Gloria Swansong,
Sometimes this blog sends things to spam for strange reasons, generally the mods do a bang-up job fishing them out.
Well that’s one way to save yourself some research. I asked Google before I asked you … there isn’t a hard number. The sense I get is that model budgets are difficult to tease out of large grants that nobody really knows. Comforting, yes? I didn’t think so.
Well yes, I’m the curious sort.
Ah. Well I’ve lost track of how many times I’ve read that mantra. It was tired, old and useless the second time I did so. Here’s what someone who actually knows what they’re talking about has to say about the black arts of tuning models to reality: http://www.mpimet.mpg.de/fileadmin/staff/klockedaniel/Mauritsen_tuning_6.pdf
Your opinions are noted. Explanations, documentation, citations, evidence to support your criteria — as is becoming a pattern — are lacking.
ROFL! You just told me we don’t know squat, yet you’re entirely confident that we can afford 30 years of “wait and see” before lifting a finger to do anything. Maybe we should trade crystal balls … perhaps then I’d better understand your unwavering confidence that everything is going to be hunky dory.
goes
again
and
Crappy arguments lend themselves to being cut to ribbons.
Brandon
misconstrue
slice
dice
means
I think I understand perfectly well what Gloria is dishing. I simply don’t agree with it. She, on the other hand, hasn’t the first clue about what I think, how I think, or why I think it. Quite possible I’ve got her completely wrong … but guess what: that’s for her to dispute with me, not you.
The uncertainty in the physical magnitudes of the observables used to tune a model are never, ever, propagated through the projections made using that model.
For example, models are typically tuned to the TOA radiance. TOA radiance is known to about (+/-)3.9 W/m^2. That means the resolution of a tuned model, with respect to the thermal energy flux bath of the troposphere, is not better than (+/-)3.9 W/m^2.
Every step of a projection then starts with that uncertainty in its initial condition. The thermal flux bath of the troposphere is uncertain to that level, and the behavioral response of the climate cannot be known to better than that. Behavior of the climate means the emergent tropospheric temperature, the state and distribution of clouds, the intensity and variability of precipitation, the warming of the ocean surface, the rate of evaporation, and so forth.
All of those must be uncertain because the tuned magnitude of the tropospheric thermal flux bath is not known to better than (+/-)3.9 W/m^2.
That uncertainty must be propagated through the simulation steps, because the flux bath uncertainty never goes away. But the uncertainty is never propagated. Model projections are displayed without propagated physical uncertainty and without physically valid error bars. They are presented with a false precision.
If all the parameter errors and uncertainties, and the model theory biases (errors in theory) were propagated through a climate model projection, the uncertainty envelope would be the size of North America. Climate model projections are physically meaningless, in the strict scientific sense. They are non-predictive and non-falsifiable.
Brandon you didn’t seem to answer any of Pat Franks questions or replies……..
Michael Spurrier
You write
Of course he didn’t. Brandon Gates only answers specific points by copying&pasting long screeds he does not understand but which he thinks seem to be related to the issue.
Pat Frank made clear technical points in simple language, and those technical points are not mentioned by the warmunist web sites Gates copies from.
Richard
Michael Spurrier,
Even I need sleep from time to time. Once a month at least.
richardscourtney,
I look forward to your thorough and complete documentation of that assertion. Thanks.
Pat Frank,
This applies to the conversation you and I are having above, not to the conversation I’m having with Gloria. My latest reply to you is here: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1914235
Gloria’s conversation with you, Brandon, involves the validity of climate model projections. My comment is directly relevant to that topic.
Pat Frank,
Fair enough. my reply was poorly stated. I’ll simply note that you and I already have one conversation running covering the same concepts, and that I would be pleased if it didn’t bifurcate all over the entire thread.
It’s an open forum, Brandon. I comment as I see fit; as you do. You’re free to ignore whatever you like, as well.
Brandon…. it is often the case that you provide me with wonderful entertainment at the start of my day. I genuinely enjoy your light hearted, but very accurate comments here. Keep up the good work.
@ wendy, you gotta take YHO ( Chapeau) for him trying though but persistence in this case is not the answer.
Thank you, wendy.
Brandon Gates
In response to my accurate statement saying
you have said
Complete?! Don’t be silly!
Anybody can see the truth of my report for themselves, and it would require compiling several volumes to document every example. Furthermore, by the time I had finished you would have provided loads more of your similar nonsense.
Examples in this thread alone include your posts at
April 21, 2015 at 4:17 pm
April 21, 2015 at 5:52 pm
April 21, 2015 at 6:02 pm
April 23, 2015 at 12:16 am (where you dispute a statistical analysis with Robert Brown!)
April 23, 2015 at 12:50 am (where you make the laughable assertions that you are not “stupid or uninformed”)
etc.
Richard
richardscourtney,
Me silly? You’re the one claiming that I “only answer by copying&pasting”.
That was kind of my point. But it did have the desired effect of you giving some examples. Let’s have a look at the alleged truth of your assertion that I “only answer by copying&pasting”:
April 21, 2015 at 4:17 pm
I wrote: Internal variability is not presently predictable, yet demonstrably capable of inducing +/- 0.25 K deviations or more around the mean trend predicted by external forcings:
… followed by a link to a plot I generated myself from freely available sources on the Internet.
On what planet is that consistent with “Brandon Gates only answers by copying&pasting”? Do I have a ghostwriter according to you now?
April 21, 2015 at 5:52 pm
This one has me responding to sunsettommy, who wrote: Warming of .2 C PER DECADE! They left NO room for your stupid “internal Variability” argument.
