Global temperature update: no warming for 18 years 6 months
By Christopher Monckton of Brenchley
For 222 months, since December 1996, there has been no global warming at all (Fig. 1). This month’s RSS temperature – still unaffected by a slowly strengthening el Niño, which will eventually cause temporary warming – passes another six-month milestone, and establishes a new record length for the Pause: 18 years 6 months.
What is more, the IPCC’s centrally-predicted warming rate since its First Assessment Report in 1990 is now more than two and a half times the measured rate. On any view, the predictions on which the entire climate scare was based were extreme exaggerations.
However, it is becoming ever more likely that the temperature increase that usually accompanies an el Niño may come through after a lag of four or five months. The Pause may yet shorten somewhat, just in time for the Paris climate summit, though a subsequent La Niña would be likely to bring about a resumption of the Pause.
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 6 months since December 1996.
The hiatus period of 18 years 6 months is the farthest back one can go in the RSS satellite temperature record and still show a sub-zero trend. Note that 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 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. For the time being, these two graphs will be based on RSS alone, since the text file for the new UAH v.6 dataset is not yet being updated monthly. However, the effect of the recent UAH adjustments – exceptional in that they are the only such adjustments I can recall that reduce the previous trend rather than steepening it – is to bring the UAH dataset very close to that of RSS, so that there is now a clear distinction between the satellite and terrestrial datasets, particularly since the latter were subjected to adjustments over the past year or two that steepened the apparent rate of warming.
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 305 months January 1990 to May 2015 (orange region and red trend line), vs. observed anomalies (dark blue) and trend (bright blue) at less than 1.1 K/century equivalent, taken as the mean of the RSS and UAH v. 5.6 satellite monthly mean lower-troposphere temperature anomalies.
Figure 3. Predicted temperature change, January 2005 to May 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. 5.6 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.
Key facts about global temperature
Ø The RSS satellite dataset shows no global warming at all for 222 months from December 1996 to May 2015 – more than half the 437-month satellite record.
Ø The entire RSS dataset from January 1979 to date shows global warming at an unalarming rate equivalent to just 1.2 Cº per century.
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 0.8 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 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 1.1 Cº per century. The IPCC had predicted two and a half times as much.
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 bathythermograph buoys, are warming at a rate of just 0.02 Cº per decade, equivalent to 0.23 Cº per century.
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 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 to capture such fluctuations without artificially filtering them out than other datasets.
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: 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:
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.
Curiously, Dr Mears prefers the much-altered terrestrial datasets to the satellite datasets. The UK Met Office, however, uses the satellite record to calibrate its own terrestrial record.
The length of the Great Pause in global warming, 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. It remains possible that el Nino-like conditions may prevail this year, reducing the length of the Great Pause. However, the discrepancy between prediction and observation continues to widen.
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 less extreme medium-term Scenario-A estimate of near-term warming, i.e. 1.0 [0.7, 1.5] K by 2025, rather than its more extreme Scenario-A estimate, i.e. 1.8 [1.3, 3.7] K by 2030.
It has been suggested that the IPCC did not predict the straight-line global warming rate that is shown in Figs. 2-3. In fact, however, its predicted global warming over so short a term as the 25 years from 1990 to the present differs little from a straight line (Fig. T2).
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.
Likewise, to reach 1.8 K by 2030, there would have to be four or five times as much warming in the next 15 years as there was in the last 25 years. That is still less 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).
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.
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 less than 1.1 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 two and a half 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.
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.
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.
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.
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. T7):
Figure T7. 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:
Figure T8: 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. T9):
Figure T9. 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 will shortly give a paper in Moscow in which he will conclude, 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 and by Spencer & Braswell (2010, 2011) that climate sensitivity is below – and perhaps considerably below – 1 Cº per CO2 doubling.
Figure T10. 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.
Discover more from Watts Up With That?
Subscribe to get the latest posts sent to your email.
Years ago at ClimateAudit I was ridiculed for saying that not only did we not know the magnitude of water vapor and cloud feedbacks, but also we were ignorant of the sign of it.
=============
According to fig. T9 Stephens et al (cousins of Trenberth et al ??) The imbalance of power input-output to the earth is 0.6 +/- 17 W/m^2
Now as I recall, when I was at UofA and my cohorts were doing polarized proton and neutron beam experiments, they considered it a success if they got the order of magnitude right. So 0.6 +/- 6 would have been cause for a beer at the bar.
