Great article Jaime.
I recently came under fire on the Skeptical Science (SkS) website for posting this diagram which showed that the 1970s global cooling scare was not a myth.
The diagram shows that the number of cooling papers greatly outnumbered the warming papers. However, from the amount of fire that I took at SkS, it would appear that the old WWII saying that the flak gets heaviest when you are over the target is correct.
Although the wind power generated last week was quite high, it also illustrates the ups and downs of wind power. I call this phenomenon a “squeeze box” energy system because its power output resembles someone playing an accordion. Let me explain below.
Figure 1 highlights the two largest surges and collapses in wind power output in recent times.
Additionally, the following fluctuations in weekly wind power output in 2025 are evident from Figure 1:
The above surges and collapses in wind power have occurred at nearly weekly intervals in recent times – hence the moniker the “Squeeze Box Phenomenon”. Furthermore, this phenomenon is not a one-off because Figure 1 shows similar surges and collapses in wind power from June to July in 2024.
If coal-fired power stations showed the same erratic “Squeeze Box Phenomenon” as wind farms — frequently going offline and returning at almost weekly intervals — imagine the outcry there would be from the renewables lobby.
Although the wind power generated last week was the highest ever, it was still only the fifth highest capacity factor at 48.9% as shown in Figure 1.
Figure 1: Weekly Capacity Factor showing Highs, Lows & Capacity Factor Degradation
However, what is of greater concern is the very large excursions in the power generated. For example, Figure 2 shows the following large variations in power output:
Figure 2: Wind Power Generated highlighting some Recent Rises & Falls in Output
In the last three weeks alone, wind power rose by 2631 MW, then fell by 2375 MW, only to rise again by 2631 MW. These power excursions are the equivalent of three or four coal-fired power stations suddenly going offline and then coming back online a week later.
Imagine the outcry there would be from the renewables lobby if our ageing coal-fired power stations were performing as badly as wind power.
Anton, there has been a very slight improvement in the recent wind capacity factor.
However, the recent capacity factor (CF) has still reduced from an average CF₁ = 30.6% on 11-Dec-2022 to an average CF₃ = 24.8% on 22-Jun-2025, as shown in Figures 1 and 2.
Figure 1: Recent Nameplate Capacity compared with Power Generated & Reduction Capacity Factor
Figure 2: Reduction in Recent Capacity Factor & Capacity Factor Degradation
This reduction equates to a capacity factor degradation of 2.15% p.a., which would lead to a reduction in capacity factor of 42.0% over a 25-year lifespan, i.e., a reduction in average capacity factor from 28.2% to 16.4%.
This reduction in capacity factor is not included in the levelised cost of electricity estimates produced by CSIRO in its GenCost reports. Consequently, GenCost significantly underestimates the true cost of wind power.
In summary, it would appear that adding new wind turbines does not improve the capacity factor, and I can only suggest that this may be due to one or more of the following reasons:
Cartoon by Josh cartoonsbyjosh.com
Proponents of renewable energy often cite GenCost 2018 to argue that wind power is now less costly than coal-fired power. However, inspection of GenCost 2018 shows that not all of the costs of electricity generation are included in its estimate of the Levelised Cost of Electricity (LCOE). The LCOE presented in GenCost 2018 is effectively the “farm-gate” cost of energy, i.e., the price required by the generator to break even at its site of generation.
In a similar manner to the “farm-gate” cost of milk, the GenCost 2108 LCOE does not represent the final price to the consumer, since it fails to include the cost of transportation (transmission lines). GenCost 2018 also does not include the cost of power plant degradation and demolition, etc. These (omitted) costs are not insignificant as explained below:
Including all of the items listed in (1) to (4) above more than doubles the GenCost 2018 LCOE for wind power as shown in Figure 1.
These costs should be included in the GenCost 2018 LCOE calculation if an accurate comparison with other sources of power is to be made.
