El Niño shortens the Pause by just one month

No global warming at all for 18 years 8 months

By Christopher Monckton of Brenchley

The Paris agreement is more dangerous than it appears. Though the secession clause that this column has argued for was inserted into the second draft and remained in the final text, the zombies who have replaced the diplomatic negotiators of almost 200 nations did not – as they should have done in a rational world – insert a sunset clause that would bring the entire costly and pointless process to an end once the observed rate of warming fell far enough below the IPCC’s original predictions in 1990.

It is those first predictions that matter, for they formed the official basis for the climate scam – the biggest transfer of wealth in human history from the poor to the rich, from the little guy to the big guy, from the governed to those who profit by governing them.

Let us hope that the next President of the United States insists on a sunset clause. I propose that if 20 years without global warming occur, the IPCC, the UNFCCC and all their works should be swept into the dustbin of history, and the prosecutors should be brought in. We are already at 18 years 8 months, and counting. The el Niño has shortened the Pause, and will continue to do so for the next few months, but the discrepancy between prediction and reality remains very wide.

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Figure 1. The least-squares linear-regression trend on the RSS satellite monthly global mean surface temperature anomaly dataset shows no global warming for 18 years 8 months since May 1997, though one-third of all anthropogenic forcings have occurred during the period of the Pause.

It is worth understanding just how surprised the modelers ought to be by the persistence of the Pause. NOAA, in a very rare fit of honesty, admitted in its 2008 State of the Climate report that 15 years or more without global warming would demonstrate a discrepancy between prediction and observation. The reason for NOAA’s statement is that there is supposed to be a sharp and significant instantaneous response to a radiative forcing such as adding CO2 to the air.

The steepness of this predicted response can be seen in Fig. 1a, which is based on a paper on temperature feedbacks by Professor Richard Lindzen’s former student Professor Gerard Roe in 2009. The graph of Roe’s model output shows that the initial expected response to a forcing is supposed to be an immediate and rapid warming. But, despite the very substantial forcings in the 18 years 8 months since May 1997, not a flicker of warming has resulted.

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Figure 1a: Models predict rapid initial warming in response to a forcing. Instead, no warming at all is occurring. Based on Roe (2009).

The current el Niño, as Bob Tisdale’s distinguished series of reports here demonstrates, is at least as big as the Great el Niño of 1998. The RSS temperature record is now beginning to reflect its magnitude. If past events of this kind are a guide, there will be several months’ further warming before the downturn in the spike begins.

However, if there is a following la Niña, as there often is, the Pause may return at some time from the end of this year onward.

The hiatus period of 18 years 8 months is the farthest back one can go in the RSS satellite temperature record and still show a sub-zero trend. The start date is not cherry-picked: it is calculated. And the graph does not mean there is no such thing as global warming. Going back further shows a small warming rate. The rate on the RSS dataset since it began in 1979 is equivalent to 1.2 degrees/century.

And yes, the start-date for the Pause has been inching forward, though just a little more slowly than the end-date, which is why the Pause has continued on average to lengthen.

The UAH satellite dataset shows a Pause almost as long as the RSS dataset. However, the much-altered surface tamperature datasets show a small warming rate (Fig. 1b).

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Figure 1b. The least-squares linear-regression trend on the mean of the GISS, HadCRUT4 and NCDC terrestrial monthly global mean surface temperature anomaly datasets shows global warming at a rate equivalent to 1.1 C° per century during the period of the Pause from May 1997 to September 2015.

Bearing in mind that one-third of the 2.4 W m–2 radiative forcing from all manmade sources since 1750 has occurred during the period of the Pause, a warming rate equivalent to little more than 1 C°/century (even if it had occurred) would not be cause for concern.

As always, a note of caution. Merely because there has been little or no warming in recent decades, one may not draw the conclusion that warming has ended forever. The trend lines measure what has occurred: they do not predict what will occur.

The Pause – politically useful though it may be to all who wish that the “official” scientific community would remember its duty of skepticism – is far less important than the growing discrepancy between the predictions of the general-circulation models and observed reality.

The divergence between the models’ predictions in 1990 (Fig. 2) and 2005 (Fig. 3), on the one hand, and the observed outturn, on the other, continues to widen. If the Pause lengthens just a little more, the rate of warming in the quarter-century since the IPCC’s First Assessment Report in 1990 will fall below 1 C°/century equivalent.

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Figure 2. Near-term projections of warming at a rate equivalent to 2.8 [1.9, 4.2] K/century, made with “substantial confidence” in IPCC (1990), for the 311 months January 1990 to November 2015 (orange region and red trend line), vs. observed anomalies (dark blue) and trend (bright blue) at just 1 K/century equivalent, taken as the mean of the RSS and UAH v.6 satellite monthly mean lower-troposphere temperature anomalies.

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Figure 3. Predicted temperature change, January 2005 to September 2015, at a rate equivalent to 1.7 [1.0, 2.3] Cº/century (orange zone with thick red best-estimate trend line), compared with the near-zero observed anomalies (dark blue) and real-world trend (bright blue), taken as the mean of the RSS and UAH v.6 satellite lower-troposphere temperature anomalies.

