From Untitled (call me Stephen)

How accurate are our historical temperature records?

In 2021 Bugatti released their Chiron Super Sport 300+. The “300+” is because it is the first road-legal car that has reached speeds above 300mph, although production models are electronically limited to 271mph.

This car can accelerate to its top speed of 490km/h in around 40 seconds and can come to a complete stop from that speed in less than 15 seconds.

The Dublin Port tunnel was opened on 20^th December 2006. Technically there are two 4.5km long tunnels, one for each direction of traffic.

The walls of the tunnel are hard, unlike surface level motorways which have flexible safety barriers. Crashing into the walls at high speeds would be not only fatal for those involved in the crash but could also potentially damage the tunnel’s structural integrity.

To encourage people to respect the 80km/h speed limit, average speed cameras have been installed. An average speed camera system consists of at least two cameras (but ideally more) distributed over the region where the speed limit is being enforced.

The cheap option would be two cameras on each tunnel, one at the start and one at the end. If the timestamp of your car passing the second camera is less than 202.5 seconds after you passed the first camera then you have travelled the 4.5km at an average speed faster than 80km/h and a speeding ticket and penalty points for your license will follow.

The better option is to have more than two cameras distributed along the tunnel to prevent any reckless and idiotic Chiron Super Sport 300+ driver from attempting the following…

• Enter the tunnel at a rolling 80km/h start
• Put your foot down and reach the top speed of 490km/h after about 33.5s
• Hold top speed for about 1.5s
• Break hard to 30km/h over 3.5s
• Keep to 30km/h for the remaining 164s of the journey

Because that takes exactly 202.5 seconds, if the Dublin Port tunnel only has two cameras installed per tunnel, the average speed is 80km/h even though the car’s speed varied between 30km/h and 490hm/h!

“Stephen, what exactly have the Bugatti Chiron Super Sport 300+ and the Dublin Port tunnel got to do with comparing past and present temperatures” I hear you ask. Please stick with me. I hope that it will make sense by the time you reach the end.

The thermometer is a relatively recent invention. While Galileo was messing about with thermoscopes as early as 1603, it would take until 1724 when Daniel Gabriel Fahrenheit proposed his thermometer scale before the idea of standardized temperature scales would take off. That René-Antoine Ferchault de Réaumur and Anders Celsius proposed different and competing standards in 1732 and 1742 should be unsurprising to anyone familiar with how standards work.

Unfortunately for Réaumur, his choice of 80 degrees between freezing and boiling points of water didn’t catch on.

Most of the world now uses the Celsius scale, though with the 0°C and 100°C points reversed from Anders’ original proposal, with only the United States, the Bahamas, the Cayman Islands, Palau, the Federated States of Micronesia and the Marshall Islands using Fahrenheit.

Our earliest actual temperature measurements, especially those from before 1732, rely on people either having later cross-calibrated the thermometers they originally used with other ones, or having documented their own choice of reference.

It also took a while for people to figure out how to measure the temperature. Most of the early measurements are actually indoor measurements from unheated rooms recorded once a day. Eventually it was figured out that measuring the outdoor temperature required the thermometer to actually be outside and shaded from the sun.

It would be 1864 before Thomas Stevenson would propose a standardised instrument shelter and after comparing with other shelters his final Stevenson screen design was published in 1884.

While we may laugh now at people who measured the outdoor temperature with a thermometer located in an indoor unheated room, because the room has a large heat capacity, that is it takes a while to both heat up and cool down, taking one indoor measurement a day is actually not that bad a way to measure the average outdoor temperature.

When you move your thermometer to a well-ventilated outdoor shelter such as a Stevenson screen, the thermometer will change much more rapidly. If you want to measure the average temperature you will need to take multiple readings throughout the day and night.