Figure 1: Comparison of GenCost 2018 LCOE’s with Real-world LCOE (i.e., when the Cost of Transmission Lines, Demolition, etc., are Included), Source: McFarlane (2019)
It is evident from Figure 1(b) that:
It should be emphasised that the real-world LCOE values for standalone wind presented in Figure 1(b) are verified by Stock et al (2016), which presents reverse auction values for wind power in ACT that are in the $73 to $92 per MWh range. This range compares well with the $79 to $95 per MWh range for the real-world values presented in Figure 1(b) above, which gives confidence in the accuracy of the real-world LCOE estimates presented in this review.
Furthermore, the conclusion from Figure 1(b) that wind power is more expensive than conventional generation is corroborated by the fact that real-world experience shows that those countries with the highest generation from renewables also have the highest electricity costs as shown in Figure 2.
Figure 2: Cost of Residential Electricity Compared with Installed Capacity of Renewables (after MacDonald, 2018)
It is evident from Figure 2 that those countries with the highest penetration of renewable electricity (Germany and Denmark) have the highest electricity costs, which leads to the obvious conclusion that renewables are more costly than conventional generation.
In summary, it is shown that the levelised cost of electricity generated by wind power is significantly more expensive than coal-fired power (by a factor of 2 to 3).
Therefore, it is recommended that any new generation capacity in Australia should include coal-fired power, not only because it is cheaper than wind but also because it is more reliable and provides power on an as-needed basis.
References
Brailsford et al, 2018, Powering Progress: States Renewable Energy Race, Louis Brailsford, Andrew Stock, Greg Bourne and Petra Stock, published by Climate Council of Australia Ltd 2018
https://www.climatecouncil.org.au/wp-content/uploads/2018/10/States-Renewable-Energy-Report.pdf
Coultate & Hornemann, 2018, Why wind-turbine gearboxes fail to hit the 20-year mark, The Renewable Energy Handbook (Wind), 2018
GenCost 2018, Graham, P.W., Hayward, J, Foster, J., Story and Havas, L., 2018, GenCost 2018 CSIRO, Australia
Hughes, 2012, The Performance of Wind Farms in the United Kingdom and Denmark, Published by the Renewable Energy Foundation
https://www.ref.org.uk/attachments/article/280/ref.hughes.19.12.12.pdf
MacDonald, 2018, A Look at Impacts of Wind and Solar Electric Generation on Electricity Price, Energy Performance Measurement Institute (EPMI)
McFarlane, 2019, Levelised Cost of Electricity: A Comparison between Wind and Coal Power
https://1drv.ms/b/s!AlUVozCtzbL2h6IPrDEj_I1UF4qs1g
Rutovitz et al, 2017, Rutovitz, J., McIntosh, B., Morris, T. and Nagrath, K. (2017) Wind Power in Australia: Quick Facts. Prepared for the Climate Media Centre and Australian Wind Alliance by the Institute for Sustainable Futures, UTS
Click to access 2017_Wind_Power_in_Australia_ISF.pdf
Staffell & Green, 2014, How does wind farm performance decline with age? Renewable Energy
https://www.sciencedirect.com/science/article/pii/S0960148113005727
Stock et al, 2016, Territory trailblazer: How the ACT became the renewable capital of Australia, published by the Climate Council of Australia Limited
An excellent and concise rebuttal of BBC propaganda.
This is a repost from my article in WUWT. Figures 1 and 2 have been added to the post because they were missed out in WUWT.
Whether or not there was a global cooling consensus in the 1970s is important in climate science because, if there were a cooling consensus (which subsequently proved to be wrong) then it would question the legitimacy of consensus in science. In particular, the validity of the 97% consensus on global warming alleged by Cook et al (2013) would be implausible. That is, if consensus climate scientists were wrong in the 1970s then they could be wrong now.
It is not the purpose of this review to question the rights or wrongs of the methodology of the 97% consensus. For-and-against arguments are presented in several peer-reviewed papers and non-peer-reviewed weblogs. The purpose of this review is to establish if there were a consensus in the 1970s and, if so, was this consensus cooling or warming?
