Gavin Schmidt confirms model excursions

Gavin Schmidt asks at RealClimate: “How should one make graphics that appropriately compare models and observations?” and goes on to reconstruct John Christy’s updated comparison between climate models and satellite temperature measurements. The reconstruction was cited here by Simon in response to Gary Kerkin’s reference to Christy’s graph ( – h/t Richard Cumming, Gary Kerkin and Simon for references).

There’s been a lot of blather about Christy’s telling graph and heavy criticism here from Schmidt — but the graph survives. In taking all the trouble to point out where Christy is wrong, even going so far as to provide an alternative graph, Schmidt amazingly fails to alter the impression gained from looking at it. Even in his reconstruction the model forecasts still soar way above the observations.

So Christy’s graph is true. What else does it need to say to sentence the models to fatal error and irrelevance? Are our policy makers listening?

Though he alters the baseline and other things, the graphic clearly reveals that since about 1998 most climate models have continued an excursion far above the actual surface temperatures. This failure for nearly 20 years to track actual temperatures reveals serious faults with the models and strongly suggests the greenhouse hypothesis itself is in deep trouble.

The continued refusal of those in charge of the models to announce that there’s a problem, to talk about it or explain what they’re doing to fix it, illustrates the steadfastly illusory nature of the alarm the models — and only the models — underpin. When the models are proven wrong like this yet tales of alarm don’t stop, we can be sure that the alarm is not rooted in reality.

Gavin Schmidt's 'improved' version of John Christy's iconic graph comparing climate model output with real-world temperatures

Gavin Schmidt’s ‘improved’ version of John Christy’s iconic graph comparing climate model output with real-world temperatures

Here’s Christy’s updated graph, as he presented it to the U.S. House Committee on Science, Space & Technology on 2 Feb 2016.

John Christy's updated graph as presented to the US House of Representatives committee last February

Christy comments that “the Russian model (INM-CM4) was the only model close to the observations.”

Gavin Schmidt’s confirmation of the essence of Christy’s criticism of the models signals deep problems with Schmidt’s continued (stubborn?) reliance on the models. Christy’s presentation goes on:

The information in this figure provides clear evidence that the models have a strong tendency to over-warm the atmosphere relative to actual observations. On average the models warm the global atmosphere at a rate 2.5 times that of the real world. This is not a short-term, specially-selected episode, but represents the past 37 years, over a third of a century. This is also the period with the highest concentration of greenhouse gases and thus the period in which the response should be of largest magnitude.

Richard Cumming has several times recently said (on different grounds) that “we are witnessing the abject failure of the anthropogenic global warming theory.” I can only agree with him.

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Richard C (NZ)
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Richard C (NZ)

The El Nino spike at the beginning of 2016 was as good as it gets for Schmidt, now he’s looking at his own GISTEMP cooling rapidly. That was the El Nino Schmidt claimed for man-made climate change leaving the El Nino contribution only 0.07 C:

Schmidt estimated El Niño was responsible for 0.07C of the above-average warming we saw in 2015.

https://www.carbonbrief.org/analysis-how-much-did-el-nino-boost-global-temperature-in-2015

Egg on face now.

Richard C (NZ)
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Richard C (NZ)

>”Christy comments that “the Russian model (INM-CM4) was the only model close to the observations.” I inquired from John what that model was when he first started compiling these graphs. He didn’t know why INM-CM4 was different. Others have looked into it though: INMCM4 (Russian Academy of Sciences) in Judith Curry’s post: ‘Climate sensitivity: lopping off the fat tail’ There is one climate model that falls within the range of the observational estimates: INMCM4 (Russian). I have not looked at this model, but on a previous thread RonC makes the following comments. “On a previous thread, I showed how one CMIP5 model produced historical temperature trends closely comparable to HADCRUT4. That same model, INMCM4, was also closest to Berkeley Earth and RSS series. Curious about what makes this model different from the others, I consulted several comparative surveys of CMIP5 models. There appear to be 3 features of INMCM4 that differentiate it from the others.” 1.INMCM4 has the lowest CO2 forcing response at 4.1K for 4XCO2. That is 37% lower than multi-model mean 2.INMCM4 has by far the highest climate system inertia: Deep ocean heat capacity in INMCM4 is 317 W yr m22… Read more »

Richard C (NZ)
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Richard C (NZ)

‘Climate Models are NOT Simulating Earth’s Climate – Part 4’ Posted on March 1, 2016 by Bob Tisdale Alternate Title: Climate Models Undermine the Hypothesis of Human-Induced Global Warming […] THE PECULIARITY In the real world, according to the hypothesis of human induced global warming, if the Earth had a negative energy imbalance (that is, the outgoing energy was greater than incoming), wouldn’t global surfaces be cooling? They aren’t in the 5 models with the negative energy imbalances. See Figure 4. In fact, regardless of whether the climate models are showing the extremely high positive top-of-the-atmosphere energy imbalances or showing negative imbalances, all of the models show global surface warming. In other words, global surface warming is not dependent on a positive energy imbalance in 5 of the climate models used by the IPCC for their 5th Assessment Report. More>>>>> https://bobtisdale.wordpress.com/2016/03/01/climate-models-are-not-simulating-earths-climate-part-4/ # # # The earth’s energy balance is the IPCC’s primary criteria for climate change whether natural cause or anthropogenic theory. A positive imbalance is a system heat gain, a negative imbalance is a system heat loss. But contrary to IPCC’s climate change criteria, even the climate models exhibiting a negative imbalance… Read more »

Richard C (NZ)
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Richard C (NZ)

>”The continued refusal of those in charge of the models to announce that there’s a problem,……”

To be fair, the IPCC announced the problem in Chapter 9 Box 9.2. They even offer 3 or 4 reasons why the models are wrong. Main ones are that model sensitivity to CO2 is too high (CO2 forcing is excessive) and neglect of natural variation. The latter what sceptcs had been saying for years previous to AR5 and the IPCC finally had to concede.

We didn’t read the news headlines about that though.

Thing is, if the smoothed observation data does not rise above flat over the next 3, 4, 5, 6, 7 years (give them 5 yrs), CO2 forcing is not just excessive, it is superfluous.

This is the acid test for the GCMs. The AGW theory having already failed its acid test by the IPCC’s own primary climate change criteria (earth’s energy balance measured at TOA), see this article for that:

IPCC Ignores IPCC Climate Change Criteria – Incompetence or Coverup?
https://dl.dropboxusercontent.com/u/52688456/IPCCIgnoresIPCCClimateChangeCriteria.pdf

Richard C (NZ)
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Richard C (NZ)

>”…..there’s still been no rush to a press conference to announce an investigation” No investigation but at least someone is trying to take natural multi-decadal variation (MDV) out of the models -obs comparison. I’ve intoned on this here at CCG at great length so not much here. Basically, models don’t model ENSO or MDV so both must be removed from observations before comparing to model runs. Kosaka and Xie are back on this after their first attempt which I thought was reasonable (I think I recall), I would point out that there is already a body of signal analysis literature that extracts the MDV signal from GMST – it’s not that difficult. What happens then though is that there’s a miss-attribution of the residual secular trend (ST, a curve) to the “anthropogenic global warming signal”. It becomes obvious that the ST is not CO2-forced when the ST is compared to the CO2-forced model mean. The model mean is much warmer than the ST in GMST. Problem now is: Kosaka and Xie’s latest effort below is nut-case bizarre: ‘Claim: Researchers create means (a model) to monitor anthropogenic global warming in real time’ https://wattsupwiththat.com/2016/07/18/claim-researchers-create-means-a-model-to-monitor-anthropogenic-global-warming-in-real-time/ This… Read more »

Richard C (NZ)
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Richard C (NZ)

From 1980 on, Kosaka and Xie’s graph is no different to Schmidt’s or Christy’s.

Simon
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Simon

You should probably explain to casual readers what TMT actually is, as it is not obvious.
Temperature measurements in the mid-troposphere are considerably less understood than the surface.
Note that the CMIP5 runs are projections not predictions. The comparison would have been much fairer if the models were retrospectively re-run with known solar + volcanic forcings and ENSO outcomes.
There is as yet insufficient evidence to say that the models are biased and there may yet be issues with satellite observation degradation.

Andy
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Andy

There is a big difference between a projection and a prediction. We can predict the weather a few days out, but a projection of what a company or technology might look like in 10 years time is largely speculation and guesswork.

Richard C (NZ)
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Richard C (NZ)

Simon >”The comparison would have been much fairer if the models were retrospectively re-run with known solar + volcanic forcings and ENSO outcomes.” Heh. Except for ENSO (wrong there – see below) you’re just repeating what the IPCC conceded in AR5 Chapter 9 Box 9.2. But they add that CO2 sensitivity is too high i.e. CO2 forcing is excessive, and that “natural variation” (not ENSO) has been neglected. In effect, you are tacitly admitting the models are wrong Simon. You’re not alone, the IPCC do too. Volcanics are transitory – see below. ENSO is irrelevant and NOT the “natural variation” the IPCC are referring too. Models don’t do ENSO. Therefore a direct models-obs comparison is with ENSO noise smoothed out. When Schmidt does that in his graph (as Christy did) he’ll be 100% certain that 95% of the models are junk. “Natural variation” is predominantly due to oceanic oscillations e.g. AMO, PDO/IPO etc, otherwise known as multi-decadal variation (MDV), which distort the Northern Hemisphere temperature profile which then overwhelms GMST. The oscillatory MDV signal is close to a 60 yr trendless sine wave which can be subtracted from GMST so that the residual… Read more »

Simon
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Simon

I absolutely support the general conclusions of these studies. The proportion of climate scientists who support the AGW hypothesis is greater than 95%. Do you concur?
I am most curious how an non-specialist such as yourself can somehow ‘know the truth’ whereas the scientific consensus has ‘got it wrong’. You might also like to comment how you managed to avoid the Dunning-Kruger effect.
Note also that ENSO, like weather, is chaotic. We can predict the probability of occurrence, but not when they will occur beyond a limited time horizon. What is important is the trend. An expert would know that.
Nobody apart from yourself is talking about ‘uprooting energy sources’. I would suggest that it is this concern that is causing your cognitive bias.

