Disconnect in the relationship between GMST and ECS

by Kenneth Fritsch

Abstract. An analysis is presented of  he disconnection between the CMIP5 and CMIP6 Historical and Future periods when considering the relationship of the individual model GMST changes and the climate sensitivity. I have included a simple model that can account for the period disconnection using the negative forcing of aerosol/cloud effects in the Historical period that is carried forward into the Future period.   I attribute some of the uncertainty in simulations of this simple model to endogenous model decision (selection) uncertainty that leads to variations in the changes of the negative forcing in the Historical period carried forward into the Future period.

Introduction:

There have been a number of references in the climate science literature (references 1 through10) concerning the disconnection between the change in the global mean surface temperature (GMST) in the Historical period (used in this analysis the time period 1850 or 1861 to 2014) and the climate sensitivity of models as measured by Equilibrium Climate Sensitivity (ECS) and Transient Climate Response (TCR) for individual CMIP5 and CMIP6 climate models. That disconnection has been made more obvious by the CMIP6 ensemble of models having higher climate sensitivities than that in the CMIP5 ensemble and yet having the near same GMST trends in the Historical period (references 11 and 12).

While there have been proposed explanations for this disconnection in the literature, mainly pointing to negative aerosol and cloud related forcing in the Historical period as probable causes, there has been neither an analysis of how this effect would carry over into the Future period (used in this analysis as the 2015-2100 time period) for individual models nor a direct comparison of the models’ GMST changes in Historical and Future periods. A theme in some of these papers suggests that direct model tuning of the Historical period warming does not account for the forcing compensation for differing model climate sensitivities but rather that it can be produced by selection from a range of parameter processes that can yield overall credible results and in turn a range of credible GMST trends. If the disconnection stems from a strictly structural difference between individual models, it would not change the concern for the models capability of reproducing the Historical GMST change translating to a capability to predict Future period GMST changes.

In this analysis I have used the energy budget equation, ΔT=(ΔF-ΔN)/λ , where ΔT is the GMST change, ΔF is the forcing change, ΔN is the change in TOA radiative imbalance and λ is the climate feedback parameter for an individual model. This relationship is further simplified by assuming that the quantity ΔF-ΔN in a correctly modeled form should be near constant for all models in a given scenario and time period and can be replaced by F2x which is the individual model radiative forcing from a doubling of atmospheric CO2 concentration.   F2x/ λ is equivalent to ECS but for the purposes of this analysis the term F2x/λ will be used since it better denotes the simplifying relationship it has to the energy budget.

This analysis uses OLS regression of ΔT versus F2x/λ for individual models for a given scenario and time period and ΔT versus ΔT for individual models for scenario versus scenario. The analysis covers the CMIP5 and CMIP6 Historical and representative Future period scenarios. Also included in the analysis, as a possible contributing factor in the Historical to Future scenario disconnections, were the results of OLS regression of ΔN versus ΔN for all scenario combinations. The critical results derived from all these regressions were the slope t values and r squared values.

It was obvious from the start of this analysis that Future scenario ensembles, where the forcing from greenhouse gases (GHG) is dominating over negative aerosol forcing and noise, should have more significant slope t and r squared values than those derived from the Historical period.  In this analysis the expectations of disconnections of the Historical ensemble results from those of the Future ensembles and how this could occur facilitated the construction of simple simulation scenario models (hereafter in this article referred to as Reproduction Models) that closely reproduce and provide a potential explanation of the differing model scenario results. I posted a previous thread here at Climate etc. (reference 13) on the disconnection between the Historical Future scenarios for CMIP5 models. That analysis did not provide a Reproduction like model showing how a negative forcing can compensate the climate sensitivities in the Historical period and be carried over into the Future period without materially reducing the correlations there. I attempt to provide that missing step in this analysis.

Methods:

All time series changes in climate variables in this analysis were determined using the empirical CEEMDAN method of extracting a secular trend from periodical oscillation and noise components (references 14 and 15). This method avoids having to limit the period selections to those where the non-trend components are not thought to bias the variable change. It also allows the change to be determined for the entire time period selected.

The individual model GMST and TOA radiation data and the corresponding Pre-Industrial Controls (PIC) for this analysis were taken for the CMIP5 scenarios from KNMI Climate Explorer website (reference 16) and for CMIP6 from the ESGF Node at DKRZ (reference 17). The forcing data for CMIP5 were taken from Meinshausen (reference 18) and that for CMIP6 were from Fiedler (reference 19). The λ and F2x data were taken from Gregory and Forster (references 20 and 21) for CMIP5 and from Femke (reference 22) for CMIP6.

The PIC series were tested for statistically significant trends and if none were found no adjustments were made to corresponding GMST and TOA series. There appeared no good reason to subtract non significant components (noise) from the series of interest. A with/without adjustment comparison of the final series changes over the period of interest showed no or very small differences relative to the series changes.

OLS regression was chosen for this analysis after comparing results for the slope and slope t values with Deming regressions. The small differences in the slope values for these two types of regression showed that the noise in the independent variable was not sufficient to require use of a version of Total Least Square regression. The r squared values for the regressions are reported with and without outliers along with the number of outliers found. These outliers were determined using Cook’s Distance criteria of greater than 4 times the mean of the Cook’s Distance for all the model results (reference 23). No effort was made to analyze the outliers since the motive for detecting them was not to subjectively exclude possible outliers but rather show how almost all models fit the regression line and allow comparison where all data points are used. The residuals from the OLS regressions were tested for auto correlation and fitting to a normal distribution. Based on those tests, no adjustments to the regression results were required.

Results and Discussion:

Table 1 shows the OLS regression results for the CMIP5 scenarios of Historical, RCP 4.5, RCP 6.0 and RCP 8.5 and for CMIP6 scenarios of Historical, SSP3 7.0 and the CMIP6 renditions of the CMIP5 RCP 4.5 and 8.5 scenarios. The ΔT versus ΔT regression for all scenario combinations was included with that for ΔT versus F2x/λ even though differences between the Historical and Future scenarios were expected to produce similar results with both regressions. With ΔT there were more model data available than for that with F2x/λ values and more scenario combinations to compare. The slope t and r squared values in the table show a very strong correlation for the CMIP5 and CMIP6 Future scenarios between the GMST change and the climate sensitivity parameter. The Historical scenarios for CMIP5 and CMIP6 were expected to show little correlation for these relationships and in fact show no correlation.

R is abbreviated for RCP and the 2 numbers following are the forcing change goal for that scenario, i.e. R45 stands for RCP4.5.  The R designations are carried over from CMIP5 to CMIP6.  S70 is unique to CMIP6 and has full designation as SSP3 7.0.

The results in Table 3 are from 1000 simulations of the models referred to as Reproduction Models that were constructed to reproduce the regression results of the CMIP5 and CMIP6 scenario ensembles in Table 1. The simulation models for regression used the following equations for X and Y, the independent and dependent variables, respectively:

X=(ΔR/F2x)*F2x[i]/λ[i], where X is the metric to which the individual model GMST change in the scenario should correlate without a variable negative forcing altering the relationship.

Y=(ΔR/F2x)*F2x[i]/λ[i]+rnorm(n=1, mean=K*Diff[i],sd=SD), where Y is the simulated change in the individual model GMST over the scenario time period.

