Computer simulations said “Yes,” Reality said “No”

Energy is the lifeblood of civilization – the more the better. One of the great hopes for the last 50 years has been clean energy from fusion, and many very fine physicists have dedicated careers to this holy grail.  Perhaps the greatest hope for fusion has been the National Ignition Facility at the Lawrence Livermore National Laboratory.

At the National Ignition Facility the plan is to compress a small bead containing hydrogen to the extreme temperature and pressure at which fusion will occur.  This compression would be accomplished with an extraordinary array of high-powered lasers that would all converge on to a tiny 2mm bead.  If all works well the enormous amount of energy to power the lasers would be more than replaced by the energy released by the fusion reaction.  The hope is to repeat this process with a new hydrogen bead 16 times a second, yielding a continuous supply of useful heat to generate electricity.

Scientist at the National Ignition Facilty expected that hydrogen ignition (the point where fusion occurs and more energy is released than invested) would occur last year.  But it didn’t.  According to ScienceNews…

A lot of that confidence came from computer simulations… Each simulation consisted of more than a million lines of code filled with numbers and equations describing every push and pull that nuclei in the fuel capsule would encounter once the laser fired. All the data included in the simulations were based on well-tested theories and rigorous experiments, including measurements from hundreds of thermonuclear bomb explosions. The world’s fastest supercomputers required days or weeks to spit out the results.

Many of these simulations predicted that NIF’s 192-beam laser would comfortably achieve ignition. They showed that a short, powerful laser pulse coming from all directions would compress the pellet enough to create heat and pressure more intense than that in the sun’s core, forcing hydrogen nuclei together to form high-energy helium nuclei and neutrons.

No such luck.

Ignition was a failure.  I am not condemning the scientists at the National Ignition facility.  In this type of endeavour failure is just a stepping stone to success.  In fact, I  have great admiration for the folks working on this project and I hope funding and research continues.

Complex simulations

Here’s the thing: those millions of lines of code were modeling something that is relatively simple.  Hydrogen nucleosynthesis is well understood.   The models had to simulate just a single compression and ignition event. There were only a few variables compared to the thousands of variables for something as complex as, say, the climate of the planet Earth.

I have a lot more faith in talents and mental horsepower of the quiet anonymous physicists modeling the relatively simple fusion of hydrogen than I have in some of the self-important bumbling climate modelers working on the vastly more complex climate of the planet.

Just consider the grand poobah of climate modelers, James Hansen.  Ira Glickstein did a nice job of pulling back the curtain on Hansen’s modeling skills with this …

James Hansen’s 1988 models vs reality, From Ira Glickstein, WUWT, 3/20/2013)

The folks at the National Ignition Facility run their experiments, perhaps sometimes chastened by the results, but wiser and closer to their ultimate goal.

Hansen’s experiments are run by nature and take decades, but when he is wrong he is hardly chastened.  Hansen retired from his position at NASA a few days ago.  The Washington Post reported that Hansen said he was retiring so he could “spend full time on science.”  Does that mean he wasn’t spending his time on science at NASA?  His friend, Bill McKibben was probably closer to the mark when he said Hansen ”decided to step down so he could engage in lawsuits and protests full time.”

Hansen was also predictably lauded by his friend Gavin Schmidt.  I guess McKibben and Schmidt haven’t seen the above graph.

Science or Science Fiction? Professionals’ Discursive Construction of Climate Change

The headlines blazed!!

Forbes said…

Peer-Reviewed Survey Finds Majority Of Scientists Skeptical Of Global Warming Crisis

IBD said…

Global Warming Consensus Looking More Like A  Myth

WattsUpWithThat copied the the IBD headline.  And we are off and running.

The headlines of these blog articles all refer to the paper, “Science or Science Fiction? Professionals’ Discursive Construction of Climate Change,” in the journal Organization Studies.

Essentially, Forbes, IBD and WUWT were all saying  “Yippee!!  Here is a survey that shows most science and engineering professionals lean to the skeptical side when it comes to the question of global warming.”

Lessons to be learned here, and they are not pleasant.

I was given a hard copy to the Forbes article about the paper while visiting with a friend at a coffee shop. He knows of and shares my skepticism concerning much of the global warming alarmism. He shared the Forbes article as confirmation that skepticism was gaining ground. The Forbes article certainly presented it that way.

I thought “this would be a good topic  about which to write a blog post.”  (I also selfishly thought maybe I could scoop WUWT in this one.)  So, I got out my computer, logged onto the the coffee shop’s wi-fi and looked up the article.  Much to my chagrin, I found that the Forbes article (and subsequently the IBD article and even the WUWT article) greatly misrepresented the journal paper.

For those of you who have not actually read the journal paper, here is what it is really about: some social scientists are trying to peer into the minds of “deniers” (their word choice, not mine) to see what makes them tick.  What better laboratory could they find than engineers in Alberta that are likely associated with the gas and oil industry!

