Study: Global Warming Actually More Moderate Than Worst-Case IPCC Models

GISS_temperature_2000-09_lrg.jpg

Image: NASA GISS

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

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293 thoughts on “Study: Global Warming Actually More Moderate Than Worst-Case IPCC Models

  1. “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,

      HUH?

      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.

      • 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.

      • sunsettommy,

        Warming of .2 C PER DECADE!

        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.

        They left NO room for your stupid “internal Variability” argument.

        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,

        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”?

        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,

        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?

        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,

        There is no lag in this fit — and no need for a lag — there is no evidence whatsoever of “uncommitted warming”.

        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.

        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.

        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.

        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”.

        Completely agree.

        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.

        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,

        It’s immediately clear that climate models are unable to resolve any thermal effect of greenhouse gas emissions …

        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.

        … or tell us anything about future air temperatures.

        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

        Davis and Taylor: “Does the current global warming signal reflect a natural cycle”
        …We found 342 natural warming events (NWEs) corresponding to this definition, distributed over the past 250,000 years …. …. The 342 NWEs contained in the Vostok ice core record are divided into low-rate warming events (LRWEs; < 0.74oC/century) and high rate warming events (HRWEs; ≥ 0.74oC /century) (Figure). … …. "Recent Antarctic Peninsula warming relative to Holocene climate and ice – shelf history" and authored by Robert Mulvaney and colleagues of the British Antarctic Survey ( Nature , 2012, doi:10.1038/nature11391),reports two recent natural warming cycles, one around 1500 AD and another around 400 AD, measured from isotope (deuterium) concentrations in ice cores bored adjacent to recent breaks in the ice shelf in northeast Antarctica. ….

        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,

        So, possibly, more heat is being retained by more CO2. Who disagrees with that?

        Ask sunsettommy, he’s the one calling for “proof”.

        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 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.

        The pause kind of put the kibosh on all that, or at least it would have done in another scientific field.

        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.

        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).

        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,

        I can see how it was done , so no need to explain. I must add that I am underwhelmed by the milliwatt levels.

        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.

    • 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.

      • 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.

        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.

    • 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

      Brandon Gates
      I asked you

      You repeatedly assert that it is “internal variability” which causes the empirical data to refute your assertions.
      Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.

      You have NOT answered either question.
      Instead, you have copied&pasted irrelevant graphs and linked to meaningless waffle with which you have polluted this thread.
      The nearest you provide to and answer is in this link
      http://wattsupwiththat.com/2015/04/18/too-many-wild-cards-in-the-climate-game/#comment-1912694
      which you provided.
      In that link you say

      The MIDDLE plot shows internal variability . Dark blue line is the residual of the external forcings (CO2, solar, volcanic aerosols), the magenta line is calculated based on AMO, NINO and length of day anomaly (LOD). The bottom plot breaks those three out so that you can see their individual contributions to the overall trend.

      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.
      Richard

      and here where I wrote

      Brandon Gates
      Your asserted magical mystery of “internal variability” is superstitious nonsense.
      And you repeatedly make the daft assertions that

      All models are always wrong. The question is whether or not they’re useful. See also: model skill is not an all-or-nothing proposition. Skill scores are also relative. Much depends on the reference model used in the evaluation.

      A model is wrong when it fails to provide predictions and/or descriptions that are within their determined accuracies and precisions.
      All climate models are wrong.
      Useful models are NOT “wrong”: they provide predictions and/or descriptions that are “right” to within their determined accuracies and precisions.
      All climate models are wrong and, therefore, they are NOT useful.
      Forecast skill is determined by comparing a series of predictions with empirical outcomes. No climate model has existed for the decades required to provide a series of future predictions of climate. Hence, although climate models may be useful heuristic tools, no climate model has any demonstrated predictive skill.
      Climate models have the same demonstrated predictive skill as the casting of chicken bones.
      Scientific models are evaluated by comparison with reality and NOT by comparison with other models selected as reference. Skill scores of models are relative to the models’ ability to predict outcomes in the real world and NOT what some other model does.
      Evaluating a model by comparing its performance to the performance of another model is pseudoscience.
      Brandon, you have polluted almost every part of this thread with your nonsense.
      Richard

      Mark W, It is clear that Brandon Gates is attempting to similarly pollute this thread with the same nonsense.
      Richard

      • richardscourtney,

        Clearly, what you call “internal variability” is an undefined excuse for all disagreements of the models with reality.

        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.

        In other words, your “internal variability” is magical mystery.

        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

        Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.

        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

        How do YOU explain The Pause without invoking “magic”? Come now, don’t be shy — demonstrate your superior scientific understanding and knowledge.

        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

        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.

        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

      • richardscourtney,

        I repeatedly asked 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 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.

        And you demonstrate that – as usual – you don’t understand what you have copied and pasted when you ask me
        How do YOU explain The Pause without invoking “magic”? Come now, don’t be shy — demonstrate your superior scientific understanding and knowledge.
        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.

        So, basically what you’re saying is that you don’t know.

        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.

        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.

        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
        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.
        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”.

        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.

        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.

        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

        Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.

        Your latest evasion says to me

        I don’t understand what you mean by “altering the empirical data”.

        Even by your standards, that statement is daft.
        You wrote

        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.

        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,

        My hyperbole?

        That’s what I wrote.

        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.”

        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.

        You are a lunatic … 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.

        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?

  2. Mission creep isn’t just for the boys at NASA. The NIH has joined in the climate study funding biz.

    • 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?

    • Phineas,
      ” Whatever will the hierophants of the Church of Anthropogenic Global Warming do?”
      ” … the Church of Anthropogenic Global Warming do-do”
      All sorted.
      Auto

  3. 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 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,

        It was only a few years ago we were being told that CO2 was so strong that it completely swamped all other factors.

        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,

        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

        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,

        It sure could change….. only if Brandon doesn’t bring up his “internal Variability” claims into the front of it.

        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,

        OK, so you don’t say “control knob”, but do say “dominant forcing” since 1950.

        Correct, that is how I most often see it described in literature.

        Your regression is not evidence.

        I took stats. I know that correlation does not necessarily imply causation. It can, however provide a big hint.

        All the actual physical evidence in the world falsifies your baseless assertion.

        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.

        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.

        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.

        Please provide some actual evidence. Thanks.

        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?

        If you foresee no catastrophic consequences to rising CO2, then why are you concerned about it?

        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.

        The models which you so admire predict catastrophically rising temperature and other evil consequences from more CO2. Why don’t you believe them?

        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.

        If you favor nuclear and alternate power sources for other reasons, then why does alleged but evidence-free AGW alarm you?

        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.”
        TSI levelled off at the highest levels for about 11,000 yrs (the Holocene approx) according to Usoskin (2014):
        https://wattsupwiththat.files.wordpress.com/2012/09/image_thumb6.png?w=773&h=620
        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,

        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.

        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.

      • 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.

      • 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,

        Climate models have zero predictive value.

        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 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.

      • goldminor,

        Go and show them where they are wrong with their models and long term perspective.

        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.

        All Hail, Brandon.

        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,

        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.”

        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.

        You have been repeatedly shown that Chimps (ENSEMBLE) models have never been close to the observed temperature range.

        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.

      • 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

        Pat Frank,

        Climate models have zero predictive value.

        The above statement is nonsensical gibberish.

        and

        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.

        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
        Your asserted magical mystery of “internal variability” is superstitious nonsense.
        And you repeatedly make the daft assertions that

        All models are always wrong. The question is whether or not they’re useful. See also: model skill is not an all-or-nothing proposition. Skill scores are also relative. Much depends on the reference model used in the evaluation.

        A model is wrong when it fails to provide predictions and/or descriptions that are within their determined accuracies and precisions.
        All climate models are wrong.
        Useful models are NOT “wrong”: they provide predictions and/or descriptions that are “right” to within their determined accuracies and precisions.
        All climate models are wrong and, therefore, they are NOT useful.
        Forecast skill is determined by comparing a series of predictions with empirical outcomes. No climate model has existed for the decades required to provide a series of future predictions of climate. Hence, although climate models may be useful heuristic tools, no climate model has any demonstrated predictive skill.
        Climate models have the same demonstrated predictive skill as the casting of chicken bones.
        Scientific models are evaluated by comparison with reality and NOT by comparison with other models selected as reference. Skill scores of models are relative to the models’ ability to predict outcomes in the real world and NOT what some other model does.
        Evaluating a model by comparing its performance to the performance of another model is pseudoscience.
        Brandon, you have polluted almost every part of this thread with your nonsense.
        Richard

        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,

        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.