In the equations, ΔR is the change in net outgoing radiation from ΔR=ΔF-ΔN with ΔF being the change in forcing and ΔN being the TOA radiative imbalance. These variables derive from the global energy budget ΔT=(ΔF-ΔN)/λ, where λ is the climate feedback parameter. The value used for ΔN is the mean for ΔN for the scenario model ensemble and was taken for CMIP5 from KNMI Climate Explore (reference 16) and for CMIP6 was taken from ESGF Node of DKRZ (reference 17). The values for ΔF changes and the aerosol/cloud forcing changes used for determining the K values were taken from pik-potsdam (reference 18), except for the special case of ssp 370 where the aerosol/cloud forcing changes were taken from Fiedler (reference 19). F2x is the mean radiative forcing for a doubling of atmospheric CO2 concentration for the scenario ensemble being considered. F2x[i] is the F2x for the individual model in the scenario. λ[i] is the individual model feedback parameter. Diff is the difference of the individual model feedback parameter from the mean of the scenario model feedback parameters. K is a tunable model parameter that determines how much the individual model feedback parameter is compensated in moderating the Historical ΔT.

There have been a number of papers in the climate science literature to justify assuming that the other tunable Reproduction model parameter, which is the standard deviation, SD, in the random normal function that adds noise to the Y variable, can be considered at least partially attributable to the different choices available to the modelers of the individual models analyzed here. The tendency of the models to compensate the GMST changes in the Historical period for varying individual model climate sensitivities in bringing the results more in line with the observed GMST changes points to modelers decisions adding to overall uncertainty of the model results. The structure variation from model to model could also determine the bounds of the potential influence of the modelers’ decisions in this matter. I have attempted to categorize the Reproduction model by searching the literature for similar examples. The best examples found were presented in one paper (reference 24) that dealt with stochastic and endogenous decision dependent uncertainty. A quote from reference 24 describes endogenous uncertainty in these models as: “A problem is classified as having endogenous uncertainty when decisions that are part of the problem to be solved, influences the uncertainty of parameters that are also part of the problem.”

Table 2 below lists the parameter values used in the Reproduction Model.

The fixed parameters were used at values noted previously and taken from the literature and applied to the scenarios as reasonable weights for increasing the total net forcing in the scenario progression from Historical to R85.

The tunable noise parameter of SD was applied at different values for CMIP5 and CMIP6 but with the same values across the CMIP scenarios. The tunable parameter, K, is the crux of this entire analysis and is the essential ingredient that causes most of the disconnection between the Historical and Future scenarios and at the same time closely reproduces the actual model results. The negative K for the Historical period, that is multiplied by the difference of the individual model feedback parameter, λ, and the scenario ensemble mean of λ, produces a more negative or positive forcing that compensates the resulting GMST change, ΔT, for feedback parameters by the amount they deviate from the mean. The future scenarios with the exception of S70, have positive K values that, instead of compensating for feedback differences, enhances them.

The ratios of the K parameter for the scenarios were used in this analysis based on what was found in literature searches. In other words for CMIP5, where the Historical K is -0.30 and the Future K is approximately half that of the Historical but positive, the change in the negative forcing from aerosol and cloud effects in the Historical period became nearly two times more negative than the forcing in the Future period became less negative. Only the magnitude of K was tuned, but not the ratio between Historical and Future scenarios.

The Reproductive Models reproduce closely the results obtained from the CMIP5 and CMIP6 scenario ensembles of models even though fitting with the tunable parameters for this analysis was by no means exhaustive, but rather carried out with a few subjective iterations.

Table 4 contains the results for the Reproduction Models without the factor that compensates the individual Historical model ΔT for the differing individual model feedback parameters. The scenario model ensemble correlations are affected in this case by the differing scale for net Forcing change and the SD noise factor. It can be seen from the table that the median probability correlations for both the CMIP5 and CMIP6 models of the Historical ensemble for ΔT versus F2x/λ and scenario ΔT versus ΔT have become significant and that those for the future scenarios remain significant and with slope t and r squared values generally not as large as those with the compensating factor.

The findings here are fully consistent with those in Rotstayn and Collier (reference 25) who found that the TCR values for 14 CMIP5 models had no significant correlation with the GMST change in the Historical period (1860-2000) while in the same period the negative aerosol forcing change correlated with the GMST change with r value over 0.90. In other words the negative forcing that varied from model to model was changing what otherwise should have been a significant correlation between TCR (and ECS) and the change in GMST in the Historical period.

There have been two papers published where the individual model Historical aerosol forcing for some of the CMIP5 and CMIP6 models using a fixed SST and ocean ice covering are determined. These data provided an opportunity for the analysis here to attempt to correct the Historical GMST changes for aerosol forcing and in turn regress the adjusted GMST change against F2x/λ. There were only 12 models for these regressions but the results in Table 7 show that the adjusted GMST changes become very significant and have reasonably high r squared values. The comparison of the t and r squared values between the unadjusted and adjusted Historical GMST changes shows most definitely and directly that the aerosol forcing applied in quantitatively different amounts to the individual models is the determining factor in disconnecting the model GMST changes from the model’s climate sensitivity.                                                                             

 

The adjusted GMST change was derived using the following adjustment equation:

ΔTcor= ΔTHist- (F2x(i)/F2xmean)*((0.65*ΔFaer(i))/λ(i))) where ΔTcor is the individual model GMST change corrected for the individual model aerosol forcing, ΔTHist is the uncorrected derived individual model GMST change, F2x(i) is the individual model forcing for a doubling of the atmospheric CO2 concentration, F2xmean is the ensemble mean of F2x, ΔFaer(i) is the Historical individual model aerosol forcing and λ(i) is the individual model feedback parameter. The values of ΔFaer and ΔNaer were combined under the assumption that these two variables track one another

Table 8 shows the OLS regression for CMIP5 and CMIP6 scenarios for all scenario combinations of ΔN versus ΔN.

Though the Reproduction Models did not directly take into account any ΔN differences between the Historical and Future scenarios, the results are presented in the table to show another disconnection between the Historical and Future periods. While the Zelinka paper (reference 27) indicates that individual CMIP6 models could have Historical GMST compensation for differences in climate sensitivity from ΔN that is independent of the negative aerosol compensation, it is judged that the disconnect presented here between the ΔN for the Historical and Future periods is directly related to the negative aerosol compensation disconnection. The aerosol component and its effect on GMST change would have a corresponding ΔN component and thus if there is a Historical and Future disconnection due to aerosol there should be a corresponding one for ΔN. For CMIP5 scenarios the Historical to Future correlations are significantly negative for ΔN while for Future to Future scenarios the correlations are positive and high for ΔN – as they were for ΔT. For CMIP6 scenarios the results are much the same as for CMIP5 except that the Historical to Future correlations while tending towards negative are not significant.

Conclusions:

In this analysis it was shown that there is a statistically significant disconnection between the CMIP5 and CMIP6 Historical and Future period scenarios when considering the relationship between the individual model climate sensitivities and GMST values. The correlations of changes in model GMST for scenario to scenario ensembles and ensemble scenario GMST changes to F2x/λ provide a means for analyzing the degree of disconnection between the Historical to Future scenarios and connection for Future to Future scenarios.

As an aside, using F2x/λ as a simplified version of the energy budget and obtaining high correlations with GMST changes in the Future periods indicates that ΔR is a fairly constant value for these models where model to model variations in negative aerosol/cloud forcing are not an overwhelming factor.

