Challenges to the Global Temperature Record

Social media and political propaganda sites are filled with accusations that the global temperature record is unreliable. Here is a list of the most common challenges to the reliability of global temperature records with links to my responses and short summaries of what I say in those posts. Note that each of these posts I link to cite the relevant literature and evidence, so you don't have to take my word for anything. You can verify everything I say, and if I ever get something wrong, feel free to let me know in the comments, and I'll make corrections. The subheadings below (#.#) are links to posts with more details about the following.

I. Global Temperature Data

1.1. Summary of Global Temperature Data and Trends Through 2024

In January I collected a bunch of data from various datasets on CONUS temperatures, ground thermometer data and reanalyses to compare how well they agree with each other. It's clear that 2024 was the first year to exceed 1.5C above the 1850-1900 mean in multiple datasets, though the that doesn't mean we exceeded the IPCC's target. The long-term warming is just over 1.3C.

1.2. Summary of Global Satellite Temperature Data and Trends Through 2024

In January I also collected data from the two major satellite datasets, RSS and UAH. The differences between these two are much larger than the differences between surface datasets, but both indicate sustained warming of the troposphere and sustained cooling of the stratosphere.

1.3. Accuracy of Satellite Temperatures Compared to GMST Anomalies

Long story short, satellites are very useful for temperature trends in the troposphere and stratosphere, but they don't measure surface temperatures, the uncertainties associated with satellites are about 5 times larger than surface thermometers.

1.4. Growing Extreme Heat with Global Warming

As global warming continues, the distribution of land temperatures widens, and extremely hot summers becomes much more prevalent on land. 

II. Can We Calculate Global Temperature?

There are various forms of argumentation that a global average either doesn't exist, that it can't be accurately calculated, or that the calculation is not meaningful. These are all rather silly, but some prominent contrarian influencers sometimes make these claims.

2.1. Claims That There is no Global Average Temperature

There are a variety of strange claims that there is no global mean surface temperature, all for very strange and silly reasons, including that you can't directly measure the temperature of the globe and/or that it requires calculation from sample data. However, it is clear that:

1. Temperature is proportional to average kinetic energy.
2. All molecules at the surface have kinetic energy.
3. So there can't not be a global mean surface temperature.

Calculating this mean temperature from sample data is no different from calculating any other mean from sample data

2.2. Claims that Temperature is an Intensive Property so it Can't be Averaged

A paper was published arguing what GMST is not meaningful because temperature is an intensive property so temperatures can't be added. But the paper explicitly contradicts itself. It claims:

1. "A sum over intensive variables carries no physical meaning. Dividing meaningless totals by the number of components cannot reverse this outcome" AND
2. "After putting [two containers of the same liquid each of the same volume] in thermal contact they will equilibrate at the common temperature (Ta + Tb)/2."

So apparently you can add temperatures and divide by the number of components after all. 

2.3. Claims That Global Average Temperature is Misleading

Richard Lindzen and John Christy wrote a political tract for the CO2 Coalition arguing, among other things, that GMST is misleading because seasonal and diurnal changes in temperature swamp the warming signal from CO2.

2.4. Claims That We Can't Know GMST, only Anomalies

It's true that most GMST graphs are usually plotted as anomalies, but they do this for very good reason. We can calculate anomalies with a much smaller uncertainties than the absolute value, since temperature changes are highly correlated regionally, meaning that while temperatures fluctuate by a lot on a regional level they change at about the same rate. So the information radius for a single station (for anomalies) is about 1100 km

2.5. Claims That GMST Must not be Changing Because of Arrhenius' 1896 Paper

Arrhenius calculated GMST to be 15 C in the late 19th century, but without any access to temperature data in polar regions, so his estimate was likely too high. 