Richard C (NZ)
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Richard C (NZ)

‘A TSI-Driven (solar) Climate Model’ February 8, 2016 by Jeff Patterson “The fidelity with which this model replicates the observed atmospheric CO2 concentration has significant implications for attributing the source of the rise in CO2 (and by inference the rise in global temperature) observed since 1880. There is no statistically significant signal of an anthropogenic contribution to the residual plotted Figure 3c. Thus the entirety of the observed post-industrial rise in atmospheric CO2 concentration can be directly attributed to the variation in TSI, the only forcing applied to the system whose output accounts for 99.5% ( r2=.995) of the observational record. How then, does this naturally occurring CO2 impact global temperature? To explore this we will develop a system model which when combined with the CO2 generating system of Figure 4 can replicate the decadal scale global temperature record with impressive accuracy. Researchers have long noted the relationship between TSI and global mean temperature.[5] We hypothesize that this too is due to the lagged accumulation of oceanic heat content, the delay being perhaps the transit time of the thermohaline circulation. A system model that implements this hypothesis is shown in Figure 5.” “The… Read more »

Andy
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Andy

The proportion of climate scientists who support the AGW hypothesis is greater than 95%.

What is the AGW hypothesis?

What hypothesis, or lack thereof, do the other 3-5% subscribe to, to explain whatever phenomenon they assert needs explaining?

Richard C (NZ)
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Richard C (NZ)

Simon >”I absolutely support the general conclusions of these studies. The proportion of climate scientists who support the AGW hypothesis is greater than 95%. Do you concur?” Climate scientists? I don’t think so. From Verheggen (2014): Gonzalez, G. A. An eco-Marxist analysis of oil depletion via urban sprawl. Environ. Polit. 2006, 15, 515−531. Entman, R. M. Improving Newspapers’ Economic Prospects by Augmenting Their Contributions to Democracy. Int. J. Press- Polit. 2010, 15, 104−125. Harribey, J. M. The unsustainable heaviness of the capitalist way of development. Pensee 2002, 31 − +. Delmelle, E. C.; Thill, J.-C. Urban Bicyclists Spatial Analysis of Adult and Youth Traffic Hazard Intensity. Transp. Res. Record 2008, 31−39. Howard, C.; Parsons, E. C. M. Attitudes of Scottish city inhabitants to cetacean conservation. Biodivers. Conserv. 2006, 15, 4335−4356. McCright, A. M.; Dunlap, R. E. Cool dudes: The denial of climate change among conservative white males in the United States. Glob. Environ. Change-Human Policy Dimens. 2011, 21, 1163−1172. An “eco-Marxist analysis” is a scientific analysis of global warming by climate scientists? Get real Simon. Similarly for Cook et al. Psychologist José Duarte writes: The Cook et al. (2013) 97% paper included a… Read more »

Richard C (NZ)
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Richard C (NZ)

Andy

>”What is the AGW hypothesis?”

Has never been formally drafted. But we can infer one from the IPCC’s primary climate change criteria:

The AGW hypothesis: The earth’s energy balance, measured at the top of the atmosphere, moves synchronous with and commensurate with anthropogenic forcing

Falsified by the IPCC’s cited observations in AR5 Chapter 2.

Richard C (NZ)
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Richard C (NZ)

Simon >”What is important is the trend.” No Simon, the (temperature) trend is not important. It is not even critical. What is critical is the IPCC’s primary climate change criteria: “The energy balance of the Earth-atmosphere system…..measured at the top of the atmosphere” The critical trend is in this criteria and it is NOT temperature in Kelvin or Celsius, it is the TOA energy imbalance stated in units of W.m-2. The IPCC concede in AR5 Chapter 2 that it is “highly unlikely” that there is a statistically significant trend in the imbalance. If the IPCC’s forcing theory was valid, there SHOULD be a trend because both theoretical CO2 RF and total effective anthro forcing (ERF) is increasing. In AR5 CO2 RF was 1.83 W.m-2 and ERF was 2.33 W.m-2. Instead, the IPCC reported that the imbalance was static around 0.6 W.m-2 i.e. their forcing theory is invalid. But the IPCC didn’t address the critical discrepancy. Read about that here: IPCC Ignores IPCC Climate Change Criteria – Incompetence or Coverup? https://dl.dropboxusercontent.com/u/52688456/IPCCIgnoresIPCCClimateChangeCriteria.pdf But back to the trend that you seem to think is “important”. John Christy states in the post above: “On average the models… Read more »

Richard C (NZ)
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Richard C (NZ)

Crud. Missed a tag after “The energy balance of the Earth-atmosphere system…..measured at the top of the atmosphere”

I Was using my “slim”, but fast, browser version which doesn’t give me the Edit facility.

Richard C (NZ)
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Richard C (NZ)

>”The oscillatory MDV signal is close to a 60 yr trendless sine wave which can be subtracted from GMST so that the residual secular trend (ST) can be compared to to the model mean…..” Bob Tisdale doesn’t grasp this. See his latest: ‘June 2016 Global Surface (Land+Ocean) and Lower Troposphere Temperature Anomaly Update’ Bob Tisdale / July 19, 2016 https://wattsupwiththat.com/2016/07/19/june-2016-global-surface-landocean-and-lower-troposphere-temperature-anomaly-update/ Scroll down to MODEL-DATA COMPARISON & DIFFERENCE The graph below shows a model-data difference using anomalies, where the data are represented by the UKMO HadCRUT4 land+ocean surface temperature product and the model simulations of global surface temperature are represented by the multi-model mean of the models stored in the CMIP5 archive. Like Figure 10, to assure that the base years used for anomalies did not bias the graph, the full term of the graph (1880 to 2013) was used as the reference period. In this example, we’re illustrating the model-data differences smoothed with a 61-month running mean filter. (You’ll notice I’ve eliminated the monthly data from Figure 11. Example here. Alarmists can’t seem to grasp the purpose of the widely used 5-year (61-month) filtering, which as noted above is to minimize the variations… Read more »

Richard C (NZ)
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Richard C (NZ)

Michael Mann:

“I am a climate scientist and have spent much of my career with my head buried in climate model output and observational climate data, trying to tease out the signal of human-caused climate change.”

http://www.ecowatch.com/right-wing-denial-machine-distorts-climate-change-discourse-1924120031.html

Apparently Michael Mann “supports the AGW hypothesis” (as per Simon), but he’s having a great deal of difficulty actually applying it to the real world.

That’s if his use of the phrase “trying to tease out” is anything to go by.

Alexander K
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Alexander K

I am not a scientist of any kind, but learned many years ago that data gained from careful and thorough observation trumps models every time.
While I have earned a living doing many things at various times, I have found that engineers work from a philosophy that I can agree with. Scientists not so much, particularly ‘Climate Scientists’.

Richard C (NZ)
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Richard C (NZ)

Schmidt’s latest:

When it comes to what caused the record highs of 2016, “we get about 40 per cent of the record above 2015 is due to El Nino, and 60 per cent is due to other factors”, Schmidt said.

http://www.smh.com.au/environment/climate-change/june-sets-another-global-temperature-record-extending-a-blazingly-hot-year-20160719-gq9eo4.html

No mention of what the “other factors” are. Note the plural.

And no mention that the temperature spike peaking in Feb 2016 was only in the Northern Hemisphere.

Gary Kerkin
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Gary Kerkin

Richard C. “When it comes to what caused the record highs of 2016, “we get about 40 per cent of the record above 2015 is due to El Nino, and 60 per cent is due to other factors”, Schmidt said.”

When I eyeball the graphs presented by Christy and Spencer it looks to me as though the fractions are the other way round i.e. 40% is due to other factors and 60% is due to El Niño. Seems to be equally true of both 1998 and 2015.

“Other factors” means, I presume, those factors which have caused the rise in temperature since the Little Ice Age.

