Arguments
Recent Comments
Prev 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 Next
Comments 7401 to 7450:
-
Nylo at 16:54 PM on 3 July 2020Hansen's 1988 prediction was wrong
MA Rodger @57 I think you are making a mistake but I cannot blame you. I was taking for granted some of the things claimed in the main article but I have done some calculations and it happens that they were not true!
This is how Hansen describes the evolution of the CH4 increases in Scenario A, the one with the most emissions, I copy literally:
"CH4, based on estimates given by Lacis et Al. [1981], increases from 1.4ppbv in 1958 at a rate of 0.6% yr-1 until 1970, 1% yr-1 in the 1970s, and 1.5% yr-1 thereafter".
By this description, if you do the calculations, the yearly increase by 1970 would be 1.5ppbv, then 1.66ppbv by 1980... etc (continue to multiply by 1.015 each year) until 3.01ppbv per year today, in 2020. This is, I repeat, the evolution of CH4 concentrations in Scenario A. The reality, what the data shows, is that today's CH4 concentrations are increasing by more than 5ppbv per year, every year in the last decade, and some years almost 10ppbv, averaging +8ppbv per year. My data comes from here, if you have different data feel free to share:
https://www.methanelevels.org/
Now, I don't know what is the starting methane concentration that Hansen is using. I highly doubt that he is using the concentration in 1958 because we already knew by 1988 that the progression in the methane levels of the model would have been completely wrong. But no matter what his starting concentration is, he would get a total increase of +70ppbv in the 30 years following 1988. And what we have witnessed is more than twice that ammount. More than twice the methane increase of Scenario A. Therefore not only do we have a worse increase in CO2 than Scenario A, we also have a twice as bad increase of Methane than Scenario A. And they are the main contributors according to Fig b2. The only one that is lower than expected by Hansen is CFCs.
As you say, the effect of the extra 0.5ppm per year of CO2 would be quantified by Hansen as having a 0.027 additional forcing. With a similar calculation, the twice-as-big-as-1980 increase that Hansen expected to have by now in Scenario A (3ppbv/year vs a starting 1.5ppbv/year) would have had a +0.06ºC forcing per decade, and given that the real, measured, increase in concentration has been twice as big as what Hansen expected, we are getting another +0.06 forcing compared to Hansen expectations in our last decade. So we are already at a +0.087ºC/decade forcing compared to Hansen's scenario A, if we add together the extra CO2 and the extra CH4.
Now, Hansen expected a lower forcing from CFCs than from methane, like you have said. This means that if the real forcing of Methane has doubled, then it would not matter even if the CFCs had stopped increasing in 1988, reducing their impact to zero. The effect of Methane alone, would still be larger than what Hansen predicted for the two. And again, we are talking about scenario A, not B!
Emissions of the largest contributor by Hansen's expectations are 26% bigger than scenario A. Emissios of the second largest contributor by Hansen's expectations have been twice as big (+100%) as scenario A. Are we saying that the reduction of CFCs, the third largest contributor, have the power to counter all of that? Even if it had such a power, we would still be at scenario A's expected increase of temperatures, not B's!
I beg you to tell me where is it that I did wrong the calculations. Because I cannot find it.
-
Deplore_This at 12:20 PM on 3 July 2020Models are unreliable
@scaddenp
Thank you for your response. I'll look at the CMIP6 and respond to you. But for now I have a quick question; When you say "us", what organization are you associated with?
Thank you.
-
scaddenp at 12:13 PM on 3 July 2020Models are unreliable
You can find the list of participants in the CMIP6 project here (via the map). CMIP models are what inform IPCC reports.
-
scaddenp at 12:07 PM on 3 July 2020Models are unreliable
Looking at CMIP6, I see about 100 different climate models from 49 modelling groups worldwide. Most of climate science is not building AOGCMs. Vast resources are required just to observe climate. I dont do GCMs but the models I work with and maintain involve people learning on the job not products of university courses. I expect the university to provide us with graduates who have the necessary skill base (physics, coding, numerical analysis) to be able to contribute and learn by getting their hands dirty improving the code or adding new features Models are developed by slow evolution.
On a side note, as far as I can see EPA doesnt do any climate modelling of the AOGCM. I may be mistaken, but it also doesnt strike me as something that would be part of their brief.
Most people dont have access to the kind machinery required to run an AOGCM. You would be better getting the code from an earlier generation of models and starting with running that. You might want to look at the isca framework or an old model E. Tom has also suggested the EDCGM which looks an excellent way to learn how these are put together and get a feel for code. Lots of university resources based on it and fits with your desire to understand the models.
"But there are scientists who disagree with their conclusions" Want to tell more about these people? I assume you have investigated whether they have the requisite background to make useful criticism and not just reflecting an ideological bias.
-
Deplore_This at 11:55 AM on 3 July 2020Models are unreliable
@Dayton
It's OK if your answer is "no". That isn't a problem. No worries.
-
Deplore_This at 11:38 AM on 3 July 2020Models are unreliable
@Dayton 1184
That’s not very nice or respectful. I thought this was a scientific community. Please just answer my question; do you know of any course that is comparable to Penn State's METRO-523?
Thank you.
-
Tom Dayton at 11:19 AM on 3 July 2020Models are unreliable
Deplore_This: Clearly you are not actually interested in learning anything.
