Falsified Hypotheses Are Rejected In Science. For Consensus Climate Science, Failed Hypotheses Are Upheld

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In most scientific fields, hypotheses that fail to be verified by real-world observations 85% to 100% of the time are rejected immediately.

In Consensus Climate Science, when 126 of 126, 111 of 114, 42 of 49… modeled projections are wrong, or when the opposite sign of the modeled trend is observed, the climate models are still regarded as mechanistically correct, especially with regard to the CO2 climate influence.

Those who disagree are dismissed as “denialists”.

Image Source: Tabari and Willems, 2018

For 2019, the opposite-sign, contradicted-by-observations models continue to be highlighted in the scientific literature.

At what point will Consensus Climate Science actually question if the greenhouse gas forcings the models are predicated on need reconsideration?

Connolly et al., 2019

Observed changes in Northern Hemisphere snow cover from satellite records were compared to those predicted by all available Coupled Model Intercomparison Project Phase 5 (“CMIP5”) climate models over the duration of the satellite’s records, i.e., 1967–2018. A total of 196 climate model runs were analyzed (taken from 24 climate models). Separate analyses were conducted for the annual averages and for each of the seasons (winter, spring, summer, and autumn/fall). A longer record (1922–2018) for the spring season which combines ground-based measurements with satellite measurements was also compared to the model outputs. The climate models were found to poorly explain the observed trends. While the models suggest snow cover should have steadily decreased for all four seasons, only spring and summer exhibited a long-term decrease, and the pattern of the observed decreases for these seasons was quite different from the modelled predictions. Moreover, the observed trends for autumn and winter suggest a long-term increase, although these trends were not statistically significant.”

He and Yang, 2019

“However, three combined gridded observational datasets, four reanalysis datasets, and most of the CMIP5 models cannot capture extreme precipitation exceeding 150 mm day−1, and all underestimate extreme precipitation frequency. The observed spatial distribution of extreme precipitation exhibits two maximum centers, located over the lower-middle reach of Yangtze River basin and the deep South China region, respectively. Combined gridded observations and JRA-55 capture these two centers, but ERA-Interim, MERRA, and CFSR and almost all CMIP5 models fail to capture them. The percentage of extreme rainfall in the total rainfall amount is generally underestimated by 25%–75% in all CMIP5 models.”

Bishop et al., 2019

Atmospheric models forced by observed SSTs and fully coupled models forced by historical anthropogenic forcing do not robustly simulate twentieth-century fall wetting in the SE-Gulf. SST-forced atmospheric models do simulate an intensified anticyclonic low-level circulation around the NASH, but the modeled intensification occurred farther west than observed. CMIP5 analyses suggest an increased likelihood of positive SE-Gulf fall precipitation trends given historical and future GHG forcing. Nevertheless, individual model simulations (both SST forced and fully coupled) only very rarely produce the observed magnitude of the SE-Gulf fall precipitation trend.”

Chung et al., 2019

“Here, by conducting a comprehensive analysis based on multiple independent observational records, including satellite observations along with a large ensemble of model simulations, we objectively determine the relative contributions of internal variability and anthropogenic warming to the emergence of long-term PWC [Pacific Walker Circulation] trends. Our analysis shows that the satellite-observed changes differ considerably from the model ensemble-mean changes, but they also indicate substantially weaker strengthening than implied by the reanalyses. Furthermore, some ensemble members are found to reproduce the observed changes in the tropical Pacific. These findings clearly reveal a dominant role of internal variability on the recent strengthening of the PWC [Pacific Walker Circulation].”

Zhang et al., 2019

Observed Southern Ocean surface cooling and sea-ice expansion over the past several decades are inconsistent with many historical simulations from climate models. Here we show that natural multidecadal variability involving Southern Ocean convection may have contributed strongly to the observed temperature and sea-ice trends.”

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16 responses to “Falsified Hypotheses Are Rejected In Science. For Consensus Climate Science, Failed Hypotheses Are Upheld”

  1. tom0mason

    “At what point will Consensus Climate Science™ actually question if the greenhouse gas forcings the models are predicated on need reconsideration?”

    Sorry Kenneth can not see that ever happening — there’s too much money and political power to be lost if the (consensus) science community let that happens.

    So what is likely to happen?
    Much the same as now, every 5-6 years the models will be revamped with new tweaks and caveats, most of the minor identified errors from previous iterations will be said to have been solved (but if standard practice prevails they’ll just be hidden/obscured). Still no one will be looking at the overall regional/global atmospheric pressure changes trends. The most glaring errors with the dynamics of clouds and precipitation, SST, and glacial ice changes will still be mis-characterized and inaccurately modeled (but done slightly differently).
    Overall it will just be more make-up being applied to the model pig!

    Thankfully by time CMIP7 is out the cooling will be so obvious and such a political hot potato (pun intended), people will be demanding action on global cooling. Hopefully by then the UN and the IPCC will have it’s evil fangs pulled, and their pronouncements/diktats will have been either rescinded, or sideline and ignored by the majority of world.
    Eventually people might understand that we humans do not command the climate, nature does.