In 1780, James Six invented a thermometer that keeps track of the maximum and minimum temperature since it was reset, though as it relied on mercury to move the markers, it can have issues in cold temperatures. By 1790 Daniel Rutherford had developed designs for separate minimum and maximum thermometers that used alcohol and mercury respectively and allowed for greater accuracy of both readings.

It would take until the 1870’s before minimum and maximum thermometers would be widely used to track the variability of temperature. For example the Central England Temperature history, the longest temperature record, is based on observations for a variety of hours prior to 1877 with daily minimum and maximum temperatures used thereafter.

Meteorologists use the daily minimum and maximum temperatures to estimate the daily average temperature by just averaging the minimum and maximum. This is called T_axn and the formula is: T_axn=(T_max+T_min)/2.

Do not get me wrong, if all you have is the daily minimum and maximum temperatures, averaging the two is the best guess you can make, but it is not the average daily temperature called T_avg which you get from measuring the temperature ideally more than 20 times evenly spaced throughout the 24 hour period and averaging all of those results.

Here’s where the Bugatti Chiron Super Sport 300+ and the Dublin Port tunnel come back in. If I told you the top speed of the Bugatti in the tunnel was 490km/h and it never went slower than 30km/h, if we used the Meteorologists’ algorithm we would conclude that it was travelling on average at (490+30)/2=260km/h. Yet we know from earlier that it is possible for those two limits to result in an average speed of 80km/h.

If you work it out, keeping the minimum and maximum speeds in the tunnel at 30km/h and 490km/h it is possible to get an average speed anywhere between 71km/h and 332km/h. While the Meteorologists’ 260km/h average speed is in that range, the range is quite wide.

To give another example of how the Meteorologists’ method can give an estimate that is quite a bit off, according to the Irish Central Statistics Office, in 2022 the top 1% of workers earned at least €3,867 per week. In contrast the bottom 1% of workers earned at most €92 per week. The mean weekly earnings were €856 per week and only 27% of workers earned at least that with the median weekly earnings being €671.

If we take the average of €3,867 and €92 that’s €1,980 per week. Less than 6% of earners received at least €1,980 per week which puts the Meteorologists’ average quite a bit off for estimating earnings or the average speed of a Bugatti through the port tunnel.

In the 1970’s, with the advent of cheap computers, it became possible to automate temperature measurement. A computer has no choice, if we tell it to measure the temperature every hour or every 5 minutes, rain or shine, sleet or snow, the measurement will be recorded. As most of the weather stations transitioned to automated measurement, mostly in the period 1990-2010, we are now able to measure the true average temperature, T_avg.

Valentia Observatory is 1km west of Cahirciveen, Co Kerry and a weather station has been operated in the area, with some temperature records for 1850-51 and continuous daily min-max records since mid-January 1872. The historical data sets have been carefully transcribed and are available from Met Éireann, 1850-1920 and 1921-1943. In 1944 Met Éireann did something a bit unusual, they started measuring the temperature every hour. Rain or shine, sleet or snow, the diligent staff of Met Éireann would go out to the weather station and record the temperature. Between January 1944 and April 2012 when the station was replaced with an automated station only 2 hours were missed. The data set from 1944 onwards is available from the Irish Government website: daily summary (includes minimum and maximum temperature) and hourly measurements.

Because we have an overlap of measurements from minimum and maximum thermometers and the 24 hourly measurements for Valentia, this means we can check just what the difference is between T_avg and T_axn to see how accurate the Meteorologists’ method of estimating average temperature from T_min and T_max is.

This first graph shows the difference T_avg-T_axn for every day since 14^th January 1944 plotted as blue points. Overlaid is the 1 year rolling average as a red line. If you are interested in the statistics, T_avg is greater than T_axn in Valentia on average by 0.17ºC (std deviation 0.53, N=29339, min=-2.20, max=3.20).

If we just look at the rolling average, you can see that the relationship is not constant, for example in the 1970’s the average temperature was on average 0.35ºC warmer than the Meteorological estimate, while in the late 1940’s, 1990’s and 2000’s there were occasions where the Meteorological estimate was slightly higher that the actual average daily temperature.