My reply included text from this link: https://www.ipcc.ch/pdf/assessment-report/ar5/wg1/WG1AR5_Chapter11_FINAL.pdf
For brevity, the salient quotes are: Climate scientists do not attempt or claim to predict the detailed future evolution of the weather over coming seasons, years or decades … Some types of naturally occurring so-called ‘internal’ variability can—in theory at least—extend the capacity to predict future climate. Internal climatic variability arises from natural instabilities in the climate system.
Demonstrating that:
1) Internal variability is not my “stupid … argument” but based on published IPCC literature.
2) The IPCC themselves do not claim to be able to make detailed seasonal, annual or decadal weather predictions.
Very much to the point of the context of the discussion, certainly not lobbed in there randomly because I don’t “understand” something.
April 21, 2015 at 6:02 pm
Again this post is me responding to sunsettommy, who wrote: It’s immediately clear that climate models are unable to resolve any thermal effect of greenhouse gas emissions …
I responded with a literature citation to Harries et al. (2001), which I’d already used with him, and discussed, previously. That paper was the first study which reconciled the time evolution of GHG absorption by spectral line with the output of a line-by-line radiative transfer code. Again, clearly I understood what objection was being raised and I countered it with an appropriate citation to literature.
What is it you’ve been saying to me … I don’t stand for correction? Et tu, sunsettommy?
April 23, 2015 at 12:16 am (where you dispute a statistical analysis with Robert Brown!)
lol, I guess you missed this portion of my response: I mostly agree, but with caveats.
By the way, why should I not be able to disagree with Dr. Brown? (I believe he’s a PhD at Duke, yes?) This forum has turned disagreeing with expert opinions into a cottage industry. Oh, such marvelous double-standards you lot have.
April 23, 2015 at 12:50 am (where you make the laughable assertions that you are not “stupid or uninformed”)
etc.
Odd thing for you to say about me as your very first example above, my post from April 21, 2015 at 4:17 pm, disproves your ridiculous contention that I “only answer by copying&pasting”.
Good evening.
Brandon Gates
I have no intention of debating all your childish excuses for copying&pasting passages you don’t understand.
I wrote
Well, you did provide “similar nonsense” almost immediately here and I have explained that you don’t understand what you there copied&pasted here.
Please desist from thread bombing with your childish idiocy which is wasting so much space on threads.
Richard
richardscoutney,
Then you will kindly desist with your handwaving assertions of same.
Troll posting as Brandon Gates
I have made NO “handwaving assertions”.
You persistently copy&paste stuff you don ‘t understand in failed attempts to pretend you can justify your daft assertions. The most recent example is here and here I explain that you clearly don’t understand what you copied&pasted because it refutes your superstitious belief in man-made global climate change.
Please stop posting stuff that is plain wrong and when called on it replying by copying&pasting stuff you don’t understand. Your behaviour is wasting space on threads.
Richard
richardscourtney,
I hardly think that posting excerpts from relevant literature citations conforms to even the broadest definition of “troll”. Your sweeping allegations of such does, in my mind, constitute an attempt to poison the well.
Your immediately following comment demonstrates yet another example:
Whether AGW is real or not is the substance of this whole debate, Richard. You declaring it superstitious by fiat doesn’t make it so, and as yet I’ve seen you do precious little to explain what exactly it is I “clearly don’t understand” about my copypasta.
More sound and fury, signifying nothing. I get it that my cogent, on-topic and well-cited remarks bother you. But as they conform to site policy, I believe that I shall continue my activities at the pleasure of Mr. Watts and ignore your request, however polite you are attempting to make it appear.
Troll posting as Brandon Gates
It beggars belief that you have the gall to write saying to me
It may have escaped your notice that this thread is about a study showing global warming is actually more moderate than worst case IPCC models. None of your posts in this thread – not one of them – has been on-topic. Your sole purpose of posting in this thread seems to have been your intention to troll the thread from its topic.
This thread is NOT about your superstitious belief in anthropogenic (i.e. man-made) global warming (AGW).
I remind that without any prompting YOU cited the Lorenz explanation that all climate change could be the chaotic climate system seeking but never attaining its strange attractors. Thus, YOU pointed out that there is no evidence that any AGW exists. But YOU persist in claiming it does. Brandon, that persistent claim IS superstitious belief and it cannot be anything else.
Your citation of Lorenz’ work was yet another example of your failing to understand what you had copied&pasted. And your promotion of your superstitious belief bothers me which is why I have been stamping on it.
You have still not answered my simple question; viz.
I yet again repeat my request that you stop polluting threads by thread bombing them with your irrational drivel.
Oh, and it would be good if you were to apologise to Gloria Swansong for your obnoxious and repeated rudeness to her. That aspect of your trolling is egregious.
Richard
richardscourtney,
Oh for sod’s sake, Richard. Very first post in this thread, to which I responded:
sunsettommy
April 21, 2015 at 3:39 pm
“Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
There’s no guarantee, however, that this rate of warming will remain steady in coming years, Li stressed. “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change.”
HUH?
The whole thing seems to be more of babble than scholarly here…..
Read this bit again: “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change.”
What does “shouldn’t expect rates of warming to be constant” mean to you, Richard?
ROFL!!! So IPCC models are projecting the number of wedding cakes produced in Romania by the year 2100? Give it a rest man, before you go completely barking mad chasing your own tail.