The Technical Note explains the sources of the IPCC’s predictions in 1990 and in 2005, and also demonstrates that that according to the ARGO bathythermograph data the oceans are warming at a rate equivalent to less than a quarter of a Celsius degree per century. In a rational scientific discourse, those who had advocated extreme measures to prevent global warming would now be withdrawing and calmly rethinking their hypotheses. However, this is not a rational scientific discourse.

Key facts about global temperature

These facts should be shown to anyone who persists in believing that, in the words of Mr Obama’s Twitteratus, “global warming is real, manmade and dangerous”.

Ø The RSS satellite dataset shows no global warming at all for 224 months from May 1997 to December 2015 – more than half the 444-month satellite record.

Ø There has been no warming even though one-third of all anthropogenic forcings since 1750 have occurred since 1997.

Ø The entire UAH dataset for the 444 months (37 full years) from December 1978 to November 2015 shows global warming at an unalarming rate equivalent to just 1.14 Cº per century.

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Ø Since 1950, when a human influence on global temperature first became theoretically possible, the global warming trend has been equivalent to below 1.2 Cº per century.

Ø The global warming trend since 1900 is equivalent to 0.75 Cº per century. This is well within natural variability and may not have much to do with us.

Ø The fastest warming rate lasting 15 years or more since 1950 occurred over the 33 years from 1974 to 2006. It was equivalent to 2.0 Cº per century.

Ø Compare the warming on the Central England temperature dataset in the 40 years 1694-1733, well before the Industrial Revolution, equivalent to 4.33 C°/century.

Ø In 1990, the IPCC’s mid-range prediction of near-term warming was equivalent to 2.8 Cº per century, higher by two-thirds than its current prediction of 1.7 Cº/century.

Ø The warming trend since 1990, when the IPCC wrote its first report, is equivalent to little more than 1 Cº per century. The IPCC had predicted close to thrice as much.

Ø To meet the IPCC’s original central prediction of 1 C° warming from 1990-2025, in the next decade a warming of 0.75 C°, equivalent to 7.5 C°/century, would have to occur.

Ø Though the IPCC has cut its near-term warming prediction, it has not cut its high-end business as usual centennial warming prediction of 4.8 Cº warming to 2100.

Ø The IPCC’s predicted 4.8 Cº warming by 2100 is well over twice the greatest rate of warming lasting more than 15 years that has been measured since 1950.

Ø The IPCC’s 4.8 Cº-by-2100 prediction is four times the observed real-world warming trend since we might in theory have begun influencing it in 1950.

Ø The oceans, according to the 3600+ ARGO buoys, are warming at a rate of just 0.02 Cº per decade, equivalent to 0.23 Cº per century, or 1 C° in 430 years.

Ø Recent extreme-weather events cannot be blamed on global warming, because there has not been any global warming to speak of. It is as simple as that.

Technical note

Our latest topical graph shows the least-squares linear-regression trend on the RSS satellite monthly global mean lower-troposphere dataset for as far back as it is possible to go and still find a zero trend. The start-date is not “cherry-picked” so as to coincide with the temperature spike caused by the 1998 el Niño. Instead, it is calculated so as to find the longest period with a zero trend.

The fact of a long Pause is an indication of the widening discrepancy between prediction and reality in the temperature record.

The satellite datasets are arguably less unreliable than other datasets in that they show the 1998 Great El Niño more clearly than all other datasets. The Great el Niño, like its two predecessors in the past 300 years, caused widespread global coral bleaching, providing an independent verification that the satellite datasets are better able than the rest to capture such fluctuations without artificially filtering them out.

Terrestrial temperatures are measured by thermometers. Thermometers correctly sited in rural areas away from manmade heat sources show warming rates below those that are published. The satellite datasets are based on reference measurements made by the most accurate thermometers available – platinum resistance thermometers, which provide an independent verification of the temperature measurements by checking via spaceward mirrors the known temperature of the cosmic background radiation, which is 1% of the freezing point of water, or just 2.73 degrees above absolute zero. It was by measuring minuscule variations in the cosmic background radiation that the NASA anisotropy probe determined the age of the Universe as 13.82 billion years.

The RSS graph (Fig. 1) is accurate. The data are lifted monthly straight from the RSS website. A computer algorithm reads them down from the text file and plots them automatically using an advanced routine that automatically adjusts the aspect ratio of the data window at both axes so as to show the data at maximum scale, for clarity.

The latest monthly data point is visually inspected to ensure that it has been correctly positioned. The light blue trend line plotted across the dark blue spline-curve that shows the actual data is determined by the method of least-squares linear regression, which calculates the y-intercept and slope of the line.

The IPCC and most other agencies use linear regression to determine global temperature trends. Professor Phil Jones of the University of East Anglia recommends it in one of the Climategate emails. The method is appropriate because global temperature records exhibit little auto-regression, since summer temperatures in one hemisphere are compensated by winter in the other. Therefore, an AR(n) model would generate results little different from a least-squares trend.

