Propagation of Error and the Reliability of Global Air Temperature Projections, Mark II.

Readers of Watts Up With That will know from Mark I that for six years I have been trying to publish a manuscript with the post title. Well, it has passed peer review and is now published at Frontiers in Earth Science: Atmospheric Science. The paper demonstrates that climate models have no predictive value.

Before going further, my deep thanks to Anthony Watts for giving a voice to independent thought. So many have sought to suppress it (freedom denialists?). His gift to us (and to America) is beyond calculation. And to Charles the moderator, my eternal gratitude for making it happen.

Onward: the paper is open access. It can be found here , where it can be downloaded; the Supporting Information (SI) is here (7.4 MB pdf).

I would like to publicly honor my manuscript editor Dr. Jing-Jia Luo, who displayed the courage of a scientist; a level of professional integrity found lacking among so many during my 6-year journey.

Dr. Luo chose four reviewers, three of whom were apparently not conflicted by investment in the AGW status-quo. They produced critically constructive reviews that helped improve the manuscript. To these reviewers I am very grateful. They provided the dispassionate professionalism and integrity that had been in very rare evidence within my prior submissions.

So, all honor to the editors and reviewers of Frontiers in Earth Science. They rose above the partisan and hewed the principled standards of science when so many did not, and do not.

A digression into the state of practice: Anyone wishing a deep dive can download the entire corpus of reviews and responses for all 13 prior submissions, here (60 MB zip file, Webroot scanned virus-free). Choose “free download” to avoid advertising blandishment.

Climate modelers produced about 25 of the prior 30 reviews. You’ll find repeated editorial rejections of the manuscript on the grounds of objectively incompetent negative reviews. I have written about that extraordinary reality at WUWT here and here.

Propagation of nonsense – part II

September 10, 2019 ...and Then There's Physics

I thought I would look again at Pat Frank’s paper that we discussed in the previous post. Essentially Pat Frank argues that the surface temperature evolution under a change in forcing can be described as

$\Delta T(K) = f_{CO2} \times 33K \times \left[ \left( F_o + \sum_i \Delta F_i\right) / F_o \right] + a,$

where $f_{CO2} = 0.42$ is an enhancement factor that amplifies the GHG-driven warming, $F_o = 33.946 W m^{-2}$ is the total greenhouse gas forcing, $\Delta F_i$ is the incremental change in forcing, and $a$ is the unperturbed temperature (which I’ve taken to be 0).

Pat Frank then assumes that there is an uncertainty, $\pm u_i$ , that can be propagated in the following way

$u_i = f_{CO2} \times 33K \times 4 Wm^{-2}/F_o,$

which assumes an uncertainty in each time step of $4 Wm^{-2}$ and leads to an overall uncertainty that grows with time, reaching very large values within a few decades.

Since I’m just a simple computational physicist (who is clearly has nothing better to do than work through silly papers) I thought I would code this up. That way I can simply run the simulation many times to try and determine the uncertainty. Since it’s not quite clear which term the uncertainty applies to, I thought I would start by assuming that it applies to $F_o$ . However, $F_o$ is constant in each simulation, so I simply randomly varied $F_o$ by $\pm 4 Wm^{-2}$ , assuming that this variation was normally distributed. I also assumed that the change in forcing at every step was $\Delta F_i = 0.04 Wm^{-2}$ .

The result is shown in the figure on the upper right. I ran a total of 300 simulations, and there is clearly a range that increases with time, but it’s nothing like what is presented in Pat Frank’s paper. This range is also really a consequence of the variation in $F_o$ ultimately being a variation in climate sensitivity.

The next thing I can do is assume that the $\pm 4 Wm^{-2}$ applies to $\Delta F_i$ . So, I repeated the simulations, but added an uncertainty to $\Delta F_i$ at every step by randomly drawing from a normal distribution with a standard deviation of $4 Wm^{-2}$ . The result is shown on the left and is much more like what Pat Frank presented; an ever growing envelope of uncertainty that produces a spread with a range of $\sim 40$ K after 100 years.

Given that in any realistic scenario, the annual change in radiative forcing is going to be much less than $1 Wm^{-2}$ , Pat Frank is essentially assuming that the uncertainty in this term is much larger than the term itself. I also extracted 3 of the simulation results, which I plot on the right. Remember, that in each of these simulations the radiative forcing is increasing by $0.04 Wm^{-2}$ per year. However, according to Pat Frank’s analysis, the uncertainty is large enough that even if the radiative forcing increases by $4 Wm^{-2}$ in a century, the surface temperature could go down substantially.

Pat Frank’s analysis essentially suggests that adding energy to the system could lead to cooling. I’m pretty sure that this is physically impossible. Anyway, I think we all probably know that Pat Frank’s analysis is nonsense. Hopefully this makes that a little more obvious.

Posted in Climate sensitivity, ClimateBall, physicists, Research, Satire, Scientists| Tagged Climate models, Computational physicist, Frontiers, Pat Frank, Uncertainty propagation| 72 Comments

Monday, September 16, 2019

AUTHOR ! AUTHOR !

Propagation of Error and the Reliability of Global Air Temperature Projections, Mark II.

Propagation of nonsense – part II