It’s important to highlight that this multi-year variability is both unexpected and intriguing, particularly for those examining temperature anomalies. However, putting aside the multi-year variability, by squeezing nearly 30,000 data points onto the x-axis we may have hidden a potential explanation why the blue points typically show a spread of about ±1ºC… Is ±1°C spread seasonal variability?

The shortest day of the year in Valentia is December 21^st  when the day lasts for approximately 7h55m. The longest day of the year is June 21^st when the day lasts for 16h57m. On the shortest day of the year there is little time for the sun to heat up and most of the time it is dark and we expect heat to be lost. So we expect the average temperature to be closer to the minimum temperature during the winter than during the summer.

We can check the seasonal effects in the difference between T_avg and T_axn by looking at a time dependent correlation. As not everyone will be familiar with this kind of analysis, I will start by showing you the time dependent correlation of T_avg with itself:

The x-axis is how many days there are between measurements and the y-axis is the Pearson correlation coefficient, known as r, which measures how similar measurements are averages across all the data. A Pearson correlation coefficient of +1 means that the changes in one are exactly matched by changes in the other, a coefficient of -1 means that the changes are exactly opposite and a correlation coefficient of 0 means that the two variables have no relationship to each other.

The first point on the x-axis is for 1 day separation between the average temperature measurements.

The laziest weather forecast is the following:

“Tomorrow’s weather will be basically the same as today’s”

The r value of +0.91 for 1 day separation is an illustration of the accuracy of the laziest weather forecast and suggests that for average temperature it is approximately 82% accurate.

If we move out to half a year separation, we get an r value of -0.64 which says that 6 months from now, 41% of the average daily temperature can be explained as the opposite of today’s.

At a year separation the r value of 0.67 days that 44% of today’s average temperature can be explained as seasonal for this time of year. What this means is that actually the laziest weather forecast is only explaining 38% better than the seasonal forecast

You see very similar graphs if you look at the time-dependent correlation of the  T_max,  T_min or indeed the T_axn, with the 1 day r values being 0.90, 0.81 and 0.90 respectively and the seasonal swing being approximately -0.6 to +0.6 for 6 months and 1 year.

The above graph basically tells us what to expect when something is strongly seasonal.

What happens when we plot the time-dependent correlation of T_avg-T_axn? Well you get this:

The 1 day correlation is 0.19, this tells us that approximately 4% of today’s correction factor between T_avg and T_axn can be predicted if we know yesterday’s correction factor. The seasonality is even worse, the 6 month correlation coefficient is -0.02 and the 1 year correlation coefficient is +0.07.

This answers our earlier question… The ±1°C spread is not seasonal variability.

What this means is that if we only know T_axn then T_avg could be anywhere ±1°C.

Here is another graph to illustrate this. The x-axis is T_avg and the y-axis is T_axn. Now obviously when the average daily temperature is higher, the average of the minimum and maximum temperatures is also higher and so we get a straight line of slope 1, but the thickness of the line represents the uncertainty of the relationship, so if we know T_axn is say 15°C then from this graph we can say that T_avg is probably between 13.5°C and 16.5°C.

Now because most weather stations were not recording hourly until recently, most of our historical temperature data is the T_axn form and not the T_avg. That means that if Valentia is representative then the past temperature records are only good to ±1°C. If somebody tells you that the average temperature in Valentia on the 31^st of May 1872 was 11.7°C, the reality is that we just do not know. It’s 95% likely to have been somewhere between 10.6ºC and 12.7ºC and we have no way of knowing just like knowing what the maximum and minimum speeds of the Bugatti through the port tunnel doesn’t really tell us much about its average speed.