        Ok, read all that. From your WUWT article, I take it the crux of your argument is this:

        http://wattsupwiththat.files.wordpress.com/2015/02/clip_image002_thumb2.png
        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.

        Please explain why the uncertainty envelopes in Panel B start circa 2000 instead of 1850.

        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.

        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,

        Useful models are NOT “wrong”: they provide predictions and/or descriptions that are “right” to within their determined accuracies and precisions.

        How does one “determine” a model’s “accuracies and precisions”?

        All climate models are wrong and, therefore, they are NOT useful.

        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 skill is determined by comparing a series of predictions with empirical outcomes.

        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

        Evaluating a model by comparing its performance to the performance of another model is pseudoscience.

        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.

        Climate models have the same demonstrated predictive skill as the casting of chicken bones.

        Please show your work.

      • The Ghost Of Big Jim Cooley,

        Brandon, you clearly underestimated Pat Frank – by using a flippant, throwaway line in a dismissive fashion.

        Interesting that you claim to know the outcome of the discussion even though it’s only just gotten underway.

      • HAS,

        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).

        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.

        The panel at the side shows just how far the modeled absolute temps are from the actual.

        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,

        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.

        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.

        Side-stepping your own argument is not allowed.

        Putting words in my mouth isn’t either.

        In your equation, mean squared error is, in fact, the definition of variance.

        You don’t say. The key question is: variance from what?

        So, you have now denied that skill score means inter-model variance, and then redefined skill score to mean inter-model variance.

        It’s not my definition.

        The PWM was used to demonstrate that climate models linearly extrapolate GHG forcing. It’s not a reference model, in your sense, at all.

        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.

        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.

        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 believe Richard Courtney has told you this repeatedly. You should pay attention, because he’s right.

        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,

        Just another couple of little contributions to the noise.

        Reading ahead, your contributions don’t look like noise to me at all.

        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.

        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.

        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.

        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.

        Second, data mining to find a correlation (say between temps and CO2) is fun, but it isn’t statistical analysis.

        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.

        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.

        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.”

        The paper that is the subject of this post shows some of the complications in doing all this.

        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,

        Brendon, bit of advice if you don’t understand something ask.

        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.

        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.

        Yup, that’s what I understood you to be referring to.

        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.

        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,

        Yes, agreed, you might have not thought you didn’t understand. From your comments here I can see how that could arise.

        “We fundamentally disagree, so you must not know anything” is not an atypical hypothesis.

        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.

        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.

        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.

        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

        Brandon Gates
        Your asserted magical mystery of “internal variability” is superstitious nonsense.bold
        And you repeatedly make the daft assertions that

        All models are always wrong. The question is whether or not they’re useful. See also: model skill is not an all-or-nothing proposition. Skill scores are also relative. Much depends on the reference model used in the evaluation.

        A model is wrong when it fails to provide predictions and/or descriptions that are within their determined accuracies and precisions.
        All climate models are wrong.
        Useful models are NOT “wrong”: they provide predictions and/or descriptions that are “right” to within their determined accuracies and precisions.
        All climate models are wrong and, therefore, they are NOT useful.
        Forecast skill is determined by comparing a series of predictions with empirical outcomes. No climate model has existed for the decades required to provide a series of future predictions of climate. Hence, although climate models may be useful heuristic tools, no climate model has any demonstrated predictive skill.
        Climate models have the same demonstrated predictive skill as the casting of chicken bones.
        Scientific models are evaluated by comparison with reality and NOT by comparison with other models selected as reference. Skill scores of models are relative to the models’ ability to predict outcomes in the real world and NOT what some other model does.
        Evaluating a model by comparing its performance to the performance of another model is pseudoscience.
        Brandon, you have polluted almost every part of this thread with your nonsense.
        Richard

        THOSE ARE CLEAR STATEMENTS OF SCIENTIFIC MODELLING PRINCIPLES.
        However, you have – at last – replied here but with (deliberate?) idiocy that begins

        richardscourtney,

        Useful models are NOT “wrong”: they provide predictions and/or descriptions that are “right” to within their determined accuracies and precisions.

        How does one “determine” a model’s “accuracies and precisions”?

        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

        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.

        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

        Climate models have the same demonstrated predictive skill as the casting of chicken bones.

        then asking me

        Please show your work.

        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,

        In reality, the usefulness of a model is a function of the model’s purpose.

        I agree, with the the additional criterion that a model cannot be expected to deliver better results than its stated design parameters.

        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.

        Ok good, now I understand better what you meant about accuracies and predictions. Thank you for elaborating.

        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.

        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,

        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.

        I repeat: Please describe for the class what the actual error is as of the year 2000.

        Back of the class for you.

        Um, ±18 C — the figure I stated — is the correct answer according to you.

        You made no mention at all of an observational standard.

        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

        It’s galling to be held to a higher standard of proof than the person making sweeping insinuations about my alleged dishonesty.

        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:

        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.

        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

        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?

        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,

        You ask me
        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?
        I answer: Total failure as predictive tools according to every metric.

        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.

        Please state what you mean by “internal variability” and how you determine when it is and when it is not altering the empirical data.

        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,

        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.

        !!!!
        Where’s the fire then?

        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.

        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.

        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.

        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.

        So, we’re back to you having never mentioned an observational standard until your third post on forecast skill in reply to Richard Courtney.

        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

  4. 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?

    • John Rolin,

      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?

      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.

      • Gloria Swansong,

        “They” can start modeling again in a few decades after more fundamental data have been collected.

        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,

        My reply didn’t post. I’ll try again.

        Sometimes this blog sends things to spam for strange reasons, generally the mods do a bang-up job fishing them out.

        Whatever is spent on GCMs is too much.

        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.

        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?

        Well yes, I’m the curious sort.

        At present the GCMs are repeatedly falsified cartoons that intentionally distort reality.

        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

        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.

        Your opinions are noted. Explanations, documentation, citations, evidence to support your criteria — as is becoming a pattern — are lacking.

        Climatology is in its infancy, or perhaps just starting to walk, but was tragically retarded by 30 years of ideologically motivated gibberish.

        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.

      • 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.

      • Michael Spurrier
        You write

        Brandon you didn’t seem to answer any of Pat Franks questions or replies……..

        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,

        Brandon you didn’t seem to answer any of Pat Franks questions or replies……..

        Even I need sleep from time to time. Once a month at least.

      • richardscourtney,

        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.

        I look forward to your thorough and complete documentation of that assertion. Thanks.

      • Pat Frank,

        Gloria’s conversation with you, Brandon, involves the validity of climate model projections. My comment is directly relevant to that topic.

        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.

    • Brandon Gates
      In response to my accurate statement saying

      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.

      you have said

      I look forward to your thorough and complete documentation of that assertion. Thanks.

      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,

        In response to my accurate statement saying
        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.
        you have said
        I look forward to your thorough and complete documentation of that assertion. Thanks.
        Complete?! Don’t be silly!

        Me silly? You’re the one claiming that I “only answer by copying&pasting”.

        Anybody can see the truth of my report for themselves, and it would require compiling several volumes to document every example.

        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

        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.

        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,

        I have no intention of debating all your childish excuses for copying&pasting passages you don’t understand.

        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,

        Troll posting as Brandon Gates

        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.

        I have made NO “handwaving assertions”.

        Your immediately following comment demonstrates yet another example:

        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.

        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.

        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.

        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

        More sound and fury, signifying nothing. I get it that my cogent, on-topic and well-cited remarks bother you.

        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.

        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 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,

        It beggars belief that you have the gall to write saying to me
        More sound and fury, signifying nothing. I get it that my cogent, on-topic and well-cited remarks bother you.
        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.

        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?

        This thread is NOT about your superstitious belief in anthropogenic (i.e. man-made) global warming (AGW).

        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.

        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.

        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?

        You have still not answered my simple question; viz.

        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, 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.

        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 yet again repeat my request that you stop polluting threads by thread bombing them with your irrational drivel.

        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

      • Troll posting as Brandon Gates
        Of course you don’t take me seriously. Clowns don’t take anything seriously.
        Richard

      • 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,

        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.

        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.