But 0.6 +/- 17 is not in the beer at the bar class.
More like going to the bar for a game of darts !!
And I’ve only just perused Lord Monckton’s latest essay, so I can’t wait to find out what other jewels he has exposed for us.
So back to the reading.
g
And if the surface imbalance is essentially zero +/- 17 W/m^2, how does that “knowledge” improve to +/- 0.4 by the time it gets escaped to space ??
I must have skipped the statistics class that tells you how to add noise to noise, and get silence.
University of Arizona or University of Alberta?
@george e. smith
Please explain figure 1.
“However, the effect of the recent UAH adjustments – exceptional in that they are the only such adjustments I can recall that reduce the previous trend rather than steepening it ”
Read more:
for UAH:
version B, NOAA-7 correction, reduced the trend
version C, removal of residual annual cycle increased the trend
version D, orbital decay adjustment increased the trend
version D, hot target temperature correction decreased the trend
version 5 di urnal correction increased the trend
version 5.1 tightening data screening decreased the trend
version 5.2 diurnal drift correction increased the trend
or look at CRU oocean or NOAA ocean. adjustments cool
Those adjustments certainly cooled the 1930’s and before, eh?
(Using my best Canadian accent.)
I have no idea what Stephen Mosher is trying to say with relation to what Christopher Monckton of Brenchley has to say. I read the post by Christopher Monckton of Brenchley and found his points believable and accurate.
So come on Stephen, please explain EVERYTHING that is wrong with this post by Christopher Monckton of Brenchley and not just allude in some drive-by trolling way that something is wrong in the state of Denmark.
I believe his point is that anyone who has criticized the adjustments made to the surface record data, must also criticize these adjustments.
Of course he either just doesn’t get the fact, or is doing his best to ignore the fact that we aren’t criticizing adjustments per se, we are criticizing adjustments using faulty methods or worse, undisclosed methods.
Monkton claim:
“However, the effect of the recent UAH adjustments – exceptional in that they are the only such adjustments I can recall that reduce the previous trend rather than steepening it”
1. he claims the are EXCEPTIONAL because they are the ONLY adjustments that REDUCE a trend.
2. The caveat being “that he knows of”
So I help the good lord. he needs to READ MORE because they are not exceptional.
in fact the most important adjustments COOL THE RECORD
Mosher
And, by cooling the record (the old temperatures), that change CREATES a warming trend because the RECENT temperatures are not changed.
You are making our point that the RESULT of the adjustments CREATES today’s Man-made global warming.
Are you finally admitting that you can’t actually criticize the adjustments, despite the fact that all the data and all of the methods have been made publicly available?
Because they are the oniy ones that do not have a AGW agenda. It is so obvious.
RSS May = 0.31 anomoly
Up from 0.175 in April
Just below Feb’s anomaly of 0.33c then!
We’re all going to die!!!!!!
According to the Met Office the 2014 for the CET was one of the warmest on the record. However, in last 5 months the CET has stalled a bit and it has been hovering around its 20 year average, detailed daily min/max temps HERE
By clever use of the two definitions of GW (only the man made component versus all inclusive) you can still say that global warming continues and the models are right, even if the measured temperature drops.
I wonder if the models were made according to the old definition. Most work on the models began when the old definition was still effective.
The habitues of the Climate Fearosphere are hilariously famous for their knee- jerk “Oh, but…” excuses which spread like wildfire amongst their myriad group think outlets. One of their funniest repeat- after- me refrains is that the pause is cherry picked. I’m gonna just LOL at the thought of that blathering stupidity and nonsense.
So, LOL.
There is no such opportunities to be strengthened El Niño. Falls amount of solar energy extending into the system.
El Nino now looking like El Nono: http://www.warwickhughes.com/blog/?p=3757
Monthly Niño-3.4 index
2014 8 26.83 26.92 -0.09
2014 9 27.01 26.83 0.18
2014 10 27.25 26.79 0.46
2014 11 27.57 26.74 0.83
2014 12 27.36 26.69 0.67
2015 1 27.21 26.68 0.53
2015 2 27.31 26.84 0.47
2015 3 27.84 27.34 0.51
2015 4 28.62 27.81 0.81
2015 5 28.82 27.91 0.91
Let’s see the temperature at the altitude of 1,500 meters over the North Atlantic.
http://earth.nullschool.net/#current/wind/isobaric/850hPa/overlay=temp/equirectangular
which will eventually cause temporary warming..