The authors of the paper are not saying “a bunch of smart scientist and engineer types think global warming is largely over-blown – maybe you should consider their perspective.” Rather, they are saying “Those poor engineer types up there in Alberta live in a world that revolves around oil and gas and their psyches are not able to grasp the true dangers of global warming because of the social and political structure in which they live.  What are the proper tactics to bring them around to the right kind of thinking?” (Not their actual words, but my interpretation of their words.)

Lesson #1

Maybe we ought to actually read journal papers before we start writing blog posts to interpret them for others.

Lesson #2

This journal article is an illustration of the primary problem in the global warming debate, and debates concerning other controversial scientific subjects (like GM plants and animals).  That is, many are fooled into thinking that weighing the credentials (or the social background, or the professional background, or the political affiliation, etc) of the advocate of a particular perspective is an adequate shortcut around the more arduous task of weighing the arguments of the advocate.  To wit, we don’t have to waste time listening to the reasoning of scientists and engineers from Alberta, we can simply dismiss them because the circumstances of those poor souls prevents them from being able to reason fairly.  This is the seductive path of lazy thinkers.

Lesson #3

Bad things could happen at WUWT when Anthony Watts takes a well deserved week-end break.

Lesson #4

My guess is that the authors of “Science or Science Fiction? Professionals’ Discursive Construction of Climate Change” are having a good laugh at the expense of Forbes, IBD, and WUWT

Rahmstorf (2011): Robust or Just Busted (Part 6): Holgate’s sea level data

This is part 6 of a multi-part series about “Testing the robustness of semi-empirical sea level projections,” Rahmstorf, et. al., Climate Dynamics, 2011. You can see an index of all parts here. I frequently refer to this paper as R2011.

Recall figure 1 from R2011[1]…

One of the primary points of this graphic is the quadratic fit of one data set (CW06) overlaid on all the other data sets.  The message that you are to receive is that these various sets of sea level data all tell the same essential story.  The falseness of this claim was discussed in “Quadratic fits of laughter.”

But let’s take Rahmstorf at his word.  Let’s agree with him that these sea level data sets all tell essentially the same story.  R2011′s big point is that the Rahmstorf model is “robust” given a variety of different historical data sources.  So it seems a tad bit strange that after going to all the trouble to point out these various sea level data sources and their similarities, he only gives the projection results of his model for three of them (CW06[2], CW11[3], and JE08[4]).

Of those three input sea level data sets, only two of them give similar sea level projections for the 21st century.  The outlier which results from CW11 shows significantly lower sea level projections.  Because of this, the outlier must be rejected (according to R2011), even though Church and White, the authors of both CW06 and CW11, clearly think the CW11 data is an improvement over their Cw06 data.

What about some of the other sea level rise data sets shown in R2011′s figure 1?  What type of 21st century sea level projections do they yield when inserted into Rahmstorf’s model?

Holgate’s sea level data

Let’s consider the sea level rise data of Simon Holgate.    The above image shows Holgate’s 2004 data[5], labeled HW04.  As I have previously pointed out, R2011 oddly includes Holgate’s 2004 data but ignores his 2007 data[6], H07.  I will consider both.  In my previous post I showed the results of Rahmstorf’s model when either CW06 and CW11 are input with six different combinations of reservoir storage and ground water depletion inputs.  The following two graphs show the results in the same format using HW04 and H07 (instead of CWo6 and CW11) with the same combination of reservoir storage and ground water depletion inputs.  I have kept the horizontal axis scaling the same as in the previous post to highlight the different results when Church and White data is used and when Holgate data is used.  Data files with all the specifics of this data are at the bottom of the post.

FIGURE 2. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP45 emissions scenario (Moss, 2010)[7] for Holgate sea level data coupled with various combinations of reservoir storage and groundwater depletion data inputs.

FIGURE 3. Sea level rise projections for the 21st century based on my implementation of Rahmstorf’s model under the RCP85 emissions scenario (Moss, 2010)[7] for Holgate sea level data coupled with various combinations of reservoir storage and groundwater depletion data inputs.

For comparison, here are the previously posted results using Church and White sea level data…

 RCP45

 RCP85

Hmmm…

Didn’t R2011 imply that those various sea level data sets shown if figure 1, above, told the same essential story?  Yes, I believe he did!  That is why they overlaid the same quadratic fit onto all of them.

And didn’t R2011 say that their model was “robust?”  Yes, I am quite certain that they did!  In fact the word “robust” was in the title of their paper, and they said…

“We determine the parameters of the semiempirical link between global temperature and global sea level in a wide variety of ways…We then compare projections of all these different model versions (over 30) for a moderate global warming scenario for the period 2000–2100. We find the projections are robust“

and

“we will systematically explore how robust semi-empirical sea level projections are with respect  to the choice of data sets”

So, they claim to use “a wide variety of ways” to look at “all these different model versions (over 30).”  They show plots of seven different sea level data sets and imply their similarity.  But they only show projections based on three of them.  Then they reject the projections based on one of the three, even though it is arguably the best sea level data of the bunch.

What do they say about their model’s projections based on the ”wide variety” other sea level data sets that look so good overlaid with the same quadratic fit…?

Cricket. Cricket.

How would R2011 reject the projections based on the Holgate data?

