Update March 23, 2022
For a possible explanation of natural warming and CO2 emissions see Little Ice Age Warming Recovery May be Over
This post is about proving that CO2 changes in response to temperature changes, not the other way around, as is often claimed. In order to do that we need two datasets: one for measurements of changes in atmospheric CO2 concentrations over time and one for estimates of Global Mean Temperature changes over time.
Climate science is unsettling because past data are not fixed, but change later on. I ran into this previously and now again in 2021 and 2022 when I set out to update an analysis done in 2014 by Jeremy Shiers (discussed in a previous post reprinted at the end). Jeremy provided a spreadsheet in his essay Murray Salby Showed CO2 Follows Temperature Now You Can Too posted in January 2014. I downloaded his spreadsheet intending to bring the analysis up to the present to see if the results hold up. The two sources of data were:
Temperature anomalies from RSS here: http://www.remss.com/missions/amsu
CO2 monthly levels from NOAA (Mauna Loa): https://www.esrl.noaa.gov/gmd/ccgg/trends/data.html
Changes in CO2 (ΔCO2)
Uploading the CO2 dataset showed that many numbers had changed (why?).
The blue line shows annual observed differences in monthly values year over year, e.g. June 2020 minus June 2019 etc. The first 12 months (1979) provide the observed starting values from which differentials are calculated. The orange line shows those CO2 values changed slightly in the 2020 dataset vs. the 2014 dataset, on average +0.035 ppm. But there is no pattern or trend added, and deviations vary randomly between + and -. So last year I took the 2020 dataset to replace the older one for updating the analysis.
Now I find the NOAA dataset in 2021 has almost completely new values due to a method shift in February 2021, requiring a recalibration of all previous measurements. The new picture of ΔCO2 is graphed below.
The method shift is reported at a NOAA Global Monitoring Laboratory webpage, Carbon Dioxide (CO2) WMO Scale, with a justification for the difference between X2007 results and the new results from X2019 now in force. The orange line shows that the shift has resulted in higher values, especially early on and a general slightly increasing trend over time. However, these are small variations at the decimal level on values 340 and above. Further, the graph shows that yearly differentials month by month are virtually the same as before. Thus I redid the analysis with the new values.
Global Temperature Anomalies (ΔTemp)
The other time series was the record of global temperature anomalies according to RSS. The current RSS dataset is not at all the same as the past.
Here we see some seriously unsettling science at work. The purple line is RSS in 2014, and the blue is RSS as of 2020. Some further increases appear in the gold 2022 rss dataset. The red line shows alterations from the old to the new. There is a slight cooling of the data in the beginning years, then the three versions mostly match until 1997, when systematic warming enters the record. From 1997/5 to 2003/12 the average anomaly increases by 0.04C. After 2004/1 to 2012/8 the average increase is 0.15C. At the end from 2012/9 to 2013/12, the average anomaly was higher by 0.21. The 2022 version added slight warming over 2020 values.
RSS continues that accelerated warming to the present, but it cannot be trusted. And who knows what the numbers will be a few years down the line? As Dr. Ole Humlum said some years ago (regarding Gistemp): “It should however be noted, that a temperature record which keeps on changing the past hardly can qualify as being correct.”
Given the above manipulations, I went instead to the other satellite dataset UAH version 6. UAH has also made a shift by changing its baseline from 1981-2010 to 1991-2020. This resulted in systematically reducing the anomaly values, but did not alter the pattern of variation over time. For comparison, here are the two records with measurements through February 2022.
Comparing UAH temperature anomalies to NOAA CO2 changes.
Here are UAH temperature anomalies compared to CO2 monthly changes year over year.
Changes in monthly CO2 synchronize with temperature fluctuations, which for UAH are anomalies now referenced to the 1991-2020 period. As stated above, CO2 differentials are calculated for the present month by subtracting the value for the same month in the previous year (for example June 2021 minus June 2020). Temp anomalies are calculated by comparing the present month with the baseline month.
The final proof that CO2 follows temperature due to stimulation of natural CO2 reservoirs is demonstrated by the ability to calculate CO2 levels since 1979 with a simple mathematical formula:
For each subsequent year, the co2 level for each month was generated
CO2 this month this year = a + b × Temp this month this year + CO2 this month last year
Jeremy used Python to estimate a and b, but I used his spreadsheet to guess values that place for comparison the observed and calculated CO2 levels on top of each other.
In the chart calculated CO2 levels correlate with observed CO2 levels at 0.9979 out of 1.0000. This mathematical generation of CO2 atmospheric levels is only possible if they are driven by temperature-dependent natural sources, and not by human emissions which are small in comparison, rise steadily and monotonically.
Previous Post: What Causes Rising Atmospheric CO2?
This post is prompted by a recent exchange with those reasserting the “consensus” view attributing all additional atmospheric CO2 to humans burning fossil fuels.
The IPCC doctrine which has long been promoted goes as follows. We have a number over here for monthly fossil fuel CO2 emissions, and a number over there for monthly atmospheric CO2. We don’t have good numbers for the rest of it-oceans, soils, biosphere–though rough estimates are orders of magnitude higher, dwarfing human CO2. So we ignore nature and assume it is always a sink, explaining the difference between the two numbers we do have. Easy peasy, science settled.