==
and they will claim that they were right…..without realizing it proves they were wrong
I would like to hear how the magical CO2 dust creates or affects the el Niño wave. Back radiation heating water again, but controlling 380 ppm of the atmosphere against Mother Natures 30,000 ppm water vapor will save us.
With the May anomaly at 0.310, the 5 month average is 0.287 and RSS would remain in 6th place if it stayed this way.
Figure T6 – global ocean heat content change
y-axis scale intervals
50ZJ = 0.02K
100ZJ = 0.04K
150ZJ = 0.06K
200ZJ = 0.07K??
250ZJ = 0.09K
Mistake or rounding?
Rounding.
Interesting take here:
http://www.timescolonist.com/opinion/letters/el-ni%C3%B1o-is-late-to-the-blob-party-1.1954094
I can’t find a link to the article he refers to.
He’s a tidal expert at University of Victoria.
http://web.uvic.ca/~rdewey/eos110/tides/tideswaves.html
It is an interesting exercise to print out the Australian BOM SOI monthly data and simply color in the months of El Nino in Red and La Nina in Blue. ( values -8 and more negative El Nino months : La Ninas +8 and more positive. Look at the frequency and amplitudes of each during warming and cooling episodes.
Note these events are symptoms not the ultimate cause of the warming and cooling.
http://www.bom.gov.au/climate/current/soihtm1.shtml
Compare the current trend with say the super EL Nino of 1997-8. This one probably won’t amount to much as far as temperatures are concerned. Maybe a modest peak in about October – November.
The current daily SOI has turned recently turned positive see
https://www.longpaddock.qld.gov.au/seasonalclimateoutlook/southernoscillationindex/30daysoivalues/
At the present, the cooling trend since the RSS Millennial temperature peak in 2003 continues. See
http://www.woodfortrees.org/plot/rss/from:1980.1/plot/rss/from:1980.1/to:2003.6/trend/plot/rss/from:2003.6/trend
For forecasts of the timing and amplitude of the further coming cooing see
http://climatesense-norpag.blogspot.com/2014/07/climate-forecasting-methods-and-cooling.html
Thank you, Lord Monckton, for your very informative and entertaining presentations that I’ve viewed on the internet.
and from the impostors….
http://vvattsupwiththat.blogspot.co.uk/2015/06/has-monckton-dynasty-lost-mandate-of.html
That “person” used to post frequently on National Review.
He got all bent out of shape because we didn’t afford him the level of worship that he felt a full professor such as himself was due.
When he found himself incapable of winning an open argument he retreated to a forum in which he could win any argument because the opposition was banned.
Much as I presume his classroom operates.
“When he found himself incapable of winning an open argument he retreated to a forum in which he could win any argument because the opposition was banned.
Much as I presume his classroom operates.”
Well, he’s banned here.
Nick Stokes
Yes, such abusive and offensive trolls who persistently and deliberately disrupt serious debate should be removed from any serious blog. I don’t understand why you are permitted the leniency afforded to your behaviour.
Richard
@Nick Stokes
Please explain the reasoning behind your observation. As it stands, it makes no sense.
Lord Monckton fails to mention that his Monckton of Brenchley et al. (2015) article was recently refuted by a peer-reviewed article in the same journal, Richardson et al. (2015), which found that:
“In summary, M15 fail to demonstrate that IPCC estimates of climate sensitivity are overstated. Their alternative parameterization of a commonly used simple climate model performs poorly, with a bias 350 % larger and RMSE 150 % larger than CMIP5 median during 2000–2010. Their low estimates of future warming are due to assumptions developed using a logically flawed justification narrative rather than physical analysis. The key conclusions are directly contradicted by observations and cannot be considered credible.”
http://link.springer.com/article/10.1007/s11434-015-0806-z
Whole subject of sensitivity has grown from an amoeba to a half a tone jellyfish.