In their 2008 paper, The Myth of the 1970s Global Cooling Scientific Consensus, Peterson, Connolley and Fleck (hereinafter PCF-08) state that, “There was no scientific consensus in the 1970s that the Earth was headed into an imminent ice age. Indeed, the possibility of anthropogenic warming dominated the peer-reviewed literature even then.” This conclusion intrigued me because, when I was growing up in the early 1970s, it was my perception that global cooling dominated the climate narrative. My interest was further piqued by allegations of “cover-up” and “skulduggery” in 2016 in NoTricksZone and Breitbart.
Therefore, I present a review that examines the accuracy of the PCF-08 claim that 1970s global cooling consensus was a myth. This review concentrates on the results from the data in the peer-reviewed climate science literature published in the 1970s, i.e., using similar sources to those used by PCF-08.
The case for the 1970s cooling consensus being a myth relies solely on PCF-08. They state that,”…the following pervasive myth arose: there was a consensus among climate scientists of the 1970s that either global cooling or a full-fledged ice age was imminent…A review of the climate science literature from 1965 to 1979 shows this myth to be false. The myth’s basis lies in a selective misreading of the texts both by some members of the media at the time and by some observers today. In fact, emphasis on greenhouse warming dominated the scientific literature even then.” [Emphasis added].
PCF-08 reached their conclusion by conducting a literature review of the electronic archives of the American Meteorological Society, Nature and the scholarly journal archive Journal Storage (JSTOR). The search period was from 1965 to 1979 and the search terms used were “global warming”, “global cooling” and a variety of “other less directly relevant” search terms. Additionally, PCF-08 evaluated references mentioned in the searched papers and references mentioned in various history-of-science documents.
In total, PCF-08 reviewed 71 papers and their survey found 7 coolingpapers, 20 neutral papers and 44 warming papers. Their results are shown in their Figure 1.
A cursory examination of Figure 1 indicates that there is a 62% warming consensus if we use all the data and this consensus increases to 86% pro-warming, if we were to ignore the neutral papers (as was done in the 97% consensus). Therefore, the Figure 1 data seems to prove the contention in PCF-08 that 1970s global cooling was a myth.
However, I find it difficult to believe that the 1970s media “selectively misread” the scientific consensus of the day and promoted a non-existent cooling scare. Therefore, I present an alternative to the PCF-08 analysis below.
In this review, I use an identical methodology to PCF-08, i.e., I examine peer-reviewed scientific journals. Non-peer-reviewed newspaper and magazine articles are not used. A significantly larger number of papers are presented in the current review than were used in PCF-08.
The PCF-08 database of articles is used but this is extended to examine more literature. Note that examining all of the scientific literature would have been beyond my resources. However, my literature survey was facilitated by the work of Kenneth Richard in 2016 (hereinafter, KR-16) at NoTricksZone, in which he has assembled a large database of sceptical peer-reviewed literature.
Some people may wish to ignore the KR-16 database as being from a so-called “climate denier” blog. However, almost all of the papers in KR-16 are from peer-reviewed literature and consequently it is a valid database. It is also worth noting that 16 of the papers used in the KR-16 database are also contained in the PCF-08 database.
The combined PCF-08 and KR-16 databases form the benchmark database for the current review. It was intended to significantly extend the benchmark database but, on searching the relevant journals, only 2 additional papers were found and these were added to form the database for this review.
It should be noted that KR-16 states that there were over 285 cooling papers. However, many of these papers were deleted from the current review as not being relevant. For example, several papers were either outside the 1965-1979 reference period or they emphasise the minor role of CO2 but do not consider climate trends.
I agree with PCF-08 that no literature search can be 100% complete. I also agree that a literature search offers a reasonable test of the hypothesis that there was a scientific consensus in the 1970s. I reiterate that the resulting database used in this review is significantly larger than that used by PCF-08 and consequently it should offer a more accurate test of the scientific consensus in the 1970s.