Gary Kerkin
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Gary Kerkin

I have been watching this thread throughout the day but because I’ve been trotting backwards and forwards from Hutt Hospital experiencing the modern technological miracle of a camera capsule which has been peering at the inside of my gut, it is only now that I’ve had a chance to comment. A couple of points seem very clear to me. One is that associated with trying to compare reality with simulations and, in particular the Schmidt criticisms of the comparisons of Christy and Spencer. I commented on this in the previous post, highlighting the carping nature of the criticisms. These have been reinforced by the comments of both Richards today. As has been pointed out, even if the parameters are manipulated as described by Schmidt, we are still left with the indisputable conclusion that the output of the models do not match reality. This has also been commented on by Tisdale, as pointed out by Richard C. Despite what RC sees as deficiencies in Tisdale’s number crunching, the difference is clear. The other point relates to semantics. Andy comments that there is a difference between “projection” and “prediction”. If you Google the terms together… Read more »

Richard C (NZ)
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Richard C (NZ)

Gary >“Other factors” means, I presume, those factors which have caused the rise in temperature since the Little Ice Age. Yes those, of which Schmidt is wedded to AGW, but I think he’s alluding to other phenomena too which are the greater influence in this case I think and Schmidt seems to think too. When Gareth Renowden posted his February 2016 “wakeup call” post, Andy S and I both looked at the latitudinal breakdown in the Northern Hemisphere and said there’s some research needed to be done because the spike was minimal to non-existent around the NH tropics but from the NH extratropics to the NH polar latitudes the spike just got greater and greater. That’s this graph: GISTEMP LOTI February 2016 mean anomaly by latitude http://l2.yimg.com/bt/api/res/1.2/ABpZjd4AnHFp.4g2goHRfg–/YXBwaWQ9eW5ld3NfbGVnbztxPTg1/http://media.zenfs.com/en-US/homerun/mashable_science_572/bb88a1a459ed8b467290bac3540e39dd Sometimes that URL gives a browser error but I’ve just checked and got the graph up so shouldn’t be a problem (try ‘Open in another tab’). I’m sure you will agree that the graph is extraordinary. There must be much more than just an El Nino effect. I’m guessing something like AMO or Arctic Oscillation (AO a.k.a. Northern Hemisphere annular mode). But I really don’t know… Read more »

Gary Kerkin
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Gary Kerkin

Richard C, yes it does look quite extraordinary. I assume there is a strong seasonal component, i.e. the same plot for, say, July, would be something like a mirror image? Did you and Andy look at all months, or just February?

My comment about relative attribution was based merely on eyeballing the temperature graph and looking at the size of the spike compared to where some sort of average would pass beneath it. I have to say that I try to keep it very simple. So much of the information is buried in what I can only refer to as noise that I find it hard to believe than anything useful can be extracted from the data. Even using the most sensitive type of filtering (Kalman, say) I would have difficulty in believing anything that came out of it. GIGO?

Richard C (NZ)
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Richard C (NZ)

[IPCC] >“When a projection is branded ‘most likely’ it becomes a forecast or prediction”

“Branded”?

This is the ultimate in confirmation bias by whoever does the branding. If the forecast scenario is a “description of the future and the pathway leading to it” then it is merely speculation whatever “branding” is assigned to it.

The forecast only becomes ‘most likely’ when it tracks reality i.e. regular checks like those of Christy and Schmidt are needed to see how the forecast is tracking. When a forecast doesn’t track reality it is useless, not fit for purpose, a reject in quality control terms. This is the scientific equivalent of industrial/commercial key performance indicators (KPIs) or budget variances.

The only purpose 95% of the models at mid troposphere (97% at surface) have now is to demonstrate that the assumptions they are based on are false.

We should challenge the MfE, NIWA, and Minister for Climate Change Paula Bennett to post the IPCC’s forecasts graphed against real world atmospheric temperature (also sea levels) and updated as new data comes in. All MfE and NIWA do is state forecasts, there is never any governmental check of those forecasts against reality.

Gary Kerkin
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Gary Kerkin

Richard C >”We should challenge the MfE, NIWA, and Minister for Climate Change Paula Bennett to post the IPCC’s forecasts graphed against real world atmospheric temperature (also sea levels) and updated as new data comes in”

They might do it, but I doubt it. I rather feel they would want to restrict themselves to NZ only at best. At worst they would just ignore it. The PCE did but only succeeded in opening herself up to the criticism that the IPCC prognostications on sea level most certainly do not apply to NZ.

The government can quite rightly claim that it is not within its purview to “check” the correctness or otherwise of agency forecasts. The forecasts are published regularly and anyone with the desire to find out for themselves can compare reality with forecast. I suppose a comparison of forecast with reality could be included in the kpi’s of an agency, the outcome of which could influence future funding. But that is another can of worms!

Richard C (NZ)
Guest
Richard C (NZ)

Gary >”Did you and Andy look at all months, or just February?” No unfortunately. I picked up that graph from a comment thread somewhere. I don’t where to access the original graphs. I know there are similar graphs of each month because I saw another one recently of May I think it was but I didn’t save the link. I wish I knew who produces them. It’s not GISS I don’t think. I suspect it’s someone at Columbia University because the GISTEMP Graphs page links to Columbia: Columbia: Global Temperature — More Figures http://www.columbia.edu/~mhs119/Temperature/T_moreFigs/ About half way down there’s this latitudinal breakdown: Regional Changes – Zonal Means Zonal mean, (a) 60-month and (b-d) 12-month running mean temperature changes in five zones: Arctic (90.0 – 64.2°N), N. Mid-Latitudes (64.2 – 23.6°N), Tropical (23.6°S), S. Mid-Latitudes (23.6 – 64.2°S), and Antarctic (64.2 – 90.0°S). (Data through June 2016 used. Updated on 2016/07/19, now with GHCN version 3.3.0 & ERSST v4) http://www.columbia.edu/~mhs119/Temperature/T_moreFigs/ZonalT.gif Perfectly clear in (a) that the Arctic skews the entire global mean. Perfectly clear in (b) that the Antarctic is going in the opposite direction to the Arctic. Perfectly clear in (c) that the… Read more »

Gary Kerkin
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Gary Kerkin

Richard C>”In other words, the global mean is meaningless.”

Yes and/or no, Richard.

My guess is that the skew on those graphs is, as I implied earlier, a seasonal factor and, as I stated, July should almost be a mirror image of February. That implies that that seasonality should be removed and the simplest way of doing that is to average over a year. The shape of the graph if all values were averaged over 12 months would show the underlying skewness applying to either pole.

There are some (Vincent Gray, for example) that argue that a global average is meaningless. My view is that a number of some sort has to be generated if any sort of comparison is to be made. But (and it is a big “but”) having generated an average which contains both geographic and time components, we need to be extremely circumspect about how we use it and what conclusions we may draw from it. Especially if variations in time sit in what is obviously noise!

Simon
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Simon

“The global mean is meaningless.” What do you mean? It is a useful metric.
The important thing is that reality is panning out just as the models predicted. The Arctic would warm the fastest, whereas the Antarctic is insulated by the circumpolar winds and ozone depletion. Note that the un-insulated Antarctic peninsula, is one of the fastest warmest parts of the world. We have always known that New Zealand, because of its isolation from large land-masses, would not warm as quickly as temperate continents.
With surface temperatures now matching closely with the models, the obfuscation has had to shift to the mid-troposphere, where there is still much to understand and measure. Natural variation may give the impression of a temporary hiatus, but the trend continues. Especially so now that the Pacific Decadal Oscillation has flipped over to a positive phase.

Richard C (NZ)
Guest
Richard C (NZ)

The Arctic is of course the Great White Warm Hope, but not going so well ………..

‘Global Warming Expedition Stopped In Its Tracks By Arctic Sea Ice’

The icy blockade comes just over a month after an Oxford climate scientist, Peter Wadhams, said the Arctic would be ‘completely ice-free’ by September of this year. While it obviously isn’t September yet, he did reference the fact that there would be very little ice to contend with this summer.

“Even if the ice doesn’t completely disappear, it is very likely that this will be a record low year,” Wadhams told The Independent in June.

Wahdams says he expects less than one million square kilometers by summers end, but the current amount of Arctic sea ice is 10.6 million square kilometers, according to data from the National Snow and Ice Data Center (NSIDC).

http://dailycaller.com/2016/07/20/global-warming-expedition-stopped-in-its-tracks-by-arctic-sea-ice/

# # #

They are not in the Arctic at this juncture, currently stuck in Murmansk.

Pictured is another ‘Ship of Fools’, the MV Akademik Shokalskiy stranded in ice in Antarctica, December 29, 2013.

Remember Chris Turney?

Richard C (NZ)
Guest
Richard C (NZ)

Simon >“The global mean is meaningless.” What do you mean? It is a useful metric. For what? The “global mean” doesn’t exist anywhere on earth. It is a totally meaningless metric. >”The important thing is that reality is panning out just as the models predicted.” What utter rubbish Simon. Just look at Schmidt’s graph, or any other of obs vs models graphs e.g. HadCRUT4 vs models (see below). The models are TOO WARM. >”Note that the un-insulated Antarctic peninsula, is one of the fastest warmest parts of the world” ‘After warming fast, part of Antarctica gets a chill – study’ http://www.stuff.co.nz/world/82321379/after-warming-fast-part-of-antarctica-gets-a-chill–study >”With surface temperatures now matching closely with the models” Simon, just repeating an untruth doesn’t make it true – and it makes you look ridiculous: “The essential English leadership secret does not depend on particular intelligence. Rather, it depends on a remarkably stupid thick-headedness. The English follow the principle that when one lies, it should be a big lie, and one should stick to it. They keep up their lies, even at the risk of looking ridiculous.” – Joseph Goebbels HadCRUT4 vs Models Clearly, surface temperatures are NOT “now matching closely with… Read more »

Richard C (NZ)
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Richard C (NZ)

Simon >”Natural variation may give the impression of a temporary hiatus, but the trend continues” By what trend technique does “the trend continue”? Extrinsic e.g. statistically inappropriate (i.e. not representative of the data) linear analysis? Or, Intrinsic e.g. Singular Spectral Analysis (SSA) or Empirical Mode Decomposition (EMD)? Extrinsic is an externally imposed technique. Intrinsic is the inherent data signal. A curve (e.g. polynomial) is an extrinsic technique as is linear regression but a curve represents the temperature data better by statistical criteria. But I actually agree with you Simon. Yes, the “the trend continues”, but trend of what? Upthread I’ve shown that it is necessary to subtract MDV from GMST before comparing to the model mean. ST = GMST – MDV The residual is the secular trend (ST – a curve) which looks nothing like the trajectory of the data. The trajectory of 21st century GMST data is flat but the secular trend certainly is NOT flat (see Macias et al below). Problem for MMCC theory is: A) The secular trend (ST) in GMST now has a negative inflexion i.e. increasing CO2 cannot be the driver. B) The CO2-forced model mean does NOT… Read more »

Richard C (NZ)
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Richard C (NZ)

[Macias et al] >”Since the start of the 21st century, the surface global mean temperature has not risen at the same rate as the top-of-atmosphere radiative energy input or greenhouse gas emissions, provoking scientific and social interest in determining the causes of this apparent discrepancy.”

