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All IPCC definitions taken from Climate Change 2007: The Physical Science Basis. Working Group I Contribution to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change, Annex I, Glossary, pp. 941-954. Cambridge University Press.

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Comments 6901 to 6950:

  1. Models are unreliable

    Bob Loblaw @1204 ,

    The "search" for a course on DIY  GCM's is not just certainly odd  ~ it is positively hilarious.

    But maybe technology is moving faster than I thought.  And I had better check Amazon for stocks of those long-promised pocket-size quantum supercomputers (powered by cold fusion, I hope).   Doubtless these miniaturized marvels would be quite expensive at first ~ but perhaps early adopters will be issued with a bonus App for a GCM or two.

    Our moderator seemed to think that the good Deplore_This  was doing some "baiting" ( aka "trolling" ? ).    Never in a million years would I have thought such a thing . . . but it might explain the underlying motivation of this recent "encounter" at SkS, and it would explain the confused rambling denialism that he/she is throwing up.  And explain the DK-like complacency.

    Phillipe C @ 1203 ,

    your suggestion that the Lady in Question might be the good Dr Curry, is, surely, a tad ungentlemanly?   After all, the literary style is somewhat different ~ though I suppose I could be wrong on that (or the style might have had an extensive makeover per Grammarly or similar App).

    Still, it will be interesting if there are more developments.  I always hope there will be something new to learn, from every "challenge" to mainstream climate science.   Admittedly, my hopes have always been dashed ~ but some day there may be a grain of wisdom to be found among the bucketloads of BS.

  2. Models are unreliable

    Yes, the "search" for a class on "Make your own GCM" is certainly odd.

    I'll bet if I did a search through university catalogues for courses on "How to program a Word Processor", I would not find much at all. To use that as evidence that word processing software is not useful - hey, I"m a word processing skeptic! - would not be an effective argument.

    I could then switch to listing people that have found bugs in word processing programs as evidence that "word processing is not settled", or that "you can't trust word processors".

    Yet somehow, each day people use word processing softare to create all sorts of useful texts. (They seem to create some awful ones, too, but that is another story...)

  3. Philippe Chantreau at 09:11 AM on 4 July 2020
    Models are unreliable

    My opinion is that the lady that protest too much might be Curry.

    From the WIKI page on GCMs: "Versions designed for decade to century time scale climate applications were originally created by Syukuro Manabe and Kirk Bryan at the Geophysical Fluid Dynamics Laboratory (GFDL) in Princeton, New Jersey.[1]"

    Further:"In 1956, Norman Phillips developed a mathematical model that could realistically depict monthly and seasonal patterns in the troposphere. It became the first successful climate model.[2][3] Following Phillips's work, several groups began working to create GCMs.[4] The first to combine both oceanic and atmospheric processes was developed in the late 1960s at the NOAA Geophysical Fluid Dynamics Laboratory.[1]"

    It is obvious that Fluid Dynamics are at the foundation of all the current coupled atmosphere-ocean GCMs. I find that the dissatisfied search for a specific university course on such models is perhaps disingeneous. They are an area of research, very much at the edge of knowledge. People who participate in them have already obtained graduate degrees in fluid dynamics, applied mathematics and a variety of other fields. I doubt that there are university courses on specific protein folding methods, short of outlining the basic principles and current state og knowledge. However, those who want to orient themselves in that field will easily come across the areas of knwoledge they should master first. Then they can try to go hack it at the cutting edge.

    Curry does a favorite trick of hers by exploiting the fact that GCMs are not very good at delivering regional results, something well known in the modeling community, to suggest that they have no usefulness. In any case, the claim that fluid dynamics expertise is absent in the modeling community has no merit.

  4. Models are unreliable

    Deplore_This:

    You have now reached the point where moderators are starting to cut stuff.

    You posted a long story from E&E. You are hitting all the main climate denier sites. Well done. You are selecting to quote places that confirm your bias.

    https://www.desmogblog.com/energy-and-environment

    FYI, I started learning about this stuff in the 1970s. I read a lot of the primary literature long before there was an IPCC. I can tell when someone is trying to fool me.

  5. Models are unreliable

    Deplore_This , yes everyone with reasonable climate knowledge has heard of Dr Judith Curry ( and I myself visit her blog several times a month . . . it's a sort of upmarket version of WUWT  blog ).   Dr Curry's commentary is an excellent object lesson for those who wish to exercise their critical thinking!    She is one of the very very  few climate-contrarian scientists (a dying breed, it appears).