The model ensemble correlations for both CMIP5 and CMIP6 Historical and Future scenarios can be closely reproduced with a simple model (Reconstruction model). This model accounts for negative aerosol/cloud forcing that can compensate GMST changes for differences in individual model climate sensitivities in the Historical period while allowing carry-over that forcing effect into the Future period scenarios and maintaining the higher scenario correlations in that period. The Reproduction model can provide a probable explanation for the Historical to Future disconnection that is consistent in time and forcing. Added evidence favoring the Reproduction model comes from the result of using the model without the λ compensation factor and the observation that without inclusion of that factor there are significant changes in the Historical period correlations(higher) and smaller but noticeable ones(lower) in the Future period scenarios. The results from adjusting the GMST changes in the Historical period for aerosol forcing adds more direct evidence that the aerosol forcing is the primary cause of the Historical GMST to climate sensitivity disconnection and is well aligned with the Reproduction model results. This added evidence negates the alternative explanation that the disconnection is the result of a scaling factor for a smaller ΔR in the Historical period. It also shows that the negative aerosol/cloud forcing carried over from the Historical periods to the Future periods increases the leverage that climate sensitivity has on GMST in the Future periods and thus increases Future correlations of ΔT to F2x/λ.

It should be noted that the 95% confidence intervals for the Reproduction model simulations for the Historical Period are sufficiently wide in some cases to show statistically significant slopes and correlations (but with a low probability) in the 1000 regressions carried out. That interval is related to the size of the tunable parameter of standard deviation. That standard deviation has to include the variations in how the models and modelers handle the variable application of the negative aerosol/cloud forcing and that variation might well be truncated by some common sense judgments on selections. The Reproduction model provides a wide range of choices but the modelers of individual models as a group could very well have independently selected from near the middle of the distribution of choices and that appears to be the case.

What is the import of the disconnection of the ensembles of CMIP5 and CMIP6 models used in Historical and Future period scenarios? The process of using the Historical period model results for the climate variable of GMST change and how closely it matches the observed changes as a test of its credibility and capability of predicting future GMST changes becomes questionable if model selections of parameters and processes were aimed at better reproducing the observed GMST changes and more specifically those choices related to the resulting negative aerosol/cloud forcing and potential for compensating for models with higher (and lower) climate sensitivities.

Alternatively if increasingly more negative aerosol/cloud forcing in the Historical period is handled as a natural feature of the model and does not get used either intentionally or unintentionally to moderate GMST changes, and further, if the Future period sees the aerosol/cloud forcing getting less negative, it could be supposed that a model with a higher climate sensitivity could reasonably well reproduce the observed GMST changes. If all the models had nearly the same Historical and Future changes in the negative aerosol/cloud forcing the correlations performed in this analysis would not show the disconnections that were found. That means that only some – or none – of the models could be getting the negative forcing reasonably correct.

The finding of this analysis that the ΔN values for the ensemble Historical and Future periods do not correlate or are anti-correlated adds another independent means of the disconnection of the two periods. As stated previously the ΔN data while being an independent source of data it is not necessarily independent of the main aerosol effect.

The only practical way out of this dilemma in my view is to find, or at least keep looking for, a more precise method of determining the observed climate sensitivity with narrowed confidence intervals. The observed variables with the largest uncertainty required for the energy budget to estimate the observed climate sensitivity are the aerosol/cloud forcing and ΔN. It is these variables that are also available in the climate models to compensate GMST Historical changes for variable climate sensitivities. It is therefore those two forcing entities that need attention, in the observations and the models.

The use of more complex and informed models that include endogenous decision uncertainty for modeling selection leading to variations in negative forcing between individual models in the Historical period could provide some needed insights in this area of climate science.

References [ References]

142 responses to “Disconnect in the relationship between GMST and ECS

  1. typing error

    “Abstract. An analysis is presented of he disconnection between the CMIP5 and” …THE !

  2. Very interesting study by Fritsch. Thank you. I did a correlation study of the CMIP5 forcings. Here are the results.

    https://tambonthongchai.com/2018/08/31/cmip5forcings/

  3. Thank you for another analyses revealing the problems with projecting future GMST changes.

    However, it is important to recognise that the entire climate scare campaign is based on what may be a false premise – i.e, that global warming will be harmful or worse catastrophic or apocalyptic.

    https://judithcurry.com/2020/02/08/economic-impact-of-energy-consumption-change-caused-by-global-warming/

    https://doi.org/10.3390/en12183575

    https://doi.org/10.1007/s10018-020-00263-w

  4. Kenneth Fritsch: Thank you for the essay.

    This is a little confusing: The ratios of the K parameter for the scenarios were used in this analysis based on what was found in literature searches. In other words for CMIP5, where the Historical K is -0.30 and the Future K is approximately half that of the Historical but positive, the change in the negative forcing from aerosol and cloud effects in the Historical period became nearly two times more negative than the forcing in the Future period became less negative. Only the magnitude of K was tuned, but not the ratio between Historical and Future scenarios.

    • Matthew, the negative forcing change from the literature for the various scenarios was used in the model to ratio the value of K amongst the scenarios. In practice a starting value of magnitude K for the Historical period was fitted and followed by using the literature based ratio of values for the Future scenarios to determine the K value for those scenarios.
      I should have used a subtext for the K values or better used a K value for the historical period with coefficients times that K value for the Future scenarios that was based on the aforementioned ratios.
      Thanks for pointing to the confusion I created here.

  5. Occam has been my hero for many, many years.

    People spend hours diagnosing why something does not work and then someone plugs it in. My network quit. After a day without internet, I went into the attic and found out the circuit was out that powered a splitter.

    After many years of trying to understand how temperature changes caused ice to advance and retreat, in April, 2007, Tom Wysmuller presented the Theory that Maurice Ewing and William Donn developed in the 1950’s, explaining that it snows more when oceans are warm and thawed and advancing ice causes colder. The more ice dumping into the oceans causes warm saltwater ocean currents to chill to below freezing and sea ice forms and cuts off evaporation and snowfall and sequestering of enough ice to maintain the ice sheets. The ice sheets spread and cause more cooling until the ice is depleted, then the ice sheets retreat and cause warming. Then the cycle repeats, again and again.

    An Occam Razor, Simple, Factor is ignored forever, because natural causes of climate change are not scary and do not give the power to tax and control people.

    Use what you can of this,

    The extreme alarmists are well aware that if they can keep their opposition focused only on emissions, They will continue to win. The public sees the alarmists trying to lower the carbon footprints and the people on the other side push back only using information related to CO2 and carbon footprints. Even bad commercials sell products. The alarmists win this, almost every time.

    Self-Correcting Climate Temperatures and Sea Levels are regulated by internal response due to factors related to much more abundant water, in all its phases and phase changes. We must Study, Understand and Teach Natural Factors that cause the climate system to be Stable and Self-Correcting in repeating warm and cold bounds.

    Most everyone looking at climate, has their own opinion on ECS, Equilibrium Climate Sensitivity.

    That is treating the Climate System as a Statics Problem.

    The Climate System is a Dynamics Problem, the Climate System has never been in a Steady State of Equilibrium.

    Different parts of the climate systems are resonating, based on local internal response and based on external forcing and internal exchange of energy with the other regions.

    The alarmist groups are well funded, well organized, and well infiltrated into all the major groups that are fighting back. They promote the idea that climate is Chaotic, except when exposed to increasing manmade CO2, the promote the idea that climate is complicated and not understandable except when exposed to increasing manmade CO2. They are keeping all the ballgames inside the Emissions Home Field, where they Hire and Fire the Umpires.

    This is supported by serious Gaslighting.