By “top-of-atmosphere radiative energy input” they are referring to radiative forcing theory i.e. the theoretical effective anthropogenic radiative forcing (ERF) was 2.33 W.m-2 at the time of AR5 and increasing.

But neither the earth’s energy balance nor surface temperature is increasing as MMCC theory predicts as a result of a theoretical ERF of 2.33+ W.m-2:

0.6 W.m-2 trendless – earth’s energy balance AR5 Chapter 2
2.33+ W.m-2 trending – theoretical anthropogenic forcing AR5 Chapter 10 (CO2 1.9 W.m-2 @ 400ppm).

This is the critical discrepancy that falsifies the MMCC conjecture.

Richard C (NZ)
Guest
Richard C (NZ)

Gary >”That implies that that seasonality should be removed and the simplest way of doing that is to average over a year. The shape of the graph if all values were averaged over 12 months would show the underlying skewness applying to either pole.” Agreed. That is exactly what Columbia University did in the graphs I linked too in the comment you are replying to: Regional Changes – Zonal Means Zonal mean, (a) 60-month and (b-d) 12-month running mean temperature changes in five zones: Arctic (90.0 – 64.2°N), N. Mid-Latitudes (64.2 – 23.6°N), Tropical (23.6°S), S. Mid-Latitudes (23.6 – 64.2°S), and Antarctic (64.2 – 90.0°S). (Data through June 2016 used. Updated on 2016/07/19, now with GHCN version 3.3.0 & ERSST v4) http://www.columbia.edu/~mhs119/Temperature/T_moreFigs/ZonalT.gif After the seasonal adjustment you require there’s a massive Arctic skew to the global mean. And a Northern Hemisphere skew too. The global mean is irrelevant to the Southern Hemisphere excluding tropics (think Auckland, Sydney, Johannesburg, Buenos Aires) as demonstrated by GISTEMP below. GISTEMP: Annual Mean Temperature Change for Three Latitude Bands [Graph] http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.B.pdf Here’s the anomaly data: Year Glob NHem SHem 24N-90N 24S-24N 90S-24S 2000 42 51 33 71 27… Read more »

Richard C (NZ)
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Richard C (NZ)

Simon >”Natural variation may give the impression of a temporary hiatus, but the trend continues. Especially so now that the Pacific Decadal Oscillation has flipped over to a positive phase” Do you really know what you are talking about Simon? Pacific Decadal Oscillation (PDO) When SSTs are anomalously cool in the interior North Pacific and warm along the Pacific Coast, and when sea level pressures are below average over the North Pacific, the PDO has a positive value. http://www.ncdc.noaa.gov/teleconnections/pdo/ A positive PDO does not necessarily mean GMST warming and a positive phase of natural multidecadal variation (MDV). 2000 was max positive MDV. 2015 was MDV-neutral. From 2015 to 2030 MDV will be in negative phase (see Macias et al upthread). So to reproduce the GMST profile from 2015 to 2030 starting from ST, MDV must be subtracted from ST: ST – MDV = GMST From 2015 until ST peaks, GMST will remain flatish i.e. ST will be ABOVE the GMST profile. After ST peaks GMST will go into cooling phase unless the MMCC is proved correct (doubtful) because ST will be cooling and it has more long-term effect on GMST than the oscillatory… Read more »

Gary Kerkin
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Gary Kerkin

Richard C>”The global mean is irrelevant to the Southern Hemisphere excluding tropics (think Auckland, Sydney, Johannesburg, Buenos Aires) as demonstrated by GISTEMP below.”

Actually, a global mean is irrelevant to any particular point somewhere on the globe! Which is to the point I was making about being circumspect about how it is to be used. I commented that it may be useful to have some sort of number for comparison purposes, but I would hesitate to give it any importance as a “metric”, which Simon considers appropriate. When noise is around ±0.5ºC differences of, say, ±0.2ºC do not convey much in the way of meaning.

One of the obfuscation techniques commonly in use is to display the information as “anomalies”. Everyone would be well advised to plot the information in actual values of, say, ºC with the origin set at 0º. Just eyeballing the data will give even the most casual viewer some perspective. That perspective is even better appreciated when considering a typical diurnal variation.

Richard C (NZ)
Guest
Richard C (NZ)

Should be:

“So to reproduce the GMST profile from 2015 to [2045] starting from ST, MDV must be subtracted from ST: ST – MDV = GMST [2015 – 2045]”

The equations over the MDV cycle are:

2045 neutral
2030 < MDV max negative ST – MDV = GMST
2015 neutral
2000 < MDV max positive ST + MDV = GMST
1985 neutral
1970 < MDV max negative ST – MDV = GMST
1955 neutral
1940 < MDV max positive ST + MDV = GMST
1925 neutral
1910 < MDV max negative ST – MDV = GMST
1895 neutral

Richard C (NZ)
Guest
Richard C (NZ)

Schmidt clarifies:

“While the El Niño event in the tropical Pacific this winter gave a boost to global temperatures from October onwards, it is the underlying trend which is producing these record numbers,” Gavin Schmidt said.

https://www.theguardian.com/environment/2016/jul/20/june-2016-14th-consecutive-month-of-record-breaking-heat-says-us-agencies

He’s got a problem looming with that though, his own GISTEMP Monthly shows GMST is plummeting back to neutral.

GISTEMP: Global Monthly Mean Surface Temperature Change
http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.C.pdf

The June anomaly is unremarkable. After this a La Nina.

Simon
Guest
Simon

This post describes the models overshooting observed temperatures over a period of 15 years in the tropical mid-troposphere, i.e. 10 km above us. It is unclear whether this is natural variation, model inaccuracy, measurement error, or a combination of all three. 2016 will be interesting as I suspect that will be somewhere well within the models’ envelope. Also note Gavin’s point, which you ignored, that if the models were retrospectively initialised with now known realised forcing, the models’ projections would have been lower.

Richard C (NZ)
Guest
Richard C (NZ)

Gary

[You] >”Did you and Andy look at all months, or just February?”

[Me] >”No unfortunately. I picked up that graph from a comment thread somewhere. I don’t where to access the original graphs. I know there are similar graphs of each month because I saw another one recently of May I think it was but I didn’t save the link. I wish I knew who produces them. It’s not GISS I don’t think”

I remember now. You can generate your own from a GISS page but not from GISTEMP. June is set up to be generated here:

GISS Surface Temperature Analysis – Global Maps from GHCN v3 Data
http://data.giss.nasa.gov/gistemp/maps/

Just click ‘Make Map’ and scroll down to “Get the zonal means plot as PDF, PNG, or PostScript file”

PNG graphs

June 2016 Zonal Mean
http://data.giss.nasa.gov/tmp/gistemp/NMAPS/tmp_GHCN_GISS_ERSSTv4_1200km_Anom6_2016_2016_1951_1980_100__180_90_0__2_/amaps_zonal.png

February 2916 Zonal Mean
http://data.giss.nasa.gov/tmp/gistemp/NMAPS/tmp_GHCN_GISS_ERSSTv4_1200km_Anom2_2016_2016_1951_1980_100__180_90_0__2_/amaps_zonal.png

These graphs show the real GMST story by latitudinal zone.

Richard C (NZ)
Guest
Richard C (NZ)

Credit to where I got to that GISS zonal anomaly generator. A warmy blogger, Robert Scribbler, has been posting the graphs at his website: robertscribbler https://robertscribbler.com/

May 2016 Zonal Anomalies
https://robertscribbler.com/2016/06/13/may-marks-8th-consecutive-record-hot-month-in-nasas-global-temperature-measure/nasa-zonal-anomalies-may-2016/

June 2016 Zonal Anomalies
https://robertscribbler.com/2016/07/19/2016-global-heat-leaves-20th-century-temps-far-behind-june-another-hottest-month-on-record/june-zonal-anomalies/

Scribbler has this post:

‘Rapid Polar Warming Kicks ENSO Out of Climate Driver’s Seat, Sets off Big 2014-2016 Global Temperature Spike’
https://robertscribbler.com/2016/06/17/rapid-polar-warming-kicks-enso-out-of-the-climate-drivers-seat-sets-off-big-2014-2016-global-temperature-spike/

Read Arctic for”Polar”. I actually agree with this except now the “Rapid Arctic Warming” has dissipated. It turned into Rapid Arctic Cooling. Compare February Zonal Mean to June Zonal Mean side by side.