-
Deplore_This at 11:17 AM on 3 July 2020Models are unreliable
@Dayton 1179, 1180, 1181 and 1182
Thank you for your responses. All of the other courses that reference GCM's that I've seen don't give me the opportunity to get under the hood of the models and determine for myself how they work. Your suggested Module 4: Introduction to General Circulation Models How Good are GCM's? is a perfect example. https://www.e-education.psu.edu/earth103/node/1013 So is Tom Osborn's page. There are explanations but there is no way I can hands on understand the nuances of the models and confirm their observations.
My objective is to understand the models themselves. I apologize in advance if this sounds rude but I really don't care what your opinion is concerning whether I have the sufficient prerequisites to take a course in this subject. Quite candidly, you're wasting your time trying to steer me in a different direction. I know where I want to go and I'm smart enough to determine if I meet the prerequisites for a particular course and to negotiate any shortfall with the school. My question is very simple, do you know of any course that is comparable to Penn State's METRO-523?
Thank you again for your help and I apologize if I am being too coarse.
-
Tom Dayton at 11:07 AM on 3 July 2020Models are unreliable
Deplore_This: Tim Osborn has an excellent web page Climate Models for Teaching.
-
Tom Dayton at 09:59 AM on 3 July 2020Models are unreliable
Deplore_This: The very first thing you might do is take Module 4: Introduction to General Circulation Models, from the Earth in the Future series.
-
Tom Dayton at 09:52 AM on 3 July 2020Models are unreliable
Deplore_This: Your own description of your background makes it sound like you are unlikely to benefit much from a specialized course in climate modeling, due to your lack of the prerequisite knowledge. So again I urge you to take some other courses, or if you really are dead set on diving into specifically GCMs (versus other types of models and theories), then get a textbook. Before you even attempt to write code for a GCM, or even look at the code of a GCM, experiment with the easier to use human-computer interface of the EdGCM project, whose underlying GCM is the actual GISS Model II GCM. If you want to look at the code of that underlying GCM, you can get it here.
-
Tom Dayton at 09:45 AM on 3 July 2020Models are unreliable
Deplore_This: You are finding few courses because you are looking too narrowly for courses labeled specifically "Climate Modelling." As scaddenp explained, there are many components of GCMs, and they are used also independently from GCMS. Also, GCMS use theories, models, and computer code from multiple sub-disciplines.
So nearly any course you take in atmospheric science will give you some knowledge about GCMs. If you try to take a course specifically about GCMs, you will need to have that prerequisite knowledge in order to gain the insight you say you want to gain. Just look at the Penn State meteorology course list, for example. In addition to the Modelling the Climate System course you wrote is "no longer offered," are many other courses that include solidly relevant knowledge for climate models. (By the way, universities do not offer all listed courses in every academic period. So that course unlikely is discontinued, because unlikely they would list it at all. It might happen to not be offered right now when you want it.) Just one example is course METEO 520: Geophysical Fluid Dynamics, whose prerequisites are vector calculus and differential equations.
-
Deplore_This at 08:33 AM on 3 July 2020Models are unreliable
@scaddenp 1177
Thank you for your response. I don’t know what an AOGCM computer model looks like under the hood which is why I am looking for a university course on them. I have a minor in math, I took differential equations, I’ve taken Physics in Engineering school, I’ve not only written computer code but in my career I’ve project managed the creation of multi-million dollar IT systems. I wasn’t planning on writing a half million lines of code but I haven’t seen anything yet that would make me believe I would be in over my head working with an AOGCM model. But I haven’t been successful finding a way to actually work with one.
I am somewhat confused by your comment. I would think there would be a plethora of courses on climate modeling otherwise how would all of the climate scientists learn how to construct and evaluate them? We have legions of climate researchers at the EPA, who taught them?
I understand the paleoclimate approach but I am specifically interested in understanding the more sophisticated AOGCMs, specifically their fidelity on climate sensitivity. I’ve gone through the WG1 report and read the results and conclusions. But there are scientists who disagree with their conclusions. To understand the competing arguments I’m trying to educate myself on the models they are using and how they are used. I thought that taking a university course on the subject would be a good approach but not finding one I am stuck. How do the climate researchers at the EPA get the knowledge of which expert and model to believe? What course would they take?
Thank you again for your help.
-
scaddenp at 07:44 AM on 3 July 2020Models are unreliable
Climate models are around 0.5 million line of code created by discipline experts for each of the climate processes. Starting from scratch to write your own is somewhat ambitious. Note that they are not statistically based so I am skeptical that a background in stats or operations research would help you much. The background requirement is numerical solution to systems of partial differential equations. No shortage of courses of these.
I cannot comment on US university or course, but going into serious atmospheric sciences here would be based on undergraduate degree in physics and maths. The numerical solution of systems of partial differential equation is specialist area of mathematics - numerial analysis. Our institute (geology/geophysics) typically has mathematicians, programmers and subject specialists working together on problems of this kind of class.
I still think predicting the base level of future isnt that hard. If surface irradiation increases, then surface gets warmer. The complicated bit is by how much will feedbacks magnify that effect. (Equilibrium Climate Sensitivity) And yes, predictions of future are based are done by AOGCMs. However, there are also paleoclimate constraints on climate sensitivity. Too crude compared to models but good enough to cause serious concern. Again, the WG1 report is good place to find the papers on emperical constraints on climate sensitivitiy. -
nigelj at 07:21 AM on 3 July 2020House Democrats eye 2021 with comprehensive climate action plan
I live in a parliamentary democracy, but I understand that Americas 'Senate' is apparently supposed to be a brake on power, like the upper house in some parliamentary systems. I think its a great system that has a brake on power, but it seems strange that you need a senate when the courts can apparently strike down legislation. I mean how many brakes on power do you need?