2.6 Claims that Confidence Intervals for GMST are Very Large Because of Bias Correction

Clintel claimed that there are large uncertainties associated with NASA's global temperature record by comparing older versions of NASA's dataset to newer versions. They attributed the changes to bias correction, but in fact most of the changes had to do with new thermometer records added to the network, increasing global coverage on land and adding sea surface temperatures.

2.7 Claims that Confidence Intervals for GMST are Very Large Because of Instrumental Biases

This paper is so full of math errors it's really kind of hilarious. Patrick Frank, the author of the paper, tried to take issue with me on this, but his claims fall flat. Aside from the basic math errors, Franks paper argues that instrumental error correlate geographically, which in essence requires communication of error between stations, as in a "spooky action at a distance" sort of way.

2.8. Comic Relief: Temperature.Global

An anonymous person (or small group of people) set up a website with a "real time" (very loosely defined) GMST using a Heller-styled method of just calculating a simple average of station data. It did not go well, and the website shut down in 10 years.  

III. Are Scientists Manipulating Global Temperatures?

There is no shortage of claims that scientists are manipulating global temperatures to fabricate global warming.

3.1. Claims that Scientists Fabricate Global Warming with Bias Correction and Homogenization

Every scientific institution on the planet corrects biases that affect raw data. For temperature data, scientists have published numerous studies that can identify these biases, quantify them, and develop methodologies to correct them. The results of this work can be found in the scientific literature and in the documentation associated with the published datasets. As a general rule, bias correction to land temperatures increases warming trends, but adjustments to sea surface temperatures reduces warming trends by a larger amount. The net effect of all adjustments is to lower the amount of global warming. 

3.2. Claims that Global Warming is Due the Urban Heat Island (UHI) Effect

Wickham et al 2013 compared a "very rural" subset of station data and compared this subset to "all stations" and found that the very rural subset is warming at least as rapidly as all stations. This confirms that UHI is not having any demonstrable effect on either global or CONUS temperature trends. This is for several reasons:

1. Cities warm at the same rate as rural areas.
2. Bias correction removes biases associated with urbanization.
3. Urban areas are only ~1% of global surface area.

Robert Rhodes at Berkeley Earth plotted global land mean surface temperatures using both all stations and only "very rural" stations from 1850-2024. The two are indistinguishable from each other, so it simply cannot be that UHI is having a measurable effect on land temperature anomalies.

3.3. A Sniff Test for the UHI effect on Global Temperatures

If UHIs were responsible for a significant fraction of warming in the CONUS temperature record, then temperature anomalies would be much higher at cities than in rural areas, but they aren't. You can pick out cities in maps of population density, but they are invisible on maps of temperature anomalies.

3.4. Claims that Tom Wigley Fudged SST Data to Fabricate Warming

Wigley was addressing biases affecting SSTs due to changes in temperature collection methods from ships, and the adjustment actually went in the opposite direction to what contrarians claim.

3.5. Claims that John Bates was a Whistle Blower for Data Manipulation from NOAA

Even John Bates says there was no data manipulation. If you believe Bates, the claim that NOAA manipulates data goes away.

IV. Related Issues

4.1. Claims That the Spike in Global warming in 2023-2024 was due to the Tonga Eruption

I've fond at least 6 studies evaluating the impact of Tonga on the anomalous 2023-24 warmth, and none of them find compelling evidence that Tonga had any significant impact. In fact, it more likely had a cooling influence.

4.2 Claims that Current Global Warming Rates Aren't Rapid

Compared to the best evidence we have from paleoclimate data, current warming ranks among the most rapid warming events of the Phanerozoic.

4.3. Claims that Global Warming in the early 20th Century was as Rapid as the 21st Century

Matthew Wielicki claimed that warming from 1916-1942 was the same as from 1998-2024. His claim depended on some exceptionally bad math.

4.4. Claims About Pauses in Global Warming

After every El Nino event, contrarians claim that global warming has paused. These claims continue until the next El Nino event, then contrarians claim that it's only hot because of El Nino, so it doesn't count. Ad nauseam.