Dr Stephen Farish, Professor of Epidemiological Statistics at the University of Melbourne, kindly verified the reliability of the algorithm that determines the trend on the graph and the correlation coefficient, which is very low because, though the data are highly variable, the trend is flat.

RSS itself is now taking a serious interest in the length of the Great Pause. Dr Carl Mears, the senior research scientist at RSS, discusses it at remss.com/blog/recent-slowing-rise-global-temperatures.

Dr Mears’ results are summarized in Fig. T1:

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Figure T1. Output of 33 IPCC models (turquoise) compared with measured RSS global temperature change (black), 1979-2014. The transient coolings caused by the volcanic eruptions of Chichón (1983) and Pinatubo (1991) are shown, as is the spike in warming caused by the great el Niño of 1998.

Dr Mears writes:

“The denialists like to assume that the cause for the model/observation discrepancy is some kind of problem with the fundamental model physics, and they pooh-pooh any other sort of explanation.  This leads them to conclude, very likely erroneously, that the long-term sensitivity of the climate is much less than is currently thought.”

Dr Mears concedes the growing discrepancy between the RSS data and the models, but he alleges “cherry-picking” of the start-date for the global-temperature graph:

“Recently, a number of articles in the mainstream press have pointed out that there appears to have been little or no change in globally averaged temperature over the last two decades.  Because of this, we are getting a lot of questions along the lines of ‘I saw this plot on a denialist web site.  Is this really your data?’  While some of these reports have ‘cherry-picked’ their end points to make their evidence seem even stronger, there is not much doubt that the rate of warming since the late 1990s is less than that predicted by most of the IPCC AR5 simulations of historical climate.  … The denialists really like to fit trends starting in 1997, so that the huge 1997-98 ENSO event is at the start of their time series, resulting in a linear fit with the smallest possible slope.”

In fact, the spike in temperatures caused by the Great el Niño of 1998 is almost entirely offset in the linear-trend calculation by two factors: the not dissimilar spike of the 2010 el Niño, and the sheer length of the Great Pause itself. The headline graph in these monthly reports begins in 1997 because that is as far back as one can go in the data and still obtain a zero trend.

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Fig. T1a. Graphs for RSS and GISS temperatures starting both in 1997 and in 2001. For each dataset the trend-lines are near-identical, showing conclusively that the argument that the Pause was caused by the 1998 el Nino is false (Werner Brozek and Professor Brown worked out this neat demonstration).

Curiously, Dr Mears prefers the terrestrial datasets to the satellite datasets. The UK Met Office, however, uses the satellite data to calibrate its own terrestrial record.

The length of the Pause, significant though it now is, is of less importance than the ever-growing discrepancy between the temperature trends predicted by models and the far less exciting real-world temperature change that has been observed.

Sources of the IPCC projections in Figs. 2 and 3

IPCC’s First Assessment Report predicted that global temperature would rise by 1.0 [0.7, 1.5] Cº to 2025, equivalent to 2.8 [1.9, 4.2] Cº per century. The executive summary asked, “How much confidence do we have in our predictions?” IPCC pointed out some uncertainties (clouds, oceans, etc.), but concluded:

“Nevertheless, … we have substantial confidence that models can predict at least the broad-scale features of climate change. … There are similarities between results from the coupled models using simple representations of the ocean and those using more sophisticated descriptions, and our understanding of such differences as do occur gives us some confidence in the results.”

That “substantial confidence” was substantial over-confidence. For the rate of global warming since 1990 – the most important of the “broad-scale features of climate change” that the models were supposed to predict – is now below half what the IPCC had then predicted.

In 1990, the IPCC said this:

“Based on current models we predict:

“under the IPCC Business-as-Usual (Scenario A) emissions of greenhouse gases, a rate of increase of global mean temperature during the next century of about 0.3 Cº per decade (with an uncertainty range of 0.2 Cº to 0.5 Cº per decade), this is greater than that seen over the past 10,000 years. This will result in a likely increase in global mean temperature of about 1 Cº above the present value by 2025 and 3 Cº before the end of the next century. The rise will not be steady because of the influence of other factors” (p. xii).

Later, the IPCC said:

“The numbers given below are based on high-resolution models, scaled to be consistent with our best estimate of global mean warming of 1.8 Cº by 2030. For values consistent with other estimates of global temperature rise, the numbers below should be reduced by 30% for the low estimate or increased by 50% for the high estimate” (p. xxiv).

The orange region in Fig. 2 represents the IPCC’s medium-term Scenario-A estimate of near-term warming, i.e. 1.0 [0.7, 1.5] K by 2025.

The IPCC’s predicted global warming over the 25 years from 1990 to the present differs little from a straight line (Fig. T2).

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Figure T2. Historical warming from 1850-1990, and predicted warming from 1990-2100 on the IPCC’s “business-as-usual” Scenario A (IPCC, 1990, p. xxii).

Because this difference between a straight line and the slight uptick in the warming rate the IPCC predicted over the period 1990-2025 is so small, one can look at it another way. To reach the 1 K central estimate of warming since 1990 by 2025, there would have to be twice as much warming in the next ten years as there was in the last 25 years. That is not likely.