What about the fact that nature continues to absorb about half of human emissions, even while FF CO2 increased by 60% over the last 2 decades? What about the fact that in 2020 FF CO2 declined significantly with no discernable impact on rising atmospheric CO2?
These and other issues are raised by Murray Salby and others who conclude that it is not that simple, and the science is not settled. And so these dissenters must be cancelled lest the narrative be weakened.
The non-IPCC paradigm is that atmospheric CO2 levels are a function of two very different fluxes. FF CO2 changes rapidly and increases steadily, while Natural CO2 changes slowly over time, and fluctuates up and down from temperature changes. The implications are that human CO2 is a simple addition, while natural CO2 comes from the integral of previous fluctuations. Jeremy Shiers has a series of posts at his blog clarifying this paradigm. See Increasing CO2 Raises Global Temperature Or Does Increasing Temperature Raise CO2 Excerpts in italics with my bolds.
The following graph which shows the change in CO2 levels (rather than the levels directly) makes this much clearer.
There are big swings in the amount of CO2 emitted. Taking the mean as 1.6 ppmv/year (at a guess) there are +/- swings of around 1.2 nearly +/- 100%.
And, surprise surprise, the change in net emissions of CO2 is very strongly correlated with changes in global temperature.
This clearly indicates the net amount of CO2 emitted in any one year is directly linked to global mean temperature in that year.
For any given year the amount of CO2 in the atmosphere will be the sum of
- all the net annual emissions of CO2
- in all previous years.
For each year the net annual emission of CO2 is proportional to the annual global mean temperature.
This means the amount of CO2 in the atmosphere will be related to the sum of temperatures in previous years.
So CO2 levels are not directly related to the current temperature but the integral of temperature over previous years.
The following graph again shows observed levels of CO2 and global temperatures but also has calculated levels of CO2 based on sum of previous years temperatures (dotted blue line).
The massive fluxes from natural sources dominate the flow of CO2 through the atmosphere. Human CO2 from burning fossil fuels is around 4% of the annual addition from all sources. Even if rising CO2 could cause rising temperatures (no evidence, only claims), reducing our emissions would have little impact.
Fearless Physics from Dr. Salby
In this video presentation, Dr. Salby provides the evidence, math and charts supporting the non-IPCC paradigm.
Footnote: As CO2 concentrations rose, BP shows Fossil Fuel consumption slumped in 2020
Warmists got the cart before the horse.
Indeed beth. I got this from you years ago.
Stunning analysis, Ron. Thanks for expanding this data set to the present.
Thanks Michael. Trying as always to get to the truth hidden in the weeds.
Reblogged this on Climate Collections.
Ron thanks for the mention
even more thanks for updating the analysis
Jeremy, your original article was an eye-opener for me, and I learned even more figuring out how your spreadsheet plumbing works. So it is true in my case: “Imitation is the sincerest form of flattery.”
And of course, the CO2 message needs even more to be heard these hysterical days.
Great work, Ron. It looks like there is more to come.
Thanks Will. I was aware of both Salby’s and Harde’s prior work on this issue. I will have to look into Harde’s Earth Sciences 2019 article
What Humans Contribute to Atmospheric CO2: Comparison of Carbon Cycle Models with Observations
Reblogged this on WeatherAction News and commented:
I was listening to a Delingpod earlier this week and the Co2 leads temperature canard came out. I immediately thought of Salby’s work and the geological record, but with the smoothing and difficulties with precision for icecores it’s nice to see something with real time data to see it in effect (even if the adjustments to the temperature record are a bit disconcerting).
A fascinating post. Great work Ron.
Reblogged this on Tallbloke's Talkshop and commented:
The short answer to the climate question.
Hopefully this will enable Govts to use our best and most reliable energy sources.
Thanks Phil, for that thought. I also hope that political leaders come to their senses.
But they are greatly tempted to usurp power over the energy sector and thereby control the citizenry.
remss were forced to change their data a year or more ago in order to dis-align them selves with UAH. Couldn’t have two satellite datasets that agreed. That would devalue the surface datasets.
Ron ==> A marvelous piece of work. The ability to duplicate 40 years of CO2 data with a simple temperature to year+1 CO2 concentration is a powerful demonstration. Very well done.
As you know, I once duplicated the GMST over a century with a simple chaotic formula.
Thanks Kip. Much appreciated.
Ron ==> That said, I’m not sure that we can discern “cause” from all that — but I find it interesting that the math of it can be so simplistically demonstrated.
Perhaps the CO2 is the natural effect of the secular 0.5C per century warming since the Little Ice Age. The key is the long slow accumulation marking the momentum of a massive system.
Ron ==> There is just so much we don’t know or understand.
Interesting to watch our knowledge base grow, in spurts and spats — sometimes right, sometimes wrong.
Actually, your method of determining the CO2 anomaly differentiates the data (You even call it a differential). In doing so, your method removes the long term anthropogenic signal and the seasonal signal (time step choice). What you are left with are the short term variations, which are primarily the El Nino/La Nina process.
When you check the correlation, you add in the linear term and the seasonal signal that you just removed. Of course you will get high correlation.
No Frank. By using differentials you integrate the variations to show the cumulative effect, which is the emissions of CO2 from natural sources stimulated by rising temperatures.