Guest post by Willis Eschenbach
Among my other sins, I made money as an accountant for multiple businesses and non-profits as well as an accountant for two of my own, a tax accountant, and the CFO of a company with $40 million in annual sales. So I often think about things like this Return on Investment (ROI) and Energy Return on Investment (EROI). From that excellent source:
Energy Return on Investment (EROI) is a ratio that describes the relationship between the energy produced and the energy used to create it. For example, the ratio would describe the amount of energy used to locate, extract, transport, and refine crude oil compared to the amount of usable energy produced.
Today I realized I could create a similar ratio to analyze climate, I called this ratio “WROI” “Watt ROI”. It is defined as the value at the Earth's surface:
Downwelling thermal radiation from the atmosphere divided by upwelling thermal radiation from the surface
Conceptually, this is how it works. Depending on its temperature, a surface emits a certain amount at each location upwelling thermal radiation. This is invest, measured in watts per square meter of surface. (W/m2)
Part of the upwelling thermal radiation is absorbed by the atmosphere, and part returns to the surface downwelling thermal radiation. This is returnagain in W/m2.
Watt return on investment (WROI) is the ratio of these two. It is the percentage of downwelling thermal radiation to upwelling surface thermal radiation.
Why is this interesting?
Well, CO2 Lutz temperature theory shows that as CO2 increase, the amount of downflow thermal radiation should Increase worldwide due to increased absorption of upwelling surface thermal radiation.
More importantly, I realize that depending on its size, this change may be visible in the WROI profile.
This is the fun part. This morning I was taking a break from riding my bike on a trail far from home when I was thinking about this.
There was a bench in that place where I could sit and think. It was there that I came up with the idea of WROI.
As you can probably imagine, I'm excited to flesh out this concept and see what the data actually shows, CO2 The changes are visible, where is the maximum and minimum WROI…without seeing the computer, of course. Gulu.
Frustrating, but it means I have time to think about the uses of CO2 Lutz temperature theory can predict. it will predict WROI should increase over timean increase in the percentage of rising longwave radiation absorbed due to an increase in CO2 in the atmosphere2.
I also think the WROI in the Northern Hemisphere may be greater because of the CO in the atmosphere2 Concentrations are higher in the north.
Even better, I can calculate how much WROI should increase due to an increase in CO2.
Encouraged by all this, I got back on my bike and kept riding. Obviously, I'm home now. Here are some logs from my initial wanderings around the WROI stuff.
I looked at changes in WROI over time in the CERES satellite data set. Remember, CO2 roolz temperature theory predicts that WROI will increase during this period.
In the graph of the WROI time series, I have added a line showing the magnitude and timing of the increase in WROI predicted by the increase in atmospheric CO2. (Red line in Figure 1 below, calculation details in footnotes.) Here are the results.
Figure 1. Percentage of rising surface radiation that is radiated back to the surface.
Dang-a-lang, sez I…this is a most interesting diagram.
It shows that whatever has caused the rise in temperatures over the past two decades… This is clearly not due to increased surface rising thermal radiation absorbed by atmospheric carbon dioxide2.
Anyway, that was my morning. I'm going for a walk now. There's more to discuss in the WROI data, but that's for another day.
My best wishes to everyone, including climate skeptics, pagans like me, and the mainstream,
w.
Yes, you've heard it before: When you leave a comment, please quote the exact words you are referring to. I can only defend my words, not what you think I said.
Trigger warning: Math is here!
Calculate the predicted percentage change in WROI due to CO2 It takes a few steps.
First I converted the time series of CO2 ppmv to W/m change2 forecast forcing.
Forced anomaly (W/m2) = log2(carbon monoxide2 time series/(the first of CO2 Time series))*CO 3.7 W/m2 per doubling2
Then I converted the CO2 The anomaly time series was forced into percentage units by dividing it by the same value I used to create the WROI (i.e., the CERES time series of upwelling thermal radiation from the surface). This gives me CO2 Force exceptions in the same percentage units as WROI.
Finally, I added CO2 Forces the anomaly percentage time series to the starting point of the CEEMD smoothing of the WROI time series. This is the red line in Figure 1, the predicted percentage increase in atmospheric CO.2.
related