In this last graph the blue points show the average T_axn of each year at Valentia since 1873 with vertical error bars showing the 95% confidence interval. The red points show the average T_avg for each year starting from 1944 with error bars showing the annual variation. The blue poking out from under the red shows the difference, even on the scale of a yearly average between the Meteorologist’s estimate of average temperature and the actual average temperature.

Valentia Observatory is one of the best weather stations globally. With the switch to automated stations in the 1990s, we can now get precise average temperatures.

Thanks to the meticulous efforts of past and present staff of Valentia Observatory and Met Éireann, we have 80 years of data which allows comparison of the old estimation methods with actual averages.

The takeaway?

Our historical temperature records are far less accurate than we once believed.

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By Andy May

Wow! Our new paper “Carbon Dioxide and a Warming Climate are not problems,” in the American Journal of Economics and Sociology has struck a nerve, judging by the traffic about it on twitter. An anonymous twitter troll who calls himself “Bonus @TheDisproof” has published what he (or she) calls a list of errors in our paper that is getting a lot of views and likes from the usual alarmist suspects, some of whom are probably actually people as opposed to “bots.” One person who has reposted the “Bonus” critique is Michael Mann. Michael Mann says, “This article is a Crok.” I don’t think he was complementing my co-author Marcel Crok, but then Mann is well known for crude and juvenile remarks. Mann might still remember Marcel for his 2005 award-winning article about Mann’s notorious hockey stick graph. Marcel was the first who wrote extensively about the critique of McIntyre and McKitrick on this graph.

I’ve tried answering most of Bonus’s criticisms on twitter, but the responses keep disappearing. Not sure what is going on there. Normally answering an anonymous troll isn’t worth the bother but judging from my email and phone calls about this one, I should. So, this post addresses his list of complaints to date. I’ll indent the complaints and number them.

Bonus:

“A new climate denial paper in an obscure low impact, non-climate related journal has popped up. It is written by Marcel Crok @marcelcrok & Andy May @Andy_May_Writer, both of which spread disinfo on a regular basis. I’ll go through just some of their multiple errors here.”

First of all, I don’t know of any disinformation that either Marcel or I have posted anywhere. All our posts and the paper are solidly supported by references and/or data. Bonus’s list of “errors” follows.

Bonus #1

“Their paper falsely claims “. Sea level rise is currently a very modest two millimeters per year”. They cite their own non peer reviewed source (A Clintel climate denial “report”) but omit that both tide gauges AND satellite data shows a faster rate and an accelerating rate.”

First of all, the Clintel Report we cite, “The Frozen Climate Views of the IPCC: An Analysis of AR6” was extensively peer-reviewed by a team of four independent reviewers as well as the eight named authors of the chapters. There were also two other members of the Clintel team that helped review selected chapters. The Clintel team reside in 8 countries and work in academia, government, and industry. Their professions cover numerous disciplines including economics, geology, meteorology, chemistry, physics, molecular biology, atmospheric physics, and climatology. See the book for more details.

There are two chapters in the book that deal with sea level, one by Kip Hansen and the other by Ole Humlum. Both agree, along with those who peer-reviewed the work, that the rate of sea-level rise over the past 150 years or so is about 1-2 mm/year according to tide gauges. It varies up and down cyclically over the 150-year period, so one can (and some do) cherry-pick intervals in an attempt to show acceleration, but no definitive acceleration is apparent in the record, at least on climate scale periods of time. One reason is that the data, whether satellite or tide gauge, is not accurate enough at the present very slow rate of sea level rise to be definitive, as discussed in the book.

Sea level fell during the Little Ice Age as more and more water was taken up to enlarge glaciers and the ice caps during that very cold period. When the Little Ice Age ended around 1850, the expanded glaciers began to melt, and sea level began to rise. This is all normal. The overall rate of increase was between 0.8 and 1.95 (very likely range) mm/year according to AR6 Chapter 9 (IPCC, 2021, p. 1287) and other sources.