On purpose — it establishes the concept of “internal variability”, which half the time you’re saying is my delusional fantasy, and half the time you subscribe to. Make up your bleedin’ mind already.
And not for the first time, I ask you: why does your conclusion of no AGW necessarily follow from the premise that it’s blindingly obvious this planet has been observed to march to the beat of its own drummer?
WordPress ate my latest rather lengthy reply to that query. That you don’t like my previous answers is frankly not my bloody problem.
Oh sweet irony. Could anyone possibly put on a more classic display of pompously sanctimonious duplicity. Perhaps so, but it would take some doing. I find it almost charming in a horrifying sort of way.
Gloria got as good as she gave, my standard mode of operation. You use the same justification with me.
I’m telling you in no uncertain terms: I ultimately answer only to Mr. Watts and his delegated authorities in this forum. Some requests from others I have and will consider abiding by. However, I will not hew to your sweeping arbitrary demands no matter how couched they are in sugary pleeeezes. If one looks at it rationally and objectively, a good quarter of my “threadbombing” in this topic is you repeatedly demanding answers to questions I’ve already given and rebutting your nonsensical charges such as I only copy&paste things which I do not understand. The very first example you gave of that falsified your allegation!
Do you know the meaning of the word “farcical”? How about YOU think about what you’re going to write before vomiting all over the keyboard, eh?
Sorry, no, request respectfully denied. I don’t subscribe, or respond kindly, to the sort of impotent intimidation claptrap game you’re running. Or even more plainly: how about you just go right ahead and piss off.
On that note, a polite good day to you, sir.
Troll posting as Brandon Gates
I read your most recent long piece of masturbatory self delusion.
It ends by making the ridiculous claim that you were being “polite”. That claim leads to the question as to whether you can learn anything.
Richard
More like dry irony because I don’t take you seriously.
Troll posting as Brandon Gates
Of course you don’t take me seriously. Clowns don’t take anything seriously.
Richard
People with actual arguments … use them.
Troll posting as Brandon Gates
Ah! That explains why you make assertions and when you are pressed on them you can’t provide arguments to support them so instead you copy&paste stuff you don’t understand..
Your arguments are still awaited concerning whatever is that you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.
People who don’t have arguments cannot provide them.
Richard
richardscourtney,
I have answered: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1915532
I thought the first bit I quoted made it quite clear: “Various attempts to simulate this temperature record (Schneider and Mass, 1975; Pollack et at., 1976; Bryson and Dittberner, 1976) have all focused on external causes, such as volcanic dust, solar constant variations and anthropogenic effects. It is possible, however, that even in the absence of any external forcing a unique climate may not exist. Climate change may be a natural internal feature of the land-ocean-ice-atmosphere (climate) system.”
IOW, “internal variaiblity” is a change in surface temperature not driven by external radiative effects. I cited two well documented examples, AMO and ENSO, both of which are driven by coupled ocean/atmospheric energy exchanges. So, once again, you have my definition and two well-known examples … and I note that you yourself cite NAO and ENSO.
Emphasis added to draw your eye to MY definition. You know, the one you keep repeatedly asking me after I’ve already provided it.
Immediately following that definition, I asked you a question: Please explain why it necessarily follows that postulated effects of natural internal/external variability or forcings preclude any human influence on the system.
Thus far you have failed to answer that direct question.
Your very next post makes it clear my answer was — again, and for some unfathomable reason — not good enough for you. What I believe you are actually asking is your restated question, in bold, at the bottom of that post:
So, how do you know when your magical mystery of “internal variability” is causing measured temperatures to decline or to rise and by how much when – as you quote – ALL such rises and falls could be “the natural variations due to the complex nonlinear interactions among the various components of the climate system”?
The beginning of the answer to how I estimate those things may be found alllllll the way back at the beginning of the thread in a reply, not to you, but sunsettommy: http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913430
That post contains the following plot:
http://1.bp.blogspot.com/-oxFP6mUKqIY/VTWEdb3gJzI/AAAAAAAAAbU/YiRjFJ8Zb8M/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BForcings.png
A short description of the method:
1) First I regressed ln(CO2/280), the solar constant (TSI), and volcanic aerosol optical depth (AOD) against the HADCRUT4 temperature timeseries from 1880-2014. The result is what I call Net External Forcing. The R^2 statistic for that prediction is 0.8480.
2) I then subtract the observed temperature from regression prediction to obtain a monthly residual value, which residuals represent temperature movements which are not explained by the combined forcings from CO2, TSI and AOD. Thus, I call it Internal Variability (External Forcing Residual).
3) The next step is to regress the external forcing residual against AMO, ENSO and LOD (length of day). The result of that regression is what I call Internal Variability (Calculated). The R^2 statistic for that prediction is 0.6625.
4) I then add the calculated internal variability prediction to the net external forcing prediction from (1), which I call HADCRUT4 prediction. The R^2 statistic for that prediction is 0.9493.
Walk the talk, Courtney; there are some long unanswered questions on this thread:
1) To Gloria: If you’ve got a better plausible physical mechanism to explain the post-1950 temperature rise, now would be your chance to offer it. Bonus points if you can show me a correlation which beats out CO2+TSI+AOD plus the modes of internal variability I’ve regressed for the entire 1880-2014 interval shown, a pretty tall order; R^2 for that regression is 0.85. [a typo, s/b 0.95]
2) To you: How do YOU explain The Pause without invoking “magic”?
3) To you: Please explain why it necessarily follows that postulated effects of natural internal/external variability or forcings preclude any human influence on the system.
Good day.