It also seems hard to understand why one party can win both the presidency and congress then have all its legislation proposals anulled by a senate that has a majority of members affiliated towards the other party - and with this makeup locked in for lengthy periods of time. What is the logic behind this arrangement?
And do the brakes on power even work, because the president seems to be able to get away with almost anything. Thats how it seems to us right now.
From the outside of America looking in its all very strange. But I wish the Democrats luck with their sensible sounding proposals. Probably quite good to have specific propoosals and also a more general price on carbon which maximises the chances of at least something getting thru the senate.
There is analysis in our media here of how green projects like these potentially create a lot of new jobs, which is very timely given the covid 19 problem, which looks like its hanging around for quite a while yet. Voters might want to bear this in mind.
-
Deplore_This at 03:49 AM on 3 July 2020Models are unreliable
@ ClimateDemon 1173
Thank you for your response. I have a background in Operations Research developing and using models and simulations for other disciplines. This is partly why the models used for climate change predictions are of interest to me. I see that parts of your comment has been censored but my understanding is that AOGCM climate simulation models are in fact used to generate long-term predictions which in turn are used to justify carbon taxes and regulations. This is why I am challenging the validity of the models.
I think I’m posting in the correct article which states the science is:
“While there are uncertainties with climate models, they successfully reproduce the past and have made predictions that have been subsequently confirmed by observations.”So I am trying to understand what are these uncertainties as well as how well these models hindcast by acquiring an understanding of and hands on use of these AOGCM. I was looking for a university course that teaches this subject to climate researchers.
You threw me off course by stating that models that accurately predict climate change are a set of differential equations because I haven’t seen that courses in differential equations or even calculus for that matter are course requirements for degrees in atmospheric sciences. So my questions are how are climate researchers taught to use and evaluate these models? And what course can I take that teaches the models that are used to generate long-term predictions which in turn are used to develop public policy?
Thank you again for your help.
-
Deplore_This at 02:45 AM on 3 July 2020Models are unreliable
@Dayton 1169, 1170, 1171 and 1172
Thank you for your response. I have spent considerable time studying climate theory and when it comes to predicting future climate change everything I’ve seen is that they are all based upon AOGCM climate simulation models like those evaluated in the IPCC WG1 report you referenced. I am trying to take it to the next level to actually understand and scrutinize the models themselves.
Rather than teaching myself with an open-source model and a text book I am looking to enroll in a university course that will “provide instruction on development of climate models and… the use of climate models for understanding the dynamics of the climate system processes and behavior”. This is the description for METEO 523 at Penn State:
http://www.met.psu.edu/intranet/course-syllabi-repository/2020-spring-syllabi/meteo-523This is the only course I’ve found on the subject and unfortunately this course is no longer offered. So I am asking if anyone on this board has a recommendation of a similar course that I can enroll in.
Thank you again for your help.
-
MA Rodger at 01:25 AM on 3 July 2020Hansen's 1988 prediction was wrong
Nylo @56,
I'm with you part the way on your first point. (And your second point, the comparison with Scenario C; that seems a step too far.)
On the first part of the first point, the value given for Scenario B CO2 increase post-2010 in Hansen et al (1988) (PDF p21) is 1.9ppm/y, the MLO-measured CO2 ran at 2.4ppm/y and that does translate into being 26% above Scenatio B.
From here, I initially assumed you are looking at Fig b1 which gives a value for CO2 at 1.2 and a combined value for CFCs & CH4 of 0.46 or 38% of the value given for CO2, or 2.6x the given CO2 value. So, firstly, I am not sure where you get the "4 times the sum" and , secondly, I'm not sure why you woud be taking numbers from Fig b1. Indeed, I'm not exactly sure what Fig b1 is meant to be demonstrating. The values are described as "arbitrary" but, in the case of CO2 give a value of non-feedback warming for a doubling of CO2 (315ppm→630ppm). The CFC11&12 is for 0→2ppb each and the CH4 also for doubling although there are complications with such a stand-alone value for CH4.
I think you should be examining Fig b2 which provides the values for the decadal increments of forcing - for the 1980s CO2 0.08, CH4 0.03 & CFC11&12 0.2. Thus, back-of-fag-packet, the 2010s CO2-above-ScenarioB of +0.5ppm/y equates to a third of the 1980s annual increase or 0.027 of the 0.8 from figb2. If you venture to examine the NOAA AGGI numbers, you'll find CFC11&12 today remain at 1990 values and the CH4 increase post-2010 is a third the 1980s increase suggesting forcing below ScenarioB of -0.2 & -⅔ of 0.3 = -0.4. So by that reckoning, the additional 26% CO2 forcing would sit below the lost CFC & CH4 forcing, not "ABOVE".
Or a simpler analysis using just AGGI, the missing CO2 forcing 2010-on would be 20.6% of the additional CO2 forcing = +0.065Wm^-2, or perhaps double that for all three of the three post-1990 decades combined. The CH4/CFC11&12 forcing through the 1980s was +0.126Wm^-2 which would continue at or above that value for the following 3 decades in Scenario3, so totaling +0.378Wm^-2. But the actual forcing is given over this period 1990-2019 as +0.056Wm^-2 so relative to ScenarioB forcing that is -0.322Wm^-2 from CH4/CFC11&12 and with the extra CO2 forcing included yielding (-0.322 + 2x0.065 = ) -0.192Wm^-2. It works out again with less forcing, not "ABOVE".