But is the Pause perhaps caused by the fact that CO2 emissions have not been rising anything like as fast as the IPCC’s “business-as-usual” Scenario A prediction in 1990? No: CO2 emissions have risen rather above the Scenario-A prediction (Fig. T3).

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Figure T3. CO2 emissions from fossil fuels, etc., in 2012, from Le Quéré et al. (2014), plotted against the chart of “man-made carbon dioxide emissions”, in billions of tonnes of carbon per year, from IPCC (1990).

Plainly, therefore, CO2 emissions since 1990 have proven to be closer to Scenario A than to any other case, because for all the talk about CO2 emissions reduction the fact is that the rate of expansion of fossil-fuel burning in China, India, Indonesia, Brazil, etc., far outstrips the paltry reductions we have achieved in the West to date.

True, methane concentration has not risen as predicted in 1990 (Fig. T4), for methane emissions, though largely uncontrolled, are simply not rising as the models had predicted. Here, too, all of the predictions were extravagantly baseless.

The overall picture is clear. Scenario A is the emissions scenario from 1990 that is closest to the observed CO2 emissions outturn.

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Figure T4. Methane concentration as predicted in four IPCC Assessment Reports, together with (in black) the observed outturn, which is running along the bottom of the least prediction. This graph appeared in the pre-final draft of IPCC (2013), but had mysteriously been deleted from the final, published version, inferentially because the IPCC did not want to display such a plain comparison between absurdly exaggerated predictions and unexciting reality.

To be precise, a quarter-century after 1990, the global-warming outturn to date – expressed as the least-squares linear-regression trend on the mean of the RSS and UAH monthly global mean surface temperature anomalies – is 0.27 Cº, equivalent to little more than 1 Cº/century. The IPCC’s central estimate of 0.71 Cº, equivalent to 2.8 Cº/century, that was predicted for Scenario A in IPCC (1990) with “substantial confidence” was approaching three times too big. In fact, the outturn is visibly well below even the least estimate.

In 1990, the IPCC’s central prediction of the near-term warming rate was higher by two-thirds than its prediction is today. Then it was 2.8 C/century equivalent. Now it is just 1.7 Cº equivalent – and, as Fig. T5 shows, even that is proving to be a substantial exaggeration.

Is the ocean warming?

One frequently-discussed explanation for the Great Pause is that the coupled ocean-atmosphere system has continued to accumulate heat at approximately the rate predicted by the models, but that in recent decades the heat has been removed from the atmosphere by the ocean and, since globally the near-surface strata show far less warming than the models had predicted, it is hypothesized that what is called the “missing heat” has traveled to the little-measured abyssal strata below 2000 m, whence it may emerge at some future date.

Actually, it is not known whether the ocean is warming: each of the 3600 automated ARGO bathythermograph buoys takes just three measurements a month in 200,000 cubic kilometres of ocean – roughly a 100,000-square-mile box more than 316 km square and 2 km deep. Plainly, the results on the basis of a resolution that sparse (which, as Willis Eschenbach puts it, is approximately the equivalent of trying to take a single temperature and salinity profile taken at a single point in Lake Superior less than once a year) are not going to be a lot better than guesswork.

Unfortunately ARGO seems not to have updated the ocean dataset since December 2014. However, what we have gives us 11 full years of data. Results are plotted in Fig. T5. The ocean warming, if ARGO is right, is equivalent to just 0.02 Cº decade–1, equivalent to 0.2 Cº century–1.

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Figure T5. The entire near-global ARGO 2 km ocean temperature dataset from January 2004 to December 2014 (black spline-curve), with the least-squares linear-regression trend calculated from the data by the author (green arrow).

Finally, though the ARGO buoys measure ocean temperature change directly, before publication NOAA craftily converts the temperature change into zettajoules of ocean heat content change, which make the change seem a whole lot larger.

The terrifying-sounding heat content change of 260 ZJ from 1970 to 2014 (Fig. T6) is equivalent to just 0.2 K/century of global warming. All those “Hiroshima bombs of heat” of which the climate-extremist websites speak are a barely discernible pinprick. The ocean and its heat capacity are a lot bigger than some may realize.

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Figure T6. Ocean heat content change, 1957-2013, in Zettajoules from NOAA’s NODC Ocean Climate Lab: http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT, with the heat content values converted back to the ocean temperature changes in Kelvin that were originally measured. NOAA’s conversion of the minuscule warming data to Zettajoules, combined with the exaggerated vertical aspect of the graph, has the effect of making a very small change in ocean temperature seem considerably more significant than it is.

Converting the ocean heat content change back to temperature change reveals an interesting discrepancy between NOAA’s data and that of the ARGO system. Over the period of ARGO data, from 2004-2014, the NOAA data imply that the oceans are warming at 0.05 Cº decade–1, equivalent to 0.5 Cº century–1, or rather more than double the rate shown by ARGO.

ARGO has the better-resolved dataset, but since the resolutions of all ocean datasets are very low one should treat all these results with caution.