    Now, I notice your rapid-fire uploading of long posts at 1:23 AM and 1:24 AM and 1:25 AM.    Clearly these were pre-selected & prepared to go, and were not really a response to Scaddenp.

    And as you say: "... I've read criticism of the validity of ..."    And there is the nub of your problem, Deplore_This.

    The internal evidence of your many posts, is that you have not bothered to learn the fundamental science of climate yet.  Once you have done so, then you will be able to (A) make an informed decision whether or not to attempt the various complexities of climate modeling (with or without access to a supercomputer)

    . . . and (B) see right through the ludicrous nonsense of "the 500" scientists you mentioned

    . . . and (C) see right through Dr Curry's vague obfuscatory sophistry.

    It is a red-flag sign, that you have allowed yourself to be taken in by the simply unscientific propaganda exhibited by "the 500".    But Dr Curry's propaganda is a different matter ~ she uses a more subtle approach (analogous to what the hypnotherapists call "the Indirect method" ).   If you yourself are strongly motivated to believe her - which indeed you are - then she seems to make sense.   That is, she seems to make sense until you educate yourself past the "veneer" level of climate science.  And then, using skepticism and critical thinking, you will see the fatal flaws in her presentations.

    #  My apologies for sounding patronizing ~ but you really do need to learn the climate science first.   Don't be an Ivar Giaever, who succumbed to Motivated Reasoning, and reckoned that half a day or so on the internet sufficed for him to lecture the climate experts on their multitude of errors.   ( Yes, there are many humorous events to be found in the sphere of climate science ! )

    Moderator Response:

    [TD] I deleted Deplore_This's lengthy cut and paste about Curry, because only a tiny fraction of it was directly relevant to the Models topic of this thread. Despite the baiting that Deplore_This is doing, please let's try to stick to the thread topic. Thanks.

  6. Deplore_This at 04:15 AM on 4 July 2020
    Models are unreliable

    @Bob Lowlaw 1199

    Quit with your sanctimonious crap. It certainly doesn’t reflect well on your scientific reputation. I came here stating that I’m a skeptic and wanted a recommendation for university course on GCM, not to believe one person over another.

    Judith Curry was the Chair of the School of Earth and Atmospheric Sciences at a well-respected technical university and was obviously imminently qualified to get the job. I’m not going to post people’s names on the Internet to satisfy your curiosity.

    I looked at the Spencer Weart link and I’m already beyond that level. I have read the IPCC reports.

    If you were going to scientifically challenge Judith Curry’s opinions that I referenced you would point to published scientific scrutiny and not just make juvenile comments. The more emotional you become the more you add to her credibility in my eyes.

    Regards.

  7. Hansen's 1988 prediction was wrong

    Nylo @62,

    It is good to see we make progress, but it is not giant strides.

    While you do rush past many aspects of this matter that do require consideration and perhaps have dropped a few beads off the abacus before reaching your assessment that the Hansen et al Scenario A results "seem to be off by approximately 44%", I perhaps would flag up the point that climatologists do use complex climate models for a reason.

    On the CH4, I don't find the -200ppb value you arrive at for the 2010-20 difference between Scenario A and 'actual'. And I'm not aure that is a useful measure even if it were correct.

    The Scenario A increase from1400ppb at 0.6%, 1% then 1.5% yields roughly the 1500ppb and 1650ppb 1970-80 seen in Lacis et al Table 1. Running forward, that gives 2984ppb for 2019, and an increase over the decade from 2009 of 413ppb. The measured CH4 levels (from ESRL) are 1794ppb and 1867ppb, a 2009-19 rise of 73ppb. Thus 'Actual' - Scenario A = 340ppb. But do also note that the 'actual' CH4 increase 1988-2019 is also similarly less that the Scenario A projection for the two preceeding decades.

    And while you might imagine we could put that CO2 assessment to bed as the concentrations projected by Scenario A and 'actual' are entirely similar, the assessment of the resulting forcing from such a CO2 increase has been revised in the years since 1988. As per Fig b1, the 1988 assessment was a non-feedback equilibrium temperature increase for 2xCO2 of +1.2ºC. Yet today that is put at +1.0ºC, a significant difference in the underlying forcing.

