> Now, imagine that I read Mann’s dissertation and made those bald assertions?
Now, imagine ze Moshpit read Wegman’s report.
Comment on Questioning the robustness of the climate modeling paradigm by Willard
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Comment on Questioning the robustness of the climate modeling paradigm by A fan of *MORE* discourse
These physical principles are not complicated “Nickels”!
Remember local dynamics is chaotic; global thermodynamics is well-conditioned:
Again local weather is chaotic; global climate is well-conditioned:
Yet again that’s why the sea-level is rising, the oceans are heating (and acidifying), and the polar ice is melting … all without pause or near-term limit … despite the chaotic dynamics of local weather.
Nickels, it is a pleasure to assist your mathematical and physical understanding!
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Comment on Week in review by ATAndB
TonyB,
“I still have found no evidence that it precipitated the LIA as claimed by Mann and Miller.”
I am confused. I thought Mann erased the LIA from existence. How could he attribute the LIA that he doesn’t believe exists to a volcano?
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Comment on Questioning the robustness of the climate modeling paradigm by vukcevic
Hi Tony
Thanks for the email. I now got one up on Dr. Svalgaard, he has been trying for about 2-3 years to change the 310 year long the SSN ( sunspot record) and has not got the official change accepted, and here is ‘pseudo-science’ Vuk, just one email and the 350 CET got changed. If would be nice of the Met Office if they told me too.
I will email the appropriate people and thank them for the accepting the recommendation.
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Comment on Questioning the robustness of the climate modeling paradigm by Matthew R Marler
Rud Istvan: Matthew R Marler, it isnt documented anywhere.
Rud Istvan: MRM, your above latest comment indicates you did not read the NCAR GCM manual I referenced above. Never mind the differential equations or the algorithmic numerical approximation methods. Just read the chapter outlines to understand my point.
I wish you would make up your mind on this point. So far, I have not found anything that looks like “tuning” or parameters.
Climate model parameters have to do with guessing stuff the GCMs are inherently incapable of simulating. For illustrations from the NCAR CAM3 technical manual referenced above, here are some Chapter 4 (model physics) chapter subsection headings, all direct quotes. Prognostic Condensate and Precipitation Parameterization (humidity fail, the missing modeled tropical troposphere hotspot!). 4.7 Parameterization of cloud fraction (ah, the AR5 WG1 chapter seven cloud uncertainty). 4.9.3 Trace gas parameterization. And so forth.
So far, I have not found where those are based on “tuning” instead of physical considerations.
Here is Appendix A from NCAR/TN-464+str(2004) (by the way, is that thing available in pdf format?);
A. Physical Constants
Following the American Meteorological Society convention, the model uses the International System of Units (SI) (see August 1974 Bulletin of the American Meteorological Society, Vol. 55, No. 8, pp. 926-930).
\begin{displaymath}\begin{array}{lcll} a & = & 6.37122 \times 10^{6} \quad\mathr… …y \: air \: at \: standard \: pressure/temperature} \end{array}\end{displaymath}
{oops, the table does not display here, but there are 23 constants listed, including the dry air density at STP, and the specific heat of air at STP}
The model code defines these constants to the stated accuracy. We do not mean to imply that these constants are known to this accuracy nor that the low-order digits are significant to the physical approximations employed.
section 4.7 includes this: Convective cloud fraction in the model is related to updraft mass flux in the deep and shallow cumulus schemes according to a functional form suggested by Xu and Krueger [192]:
$\displaystyle \cfrac _{shallow} = k_{1,shallow} ln(1.0+k_2 M_{c,shallow})$ (4.170)
$\displaystyle \cfrac _{deep} = k_{1_deep} ln(1.0+k_2 M_{c,deep})$ (4.171)
where $ k_{1,shallow}$ and $ k_{1_deep}$ are adjustable parameters given in Appendix C, $ k_2 = 500$, and $ M_c$ is the convective mass flux at the given model level.
Then Appendix C contains in total:
C. Resolution and dycore-dependent parameters
The following adjustable parameters differ between various dynamical cores and model resolutions in CAM 3.0.
Table C.1: Resolution and dycore-dependent parameters Parameter FV T85 T42 T31 Description
$ q_{ic,warm}$ 8.e-4 4.e-4 4.e-4 4.e-4 threshold for autoconversion of warm ice
$ q_{ic,cold}$ 11.e-6 16.e-6 5.e-6 3.e-6 threshold for autoconversion of cold ice
$ k_{e,strat}$ 5.e-6 5.e-6 10.e-6 10.e-6 stratiform precipitation evaporation efficiency parameter
$ RH_{\min}^{low}$ .91 .91 .90 .88 minimum RH threshold for low stable clouds
$ RH_{\min}^{high}$ .80 .70 .80 .80 minimum RH threshold for high stable clouds
$ k_{1,shallow}$ 0.04 0.07 0.07 0.07 parameter for shallow convection cloud fraction
$ k_{1,deep}$ 0.10 0.14 0.14 0.14 parameter for deep convection cloud fraction
$ p_{mid}$ 750.e2 250.e2 750.e2 750.e2 top of area defined to be mid-level cloud
$ c_{0,shallow}$ 1.0e-4 1.0e-4 2.0e-4 5.0e-4 shallow convection precip production efficiency parameter
$ c_{0,deep}$ 3.5E-3 4.0E-3 3.0E-3 2.0E-3 deep convection precipitation production efficiency parameter
$ k_{e,conv}$ 1.0E-6 1.0E-6 3.0E-6 3.0E-6 convective precipitation evaporation efficiency parameter
dif4 N/A 1.0e15 1.0e16 2.0e16 horizontal diffusion coefficient
I can see why you don’t quote from this sucker.