-
Eclectic at 22:35 PM on 2 July 2020Models are unreliable
ClimateDemon @1173 ,
Your "CO2 control knob" ideas fall flat, because you have made the critical mistake of looking at climate models only.
If you look at the bigger context, and examine the paleological evidence, then it becomes very evident CO2 has exerted a major "control knob" effect on planetary climate. That is also reinforced by the empirical evidence of modern historical data.
-
ClimateDemon at 21:53 PM on 2 July 2020Models are unreliable
I agree that over the past century, the state-of-the-art of modeling and simulation has grown by leaps and bounds, especially since the development of supercomputers in the 1980s. They have been valuable tools for research and development in general, not just climate science. It should be noted, however, that such models are meant to aid scientists in their understanding of certain phenomenon, possibly identifying causes and even making short-term general predictions. They are NOT meant for government use to generate long-term predictions (which no model can do reliably), and use them as a basis for carbon taxes and regulations.
In order for a model to accurately predict climate change, it must take into account the dynamics of atmospheric fluid motion, realizing that the atmosphere is not in thermal equilibrium. [If it were in thermal equilibrium, there would be a uniform temperature and humidity over the entire surface with no winds nor storms.] This involves solving the time-dependent equations of mass balance (equation of continuity), momentum balance (Navier-Stokes equation), and energy balance which is what is done in the climate General Circulation Models. This is a set of partial differential equations that are first order in time which are generally solved in time by some type of finite difference method given the initial conditions. Note that the terms "forcings" and "feedbacks" aren't even in the vocabulary. Therefore, if there is H2O vapor in the air, its greenhouse effect is accounted for in the energy balance equation. If there is CO2 in the air, its greenhouse effect is also accounted for in the same energy balance equation. The contributions from the H2O greenhouse warming will, of course, be much greater than those of the CO2 warming, but there is nothing to indicate that CO2 has any "control knob" effect.
The only model that predicts AGW and the CO2 control knob is the one used by Lacis et. al. 2010, the staff here at SkS, or wherever AGW is preached. This is a highly oversimplified, zero dimensional model in which the earth's temperature is represented by a single scalar value T, and the H2O vapor concentration is determined by the Clausius-Clapeyron equation at temperature T. This means that the entire globe is rigidly held to this one fixed value of temperature and corresponding value of humidity, which we know is false. Furthermore, it assumes (through the Clausius-Clapeyron equation) that H2O in its vapor state and condensed states are in constant thermal equilibrium with each other, which is also false. At this point, AGW advocates generally understand the (invalid) argument as to how CO2 becomes the controlling GHG even though it is much weaker than H2O vapor, so I won't repeat it here. In general, those who preach the doctrine that a non-condensable GHG can only be a “forcing” and a condensable GHG can only be a “feedback” have been duped by the fallacies and self-inconsistencies of this “carbon-in-control” model. Another false manifestation of this model is the frozen earth scenario where all CO2 is eliminated, and as a result, there is no non-condensable GHG in the atmosphere to provide the temperature forcing needed to put H2O vapor, the stronger GHG, in the air. As a result, the entire terrestrial greenhouse effect collapses since there isn’t any of either GHG in the atmosphere, thereby leaving an iceball of an earth behind. Aside from the highly anti-intuitive nature of this prediction, it would be totally impossible to test it.
So what should we do about this CO2 control-knob theory? Do we say "It's what the science says, so we must accept it since we are scientists.", or do we do some critical thinking and say "It took several false assumptions to make the control knob argument, so there are very likely problems with it."?
Moderator Response:[DB] As this iteration of this user account is new, please read the Comments Policy linked near each Comment Box. Pay particular attention to the prohibition against sloganeering and note that assertions made must be accompanied by citations to credible evidence, with the more egregious the claim the higher the Burden Of Proof is upon you, the asserter, to fulfill that burden. Simply saying "ugh-ugh" is insufficient. Please compose future comments to better comport with the Comments Policy.
Sloganeering snipped.
-
Nylo at 21:25 PM on 2 July 2020Hansen's 1988 prediction was wrong
Thank you very much for the update.
MA Rodger @54, thanks a lot for the explanation. You say that the increased CO2 emissions compared to scenario B is compensated by the drop in emissions of CFC and CH4. Page 21 of the PDF of James Hansen's article, which is part of Annex B, shows (literally) that in Scenario B he expected a constant increase of 1.9ppmv of CO2 yearly from 2010 onwards. But the average yearly increase of CO2 that we have witnessed since 2010 is 2.4ppmv yr-1. That's a whopping additional 26%. In the same page, James Hansen's article has a graphic showing the relative contribution of the different gases, in which CO2 contributes 4 times the sum of the contributions of CFCs and CH4. Even if we had 100% halted the increase of these gases as soon as 1988 and reduced their influence to zero, the additional 26% of CO2 would put the total influence ABOVE the combined effects of all gases predicted by Hansen. But not only have we not reduced the emissions of those gases to zero, the concentration of both gases is today quite higher than in 1988, which must have a warming effect.