Troll posting as Brandon Gates
At long, long last you have attempted to answer the question
Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.
Thankyou.
Unfortunately, your attempt at an answer – while being long-winded and rambling – is illogical and incomplete.
You refer to a post in which you wrote
OK. That is an honest statement of opinion (which is rare from you and is appreciated).
But in that same post which you claim to now paraphrase (aciually mis-state but that can be ignored), you cited the Lorenz equations and you quoted
As I have repeatedly pointed out to you, that is yet another example of you copying&pasting something you don’t understand. Any need for any assertion of ANY discernible effect of “external radiative effects is refuted by “The possibilty that “climate change might just be the natural variations due to the complex nonlinear interactions among the various components of the climate system”.
Which returns us to my question of how you determine when your “internal variability” is and when it is not altering the empirical data. The Lorenz equations suggest that there is no need to consider anything as cause of all climate changes “except the natural variations due to the complex nonlinear interactions among the various components of the climate system”.
I will spell this out because I have repeatedly explained it above but you have not yet managed to get it into whatever is between your ears,
1.
You raised the Lorenz equations in this discussion, and
2.
the Lorenz equations suggest that what you call “natural variation” is the cause of ALL climate changes indicated by the empirical data, so
3.
there is no need to assume “external radiative effects” have any discernible effects on climate changes indicated by the empirical data, but
4.
climate model projections assume the climate changes indicated by the empirical data are driven by “external radiative effects”.
5.
You say your “internal variability” sometimes does alter the “empirical data” (e.g. by PDO or volcanism) forecast by climate model projections but most of the time “internal variability” does not alter the “empirical data” forecast by climate model projections, so
6.
How do you determine when your “internal variability” is and when it is not altering the empirical data while – as you have – citing that the Lorenz equations indicate your “internal variability” may be causing ALL climate change?
In summation, as I have repeatedly pointed out,
Clearly, what you call “internal variability” is an undefined excuse for all disagreements of the models with reality. In other words, your “internal variability” is magical mystery.
And I conclude by answering your two daft and off-topic ‘have you stopped beating your wife questions’ which you address to me; viz.
Answer 1:
There are many explanations for the mis-named ‘pause’ (more than 60 different excuses for cessation of global warming are in the peer reviewed literature). The most likely cause is that the interruption to recovery from the Little Ice Age (LIA) known as the ‘pause’ is the same as the cause of previous interruptions to recovery from the LIA. The recovery from the LIA cannot be an effect of changes to radiative forcing induced by emissions of greenhouse gases from human activities. The most probable explanation of the recovery from the LIA and interruptions to it was provided decades ago by Lorenz, and you provided an unsolicited statement of it in this discussion. It is that the climate system is constantly moving towards – but never reaching – its chaotic strange attractors.
Answer 2.
It does NOT necessarily follow that postulated effects of natural internal/external variability or forcings preclude any human influence on the system. That assertion is merely another of your many delusions.
The observed effects of natural internal/external variability or forcings removes any need to postulate any human influence on the global climate system especially when no such postulated human influence has been observed.
Richard
richardscourtney,
Charming to the last.
I want to say you’re welcome, but that could be seen a tacit admission that I’d been evading the question.
I doubt you’ll believe me, however FWIW: I posted a rather longer reply to you two days ago with the same specifics, but with an unclosed blockquote I subsequently asked the mods to fix. Subsequently both the original post AND the request disappeared from the thread.
Do you not realize that your own posts to me are rather long and, well, somewhat circuitous? One might even say tedious? What would happen if in the interest of brevity I didn’t respond to them, in kind, point by point, I wonder.
Again, you make it difficult to thank you for the compliment without implicitly being self-incriminating on the rarity of my candour.
So solar variations are out? Willie Soon, for one, would dispute that. So would the IPCC. How about orbital forcing a la Milankovitch theory?
Process of elimination as I’ve already explained. That which cannot be accounted for due to external forcings must be due to internal transfers of energy from within the system. My regression is not perfect, an R^2 of 0.95 does leave a final residual unaccounted for. Recall, however that the external forcing R^2 statistic is 0.85 whilst the internal variability regression attains an R^2 statistic of 0.66. I believe it reasonable to infer that the external forcing regression is the more certain result and that therefore most unexplained variance belongs to unaccounted for factors in the internal variability parameters I used.
You’re entirely free — and welcome — to dispute my conclusions, however:
I suggest that you would make the strongest case for your arguments by providing an alternative analysis which is data-driven and better explains temperature trends from 1880-present than does my analysis here. Like I said, it’s a tall order: an overall R^2 statistic of 0.95 is quite good.
It’s not a question of me not getting it between my ears. I believe that understand your argument perfectly — I simply don’t agree with it. In this particular case, the main problem I have is with your point (2) above. My reading of Lorenz does not have him saying that all fluctuations in the system must be natural … only that they may or could be.
(3) is extremely problematic because the Earth’s climate system gets the vast majority of its energy externally, namely from the star we call the Sun.
The rest of your points proceed from what I consider bad premises, thus rendering (4) and (5) getting a bit ahead of ourselves, and (6) especially moot until such time as we’ve resolved our disagreements on (2) and (3).
Clearly that’s your opinion, and clearly I contest it.
Sorry, Richard, but when someone says they think my explanation is bollocks, I feel well within my rights in an evidence-based discussion about physical phenomena to ask them to provide an alternative, plausible physical explanation backed by observation. I mean, to me, that’s what scientific practice is all about.