What one can say is that, on such evidence as these datasets are capable of providing, the difference between underlying warming rate of the ocean and that of the atmosphere is not statistically significant, suggesting that if the “missing heat” is hiding in the oceans it has magically found its way into the abyssal strata without managing to warm the upper strata on the way.

On these data, too, there is no evidence of rapid or catastrophic ocean warming.

Furthermore, to date no empirical, theoretical or numerical method, complex or simple, has yet successfully specified mechanistically either how the heat generated by anthropogenic greenhouse-gas enrichment of the atmosphere has reached the deep ocean without much altering the heat content of the intervening near-surface strata or how the heat from the bottom of the ocean may eventually re-emerge to perturb the near-surface climate conditions relevant to land-based life on Earth.

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Figure T7. Near-global ocean temperatures by stratum, 0-1900 m, providing a visual reality check to show just how little the upper strata are affected by minor changes in global air surface temperature. Source: ARGO marine atlas.

Most ocean models used in performing coupled general-circulation model sensitivity runs simply cannot resolve most of the physical processes relevant for capturing heat uptake by the deep ocean.

Ultimately, the second law of thermodynamics requires that any heat which may have accumulated in the deep ocean will dissipate via various diffusive processes. It is not plausible that any heat taken up by the deep ocean will suddenly warm the upper ocean and, via the upper ocean, the atmosphere.

If the “deep heat” explanation for the Pause were correct (and it is merely one among dozens that have been offered), the complex models have failed to account for it correctly: otherwise, the growing discrepancy between the predicted and observed atmospheric warming rates would not have become as significant as it has.

In early October 2015 Steven Goddard added some very interesting graphs to his website. The graphs show the extent to which sea levels have been tampered with to make it look as though there has been sea-level rise when it is arguable that in fact there has been little or none.

Why were the models’ predictions exaggerated?

In 1990 the IPCC predicted – on its business-as-usual Scenario A – that from the Industrial Revolution till the present there would have been 4 Watts per square meter of radiative forcing caused by Man (Fig. T8):

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Figure T8. Predicted manmade radiative forcings (IPCC, 1990).

However, from 1995 onward the IPCC decided to assume, on rather slender evidence, that anthropogenic particulate aerosols – mostly soot from combustion – were shading the Earth from the Sun to a large enough extent to cause a strong negative forcing. It has also now belatedly realized that its projected increases in methane concentration were wild exaggerations. As a result of these and other changes, it now estimates that the net anthropogenic forcing of the industrial era is just 2.3 Watts per square meter, or little more than half its prediction in 1990 (Fig. T9):

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Figure T9: Net anthropogenic forcings, 1750 to 1950, 1980 and 2012 (IPCC, 2013).

Even this, however, may be a considerable exaggeration. For the best estimate of the actual current top-of-atmosphere radiative imbalance (total natural and anthropo-genic net forcing) is only 0.6 Watts per square meter (Fig. T10):

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Figure T10. Energy budget diagram for the Earth from Stephens et al. (2012)

In short, most of the forcing predicted by the IPCC is either an exaggeration or has already resulted in whatever temperature change it was going to cause. There is little global warming in the pipeline as a result of our past and present sins of emission.

It is also possible that the IPCC and the models have relentlessly exaggerated climate sensitivity. One recent paper on this question is Monckton of Brenchley et al. (2015), which found climate sensitivity to be in the region of 1 Cº per CO2 doubling (go to scibull.com and click “Most Read Articles”). The paper identified errors in the models’ treatment of temperature feedbacks and their amplification, which account for two-thirds of the equilibrium warming predicted by the IPCC.

Professor Ray Bates gave a paper in Moscow in summer 2015 in which he concluded, based on the analysis by Lindzen & Choi (2009, 2011) (Fig. T10), that temperature feedbacks are net-negative. Accordingly, he supports the conclusion both by Lindzen & Choi (1990) (Fig. T11) and by Spencer & Braswell (2010, 2011) that climate sensitivity is below – and perhaps considerably below – 1 Cº per CO2 doubling.

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Figure T11. Reality (center) vs. 11 models. From Lindzen & Choi (2009).

A growing body of reviewed papers find climate sensitivity considerably below the 3 [1.5, 4.5] Cº per CO2 doubling that was first put forward in the Charney Report of 1979 for the U.S. National Academy of Sciences, and is still the IPCC’s best estimate today.

On the evidence to date, therefore, there is no scientific basis for taking any action at all to mitigate CO2 emissions.