Scenario C also shows that the biggest influence for the dramatic drop in expected temperatures compared to Scenario B is CO2, because it is CO2 that experiences a huge change compared to Scenario B whereas CFCs and CH4, while smaller, do not show such an abrupt difference. So clearly Hansen attributes to CO2 a much bigger effect on temperatures than the other 2 gases. And he expected a waaaaaay smaller increase of CO2 in his scenario B compared to what we have witnessed, which is more according to Scenario A. It may not be fair to expect temperatures to evolve like in Scenario A as the CFCs and CH4 increases are smaller, but we should expect something between the 2 scenarios. And what we get is in temperatures is below scenario B. We are approximately 0.3ºC cooler than what would have been be expected by Hansen's models, back in 1988, with the known GHGs evolution as input.
-
michael sweet at 20:45 PM on 2 July 2020Hansen's 1988 prediction was wrong
Nylo@53:
Skeptical Science is staffed completely by volunteers. It turns out that few people can find the time to update old posts' graphs to reflect new data. That is life.
If you want to find out what the updated graph would look like you might go to the Real Climate Climate model comparison page, which is updated yearly. Their up to date graph looks like this:
Measuring carefully with my eyecrometer I findl that the data from 2017-2019 makes the model look better. If the writers were attempting to cherry pick their data they did a poor job and left off data that they should have included.
It looks like 2020 is going to be a very hot year. Perhaps when RealClimate updates their graph next January you can come back here and show us what the new graph looks like.
-
MA Rodger at 20:19 PM on 2 July 2020Hansen's 1988 prediction was wrong
Nylo @53,
The graph Fig 1 of the 'basic' OP above without the post-2016 GISS data does indeed suggest a more robust record of warming than would be the case with 2017-19 data added, but I wouldn't go so far as to describe it as being "a very red and tasty cherry". The climate forcing 1988-to-date is a little short of Scenario B and so also is the trend in global temperature. (GISS data relative to 2016, the following years sit 0.09ºC, 0.17ºC, 0.04ºC below 2016 with 2020 potentially topping 2016.)
Regarding the forcings relative to 1988, Fig 4 of the 'advanced' OP above plots 'actual' relative to the scenarios of Hansen et al. These derive from annual emissions of all anthropogenic forcings as does the 1.5% you quote for Hansen et al for Scenario A. The paper's Appendix B describes in more detail the acceleration in emissions for the various gases in Scenario A and the tailing-off that accelerations in Scenario B.
I'm not sure you are describing this change in annual emissions.
I suspect you are looking at either accumulative CO2 emissions since pre-industrial times (an increase of 69% since 1988) or solely annual FF CO2 emissions (an increase of 67% although that is reduced to 57% if LUC CO2 emissions are included). The numbers I quote are calcuated from Global Carbon Project data.
The NOAA AGGI gives the annual forcing data from GHG emissions which shows today's annual increase in forcing is slightly reduced relative to 1988 (this the net effect of increasing CO2 emissions balanced by the drop in CFC emissions and the 'hiatus' in CH4 emissions). In more detail, the annual forcing increase dropped from the 1980s into the 1990s but has since been on the rise again. So the forcing accounted in the AGGI are running below the Hansen et al Scenarion B but AGGI does not include any change in negative forcing from aerosols which will have boosted net forcing a bit over the period (as shown in that Fig 4 of the OP).
-
Nylo at 16:44 PM on 2 July 2020Hansen's 1988 prediction was wrong
Dear friends of Skeptical Science, are you planning to update the graphic to show the data through 2019? Or can we assume that you only updated the graphic until 2016 because it proved to be a very red and tasty cherry to pick?
As a separate question, why do you say that Scenario B was closest to reality? I mean, on what basis? I have read the Hansen paper through your link and Hansen was expecting our emissions to grow 1.5% per year in Scenario A, which would have led to a 52% growth by 2016 compared to our emissions in 1988. But our emissions have increased by a whopping 63% since 1988, which is far worse than what scenario A expected. So probably you are referring to something else appart from CO2 emissions to claim that Scenario B is "closest to reality". What is that sentence based on?
Thanks a lot.
-
Tom Dayton at 16:11 PM on 2 July 2020Models are unreliable
Deplore_This: I suspect you incorrectly believe that "climate models" are different from climate theory, which is why you do not want to take any of those courses that are not devoted to what you incorrectly think of as climate models. General Circulation Models (GCMs) are just instantiations of those theories in those courses and textbooks. So by learning those theories you will be learning about what you call "climate models." Please try reading Tamino's "Not Computer Models."
-
Tom Dayton at 14:15 PM on 2 July 2020Models are unreliable
Deplore_This: Perhaps the ISCA framework is what you want.
-
Tom Dayton at 13:46 PM on 2 July 2020Models are unreliable
Deplore_This: You should use one of the textbooks to inform you as you play with that model.
-
Tom Dayton at 13:42 PM on 2 July 2020Models are unreliable
Deplore_This: I strongly suggest you take some courses instead of merely reading the syllabi. if you refuse to do that, thinking you know too much already, then go ahead and skip the courses and dive into an open source model: https://www.giss.nasa.gov/tools/modelE/
-
Deplore_This at 12:25 PM on 2 July 2020Models are unreliable
@Dayton 1163, 1164 and 1165
@ scaddenp 1166 and 1167Thank you for the responses. However, I had previously found and reviewed on my own the course syllabuses for your suggested courses before posting.