It can be easily numerically demonstrated that the so called average ‘global temperature’s sensitivity to the annual change of either of two natural variables:
1. The Earths rate of rotation
2. Geomagnetic dipole
btw which are measured BY FAR more accurately than the estimate of the ‘GT’, is similar or even greater than the one in the respect of CO2.concentration.
http://www.vukcevic.talktalk.net/MTCa.gif
What does the symbol uT on the right side hand of the graph stand for? Thanks and you are on to something .
Micro Tesla. Tesla is MKS unit for strength of magnetic field, 1T= Webber/m2 or 1T= 10,000 Gauss.
a) Geomagnetic field is by far strongest modulator of cosmic rays
b) Secular change in the GMF is more often than not result of circulation within the liquid core at or near the mantle’s boundary.
Jackson – Bloxham data for the field variability at the boundary show close correlation to the sunspot cycles
http://www.vukcevic.talktalk.net/J-V.gif
In that respect the current temperature pause associated with the swing in the dipole values direction, may well be related to some elements of the solar activity.
Graph is obtained by extracting shorter periodicities from Jackson – Bloxham data published in early 1990s, thus to eliminate the end effect of filtering the output is curtailed to 1980.
It is regretful that the authors of the data compilation, have not gone back since to update it.
thanks for the information.
Don’t be modest Zeke, you are one of the coauthors.
Tonyb
I didn’t realize that Zeke had succumbed to the dark side quite so completely.
Seriously?
The list of authors suggesting that M15 cannot be considered credible comprises Mark Richardson, Zeke Hausfather, Dana A. Nuccitelli, Ken Rice and John P. Abraham.
What a mind bending collection of honesty, integrity, openness and dedication to scientific discovery.
Just think, with the addition of Michael Mann, Ben Santer and Stephen Lewandowsky you could have assembled 97% of climate science’s most dedicated shysters all in one place.
Golden!
Right on! I’m hoping that an orange suit and a hopalong walk are in the future for at least some of these people, as they are escorted into Sheriff Joe’s emporium for some baloney sandwiches for quite a few years in the future.
“””””….. Their low estimates of future warming are due to assumptions developed using a logically flawed justification narrative rather than physical analysis. The key conclusions are directly contradicted by observations and cannot be considered credible.” …..””””
This is my selection for getting the Bullwer Lytton prize this year.
Congratulations to its authors.
g
Chuckle.
“T’was a dark and stormy night…”
Their low estimates of future warming … are directly contradicted by observations and cannot be considered credible.”
================
hop into the way-back machine sherman, were off to observe the future.
Weren’t you a co-author of this? Why wouldn’t you identify yourself as such?
MRW
Would you want to publicise it if you were associated with such tripe?
Richard
@Zeke Hausfather,
Ah! I see another has identified you as a co-author.
Since the Richardson et al. paper is paywalled, I have no idea what is meant by “Their alternative parameterization of a commonly used simple climate model.”
What Monckton et al. did was use an equation that wildly miscalculates the responses of the Roe models the authors ostensibly assumed; their equation is the wrong one for calculating such models’ transient responses. The systems described by the Roe models (as abstracted in Monckton et al.’s Table 2) are all time-invariant, and all but the first one impose delay: they have memory. But Monckton et al.’s equation treats those models as though they all described time-variant, memoryless systems. If you were to follow the logic of their equation, for example, you would conclude that all the water in a leaky bathtub vanishes the instant the faucet is closed, no matter how much water was in it previously or how small the leak is. Consequently, the calculations in their Tables 4 and 6 are meaningless.
Their projection for the rest of this century doesn’t depend on that feature, though. It’s essentially just the result of assuming a model that’s memoryless and exhibits a feedback level at the center of a range the authors divined from gazing at the last 800,000 years, chanting “thermostasis,” throwing in some eye of newt, and dubbing the range’s high end the “process engineer’s design limit.” For that model their equation is okay; unlike the Roe models depicted in Monckton et al.’s Fig. 4, that model is memoryless,
So an explanation of the Richardson et al. paper’s rationale would be helpful.
Mr Born’s points have been raised and answered before.
Monckton of Brenchley: “Mr Born’s points have been raised and answered before.”
The mark of the charlatan: first evade, then contend the question has already been answered. From the Clinton school of public discourse.