Finally, how long will it be before the Freedom Clock (Fig. T12) reaches 20 years without any global warming? If it does, the climate scare will become unsustainable.

clip_image038Figure T12. The Freedom Clock edges ever closer to 20 years without global warming

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co2islife
January 14, 2016 2:38 am

1) Q: How does CO2 400 ppm in the N Hemi and 400 ppm in the S Hemi result in a temperature differential bewtween the Hemis? A: It doesn’t
2) Q: What causes the difference? What is different? The N Hemi is largely land, whereas the S Hemi is largely H2O. H20 is an infinitely more uniform heat absorber than land.
3) Q: Has anything happened since the 1950s that could cause the N Hemi land mass to alter the climate and temperature? A: Yes, there are far more trees increasing the H2O in the atmosphere, and we now have miles and miles of blacktop and roads where green fields used to exist.
4) Isn’t the real signal of CO2 warming at night? CO2 is transparent to incoming radiation, so daytime temperatures are caused by visible light. A: Yes, those videos of an egg cooking on a side walk prove the incoming radiation is warming the earth surface, and that has nothing to do with CO2.
5) Are desert nightime temperatures increasing when adjusted for the daytime peak temperatures? A: I’ve found no evidence of that.
http://theinconvenientskeptic.com/wp-content/uploads/2012/01/Final-BW-Print-Version-TIS_html_5f0398df.png

co2islife
January 14, 2016 2:52 am

BTW, look again at this chart. The hottest hemisphere also is the coldest, proving that the atmosphere doesn’t trap much heat, and it is the black body radiator that is most important. In the N Hemi the surface goes from temperature extremes. In the summer you can fry and egg on the highway, and in the winter it is covered in ice. Because the earth surface doesn’t have the heat storing capacity of the oceans, as it cools, so does the atmosphere above it. If CO2 was the cause of the warming, you wouldn’t see such a drop off in the winter. In the S Hemi you have a constant thermostat called the oceans, and as the sun warms them, the oceans warm the atmosphere above them. As they cool, you will see the atmosphere above them cool as well. Clearly, if you explain what is warming the radiating black body you can explain what is warming the atmosphere above it, and warming the black body radiator has absolutley nothing to do with CO2. Everyone agrees, daytime temperatures are warming. If that is so, visible light, not CO2 is the culpret.If CO2 was the cause the slope of the nigth time would be greater than the daytime. It isn’t.
http://fas.org/irp/imint/docs/rst/Sect9/originals/Fig9_45.gif
http://theinconvenientskeptic.com/wp-content/uploads/2012/01/Final-BW-Print-Version-TIS_html_5f0398df.png

David A
Reply to  co2islife
January 14, 2016 3:28 am

CO2islife, I have maintained there is much which we can learn from the seasonal response where the atmosphere cooks in January despite a 90 watt per square meter increase. Thank you for illustrating this.
A question which I have not found an answers to is; does the earth, (land, oceans and atmosphere as a whole) gain or lose energy during the S.H. summer?

David A
Reply to  David A
January 14, 2016 3:30 am

### damm phones, atmosphere cools in January, not cooks.

richardscourtney
Reply to  David A
January 14, 2016 3:38 am

David A:
You ask

does the earth, (land, oceans and atmosphere as a whole) gain or lose energy during the S.H. summer?

The answer is ‘both’.
However, I suspect that by energy you mean ‘net energy’. It would be interesting to know why you ask because the considered time scale affects calculated changes to net energy.
Richard

January 14, 2016 2:53 am

Q: How does CO2 400 ppm in the N Hemi and 400 ppm in the S Hemi result in a temperature differential bewtween the Hemis?
Because its mixed with unicorn dust….don’t you know anything !!!

Hoplite
January 14, 2016 1:05 pm

Forecast of pause length 2016-2018
I am now forecasting that the pause will end in November 2016 and return again to more than 18 years in December 2017. In November 2017 it will almost completely disappear to less than 1 year in length.
I created 2 models of the RSS dataset for 2016 to 2018. One was 1998-2000 spliced onto the end of the latest RSS dataset and the other was 2010-2012 spliced on instead. I think it is a reasonable assumption that 2016-2018 will be something between those periods. The main point you will see in the graph below is that it doesn’t matter a whole lot between them the results are very similar.
http://s28.postimg.org/5nbqmq63x/Pause_length_2016_18.jpg

Hoplite
Reply to  Hoplite
January 14, 2016 1:12 pm

Edit: It will disappear in Nov 2016 not ’17 and will return somewhere between Dec 2017 and March 2018

Hoplite
Reply to  Hoplite
January 14, 2016 1:49 pm

Sorry another edit! Looking at the graph I couldn’t understand how the pause was not increasing after it recovered. I had forgotten to include the months after Dec-15 in the calculation of the length of the pause as I wasn’t doing any slopes within the period 2016-18 itself. For every month from Dec-15 to Dec-18 trends are calculated for every month from Jan-79 to Nov-15. It is now forecasting the pause to exceed 20 years sometime between January and March 2018. Basically, it looks like the AGW true believers will get all of 2017 to say the pause has ended in the troposphere! Then the sceptics get to gloat in 2018! As I said before, for two quite different el nino/la nina periods the pause lengths end up being quite similar.
This is the corrected graph:
http://s18.postimg.org/hrrynyh7t/Pause_length_2016_18_2.jpg

Hoplite
Reply to  Hoplite
January 14, 2016 1:51 pm

A further thing to note in the results is that they are predicting the pause to exceed 19 years this year in the July to September period.