    The Climate System is a Dynamics Problem with Energy stored in Oceans, and then removed from the system as it produces the Ice that is Sequestered, which is Energy Adsorbing when it Thaws later, keeping cold times cold. These are Dynamic Cycles and not Steady State Equilibrium and any time.

    • Great post Herman.

      “The alarmist groups are well funded, well organized, and well infiltrated into all the major groups that are fighting back. They promote the idea that climate is Chaotic, except when exposed to increasing manmade CO2, the promote the idea that climate is complicated and not understandable except when exposed to increasing manmade CO2. They are keeping all the ballgames inside the Emissions Home Field, where they Hire and Fire the Umpires.”

      We think very similarly.

    • It adds up to a conclusion you may find very surprising — and you get points for guessing which denier said this. “In sum, a strategy must recognise what is possible. In climate research and modelling, we should recognise that we are dealing with a coupled non-linear chaotic system, and therefore that the long-term prediction of future climate states is not possible.” It means that most of “the science” — the data interpretation, the methods and the theories are utterly inadequate to the task of explaining climate for us. But both sides of the climate battle continue to insist on a certainty that is impossible – and continue a battle in which one side is heavily outgunned. The climate change battalion is all of the global scientific institutions, the liberal press, governments, major scientific journals, etc. Opposed is a ragtag collection of a few marginalized cheerleaders for curmudgeons with crude and eccentric theories they insist is the true science. from – https://watertechbyrie.com/2015/06/08/attrition-in-the-climate-trenches/

      Pope’s climate metaphors, Lowey’s dark matter inspired rejection of the empirical gravitational constant and Vournas’ invention of a new physical constant to support rotational warming are crude and eccentric theories. Scientific paradigms evolve – as they have for climate science. But these guys do so only kicking and screaming.

      • Robert:
        “Pope’s climate metaphors, Lowey’s dark matter inspired rejection of the empirical gravitational constant and Vournas’ invention of a new physical constant to support rotational warming are crude and eccentric theories. Scientific paradigms evolve – as they have for climate science. But these guys do so only kicking and screaming.”

        It was a very windy week in Greece, 7-8 Bufford – I couldn’t go out for the necessary exercise-walk, wearing the obligatory mask of course.
        I felt comforted though, the windy and sunny weather were supplying our grid with cheap renewable electric power.
        Many thousands tons of coal were being preserved.

        Every ton of carbon we do not burn will be in very much demand for the future generations.

        To-day is completely calm. Not even a slightest movement of the air. Hopefully the sun is still shining well. Later on, when it is warmer I’ll go out.
        We are in National lockdown – things are not well with the coronavirus.

        Robert,
        “… Vournas’ invention of a new physical constant to support rotational warming…”

        I did not invent the new physical constant. What I did is to discover it.
        This constant is a universal constant, that is all.
        This universal constant is a good universal constant.

        The faster rotating planets appear warmer planets, everything else equal.
        Universal constant doesn’t warm planet’s surface. The solar energy is what warms planet’s surface.

        Also you said something about “… kicking and screaming.”

        http://www.cristos-vournas.com

      • We calling it the Christos constant?

      • “Lowey’s dark matter inspired rejection of the empirical gravitational constant” – Robert I. Ellison

        It just goes to show your lack of knowledge in the subject. The acceleration of baryonic matter on the surface of the Earth is known to change depending on one’s location. The term “constant” is a misnomer.

      • GRACE data. It hardly falsifies Newton and Einstein.

        https://cdn.earthdata.nasa.gov/conduit/upload/8054/matter_2.jpg
        “This map, created using data from the Gravity Recovery and Climate Experiment (GRACE) mission, reveals variations in the Earth’s gravity field. Dark blue areas show areas with lower than normal gravity, such as the Indian Ocean (far right of image) and the Congo river basin in Africa. Dark red areas indicate areas with higher than normal gravity. The long red bump protruding from the lower left side of the image indicates the Andes Mountains in South America, while the red bump on the upper right side of the image indicates the Himalayan mountains in Asia. (Image prepared by The University of Texas Center for Space Research as part of a collaborative data analysis effort with the NASA Jet Propulsion Laboratory and the GeoForschungsZentrum in Potsdam, Germany)”

      • Your response shows your lack of understanding of dark matter candidates. I’m advocating a self-interacting dark matter (SIDM) model which is a mainstream solution in the simulation of satellite dwarf galaxies.

        The GRACE data isn’t ‘proof’ that nucleic density matter doesn’t exist at Earth’s core, because this dark matter would only interact very weakly with the two spacecraft, just like ordinary matter. The *strong* gravitational pull is only felt on similar matter that exists at the cores of the Moon (millennial cycle), the sun (100,000-year cycle) and the planets Jupiter & Venus (405,000-year cycle).

        It’s beyond your knowledge range because deep down, you’re only a glorified salesman who’s learnt some basic science in order to sell products on commission to the developing world.

        You’re not qualified to denounce the exotic core hypothesis, which can be easily tested for by use of satellites to monitor solid body earth-tides, which are predicted to be increasing.

        You shouldn’t be calling sceptics “curmudgeons” because this would include Dr. Judith Curry, in her belief that natural variation plays a greater than 50% role in current climate change.

        You’re not a scientist.

      • I’ll just explain one thing again – Judith Curry is not a sky-dragon slayer, Gravity sucks and so do you.

      • The current theory of gravity doesn’t dovetail with quantum mechanics – which to me suggests it needs a complete overhaul.

        A spinning helical ‘corkscrew’ graviton model does just that. It allows for a *strong* gravitational interaction between nucleic density matter cores, with a stronger force on the orbital plane.

        A tidal forcing hypothesis for climate change is therefore a legitimate contender.

      • There is a theory of gravity contained in general relativity field equations – and experimentally validated – and the Lowey thought bubble.

      • “There is a theory of gravity contained in general relativity field equations – and experimentally validated” – Robert (the engineer)

        Professor Carlo Rovelli – a physicist & author in the philosophy of physics would give your attitude caution:

        “..found that even in the most extreme of conditions, his argument and calculations cannot be disproven. Does this mean that we should take everything he did as correct? That he never made mistakes? On the contrary. In fact, few scientists have made as many errors as Einstein. Few have changed their minds as frequently as he did.”

        https://inews.co.uk/news/science/carlo-rovelli-making-mistakes-sign-of-intelligence-einsteins-errors-757427

      • Repeating yourself doesn’t mean help. There field equations have been confirmed experimentally many times. That seems to be the step you don’t understand. Go back to Feynman and take in the bit after guesses.