    To complete this analysis will require an item by item assessment. A quick back-of-fag-packet calculation suggests to me that adding all the forcings from the different GHGs shows the 1988-2019 projections of Scenario A to be 200% of 'actual'. I'm not surprised to see that is roughly what is shown in Fig 4 of the Advanced OP above.  So, without considering negative forcings, we should expect Scenario A to be showing a lot more warming than 'actual'.

    If you wish, we could work through this assessment. But that does lead to the need to calculate the resulting warming. Climatologists turn to their models at that point. Maybe we can dodge that with a short cut. Yet reaching that objective is, on our past performance, not a quick exercise to see through to a conclusion.

  8. Models are unreliable

    Deplore_This:

    Who tells you she is "credible"? On what basis are they credible?

    You have chosen who you are going to believe. That is not the sign of a skeptic. You have bought into the shite they are selling to you. There are lots of places on the internet that will point out the crap you have read that is confirming your bias.

    Go read the Spencer Weart link I posted earlier.

    Have you read the IPCC reports, or do you just read the comments about the IPCC that you get from your "credible" sources?

    I agree with Tom Dayton. You are not here to learn anything.

  9. Deplore_This at 02:44 AM on 4 July 2020
    Models are unreliable

    @Bob Lowlaw 1197

    As I stated Judith Curry was the Chair of the School of Earth and Atmospheric Sciences at my alma mater. I don’t know her personally but I know people who do and they tell me she is credible. As a courtesy I reviewed your links and I don’t see anything that refutes that opinion. It appears to me that Judith Curry is a scientist who disputes some of the “group think” and is shunned and unfunded. If the climate science community can not engage in open debate then it is not practicing science. As a climate skeptic I am accused of not believing science but without open debate it is not science.

    Bob, I believe Judith Curry before I believe you. So my dilemma remains and I’m not sure what to do next. Thank you for your response.

  10. Models are unreliable

    Deplore_This:

    Judith Curry is not, I repeat, not, a reliable source of information. She peddles "uncertainty", and much of what she says is simply wrong. Start here:

    https://skepticalscience.com/skeptic_Judith_Curry.htm

    and continue here:

    https://www.desmogblog.com/judith-curry

    In addition, pretty much anything published by the GPWF is full of crap:

    https://www.desmogblog.com/global-warming-policy-foundation

    Same for the Climate Intelligence Foundation:

    https://www.desmogblog.com/climate-intelligence-foundation-clintel

    You need to find better sources of information. You're paying attention to people that are selling shite to you.

  11. Deplore_This at 01:41 AM on 4 July 2020
    Models are unreliable

    @Bob Lowlaw 192

    Thank you for your response. As I stated in my first post 1162 and my post at 1195 I am an anthropogenic climate change skeptic because I’ve read criticism of the validity of the climate temperature models referenced by the IPCC like those posted in 1193 and 1194. I am aware that there are multiple climate models and classes of climate models. According to the syllabus the Penn State course I referenced included multiple climate system components including atmosphere, ocean, land, cryosphere, biosphere, role of parameterizations and model coupling.
    http://www.met.psu.edu/intranet/course-syllabi-repository/2020-spring-syllabi/meteo-523

    Without repeating my post at 1195 I’ll just state here that I remain open to any suggestions. Thank you again for your response.

  12. Deplore_This at 01:25 AM on 4 July 2020
    Models are unreliable

    @scaddenp

    As I stated in my first post 1162 I am an anthropogenic climate change skeptic because I’ve read criticism of the validity of the climate temperature models referenced by the IPCC like those posted in 1193 and 1194. The corrupt media and the bureaucrats at the EPA say it’s settled science but I see no record of balanced climate research or any open debate. It appears that scientists who raise doubts of the validity are shunned and unfunded.

    So my dilemma is how do I know what and who to believe. It is my nature not to blindly believe anything, especially what the government tells me. I thought a solution would be to take a university course in climate modelling so that I could hands on use and understand the development of GCMs and form my own opinion. If this was the 16th century and I’d probably get a telescope to test Galileo’s claim of heliocentrism. I am surprised to find that there aren’t such courses which leads to an even more startling revelation that the majority of the “97% of climate experts agree humans are causing global warming” have never been taught or used a GCM themselves and base their opinion on the opinion of others. To me that looks more like group think than science. And they call us climate skeptics “flat earthers”.