Most of the papers in the review database acknowledge the global cooling from the 1940s to the 1970s (typically 0.3 °C global cooling). Therefore, deciding between cooling, neutral or warming was relatively straightforward in most cases; namely did the paper expect the climate regime during the 1940s-1960s period to either to continue from the date that the paper was published, or did it expect a different climate regime in the medium-to-long-term?
Notwithstanding the straightforward test described above, some of the papers make contradictory statements and are thus more difficult to classify. Consequently, their classification can include an element of subjectivity. Fortunately, there are very few papers in this category and consequently an inappropriate classification does not materially affect the overall results.
The test criteria are summarised in Table 1.
| Classification | Test of Classification of Papers | Typical Examples from Papers |
| Cooling | Cooling expected to either continue or initiate | Kukla & Kukla (1972) “…the prognosis is for a long-lasting global cooling more severe than any experienced hitherto by civilized mankind.” |
| Neutral | Either non-committal on future climate change or expects warming or cooling to be equally possible | Sellers (1969) “The major conclusions that removing the arctic ice cap would have less effect on climate than previously suggested, that a decrease of the solar constant by 2-5% would be sufficient, to initiate another ice age, and that man’s increasing industrial activities may eventually lead to the elimination of the ice caps and to a climate about 14C warmer than today…” |
| Warming | Warming expected to either continue or initiate | Manabe & Weatherald (1967) “According to our estimate, a doubling of the CO, content in the atmosphere has the effect of raising the temperature of the atmosphere (whose relative humidity is fixed) by about 2C.” |
The search terms “global cooling” and “global warming” used by PCF-08 are used in this review but they have been expanded to include “cool”, “warm”, “aerosol” and “ice-age” because these, more general terms, return a larger number of relevant papers. Additional search terms such as “deterioration”, “detrimental” and “severe” have also been included. These would fit into the PCF-08 category of “other less directly relevant” search terms.
Several of the papers in the database are concerned about the effects of aerosol cooling and they state that this effect dominates the effect of the newly emerging CO2-warming science. Indeed, a few papers warn of CO2cooling.
However, PCF-08 do not include any papers that refer to aerosol cooling by a future fleet of supersonic aircraft (SST’s) but several papers in the 1970s assumed an SST fleet of 500 aircraft. This seems incongruous now but, to show that this number of aircraft is not unrealistic; Emirates Airlines currently have a fleet of 244 (non-supersonic) aircraft and 262 more on order. Therefore, I have included papers that refer to the effects of aerosols from supersonic aircraft and other human activities. Of course, supersonic travel was killed-off by the mid-1970s oil crisis.
Furthermore, a number of PCF-08 and KR-16 papers were re-classified (from cooling, neutral or warming) as summarised Table 2.
| Reference | Original | Amended |
| Sellers (1969) | Warming | Neutral |
| Benton (1970) | Warming | Neutral |
| Rasool and Schneider (1972) | Neutral | Cooling |
| Machta (1972) | Warming | Neutral |
| FCSTICAS (1974) | Warming | Cooling |
| National Academy of Sciences (1975) | Neutral | Cooling |
| Thompson, 1975 | Warming | Neutral |
| Shaw (1976) | Neutral | Cooling |
| Bryson and Dittberner (1977) | Neutral | Cooling |
| Barrett, 1978 | Neutral | Cooling |
| Ohring and Adler (1978) | Warming | Neutral |
| Stuiver (1978) | Warming | Neutral |
| Sagan et al. (1979) | Neutral | Cooling |
| Choudhury and Kukla, 1979 | Neutral | Cooling |
| a. Amended Classifications to PCF-08 | ||
| Reference | Original | Amended |
| Budyko, 1969 | Cooling | Warming |
| Benton (1970) | Cooling | Neutral |
| Mitchell, 1970 | Cooling | Neutral |
| Mitchell (1971) | Cooling | Warming |
| Richmond, 1972 | Cooling | Neutral |
| Denton and Karlén, 1973 | Cooling | Warming |
| Schneider and Dickinson, 1974 | Cooling | Neutral |
| Moran, 1974 | Cooling | Neutral |
| Ellsaesser, 1975 | Cooling | Neutral |
| Thompson, 1975 | Cooling | Neutral |
| Gates, 1976 | Cooling | Neutral |
| Zirin et al., 1976 | Cooling | Neutral |
| Bach, 1976 | Cooling | Warming |
| Norwine, 1977 | Cooling | Warming |
| Paterson, 1977 | Cooling | Neutral |
| Schneider, 1978 | Cooling | Warming |
| b. Amended Classifications to KR-16 |
Two examples of the amendments to the classification of the papers in the database are explained below:
The review database contains a total 190 relevant papers, which is 2.7 times the size of the PCF-08 database. Of the 190 papers in the review database, 162 full papers/books and 25 abstracts were reviewed (abstracts were used when the full papers were either pay-walled or could not be sourced). Furthermore, 4 warming papers from PCF-08 were not reviewed because they could not be sourced. Therefore, the PCF-08 classification was used for these papers in this review.