What specific statements by Lorenz provide the explanation? I don’t find any in the present discussion. Closest I come is to this statement ABOUT Lorenz’s work from Robock (1978):
The theory of internal causation of climate change has been developed by Lorenz (1968, 1970, 1976). He suggested that climate change might just be the natural variations due to the complex nonlinear interactions among the various components of the climate system.
Emphasis added. Raising a reasonable hypothesis is far and away from demonstrating that it must be the only explanation.
Richard, you’re simply repeating the same argument you’ve already made. Again, I believe that understand it; however, I do not agree with it.
Perhaps I have not been clear enough about what I am asking you to provide. When you state that no evidence of human influence — at least in part — explains the rise in temperatures from 1880-present (and certainly 1950-present), unless you provide an alternative plausible physical mechanism backed with an analysis empirical data, then you have precious little basis for making any conclusions at all.
Appealing to chaos theory as a non-process and leaving the argument there doesn’t cut it for me — I consider that magical thinking because in a largely deterministic system with observable properties, I think it’s ridiculous to imply that stuff like “recovery” from the LIA “just happens”. No. Some physical process, whether known or unknown, is doing it.
Chaos does have some implication for predictability of such a system, but it does NOT rule out the possibility of appealing to empirical data post hoc and determining causal physical mechanisms which are driving changes to observed physical parameters.
I tire of being asked to provide evidence and my own analysis substantiating my beliefs and having them rejected out of hand by parties who do not effect the return courtesy of providing the same level of evidence and analysis by way of rebuttal.
In sum, as I see it your best options are to substantiate your claims by appeals to observed phenomena or withdraw your objections and adopt an agnostic position about what is causing the instrumental temperature record to do what it has done and is doing.
At long last, that is all for this round.
Troll posting as Brandon Gates
I see you are still providing long-winded nonsense in silly attempt to excuse your idiocy.
However, I am glad that I ( probably only me) struggled through all that tripe because it contains this gem of Pythonesque humour
Your “candour”!? Oh, how I laughed at that!
Troll, it is clear that you would have difficulty being honest if your life depended on it.
Amongst all your latest daft tripe you respond to my again pointing out
by you replying
NO, Troll, it is NOT an “opinion”: it is a statement of YOUR assertions.
If the statement were untrue in any way then you would provide a simple demonstration of what is wrong with that the statement instead of merely saying you “contest it”. And, in fact, you do NOT “contest it”: you merely say you don’t agree it.
That failure to agree an obvious truth is typical of your repeated idiocy in this thread.
So, Troll, if you do want to “contest it” then please try. Such “contest” would state in plain language
1.
how you determine when what you call “internal variation” is affecting the empirical data and when what you call “internal variation” is not affecting the empirical data, and
2.
how you know when Lorenzian chaos – which you introduced to the thread – is not operating but
3.
you would NOT include long-winded irrelevance which merely serves to demonstrate your idiocy.
I anticipate another couple of pages of irrelevant drivel from you as you yet again avoid the issue.
Richard
Actual warming seems to validate the middle-of-the-pack model predictions fairly well, they say, but is more moderate than the “most severe” scenarios. This amounts to cautious validation and endorsement of the IPPCs model portfolio, if you toss the outlier models. I don’t view this as vindication for skeptics at all, sorry. And I am highly skeptical.
No one knows the magnitude of the “actual warming,” brians356. The surface air temperature record, land- and SST, both, is corrupted with systematic measurement error; error that the entire field studiously ignores. Mostly because it doesn’t average away. The true accuracy-revealing error bars are at least (+/-)0.5 C.
This isn’t about jiggering the values, cooling the past, or any of that other adjustment stuff that people worry about.
It’s straight-forward, what-is-the-field-accuracy-of-the-temperature-sensor stuff. We all remember accuracy — something all experimental scientists, except consensus climate scientists, worry about.
Brandon Gates at April 21, 2015 at 8:27 pm
“…hasn’t the first clue about what I think, how I think, or why I think it.”
☭ propaganda!
Peterk
The real question is does Brandon actual think anything or does he just play word games and quote those that he is smitten with.
bob boder,
Irony.
If you’re on the road again, stay safe.
No, it doesn’t, even using the cooked books upon which IPCC relies.
Of the dozens (hundreds?) of models, only two to a few even come close to reality.
Gloria Swansong,
Again, you’re big on assertion, light on substantive evidence. Yet somehow I’m the propagandist according to PeterK.
All you have to do is look at any version of this graphic, which I’m sure you’ve seen over and over (how could you miss it on WUWT, for instance), to see the truth of my statement. Somehow its messages is lost on you:
http://l.yimg.com/fz/api/res/1.2/u.i.A9hIbX2Ql7L7LC5_jg–/YXBwaWQ9c3JjaGRkO2g9Njk5O3E9OTU7dz0xMDE1/http://notrickszone.com/wp-content/uploads/2013/09/73-climate-models_reality.gif
You are not only light on substance, but totally lacking. I’ve backed up every statement I’ve made, apparently irrefutably, since you ignore my demonstrations of the falsity of your baseless assertions.
It’s clear you’re just spewing garbage, like Denial, if indeed you are even two separate entities.
Gloria Swansong,
I have this thing about not assuming that I know what people are referring to when they don’t deal in specifics.
I’ve seen several plots like that one out of C&R from UAH (usually R), but not that particular one. Thanks, it’s a keeper.