    So my dilemma remains and I’m not sure what to do next. I may contact Penn State and see if course material is available from their last course on GCM. I’m not going down the paleological path because there are other issues there and because the IPCC’s opinion that is used for public policy is based on GCM predictions. I remain open to any suggestions. Thank you again for your help.

  13. Deplore_This at 01:24 AM on 4 July 2020
    Models are unreliable

    @scaddenp 1187

    Here is another example of scientists who disagree with the IPCC’s conclusion on GCMs where more than 500 scientists and professionals in climate and related fields sent a “European Climate Declaration” to the Secretary-General of the United Nations asking for a “long-overdue, high-level, open debate on climate change” and were denyed.

    “There is no climate emergency…Climate science should be less political, while climate policies should be more scientific. Scientists should openly address the uncertainties and exaggerations in their predictions of global warming, while politicians should dispassionately count the real benefits as well as the imagined costs of adaptation to global warming, and the real costs as well as the imagined benefits of mitigation.”

    “Natural as well as anthropogenic factors cause warming. The geological archive reveals that Earth’s climate has varied as long as the planet has existed, with natural cold and warm phases. The Little Ice Age ended as recently as 1850. Therefore, it is no surprise that we now are experiencing a period of warming.”

    “Warming is far slower than predicted. The world has warmed at less than half the originally-predicted rate, and at less than half the rate to be expected on the basis of net anthropogenic forcing and radiative imbalance. It tells us that we are far from understanding climate change.”

    “Climate policy relies on inadequate models. Climate models have many shortcomings and are not remotely plausible as policy tools. Moreover, they most likely exaggerate the effect of greenhouse gases such as CO2. In addition, they ignore the fact that enriching the atmosphere with CO2 is beneficial.”

    “There is no statistical evidence that global warming is intensifying hurricanes, floods, droughts and suchlike natural disasters, or making them more frequent.” “However, CO2-mitigation measures are as damaging as they are costly. For instance, wind turbines kill birds and bats, and palm-oil plantations destroy the biodiversity of the rainforests.”

    “We invite you to organize with us a constructive high-level meeting between world-class scientists on both sides of the climate debate early in 2020. The meeting will give effect to the sound and ancient principle no less of sound science than of natural justice that both sides should be fully and fairly heard. Audiatur et altera pars!”

    https://clintel.nl/brief-clintel-aan-vn-baas-guterres/

  14. Deplore_This at 01:23 AM on 4 July 2020
    Models are unreliable

    @scaddenp 1187

    Thank you for your response. To answer your question here this is an example of scientists who disagree with the IPCC’s conclusion on GCMs:

    “GCMs are important tools for understanding the climate system. However, there are broad concerns about their reliability:

    • GCM predictions of the impact of increasing carbon dioxide on climate cannot be rigorously evaluated on timescales of the order of a century.
    • There has been insufficient exploration of GCM uncertainties.
    • There are an extremely large number of unconstrained choices in terms of selecting model parameters and parameterisations.
    • There has been a lack of formal model verification and validation, which is the norm for engineering and regulatory science.
    • GCMs are evaluated against the same observations used for model tuning.
    • There are concerns about a fundamental lack of predictability in a complex nonlinear system.

    There is growing evidence that climate models are running too hot and that climate sensitivity to carbon dioxide is at the lower end of the range provided by the IPCC. Nevertheless, these lower values of climate sensitivity are not accounted for in IPCC climate model projections of temperature at the end of the 21st century or in estimates of the impact on temperatures of reducing carbon dioxide emissions. The IPCC climate model projections focus on the response of the climate to different scenarios
    of emissions. The 21st century climate model projections do not include:

    • a range of scenarios for volcanic eruptions (the models assume that the volcanic activity will be comparable to the 20th century, which had much lower volcanic activity than the 19th century
    • a possible scenario of solar cooling, analogous to the solar minimum being predicted by Russian scientists
    • the possibility that climate sensitivity is a factor of two lower than that simulated by most climate models
    • realistic simulations of the phasing and amplitude of decadal- to century-scale natural internal variability

    The climate modelling community has been focused on the response of the climate to increased human caused emissions, and the policy community accepts (either explicitly or implicitly) the results of the 21st century GCM simulations as actual predictions. Hence we don’t have a good understanding of the relative climate impacts of the above or their potential impacts on the evolution of the 21st century climate.”
    -— Judith Curry, the former Chair of the School of Earth and Atmospheric Sciences at my alma mater
    https://www.thegwpf.org/content/uploads/2017/02/Curry-2017.pdf

  15. Models are unreliable

    Deplore_This:

    I am still unsure as to exactly what you expect to accomplish with respect to climate models. So far, it looks like you have a pre-conception that something must be wrong, and you are on a search for details to support that position. I think you may experience a bad case of confirmation bias, if your postings here are an indication.