More recently we gained the ability to estimate sea level using satellites. Problems reconciling the satellite measurements and the tide gauge records have made sea level rise estimates difficult since the first satellite data became available in 1992. A much more detailed discussion is available in Chapters 5 and 10 in the “The Frozen Climate Views…” (Crok & May, 2023).

Bonus #2

“They cited just two climate proxy papers Vinther et al 2009 and Rosenthal et al 2003 [sic] and attempted a cherry pick. But they ignored that Vinther et al uses data that ends decades ago so omits the rapid and significant warming in Greenland since then.”

The two temperature proxy papers we cite are (Vinther, et al., 2009) and (Rosenthal, Linsley, & Oppo, 2013). We plotted the entire proxy record from both sources back to the beginning of the Holocene approximately 9,000BC, nothing was cherry-picked. Vinther and Rosenthal’s data ends in the early to mid-20^th century because the proxies for later than that haven’t formed yet. The Greenland ice is still snow or firn and the animal shells in the Makassar Strait that Rosenthal used are not stabilized in the ocean floor sediments yet. This is how all proxies work. The only way to incorporate modern temperatures into the graph is to mix instrumental data with the proxies which must be done very carefully for number of reasons, the modern data must be made to conform to the proxy dataset. We did this in our figure 4 from (May & Crok, 2024), shown below.

To validly compare proxies to modern temperatures you must average the modern temperatures over the temporal resolution of the proxies and compare them at the proxy location. There are very few proxies in 9000BC, so a valid global average temperature (proxy or otherwise) isn’t possible. Proxies are very low resolution compared to the daily temperatures we gather today with thermometers. Further, besides resolution problems, proxy temperatures just are not very accurate, those in figure 1 are among the better proxies and their accuracy is ±0.3 to 0.4 deg C.

Figure 4 in our paper (figure 1 above) does do a valid comparison for the Makassar Strait record by averaging the 500-meter depth temperatures from the University of Hamburg’s ocean database from 2006-2016 (Gouretski, 2019). This temperature is shown as a red box on the figure, presumably Bonus missed this or didn’t understand it. The temporal resolution of the Vinther and Rosenthal records in the twentieth century is about 20 years between temperature estimates, so 2006-2016 is close to that, it is also the time period with the best data in the Makassar Strait. Earlier than 2006 the data gets poor very quickly.

Thus, what Bonus wants us to do is invalid and erroneous. We did the most valid comparison to modern instrumental temperatures possible. To see the Greenland data treated in the same way, see this post, figure 1. In it, the modern data in the Greenland area is compared to the Alley Greenland ice core record for the past 4,000 years.

Bonus #3

In addition: Rosenthal et al 2009 AND Rosental et al 2013 shows current GLOBAL SST is currently above the level seen in the very regional Rosenthal 2003 paper.

Again, Bonus gets his Rosenthal papers mixed up. The data we present is the Rosenthal (2013) data and it is not the SST (sea surface temperature) data he is referring to. We use the intermediate water temperature (500-meter depth) because it represents SST temperatures in the northern Pacific Ocean. Bonus is just confused here and didn’t read the paper carefully enough.

Bonus #4

Not to mention that collectively climate proxies show that current global temperatures are well above anything in the human civilization history. See also Marcott et al 2021.

Again Bonus is confused, no one knows what the global average surface temperature was in 9000BC, or even in 1000AD. Proxies are not that accurate. Plus according to AR6, (Kaufman, McKay, & Routson, 2020) and (Kaufman & McKay, 2020b) the median/average temporal resolution of the proxies used in the graph he shows from Marcott and Shakun (2021) is 164 years between temperatures or the entire industrial period record since 1880. You can’t compare current rates of warming from daily measurements to rates from that proxy data. All you can do is average all the temperatures since 1880 and compare it to selected proxies at the specific proxy locations. Nothing else is a valid comparison. See this post by Renee Hannon for a further discussion of this issue.

Bonus #5

They repeat Bjorn Lomborg’s false claim that climate related deaths have declined 99% since the early 20thC. Lomborg’s claim [is] debunked.