Reading the syllabuses of these courses they include basic discussions of what GCM is but not how to do it. None of these courses give the student the opportunity to construct and run GCM and measure their predictive capability by hindcasting.
I am candidly stating that I am a skeptic of these models and I’m trying to understand the science. I have been frustrated that everything I find is a consensus opinion on these models but I haven’t found anything that allows me to get under the hood and see how the models work for myself and to evaluate the predictive sensitivity of these models.
I’m not looking for a book. I’m retired and have the time and the money to pay for the best university course I can take. I have the academic qualifications and professional technical knowledge and experience to dig deep into this. My problem is I haven’t found one. I’ve reviewed the curriculum of the top environmental science university programs and I haven’t found a single course. I am asking for a recommendation.
Thank you again for your response but I still don’t know where to find a course that achieves my objective. I appreciate any assistance you can provide.
-
scaddenp at 08:33 AM on 2 July 2020Models are unreliable
I would also recommend that read the chapter in the IPCC WG1 report on evaluation of climate models before getting too far into the course. (chp 9 in the latest report).
-
scaddenp at 08:26 AM on 2 July 2020Models are unreliable
Deplore_This: Not exactly sure what you mean by "climate temperature models referenced by the IPCC" but I assume you mean the GCMs used by CMIP to predict future climate (of which temperature is but variable that can be extracted). If this is the case, then note that these are the best means we have available to predict future climate, but by themselves say nothing about the validity of anthropogenic climate change. They could be completely wrong do to some fundimental algorithmic error which would affect their ability to infer the future, but say nothing about the accuracy of the physic of anthopogenic climate change.
The science does depend on other models (but not necessarily computer models), especially the radiative properties of gases and the Radiative Transfer Equations in particular. These have real-world applications and the detailed work was initially done by USAF because laser-guided bombs depend on them.
There are rather more direct ways of checking validity of science (eg empirical evidence). You can also directly measure the increase in surface irradiation. I rather suspect that you would agree that an increase in surface irradation because sun increased its output would warm the planet. The GHE can do that too. -
Tom Dayton at 07:23 AM on 2 July 2020Models are unreliable
Deplore_This, you could also simply search the internet for climate modelling textbook, and you'll get a plethora of books.
-
Tom Dayton at 07:07 AM on 2 July 2020Models are unreliable
Deplore_This, also from that simple search of the internet I quickly found a course at the U. of Washington, Swedish e-Science Education (taught in English), several by MIT, University of California Santa Cruz...
-
Tom Dayton at 06:55 AM on 2 July 2020Models are unreliable
Deplore_This: I don't understand how you could have trouble finding courses. David Archer at U. of Chicago has an online course that starts today. It was the fourth result from my Duck Duck Go search for climate modeling course class online.
-
Deplore_This at 05:57 AM on 2 July 2020Models are unreliable
I am an anthropogenic climate change skeptic because I’ve read criticism of the validity of the climate temperature models referenced by the IPCC. I am not a climate researcher by training or profession and to satisfy my scientific curiosity I’ve been trying to find a university course in climate temperature modeling including CO2 sensitivity analysis. From my undergraduate degree I have an extensive background in operations research, mathematics, computer science and basic physics and chemistry courses for Engineers. So I can’t imagine there is any computer modelling that will be beyond my ability.
I’ve looked at the undergraduate and graduate curriculum for the top US environmental science universities and have found only one course on climate modeling. Penn State offered METEO 523 in Spring 2020 and only 6 of 30 seats were filled and the course has been since dropped.
Can anyone suggest a climate modeling course I can pursue? Sorry to ask here but I’ve spent a lot of time searching and have come up short.
Thank you.
-
Eclectic at 20:20 PM on 1 July 2020Is Nuclear Energy the Answer?
Michael @156 ,
I haven't seen Shellenberger's presentations favoring extensive usage of "nuclear" (and as you do, I strongly suspect it cannot be achieved in a timely & economic manner . . . and it would be a harmful diversion of resources that would much better be spent on "renewables").
However, readers may have noted an article by Shellenberger titled: "On behalf of environmentalists, I apologize for the climate scare".
But I am not in any way recommending his article. Shellenberger's article is quite appalling in quality ~ it resembles the "holiest" of Swiss cheeses, in that it is burdened with a vast number of logical errors & misleading informations. In short, a propaganda piece. Although he appears to make an acknowledgement of AGW as a problem, he slants his message to the position that tackling AGW is non-urgent & can reasonably be postponed for decades (while other world problems get precedence). Altogether, his article fits in well with the run-of-the-mill Denialist nonsense. The same flavor, almost entirely !
-
michael sweet at 12:29 PM on 1 July 2020Is Nuclear Energy the Answer?
At post 90 in this thread I commented on a Shellenberger video. Shellenberger is a paid shill for the nuclear industry. His presentations are filled with falsehoods and misinformation.
I recommend you read Abbott 2012, linked in the OP. Abbott is a peer reviewed critique of nuclear power. Abbott shows that there is no hope of a significant (more than 5% of all power) amount of nuclear power in the future. Shellenberger has not attempted to answer the issues raised by Abbott. Who do you believe, a peer reviewed paper or an unreviewed paid shill?
I note that even Shellenberger only claims that 50% of current electricity (about 10% of all power) can be generated using nuclear power. The remainder would have to be generated by renewables.