        People who don’t have arguments cannot provide them.

        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

        IOW, “internal variaiblity” is a change in surface temperature not driven by external radiative effects.

        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

        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.

        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.

        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.

        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,

        Troll posting as Brandon Gates

        Charming to the last.

        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.

        I want to say you’re welcome, but that could be seen a tacit admission that I’d been evading the question.

        Unfortunately, your attempt at an answer – while being long-winded and rambling – is illogical and incomplete.

        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.

        You refer to a post in which you wrote
        IOW, “internal variaiblity” is a change in surface temperature not driven by external radiative effects.
        OK. That is an honest statement of opinion (which is rare from you and is appreciated).

        Again, you make it difficult to thank you for the compliment without implicitly being self-incriminating on the rarity of my candour.

        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
        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.
        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”.

        So solar variations are out? Willie Soon, for one, would dispute that. So would the IPCC. How about orbital forcing a la Milankovitch theory?

        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”.

        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.

        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?

        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).

        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.

        Clearly that’s your opinion, and clearly I contest it.

        And I conclude by answering your two daft and off-topic ‘have you stopped beating your wife questions’ which you address to me; viz.
        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.

        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.

        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.

        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.

        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, 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

        Again, you make it difficult to thank you for the compliment without implicitly being self-incriminating on the rarity of my candour.

        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

        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.

        by you replying

        Clearly that’s your opinion, and clearly I contest it.

        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

  5. 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.

    • 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,

        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.

        I have this thing about not assuming that I know what people are referring to when they don’t deal in specifics.

        Somehow its messages is lost on you:

        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.

        You are not only light on substance, but totally lacking.

        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.

        I’ve backed up every statement I’ve made, apparently irrefutably, since you ignore my demonstrations of the falsity of your baseless assertions.

        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.

      • 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,

        Apparently you don’t know what evidence is.

        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]

        You have provided exactly zero in support of your baseless assertions and, it must be said, outright falsehoods.

        Then show me evidence of the truth. Since 1950. Chop chop.

        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.

        Ok, how do YOU determine causality in a complex system?

        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.

        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.

        Lots can be found within seconds by searching.

        So get to searching internal variability already.

        I shouldn’t have had to do so for you.

        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.

        QED. End of subject for me. As it should be for you, had you any shame. Trolling must be your job.

        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.

  6. 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

      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”

      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

      Near-zero and even negative trends are common for intervals of a decade or less in the simulations, due to the model’s internal climate variability. The simulations rule out (at the 95% level) zero trends for intervals of 15 yr or more, suggesting that an observed absence of warming of this duration is needed to create a discrepancy with the expected present-day warming rate.

      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

    • ” 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..

    • “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.

      • 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.

  7. 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.

  8. 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.

  9. 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.”
        Yes, Spring has a way of melting away Winter’s worries and thawing the frozen earth, does it not?

  10. 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.

  11. 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.

  12. ‘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.

  13. “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!

  14. 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.

  15. “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?

  16. 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!

      • 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.

      • 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,

        Gates, you promote yourself as a smart guy, yet you don’t get it.

        Smart as I allegedly am, I’ve never been able to understand nonsensical gibberish.

        Sad, but not my problem.

        I’m tempted to blame your science teachers, but that would be giving you an out I really ought not offer.

        And just to blow up your BS about ‘flat earth’, the earth is indeed flat over short distances.

        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.

        You may go now.

        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.

  17. 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.

      • 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.

      • There are people like Gates,who continue to persist with the idea that failed models such as Chimps are useful because, they supposedly tell us how to make better FUTURE Chimps models.
        Since the IPCC, for 20 years keeps posting a whole bunch of new Temperature modeling scenarios/predictions/projections, but be wrong EVERY TIME for those same 20 years,as they almost always run hot,sometimes waaaay hot!
        It would seem there has to be a time when people stop following a failed method (modeling scenarios in its present forms) try a different tack for better results,otherwise it is going to just another computer generated exercise that turns ever more people off, that it stagnates science research and that it becomes waste of time,as dead ends.
        I thought science is better advanced when they learn from failures, drop them or greatly modify their research run. But the IPCC , subsidiary groups keeps advancing the SAME failing approach,which make me believe they are NOT really advancing good science research. That they really do not know HOW to improve on their approach in producing better ,useful results that would truly advance the research field, to a greater level of understanding.
        I suspect part of the problem is their irrational fixation of casting CO2 as a powerful warm forcing villain,when the many discussions I have seen over the years show that it is only a minor absorber of IR energy. That WV is frequently overlooked as a much more active absorber of IR, with its greater capacity to absorb and “carry” energy it absorbs. That there are many factors,known unknown that also influence energy flows in and out of the system.
        I believe we have a long ways to go before we can even predict in the near future (5 years?) what the trends will be with a good level of confidence,simply because Climate is a highly chaotic phenomenon,with so many variables to account for.
        Thus I am always gobsmacked when I read of AGW believers who thinks CO2, a trace gas with a minor IR absorption capacity,can really move the temperature up rapidly. It is a place that should be considered as the twilight zone, as it is delusional.

  18. Since the end of the Little Ice Age in 1850, there have only been two brief periods with warming trends of around 0.14C~0.16C/decade: 1913~1943 and 1978~1998.
    The 1913~1943 warming cycle can’t be attribiputed to CO2 because CO2 concentrations were too low at that time. The only similarities between these two brief warming cycles are 1) both occurred during 30-yr PDO Warm Cycles and 2) both occurred during the strongest 63-yr string (1933~1996) of solar cycles in 11,400 years.
    When the strong solar cycles ended in 1996, so did the global warming trend:
    http://www.woodfortrees.org/plot/rss/from:1996.6/plot/rss/from:1996.6/trend/plot/esrl-co2/from:1996.6/normalise/trend/plot/esrl-co2/from:1996.6/normalise
    A 30-yr PDO COOL cycle started in 2005, so it’s highly likely that global temps will continue to remain flat/falling for another 20 years, in addition to the 18+ years of flat global temps trends observed since the middle of 1996.
    Moreover, the sun is entering a long inactive cycle, with a good chance of a Grand Solar Minimum (GSM) starting from solar cycle #25, which begins around 2022, which is highly likely to cause cooling global temp trends for the next 75 years if a GSM occurs.
    Almost 30% of all man made CO2 emissions since 1750 have been emitted over just the last 18 years, with virtually no global warming trend to show for it.
    Should flat/falling global temp trends continue for another 5~7 years, there will be more than sufficient empirical evidence to disconfirm the CAGW hypothesis because observations will exceed model projections by more than 3+ standard deviations for a period approaching a quarter of a century…
    CAGW is so busted…

      • “pining for the ocean bottoms”
        You do know how laughable that is, don’t you?
        Perhaps you should choose one of the other 67 mutually incompatible excuses for the pause.

      • MeNicholas– Robert was just making a joke from a line in Monty Python’s “Dead Parrot” skit:
        Customer: The parrot you sold me is dead.
        Proprietor: No it’s not. It’s just pining for his Norwegian fjords…