Richard C (NZ)
Guest
Richard C (NZ)

Simon <"This post describes the models overshooting observed temperatures over a period of 15 years in the tropical mid-troposphere, i.e. 10 km above us. It is unclear whether this is natural variation, model inaccuracy, measurement error, or a combination of all three." Wrong at surface too. You might read the IPCC Chapter 9 quote upthread Simon. Here's their reasoning: This difference between simulated and observed trends could be caused by some combination of (a) internal climate variability, (b) missing or incorrect radiative forcing and (c) model response error. >”2016 will be interesting as I suspect that will be somewhere well within the models’ envelope.” Good luck with that Simon. RSS is plummeting out of the envelope: RSS from 2005 http://woodfortrees.org/plot/rss/from:2005 >”Also note Gavin’s point, which you ignored, that if the models were retrospectively initialised with now known realised forcing, the models’ projections would have been lower.” Yes, EXAVTLY Simon. The IPCC agrees totally that the models are WRONG. They give 3 reasons as quoted above: (a) (b) and (c). They have neglected natural variation (a). Incorrect theoretical forcing (b) doesn’t seem to be the problem. That leaves model response error (c) in combination… Read more »

Richard C (NZ)
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Richard C (NZ)

Simon [You] >”Also note Gavin’s point, which you ignored, that if the models were retrospectively initialised with now known realised forcing, the models’ projections would have been lower.” [Me] >”Incorrect theoretical forcing (b) doesn’t seem to be the problem” Here’s what the IPCC has to say about (b) theoretical Radiative Forcing: (b) Radiative Forcing On decadal to interdecadal time scales and under continually increasing effective radiative forcing (ERF), the forced component of the GMST trend responds to the ERF trend relatively rapidly and almost linearly (medium confidence, e.g., Gregory and Forster, 2008; Held et al., 2010; Forster et al., 2013). The expected forced-response GMST trend is related to the ERF trend by a factor that has been estimated for the 1% per year CO2 increases in the CMIP5 ensemble as 2.0 [1.3 to 2.7] W m–2 °C–1 (90% uncertainty range; Forster et al., 2013). Hence, an ERF trend can be approximately converted to a forced-response GMST trend, permitting an assessment of how much of the change in the GMST trends shown in Box 9.2 Figure 1 is due to a change in ERF trend. The AR5 best-estimate ERF trend over 1998–2011 is 0.22… Read more »

Simon
Guest
Simon

June’s GISTemp measures are now out. Despite the drop in temperature, June 2016 is still by far the warmest June ever recorded.

Richard C (NZ)
Guest
Richard C (NZ)

Simon >”June’s GISTemp measures are now out. Despite the drop in temperature, June 2016 is still by far the warmest June ever recorded.” “By far”? That Hot Whopper graph is wrong. June 2016 is unremarkable. LOTI is only 0.02 warmer than June 1998: Monthly Mean Surface Temperature Anomaly (C) ——————————————– Year+Month Station Land+Ocean 2016.04 1.36 1.14 January …..[ Hot Whopper gets this right ] 2016.13 1.64 1.33 February …..[ Hot Whopper says about 1.24 – WRONG ] 2016.21 1.62 1.28 March …..[ Hot Whopper gets this about right ] 2016.29 1.36 1.09 April …..[ Hot Whopper says about 1.22 – WRONG ] 2016.38 1.18 0.93 May …..[ Hot Whopper says about 1.16 – WRONG ] 2016.46 0.94 0.79 June …..[ Hot Whopper says about 1.1 – WRONG ] 1998.46 1.03 0.77 June …..[ Hot Whopper says about 0.7 – WRONG ] http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.C.txt By station, June 2016 is cooler than June 1998 by 0.09. Here’s a tip Simon: Hot Whopper is not a credible source. If you want GISS graphs and data go to GISS or someone whot knows how to plot graphs correctly.

Gary Kerkin
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Gary Kerkin

IPCC>”This difference between simulated and observed trends could be caused by some combination of (a) internal climate variability, (b) missing or incorrect radiative forcing and (c) model response error.” (cited by Richard C)

This is fascinating. A semantic analysis might suggest:

(a)Internal climate variability: We haven’t been able to describe, or haven’t wished to include, all the physics.
(b)Missing or incorrect radiative forcing: We haven’t been able to correctly describe the AGW hypothesis.
(c)Model response error: We haven’t been able to force the assumptions and regression predictors and/or whatever to give us the answer we want.

Richard C (NZ)
Guest
Richard C (NZ)

Gary >”(b)Missing or incorrect radiative forcing: We haven’t been able to correctly describe the AGW hypothesis.” They looked at that but decided they’d got their forcings right. From IPCC Chapter 9 (b) Radiative Forcing quote upthread: [(b) Radiative Forcing] Although the forcing uncertainties are substantial, there are no apparent incorrect or missing global mean forcings in the CMIP5 models over the last 15 years that could explain the model–observations difference during the warming hiatus So that just leaves (a) and (c) by their reasoning. But (b) and (c) are BOTH within their theoretical radiative forcing paradigm i.e. the models are responding (c) correctly to forcings (b) that don’t exist if their theory is wrong. They haven’t considered that very real possibility. That their theory is wrong and the IPCC haven’t addressed the issue is laid out here: IPCC Ignores IPCC Climate Change Criteria – Incompetence or Coverup? https://dl.dropboxusercontent.com/u/52688456/IPCCIgnoresIPCCClimateChangeCriteria.pdf And when the internal climate variability signal (a) is added in to the model mean profile as per the MDV signal extracted by Macias et al (see upthread), it makes the model mean profile even worse. MDV was max positive at 2000 but is missing… Read more »

Richard C (NZ)
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Richard C (NZ)

Hot Whopper’s whopper: Hottest June on record – global surface temperature with year to date Sou| Wednesday, July 20, 2016 “According to GISS NASA, the average global surface temperature anomaly for June was 0.79 °C, which just pipped June 2015 (0.78 C) and June 1998 (0.77 °C).” http://blog.hotwhopper.com/2016/07/hottest-june-on-record-global-surface.html OK so far, these numbers correspond to the NASA GISS anomaly data page upthread a bit and are unremarkable in respect to June 2016 compared to June 2015 and June 1998. But then she goes on: “The average for the six months to the end of June is 1.09 °C, which is 0.28 °C higher than any previous January to June period.” This is the spin. She can’t crow about the June anomaly because it’s unremarkable compared to 2015 and 1998. NASA GISS resorts to the same spin for the same reasons: 2016 Climate Trends Continue to Break Records NASA GISS Posted July 19, 2016 Each of the first six months of 2016 set a record as the warmest respective month globally in the modern temperature record, which dates to 1880, according to scientists at NASA’s Goddard Institute for Space Studies (GISS) in New York.… Read more »

Richard C (NZ)
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Richard C (NZ)

GISS and Sou have different values for their 6 month average:

GISS – “The six-month period from January to June was also the planet’s warmest half-year on record, with an average temperature 1.3 degrees Celsius”

Sou – “The average for the six months to the end of June is 1.09 °C”

They are both correct but GISS zeal trumps Sou’s. GISS have averaged the Station data – NOT the LOTI data that Sou averaged:

GISS: Monthly Mean Surface Temperature Anomaly (C)
Year+Month Station Land+Ocean
2016.04 1.36 1.14 January
2016.13 1.64 1.33 February
2016.21 1.62 1.28 March
2016.29 1.36 1.09 April
2016.38 1.18 0.93 May
2016.46 0.94 0.79 June
2015.46 0.84 0.78 June
1998.46 1.03 0.77 June
http://data.giss.nasa.gov/gistemp/graphs_v3/Fig.C.txt

The lesson being: If you are going to resort to spin, you MUST choose the data that spins best.

Sou still has much to learn from GISS about spin apparently.

Richard C (NZ)
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Richard C (NZ)

If Sou is going to plot “the average of the year to that month” (and neglect to tell anyone in the graph title), then she would have to plot the average of January to June at March/April – not June.

The average of January – June occurs at March/April.

This is no different to the IPCC’s Assessment Report prediction baseline as quoted by NIWA, T&T, and whoever else. Their baseline is the average of 1980 to 1999 data nominally centred on 1990 – not 1999.

Scurrilous Sou.

Richard C (NZ)
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Richard C (NZ)

By June, Sou has a 6 month TRAILING average which she could then plot if she stipulated as such. But her graph is NOT of “trailing averages”: ‘How do I Calculate a Trailing Average?’ http://www.ehow.com/how_6910909_do-calculate-trailing-average_.html For January, the 6 month trailing average is 0.99 but Sou plots “year to date” which is the January anomaly (1.14). For February, Sou plots the average of January and February – NOT the 6 month trailing average. For March, Sou plots the average of January February and March – NOT the 6 month trailling average. And so on. Sou has 6 unrelated graph datapoints: 1 month trialling average (January) 2 month trailing average (February) 3 month trailing average (March) 4 month trailing average (April) 5 month trailing average (May) 6 month trailing average (June) What does ‘Trailing’ mean Trailing is the most recent time period, often used to describe the time that a particular set of data is referring to. Trailing is used to describe a past statistic, such as same-store sales, but can also be used to describe a technique, such as a trailing stop order. Most often you will hear the term “trailing 12 months,”… Read more »

Richard C (NZ)
Guest
Richard C (NZ)
Richard C (NZ)
Guest
Richard C (NZ)

Richard C (NZ) on July 21, 2016 at 10:20 pm said:

>”That just leaves (a) natural variation and (b) model response error. The IPCC say their radiative forcing theory (a) is OK.”

Got it horribly wrong to. Should be:

“That just leaves (a) natural variation and [(c)] model response error. The IPCC say their radiative forcing theory [(b)] is OK.”