The results from the review are summarised in Figure 2.
It is evident from Figure 2 that, for the 1965-1979 reference period used by PCF-08, the number of cooling papers significantly outnumbers the number of warming papers. It is also apparent that there are two distinct sub-periods contained within the reference period, namely:
The following observations are also worth noting from Figure 2 for the 1965-1979 reference period:
Although not presented in Figure 2, it is worth noting that 30 papers refer to the possibility of a New Ice-Age or the return to the “Little Ace-Age” (although they sometimes they used the term “Climate Catastrophic Cooling”). Timescales for the New Ice Age vary from a few decades, through a century or two, to several millennia. The 30 “New Ice Age” papers are not insignificant when compared with the 46 warming papers.
A review of the climate science literature of the 1965-1979 period is presented and it is shown that there was an overwhelming scientific consensus for climate cooling (typically, 65% for the whole period) but greatly outnumbering the warming papers by 3-to-1 during the 1968-1976 period, when there were 63 cooling papers (74%) compared with 22 warming (26%).
It is evident that the conclusion of the PCF-08 paper, The Myth of the 1970s Global Cooling Scientific Consensus, is incorrect. The current review shows the opposite conclusion to be more accurate. Namely, the 1970s global cooling consensus was not a myth – the overwhelming scientific consensus was for climate cooling.
It appears that the PCF-08 authors have committed the transgression of which they accuse others; namely, “selectively misreading the texts” of the climate science literature from 1965 to 1979. The PCF-08 authors appear to have done this by neglecting the large number of peer-reviewed papers that were pro-cooling.
I find it very surprising that PCF-08 only uncovered 7 cooling papers and did not uncover the 86 cooling papers in major scientific journals, such as, Journal of American Meteorological Society, Nature, Science, Quaternary Research and similar scientific papers that they reviewed. For example, PCF-08 only found 1 paper in Quaternary Research, namely the warming paper by Mitchell (1976), however, this review found 19 additional papers in that journal, comprising 15 cooling, 3 neutral and 1 warming.
I can only suggest that the authors of PCF-08 concentrated on finding warming papers instead of conducting the impartial “rigorous literature review” that they profess.
If the current climate science debate were more neutral, the PCF-08 paper would either be withdrawn or subjected to a detailed corrigendum to correct its obvious inaccuracies.
I reiterate that no literature survey can be 100% complete. Therefore, if you uncover additional references then please send them to me in the comments. It would make this review much better if we could significantly increase the number of relevant references.
Additionally, if you disagree with the classification of some of the references then please let me know why you disagree and I will consider appropriate amendments. Your comments on classification would certainly increase the veracity of the review by providing an independent assessment of my classifications.
The references used in this review and their classification are included in the spreadsheet here:
References-Global Cooling Consensus.xlsx
Revision 02
29-Dec-2022: Minor errors corrected by Angus McFarlane.