    As has been pointed out, climate General Circulation Models (GCMs) are only a small part of climate science. I suggest that you read Spencer Weart's "The Discovery of Global Warming" to learn more about climate science in general.

    https://history.aip.org/climate/index.htm

    In addition, you seem to be under the impression that GCMs represent a "single" climate model. They do not. A GCM is a collection of many types of climate-related models that are knit together to provide a comprehensive view of climate - much as the science of climatology has many, many areas of specialization that need to be knit togther to form a  full picture. Areas that represent distinct sub-classes of "climate" models include (but are not limited to):

    • radiation transfer. Much detailed work was done in the 1960s, when the military wanted to make sure that their IR-seeking missiles would hit the intended targets. (HInt: their "target" was not "climate")
    • atmospheric dynamics (motions). Especially important for weather forecasting. The general field is "Geophysical Fluid Dynamics" (GFD) and atmospheric motion is only one area of application. The same science is used to model air flow on airplane wings, or fluids in pipes or in-ground oil reservoirs, etc. Each application has its own specific issues, so modelling approaches differ - but there is a lot in common.
    • ocean dynamics. Another application of GFD, Oceans have some different issues from atmospheric motions, though.
    • Surface energy balance issues. Receipt of radiation, partitioning into evapotranspiration, thermal fluxes (to atmosphere, to soil or water). Effects of surface type, vegetation, etc. Often referred to as "microclimate". (This was my area of specialization when I worked in the discipline.)
    • soil heat transfer.
    • cloud physics.
    • and so on.

    And once the climatologists develop their theories, there is the task of finding efficient algorithms to transform the science (usually in some mathematical form) into computer solutions. Generally covered as "Numerical Methods" in the computing science world. Systems of partial differential equations that cah be solved either through finite difference, finite element, or spectral methods. These methods are not unique to "climate science".

    No single university course is going to cover the full level of details of every aspect of climate models - or climatology in general. Different groups that develop GCMs make different decisions on which components of which "climate" sub-models will be incorporated, and how they want to code numerical solutions.

    These difference approaches lead to different results in detail, but the broad picture is the same: CO2 from fossl fuels plays an important role in current temperature trends.

  16. Hansen's 1988 prediction was wrong

    MA Rodger @61 I think that what you say is good. The description by Hansen of what the evolution of methane is in his scenario A must contain an errata. Lacis claimed a 150ppbv increase in 1970-1980 instead of 1.5ppbv per year which would hardly achieve 15ppbv.

    Admitting that you are probably correct and reworking my calculations accordingly, Hansen would have expected a rise of 282ppbv for the period of 2010-2020, and we have experienced only 80ppbv. So we are indeed below Scenario A emissions in terms of methane, by 200ppbv in the last decade, which would lead to around 1/8 of 0.16ºC less (by figure B1, as 200ppbv=0.2ppmv is 1/8 of 1.6ppmv), or 0.02ºC less in this latest 10 years period for which Scenario A forecast half of a degree increase (by latest Real Climate diagram shown above in @55). So based on methane and CO2 alone, we should change that 0.45ºC increase in 2010-2020 to 0.43ºC. The observed increase has been 0.26ºC so the remaining extra 0.17ºC that we have not experienced in the last 10 years must all be due to differences in CFC emissions compared to Scenario A expectations.

    For CFCs (F11, F12) the forcing in the 1980s was, according to figure B2, roughly 0.02ºC. As Scenario A expected a 3% increase in emissions per year, doing the calculations the forcing in 2010-2020 for CFCs would be 2.57 times bigger than the forcing in the 80's, or about 0.055ºC. Assuming that, instead, we have experienced none, that would reduce the expected temperature increase in that scenario for this decade if we use actual instead of modelled emissions by 0.055ºC. The +0.43ºC warming that the model would have predicted by replacing methane projections with actual values, goes down to +0.375ºC if we do the same with CFCs. And again, we have witnessed +0.26ºC. Hansen projections seem to be off by approximately 44% (44% more warming in his models than in real world).