But all things considered, I do not find “tuning” in the sense most people understand it, but consideration of physics, standard physical constants, and other published literature. With evidence of changes from CAM 3.0, perhaps you could say that some of the parameter values were changed in light of model performance (“tuned” to a degree, at least, in a manner of speaking), but mostly this looks like thinking carefully and at length about the physics.
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Comment on Week in review by Jeff Norman
” I think he hooked up with people far below him in skills.”
+1/2
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Comment on Week in review by Tonyb
ATS and B
Dr Mann always believed there was an lia but that it was limited and localised. He did somewhat review his pOsition and accepted there was a larger variation than he had at first believed but still somewhat less than that believed by other researchers.
His paper here looks at the 1258 volcano which didnt show up in tree rings but should have done, as some believe the volcano caused severe cooling and that it led to the decline into the lia. Dr Mann came to see this date as significant
http://www.meteo.psu.edu/holocene/public_html/Mann/articles/articles/jgrd50609.pdf
Having examined the sorts of contemporary observations that Mosh derides as anecdotal it is apparent that there had already been a decade of cold weather prior to the volcano eruption and temperatures warmed up shortly afterwards.
But then, what do those who were there at the time know?
Tonyb
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Comment on Questioning the robustness of the climate modeling paradigm by Tonyb
Vuk
Yes, there is no doubt the CET record was changed thanks to your diligence. Whilst small, The changes are still larger than the tiny differences that mark whether the hottest temperatures in the record is THE hottest or in the top ten.
The met office were circumspect in their handling of the 2014 data and they have been receptive to your work on CET so credit to them as well as you.
Tonyb
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Comment on Questioning the robustness of the climate modeling paradigm by Willard
> So, the hypothesis is tested by a formalisation of the hypothesis itself.
So now GCMs are used to test AGW.
Fascinating.
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Comment on Week in review by Steven Mosher
“Having examined the sorts of contemporary observations that Mosh derides as anecdotal it is apparent that there had already been a decade of cold weather prior to the volcano eruption and temperatures warmed up shortly afterwards.”
That is not my argument.
1. I have yet to see how the “observations” are turned into numbers
2. I have yet to see how the quality of the “observations” are ascertained.
3. I have yet to see how the process of turning ‘it was cold” into a number has been validated.
you know, I’ve yet to see the science.
nothing wrong with estimating temperature from a written record ( regardless of Cripwell type argument ) but one has to show the work.
And show that any reader of the document would come to the same numerical answer.
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Comment on Questioning the robustness of the climate modeling paradigm by HR
I have no personal knowledge of this guy but reading his blog makes me think he’s open minded, I’ll suggest Isaac Held would support a rigorous review of climate models.
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Comment on Questioning the robustness of the climate modeling paradigm by A fan of *MORE* discourse
Betablocker, your concerns are addressed in the reply (above) to “nickels.”
In a nutshell local dynamics (namely “weather”) is chaotic; global thermodynamics (namely “climate”) is well-conditioned
Betablocker (and nickels too), it is a continuing pleasure to assist your understanding of the Bakker/Hansen/Oreskes thesis. Namely, that thermodynamics is primary, while numerical models are secondary, in regard to the scientific understanding of climate-change!
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Comment on Questioning the robustness of the climate modeling paradigm by nickels
So the claim is that even tho we cannot compute local weather. If we do so, everywhere, and sum all the results they will be correct?
So, in other words, if we run a climate simulation, and 1 month out the solution has 100% error (which it will) nevertheless averaging we will have the correct climate.
Well, no.
Let me explain to you how mathematical modeling works.
1) You have reality.
2) you have your model.
3) You run your model. It begins to diverge from reality. Before it completely diverges some things (like global averages) might still have some accuracy, which can be demonstrated by a-posteriori analysis.
4) Your solution finally diverges completely.
5) Your solution is worthless except for making pretty pictures and feeding the CAGW propaganda machine.
There is no diverging completely from the local solution but still maintaining some sort of global accuracy.
This is nonsense.