Richard C (NZ)
Guest
Richard C (NZ)

What Schmidt actually said about incorrect forcing in regard to TMT: So what? In work we did on the surface temperatures in CMIP5 and the real world [hotlink – see below], it became apparent that the forcings used in the models, particularly the solar and volcanic trends after 2000, imparted a warm bias in the models (up to 0.1ºC or so in the ensemble by 2012), which combined with the specific sequence of ENSO variability, explained most of the model-obs discrepancy in GMST. This result is not simply transferable to the TMT record (since the forcings and ENSO have different fingerprints in TMT than at the surface), but similar results will qualitatively hold. http://www.realclimate.org/index.php/archives/2016/05/comparing-models-to-the-satellite-datasets/ Qualitatively but why not quantitatively? Reason: “This result is not simply transferable to the TMT record” i.e. it does not necessarily follow – a non sequitur. The hotlink leads to this article: ‘Reconciling warming trends’ Gavin A. Schmidt, Drew T. Shindell and Kostas Tsigaridis http://www.blc.arizona.edu/courses/schaffer/182h/Climate/Reconciling%20Warming%20Trends.pdf Climate models projected stronger warming over the past 15 years than has been seen in observations. Conspiring factors of errors in volcanic and solar inputs, representations of aerosols, and El Niño evolution, may explain… Read more »

Richard C (NZ)
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Richard C (NZ)

>”The simulation is missing the MDV signal present in the observations. Conversely, the secular trend (ST) in the observations, which has MDV removed, is nothing like the model mean except that is also a smooth curve but it is well below the model mean over the 21st century and coincides with MDV-neutral ENSO-neutral observations at 2015. At this date, the “adjusted” model mean is still well above the observations ST.” Best seen in Macias et al Figure 1: Figure 1. SSA reconstructed signals from HadCRUT4 global surface temperature anomalies. http://journals.plos.org/plosone/article/figure/image?download&size=large&id=info:doi/10.1371/journal.pone.0107222.g001 The secular trend (ST, red line) is directly comparable to the model mean (not shown). At 2000 the ST (red line) is well below reconstructed GMST (thick black line). The model mean is above the GMST reconstruction (thick black line). Therefore the models are performing rather more badly than Schmidt, Shindell, and Tsigaridis think and even worse than most sceptics think. Also easy to see that the ST (red line) is the MDV-neutral “spline” about which the GMST reconstruction (thick black line) oscillates. MDV-neutral is where the GMST reconstruction (thick black line) crosses the ST (red line). 2045 neutral 2030 < MDV max… Read more »

Richard C (NZ)
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Richard C (NZ)

>”Jeff Patterson has a lot of the MDV issue figured out in his ‘TSI-Driven (solar) Climate Model’ linked in previous comment.”
>”How long before Schmidt, Shindell, Tsigaridis, and all the other IPCC climate modelers figure it out?”

The IPCC are particularly clueless. Their “natural forcings only” simulations are laughable. Compare Jeff Patterson’s natural only model to the IPCC’s natural only models from Chapter 10 Detection and Attribution:

Patterson Natural Only: Modeled vs Observed
comment image

IPCC Natural Only: Modeled vs Observed (b)
http://www.ipcc.ch/report/graphics/images/Assessment%20Reports/AR5%20-%20WG1/Chapter%2010/Fig10-01.jpg

The IPCC then go on to conclude anthropogenic attribution from their hopelessly inadequate effort.

Patterson on the other hand, doesn’t need to invoke GHG forcing as as input parameterization. On the contrary, he models CO2 as an OUTPUT after getting temperature right.

Richard C (NZ)
Guest
Richard C (NZ)

Patterson: [Re Figure 7, HadCRUT4 with wavelet denoising below] “The resulting denoised temperature profile is nearly identical to that derived by other means (Singular Spectrum Analysis [hotlink 1], Harmonic Decomposition [hotlink 2], Principal Component Analysis, Loess Filtering [hotlink 3], Windowed Regression [hotlink 4] etc.)” Figure 7 ?w=774&h=503 A TSI-Driven (solar) Climate Model https://wattsupwiththat.com/2016/02/08/a-tsi-driven-solar-climate-model/ [1] Singular Spectrum Analysis Detecting the AGW Needle in the SST Haystack – Patterson Conclusion As Monk would say, “Here’s what happened”. During the global warming scare of the 1980’s and 1990’s, the quasi-periodic modes comprising the natural temperature variation were both in their phase of maximum slope (See figure 5). This naturally occurring phenomenon was mistaken for a rapid increase in the persistent warming trend and attributed to the greenhouse gas effect. When these modes reached their peaks approximately 10 years ago, their slopes abated, resulting in the so-called “pause” we are currently enjoying. This analysis shows that the real AGW effect is benign and much more likely to be less than 1 °C/century than the 3+ °C/century given as the IPCC’s best guess for the business-as-usual scenario. https://wattsupwiththat.com/2013/09/26/detecting-the-agw-needle-in-the-sst-haystack/ [2] Harmonic Decomposition Digital Signal Processing analysis of global temperature… Read more »

Richard C (NZ)
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Richard C (NZ)

Schmidt, Shindell, and Tsigaridis Figure 1:

“Adjusting for the phase of ENSO by regressing the observed temperature against the ENSO index adds interannual variability to the CMIP5 ensemble mean (dashed blue)”

“Interannual variability” ? Whoop-de-doo.

They adjust for a bit of noise but neglect multidecadal variabilty (MDV) with a cycle of around 60 years.

They’re so fixated on noise that they can’t see the signals.

They can’t see the wood for all the trees in the way.

Gary Kerkin
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Gary Kerkin

Sorry Richard C that I haven’t been back regarding what you’ve posted since my last comment. Some medical problems got in the way yesterday which put paid to any activity!

My comment with a “semantic analysis” was meant to be sarcastic, and much of what you found and posted reinforces my comments. Rather curiously, I think. When a document starts to over-explain why there are deficiencies in models which purport to explain an hypothesis my antennae start to quiver. Others have described it as a bullshit metre. I wouldn’t, of course—I prefer a more refined statement. Much of it, and much of the information you followed it with have all the hallmarks of self-justification and desperation.

This discussion started a while back with the “Almost 100% of scientists …” statement from the Renwick and Naish road show and which I categorized as a fundamental need to have their stance vindicated by having others agree with them. This is, I believe, the rationale for trying to establish a “consensus”.

Gary Kerkin
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Gary Kerkin

Richard C, the information you have posted on modelling is informative and interesting and the conclusions various authors have drawn offer an insight into what is, and what is not, possible. In the far distant past (about 30 years ago) I had great success with linear modelling. That is where something can be described by linear relationships such as A + Bx1 + Cx2 + … for example I modeled the control of an alumina digester where two parallel trains of 12 shell-and-tube heat exchangers heated incoming caustic liquor flowed into three digesters into which bauxite slurry was injected. The stream out of the final digester passed through 12 flash tanks which supplied steam to the heat exchangers heating the incoming liquor. Each heat exchanger had 2 liquor temperatures and a pressure, a steam temperature and pressure totaling 6x12x2 or 144 variables, incoming liquor flow rate, 3 digester pressures, 3 digester temperatures, and the flow rate out of the final digester, 12 flow rates out of each of the flash tanks, and the 12 steam flow rates out of each of the flash tanks. That’s a total of 174 variables, most of which… Read more »

Gary Kerkin
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Gary Kerkin

Richard C > “They’re so fixated on noise that they can’t see the signals.”

Isn’t that the point? If the signal is buried in noise it is extremely difficult to extract it. As I understand signal processing, information (such as signals from deep space explorers) can be extracted from the noise because the useful information is associated with some sort of carrier signature which can be recognised by the processing system. If, however, the carrier signature is not known how can it be recognized and how can the information be extracted. I realise that this is the basis for a huge amount of research effort in signal processing and digital filtering but none-the-less I maintain that if you don’t know what you are looking for how will you recognize it when you see it? Wasn’t this part of the problem with SETI?

Richard C (NZ)
Guest
Richard C (NZ)

Gary >”f the signal is buried in noise it is extremely difficult to extract it” Except the 2 major signals in GMST (which is overwhelmed by the Northern Hemisphere) are neither buried nor difficult to extract. On the contrary, they are staring everyone in the face and reasonably easy to extract with EMD (I’ve done this with HadSST3) and SSA (haven’t got to grips with this unfortunately). The 2 major signals in GMST are the secular trend (ST) and multidecadal variation/oscillation (MDV/MDO) which has a period of about 60 years (the “60 year Climate Cycle”). Once these signals are extracted, they can then be added to reconstruct noiseless GMST. The best SSA example of this that I know of is Macias et al linked upthread. Here’s their paper, their Figure 1, and my commentary again: ‘Application of the Singular Spectrum Analysis Technique to Study the Recent Hiatus on the Global Surface Temperature Record’ Diego Macias, Adolf Stips, Elisa Garcia-Gorriz (2014) Full paper: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0107222 Figure 1. SSA reconstructed signals from HadCRUT4 global surface temperature anomalies. http://journals.plos.org/plosone/article/figure/image?download&size=large&id=info:doi/10.1371/journal.pone.0107222.g001 The secular trend (ST, red line) is directly comparable to the model mean (not shown). At 2000 the… Read more »

Richard C (NZ)
Guest
Richard C (NZ)

>”BTW #2. I had gut inflammation for years, lost a lot of weight and couldn’t put it on because I couldn’t digest food properly. Exacerbated by night shift work.”

I’ve been wondering lately whether it was started by glyphosate (think Roundup), possibly in bread. This is the big controversy in Europe and North America, wheat growers in USA spray Roundup on the crop just before harvest as a desiccant. NZ gets wheat from Australia but I don’t know if there is the same practice in Australia or not.