Repost from Watts up with That here: WUWT
Some typos in the text and diagrams have been corrected
Introduction
In this article I pose the following questions:
The reasons for asking these questions are that climate establishment have tried to sideline the MWP as a purely local North Atlantic event. They also frequently state that current temperatures are the highest ever.
I attempt to answer these questions below.
Mapping Project for the Medieval Warm Period
I use the mapping project for the Medieval Warm Period (MWP) developed by Dr Sebastian Luening and Fritz Vahrenholt to establish the global extent of the MWP. This project is a considerable undertaking and I commend the authors for their work.
Luening states on Research Gate that,
“The project aims to identify, capture and interpret all published studies about the Medieval Climate Anomaly (Medieval Warm Period) on a worldwide scale. The data is visualized through a freely accessible online map: http://t1p.de/mwp.”
I show a screenshot from the project in Figure 1 but I recommend that you use the online version at http://t1p.de/mwp because it contains a wealth of data, including abstracts and links to the individual papers.
(Note – The t1p.de/mwp URL given may or may not be reachable by some viewers as it’s one of those mangled “URL shorteners” that may or may not work. It does not work for me. The author claims the URL is valid, and offered no alternate, I independently found this link to a Google maps document which might work better for some readers – Anthony)
Figure 1: Screenshot of MWP Mapping Project (Source: Luening http://t1p.de/mwp downloaded 27-Dec-2016)
A cursory inspection of Figure 1 indicates that there are a large number of warm study locations dispersed throughout the world. However, to determine the global numbers for the Warm-Cold-Neutral-Dry-Wet studies, I downloaded the mapped data for the 934 studies that were available on 30 December 2016 and these are summarised in Figure 2.
Figure 2: Results from MWP Mapping Project (Source: Luening http://t1p.de/mwp downloaded 30-Dec-2016)
The following observations are evident from Figure 2;
a. The number of Warm studies (497) greatly exceed the other studies, namely, 53% of the studies when temperature and hydroclimate data is used and 88% when temperature only data is used.
b. The number of Cold studies (18) is very small, at 2-3% of the overall studies.
c. The number of Neutral studies (53) is comparatively low, at 6-9% of the overall studies.
d. The number of studies that report only Hydroclimatic data is not insignificant. The number of Dry studies (184) and the number of Wet studies (182) are 20% and 19% of the overall studies respectively.
In summary, the overwhelming evidence from the Luening MWP Mapping Project to date is that the MWP was globally warm but it is not immediately obvious what the definition of warm is?
Descriptions of warm or cold are given the individual studies. For example, Kuhnert & Mulitza (2011: GeoB 9501) (extracted from Luening) states that the,
“Medieval Warm Period 800-1200 AD was about 1.1°C warmer (50 years mean) than subsequent Little Ice Age.”
Now, whilst this description is useful, it does not allow us to compare MWP temperatures with modern warming. Therefore, I compare modern temperatures with the MWP below.
How Warm was the MWP?
Several of the references in the Luening MWP Mapping project are also so referenced in Ljungqvist (2010), therefore the latter may be used to estimate the temperature in the Northern Hemisphere (NH) during the MWP.
Note that I have used the Ljungqvist (2010) NH paper because I already had the data available on my laptop. However, readers could carry out a similar exercise by using their preferred study to derive appropriate temperatures for global or hemispherical temperatures for comparison with the present day.
Ljungqvist published his data along with his paper (other climate scientists should do the same) and Figure 3 shows my version of the Ljungqvist chart (reproduced using his data). I have also annotated the chart to show previous warm and cold periods.
Figure 3: Estimate of Extra-tropical Northern Hemisphere (90–30°N) Decadal Mean Temperature Variations (after Ljungqvist, 2010)
a. All values are decadal mean values.
b. Proxy temperatures are shown in the thick black line and are relative to the 1961–1990 mean instrumental temperature from the variance adjusted CRUTEM3+HadSST2 90–30°N record.
c. Two standard deviation error bars are shown in light grey shading.
d. CRUTEM3+HadSST2 instrumental temperatures are shown in the red line.