Well let’s review. You asked for evidence. I presented some, then said to you:
If you’ve got a better plausible physical mechanism to explain the post-1950 temperature rise, now would be your chance to offer it. Bonus points if you can show me a correlation which beats out CO2+TSI+AOD plus the modes of internal variability I’ve regressed for the entire 1880-2014 interval shown, a pretty tall order; R^2 for that regression is 0.85.
Your response: Please provide some actual evidence. Thanks.
Sure, you do a bang up job “proving” that CMIP5 deviates from observations. Try explaining why, hmm? How about offering an alternative explanation for the temperature rise for a longer interval of time, say 1950-present, as I have already asked you, hmm?
I’m sorry, but when someone asks for and their response is “That’s not evidence” when I provide it, I tend to think that I’m not the one obstinately choosing to remain ignorant.
Errata: … C&S from UAH (usually S) …
Apparently you don’t know what evidence is. You have provided exactly zero in support of your baseless assertions and, it must be said, outright falsehoods.
For the last time, your regression analysis is not evidence in support of the repeatedly falsified hypothesis that CO2 has been the dominant forcing on global climate since c. 1950. You have nada, zip, zilch.
You can’t offer any actual physical evidence, any more than can IPCC. Nature shows your failed hypothesis false yet again with each passing year without statistically significant warming. Not that that’s needed since the valid observations I’ve made over and over without any response from you already show how abysmally and epically CAGW advocates have failed.
QED. End of subject for me. As it should be for you, had you any shame. Trolling must be your job.
Not EoS. Forgot to say you’re welcome for the graphic. Lots can be found within seconds by searching. I shouldn’t have had to do so for you.
PS: If it is your job, you’ve blown it.
Gloria Swansong,
No, as I stated above, I apparently don’t understand what you mean when you say “evidence”. Which is why I’ve asked you for an alternative explanation for the observed temperature rise since 1950. Three times in a row … [crickets]
Then show me evidence of the truth. Since 1950. Chop chop.
Ok, how do YOU determine causality in a complex system?
The piece of the puzzle YOU keep ignoring is that 40 year pauses have precedent in the instrumental record:
http://3.bp.blogspot.com/-MW_NJp28Udc/VNS3EAEqpOI/AAAAAAAAAUs/hjhuLZFkdoM/s1600/hadcrut4%2Bhiatuses.png
Those two 40-year declines in temperature correspond very well with my estimates of internal variability
In net:
http://2.bp.blogspot.com/-sCuOxDdbiXo/VTb4ffCsPgI/AAAAAAAAAb8/cEgSwN3Dik8/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BInternal%2BVariability%2BNet.png
Broken into component parts:
http://3.bp.blogspot.com/-TBdZYOd0BrI/VTb4fLSnx0I/AAAAAAAAAb4/uHrvfzQ1BYo/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BInternal%2BVariability%2BComponents.png
Got it? AMO, ENSO and LOD (length of day) are indices based on estimates from measured physical quantities … otherwise known as empirical evidence.
So get to searching internal variability already.
When someone makes specific claims, I feel well within my rights to ask for specific evidence. That way it’s clear exactly what is being debated. Also known as: effective communication.
And yes, that plot is quite helpful — I’ve seen many versions of it before, but none where the deviation was quite so exaggerated. 0.65 K!! I’m gonna have a field day with that one.
I don’t participate here for money. I take it that since we’ve entered the name-calling phase that you really don’t have much more than tired, old, standard “skeptical” talking points to offer. Ta.
Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
First global warming was unstoppable, then there was no hiatus, now the hiatus has been predicted all along.
“We’ve always been at war with Eastasia”
I predict that the main stream will shortly be predicting a longer pause and that they predicted it all along but wait – the pause will shortly end with an outpouring of hidden heat from “the blob”
Neil
You say
Perhaps “Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050” but the IPCC did not say that.
We do know that in 2008 the US Government’s National Oceanic and Atmospheric Administration (NOAA) reported
Ref. NOAA, ‘The State of the Climate’, 2008
http://www1.ncdc.noaa.gov/pub/data/cmb/bams-sotc/climate-assessment-2008-lo-rez.pdf
The mis-named ‘pause’ has already lasted for more than 15 years.
Richard
More of the same. This theory has yet to predict one atmospheric process correct and the data does not lend any support to it . I will send over the greenhouse score card.
” the data does not lend any support to it “.
The only reliable data we have going back 1000 years is the position of the sun and planets and the tilt of the Earth’s axis. All the other data is speculative proxy data – a hand full of values to support a global temperature that we are assuming is accurate to 1/100th of a degree C..
http://www.warwickhughes.com/hoyt/scorecard.htm
They should give this a review. I fully expect a downward temperature trend in response to prolonged minimum solar conditions as this decade proceeds.
“Based on our analysis, a middle-of-the-road warming scenario is more likely, at least for now,” said Patrick T. Brown, a doctoral student in climatology at Duke University’s Nicholas School of the Environment. “But this could change.”
It could change!
“The researchers say these “climate wiggles” can slow or speed the rate of warming from decade to decade, and accentuate or offset the effects of increases in greenhouse gas concentrations. If not properly explained and accounted for, they may skew the reliability of climate models and lead to over-interpretation of short-term temperature trends.”
Past temperature data already showed this ALL ALONG, they just learned this recently?
I knew this way back in the 1970’s.
Notice how they assume that the only possible change will be back to fast warming.
Not only that Mark,they are trying to minimize the rolling damage of many past modeling failures,with feeble rationalizations on why it didn’t warm as fast as their AGW conjecture says it should.
It is an attempt to explain away the poor results,and it pathetic.