Not sure where the issue has got to but here’s an article from April 15, 2014 for example:

‘Gut-Wrenching New Studies Reveal the Insidious Effects of Glyphosate’

Glyphosate, the active ingredient in Monsanto’s Roundup herbicide, is possibly “the most important factor in the development of multiple chronic diseases and conditions that have become prevalent in Westernized societies”

http://articles.mercola.com/sites/articles/archive/2014/04/15/glyphosate-health-effects.aspx

Gary Kerkin
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Gary Kerkin

Richard C thanks for your concern and advice. Yesterday the pool at Porirua had to be closed because of 5 people infected with cryptosporidiosis. It appears to be going round the Wellington region and the symptoms exactly match what I have encountered over the last 10 days: stomach cramps & etc! The symptoms can last for up to 2 weeks so hopefully that is about over for me.

Richard C (NZ)
Guest
Richard C (NZ)

‘U.N. experts find weed killer glyphosate unlikely to cause cancer’ – May 16, 2016

The pesticide glyphosate, sold by Monsanto in its Roundup weed killer product and widely used in agriculture and by gardeners, is unlikely to cause cancer in people, according to a new safety review by United Nations health, agriculture and food experts.

In a statement likely to intensify a row over its potential health impact, experts from the U.N.’s Food and Agriculture Organization (FAO) and World Health Organization (WHO) said glyphosate is “unlikely to pose a carcinogenic risk to humans” exposed to it through food. It is mostly used on crops.

Having reviewed the scientific evidence, the joint WHO/FAO committee also said glyphosate is unlikely to be genotoxic in humans. In other words, it is not likely to have a destructive effect on cells’ genetic material.

http://www.reuters.com/article/us-health-who-glyphosate-idUSKCN0Y71HR

# # #

“Unlikely” is not very reassuring.

I think the danger, if any, is more insidious than as a direct cause of cancer.

Richard C (NZ)
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Richard C (NZ)

Gary >”cryptosporidiosis. …….. symptoms ………..stomach cramps & etc!…….2 weeks”

Inflammatory bowel disease much the same but months and years not weeks. I had stomach cramps for 12 hours straight one day, everything cramped up and I couldn’t straighten up. I wouldn’t wish it on anyone.

I thought it was just night shifts but when Psa struck kiwifruit certain people in the industry had to have medical tests. That’s how I found out my condition eventually but I had it before night shifts when I thought about it. People were finding out conditions they never knew about from the Psa medical tests. I talked to a guy who was found to have prostate cancer he didn’t know about. He was in hospital the week after the test result. Saved his life.

Gary Kerkin
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Gary Kerkin

Richard C we’re kinda straying away from the topic. There is a strong message coming through though. If you have a problem, don’t delay doing something about it. I lost a good friend a couple of weeks ago with some form of stomach cancer. He ignored it for years until the pain became too much. By then it was too late to do anything. Peter Williams, the QC and activist ignored prostate cancer until it was too late: probably cost him 10 years of life. My prostate was removed a couple of years ago after 10 years of close monitoring. PSA markers are now undetectable. My recent condition is exacerbated by a bout of anæmia which landed me in hospital for a week or so. Still don’t know what the problem was but I’m awaiting the results of a camera capsule examination. The wonders of modern technology!

Gary Kerkin
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Gary Kerkin

Richard C, thanks for the reference on singular spectrum analysis. I’m working through it and trying to reconcile it with some things I know. What I don’t know is how they allocated certain meanings to the Eigenvalues. And I am still puzzling over their use of the term “secular”—although it may be appropriate in that proponents of AGW seem to have a “belief” or “faith” in the hypothesis that physics doesn’t seem to yield! I have found that UCLA has a program (an App) which will calculate the Eigenvalues and is implementable on a UNIX based system (various flavours of Linux, or Mac OS X version 10) which I am looking at with a view to installing it on my MacBook Pro. If I can successfully implement it I might try running the NIWA data on it (Raw and adjusted 7SS series) to see what we can get out of it. Might be worth a post, Richard T? For what it is worth, although I have only just done some preliminary reading, it has a familiarity about it. 40 years ago I developed a method for endeavouring to analyse very noisy pressure measurements… Read more »

Richard C (NZ)
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Richard C (NZ)

Gary I was hoping to pique your interest in SSA because you have the background and skills to go further with SSA than I can. I’ve looked at some of those packages including coding in R but have not gone any further. I saw that UCLA App listed too. >And I am still puzzling over their use of the term “secular” Just the more appropriate term for the inherent trend after all the noise and fluctuations are eliminated. In EMD it is the residual after all of the intermediate frequencies have ceased to be extracted e.g. rough example, IMFs 1, 2, 3 just noise, IMF 5 a minor oscillation, IMF 7 a major oscillation, last a residual. When new data is added to the series, eventually the residual becomes the last IMF (IMF 8 in example) and a new residual emerges. In other words, you cannot really “project” an EMD residual because after a period of time elapses you will have only projected an IMF. I think there’s a similar situation with SSA i.e. you may have subjectively selected a spectral “window” in which you think the secular trend lies but new data… Read more »

Richard C (NZ)
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Richard C (NZ)

Two more interesting comparisons:

HadSST3 NH vs HadSST3 SH
http://woodfortrees.org/plot/hadsst3nh/mean:60/plot/hadsst3sh/mean:60

CRUTEM4 NH vs CRUTEM4 SH
http://woodfortrees.org/plot/crutem4vnh/mean:60/plot/crutem4vsh/mean:60

Ocean is similar but Land is radically different in each hemisphere.

I don’t how anyone can even consider “trying to tease out the signal of human-caused climate change” from all of this (as Micheal Mann puts it).

Gary Kerkin
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Gary Kerkin

Richard C > “I was hoping to pique your interest in SSA ”

You’ll keep!

I have downloaded the package from UCLA: requires a Unix command to start it. I’ve also downloaded about 150 pages of notes to read. As I said, don’t hold your breath, this is going to take some time.

As to what I look at I think I will look at the 7SS series first.

Gary Kerkin
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Gary Kerkin

Richard C, just to let you know what you have let me in for!

“SSA allows one to unravel the information embedded in the delay-coordinate phase space by decomposing the sequence of augmented vectors thus obtained into elementary patterns of behaviour. It does so by providing data-adaptive filters that help separate the time series into components that are statistically independent, at zero lag, in the augmented vector space of interest. These components can be classified essentially into trends, oscillatory patterns, and noise. As we shall see, it is an important feature of SSA that the trends need not be linear and that the oscillations can be amplitude and phase modulated.”

http://research.atmos.ucla.edu/tcd//PREPRINTS/2000RG.pdf

Whew!

Richard C (NZ)
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Richard C (NZ)

Gary >”Richard C, just to let you know what you have let me in for!” Heh. How many PhDs’ were involved in producing that first sentence? Nuts. Now I will have to get some familiarity with that paper I suppose. I see M-SSA in there beginning page 27: “In M-SSA, on the other hand, on the basis of the single channel experience reviewed in sections 2 and 3.3, one usually chooses L [smaller than or equal to] M (see also Appendix A). Often M-SSA is applied to a few leading PCA components of the spatial data, with M chosen large enough to extract detailed temporal and spectral information from the multivariate time series.” More on M-SSA below because in the author list I see Michael E. Mann: ADVANCED SPECTRAL METHODS FOR CLIMATIC TIME SERIES M. Ghil, M. R. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, M. E. Mann, A. W. Robertson, A. Saunders, Y. Tian, F. Varadi, and P. Yiou (2001) Ok, so Mann's been on to this since before 2001 so why has he not been applying SSA appropriately since then in climate series analysis where it matters? Wyatt and Curry… Read more »

Richard C (NZ)
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Richard C (NZ)

Gary. Following on from the comment above involving Mann and how he will do anything to get the “right” answer. I’m reproducing a comment from a post earlier this year: ********************************************************************* Richard C (NZ) on March 20, 2016 at 6:06 pm said: Steve Sherwood and Stefan Rahmstorf at Hot Topic: “In the longer run the global warming trend agrees very well [hotlink] with longstanding predictions” http://hot-topic.co.nz/februarys-global-temperature-spike-is-a-wake-up-call/#more-14425 This is dead wrong. The hotlink is to this Rahmstorf Tweet: https://twitter.com/rahmstorf/status/698380997222510592 Which contains this graph: Graph looks dodgy. Reason becomes clear by following the link in the Tweet to this paper: ‘The Likelihood of Recent Record Warmth’ Michael E. Mann, Stefan Rahmstorf, Byron A. Steinman, Martin Tingley & Sonya K. Miller (2015) http://www.nature.com/articles/srep19831 Yes you are looking at GISTEMP. No you are not looking at CMIP5 model output. You are looking at “adjusted” model output i.e. a residual. The giveaway is this: “It is critical to take into account these contributions in estimating the likelihood of record temperature values. One body of past work5,6,7 has employed model-based fingerprint detection methods to study temperature extremes in a generic sense, though without any focus on the types of… Read more »

Richard C (NZ)
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Richard C (NZ)

Note that Rahmstorf Tweeting his bogus graph is not much different to Simon upthread posting the shonky Hot Whopper graph.

It’s the Warmy way apparently.