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Comment on Questioning the robustness of the climate modeling paradigm by Willis Eschenbach
Kenneth, first, a most excellent comment. I do enjoy a man who runs his own numbers.
Regarding the models and the equilibrium or the transient climate sensitivities, (ECS & TCS), over a series of posts and with invaluable assistance from commenters I established that the global temperature output of the models is equivalent to a lagged linear function of the forcings. See my posts:
<a href="http://wattsupwiththat.com/2010/12/02/testing-testing-is-this-model-powered-up/" rel="nofollow"><b>Testing … testing … is this model powered up?</b></a>
<a href="http://wattsupwiththat.com/2010/12/19/model-charged-with-excessive-use-of-forcing" rel="nofollow"><b>Model Charged with Excessive Use of Forcing</b></a>
<a href="http://wattsupwiththat.com/2011/01/17/zero-point-three-times-the-forcing/" rel="nofollow"><b>Zero Point Three times the Forcing</b></a>
I went on to using that to look at climate sensitivity
<a href="http://wattsupwiththat.com/2013/05/21/model-climate-sensitivity-calculated-directly-from-model-results/" rel="nofollow"><b>Model Climate Sensitivity Calculated Directly From Model Results</b></a>
Regarding your comment on "obtaining global mean TOA radiation data from gridded nc file data", what you need may be available in the CERES data. It's available <a href="http://ceres.larc.nasa.gov/order_data.php" rel="nofollow"><b>here</a></b>. My first of many uses of the CERES data was <a href="http://wattsupwiththat.com/2012/06/12/observations-on-toa-forcing-vs-temperature/" rel="nofollow"><b> Observations on TOA Forcing vs Temperature </a></b>.
If all you need is some form of the gridded monthly variation in TOA solar, let me know and I'll extract it from the CERES nc data as a 1° x 1° grid.
Finally, if you are using R, the package "ncdf" contains the functions to read/write the .nc files.
Best wishes in your explorations,
w.
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Comment on Questioning the robustness of the climate modeling paradigm by R. Gates
“Gates writes- “general intensification of the hydrological cycle as accompanies all rising GH gas climates”
You make many unsupportable claims.”
_____
Suggest you do a bit more research on the subject of natural feedbacks to rising GH gases before making this ignorant claim. The rock-carbon cycle and intensification of the hydrological cycle are natural ways for the sequestration of carbon to occur. Problem is, the Human Carbon Volcano has vastly over-whelmed this natural negative feedback as each is working on completely different time scales. The net result is that, without significant downscaling of the rate to which humans are transferring carbon to the atmosphere, we’ll have to commit to serious sequestration of carbon ourselves.
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Comment on Questioning the robustness of the climate modeling paradigm by Matthew R Marler
Group of Physicists: Their version of the Second Law could be used to “prove” that water could flow up a mountainside provided that it flowed further down on the other side.
It would have to be in enclosed watertight pipes, as with siphoning. Or is there a maximum height (say 14 feet of elevation) over which that would work?
The Earth receives a steady stream of energy from the sun, some of which gets stored in tight chemical bonds in cellulose, sugar and bones. What are the implications of this steady stream of incoming energy for second law arguments in the atmosphere?
Until those promulgating the hoax can do that they have contrary evidence staring them in the face.
Could you avoid the word “hoax”, which, like “lie”, implies that they know that what they are promulgating is wrong?
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Comment on Questioning the robustness of the climate modeling paradigm by Matthew R Marler
R. Gates: <i>The rock-carbon cycle and intensification of the hydrological cycle are natural ways for the sequestration of carbon to occur. </i>
How much additional energy (or power, if you prefer) is consumed by the intensification of the hydrological cycle of which you just wrote?
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Comment on Questioning the robustness of the climate modeling paradigm by Matthew R Marler
R. Gates: They are excellent at uncovering dynamics and displaying long-term trends, and actually have far less systematic errors than many “skeptics” would posit:
Where is the evidence that the display of long-term trends by GCMs has been “excellent”?
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Comment on Week in review by Tonyb
Mosh
We are fortunate in having a number of continuous contemporary observation and for the period surrounding 1258 they are consistent in placing that year into context as a continuation of what went before not a radical departure from it.
I have told you at least three times that I follow the van engelen, buisman and Unsen formula of splittimg years into various categories of cold and warmth which was detailed in Phil jones ‘ book ‘ history and climate’ page 105 .
I also emailed this information to you several years ago.
How do you validate the quality of the individual temperature observations used in BEST, some of which come from rather dubious sources?
Camuffo dismissed many of the European historic observations and they were taken by apparently more reliable people and instrumentation than fills much of of the BEST historic database. The figures are often just as anecdotal as my written accounts.
Tonyb
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Comment on Questioning the robustness of the climate modeling paradigm by nickels
@gates
But you do agree that climate models diverge from reality pretty fast, like in a month or so, yes?
I mean, otherwise we could predict the weather long term.
So, how is it that models which diverge completely from the solution still provide useful information?
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