Bonus shows a video clip of someone (unidentified, like Bonus himself) claiming that Lomborg misrepresented the EM-DAT data he used to create his now famous graph, which comes from a peer-reviewed paper he wrote in 2020 (Lomborg, 2020). The graph is shown below.

The anonymous video is a rather tiresome complaint that Lomborg prepared the data incorrectly and presented it incorrectly, the narrator’s arguments don’t hold water. It is very clear that no matter how the data are presented, deaths from extreme weather have decreased radically since the early twentieth century. One could quibble about the classifications of the deaths by EM-DAT or the data prep forever, but the underlying idea is sound. Besides, Lomborg’s paper is peer-reviewed and we don’t even know who Bonus or the narrator in the video are. I’ll take peer-reviewed over anonymous drivel any day.

Bonus #6

They mention a paper on CO2 Greening (Zhu et al 2016) but fail to mention a more detailed analysis found that the greening dominated in China and India and was due to “programs to conserve and expand forests” and “intensive cultivation of food crops”.

This demonstrates that Bonus has not read the papers he cites very well. Zhu (the paper we cite, (Zhu, Piao, & Myneni, 2016)) calculates that 70% of Earth’s global greening in the modern period is due to CO2 and about 13% is due to fertilizer and land use changes by humans. The non-peer-reviewed NASA blog post that Bonus cites, states that China and India account for 30% of the global greening, there is no inconsistency in the numbers from the two sources, they are about different things. Both articles agree that the Earth is greener in recent years, but the NASA blog post is silent on the impact of CO2. Bonus was confused and in over his head.

Bonus #7

“They claim more CO2 benefits plants but ignore the greater harmful side effects of climate”

CO2 is pumped into greenhouses to achieve more rapid growth and Craig Idso (Idso, 2013) has estimated the monetary benefit to farming output of increased CO2 is $3 trillion since 1961. What are the harmful side effects of additional CO2 that our anonymous Bonus has to offer. Again, he refers to an anonymous non-peer-reviewed video. His source tweet is here, I did not try and figure out which source was which, and Bonus provided no help. The reader is welcome to try and figure it out, I will not bother with it.

The first argument from the video is that CO2 is not the only limiting factor to plant growth, plants also need water, pests are a problem, etc. These have absolutely nothing to do with CO2 and are red herrings. Then they say the rate of additional growth due to more CO2 lessens as CO2 increases. So what? You still get more growth. Then they say additional CO2 benefits weeds as well as crops, well duh, of course that is the case. Weed control is a separate issue.

Then they claim that recently crop production has declined. Not according to the data in Ourworldindata.org and FAO, see below.

Then they claim that additional CO2 increases global temperature and drought. As our peer-reviewed paper (May & Crok, 2024) makes clear the connection between CO2 and temperature is possible, but not proven and meteorological drought is decreasing or staying the same [(Klotzbach, Bowen, Pielke, & Bell, 2018), (Crok & May, 2023, pp. 142-157), and (Pielke, 2019)], and not increasing globally according to AR6 (IPCC, 2021, pp. 1579-1580). Finally, they say, global warming increases the growing season, true, but then they complain that this increases the use of water and gives pests more time to get to the crop. A rather silly argument, longer growing time is a good thing, whether caused by CO2 or not. The video is anonymous and unsourced, like Bonus, whereas our sources are all peer reviewed.

Bonus #8

Near the end of their paper they cite an Exxon corporate document for their claim that we will need more fossil fuels.

The data we cite is from ExxonMobil’s yearly Outlook. It is widely used as a very credible source of energy production and consumption data. It is used, and cited, globally, like similar reports generated by BP and Shell are used. This is pure prejudice and not a valid criticism, Exxon’s Outlook is a very credible source.