  19. Here is a fantastic comment from rgb,that I will post in full since it is from WUWT,but here is the link to it:
    http://wattsupwiththat.com/2013/10/14/90-climate-model-projectons-versus-reality/#comment-1449916
    When reading what Courtney,Brown and other scientists say about the OBVIOUS lack of demonstrated forecast skills, these models clearly have,it becomes necessary to drop them and try something better.
    ” rgbatduke
    October 16, 2013 at 9:42 am
    f that is a reasonable statement of the IPCC’s view of the models included in their report then the certainty of the future calculated by the models in the SPM do appear overstated as many have pointed out. What occurs to me is the IPCC can just say, in the face of criticism, something like (my words) => ‘we are being reasonably pre-cautious on the safe side in showing more future warming until, in the indefinite future, we finally get the models right.
    Just looking for were the IPCC’s CAGW hockey puck is going to be come January 2014.
    Your comment?
    PERSONAL REQUEST. => rgb, what is the status of your book ? You have mentioned in previous comments over the past year or so that you are working on (IIRC) a book on epistemic subjects.
    Yes, the IPCC could indeed say something like this. If the authors of its reports wanted to be brought before congress and charged with contempt of congress as the preferable and civilized alternative to being attacked by an angry mob armed with pitchforks and torches.
    This would be basically saying “We’ve been lying to you from the beginning, but it is for your own good, maybe, because we could have turned out to be right.”
    At times like these, I like to trot out a few lines from Feynman’s Cargo Cult address:
    Details that could throw doubt on your interpretation must be given, if you know them. You must do the best you can–if you know anything at all wrong, or possibly wrong–to explain it. If you make a theory, for example, and advertise it, or put it out, then you must also put down all the facts that disagree with it, as well as those that agree with it. There is also a more subtle problem. When you have put a lot of ideas together to make an elaborate theory, you want to make sure, when explaining what it fits, that those things it fits are not just the things that gave you the idea for the theory; but that the finished theory makes something else come out right, in addition.
    The removal of the lines clearly stating reasonable doubt from AR5’s SPM — is that the mark of good, honest science? Is failing to point out that the GCMs’ GASTA predictions alone are already in poor agreement with facts, let alone all the other parts of this quintessentially complex theory that don’t fit, the mark of good, honest science?
    I would like to add something that’s not essential to the science, but something I kind of believe, which is that you should not fool the layman when you’re talking as a scientist. I am not trying to tell you what to do about cheating on your wife, or fooling your girlfriend, or something like that, when you’re not trying to be a scientist, but just trying to be an ordinary human being. We’ll leave those problems up to you and your rabbi. I’m talking about a specific, extra type of integrity that is not lying, but bending over backwards to show how you’re maybe wrong, that you ought to have when acting as a scientist. And this is our responsibility as scientists, certainly to other scientists, and I think to laymen.
    For example, I was a little surprised when I was talking to a friend who was going to go on the radio. He does work on cosmology and astronomy, and he wondered how he would explain what the applications of his work were. “Well,” I said, “there aren’t any.” He said, “Yes, but then we won’t get support for more research of this kind.” I think that’s kind of dishonest. If you’re representing yourself as a scientist, then you should explain to the layman what you’re doing– and if they don’t support you under those circumstances, then that’s their decision.
    I would think that the same principle would apply to people who claim that their research is going to “save the world” to guarantee the continuation of what has grown to become one of the world’s fattest funding trees — provided, of course, that your proposed work is looking into anthropogenic global warming (that is, provided that you’ve already begged the question that AGW exists). Is the vast research infrastructure that has been built to study the climate and predict its future capable of surviving a “never mind, sorry, we got it wrong, there probably won’t be any catastrophic AGW after all” moment? Is it capable of the scientific honesty required to commit public seppuku, to literally spill its guts in expiation of the hundreds of billions of dollars misspent and the millions of lives being lost per year all due to the artificial inflation of carbon based energy prices?
    Even if it were, will it be given the chance? For a scientist you are right — saying “I was wrong” is a part of honest science. For a politician who supported the incorrect scientific conclusion and wasted our hard earned money and quite possibly contributed to the recent depression and near-collapse of the Euro, there are no second chances. Expect the tail to wag the dog, because the tail is in control of everything from funding streams to an entire network of media devoted to controlling public opinion and perception. Why do you think that they rewrote AR5’s SPM, the same way that they rewrote AR4’s SPM, after the actual scientists were done with it? Because if the SPM honestly stated the uncertainties, the IPCC would never have been more than a tiny, nearly irrelevant UN structure devoted to predicting and ameliorating things like the southeast asian monsoon, and the world’s poorest people would have far cheaper energy. Even the energy companies benefit from the panic that has been created. It has “forced” them to raise their prices, and their profits are margins on those prices. They don’t lose money because of CAGW, they make it!
    One example of the principle is this: If you’ve made up your mind to test a theory, or you want to explain some idea, you should always decide to publish it whichever way it comes out. If we only publish results of a certain kind, we can make the argument look good. We must publish BOTH kinds of results.
    I say that’s also important in giving certain types of government advice. Supposing a senator asked you for advice about whether drilling a hole should be done in his state; and you decide it would be better in some other state. If you don’t publish such a result, it seems to me you’re not giving scientific advice. You’re being used. If your answer happens to come out in the direction the government or the politicians like, they can use it as an argument in their favor; if it comes out the other way, they don’t publish at all. That’s not giving scientific advice.
    Where is the evidence that the people running the GCMs have ever “tested their theories”? When I glance at figure 1.4 of AR5’s SPM, can I pick out model results that nobody sane would consider not to have been falsified by the actual data? I can, easily. There are model results at the very top of the spaghetti envelope that are never anywhere close to the data. Why are they still there in the first place, contributing to the “meaningless mean” of all of the model results? Instead of openly acknowledging that these models, at least, have failed and throwing them out, they are included for the sole reason that they lift the meaningless mean of many GCMs, indeed, lift it a LOT as outliers.
    A lowered mean would be in better agreement with observation (and still would be meaningless as the average of many models is not a predictor of anything other than the average of many models according to the theory of statistics) but it would weaken all of the political arguments for expensive and pointless measures such as “Carbon Taxes” that bring great profit to selected individuals and will not, even according to their promoters, solve the climate problem by ameliorating CO_2 in the foreseeable future.
    We’ve learned from experience that the truth will come out. Other experimenters will repeat your experiment and find out whether you were wrong or right. Nature’s phenomena will agree or they’ll disagree with your theory. And, although you may gain some temporary fame and excitement, you will not gain a good reputation as a scientist if you haven’t tried to be very careful in this kind of work. And it’s this type of integrity, this kind of care not to fool yourself, that is missing to a large extent in much of the research in cargo cult science.
    What more can one say? AR5 has now “officially” bet the farm on its SPM. Everybody knows that the draft openly acknowledged the fact that the models are not working and contained a now-infamous figure that allowed any non-technical reader to see this for themselves. Everybody knows that this acknowledgement was removed in the official release, and that the figure in 1.4 was replaced by a figure that fairly obviously obscured the obvious conclusion — shifting and renormalizing the axes so that the data divergence was less obvious, replacing colored ranges with a plate full of incomprehensible spaghetti so that one can see that some colored strands spend some of their time as low as the actual climate.
    At this point they are at the absolute mercy of Nature. In two years, in five years, in ten years, either Nature will cause GASTA to shoot back up by 0.5C or so all at once so that it starts to correspond with the GCM predictions, or it won’t. If it doesn’t — worst case for them, if GASTA remains constant or actually descends (and there are some halfway decent reasons to think that it might well descend even without the use of GCMs at all, and they are not unaware of this and there are signs that the climate community is starting to break ranks on this) then they are done. The temporary fame and excitement that brought Michael Mann to the foreground as the cover story of many books will be replaced by ignominy, congressional investigations, and yes, pitchforks and torches and now they cannot back out of the latter because the changes in AR5’s SPM will be damning proof that climate science has been good old fashioned cargo cult science for two decades now, benefitting nobody but the high priests and politicians leading the cult.
    IMO this is unfortunate. Not all climate science has been dishonest. The actual scientific reports from the working groups have been a lot more open about uncertainties (although they too have suffered from political rewriting after the fact to eliminate some of this before the reports were allowed to go public). And I’m certain that a lot of research has been done in the best of faith. But when one is funded to do research on and report on how CAGW is going to affect the migratory behavior of species, you aren’t going to return an answer of “it isn’t” or an answer qualified by “IF AGW turns out to be a correct hypothesis”, you’re going to return an answer of “here are the expected effects given an assumed warming of X”. Bayes might as well never have lived.
    Finally, as regards my book Axioms, it is still being written, unfortunately. I’ve finished maybe half of it (and am pretty happy with that half) but the second half is the “messy” part of analyzing things like religion and ethics and I tend to rant too much and write too long every time I dig into it. I’m also insanely busy, and Axioms is just one of a dozen things on the back burner as I’m teaching a large class in physics, trying to fix up and improve my textbooks, get a startup company to take off so I can earn enough wealth in the process to be able to do whatever I like for the rest of my professional career, and get kids through college and launched. But it is near and dear to my heart. You can always go and grab the last image I uploaded before I quit working on it at:
    http://www.phy.duke.edu/~rgb/axioms.pdf
    This part does a fair job of working through elementary axiomatic metaphysics to where one has a defensibly “best” basis for epistemology and ontology, for a worldview, but one that is flexible enough to accommodate both some personal choice in what to believe and to accommodate the imperfect and incomplete and constantly changing description of “probable best belief” concerning propositions about the real world.
    Enjoy, at least so far.
    rgb”

    • Having read that several years ago, I still remember my thoughts to the value of cosmology to the laymen. Sure there aren’t any today, tomorrow or next year, but consider the following.
      450 years ago the new invention of the telescope began to allow for a clearer understanding of not just our solar system, but the universe in general. It led to a sweeping away within a century the paradigm of geocentrism that had ruled and been protected by religous authories for several millenia.
      Today’s cosmologists may indeed simply confirm the existing paradigm of Big Bang to Big Rip, or they may find a new paradigm that completely tears asunder the old. We do not know where that would lead, but today we have (or recently had) robotic explorers at Mars, Venus, Mercury, Jupiter and moons, Saturn and moons, Uranus, and soon Pluto and Charon, and two extrasolar voyagers still returning data, and samples from asteroids, and visits to comets. Galileo, Copernicus, Kepler, Brahe and many others times and fortunes of their era was money well invested.
      So too will be cosmology in the coming mid to late millenia. We just first have to cure this rabid Green Fever that generates CO2 alarmism.