The following observations are evident from Figure 3:
a. The Medieval Warm Period (MWP) temperature is warmer than the Modern Warm Period proxy temperature – at no time do the modern proxies exceed the MWP proxies.
b. The recent instrumental temperature is warmer than the Medieval Warm Period temperature.
c. The MWP is obviously preindustrial and it would be logical to use the MWP temperature as preindustrial temperature instead of the Little Ice Age (LIA) favoured by the climate establishment.
Observations (a) and (b) above are based on Ljungqvist’s comments. He states that [emphasis added],
“…the Medieval Warm Period, from the ninth to the thirteenth centuries, seem to have equalled or exceeded the AD 1961-1990 mean temperature level in the extra-tropical Northern Hemisphere.”
He also adds the following words of caution [emphasis added],
“Since AD 1990, though, average temperatures in the extra-tropical Northern Hemisphere exceed those of any other warm decades the last two millennia, even the peak of the Medieval Warm Period, if we look at the instrumental temperature data spliced to the proxy reconstruction. However, this sharp rise in temperature compared to the magnitude of warmth in previous warm periods should be cautiously interpreted since it is not visible in the proxy reconstruction itself.”
Regarding Ljungqvist’s note of caution and item (b) above, comparing instrumental temperatures with those derived from proxies is not an, “apples for apples” comparison because proxy temperatures are damped (flattened out) whilst thermometers respond very quickly to changes in temperature.
Ljungqvist describes the dampening proxy temperatures thus [emphasis added],
“The dating uncertainty of proxy records very likely results in “flattening out” the values from the same climate event over several hundred years and thus in fact acts as a lowpass filter that makes us unable to capture the true magnitude of the cold and warm periods…What we then actually get is an average of the temperature over one or two centuries.”
However, the flattening out of proxy records is not the only problem when comparing proxies with instrumental temperatures – there is also the “divergence problem.” We examine this for the Ljungqvist’s 1850-1989 calibration period in Figure 4.
Figure 4: Comparison of Proxy & Instrumental Decadal Mean Temperature Variations (after Ljungqvist, 2010)
The decadal correlation (r = 0.95, r² = 0.90) between proxy and instrumental temperature is very high during the calibration period AD 1850-1989. However, note that the 1990-1999 instrumental peak is not used in the calibration. Probably because Figure 4 shows that the instrumental peak temperature is 0.39°C for 1990-1999, which diverges from the proxy temperature of 0.06°C – a difference of 0.33°C.
This divergence is outside the 2 standard deviation error bars of ±0.12°C reported by Ljungqvist and it illustrates the divergence problem in a nutshell – proxies do not follow the instrumental record for recent high temperatures. The reason for this divergence is that the proxy response is probably nonlinear instead of the linear response that is assumed in all climate reconstructions to date.
Ljungqvist explains the nonlinearity [emphasis added],
“One circumstance that possibly has led to an underestimation of the true variability is that we must presuppose a linear response between temperature and proxy. If this response is nonlinear in nature, which is often likely the case, our interpretations necessarily become flawed. This is something that may result in an underestimation of the amplitude of the variability that falls outside therange of temperatures in the calibration period.”
As a structural engineer, I agree with Ljungqvist that nonlinearity is often likely to be the case for proxies. Most natural materials, e.g., timber, rock, etc., exhibit linear-nonlinear behaviour. However, this concept is difficult to explain in words, therefore, I explain the concept diagrammatically in Figure 5.
Figure 5: Indicative Nonlinear Response for a Temperature Proxy
For clarity, I show the positive part of the temperature response in Figure 5 but it should be noted that there would be a similar negative response. I now explain Figure 5 as follows:
a. Line OAB represents the linear proxy response to temperature currently used in reconstructions. Parameter P1 yields a temperature T1 (via point A) and the response increases linearly so that parameter P2 indicates a higher temperature T2 (via point B).
b. Line OACD represents the indicative nonlinear proxy response to temperature. Parameter P1 is in the linear portion of the curve and therefore results in the same temperature T1 as that in item (a) above.
c. In addition to item (b), parameter P1 at point C is in the nonlinear portion of the curve, which would result in the temperature T2, which is significantly higher than the value of T1 obtained from the linear response via point A.