      • Chaos is defined according with the very fast movement of all the parts consisting a system. Like the turbulence in the fluids flow. It is chaotic for us, for us observing the turbulent flow.
        We call chaotic everything we are not able to follow and “see” in every detail.

        http://www.cristos-vournas.com

  6. hit something with a hammer,
    If you hit something with a hammer, the something vibrates. The energy was delivered by the hammer, but the frequency and amplitude of the vibrations are due to internal natural response.
    Energy comes from the sun, but the climate system has internal response cycles, natural frequency vibrations, that depend on internal properties. Climate Science has been studied by looking at some correlations of the hammer strikes and internal response, but they have never looked at the internal response as natural internal cycles that sometimes are responding with the hammer motion and sometimes responding against the hammer motion. The frequencies of the ice cycles have varied from many thousands of years to now only about one thousand years, peak to peak while the external forcing from the sun has repeated the same hammer strikes, sometimes hitting the northern hemisphere more and sometimes hitting the southern hemisphere more. Ice Core data from Greenland and Antarctic show the warm and cold cycles have different frequencies and amplitudes. There are different masses of water and ice in the two hemispheres. Both hemispheres have temperature cycles that have the same bounds, the same upper and lower temperature limits, but the timing does not match. The thermostat control in both hemispheres is sea ice, the thermostat setting is the temperature that the sea ice freezes and thaws.
    In colder times ice is spread over larger ocean land areas and in warmer times ice is spread over less ocean and land areas.
    Ice cold meltwater flows into the oceans and onto the land from the great sequestered ice sheets and glaciers.
    Land ice is pushed into the oceans from the great sequestered ice sheets and glaciers and the thawing ice cools the oceans, when the supply of ice that is being dumped is adequate, the sea ice forms and prevents the sequestering of more ice. The ice flowing into the oceans from glaciers and ice sheets thaws and chills the saltwater to below freezing, like in our ice cream makers. When the supply of ice that is being dumped in the polar oceans is not adequate, sea ice thaws and the evaporation and snowfall rebuilds the sequestered ice until sea ice forms again.
    The climate got colder over the past fifty million years because land increasingly blocked flow of warm tropical water currents around the equator and sent more warm water into the polar regions. Warm currents in polar regions promote snowfall and sequestering of ice. Climate gets continually colder until sea ice forms and stops the snowfall, Climate warms until the sea ice is thawed and the ice machines are turned on again. There is always more ice extent and more ice dumped into the oceans in colder times and less ice in warmer times, that is remarkably simple and amazingly easy to understand.
    This also puts bounds on sea level, when the sea ice is thawed, evaporation of polar oceans and sequestering of ice on land in cold places stops and reverses sea level rise, this has happened. Since the atomic clock was started to keep track of Length of Day, the number of leap seconds that have been added to adjust the clocks has decreased in frequency. This does mean sea level has gone down since the atomic clock was started in 1972.
    We put ice in our drinks because we know the resulting temperature is correct. When the ice is depleted the drinks warm.
    When the drinks warm, we add more ice.
    The drinks are the oceans of earth.
    The ice machine is powered by the sun. The sun heats tropical water, the energy filled water is transported to the polar oceans where evaporation and snowfall and resulting IR out forms ice that is sequestered on land. The ice piles up on the land, spreads on the land pushes ice shelves and ice bergs out into the oceans. The thawing ice cools the land and the oceans. This is not considered by climate scientists; they do not include any cooling by thawing ice in their theory or models. They consider it a disaster when ice is flowing faster into the oceans or when an ice shelf breaks off and flows away. Look at the energy balance charts, presented by the different groups, none include cooling by thawing ice. I have asked multiple climate scientists that very question. You can find any energy balance chart in their presentations and on their websites, ice is not included. The ice that is thawing and cooling the oceans at any given time is from snowfall and IR out hundred or thousands of years earlier, They consider evaporation and forming of water and ice a closed system inside the climate system that results in no more IR out. There is IR out and some water and ice falls where it does immediate cooling of the climate systems and some ice is sequestered where it will be stored in a freezer for use many years later.

    Herman A (Alex) Pope

    • Herman:
      “Energy comes from the sun, but the climate system has internal response cycles, natural frequency vibrations, that depend on internal properties. Climate Science has been studied by looking at some correlations of the hammer strikes and internal response, but they have never looked at the internal response as natural internal cycles that sometimes are responding with the hammer motion and sometimes responding against the hammer motion.”

      Exactly.

      What I observed is that for the slow axial spin Mercury and Moon have
      Te > Tmean

      And for faster rotating Earth and Mars Tmean > Te

      Herman, it is a confirmation of what you said:

      “the internal response as natural internal cycles that sometimes are responding with the hammer motion and sometimes responding against the hammer motion.”

      http://www.cristos-vournas.com

    • When the planet warms ice becomes water. The phase change involves conversion of sensible heat to latent heat. When water evaporates – another phase change due to warming and increased internal kinetic energy – water vapour rises in the troposphere until it condenses out to water or ice and the internal, latent heat energy is released as sensible heat. It is all there in the budgets – nothing was forgotten.

      https://scied.ucar.edu/sites/default/files/images/large_image_for_image_content/radiation_budget_kiehl_trenberth_2011_900x645.jpg

      The initiation of glacials occurs with low summer insolation at high northern latitudes. Ice survives over summer until at a critical point there is runaway ice sheet growth and the planet cools. The cooler planet means less evaporation and increased aridity. Cool conditions mean that there is less biological respiration releasing CO2 into the atmosphere. The combination of aridity and CO2 starvation reduces vegetation cover opening up surfaces to wind erosion. Dust is deposited on ice sheet surfaces lowering albedo and initiating melting.

      http://clivebest.com/blog/wp-content/uploads/2016/01/Glacial-cycles-1-768×346.png
      http://clivebest.com/blog/?p=8679
      “The last 800,000 years of glacial cycles. Ice Volume (LR04) in grey, Eccentricity in black, EPICA (Antarctic) temp (red), dust(purple), CO2(yellow). The current interglacial is most similar to that 400,000 years ago which also coincided with low eccentricity.”

      A combination of low summer insolation and reduced heat transport north in the Atlantic – that’s another story – may jointly trigger runaway ice sheet growth.

      https://watertechbyrie.files.wordpress.com/2014/06/smeed-fig-71-e1523915527771.png

      • Robert,
        “When the planet warms ice becomes water. The phase change involves conversion of sensible heat to latent heat. When water evaporates – another phase change due to warming and increased internal kinetic energy – water vapour rises in the troposphere until it condenses out to water or ice and the internal, latent heat energy is released as sensible heat. It is all there in the budgets – nothing was forgotten.”

        Well, it is so far all right.

        “The initiation of glacials occurs with low summer insolation at high northern latitudes. Ice survives over summer until at a critical point there is runaway ice sheet growth and the planet cools. The cooler planet means less evaporation and increased aridity. Cool conditions mean that there is less biological respiration releasing CO2 into the atmosphere. The combination of aridity and CO2 starvation reduces vegetation cover opening up surfaces to wind erosion. Dust is deposited on ice sheet surfaces lowering albedo and initiating melting.”

        It is a pure fantasy, who told you that, Robert? How, for Earth’s sake, dust from the still warm Africa – no matter what glacials up North occur, how dust will prevail the snow?

        Robert: “The initiation of glacials occurs with low summer insolation at high northern latitudes.”
        You describe the climate warming we are witnessing now.
        So it is the dust, Robert… not the CO2 emissions which warms planet.

        Robert: “The combination of aridity and CO2 starvation reduces vegetation cover opening up surfaces to wind erosion.”

        You do confirm here there were periods in Earth’s History when the CO2 starvation reduced vegetation cover.

        http://www.cristos-vournas.com

      • This paper has been discussed here – https://www.pnas.org/content/115/9/2026

      • Interesting research, thank you, Robert.

        http://www.cristos-vournas.com

  7. However, it is important to recognize that the entire climate scare campaign is based on what may be a false premise –

    That the King Who Has No Clothes On, the Climate Alarists, has even a clue as to what caused past natural climate change or even less of a clue as to what will cause future climate change.

    • Alarists should have been Alarmists.

    • …has even a clue as to what caused past natural climate change or even less of a clue as to what will cause future climate change.

      You should read more.