  20. The term “climate wiggles” suggests that the “natural variation” they are talking about is actually a reference to what is usually called “internal variation.” Certainly they are not considering the possibility of any solar forcing beyond the very slight variation in TSI (total solar insolation), meaning that they are attributing all late 20th century warming to CO2. To the extent that it was actually caused by indirect solar effects (from the period of high solar activity that ended at the turn of the century) the implied sensitivity to a doubling of CO2 will get knocked further down, and may well be less than one.

  21. We don’t have 1000 years of temperature records. That means they had to use proxies. Since there are many proxies over this period and many of them don’t agree, the chances that this model is right are certainly in question.
    I actually like the idea, I just don’t know that it can be trusted. Maybe if several models were built using different proxies we could get a range. That might be useful.

  22. The hiatus was not modeled in either middle of the road models or any other. To assign it a value now as if it was is absurd. To pretend it is 11 years instead of 18 is childish. Do you think climate is aware of the common calendar? This is babble. An attempt to portray scientific disaster as a mere statistical misunderstanding .

  23. Here is how my simple brain translates this story into plain language:
    ” Just because we have been wronger than we thought we would be about how fast it would not get any warmer for the past twenty years, this does not mean we will continue to be wronger forever.
    Due to science, we will soon be righter than we thought, and the lack of recent warming is a bad thing, because it means it will get hotter faster, once we start being right again. Using 100 years of fake and cherry picked proxy data, we are about to figure out a new meme to justify our fat salaries and lard laden research grants, and thus keep the whole charade alive. Trust us…just because we never get anything right does not mean we do not know what we are doing or what we are talking about. That is just an optical illusion, caused by breathing record levels of poisonous CO2 carbon poison…stuff.
    In conclusion, the rates of warming that we have seen in recent years to have not occurred, should not be expected to last. Because of science, our analysis says things can change.”

    • Doh, darn… another typo: Using 1000 years of…
      I suspect these typos are lessening the impact of my careful analysis.

    • No Nicholas, you got it wrong. They are always getting righter, and in the future will be even more righter still.

      • Robert,
        I cannot tell if you really believe that or not.
        I suspect that you do not, just forgot the /sarc button.
        We need a bunch of new punctuation marks, to indicate things like sarcasm, smiling while ones says something, sneering condescension, etc.

  24. People should consider the threat of slow, decade change due to sea level rise against the threat of Islamists storming into your town on a Sunday afternoon and decapitating and raping your daughter, granddaughter, son and wife. Perhaps you’ll be left alive to contemplate the danger of climate change and 2 degree Celsius rise in a hundred years.
    It’s a matter of common sense and perspective. Religious believers become fixated on a subject and loose the ability to think and act rationally.

  25. This paper champions the fact that the Null Hypothesis of naturally changing climate cannot be rejected when real-world data is considered. The Null hypothesis is only rejected by those who accept a programmed CG simulation similar to a HollyWood superhuman movie of CG animations.

    • Do we know what significant advances in human knowledge have been made by the Meteorology dept at SJSU since that episode to justify their hatred of unorthodox views?

  26. “By comparing our model against theirs, we found that climate models largely get the ‘big picture’ ”
    Looks like the “Game of Pauses” is just a passing fad then Villagers. Better start looking for a new distraction…

  27. They do not mention the possibility that the climate scientists fiddled the results to match the previous variability when the supposed warming existed. Could it also be that there is not forcing caused by CO2 resulting in temperature changes but that CO2 is the result of temperature changes so instead of forcing there is negative feedback and a fundamentally stable system as the signal analysis would suggest?

  28. If no increase and therefore no movement is “progressing at moderate rate,” what type of movement would any increase be?
    Looks like a classic yes and no paper where the authors find it impossible to ignore what the data tells them but at the same time are fully aware that what it tells them is ‘not good news ‘ for their careers .

  29. Brandon Gates posted a graph earlier of radiation measurements made looking up and looking down made simultaneously. This is a very instructive graph to test one’s the understanding of radiative absorption.
    http://www.skepticalscience.com/images/infrared_spectrum.jpg
    When this was published in Grant Petty’s book, he asked a series of questions. These questions separate the sheep from the goats; those who know something about this subject from those who need to get up to speed.
    The questions are:
    a) what is the approximate temperature of the ground and how do you know?
    b) what is the approximate temperature of the near-surface air, and how do you know?
    c) what is the approximate temperature of the air at the aircraft’s flight altitude of 20km, and how do you know?
    So, are you a sheep or a goat?

    • First of all, this emission spectrum is from Petty 2006 and is over the Arctic Ice-Sheet on a completely cloudless day. Hardly a representative scenario.
      Second, all it shows is the effective emission temperature across the spectrum of CO2 absorption lines and Ozone absorption lines (when there is no cloud cover).
      The CO2 emissions to space cannot happen from the ground because they get intercepted in a few short metres by another CO2 molecule and technically, most of the energy is getting absorbed by Oxygen and Nitrogen when the excited CO2 molecule collides with them (at the surface, about 8 billion collions per second if you can believe it).
      It is not until one gets up to 10 kms high (in the Arctic), actually just above the tropopause, where emissions from CO2 now have 50% chance of getting emitted directly to space (and other CO2 molecules are not intercepting it and the molecular collision rate slows as the air becomes less dense). At this level, the temperature is 225K (-48C). THIS is CO2 cooling off the planet by emitting energy to space from high in the atmosphere.
      The other emission/interception area is from the Ozone layer at 8 kms up (240k at -33C) where one can see Ozone is actually intercepting sunlight at this level (it is not getting to the ground) and then the Ozone is just emitting much of that energy right back to space in a few seconds.
      This chart is NEVER described in the proper radiation physics sense that it is actually occuring at.

      • Bill, you seem to have avoided answering any of the three questions and chosen to write about something else.
        This is not a representative scenario? Sure it is. More than that, it is a real scenario. These are real measurements, not from some model. (although the Modtran model would produce a very close fit).
        http://beforeitsnews.com/mediadrop/uploads/2013/38/722d8552a9cbc163ecc372b97b57026d6b794ea6.png
        You could, of course, make measurements like this at other real location on Earth and ask exactly the same questions, only the answers would be different. Being able to interpret plots like these is essential to understanding what is happening in the real world.

      • Mike B,
        Here is the Modtran spectrum for mid-latitudes looking up from the surface on a low cloud cover day.
        The spectrum is the BLUE line (and it could be thought of as the back-radiation) and the surface temperature is 18C.
        A PERFECT blackbody spectrum with no CO2 or water vapor or Ozone emission lines. Just cloud cover blackbody. (and clouds are present in the atmosphere 65% of the time).
        http://s8.postimg.org/ugzcjycc5/Modtran_Mid_Latitude_Looking_Up_Surface.png
        The story is way more complicated than climate science says. (and your chart is for the Sahara on a cloud-free day).

      • JohnnyCrash,

        I have a vague idea what the chart means and I would like an explanation.

        I posted the plot originally as a bit of a test, MikeB backed it up with this addition:
        When this was published in Grant Petty’s book, he asked a series of questions. These questions separate the sheep from the goats; those who know something about this subject from those who need to get up to speed.
        The questions are:
        a) what is the approximate temperature of the ground and how do you know?
        b) what is the approximate temperature of the near-surface air, and how do you know?
        c) what is the approximate temperature of the air at the aircraft’s flight altitude of 20km, and how do you know?

