Global temperature update: the Pause is now 18 years 2 months

By Christopher Monckton of Brenchley

Since December 1996 there has been no global warming at all (Fig. 1). This month’s RSS temperature shows a sharp uptick to warmer worldwide weather than for two years, shortening the period without warming by a month to 18 years 2 months.

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 2 months since December 1996.

The hiatus period of 18 years 2 months, or 218 months, is the farthest back one can go in the RSS satellite temperature record and still show a sub-zero trend.

As papers continue to appear in the literature claiming that the climate models were right all along except that they were wrong, the widening of the divergence between excitable prediction and unalarming reality continues (Fig. 2).

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), January 1990 to January 2015 (orange region and red trend line), vs. observed anomalies (dark blue) and trend (bright blue) at less than 1.4 K/century equivalent, taken as the mean of the RSS and UAH satellite monthly mean lower-troposphere temperature anomalies.

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 0.34 Cº, equivalent to just 1.4 Cº/century, or a little below half of the central estimate of 0.70 Cº, equivalent to 2.8 Cº/century, in IPCC (1990). The outturn is well below even the least estimate.

Remarkably, even the IPCC’s latest and much reduced near-term global-warming projections are also excessive (Fig. 3).

Figure 3. Predicted temperature change, January 2005 to January 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 zero real-world trend (bright blue), taken as the average of the RSS and UAH satellite lower-troposphere temperature anomalies.

In 1990, the IPCC’s central estimate of near-term warming was higher by two-thirds than it is today. Then it was 2.8 C/century equivalent. Now it is just 1.7 Cº equivalent – and, as Fig. 3 shows, even that is proving to be a substantial exaggeration.

On the RSS satellite data, there has been no global warming statistically distinguishable from zero for more than 26 years. None of the models predicted that, in effect, there would be no global warming for a quarter of a century.

Key facts about global temperature

Ø The RSS satellite dataset shows no global warming at all for 218 months from December 1996 to January 2014 – more than half the 432-month satellite record.

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 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 fastest warming rate lasting ten 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 global warming trend since 1990, when the IPCC wrote its first report, is equivalent to below 1.4 Cº per century – half of what the IPCC had then predicted.

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 ten years that has been measured since 1950.

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

Ø From September 2001 to November 2014, the warming trend on the mean of the 5 global-temperature datasets is nil. No warming for 13 years 3 months.

Ø Recent extreme weather cannot be blamed on global warming, because there has not been any global warming. 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 RSS dataset is arguably less unreliable than other datasets in that it shows the 1998 Great El Niño more clearly than all other datasets (though UAH runs it close). The Great el Niño, like its two predecessors in the past 300 years, caused widespread global coral bleaching, providing an independent verification that RSS is better able to capture such fluctuations without artificially filtering them out than other datasets. Besides, there is in practice little statistical difference between the RSS and other datasets over the 18-year period of the Great Pause.

Terrestrial temperatures are measured by thermometers. Thermometers correctly sited in rural areas away from manmade heat sources show warming rates appreciably 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, takes their mean 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 via two well-established and functionally identical equations that are compared with one another to ensure no discrepancy between them. 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.

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. 4:

Figure 4. 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 largely 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. However, over the entire length of the RSS and UAH series since 1979, the trends on the mean of the terrestrial datasets and on the mean of the satellite datasets are near-identical. Indeed, the UK Met Office 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.

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.

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.

Yet 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 that are 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 hiatus in global warming is correct (and it is merely one among dozens that have been offered), then 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.

Besides, the 3500 automated Argo bathythermograph buoys have a resolution equivalent to taking a single temperature and salinity profile in Lake Superior less than once a year: and before Argo came onstream in the middle of the last decade the resolution of oceanic temperature measurements was considerably poorer even than that, especially in the abyssal strata.

Finally, though the ARGO buoys measure ocean temperature change directly, before publication NOAA craftily convert the temperature change into zettajoules of ocean heat content change, which make the change seem larger. Converting the ocean heat content change back to temperature change reveals just how little ocean warming is occurring.

Is some underlying rate of global warming captured by the ocean temperature measurements? Well, the terrifying-sounding heat content change of 260 ZJ from 1970 to 2014 is equivalent to just 0.2 K/century of global warming.

Figure 5. Ocean heat content change, 1957-2013, in Zettajoules from NODC Ocean Climate Lab: http://www.nodc.noaa.gov/OC5/3M_HEAT_CONTENT. The heat content has been converted back to the ocean temperature changes in fractions of a Kelvin that were originally measured. NOAA’s conversion of the minuscule temperature change 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.

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