    Am I ignoring something else perhaps? Feedbacks to radiative forcings? Would those change the 0.075ºC of combined radiative forcings of the differences in methane and CFCs between model and reality, to the needed +0.28ºC difference between Scenario A predictions and observations? That would require a feedback level of more than 3.5 to the forcings.

  17. Models are unreliable

    ClimateDemon @1190 ,

    You have made the mistake of promoting "binary" assertions ~ all-or-nothing, black-or-white.  Not "evidenceless"  assertions ~ but illogical assertions.  Illogical, because not sufficiently evidential  i.e. you have chosen to cherry-pick one small area which pleases you, and you have ignored the bigger context that displeases you (and which does not support your assertions).   You have therefore failed to think logically.

    (1)  The globe as a whole is in thermal equilibrium (or very close to it) over duration of time.  Obviously the globe is warming gradually, as evidenced by melting ice and rising sea level.  Surface temperature varies : and the seasonal and historical evidence is that this variation has tight bounds.

    (2)  The Clausius-Clapeyron equation describes physical activities ~ at any local terrestrial site, of varying temperature humidity and pressure.  Obviously these activities operate within bounds, and so can be said to be in a form of equilibrium dynamically within these limits and durations.

    (3)  Because of the above, the C-C equation does apply "to the earth and atmosphere system for predicting global effects"  ~ which have been observed and measured in recent decades.

    ( If my memory serves me, you have fruitlessly questioned these concepts, in other threads in past years. )

  18. Hansen's 1988 prediction was wrong

    Nylo @58/59/60,

    I don't see that I can agree with any of that.

    Note the primary source of CH4 levels is NOAA ESRL and these provide global data from 1983 although this record was not established as such until the 1990s. Thus you will note that Hansen et al (1988) references Lacis et al (1981) for its CH4 data. And this reference should give a bit of a warning that something is amiss with the passage from Hansen et al  Appendix B that you quote.

    Lacis et al describe the rise in CH4 1970-80 as being 150ppb, from 1.5ppm to 1.65ppm.

    And there is evidently an error in Appendix B of Hansen et al. We have two alternative errors, one a simple typo (although an error nonetheless) and the other one a careless omission with massively significant implications. (i) Either the error was that the "1.4ppbv" should have read "1.4ppmv" = 1,400ppbv.  (ii) Or the value "1.4ppbv" for 1958 which CH4 "increases from" is meant to be the start value of a rate-of-increase rising by a set percentage per year. If this were the case, it should have read "1.4ppbv per year in 1958".

    It is evident from Lacis et al that the corrected version is "1.4ppmv". Using percentage increases set out in Hansen et al, the "1.4ppmv" start-point in yields a 1970-80 CH4 level running from 1504ppb to 1670ppb.

    The alternative appears a tiny bit ridiculous as, if Hansen et al did work with CH4 based on "1.4ppbv per year in 1958" it would require both a profoundly mistaken reading of Lacis et al and an egregious miscalculation of the forcing resulting from the vastly reduced rise in CH4 levels. That is, CH4 rise would total 20ppb 1980-90 rather than the 270ppb using the "1.4ppm". (Modern estimates/measurements yield 220ppb 1980-90.)  If you examine Figb1, an increase of 1.6ppm CH4 yields 0.16ΔTo(ºC) which pro rata would yield from Figb2's 0.0295ΔTo(ºC) a 1980's decadal CH4 rise of 295ppb, a finding which is wholly incompatible with the adoption of a 20ppb decadal increase.

    ....

    Concerning the CH4 'hiatus' of the early 2000s, the deceleration in the atmospheric CH4 rise was spotted by the early 1990s and its cause (a reduction in anthropogenic emissions) was understood before 2010 (although which anthropogenic source wasn't clear), as was the obvious signs if it ending.

  19. House Democrats eye 2021 with comprehensive climate action plan

    Still not enough. CAT would rate existing US target under the Paris Agreement “Insufficient”, as it is not stringent enough to limit warming to 2°C, let alone 1.5˚C. However, given the decision to withdraw from the Paris Agreement, the rate is “Critically insufficient”!