In summary, a nonlinear proxy-temperature response can result in two temperature values for a single proxy value, which could be problematic in deciding which temperature result to use.
However, for modern temperatures, the nonlinear response of the proxy can be calibrated against the instrumental record. For example, if the temperature results in Figure 4 were for a single proxy then the following procedure could be used:
a. The nonlinear curve would be calibrated so that temperature T1 = 0.08°C would be in the linear portion of the curve in Figure 5.
b. The temperature T2 = 0.39 °C would be calibrated to be in the nonlinear portion of the curve in Figure 5.
Note that the linear response used in Figure 4 shows T2 = 0.06°C but the nonlinear response procedure above allows the calibration T2 = 0.39°C. This type of nonlinear calibration would mean that historical temperatures would be higher than those currently estimated by using a linear proxy-temperature response.
Furthermore, the calibration in modern times is relatively straightforward because we can compare proxies with instrumental temperatures to determine which temperature is correct, T1 or T2. However, historical temperatures are more problematic because we do not have instrumental records for several thousands of years to determine the correct temperature, T1 or T2. Nevertheless, we can estimate the correct temperature by deploying a similar methodology to that used by earthquake engineers as explained below.
Earthquake engineers routinely design structures for 1-in-500 year seismic events and for special structure (e.g., nuclear installations) 1-in-5,000 year events. However, they have only had the seismograph to measure the strength of earthquakes from 1935, when it was invented by Charles Richter. Earthquake engineers solve this short instrumental record dilemma by investigating historical descriptions of seismic events.
For example, the historical record for an earthquake may include a description such as, “The earth boiled.” This literal description does not mean that the earth actually reached boiling. It means that the groundwater in the soil bubbled to the surface – a process known as liquefaction of the soil. Earthquake engineers can then use this description to estimate the amount of shaking that would cause liquefaction and thus estimate the strength of the earthquake at that location.
In climate science, the temperature, T1 or T2, could also be estimated from historical descriptions by using changes in vegetation, human habitation, etc. For example, if our proxy were in Greenland then the following outcomes are possible:
a. If the land were in permafrost at the date of the proxy then the lower temperature T1 would be used.
b. It the land was being cultivated by Vikings at the date of the proxy (i.e., no permafrost) then the higher temperature T2 would be used.
The above nonlinear methodology would obviously require more work by paleo scientists when compared with the current linear calibration methods but this work is no more than is routinely carried out by earthquake engineers.
Additionally, up-to-date proxies for the post-2000 period would be useful to determine if the divergence between proxies and instrumental temperatures has increased. The proxies would also enable a more accurate nonlinear proxy-temperature calibration, say, point D in Figure 5. Strangely, there seems to be a reluctance in the climate establishment to publish up to date proxies.
Using a nonlinear proxy-temperature response would result in historical high temperatures being calculated to be higher and historical low temperatures being calculated to be lower.
Conclusions
A review of the global extent of the MWP is presented and the following conclusions are offered:
Until there is a good correlation between instrumental temperatures and proxies, no reputable scientist can definitely state that current temperatures are the highest ever.
Afterword
Regarding the 2°C limit proposed by the climate establishment, the following phrase (based on the facts presented in this article) does not sound nearly as alarming as is currently promulgated in the media:
“We know that the preindustrial MPW temperatures exceeded those of the LIA by ≈ 1°C without CO2 but we also think that a similar temperature rise from the LIA to 1980-1989 was caused by CO2. Therefore, we think that we need to limit CO2 emissions to stop a further (dangerous) 1°C rise. We think.”
I think that there is too much thinking going on and not enough real climate science.
A good start would be to use nonlinear proxy-temperature responses to establish accurate historical high and low temperatures.