    • It’s irrelevant what caused past natural climate change. What is relevant is the impacts. Empirical evidence suggests global warming is beneficial and global cooling is harmful. Climate research should focus on the impacts of climate change (warming and cooling).

  8. Tapio Schneider put these graphs together that I purloined from a video that I will post below.

    These lines model solutions. It should be recognised that there is no single deterministic model solution. Some of the larger centres do multiple runs – and presumably their bar is the mean of solutions – or the 50% probability in a pdf. Other centers have less computer resources. The difference according to Tapio Schneider is cloud. Cloud feedback is positive – the question is how positive.

    https://watertechbyrie.files.wordpress.com/2020/02/cloud-modelling.png

    There is no computer existing that has anywhere near the power to model climate at a cloud resolving scale using fundamental equations of state.

    https://watertechbyrie.files.wordpress.com/2019/12/cloud-physics.png

    The results show a radical loss of marine stratculous at realisable if uncertain CO2 concentrations that would transform the world rapidly to PETM conditions.

    https://watertechbyrie.files.wordpress.com/2019/09/cloud-computation.png

  9. I see that Mr Fritsch is using the ECS and also the TCR. What I find is that the TCR is a statistically flawed device that has no interpretation in the real world.

    Pls see

    https://tambonthongchai.com/2020/11/10/a-probability-distribution-function-of-the-transient-climate-response-to-cumulative-emissions/

  10. The ECS and the TCR are not compatible. It is therefore not possible to use both to explain the same phenomenon. Pls see

    https://tambonthongchai.com/2020/08/26/a-mathematical-inconsistency/

    • chaamjamal, thanks for the links. In my analysis here I used regression of GMST change versus F2x/λ which is ECS. I did not use TCR. I also used GMST change versus GMST change for various scenarios.

      It should be remembered here that these regressions are within scenario ensembles. I believe I have shown in this analysis that if the differences of the negative aerosol related forcing are removed from the individual models (or that it is overwhelmed by the GHG forcing change as in the Future scenarios) that the individual model GMST change versus F2x/λ has a high correlation. This result also indicates that the evidently small differences in the ocean heat uptake among the individual scenario models has little effect on these correlations.

  11. …wonder what percent of global atmospheric aerosols are created by tornado, cyclonic, hurricane and Coastal windstorm activities?

  12. Herman, you have it right: “However, it is important to recognize that the entire climate scare campaign is based on what may be a false premise –

    That the King Who Has No Clothes On, the Climate Alarmists, has even a clue as to what caused past natural climate change or even less of a clue as to what will cause future climate change.”
    So what can be done – in the face of manipulative and suppressive media – to communicate this insight?

    • Repost in intended place

      It’s irrelevant what caused past natural climate change. What is relevant is the impacts. Empirical evidence suggests global warming is beneficial and global cooling is harmful. Climate research should focus on the impacts of climate change (warming and cooling).

  13. The intractable problem of climate forecasting in a nonlinear world remains. Models can’t do it. The best they can provide is a probability distribution function. And we are not up to speed with that. Until then you can can dance with angels on pinheads – but still not extract useful information from models structurally unsuited to the purpose they are being put to.

    e.g. https://www.pnas.org/content/116/49/24390

    The chart below includes CFC’s and nitrous oxides – about 8% of the total. It doesn’t include anthropogenic sulfate and black carbon – that have a significant net warming effect.

    https://www.epa.gov/sites/production/files/2016-05/global_emissions_sector_2015.png

    Methane comes from feedlots, rice paddies, sewage plants, landfill and fugitive emissions. Also from cows – but that’s in the agricultural sector.
    Cows and rotational grazing are the problem and the solution there. Along with reclaiming deserts and restoring and conserving rangeland, forest, farms and wetlands.

    The solutions are obvious. Reduce pollution, strengthen infrastructure to cope with extremes whatever their cause and innovate across sectors including in energy generation.

    Warming or cooling well outside the bounds of a steadily warming world is possible. Can’t do anything about that. What we can do is reduce anthropogenic pressures and build prosperous and resilient communities in vibrant landscapes.

  14. Pingback: Disconnect in the relationship between GMST and ECS - Trending News, Latest Trending News Today, Viral News, Popular News Headlines - Journal6TV

  15. Pingback: Disconnect in the relationship between GMST and ECS |

  16. 1. Earth’s Without-Atmosphere Mean Surface Temperature calculation
    Tmean.earth

    So = 1.361 W/m² (So is the Solar constant)
    S (W/m²) is the planet’s solar flux. For Earth S = So
    Earth’s albedo: aearth = 0,306

    Earth is a smooth rocky planet, Earth’s surface solar irradiation accepting factor Φearth = 0,47
    (Accepted by a Smooth Hemisphere with radius r sunlight is S*Φ*π*r²(1-a), where Φ = 0,47)

    β = 150 days*gr*oC/rotation*cal – is a Rotating Planet Surface Solar Irradiation Absorbing-Emitting Universal Law constant
    N = 1 rotation /per day, is Earth’s axial spin
    cp.earth = 1 cal/gr*oC, it is because Earth has a vast ocean. Generally speaking almost the whole Earth’s surface is wet. We can call Earth a Planet Ocean.
    σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant

    Earth’s Without-Atmosphere Mean Surface Temperature Equation Tmean.earth is:

    Tmean.earth= [ Φ (1-a) So (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴

    Τmean.earth = [ 0,47(1-0,306)1.361 W/m²(150 days*gr*oC/rotation*cal *1rotations/day*1 cal/gr*oC)¹∕ ⁴ /4*5,67*10⁻⁸ W/m²K⁴ ]¹∕ ⁴ =
    Τmean.earth = [ 0,47(1-0,306)1.361 W/m²(150*1*1)¹∕ ⁴ /4*5,67*10⁻⁸ W/m²K⁴ ]¹∕ ⁴ =
    Τmean.earth = ( 6.854.905.906,50 )¹∕ ⁴ = 287,74 K

    Tmean.earth = 287,74 Κ

    And we compare it with the
    Tsat.mean.earth = 288 K, measured by satellites.

    These two temperatures, the calculated one, and the measured by satellites are almost identical.

    Conclusions:
    The mean surface temperature equation

    Tmean = [ Φ (1-a) S (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴
    produces remarkable results.
    The calculated planets temperatures are almost identical with the measured by satellites.

    Planet…Te.incompl…Tmean…Tsat.mean
    Mercury….439,6 K…….325,83 K…..340 K
    Earth………255 K………287,74 K…..288 K
    Moon……..270,4 Κ……..223,35 Κ…..220 Κ
    Mars……209,91 K……..213,21 K…..210 K

    The 288 K – 255 K = 33 oC difference does not exist in the real world.
    There are only traces of greenhouse gasses.
    The Earth’s atmosphere is very thin. There is not any measurable Greenhouse Gasses Warming effect on the Earth’s surface.

    http://www.cristos-vournas.com

  17. In all this talk of climate models, why no mention of the Russian INM-CM4/5 models, the only one that closely matches recent climate development?

    This is an example of a question that answers itself.

    https://www.researchgate.net/profile/Andrey_Gritsun2/publication/328542382_esd-9-1235-2018pdf/data/5bd36178a6fdcc3a8da91c0c/esd-9-1235-2018.pdf

  18. Richard Greene

    Temperature data before 1920 are not global — very few Southern Hemisphere measurements.