  2. tom0mason

    And then there are the problems with the each variant of computer climate model such outlined here in Impact of Physics Parameterization Ordering in a Global Atmosphere Model by Aaron S. Donahue and Peter M. Caldwell…

    Because weather and climate models must capture a wide variety of spatial and temporal scales, they rely heavily on parameterizations of subgrid‐scale processes. The goal of this study is to demonstrate that the assumptions used to couple these parameterizations have an important effect on the climate of version 0 of the Energy Exascale Earth System Model (E3SM) General Circulation Model (GCM), a close relative of version 1 of the Community Earth System Model (CESM1). Like most GCMs, parameterizations in E3SM are sequentially split in the sense that parameterizations are called one after another with each subsequent process feeling the effect of the preceding processes. This coupling strategy is noncommutative in the sense that the order in which processes are called impacts the solution. By examining a suite of 24 simulations with deep convection, shallow convection, macrophysics/microphysics, and radiation parameterizations reordered, process order is shown to have a big impact on predicted climate. In particular, reordering of processes induces differences in net climate feedback that are as big as the intermodel spread in phase 5 of the Coupled Model Intercomparison Project. One reason why process ordering has such a large impact is that the effect of each process is influenced by the processes preceding it. Where output is written is therefore an important control on apparent model behavior. Application of k‐means clustering demonstrates that the positioning of macro/microphysics and shallow convection plays a critical role on the model solution.

    [my bold]

    From https://agupubs.onlinelibrary.wiley.com/doi/full/10.1002/2017MS001067

  3. tom0mason

    And of course buried in all of the climate models is the outright guess of what
    the ECS figure.
    https://object.cato.org/sites/cato.org/files/wp-content/uploads/gsr_022714.gif

    Roll-up! Roll-up! Pick a number. Any number … 🙂

  4. Falsified Hypotheses Are Rejected In Science. For Consensus Climate Science™, Failed Hypotheses Are Upheld. – Truth is difficult but essential…

    […] […]

  5. Curious George

    There are no falsifiable hypotheses in a settled science.

  6. Yonason

    Here’s something I find amusing in the Tabari and Willems abstract.

    “Climate change results are highly model dependent so that even opposite climate change signals may be achieved from different types of climate models. . . . “

    This apparent weakness is then referred to as “ADDED VALUE,” and the reader is then edumacated (he really wanted to know what he’s being told, but he just didn’t realize it) as to just what a precious asset this is, in case he would mistakenly think it to be a liability. This “added value” seems to be attributed by the authors to whether or not the model is “fine-” or “coarse-scale,” and to have something to do with “…the extent to which the discrepancy between driving and driven climate models varies with seasons.” …as if it were only natural to expect that to be the case.

    WOW! Such double talk would have made a great comedy routine, and can best be described in the words of a polite but no-nonsense fellow whose commentary I used to listen to, as “taurine excreta” (B.S., in the vernacular).

    I suppose it is only natural that anyone believing climate models can actually work would be capable of such utter nonsense.

    I haven’t enough hands or faces to give their assertions the face palms it deserves.

  7. Petit_Barde

    Climate modelers believe they are doing rocket science, instead, after decades of observations contradicting their AGW hype, they should face reality :

    https://inebriatedpress.files.wordpress.com/2009/04/090502-rocket-scientists.jpg

    More seriously, Chap. IV, “Physical Foundations of Climate Science” in
    Gerhard Gerlich, “Falsification Of The Atmospheric CO2 Greenhouse Effects Within The Frame Of Physics” explains why climate models can’t have any predictive value.

    Even the IPCC knew this basic fact :

    IPCC TAR WG1:
    “The climate system is a coupled non-linear chaotic system, and therefore the long-term prediction of future climate states is not possible.” –

    Strangely, in the present days state of Oblivion, when I google search for “non-linear chaotic coupled system climate ipcc” the first two links found are :

    TAR Climate Change 2001: The Scientific Basis — IPCC
    https://www.ipcc.ch/report/ar3/wg1/
    Traduire cette page
    The Climate System: an Overview … Observed Climate Variability and Change … any responsibility for the accuracy of these translations into non-UN languages.

    and :

    In climate research and modelling, we should recognise that … – IPCC
    https://www.ipcc.ch/ipccreports/tar/wg1/505.htm
    Traduire cette page
    Climate states are defined in terms of averages and statistical quantities applying … recognise that we are dealing with a coupled non-linear chaotic system, and …

    And when I click on each of them, the result is :

    PAGE NOT FOUND.

    1. Yonason

      Try the “wayback macine” at internet archive. For now those links are available there, although I don’t find either very useful.

      https://web.archive.org/web/20190127223343/https://www.ipcc.ch/report/ar3/wg1/

      https://web.archive.org/web/20071216023924/https://www.ipcc.ch/ipccreports/tar/wg1/505.htm

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  12. Boooshpig

    Why is the article got a TM trademark sign after it?

    1. P Gosselin

      I think Kenneth meant it as sarcasm. But technically it probably should not be there, and so I’ve deleted it. Of course the term is not “trademarked” (as far as I know).

      1. Boooshpig

        Gotcha, was curious was all. Your response makes sense. 🙂

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