-
Doug Bostrom at 06:26 AM on 1 July 2020Skeptical Science New Research for Week #25, 2020
That's a remarkable story, David Hawk, depressing and yet hopeful.
Thank you for sharing it.
-
Doug Bostrom at 02:55 AM on 1 July 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
Thank you, BF— we'll sort it out.
[Fixed. The original report may also be found here: https://www.epa.gov/office-inspector-general/report-further-efforts-needed-uphold-scientific-integrity-policy-epa ]
-
jhnwlk at 02:53 AM on 1 July 2020Is Nuclear Energy the Answer?
Sorry for the misspelling...that would be Shellenberger
-
jhnwlk at 02:47 AM on 1 July 2020Is Nuclear Energy the Answer?
I'm looking for a critique of the case Michael Schellenberger makes for nuclear energy. Would there be one in comments in this thread or anywhere else on the website?
-
djinghis at 21:35 PM on 30 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
@JWRebel The CDC
-
MA Rodger at 21:00 PM on 30 June 2020It's only a few degrees
Jasper @3, Yet another take.
You write "I get that a few degrees make a huge difference. I don't fully understand why a few degrees matter so much." Although a huge difference is suggestive that it does matter, I read your meaning that you are after an authoritiative take on the effects of "a few degrees" and something with a bit of meat on it.
Warming the globe by "a few degrees" will make a big difference to the climate system which has been previously reasonably fixed for millenia and so will bring unprecedented change for human civilisation. But providing an authoritative account of what that change will amount to isn't so easy.
Will those "few degrees" be enough to stop the AMOC and plunge Europe into a mini-ice age, enough to broaden the Hadley Cells and turn the central US lands and the Mediterranean lands into deserts, to green the Sahara and turn the Amazon into a treeless savannah? The answers are not straightforward. There is no long list if definitive outcomes set out in the headlines of the IPCC AR5 Synthesis Report. The word "risk" features too often when IPCC describes such outcomes.
But there are a couple of definitive temperature-related outcomes from AGW.
One is that Greenland will melt out somewhere between +1ºC and +2ºC threatening serious sea level rise. (The IPCC AR5 puts the upper bound at +4°C which is rather a fudge. Antarctica's ice caps are similarly a threat but how quickly they will react to global temperature rise is not well enough understood to be so predictable.) Another is the habitability of the tropics for humanity and perhaps a third is ocean acidification which would be unprecedented in tens of million of years.
If Greenland were to melt down (a process that once started will not stop as the top of the Greenland ice sheet today sits happily frozen high up in the cold upper atmosphere), the oceans would rise by over seven metres. This compares with the last six thousand years (which spans the period of human civilisation) when changes in sea level could be measures in centimetres. A seven metre rise would be a big problem as so much of our populations today live close to sea coasts. (About a third of humanity inhabit land less than 100 metres above sea level while the loss of both Greenland and Antarctica would raise sea levens 75 metres.) The melt-down of Greenland would take a few centuries to make its mark but the process certainly becomes unstoppable if global warming remains two degrees centigrade above pre-industrial.
The "few degrees" global temperature rise that accompanied the warming from the last glacial maximum 20,000 years ago and the dramatic impact on climate has been mentioned up-thread. The change in climate resulting from another similar-sized rise in global temperature would be just as dramatic for humanity. If global temperatures rose by six degrees celsius above pre-industrial, it could perhaps be described as a "Steam Age" as the increase in wet bulb temperatures would make the tropics a death trap for humans outside air conditioning. And such a six-degree temperature increase by 2100 is within the projection of the Business-As-Usual scenario of the IPCC.
The ocean acidification would rival that of the PETM 55 million years ago but would happen in decades rather than tens-of-millenia.
There is a big pile of reason not to let AGW run beyond +1.5°C. The implications for humanity and for much of the biosphere will be catastrophic if we let AGW run. It's a bit like jumping off a cliff. Predicting the height it would require for the fall to split your skull open is not straightforward but that is no reason to consider jumping. Besides, when you fall it's the intracranial hypertension that usually kills.
-
MA Rodger at 19:56 PM on 30 June 20202020 SkS Weekly Climate Change & Global Warming News Roundup #25
Given I have criticised Slarty Bartfast for the egregious level of error he achieves, I really should correct an error of my own up-thread.
Due to a spreadsheet error, the table of decadal averages within my comment @29 is entirely wrong, along with the associated result SD=0.14°C. The spreadsheet calculation corrected, I can now concur with Slarty Bartfast on his calculated decadal SD=0.28°C. (I calculate SD=0.287°C.)
The same does not go for other of his calculated SD for the Christchurch NZ monthly raw temperature data, these scaled from the graphic @21 above. (And of course, this data shouldn't be used for any reason in their raw state and and the SD shouldn't be calculated without consideration of the trend.) The comparison runs as follows:-
Av'ged period (months) .. .. My SDs ..... .. His SDs
1 .. ..... ..... ..... ..... ..... ..... 1.58°C ..... ..... 1.06°C
3 .. ..... ..... ..... ..... ..... ..... 1.30°C ..... ..... 0.76°C
6 .. ..... ..... ..... ..... ..... ..... 0.60°C ..... ..... 0.62°C
12 . ..... ..... ..... ..... ..... ..... 0.49°C ..... ..... 0.51°C
24 ' .... ..... ...... ..... ..... ..... 0.44°C ..... ..... 0.43°C
60 . ..... ..... ..... ..... ..... ..... 0.34°C ..... ..... 0.34°C
120 ...... ..... ..... ..... ..... ..... 0.29°C ..... ..... 0.28°C
It is evident that the SD calculation does not yield the straight line that Slarty Bartfast insists they do. And there is a pile of other methodological reasons for not attempting to extrapolate the data to provide an SD for an averaged century-long 1200 month period.