Let’s consider a General Circulation Model attempting to predict a state of the planet 57 years (500,000 hours) from now. For any semblance of accuracy, the error in a 1-hour step should then be less than 1/500,000 = 0.0002%. Modelers are unusually tight-lipped regarding the accuracy. I suspect that it is nowhere near the accuracy required; I have discovered a 2.5% error in a CAM 5.1 model.
What happened to the idea of due diligence? We are more likely to get a tirade about drowning polar bears and homeless penguins than a good estimate of a model accuracy.
They did perform due diligence. The model produced the result requested by those who financed the project.
Mark, a good observation. Many years ago when computers were big mysterious unreliable machines a group of programmers worked on a problem. At a milestone a test was to be run: Process an input deck of cards and print results. The machine was mostly down and they could not get the program even to compile. So they wrote a simple program: Read a deck of cards, and print a known table of results. They passed the milestone with flying colors.
If they accounted for propagation of error and significant figures, they would have nothing. So they verify the accuracy of the models by running the simulations over and over again.
See?
Curious George, I’ve been trying to publish a paper on exactly that point — accuracy — for two years, now.
blahblahblahblahblahblahblahblahblah…………“But this could change.”
The whole armageddon life ending hysterical ninny fit 1/2 a degree could be natural variability as far as anyone knows.
Good grief Charlie Brown. The theory is good, we know that so we must understand the misbehavior of the climate. When is one of these great intellects going to say “You know what, the models are bust, useless”.
Well, I was going to say in response: “When the Great Lakes, Boston Harbor, the Delaware River, and the Potomac all freeze solid, and icebergs wash ashore in Cape Cod”, but that did not do it either.
So my new guess is…never.
Now that you mentioned it, not much news about that subject lately.
“Now that you mentioned it, not much news about that subject lately.”
Yes, Spring has a way of melting away Winter’s worries and thawing the frozen earth, does it not?
It seems that there should be more output from climate models than just temperature. Rainfall (total over earth for a year) and total sunlight should be included, but that would be grinding it too fine for the models I bet.
“Rainfall (total over earth for a year) and total sunlight should be included”
That would likely be difficult, since in the cartoon world created by models, there are no clouds, let alone thunderstorms.
The researchers say these “climate wiggles” can slow or speed the rate of warming from decade to decade
Note they still assume warming, just the wriggles modify it.
Another ad hoc explanation?
Snicker…..
The way the temps are cooling off the next thing they’ll promote is burning of fossil fuels to “heat up ” the place.
Looks like more slow climb down from models, because of the ‘pause’. Crumbling foundations.
‘There’s no guarantee, however, that this rate of warming will remain steady in coming years, Li stressed. “Our analysis clearly shows that we shouldn’t expect the observed rates of warming to be constant. They can and do change” ‘
=================================
My immediate thought was that they are implying a possible future acceleration of observed warming, and I’m sure that was their intention, but a rate change can go two ways, all of which is an indiction that I have been successfully brainwashed.
“Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
The IPCC said NOTHING about such “hiatus” possibilities,when they said this back in 2007:
A major advance of this assessment of climate change projections compared with the TAR is the large number of simulations available from a broader range of models. Taken together with additional information from observations, these provide a quantitative basis for estimating likelihoods for many aspects of future climate change. Model simulations cover a range of possible futures including idealised emission or concentration assumptions. These include SRES[14] illustrative marker scenarios for the 2000 to 2100 period and model experiments with greenhouse gases and aerosol concentrations held constant after year 2000 or 2100.
“For the next two decades, a warming of about 0.2°C per decade is projected for a range of SRES emission scenarios. Even if the concentrations of all greenhouse gases and aerosols had been kept constant at year 2000 levels, a further warming of about 0.1°C per decade would be expected. {10.3, 10.7}
Since IPCC’s first report in 1990, assessed projections have suggested global average temperature increases between about 0.15°C and 0.3°C per decade for 1990 to 2005. This can now be compared with observed values of about 0.2°C per decade, strengthening confidence in near-term projections. {1.2, 3.2}
Model experiments show that even if all radiative forcing agents were held constant at year 2000 levels, a further warming trend would occur in the next two decades at a rate of about 0.1°C per decade, due mainly to the slow response of the oceans. About twice as much warming (0.2°C per decade) would be expected if emissions are within the range of the SRES scenarios. Best-estimate projections from models indicate that decadal average warming over each inhabited continent by 2030 is insensitive to the choice among SRES scenarios and is very likely to be at least twice as large as the corresponding model-estimated natural variability during the 20th century.”
http://www.ipcc.ch/publications_and_data/ar4/wg1/en/spmsspm-projections-of.html
They use confidential language such as these:
“strengthening confidence in near-term projections”
“would occur in the next two decades”
“Best-estimate”
“very likely”
No mention of possible long pauses, of temperature trend in it at all!
I have not seen anything convincing with respect pre-instrument temperature reconstructions. When Agw is less than 1c it seems the resolution of 1000 year old tempurature reconstructions are completely useless.
It would look like a hockey stick.
“To test how accurate climate models are at accounting for variations in the rate of warming, Brown and Li, along with colleagues from San Jose State University and the USDA, created a new statistical model based on reconstructed empirical records of surface temperatures over the last 1,000 years.”
They did a test? Where are the results, and how do they know it is accurate?
Under the IPCC’s middle-of-the-road scenario, there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050, Brown said. “That matches up well with what we’re seeing.”