    Temperature data from 1920 to 1950 have far too few numbers from the Southern Hemisphere

    The temperature trend from 1940 to 1975 was originally reported as global cooling of -0.3 to -0.5 degrees C. … but after many arbitrary “adjustments”, the period now has only -0.1 degrees cooling, or no cooling at all.

    Surface data from 1950 to 1979 still include far too much infilling (wild guesses that are never verified) and hundreds of “adjustments” every month.

    UAH temperature data after 1979, from weather satellites, has the potential for accuracy because the environment does not change, the troposphere is where the greenhouse effect occurs, and the scientists involved seem honest …which may be the most important attribute of all.

    Due to low data quality, no temperature data before 1979 are worthy of mathematical statistical studies.

    The author takes non-global, very rough temperature numbers before 1979 seriously, and studies the computer games that are called climate models.

    But outside of the Russian model, not one computer game makes predictions that are accurate.

    So these computer games merely represent the personal opinions of the people who own and program them.

    A real climate model MUST be based on a very detailed understanding of the physics of climate change. Such an understanding does not exist. So a real climate model, that makes accurate predictions, CAN NOT EXIST. The Russian INM model, that seems accurate, could be a “lucky guesser” — there are enough computer games around the world so one could appear to be accurate just by chance.

    With the low quality data available for analysis before 1979,
    I believe this study could be described as mathematical mass-turbation. When data quality are so low, no amount of statistical analyses can reach useful conclusions.

  19. Would geo engineering make all this climate science of ECS and TCR irrelevant?

    https://tambonthongchai.com/2020/08/28/geo-engineering-climate-change/

    • Not a question of when (we are doing it now) but think of it more like engineering the future. It’s what our species does, right?
      Follow this link to a international organization completely dedicated to understanding what could be done.
      https://theterraforming.strelka.com/

    • Geo engineering will transform a phoney threat of catastrophe into the real prospect of catastrophe. If alarmists can’t get the catastrophe that they want from nature, they can do it themselves.

    • Some of the answer is under our feet. Rattan Lal – himself a scientific treasure – estimates that some 500 Gigatonne (GtC) carbon has been lost from terrestrial systems since the advebt of agriculture. ‘Soil is like a bank account – we must replace what we have removed.”

      https://www.epa.gov/sites/production/files/2016-05/global_emissions_sector_2015.png

      This soil carbon store can be renewed by restoring land. Holding back water in sand dams, terraces and swales, replanting, changing grazing management, encouraging perennial vegetation cover and slowing erosion, precise applications of chemicals and adoption of other management practices that create positive carbon and nutrient budgets and optimal soil temperature and moisture. Atmospheric carbon is transferred from the atmosphere to soil carbon stores through plant photosynthesis and subsequent formation of secondary carbonates. The rate of soil carbon sequestration ranges from about 100 to 1000 kg per hectare per year as humus and 5 to 15 kg per hectare per year inorganic carbon. The near term potential for carbon sequestration in agricultural soils is approximately equal to the historic carbon loss of 80 GtC during the modern era. This is about 10 years of global annual greenhouse gas emissions. At realistic rates of sequestration 25% of current annual global greenhouse gas emissions could be sequestered over 40 years. In Australia a comprehensive program of ecological restoration across landscapes – worth every cent for many reasons – would enable all and more greenhouse gas emissions from energy to be offset.

  20. Well the TCR of a period of fast solar wind is a colder AMO and La Nina conditions, amplified by the changes in lower troposphere water vapour and low cloud cover which the ocean phases drive. So there’s no need to invoke aerosols for the 1970’s global cooling. It’s really neat how weaker solar wind states since 1995 have driven a warm AMO and increased El Nino conditions, amplified by increased lower troposphere water vapour and reduced low cloud cover. That even allowed the upper OHC to jump up a tad. What a wonderful design.

    • Ireneusz Palmowski

      This is obvious to people who can patiently observe solar and ocean parameters. Without actual observation, there is no kilmatology.

  21. The blind leading the blind:

    “Simulating the pandemic: What COVID forecasters can learn from climate models”

    https://www.nature.com/articles/d41586-020-03208-1

  22. Ken and Nic Lewis fall into the category of scientists that have a hard time in explaining good ideas in an English that is user friendly, readable and understandable.
    Judith and RE both are much more user friendly.
    I have a problem in understanding both the text, too convoluted, and the gist of the post. Nothing that a few more years at University (me) would fix.

    I note as an aside that DM has a post up at WUWT on ECS and TCR as I write which confirms the fact that observations are trending lower.
    Interesting as it corroborates this article indirectly.

    So, for those needing a simple message I hear this.

    Historical parts of the models of CMIP 5 and 6 are not compatible with present and future modelling.
    People composing the historical presentations modify the data on aerosols to make the models fit reality (observations) ad hoc.
    “ mainly pointing to negative aerosol and cloud related forcing in the Historical period as probable causes“

    This is at odds with the data for aerosols in future projection which only give positive forcing.

    A combination of erroneous past aerosol negative forcing and future erroneous positive forcing leads to a marked deviation and increase in forcing in models from that of observations (reality).

    I wish that that good science and good ideas that need to be discussed could be a little more succinct though brevity means nit pickers nit pick on ideas not fully qualified.

    Thanks for the presentation Ken, very appreciated

    • Thanks, angech, for mentioning me in good company – although I doubt Nic Lewis appreciates the comment.

  23. “We are living in a world driven out of equilibrium. Energy is constantly delivered from the sun to the earth. Some of the energy is converted chemically, while most of it is radiated back into space, or drives complex dissipative structures, with our weather being the best known example.” https://www.ds.mpg.de/LFPB/chaos

    Below is the spatial structure of the Pacific Ocean in its cool state. There are temporal patterns to this spatial pattern in which states shift – with the PDO anomaly persisting for decades while ENSO has the same temporal signature in the frequency and intensity of ENSO states. A cool PDO sees periods of more intense and frequent La Niña. These patterns in the Earth flow field are diagnostic of spatio-temporal chaos. Nothing mysterious – it is the usual behaviour of turbulent flow manifesting in characteristic ways in the Earth system.

    https://watertechbyrie.files.wordpress.com/2015/11/pdoenso.jpg

    The eastern Pacific has been cooler than average over much off the past thousand. High salt content in a Law Dome ice core is correlated with both enhanced zonal wind speed in the south Pacific and rainfall in eastern Australia.

    https://watertechbyrie.files.wordpress.com/2014/06/vance2012-antartica-law-dome-ice-core-salt-content-e1540939103404.jpg

    “Rayleigh-Bénard convection is a type of natural convection, occurring in a plane horizontal layer of fluid heated from below, in which the fluid develops a regular pattern of convection cells known as Bénard cells.” Wikipedia

    On a large scale Bénard cells form low level marine strato-cumulus at the marine boundary layer that are the largest source of global cloud variability. Closed cells persist for longer over cool water before raining out to form open cells.

    https://watertechbyrie.files.wordpress.com/2014/06/clement-et-al-e1512080464744.png

    This was by far the most important source of post hiatus warming. – https://www.mdpi.com/2225-1154/6/3/62

  24. I have just watched ‘Planet of the Humans’. Their thesis is that thee is a crunch coming in a few areas and that wind. solar and biomass are not solutions. It boils down to population and consumption that are driven by the poison of profit and economic growth. ‘Our human caused apocalypse’.

    https://www.youtube.com/watch?v=Zk11vI-7czE&ab_channel=MichaelMoore

    There is a crunch coming. The unavoidable future is cyberpunk. The singularity occurs on January 26th 2065 when an automated IKEA factory becomes self-aware and commences converting all global resources to flat pack furniture. Until then – endless innovation on information technology and cybernetics will accelerate and continue to push the limits of what it is to be human and to challenge the adaptability of social structures. New movements, fads, music, designer drugs, cat videos and dance moves will sweep the planet like Mexican waves in the zeitgeist. Materials will be stronger and lighter. Life will be cluttered with holographic TV’s, waterless washing machines, ultrasonic blenders, quantum computers, hover cars and artificially intelligent phones. Annoying phones that cry when you don’t charge them – taking on that role from cars that beep when you don’t put a seat belt on. Space capable flying cars will have seat belts that lock and tension without any intervention of your part. All this will use vastly more energy and materials this century as populations grow and wealth increases.