Bonus #9

Marcel Crok is responsible for a climate denial “clintel declaration” signed mostly by fossil fuel employees, oil and gas geologists, fossil fuel lobby group members non-experts, conspiracy theorists and not a single actively publishing climate scientist.

This is completely untrue, like nearly everything Bonus writes. The 1900+ Clintel signatories include fossil fuel employees and retirees (including me) of course, but also hundreds of scientists and engineers who are or were employed by academia and in other industries. There are many, many Clintel signatories who are actively publishing climate scientists, including both Marcel and myself, as well as many others. I should mention that “climate scientist” is not a real field, most “climate scientists” have degrees in physics (like William Happer), geology (like Michael Mann or Andy May), atmospheric physics (Richard Lindzen and Judith Curry), or meteorology.

Bonus #10

Oh and Marcel Crok’s clintel released a climate denial film with @Martin_Durkin that was debunked.

Michael Durkin’s film (supported by Tom Nelson and Marcel Crok) has never been debunked and is well grounded in the peer-reviewed literature (see here for a full annotated bibliography) unlike the non-peer-reviewed and unsourced films by the anonymous filmmakers cited by Bonus.

I’ve followed the very popular and excellent Climate The Movie: The Cold Truth since it first came out and it has not been debunked by anyone credible that I’m aware of.

Bonus #11

The paper also claims no change in extremes linked to climate change which is false. I noted that Crok and May have admitted in their Clintel report on IPCC AR6 they didn’t read the full AR6 IPCC report so that might be why they didn’t find anything. i.e. they didn’t look.

We did not claim that extreme weather didn’t change, we claimed and documented that most extreme weather trends either have not changed in modern times or have decreased and that overall the impact of extreme weather declined as a percent of GDP. These are well documented facts reported in “The Frozen Climate Views of the IPCC: An Analysis of AR6” (Chapters 11-13) and in AR6. There is no evidence that extreme weather or the impact of extreme weather has increased.

As for Marcel Crok and Andy May not having read all 10,000 pages of AR6, this is true. I seriously doubt many people have. However between the entire 13-member team we assembled to write “The Frozen Climate Views of the IPCC: An Analysis of AR6” we very likely did. AR6 is ridiculously long.

Bonus #12

the plot thickens…It turns out that the Journal’s calls for papers on climate seems to be courting fossil fuel funded climate change denier groups. Their call for papers links to the CO2 coalition (a fossil fuel funded lobby group that spreads disinfo) which May is a member of.

The CO2 Coalition is a very good organization that I am a proud member of. It spreads no disinformation that I’m aware of and Bonus provides no examples. This propensity of the alarmists to lie about and disparage good organizations and people only because they disagree with them is reprehensible.

Bonus #13

……and if this is the Marty Rowland who is special editions editor at the American Journal of Economics and sociology Journal look at what he says about climate change. Wow, looks like a journal that likes climate change denial and disinformation?!

And the character assassination attempts continue. Marty Rowland has the opinion that “climate change” is a religion. It is. The “true believers,” such as Bonus or Michael Mann, will not discuss or debate the issue as true scientists would do, they just try and beat down their opponents with ad hominem attacks on twitter. One is reminded of the Spanish Inquisition.

Bonus #14

AJES ranking, not good.

This is a silly argument. The American Journal of Economics and Sociology has been around since 1941 and is well respected. This sort of argument is very juvenile, like the attacks on Marty Rowland, Marcel Crok, and myself.

Conclusions

The anonymous “Bonus” somehow created quite a stir on twitter, yet we don’t know who he or she is, could be a twelve-year-old with his mother’s phone for all we know. Bonus cites very few peer-reviewed articles and when he does, he often gets them wrong as in the Rosenthal article mix up discussed above. Yet, Michael Mann cites him in twitter, which gives you an idea about Mann’s academic integrity.

None of Bonus’s claims are true or supportable. Beware of what you read from anonymous sources. Bonus’s critique is a biased and emotional screed with no merit.

Download the references here.