Reply to  Hoplite
January 14, 2016 9:01 pm

Hoplite
This is all pure speculation
actually nobody can really say whether
2016 will be warmer or colder than 2015
This is why your local bookmaker will be going
on a luxury cruise this summer, and not you !
😉

Hoplite
Reply to  Hoplite
January 15, 2016 12:07 am

Actually it is and it isn’t. It is not speculation in that the results show for two really quite different temperature series over the next three years that the pause length sequence and significant change points are very similar. It is speculation in that I don’t know what the temperature series for the next three years is and don’t pretend that I do. But what I can say is that it is most likely to be somewhere between 1998-2000 and 2010-2012 (or at least similar) and I think most would agree that that will be so. All I was trying to do, therefore, was calculate what the likely projection of pause length will be over the next three years. That’s useful as when it disappears, as it most certainly will, and we’re screamed at that we need to start panicking again that we can say ‘that’s old news, sure we’ve know that for months and what’s more the pause will most probably return in around 12-14 months time and be greater than 20 years in length when it does!’. If it is the case that 2016-2018 is less than 2010-12 then the pause disappearance will be less and for shorter duration (I might do a calculation of that) but it will go down significantly for a while. At this point no one is saying it will be greater than 1998. What is unknown is the longer term average after this el nino but that won’t be apparent until 2020+.
I had seen some assert here on this thread that the pause length would not become less than 16-17 years due to the major 1998 event but these results show that is not correct. That was the point I was intrigued by and why I did these calculations.

Hoplite
January 15, 2016 12:55 am

Grrrh! I finished this late last night and was tired – that’s my excuse anyway!! I checked my counting of the months back to last negative trend and realised I had a small error in the routine as I didn’t reset the variable after each loop. It only became important when a month didn’t have any negatives which happened after Mar-Apr 2016. This means the disappearance of the pause is significantly earlier at March or April 2016 not November.
I have checked this in detail and am pretty sure it is now correct. My results for Dec-15 match Christopher’s exactly at last negative trend in May 1997. All the same conclusions apply: pause disappears around Mar-Apr 2016 and returns Jan-Mar 2018 at over 20 years. Ignore the very low but growing trend in between these periods as that is too dependent on the exact nature of the monthly anomalies and could be subject to major differences.
New graph:
http://s10.postimg.org/t6to66rjt/Pause_length_2016_18_3.jpg

Reply to  Hoplite
January 15, 2016 2:27 am

I did the same calculation using 1998-2000 to extend and got similar results. But 2016-8 starts from a much warmer base than the earlier El Nino, even in RSS. The mean for 1997 was 0.102°C. The mean for 2015 was 0.36°C. There is a similar contrast in the other lead-up years. If I add even 0.1 to 2016-2018 to allow for this warmer start, there is no resuscitated pause.

Hoplite
Reply to  Nick Stokes
January 15, 2016 7:29 am

Nick,
Yes I had wondered a bit about that. When looking at 1998 it appears to return to the old mean level before moving up around 2001 to the new mean level it has been at since. I will run another case with it returning in 2017-18 to the new mean but will have to extend it another 3 years to see if the pause reappears. I’ll use the 2001-2006 data for the period following 2016. I’ll report back!

Hoplite
Reply to  Nick Stokes
January 15, 2016 9:13 am

RSS 1979-2022 (2016=1998; 2017-22=2001-06)
http://s29.postimg.org/kcw2emxuf/1979_2022_98_01_06.jpg
RSS 1979-2022 (2016=2010; 2017-22=2001-06)
http://s21.postimg.org/q1awl7p9j/1979_2022_10_01_06.jpg
Pause Length Results
http://s7.postimg.org/noyewyv5n/Pause_length_2016_22_98_01_06.jpg
The pause does not return in either case as the furthest back a negative trend occurs is Jul-09 whereas it was going back to 1997 and returned there in the previous example that was up to 2018.
However, that example is a little extreme as it is an el nino followed by no la nina. To make it realistic I then replaced 2017-18 with 2011-12 as that was the la nina following 2010 at the new higher mean (post 2001).
Just showing this RSS series for a ’98 el nino:
http://s18.postimg.org/7ax718q49/1979_2022_98_11_12_03_06.jpg
And the pause length results are as follows:
http://s12.postimg.org/4v7eselnx/Pause_length_2016_22_98_11_12_03_06.jpg
In this it does indeed return by early 2018 for both cases but as you can see it’s a fairly bumpy ride thereafter if the RSS anomalies are anything like 2003-06 and keep at the same mean.
The overall conclusion is the key factor is whether or not there is a la nina at least similar to 2011-12 period. However, it seems fairly certain (unless this el nino is less than 2010) that the pause will disappear in Mar-Apr this year and will return in early 2018 if there is a comparable la nina. After that is anyone’s guess but it looks bumpy ride if there’s no downward trend in RSS after 2018.

Hoplite
Reply to  Nick Stokes
January 15, 2016 9:14 am

RSS 1979-2022 (2016=1998; 2017-22=2001-06)
http://s29.postimg.org/kcw2emxuf/1979_2022_98_01_06.jpg
RSS 1979-2022 (2016=2010; 2017-22=2001-06)
http://s21.postimg.org/q1awl7p9j/1979_2022_10_01_06.jpg
Pause Length Results
http://s7.postimg.org/noyewyv5n/Pause_length_2016_22_98_01_06.jpg
The pause does not return in either case as the furthest back a negative trend occurs is Jul-09 whereas it was going back to 1997 and returned there in the previous example that was up to 2018.