Lord Monckton’s “answer” was to say that the error was minor and to accuse me of dishonesty for not going through this non-unity-transience fraction examples. Had he gone through those examples properly as I have to compare the correct model output with the ones the Monckton et al. equation produces, he would have found some of his equation’s results are off by more than a factor of three.
Lord Monckton’s “answers” are all hat, no cattle. I can back up everything I say. He can’t.
Hi Joe,
Unfortunately we don’t have Heartland paying our open access fees, so there is no easy way around the paywall. However, I’d be happy to send you a copy if you email me at zeke@berkeleyearth.org
Richardson et al. (2015)?
Keep it in the ground Grauniadistani.
Thanks, Zeke. I’ll add to my reading list.
Note also that the whole case above against the IPCC 1990 projections is based on cherry-picking only one of four Scenarios, Scenario A, on the contention that it most closely matches emissions. But emissions are not concentrations nor forcings. Scenarios B, C and D have been disappeared. The High-Low-Best chart is based on varying climate sensitivity, not forcings. all under a single forcing – Scenario A. However Monckton himself removes the basis of his house of cards as he correctly states present day net anthropogenic forcings as 2.3W/m2, which are far closer to IPCC Scenarios B and C. (IPCC 1990 Table 2-4).
Monckton states the global temperature trend since 1990 as 1.06C / century. IPCC 1990 projected ‘just over 0.1C per decade’ under Scenario B. Thus ‘Under Scenario B the IPCC models projected the actual temperature trend accurately’ is a true statement, certainly containing more truth than the post above, because Scenario B actually came to pass, Scenario A decidedly did not.
Phil Clarke
So, you are saying it is a “cherry pick” to compare with reality the scenario that “most closely matches emissions”! And you say the resulting observation that the model predictions are wrong should be ignored because they are based on that “cherry pick”!
Phil Clarke, in all seriousness, please say who outside of an insane asylum would be willing to accept your nonsensical assertions.
Richard
No, Richard, I said that was the basis of his Lordships selection, that CO2 emissions in 2014 were closer to Scenario A. But CO2 is not the only GHG and 2015 is only one year. Scenario A had CO2 concentrations well in excess of current values and net forcings – from CO2 and all other manmade forcings ditto.
In 1990, the IPCC did not know how forcings would develop, and so they made a range of forecasts based on a range of possible futures forcings and concentrations. A glance at the report, Table 2.4, is enough to see that Scenarios B and C were a lot closer to how forcings increased in reality. Anyone still using scenario A is the person more suited to the asylum 😉
Phil Clarke
I quoted what you did say and commented on that. Then I asked you
You have replied saying
I am assuming you know your revision of your original bollocks is also bollocks.
The IPCC projected CO2 equivalence (n.b. NOT only CO2).
Scenario A was nearest to what happened in terms of emissions.
If as you claim “Scenario A had CO2 concentrations well in excess of current values and net forcings” then that is – of itself – a failure of the model when Scenario A closely matched the emissions.
And the temperature has NOT risen as the models projected for Scenario A, instead we have had the ‘pause’.
I repeat,
Phil Clarke, in all seriousness, please say who outside of an insane asylum would be willing to accept your nonsensical assertions.
Richard
“Lord Monckton fails to mention that his Monckton of Brenchley et al. (2015) article was recently refuted by a peer-reviewed article in the same journal, Richardson et al. (2015)…”
Ah, so it’s been “refuted” by all the “Usual Suspects”, in fact.
Yeah, right…
When you start to consider where they are changes that the claimed precision of these changes is often beyond the actual ability of the instruments used to measure them , given error factors, you can see how much panic has been created on the back of such poor reality based data. Which may explain way climate ‘science ‘ much prefers models where it can ‘create’ all the changes it needs .
This chart shows the RSS data before the start of Lord Monckon’s pause, with the linear trend extrapolated forward to 2015. So if warming stopped in 1997, current temperatures must be below this line, right?
http://www.woodfortrees.org/plot/rss/to:1997/plot/rss/scale/detrend:-0.26/offset:-0.1/plot/rss/to:1997/trend
Not so:
http://www.woodfortrees.org/plot/rss/to:1997/plot/rss/scale/detrend:-0.26/offset:-0.1/plot/rss/to:1997/trend/plot/rss/from:2014
There’s apparently been a slightly higher rate of warming since the “pause” started.