        Since I started this, and you have asked, I’ll give my answers. By the letters:
        a) The approximate ground temperature is just shy of 270 K (-3.15 °C, 26.33 °F). I infer this from the upper plot, which shows the intensity of the radiation detected by the aircraft in the so-called “atmospheric window” regions between 8-9 and 10-13 μm wavelengths, which follow the predicted curve of the Planck radiation distribution function for an object at that temperature.
        b) The approximate near-surface air temperature is again just of shy of 270 K, yet a smidge cooler than the ground. I infer this from the bottom plot, which shows downwelling radiation at intensities between 13-16 μm as well as from 6-8 μm. Planck distribution again.
        c) This is a little tricky. The answer is that it’s in the neighbourhood of 225 K (-48.15 °C, -54.67 °F). I infer that from the Planck distribution in the 15 μm region of the upper plot, but that rests on the assumption that the atmosphere is all but entirely opaque to radiation in that band at that altitude, which it isn’t. Annoyingly, and not for the first time, Google has failed to give me a direct answer to that particular question. I also happen to know that the US standard atmosphere puts the temperature at about 220 K for that altitude, it seems reasonable to suppose that an aircraft at 20 km looking down will “see” some upwelling IR from warmer layers below it.
        In sum, these two plots show our friendly, essential to life as we know it, “greenhouse effect” in action on a clear sky day in the Arctic. I note some grumbling going on about 65% cloud cover. Well yes, clouds complicate matters, but that doesn’t negate the 45% of the surface which isn’t seeing clouds. It’s a big issue for making predictions going forward, not so much for understanding the basic theory. Why Bill Illis didn’t just answer the questions as posed is curious.

  30. Hypothesis fiddling after the fact is a no-no. Dance with the one that brung ya. The “worst case” is tied firmly to the extreme emissions scenario, which has been consistently and significantly (both senses) exceeded. It is illegitimate to try to keep results within the error bars by moving the goal posts. Make a new prediction and wait out the forecast period.

  31. “This would indicate that the global warming hiatus would need to continue for 8–16 years beyond 2013 before it could be said with over 99% confidence that the true forced signal is not increasing as quickly as these CGCM-produced forced signals.”
    This has got to be the only “science” where as long as there is a 1% chance you are right you are right. Today they agree that they are touching the 5% chance for all the emissions models, so they are 95% probability wrong but until they are 99% chance of being wrong they don’t want to give up claiming to be right.

    • And it has to be the only “science” where sitting at 5% probability they refuse to construct the model that would represent closer to the 50% probability because I guess that’s something they don’t want to show in their paper or get accused of being a denier?

      • “We find that the interdecadal variability in the rate of global warming over the 20th century (i.e., acceleration from ~1910–1940, deceleration until ~1975, acceleration until ~2000) is within the 2.5–97.5% EUN”
        So, around 2.5% chance today of being right is okay. We’re still good. In physics they need 6 sigma to be considered possibly right. Until you get 6 sigma verification you haven’t proved anything.
        In Climate “science” you need 6 sigma against you before you are wrong.
        “We find that a negative linear trend of 11 years is not extremely unlikely in any of the forced signal trajectories over this time period. In fact, for the RCP 6.0 forced signal, there is a ~70% chance of seeing at least one negative linear trend of 11 years or longer between 1993–2050 (see Methods).”
        And so with 11 years they are not extremely likely to be wrong, so again, that’s okay. As long as they aren’t extremely likely to be wrong, they are right.
        Of course, it’s been 18 years 5 months of linear trend if you use RSS satellite records. How’s that fit into their probability computation? 0.01% right? Still good! Until 2099 and temperatures are flat the whole way they will say there is still a 0.000001% chance that next year temps will jump 10 degrees in one year and make our numbers. It’s not over till the fat lady sings.

    • its even better than that , in reality they can endlessly extend the required time line becasue they always have the fall of of claiming ‘not yet but it will’
      If a snake oils salesman has found a way he can actually get people to buy snake oil, do you think he will turn around at ‘any time’ and tell people its worthless ?

      • The temps will almost certainly be moderate till close to 2030 due to amp/pdo. That’s 16 more years. By then the probability of their models will being correct will be 0.01%. I’m frankly surprised at their tenacity and the publics tenacity to continue to believe this stuff even as orobabilities have dropped to the 5% chance.

  32. These are baby steps.
    “Based on our analysis, a middle-of-the-road warming scenario is more likely, at least for now,” said Patrick T. Brown.
    Middle of the road is still too high. But it’s a tough pill to swallow. All the models are too high. All of them.

    • Since 1945 we have 0.4C gain (according to their adjusted data) and we’ve put up 130ppm of CO2 or about 50% of a doubling. Scientifically speaking the remaining 140ppm can generate no more than 30% of the entire TCS or 0.3C more gain. That means TCS is 0.7C not 3.0 not 6.0 not 2.5 or 2.0. TCS is proven by the data over 70 years now (1945-2015) to be 0.7C.
      It is scientifically implausible that TCS is 2.5 or 3.0 or 6.0. That is simply as scientific as you can get. After 70 years of data, the fact we continue to pour CO2 into the atmosphere at astonishing rates and a 18year 5 month haitus by RSS it is very clear that any projection north of TCS = 1.0 is impossible to defend except as theoretical unproven science.
      I see no way around this argument.

  33. So, there IS natural variability. Something climate science previously said was so small, that it could just be ignored. Well, they seem to have got that wrong didn’t they.
    Secondly, when one takes into account the impact of this natural variability, then one can tease out what the global warming/CO2 signal actually is in the real Earth tm.
    They are trying to make climate science fell good about themselves by explaining the hiatus as natural variability. They can all agree now that natural variability exists and that is the cause of the pause.
    But they still do not take the next step and say “how much warming does CO2 then produce in reality”. Temperatures went down from 1880 to 1918, they went up from 1919 to 1944, down from 1945 to 1976, up from 1977 to 1998, and now is flat or declining again.
    Take all those cycles into account properly rather than just focussing on the “last” pause period, and then one gets a CO2 warming rate that is just one-third to one-half of the theory.
    THAT is what the paper should be saying and what climate science needs to face up to.
    http://s23.postimg.org/t6xdylr9n/Hadcrut4_Warming_2100_Dec14.png

    • Well said, and a very useful figure that more or less reproduces my own fits graphed out above. In fact very accurately reproduces my fits above. Your AR5 MME mean does not agree with figure 9.8a in AR5, I should point out — it lies solidly above HadCRUT4 for a disproportionate amount of time in the 20th century as well as all of the 21st. One also cannot count “agreement” across the reference period around the 1980s because that is normalization to a free parameter. Basically everywhere outside of the reference period CMIP5 runs hot compared to HadCRUT4 four or five times more likely than it runs cold, and it never runs very cold but often is substantially hot.
      Here is a figure I made that is perhaps more illustrative of this:
      http://www.phy.duke.edu/~rgb/Toft-CO2-vs-MME.jpg
      The thin red line is from figure 9.8a. Black line is HadCRUT4 with error bars. Blue is the equivalent of your red line above — a direct fit of log forcing to HadCRUT4 (where the “RCP scenario” is irrelevant for past data and where I use a smooth curve for the past CO_2 that matches mean ice core data on one end and Mauna Loa (pretty much perfectly) on the other. Note that the red line is above the black line nearly all of the time and is only balanced relative to the black line across the reference period. It sometimes dips down to the black line but pretty much never descends below the black line.
      The green line is by far the best fit, and is really the only fit that stays inside the HadCRUT4 confidence intervals (whether or not they are believable) in a way that leads to a sane chi squared. One can actually reject the specific assertion “The CMIP5 MME mean is unbiased relative to HadCRUT4” with a rather enormously high confidence. It is not. In fact, given that the reference period is fit only by virtue of the fact that there is a free parameter in both curves (the zero point of the “anomaly”, and don’t get me started on the fact that this actual zero point temperature is both critical to the physics of radiative balance and not known within one whole degree C as far as global temperature estimates are concerned) I’d say that the p-value for a lack of bias is less than 0.01, possibly as low as 0.001. It also has the wrong spectrum, the wrong fluctuation signature, etc, but that is to be expected. The real problem is that if you look at the individual model runs themselves, they have the wrong fluctuation signature not by a little, but by a lot. Look at how large the residual fluctuations are from doing a superaverage of perturbed parameter ensemble averages from the individual models! The individual models have to be fluctuating by a factor of 2 to 5 too much compared to the actual climate, and with the wrong timescales.
      From fluctuation/dissipation we can thus immediately conclude that they are not correctly computing dissipation. Since dissipation is the whole object of the exercise in trying to estimate mean temperature and future climate for a chaotic open system, it means that the climate models are producing meaningless results because they manifestly do not contain or compute the correct physics. Their dissipative modes are not those of the actual climate system.
      rgb

  34. “there was a 70 percent likelihood that at least one hiatus lasting 11 years or longer would occur between 1993 and 2050”
    Like others have asked above what is the IPCC’s likelihood of a hiatus of 18 years? What if our current hiatus lasts 20? 30? 50?
    As I always like to ask those who feel that CO2 controls the climate “How long with flat or falling temperatures and rising CO2 before you admit it doesn’t?”.
    The IPCC modelers stated 15 years wouldn’t happen with a 95% confidence interval on that statement. Santer et al said 17 years.