Hoplite
Reply to  Nick Stokes
January 15, 2016 9:18 am

However, that example is a little extreme as it is an el nino followed by no la nina. To make it realistic I then replaced 2017-18 with 2011-12 as that was the la nina following 2010 at the new higher mean (post 2001).
Just showing this RSS series for a ’98 el nino:
http://s18.postimg.org/7ax718q49/1979_2022_98_11_12_03_06.jpg
And the pause length results are as follows:
http://s12.postimg.org/4v7eselnx/Pause_length_2016_22_98_11_12_03_06.jpg
In this it does indeed return by early 2018 for both cases but as you can see it’s a fairly bumpy ride thereafter if the RSS anomlies are anything like 2003-06 and keep at the same mean.
The key is the events after 2016 and whether or not there is a la nina comparable to 2011-12.
Overall, it can be concluded that the pause will disappear in Mar-Apr this year and will return in early 2018 if there is a la nina (assuming the el nino is at least as strong as 2010). After 2018 it will jump around a lot unless a downward trend starts compared with 2003-06.

Hoplite
Reply to  Nick Stokes
January 15, 2016 9:21 am

Sorry. Wrong title on the last RSS time series graph: should be 2016=1998; 2017-18=2011-12; 2019-22 =2003-06.

Reply to  Hoplite
January 15, 2016 5:05 am

I created 2 models of the RSS dataset for 2016 to 2018. One was 1998-2000 spliced onto the end of the latest RSS dataset and the other was 2010-2012 spliced on instead.

To spare me the effort of replicating your work, could you just confirm that this means what it literally says?
I read it as saying that for the next three years you’re using the actual historical RSS anomaly values from January 1998 (or 2010) through December 2018 (or 2012). In other words, you are not instead so translating those values that the difference between December 2015 and January 2016 is the same as the one between December 1997 and January 1998 (or between December 2009 and January 2010).

Hoplite
Reply to  Joe Born
January 15, 2016 7:22 am

Hi Joe,
Yes I used the exact anomaly values for Jan-98 to Dec-00 and Jan-10 to Dec-12 appending them onto the latest RSS dataset (see below). Just a straight copy, but Nick has a point above which I’ll address now. The main point was to get an idea if the pause would disappear (i.e. become less than 15 or so years) and if the following 2 years were similar when and if the pause would reappear.
http://s9.postimg.org/ttecd800f/RSS_1979_to_2018.jpg

Reply to  Joe Born
January 15, 2016 7:55 am

Thanks a lot.
I agree that your approach affords some insight. Since “the trend’s your friend,” I probably would have added some secular trend to the previous values if I were the one hazarding a “forecast.” Still, my approach would be vulnerable to the argument that my choice of secular trend necessarily is somewhat arbitrary, so I can understand your choice of approach.

Hoplite
Reply to  Joe Born
January 15, 2016 9:28 am

Joe – yes I’m not trying to predict what the RSS anomalies will be so I’m not adding upward trends or anything to them (I wouldn’t have a clue how to predict them anyway and assume no one really knows how to either but I’m sure there are many who could make a much greater stab at it than me). As you can see, just by playing about with different scenarios of ’98 or ’10 el nino and la nina or not gives you a feel for how the pause will disappear and appear again. As things start to pan out over the next 2-3 years it should give people an idea of whether or not to expect the pause to disappear or reappear in the forthcoming 6-12 month period.

Hoplite
Reply to  Joe Born
January 15, 2016 10:04 am

Another way to look at the occurrences of negative trends is the trend map below. This is for the pause length 2016-22 graph just above. The map is created from the output of the program and is the trend matrix (36,805 values) reformatted and reduced in size. Horizontal axis is the future period Dec-15 to Dec-22 and vertical axis is the past period Nov-15 to Jan-79. In this map the red areas are negative trends and black are positives. Anything previous to May-97 is only black and I didn’t include it in this graphic. As you can see there are negative trend periods occurring at 2009, 2000 and 1997 that keep disappearing and reappearing.
http://s10.postimg.org/a7j2pj2ix/Slope_map_1979_2022.jpg

johann wundersamer
January 21, 2016 2:17 am

everybody can know that Mokton’s “irreducibly simple” model was made to mimick, in the shortest way, the behavior of the ‘climate science’ models:
and thus lay bar open their basic flaw.
So crying ‘wrong output’ always debunks the ‘climate science’ models.
____
leaning on the italian ‘you can discuss with an asshole but you can’t debate with a stupid’:
you can discuss with a contrarian but you can’t debate with an obsessed.
Hans

johann wundersamer
January 21, 2016 2:38 am

In fact you can discuss with a broad range of people having their own points of mind.
But you can’t discuss with an obsessed stupid.
____
It’s not up to Monkton et al. to fabricate a ‘right’ climate model – when it’s obvious that all climate models since are unable to represent real world.