Try again using the same data set and Monckton. UAH Satellite data.
RSS measures sea surface temperature only. UAH measures air temperature over land and sea.
Apologies … RSS is not only Sea Surface temperatures ..
With UAH it’s the same only more so
http://www.woodfortrees.org/plot/uah/to:1997/plot/uah/scale/detrend:-0.13/offset:-0.165/plot/uah/to:1997/trend/plot/uah/from:2014
Why did you stop at 1997 … ?
To skip out the El Nino ? Well, I bet that wont be cut out when it comes to alarmists claiming warmer temperatures are down to CO2
Here is your chart to 1998 ..
http://www.woodfortrees.org/plot/rss/to:1998/plot/rss/scale/detrend:-0.26/offset:-0.1/plot/rss/to:1998/trend/plot/rss/from:2014
See anything different ?
You have the parameters wrong. Try this:
http://www.woodfortrees.org/plot/rss/from:1997/to:2015/plot/rss/from:1997/trend
Reg, you beat me to posting exactly that same chart. Good for you.
I was going to ask Nigel Harris why the weird, cherry-picked offset numbers, etc? He doesn’t need those.
Let’s just look at the straight RSS data from 1997 along with a trend line, which you posted above.
That tells us what we need to know: global warming stopped a long time ago. The alarmist crowd was flat wrong. Now they’re just backing and filling, trying to get observations and data to conform to their models, rather than the other way around.
So, which of these trend lines would you say is the cherry picked one?
http://www.woodfortrees.org/plot/rss/to:2015/plot/rss/from:1997/trend/plot/rss/trend
Oh and those “weird, cherry picked offset numbers” are simply using the tools available in WFT to create a straight line that extrapolates the pre-pause trend line forward.
Nigel Harris
http://wattsupwiththat.com/2015/06/03/el-nino-strengthens-the-pause-lengthens/#comment-1953587
Neither line is “cherry picked”. The longer one is the trend based on all the data going back as far as possible, the shorter one is the longest period for which a zero trend can be calculated backwards from today.
LM did not cherry pick a start date, in fact he did not pick a start date at all, he calculated a start date. Whether you think that is a valid thing to do is a point of debate. But your comment shows that either:
1. you have not read his post
2. you are too stupid to understand it
3. you are wilfully trying to misrepresent him – which I think that is called lying? At best you can be accused of erecting a straw man.
Nigel Harris,
Start at 1997. That is Dr. Phil Jones’ designated start year. He’s your guy, we’re doing it his way.
That’s how the 18+ years of no warming is established. You can show anything with the WFT database. Just so everyone is on the same page, use Dr. Jones’ start year.
A “pause” is a failure to rise or fall. In order to find a pause, you must work backwards from the present, not forward from some point in the past. Your presentation is nonsensical.
To use an analogy from Tony Heller, for the first 18 years or so of a life, most people grow rapidly, but then they “pause”. If you plot a linear trend for such a person at, say, 30 years of age and use that trendline to reach your conclusion, you would say that they were still growing and that the “pause” was an artifact. A fallacious conclusion.
Had you, instead, plotted the trendline backwards in time, to the point at which it was no longer zero, you would conclude that the person stopped growing around 18 years of age. The correct conclusion.
Climate scientists predicted no pause. However, very few now deny that there is, in fact, such a pause.
Nigel,
you have a good idea, but your process is incomplete. If you remove the 1997to present data as it is a flat trend (which it is) you first need to determine the actual period and rate of warming, First one must remove all flat trends from the data set, then plot the linear trend extrapolation you refer to.
Using RSS Lower Tropospheric mean global temp data one can determine that the trend is nearly flat form the start of RSS data in 1979 to ~ 10/1993, and 1997 to present. The period 10/1993 to 1997 represents the time and rate of warming not associated with a flat trend in the RSS Lower Troposphere Global Mean data.
Yes, Earth’s lower troposphere is far below the extrapolated warming trend.
Please see:
http://www.woodfortrees.org/plot/rss/to:1993.75/plot/rss/to:1993.75/trend/plot/rss/from:1997/to:2015.5/plot/rss/from:1997/trend/plot/rss/from:1993.75/to:1997/trend/plot/rss/from:1993.75/to:1997/plot/rss/scale/detrend:-0.85/offset:-0.31
I take this as a hopeful development. Not too hopeful, I’ve learned not to expect too much from people, but still somewhat encouraging.