—–
27 models. 25 outside their own error bars the remaining two also running hot but not yet invalidated. Hey. I have an idea. Let’s average 27 bad models ad get a better model.
Yeah an UNVERIFIED 35 years into the future scenario,but golly they are sure they are 70% correct!
Don’t forget the nuance!
Good advice from you for once.
What you fail to grasp, Gates, is that ‘nuance’ is completely irrelevant. What matters are facts. Reproducible facts. Consensus doesn’t produce reproducible facts. You may go now.
Babsy,
There is broad literature consensus that the planet is indeed not flat.
Gates, you promote yourself as a smart guy, yet you don’t get it. Sad, but not my problem. And just to blow up your BS about ‘flat earth’, the earth is indeed flat over short distances. You may go now.
Babsy,
Smart as I allegedly am, I’ve never been able to understand nonsensical gibberish.
I’m tempted to blame your science teachers, but that would be giving you an out I really ought not offer.
Yeah, it’s called “Kansas”: http://www.improbable.com/airchives/paperair/volume9/v9i3/kansas.html
Not a reputable pal-reviewed consensus journal tho’, so I don’t believe it.
I wasn’t aware that I needed your permission.
Another warmist un-validated assumption attributed to alleged statistics.
Models failed catastrophically, failed models used for any purpose, except educating programmers of the pitfalls, is wrong.
Given that none of the models showed hiatus’s or pauses, only belief can dredge an alleged chance of hiatus our of dreck.
Fudged factors and assumptions are not science.
I think it is time to bring up a comment Richard C. Courtney posted at Dr. Spencer’s blog a couple years ago,here is the link to the comment:
http://wattsupwiththat.com/2013/10/14/90-climate-model-projectons-versus-reality/#comment-1447979
He was asked this question:
“The important question …. Why are the models so wrong?”
His reply, in part,the rest is in the link.Worth the full reading.
“I answer, because they do not model the climate system of the real Earth.
To explain that answer it seems I need to post the following yet again, and I ask all who have seen it to skip it and to forgive my posting it yet again.
None of the models – not one of them – could match the change in mean global temperature over the past century if it did not utilise a unique value of assumed cooling from aerosols. So, inputting actual values of the cooling effect (such as the determination by Penner et al.
http://www.pnas.org/content/early/2011/07/25/1018526108.full.pdf?with-ds=yes )
would make every climate model provide a mismatch of the global warming it hindcasts and the observed global warming for the twentieth century.
This mismatch would occur because all the global climate models and energy balance models are known to provide indications which are based on
1.
the assumed degree of forcings resulting from human activity that produce warming
and
2.
the assumed degree of anthropogenic aerosol cooling input to each model as a ‘fiddle factor’ to obtain agreement between past average global temperature and the model’s indications of average global temperature.
More than a decade ago I published a peer-reviewed paper that showed the UK’s Hadley Centre general circulation model (GCM) could not model climate and only obtained agreement between past average global temperature and the model’s indications of average global temperature by forcing the agreement with an input of assumed anthropogenic aerosol cooling.
The input of assumed anthropogenic aerosol cooling is needed because the model ‘ran hot’; i.e. it showed an amount and a rate of global warming which was greater than was observed over the twentieth century. This failure of the model was compensated by the input of assumed anthropogenic aerosol cooling.
And my paper demonstrated that the assumption of aerosol effects being responsible for the model’s failure was incorrect.
(ref. Courtney RS An assessment of validation experiments conducted on computer models of global climate using the general circulation model of the UK’s Hadley Centre Energy & Environment, Volume 10, Number 5, pp. 491-502, September 1999).
More recently, in 2007, Kiehle published a paper that assessed 9 GCMs and two energy balance models.
(ref. Kiehl JT,Twentieth century climate model response and climate sensitivity. GRL vol.. 34, L22710, doi:10.1029/2007GL031383, 2007).
Kiehl found the same as my paper except that each model he assessed used a different aerosol ‘fix’ from every other model. This is because they all ‘run hot’ but they each ‘run hot’ to a different degree.
He says in his paper:”
Read the rest in the link.
sunsettommy
Some people may want to (again) read that explanation.
I now write to say that later in that link I provide additional information which explains why we still have so many climate models when none of them models the Earth’s climate system: that explanation is at
http://wattsupwiththat.com/2013/10/14/90-climate-model-projectons-versus-reality/#comment-1448048
Richard
Yeah, I like this relevant part where show how they play up models, to match the temperature data:
“This (as my post explained) was compensated by inclusion of a completely arbitrary input of aerosol cooling effect in each model. However, the rise in global temperature was not uniform over the twentieth century; e.g. global temperature did not rise between ~1940 and ~1970. The degree of ‘ran hot’ in each model was an output so could not be adjusted. But a balance between the warming effect of GHGs (i.e. ECS) and the cooling effect of aerosols could be adjusted, so the modelers were able to get a ‘best fit’ for each model. And this is why each model has a unique value of ECS and effect of aerosol cooling.
Of course, they could have admitted the ‘ran hot’ was evidence that a model was inadequate and abandoned the model, but much time money and effort had been expended on each model so this was not a politically available option. Or they could have altered parametrisations in each model and to some degree they did, but the adjustment of ECS and aereosol cooling was the simplest option and each modeling team adopted it.
Hence, each model is a curve fitting exercise and, therefore, it is not surprising that Willis Eschenbach discovered he could emulate the models’ outputs with a curve fitting exercise.”
Curve fitting,data mining, tuning and so on. I have trouble getting confident with climate models, with that history behind them.