    ???? https://climateactiontracker.org/countries/usa/

  20. Hansen's 1988 prediction was wrong

    MA Rodgers @57 please allow me a small correction to what I wrote in @58, as I made a small mistake. Our CO2 emissions are higher than what was expected in Scenario B, but they are not higher than expected in Scenario A, I mixed up things. Our CO2 emissions are exactly equal to the ones expected in Scenario A, which would have provided +2.6ppmv increase per year by 2020 and an average for the last 10 years of 2.44ppmv which is almost exactly the same that has been observed. Therefore:

    * The observed CO2 concentration evolution is almost exactly what Scenario A contemplated,

    * The observed Methane concentration increase is twice as big as what Scenario A predicted,

    * The observed CFCs evolution is way smaller than what Scenario A expected, although not enough to compensate for the doubling of the emissions of CH4.

    For all of this, I think that the correct scenario to which we should compare the evolution of temperatures is Scenario A.

  21. ClimateDemon at 18:08 PM on 3 July 2020
    Models are unreliable

    I have a challenge for those who claim that I am making evidenceless assertions. Give me just one example of such an assertion. If you can, please do so and I will and I will make appropriate corrections. Otherwise, please don’t make such claims against me.


    Also, please keep in mind the fact that there are a few items upon which we must be in agreement, or there is no point in attempting to communicate.

    (1) The earth and its atmosphere are not in thermal equilibrium. This is well evidenced by the fact that temperature varies widely over the surface. If the globe were in thermal equilibrium, the surface temperature would be uniform.


    (2) The Clausius-Clapeyron equation is derived for determining the vapor pressure of a substance that is isolated and in thermal equilibrium with its condensed phase. While this equation may be useful in predicting local precipitation over ranges in which there is little temperature change, it is not applicable to global models or effects over which temperatures can vary by 50-60 degrees C.


    (3) We only use mathematical theorems or formulas within the range of their validity. This means we don’t apply the Pythagorean theorem to obtain the longest side of a non-right triangle. Similarly, we don’t use classical equations of motion to predict the motion of a particle traveling at or near the speed of light. Finally, we do not apply the Clausius-Clapeyron equation to the earth and atmosphere system for predicting global effects.

  22. Hansen's 1988 prediction was wrong

    I think I understand what is going on here, why the original article claims that the CH4 emissions have been lower than scenario B (and therefore also A) despite they have been twice as big as scenario A. The article was written in 2010, judging by the dates of the first comments. And in 2010 we had witnessed an almost complete stop in the increase of CH4 concentrations that had lasted roughly a decade. I guess it was predicted to continue to stop. It hasn't, so if we are going to continue to compare what Hansen predicted to today's temperatures, we also need to update the emissions scenario that we are closest to. And this is scenario A.

  23. Hansen'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.

  24. Deplore_This at 12:20 PM on 3 July 2020
    Models 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.

     

  25. Models are unreliable

    You can find the list of participants in the CMIP6 project here (via the map). CMIP models are what inform IPCC reports.

  26. Models 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.

  27. Deplore_This at 11:55 AM on 3 July 2020
    Models are unreliable

    @Dayton

    It's OK if your answer is "no".  That isn't a problem.  No worries.

  28. Deplore_This at 11:38 AM on 3 July 2020
    Models 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.

  29. Models are unreliable

    Deplore_This: Clearly you are not actually interested in learning anything.

  30. Deplore_This at 11:17 AM on 3 July 2020
    Models 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.

  31. Models are unreliable

    Deplore_This: Tim Osborn has an excellent web page Climate Models for Teaching.

  32. Models 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.

  33. Models 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.

  34. Models 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.

  35. Deplore_This at 08:33 AM on 3 July 2020
    Models 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.

  36. Models 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.

  37. House 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.

  38. Deplore_This at 03:49 AM on 3 July 2020
    Models 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.

  39. Deplore_This at 02:45 AM on 3 July 2020
    Models 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-523

    This 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.

  40. Hansen'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".

  41. Models 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.

  42. ClimateDemon at 21:53 PM on 2 July 2020
    Models 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.

  43. Hansen'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.

  44. michael sweet at 20:45 PM on 2 July 2020
    Hansen'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:

    Data model comparison

    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.

  45. Hansen'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).

  46. Hansen'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. 

  47. Models 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."

  48. Models are unreliable

    Deplore_This: Perhaps the ISCA framework is what you want.

  49. Models are unreliable

    Deplore_This: You should use one of the textbooks to inform you as you play with that model.

  50. Models 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/

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