Why have average temps settled down closer to the long-term mean over the last 3 years? Is it actual or an artefact of the calculation methods? Could it be that there is some sort of cycle playing out, such that there’s a few years of big swings followed by a few that are more settled?
When you get over the hill, you start picking up speed.
Same gose for warm-stop-cool hills !
g
Who knows? Maybe CO2 is ironing out the extremes. That would be the worst of all possible worlds for alarmism. An unbearable boringness.
In answer to Mr Ward, the sharp ups and downs every 4 years or so are El Niño And La Niña respectively. In between these events, temperature is often stable.
Thank you, Christopher. Always a pleasure…
Carl Mears, ( http://www.remss.com/about/profiles/carl-mears) the senior research scientists mentioned by Monckton in his article made the following statement.
” A similar, but stronger case can be made using surface temperature datasets, which I consider to be more reliable than satellite datasets (they certainly agree with each other better than the various satellite datasets do!) ”
…
This is in the link provide by Monckton. http://www.remss.com/blog/recent-slowing-rise-global-temperatures under the section titled “Measurement Errors”
…
Why does the man responsible for his own product consider surface temperature datasets to be more reliable than those coming from satellites?
He’s probably worried his funding will be terminated.
This x 100.
Richard M,
That’s exactly right. Mears is a wannabe. Just another self-serving rent seeker IMHO. He’s riding the climate gravy train for sure.
“Just another self-serving rent seeker ”
..
He’s a VP of RSS.
…
Tell all of us how working as the senior research scientist for a private company can be “riding the climate gravy train?”
http://www.remss.com/about/profiles/carl-mears
They no longer conform to his bias. Like those people that were sure that aliens were coming on Haleys Comet. Although instead of pushing the date to somewhere in the future, they just off’d themselves to avoid the embarrassment.
He’s a VP of RSS.
When someone in that position labels millions of honest people as “deniers” and “denialsits”, Mears is just protecting his gravy train. That is not professional language, that is attacking people for simply having a different scientific point of view. He calls people names because he does not have the credible science necessary to support his beliefs/rent seeking. I rest my case.
Joel D. Jackson
When was the quote made, and under what circumstances was he claimed to have made the statement, and what satellite and surface station temperature data sets was he comparing? Information and reliability of data sets has changed considerably over time.
September 22, 2014
..
He was discussing measurement errors.
.
Read the link.
That’s an old quote. With the recent calibration update to UAH there is very little variance from RSS. And the UAH agrees with the radio sonde data. What measure are taken to ensure the accuracy of the land surface data? I’m not aware of any.
and RSS adjusts its data with a GCM….
“Why does the man responsible for his own product consider surface temperature datasets to be more reliable than those coming from satellites?”
They measure different things. If you want to know the temperature of the lower troposphere, RSS is best. If you want to know the surface, that’s the place to measure.
The problem, of course, is that are no surface weather stations covering approximately 75% of the Earth’s surface (oceans and uninhabited areas).
Well if want to know the surface, the best place to measure is at the surface, where you measure.
It’s no good for any other place on the surface, except the place you measure.
g
Like at the airport on the tarmac?
OK. So when one takes stations acknowledged to be good (siting, equipage, etc.) they show cooling. When one takes stations acknowledged to be poor for whatever reasons, they show warming. So, why do you want to include the sheep with the goats, and then somehow smear the goat shit over massive areas of the globe where there are no stations at all, then bray like an ass that the globe is warming (“at an unprecedented rate”?). Are you an idiot?
I wonder how many of the skeptics here know that RSS
ADJUSTS ITS DATA…
with…
A GCM !!!
[so prove it instead of blathering about it – Anthony]
Why are anomalies used, again? It seems that if the global temp avg was, say, 13C in 1885 and the same in 2005, the placement of the zero for the anomaly could make 1885 cooler than the later date, even though it clearly would not be.
Mr Monckton, you left out the graph from the latest IPCC report which compared model ocean heat projections vs observations. There is no missing heat in the deep oceans, as the models did not underpredict ocean heat content.
What are the chances the temps have been slowly trending downward since 2000 or so? There are some independent data sets that show this, correct?