    • IIRC they also said that of all the model runs, only 3% showed pauses of 10 years or longer. Their predictions are laughable.
      “The sky is falling! The sky is falling!”
      Thirty five years later:
      “Okay, the sky hasn’t fallen, but that doesn’t mean it won’t fall in the future.”

  35. “At any given time, we could start warming at a faster rate….”
    You flip a coin 18 times and get 18 tails. So you up the ante because future coin flips could start having a faster rate of being heads.
    Sucker.

  36. A favorite trick of those who defend the models is to provide graphs that include a lot of hindcasting. The only meaningful part of the data as far as testing the model is concerned is the prospective part where the modelers attempted to actually predict the future. That is, from the day the model predictions were published on. They will tweak the model to fit the known data, so that this fits the model is a given. (They even provide the model with data about aerosols that is impossible to predict, such as volcanic eruptions.) It is the period that they tried to predict in which the data was not known that is the real test. This part model defenders attempt to hide by confining it to a small segment of the graph. Blow this part of the graph up and you can see the real performance of these models, which is dismal.

  37. I am sure I am not the only one to be irritated by the constant — and meaningless — assertions that “97% of scientists” agree on the alarmists view of “global warming”. And I know that I’m not the only “scientist” who subscribes to Dr. Brown’s (rgbatduke, above) assertion that “climate models are producing meaningless results because they manifestly do not contain or compute the correct physics. Their dissipative modes are not those of the actual climate system. ”
    In an earlier phase of my life I oversaw the activities of fifteen engineers and programmers designing and producing a large-scale computer model/simulation (ASW), funded by a fat military budget. We learned, among many other things, that transforming such a model from being useless to being very valuable was quite difficult and at times we despaired of successfully completing it. Ultimately, though, we found that we had been closer to success than we had once feared, and only a few terms and parameters had actually needed to be adjusted. to make it work (somewhat).
    I suspect that the IPCC’s climate models can’t be fixed so easily. And I also suspect (actually, I am certain) that most of the commentary on these models and their outputs comes from folk who have little or no technical understanding of the actual models. The better the knowledge, the more likely the commentator is to agree with rgbatduke that the model results are “meaningless”.
    There is an opportunity, perhaps, to assert a “consensus view” by 97% of professional modelers that IPCC models “produce meaningless results”. I’m not sure how one would go about doing this; finding and polling the necessary 55 professional modelers would not be easy. But maybe someone with more energy and imagination than I may want to try it. (Note; professional modelers, not professional models).

      • Generous of you. I’ve lost track of how many times you’ve copypastaed the same section of AR4 over and over again. Not to mention Phil Jones’ BBC interview. Say … how’s that reading up on internal variability been going for you?

    • Won!?
      If you mean beat on the head with his own illogic and deceptive graphs, then yes, Brandon won the doofus award.
      Lneraho: You need to read the MikeB’s, Bill Illis’s and Dr. Brown;s comments along with quite a few others.

    • Lneraho,

      I think Brandon won.

      Thanks. Counting wendy makes two. Unfortunately you appear to have been outvoted; this comment …
      If you mean beat on the head with his own illogic and deceptive graphs, then yes, Brandon won the doofus award.
      … looks to be a representative enough sample. Note, however, that no explanation is given for why my graphs are “deceptive”. Par for this course, I’m afraid.

  38. I’ve seen almost no coverage of this study in the media. I guess I won’t hold my breath for that.

    • Because it’s depressing. You all get excited about because you can say the IPCC was wrong, when in fact it proves they are right, just not their worst-case scenario which everyone should be happy about. The trend is the same, your arguments the same.

      • What!
        I presented the IPCC own statement of temperature projections for first two decades,then showed the official temperature data. The result was the IPCC claim failed.
        Here is the comment you missed:
        http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913444
        “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.”
        I successfully made the case that the IPCC projection a failure.
        Heck he admits the models are wrong: “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.”
        http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1913513
        He got exposed as a Cut and past artist on unrelated stuff,that does not address what I was talking about.
        Richard C. Courtney pointed this out about Gates irrelevant “internal Variability” statements:
        http://wattsupwiththat.com/2015/04/21/study-global-warming-actually-more-moderate-than-worst-case-ipcc-models/#comment-1914067

      • “just not their worst-case scenario” – big media outlets seem to love putting out stories about the worst case scenarios with screaming headlines and pictures of things on fire or animals in trouble. It would be nice to see some balance now and then, a “Hey maybe the worst case scenario won’t happen” story or two.

  39. And what difference does it make if it’s 0.2, 0.1, 0.05 or 3? It’s warming, but more importantly they finally figured it’s climate change, not just a nicer, sunnier day. In other words, increased cloud coverage can be the result of higher temperature conditions but cap actual temperature increase in various layers. That doesn’t mean that there won’t be rainfall variability, storm intensity (20 inches in Sonoma but in 2 short, violent and warm storms), and jetstream impact. If we as humans can’t figure that when a strawberry picker from Mexico can buy a 5 bdrm, new construction home from Toll it’s all going to crash, how can we assume that we can figure out the climate? In a panel?

    • It is clear you are unwilling to go with the evidence presented.
      I have showed you what the IPCC said, the temperature data showed they are very wrong.
      The models have no credibility when they are wrong.

    • What difference does it make if it occurs at 1, 3, 5 or 50 miles an hour? It’s still a car crash.
      Think about that statement in the context of your statement about climate change, and you may form some idea about why the rate of change does, in fact, make a significant difference when we are being asked to divert billions and eliminate our key sources of energy in the name of climate change mitigation.

    • Translation:
      I can’t enter into a decent discussion on science, with a scientist, therefore fall back to ad hominem instead.
      You are now falling into the troll category.

      • Definitely trolling. I just do this to amuse myself and maybe give someone an embolism to reduce the carbon footprint one denier at a time.[Snip. Please stop trolling then. And note per site policy the pejorative “denier” is not welcome here. ~ mod.]

    • They’re thinking that solar farms are in the pits!
      These pros do not buy high and sell low; they buy low and sell high.
      Industrial zoned land is always valuable. It was Buffet who answered a wannabe’s question on how to get rich; “Buy real estate and live a long time”.
      Bias is knowingly abusing the scientific process to reach predetermined decisions. When a person refuses to allow their opinions to blind their research, that is not bias.

    • Trying to reply to RACookPE1978 who makes some great observations. We actually can reverse and clean some of these places and things up. LA though…better, but you still can’t read a bold sign 5 blocks away in downtown due to the haze, not exactly the best example, and call it what you want, but the pollution from Beijing and China makes it all the way to LA and 364 days of smog is climate change from their perspective. The Yangtze River Dam was also just a local construction project but has reportedly change the tilt or rotation of the planet enough to be noticed. China as we all know is not Cooper Hill. A scientist could clarify that comment though re tilt.

      • China, needs to pass an equivalent of the 1963 Clean Aid Act, before they clean up their act.

      • The Three Gorges Dam probably hasn’t changed earth’s axis of rotation (tilt), but possibly has altered its rate of rotation by a tiny, perhaps immeasurable fraction. However, earthquakes, volcanic eruptions & the most energetic storms already do that in random, unpredictable ways. The moon’s tidal effect slows earth’s rotation & adds a second to the length of a day every 40,000 years. The sun’s tidal effect is about eight seconds per million years.
        IOW, the rotational effect is essentially non-existent. There are of course other, more significant environmental effects.