Richard C (NZ)
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Richard C (NZ)

Latest reason the models are wrong (the models are right, the observations are wrong): ‘Historical Records Miss a Fifth of Global Warming: NASA’ – Jet Propulsion Laboratory July 21, 2016 A new NASA-led study [Richardson et al (2016)] finds that almost one-fifth of the global warming that has occurred in the past 150 years has been missed by historical records due to quirks in how global temperatures were recorded. The study explains why projections of future climate based solely on historical records estimate lower rates of warming than predictions from climate models. The study applied the quirks in the historical records to climate model output and then performed the same calculations on both the models and the observations to make the first true apples-to-apples comparison of warming rates. With this modification, the models and observations largely agree on expected near-term global warming. The results were published in the journal Nature Climate Change. Mark Richardson of NASA’s Jet Propulsion Laboratory, Pasadena, California, is the lead author. More>>>> http://www.jpl.nasa.gov/news/news.php?feature=6576 # # # What “largely agree” means remains to be seen (paywalled). The “Fifth of Global Warming” the observations “miss” (apparently), is Arctic warming only the… Read more »

Richard C (NZ)
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Richard C (NZ)

Climategate email:

“What if climate change appears to be just mainly a multidecadal natural fluctuation? They’ll kill us probably “

— Tommy Willis, Swansea University

Gary Kerkin
Guest
Gary Kerkin

Mann has figured in several references in the papers I have been reading. But I note that he does not appear to be a lead author in many of them. Which suggests to me that he has been lending his imprimatur to the papers without necessarily contributing much in a technical way. That is not to say that he isn’t well versed in the methods, just that he has not chosen to use them. That’s not an unusual situation. Anyway, I would have though that his tree ring analyses would not have lent themselves to this sort of analysis, and it wouldn’t be appropriate to attempt it on the time series he generated because that would have been subjected to assumed statistical processes. Richard C > “The assumption, by circular reasoning, is this : The warming was there all along (we now “know” from our models – all the extra 19% of it) but it is only mainly in the Arctic, and we have to “tweak” the observations a bit too. If we neglect the Arctic and the Arctic warming in the models and “tweak” the observations, the models and observations will reconcile.”… Read more »

Richard C (NZ)
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Richard C (NZ)

Gary >”I would have though that his tree ring analyses would not have lent themselves to this sort of analysis” His recent opposition to Wyatt and Curry and subsequently Kravtsov, Wyatt, Curry, and Tsonis isn’t about tree rings though. His 2014 paper in response to Wyatt and curry is meteorological, climate, and oceanographic data as I understand without checking (but no tree rings I’m sure), and the signals they present. SSA more than lends itself to this sort of analysis as his opposition authors demonstrate (as do Macias et al). But Mann didn’t take that route because, I’m inclined to think, he would have to throw out his radiative forcing approach if he did. He can’t give that approach up because then he can’t make an anthro attribution because that’s the paradigm that gives him the opportunity – if he can work it in his favour. SSA (and EMD) extracts so many natural variation signals that there is no room left for an anthro signal, he can’t “tease” it out as he puts it. And then following that, the Mann et al (2015) models vs observations of temperature paper is exactly the application… Read more »

Andy
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Andy

O/T
Dr Jarrod Gilbert: Why climate denial should be a criminal offence

http://www.nzherald.co.nz/nz/news/article.cfm?c_id=1&objectid=11681154
Dr Jarrod Gilbert is a sociologist at the University of Canterbury and the lead researcher at Independent Research Solutions. He is an award-winning writer who specialises in research with practical applications.

There is no greater crime being perpetuated on future generations than that committed by those who deny climate change. The scientific consensus is so overwhelming that to argue against it is to perpetuate a dangerous fraud. Denial has become a yardstick by which intelligence can be tested. The term climate sceptic is now interchangeable with the term mindless fool.

Perhaps this “sociologist” could suggest a suitable punishment for the criminal offense of denying the climate.

Execution by firing squad? 25 years in the clinker? Hanging? Electric chair? Lethal injection?

All offers are open.

Andy
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Andy

Interesting that this gent has written a book on gangs in NZ
http://www.jarrodgilbert.com/

He’ll be well familiar with the gang at the University of Victoria then

Gary Kerkin
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Gary Kerkin

Andy, this is a topic Richard T should explore in another post, and I have no doubt he probably will. He should be told that the RICO bandwagon in the US looks like it is losing its wheels. “Rats deserting sin king ships” comes to mind!

Gary Kerkin
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Gary Kerkin

Richard C > “But it might be as you imply Gary, that Mann is not a technical exponent of SSA so he can’t use it. But he used principal components analysis (PCA) in his tree ring study so surely he could make the step to SSA?”

He is one of the authors of the seminal paper for the UCLA-developed paper I cited above http://research.atmos.ucla.edu/tcd//PREPRINTS/2000RG.pdf.

Richard C (NZ)
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Richard C (NZ)

Gary

>”He [Mann] is one of the authors of the seminal paper for the UCLA-developed paper I cited above”

Yes I saw that immediately and noted it upthread here:

Richard C (NZ) on July 24, 2016 at 11:29 pm said:
https://www.climateconversation.org.nz/2016/07/gavin-schmidt-confirms-model-excursions/comment-page-1/#comment-1501514

That was what got me going on the Mann vs Wyatt & Curry/Kravtsov et al saga.

Richard C (NZ)
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Richard C (NZ)

Re Dr Jarrod Gilbert: Why climate denial should be a criminal offence

Given Gilbert’s deference to the 97% consensus, this topic would have been better in the Naish and Renwick thread – but good to know Andy. I’ll link and reply to the Gilbert article in that thread.

Richard C (NZ)
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Richard C (NZ)

Willis Eschenbach: Precipitable Water Figure 4. Decomposition of the total precipitable water data (upper panel) into the seasonal (middle panel) and residual (bottom panel) components. ?w=720&h=674 Some things of interest. First, in the bottom panel you can see the effect on TPW of the El Nino episodes in 1997/98, 2010/11, and 2015/16. You can also see that we haven’t quite recovered from the most recent episode. Next, there is a clear trend in the TPW data. The total change over the period is ~ 1.5 kg/m^2, centered around the long-term mean of 28.7 kg/m^2. And utilizing the relationship between water content and atmospheric absorption derived above, this indicates an increase in downwelling radiation of 3.3 W/m2 over the period. Now, please note that this 3.3 W/m2 increased forcing from the long-term increase in water vapor since 1988 is in addition to the IPCC-claimed 2.3 W/m2 increase since 1750 in all other forcings (see Figure SPM-5, IPCC AR5 SPM). The IPCC counts as forcings the long-term changes in the following: CO2, CH4, Halocarbons, N2O, CO, NMVOC, NOx, mineral dust, SO2, NH3, organic carbon, black carbon, land use, and changes in solar irradiance … but… Read more »

Richard C (NZ)
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Richard C (NZ)

Two papers that together falsify the Man-Made Climate Change Theory. 1) ‘An observationally based energy balance for the Earth since 1950’ D. M. Murphy, S. Solomon, R. W. Portmann, K. H. Rosenlof, P. M. Forster, T. Wong (2009) http://onlinelibrary.wiley.com/doi/10.1029/2009JD012105/full There is obviously a massive discrepancy between theoretical forcing and actual earth heating. Murphy et al describe the discrepancy as “striking”: [38] A striking result of the Earth energy budget analysis presented here [Figure 6 below] is the small fraction of greenhouse gas forcing that has gone into heating the Earth. Since 1950, only about 10 ± 7% of the forcing by greenhouse gases and solar radiation has gone into heating the Earth, primarily the oceans. Murphy et al (2009) Figure 6 http://onlinelibrary.wiley.com/store/10.1029/2009JD012105/asset/image_n/jgrd15636-fig-0006.png?v=1&s=1d48ee59aed4b059a12eea9575028e88a7b134ce Total cumulative theoretical forcing is 1700 x 10^21 Joules 1950 – 2004 of which 10% is 170 x 10^21 Joules. In Figure 6, solar forcing is already 100 x 10^21 Joules leaving a residual of 70 x 10^21 Joules. Nordell and Gervet (2009) below estimate only 27.3 x 10^21 Joules (say 30 at 2004) actual energy accumulation total over the entire extended period 1880–2000 (say 2004): 2) ‘Global energy accumulation and… Read more »

Richard C (NZ)
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Richard C (NZ)

From my Richardson et al (2016) comment

>”Still problematic because the satellites have the coverage that surface measurements don’t including much of the Arctic region e.g. the Schmidt and Christy graphs in the post.”

Not quite right here. Only the Christy graph is “Global”. Schmidt’s is only Tropics.

Richard C (NZ)
Guest
Richard C (NZ)

Is Climate Too Complex to Model or Predict? Scientists say no By Seth B. Darling & Douglas L. Sisterson, posted Jul 27th, 2016 Seth B. Darling is a scientist at the Argonne National Laboratory, specializing in energy and water. Douglas L. Sisterson is a senior manager at the Argonne National Laboratory. http://www.popsci.com/is-climate-too-complex-to-model-or-predict Hidden away in the very long screed (no graphs) is this: “What’s the good news? Well, perhaps this sort of thing will make the skeptic stop saying that the IPCC is exaggerating the problem. The models don’t get some things right, but where they get it wrong, it is almost always in the direction of underestimating the scale and pace of the problem. (A rare counterexample would be the surface-air-temperature trends in the past decade or so, which have risen more slowly than the vast majority of models had projected. Climate scientists are beginning to understand the reasons for this error, but this reminds us that climate models are not necessarily accurate over short timescales.)” The “rare counterexample” just happens to be at the time of the highest fossil fuel emissions in the entire industrial era. So no, “this sort of… Read more »

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