How is 14C data turned into a solar or radiative proxy?
Didn’t know that, is a trivial question which has been troubling me for some time. By chance the key to understanding turned up in a 200 page tome, “Stable isotope mass spectrometry and AMS dating applied to a multi-proxy climate record from the Bliden Lake, Denmark”, doctorial thesis of Jesper Olsen.
He drew a picture.
Page 64 (page 76 of PDF) of a fascinating thesis.
Perhaps he was passing on what had been shown to him, never mind, he did it. As a result the handwaving by others, not actually saying, turned into my understanding what they omitted to say.
Want to really understand something and use it fully, take it apart, put it together, explore it.
Reproducing the 14C flux curve
The data I usedÂ is very recentÂ IntCal09
That tells the whole story, there is nothing magical, simply split the data into long and short term, and invert the Y axis so it looks like solar data. According to Fig4-5 in Olsen has shown this done for recent times by lsqr fitting a sine and then subtacting, but not inverted.
I point out this could be done using filtering, except that would need to address the end of dataset problem, avoided by most people in science.
For the moment I am looking at the most recent 9,000 years.
I used the synthesiser software here to extract the four largest long terms, thought, switched off two of them, the above is the result.
The makes reasonable sense yet raises many questions.
Added image 20th July, marine data version
Last datapoint is at 1950 when the exploding of nuclear weapons killed 14C as a useful natural proxy, later data needs extreme compensation.
In my mind the straight line from 1900 is bizarre.
A part explanation might be human mining, such as coal extraction and combustion: radioactive gases are emitted, whereas naturally these leak out slowly. That still makes little sense, the line is too straight, and why 1900? I have no answer.
Turning to the longer term
The late Jack Eddy is cited, the long term change is part of solar activity change. My reaction is more than surprise. That variation is huge relative to the supposed solar proxy when you consider what we know about observed activity change.
According to the data there has been orders of magnitude change roughly linearly during the past 30,000 years.
Radiation, presumably cosmic rays, show as a huge flux.
Next I turned to splitting the dataset using a filter, quick and easy.
What is that? Well, I am throwing a spanner in the works of 14C as a solar proxy. Four different low pass filters applied to the input data, subtract and there is the high pass, what remains without the longer term wiggles.
If you find it doesn’t look credible, I have allowed the plot software to rescale the Y-axis. It really is the same data.
Why 200, 700, 2000, 7000 year? A guess at what would show the effect without too many plots. Note the filter is end compensated, have to trust me. (otherwise walk away and do your own)
That result points to 14C being hugely influenced by something else, perhaps vegetation activity, so could be be water availability, temperature, how much of the earth is environmentally acceptable to plants?
A quick explore suggests a signature of orbital insolation variation but that will have to wait for one day maybe.