    • So far you have said nothing useful here.
      I cited the IPCC and Official temperature data,you come back with nothing,but babbling bubbles.
      You are indeed a troll.

      • I think being called a troll is an ad hominen attack, but [Snip. You admitted to being a troll above. Please stop it. The rest of this comment is way off-topic. ~mod.]

      • Moderator: [Sorry for the snip, but moderators do not debate. Please direct comments to other readers, or to the author of the article. Regarding your question about linking, others link to those sites with no problem. ~mod.]

  40. You make clear you didn’t read the links because they referred to comments,that in them explained why I stated Gates was being wrong.
    Too bad you have so much bigotry in you.
    But I will try one more time,using just the IPCC words and temperature data:
    “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.”
    http://www.ipcc.ch/publications_and_data/ar4/wg1/en/spmsspm-projections-of.html
    They say at least .30C per decade is projected, but the official temperature data shows a very different picture:
    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
    Zero to a slight cooling instead.
    Normally that is considered a catastrophic failure.
    I had honestly showed you, Gates agreement with me, that the Chimp models the IPCC used were indeed running hot, way too hot by the posted temperature data result.
    This means they failed, this means they can’t support the AGW conjecture with them,as they have been wrong for 25 years now.
    Grow up fella.

    • Referring to Pete, yes, it is the rate of change I was trying to address, not nominal numbers, as well as the direction. In most systems change happens on the margin, and does not require a substantial underlying shift to cause movement. So the fact that Boston’s average temp is down is irrelevant if Siberia and the Arctic are up which impacts the jetstream, which impacts Boston… But I personally don’t care if someone, the IPCC or Fred Singer thinks 3C is the number. They don’t know. And analyzing core samples from a glacier in Nepal to see what happened 10,000 years is irrelevant to understanding what is happening in Beijing, which is clearly man made climate change.

      • Lneraho

        And analyzing core samples from a glacier in Nepal to see what happened 10,000 years is irrelevant to understanding what is happening in Beijing, which is clearly man made climate change.

        And analyzing core samples from a glacier in Nepal to see what happened 10,000 years is irrelevant to understanding what is happening in Beijing, which is clearly man made local weather climate change.
        As was Pittsburgh’s dirty local valley conditions – which cleared up in less than ten years.
        And Los Angeles local valley conditions – which also cleared up very quickly.
        As did London’s deadly local conditions – which cleared very quickly up once electric power became available, and coal (in individual chimney burners) was not burned in stoves for cooking and heating.
        Beijiing will clean up as soon as the Chinese generals decide they want to spend the money to clean it up.
        Copper Hill TN (lead mining, sulfuric acid processing, copper mining and refining, cadmium and other deadly mineral, etc, etc … was a rocky blank hillside only 20 years ago. It is now pine trees and scrub grass. And bugs and deer and wild pigs and squirrels and tourists.

  41. That even with Asthma I haven’t had to buy canned air after 1999 I would have to say that these warmist skyfall luddite overpaid smearers of feces on paper couldn’t predict what a clock would say a minute from meow.
    The truth here is that we’re supposed to all be more than a decade dead and we haven’t done ANYTHING other than the 1998 CFC bans to stop it. Global warming happened, we fixed it.
    Has the billions we’ve poured in made a difference? Nope. Its made the world a little nicer and a little healthier and my water heater is being replaced next year by a closed cycle 240° oil ballast system that’ll cut my power bill by about $55 a month but in the end what they’re selling just isn’t possible.
    We’ll lose 90% of our atmosphere before the surface temp rises from pollution alone.

  42. Let me get this straight: isn’t this the sort of conclusion that made you a ‘flat earther’ under a decade ago??
    And now where is the discussion that, if ‘natural factors’ can cause ‘hiatuses’ of > 10 years, then presumably their magnitude must be equal to- or greater than the effect of man-made global warming, since if it weren’t, the hiatus couldn’t possibly occur, could it??
    Thirdly, where is the discussion of whether plants display Michaelis-Menten-style growth kinetics (for the non-biologists amongst you, MM Kinetics describe how the rates of enzymatically catalysed reactions proceed, namely V(E) = V(max)* [E]*[S]/(K(m) + [S]), where [E] is the concentration of enzyme, [S] is the substrate concentration and K(m) is the Michaelis Menten constant for that reaction and represents that substrate concentration at which reaction rate is 50% of the maximum possible rate V(max)) in response to carbon dioxide (i.e. increasing carbon dioxide stimulates plant growth which returns carbon dioxide to a solid carbon state at a greater rate than before, thus representing a self-correcting mechanism)?
    Fourthly, in this ‘big picture’ long term analysis, what was driving big changes before horrible old homo sapiens came along?? Was it the sun?? Was it volcanic ash in the atmosphere?? Was it great fires burning whole continents of forests down?? Must have been something ‘natural’ mustn’t it?? Because we weren’t around to drive it……
    There is no big picture from 1850 to the present day: that is just a blip in climate history.
    There is, however, a need to secure further grant funding and currently this requires ‘tweaking the revised version of the climate bible to a new politically acceptable format’.
    Isn’t it about time that a few George Foxes of quaker radicalism fame confronted the climate church in suitably formidable manners and told them where to take their idolatries, their climate gold, frankincense and myrrhs, their devotionals and their grant-seeking hymn sheets??

  43. Brandon,
    We have now had two intervals of flat to declining temperature during the period in which you claim that man-made CO2 is the dominant forcing. Together they outnumber the warming years by 2.6 to one (the 52 years 1944-76 plus 1996-present vs. the 20 years 1977-96).
    Only the ideological, delusional and bought off could possibly maintain this crazy hypothesis in the face of such irrefutable evidence. You’re worse than tired to hold such an insane opinion.
    You still haven’t responded to my evidence that your delusion is false. There is no difference between previous 20 or 30 year-long warming trends and that of the late 20th century. In fact, many have been stronger for longer.
    So this really is the last from me. You can’t or won’t respond despite repeated chances, so you’re a hopeless case, as so many have concluded.

    • Gloria Swansong,

      We have now had two intervals of flat to declining temperature during the period in which you claim that man-made CO2 is the dominant forcing. Together they outnumber the warming years by 2.6 to one (the 52 years 1944-76 plus 1996-present vs. the 20 years 1977-96).

      Counting the number of years of decline vs. rise is meaningless unless it’s also tied to the magnitude of the trends. The very fact that the data show temperatures at present ~0.3 K higher than at roughly the same point of the previous hiatus (~1965) really ought to suggest something to someone who understands basic arithmetic.
      Here’s another pretty picture:
      http://1.bp.blogspot.com/-o4vtAlhwkrI/VTrVEyu5ceI/AAAAAAAAAcs/MuA5KTmbm5I/s1600/HADCRUT4%2B12%2Bmo%2BMA%2BForcings%2Bw%2BTrendlines.png
      We can play around with cherry-picked trendline endpoints until the cows come home and “prove” whatever we want in so doing. There’s a better way … calculate continuous linear trends using multiple sampling periods:
      http://4.bp.blogspot.com/-LaL4Fv8E0UM/VTrVE1QKtBI/AAAAAAAAAco/znQkNHbJeFE/s1600/HADCRUT4%2BTrend.png
      Mind the y-axis scale changes from top to bottom. The take-away message is that the shorter the sampling period, the more dominant the wiggles from internal variability. At present, according to my estimates, CO2 forcing only exceeds historical bounds of internal variability over something between 240 and 360 month time scales. At 480 month time scales, CO2 at present levels and rate of change is pretty clearly dominant.

      You still haven’t responded to my evidence that your delusion is false.

      Hmmm, may I quote you on that next time richardscourtney goes nuclear on me for being egregiously insulting to you?

      There is no difference between previous 20 or 30 year-long warming trends and that of the late 20th century.

      Hint: look at the slope of the cooling trends. Is the temperature in 2014 higher or lower than in 1880. How did it get there if all the periodic trends are always the same?

      So this really is the last from me.

      I’ll believe it when I don’t see it.

      You can’t or won’t respond despite repeated chances, so you’re a hopeless case, as so many have concluded.

      …. annnnnd here I was thinking that science wasn’t a popularity contest. So much for THAT myth!

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