How would R2011 reject the projections based on the Holgate data that I have shown above in figures 2 and 3?  Well they would undoubtedly point out that the fit parameter, To (the so called baseline temperature, is way too low.  Recall, R2011 finds To to be on the order of -0.4 °C (below the 1950 to 1980 global average).  When Holgate’s sea level data is used, To is on the order of -4.0 °C.  Hey Rahmstorf, don’t blame me, its your model!

Maybe one of these days I will write a justification for a large negative To.  It is really quite simple.  But I am going to conclude for today.

Which of the many projections do I endorse?

Which projections are better – the ones based on CW06, CW11, JE08, HW04, or H07?  None of them.  As I have pointed out over and over, the Rahmstorf model is bogus, bogus, bogus.  I have now shown, again, that it is also not robust.  It is only marginally better than a random number generator.  HIgher temperatures would likely lead to higher sea levels, but Rahmstorf’s model is useless in determining how much.

Data files with specifics of of my implementation of Rahmstorf’s model using Holgate sea level data

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: none
Result files…
Summary: vr-summary-121110-165152.doc
Inputs: vr-input-image-121110-165152.png
Fit: vr-fit-image-121110-165152.png
Projections: vr-projections-image-121110-165152.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-121029-132349.doc
Inputs: vr-input-image-121029-132349.png
Fit: vr-fit-image-121029-132349.png
Projections: vr-projections-image-121029-132349.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-121029-132148.doc
Inputs: vr-input-image-121029-132148.png
Fit: vr-fit-image-121029-132148.png
Projections: vr-projections-image-121029-132148.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Chao 2oo8
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-121105-230616.doc
Inputs: vr-input-image-121105-230616.png
Fit: vr-fit-image-121105-230616.png
Projections: vr-projections-image-121105-230616.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Pokhrel 2012 extrapolated back to 1900
Ground water depletion: Pokhrel 2012 extrapolated back to 1900
Result files…
Summary: vr-summary-121029-133403.doc
Inputs: vr-input-image-121029-133403.png
Fit: vr-fit-image-121029-133403.png
Projections: vr-projections-image-121029-133403.png

Sea level data: Holgate and Woodworth 2004
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-121029-132906.doc
Inputs: vr-input-image-121029-132906.png
Fit: vr-fit-image-121029-132906.png
Projections: vr-projections-image-121029-132906.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: none
Result files…
Summary: vr-summary-121029-133753.doc
Inputs: vr-input-image-121029-133753.png
Fit: vr-fit-image-121029-133753.png
Projections: vr-projections-image-121029-133753.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010 extrapolated to 1880
Result files…
Summary: vr-summary-121029-135519.doc
Inputs: vr-input-image-121029-135519.png
Fit: vr-fit-image-121029-135519.png
Projections: vr-projections-image-121029-135519.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2010
Result files…
Summary: vr-summary-121029-134334.doc
Inputs: vr-input-image-121029-134334.png
Fit: vr-fit-image-1209121029-134334.png
Projections: vr-projections-image-121029-134334.png

Sea level data: Holgate 2007
Reservoir storage: Chao 2008
Ground water depletion: Wada 2012
Result files…
Summary: vr-summary-121029-135834.doc
Inputs: vr-input-image-121029-135834.png
Fit: vr-fit-image-121029-135834.png
Projections: vr-projections-image-121029-135834.png

Sea level data: Holgate 2007
Reservoir storage: Pokhrel 2012 extrapolated to 1900
Ground water depletion: Pokhrel 2012 extrapolated to 1900
Result files…
Summary: vr-summary-121029-175833.doc
Inputs: vr-input-image-121029-175833.png
Fit: vr-fit-image-121029-175833.png
Projections: vr-projections-image-121029-175833.png

Sea level data: Holgate 2007
Reservoir storage: Pokhrel 2012
Ground water depletion: Pokhrel 2012
Result files…
Summary: vr-summary-121029-140159.doc
Inputs: vr-input-image-121029-140159.png
Fit: vr-fit-image-121029-140159.png
Projections: vr-projections-image-121029-140159.png

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[1]  Rahmstorf, S., et. al., “Testing the robustness of semi-empirical sea level projections” Climate Dynamics, 2011

[2] Church, J. A., and N. J. White, “A 20th century acceleration in global sea-level rise“,  Geophys. Res. Lett., 33, 2006

[3] Church, J. A. and N.J. White, “Sea-level rise from the late 19th to  the early 21st Century“, Surveys in Geophysics, 2011

[4] Jevrejeva, S., et. al. “Recent global sea level acceleration started over 200 years ago? ,”  Geophys. Res. Lett., 35, 2008

[5] Holgate, S. J. and Woodworth, P.L., “Evidence for enhanced coastal sea level rise during the 1990s,” Geophys. Res. Lett., 31, 2004

[6] Holgate, S.J., “On the decadal rates of sea level change during the twentieth century,” Geophys. Res. Lett., 34, 2007

[7] Moss, et. al., “The next generation of scenarios for climate change research and assessment,” Nature, 463, 2010