But as Slarty Bartfast does, let us not ignore all those problems.Instead consider the situation if, as Slarty Bartfast insists is the case, for 1200 month period there were actually SD=0.18°C. What is then easy to demonstrate are the errors in his argument that a +1.0°C increase in global average temperature between two consecutive centuries is "entirely possible" indeed "probable," this "due to natural variations resulting from chaotic behaviour within the climate system," or "mostly" so.
Slarty Bartfast @30 asserts that this SD=0.18°C would have a 95% probability of a 4-sigma fluctuation or "0.7 °C minimum". There are however a couple of fundamental errors in this bold assertion.
Firstly, a 20:1 chance is not what anybody would describe as "probable." Such odds are usually seen as being "improbable."
Secondly, for a normal distribution, the odds of seeing an increase of +0.7°C, or a positive increase equal in size to 4xSD, is not 20:1 but roughly 800:1. It is actually highly improbably. And we have the data to demonstrate this point.
The raw monthly data used by Slarty Bartfast can be averaged over those different periods and so the number of actual occurances of a +4xSD fluctuation can be totted-up. So, how many times do we find the increase between two data points is greater than 4x the calculated SD? Despite over 3,000 attempts, we don't find even one. The best we can do is 3.4xSD (which for a normal distribution is about 10x more likely than 4xSD).Av'ged period (months) .. .. 4 x SDs ..... .. Dev (& xSD) achieved
1 .. ..... ..... ..... ..... ..... ..... .. +6.33°C ..... ..... +5.16°C (3.26)
3 .. ..... ..... ..... ..... ..... ..... .. +5.20°C ..... ..... +4.44°C (3.42)
6 .. ..... ..... ..... ..... ..... ..... .. +2.40°C ..... ..... +2.06°C (3.44)
12 . ..... .... ..... ...... ..... ..... .. +1.96°C ..... ..... +1.30°C (2.65)
24 . ..... ..... ..... ..... ..... ..... .. +1.74°C ..... ..... +1.18°C (2.70)
60 . ..... ..... ..... ..... ..... ..... .. +1.36°C ..... ..... +0.87°C (2.55)
120 ...... ..... ..... ..... ..... ..... .. +1.15°C ..... ..... +0.43°C (1.51)As would be expected, the longer the averaged period, the fewer the data points, the smaller the probability of consecutive 4xSD fluctuations between consecutive data points.
So, even if it were correct to use raw data, even if the presence of trends were ignorable, even if the SD for century-long smoothing could be obtained; even if all this were so, we find Slarty Bartfast's chosen data does not show what Slarty Bartfast says.
-
Eclectic at 17:22 PM on 30 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
JWRebel @3 ,
please be more clear about the thrust of your question. Unless you have been oblivious the many reports, since middle of last century, of compromised scientific integrity and/or corruption - most typically in the medical/biological field - then your question seems to be discursively open-ended. (Not much fudging takes place in the hard sciences ~ mainly just poor analysis/interpretation.)
IMO the outstanding point of the article is to emphasize the recent big surge in "top down" interference in scientific integrity. A huge surge ~ almost comparable with the ancient Lysenko scandal of Stalinist fame/infamy. COVID-19 , climate , weather reporting . . . take your pick.
-
bf at 13:38 PM on 30 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
Broken link (URL appears twice) at: "A May 2020 report published by the EPA’s Office of Inspector General"
-
JWRebel at 12:53 PM on 30 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
@ doug_bostrom
Those are all about climate change, not the COVID-19 epidemic which has seen the Lancet and Journal of New England Medicine scramble to retract peer-reviewed articles based on fraudulent data. That's why I'd like to know what exactly the author has in mind as clear examples of compromised scientific integrity and/or corruption.
-
Doug Bostrom at 05:59 AM on 30 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
JW, the answer to your question is in plain sight in the article, in numerous places:
"A June 15 article in The New York Times..."
"A May 2020 report published by the EPA’s Office of Inspector General..."
"Under significant pressure from the White House, the acting head of NOAA, Neil Jacobs, subsequently issued an unsigned statement chastising the Alabama NWS scientists and backing Trump’s false claim. This behavior by the agency leadership violated principles in NOAA’s scientific integrity policy."
Et al. I won't reproduce the entire article above down here in comments— it makes a little more sense for you to read it.
-
JWRebel at 23:12 PM on 29 June 2020CSLDF: Why We’re Concerned About Scientific Integrity Policies
The COVID-19 pandemic tragically highlights the dire and immediate threats to public health that can result when the culture of scientific integrity at research institutions is ignored or fails.
An example of compromised institutions would be in order. I don't regard this as trivially obvious.
-
One Planet Only Forever at 03:51 AM on 29 June 20202020 SkS Weekly Climate Change & Global Warming News Roundup #26
The problem is not Facebook. The problem is competition for popularity and profit.
The pursuit of popularity and profit drives the development of many understandably harmfully incorrect things, and it drives the resistance to correction of those incorrect things.
Responsible Governing is the solution, but keeping popularity and profit from influencing Governing is very challenging.
Prev 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 Next