    Providing for this future starts with caring for country. Creating a more productive and flood and drought resilient agriculture. Holding back water in sand dams, terraces and swales, replanting forests and reclaiming deserts, changing grazing management, encouraging perennial vegetation cover, precise applications of chemicals and adoption of other management practices that create positive carbon and nutrient budgets and optimal soil temperature and moisture. I could we could reverse the annual loss of gigatonnes of carbon from soils and vegetation – and sequester 10’s or 100’s of gigatonnes – but that is not the primary objective.

  25. Very interesting !
    Mars and Moon satellite measured mean surface temperatures comparison:
    210 K and 220 K

    Let’s see what we have here:

    Planet……….Tsat.mean
    ……………….. measured
    Mercury………. 340 K
    Earth………….. 288 K
    Moon………….. 220 Κ
    Mars…………… 210 K

    Let’s compare then:
    Moon:
    Tsat.moon = 220K
    Moon’s albedo is amoon = 0,11
    What is left to absorb is (1 – amoon) = (1- 0,11) = 0,89

    Mars:
    Tsat.mars = 210 K
    Mars’ albedo is amars = 0,25
    What is left to absorb is (1 – amars) = (1 – 0,25) = 0,75

    Mars /Moon satellite measured temperatures comparison:
    Tsat.mars /Tsat.moon = 210 K /220 K = 0,9545

    Mars /Moon what is left to absorb (which relates in ¼ powers) comparison, or in other words the Mars /Moon albedo determined solar irradiation absorption ability:
    ( 0,75 /0,89 )¹∕ ⁴ = ( 0,8427 )¹∕ ⁴ = 0,9581

    Conclusions:
    1. Mars /Moon satellite measured temperatures comparison
    ( 0,9545 ) is almost identical with the
    Mars /Moon albedo determined solar irradiation absorption ability
    ( 0,9581 )

    2. If Mars and Moon had the same exactly albedo, their satellite measured mean surface temperatures would have been exactly the same.
    And this is very interesting !

    http://www.cristos-vournas.com

  26. Pingback: Weekly Climate and Energy News Roundup #431 | Watts Up With That?

  27. Mars and Moon have two major differences which equate each other:

    The first major difference is the distance from the sun both Mars and Moon have.
    Moon is at R = 1 AU distance from the sun and the solar flux on the top is So = 1.361 W/m² ( it is called the Solar constant).
    Mars is at 1,524 AU distance from the sun and the solar flux on the top is S = So*(1/R²) = So*(1/1,524²) = So*1/2,32 .

    (1/R²) = (1/1,524²) = 1/2,32

    Mars has 2,32 times less solar irradiation intensity than Earth and Moon have.
    Consequently the solar flux on the Mar’s top is 2,32 times weaker than that on the Moon.

    The second major difference is the sidereal rotation period both Mars and Moon have.
    Moon performs 1 rotation every 29,531 earth days.
    Mars performs 1 rotation every ( 24,622hours / 24hours/day ) = 1,026 day.

    Consequently Mars rotates 29,531 /1,026 = 28,783 times faster than Moon does.

    So Mars is irradiated 2,32 times weaker, but Mars rotates 28,783 times faster.
    And… for the same albedo, Mars and Moon have the same satellite measured mean temperatures.

    Let’s take out the calculator now and make simple calculations:

    The rotation difference’s fourth root is
    (28,783)¹∕ ⁴ = 2,3162

    And the irradiating /rotating comparison
    2,32 /(28,783)¹∕ ⁴ = 2,32 /2,3162 = 1,001625

    It is obvious now, the Mars’ 28,783 times faster rotation equates the Moon’s 2,32 times higher solar irradiation.

    That is why the 28,783 times faster rotating Mars has almost the same satellite measured mean surface temperature as the 2,32 times stronger solar irradiated Moon.

    Thus we are coming here again to the same conclusion:

    THE FASTER A PLANET ROTATES, THE HIGHER IS THE PLANETS MEAN SURFACE TEMPERATURE

    If Moon and Mars were the same distance from the sun, the faster rotating Mars would have been a warmer planet.

    Earth and Moon are at the same distance from the sun. The faster rotating Earth is warmer than Moon.

    This very important conclusion is based on satellite measured planets mean surface temperatures. It is based on the very reliable observations.

    And it is the confirmation that the planet axial spin (rotations per day) “N” should be considered in the fourth root in the ( Tmean ) planet mean surface temperature equation:

    Tmean.planet = [ Φ (1-a) So (1/R²) (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴

    http://www.cristos-vournas.com

  28. “Bezos makes first donations from $10 billion Earth Fund for fighting climate change”: https://www.washingtonpost.com/climate-environment/2020/11/16/bezos-climate-grants/

    It is getting even more quite lucrative to suggest human induced global warming…

    • Yes indeed. Imagine when the world finally realises that it’s not due to manmade CO2 emissions but a new gravity theory & natural tidal forcing?

    • There are always politics at the core of crude and eccentric sky-dragon slayer theories. Why are these fallacies not challenged by ‘skeptics’?

      https://scied.ucar.edu/sites/default/files/users/lisagard/radiation_budget_kiehl_trenberth_2008_big.jpg

      • Because I’m ahead of my time. Combining the ‘gravity problem’ with the ‘ice age problem’ was in the realms of normality 12 years ago. Slava Turyshev of NASA inquired into my early work on the inclination hypothesis wrt the ‘pioneer gravity anomaly’. Nowadays it’s too heretical to question the mainstream narrative as the brave Dr. Judith Curry and Professor John Christy have done.

      • Did you send your songs to Slava Turyshev? That should clear everything up.

        But neither Judith Curry or John Christy reject greenhouse gas warming. You’re with Christos on that one.

      • I have the same attitude as Professor John Christy on manmade global warming, due to him being an expert on the subject. I also have the position of saying that natural climate cycles are likely to contribute more than 50% of current climate change, which is the attitude of Dr. Judith Curry.

      • “Then when you look at the core of that question, the core is do you believe that man has some influence on the climate. I don’t know anyone who would say no to that. Who are the 3 percent who didn’t agree with that? Roy and I have both made the statement that we are in the 97 percent because we believe in some (man-made) effect. It wasn’t quantified and it wasn’t this dangerous thing. That wasn’t part of the question.” John Christy

        Nor has Judith Curry quantified the natural versus anthropogenic contributions to 20th century warming.

        Sergey Kravtsov and colleagues make the only attempt to my knowledge that can be taken seriously.

        “The global-mean temperature trends associated with GSW are as large as 0.3 °C per 40 years, and so are capable of doubling, nullifying or even reversing the forced global warming trends on that timescale.”

        But the GSW – Global Stadium Wave – demonstrates that a globally coupled, complex dynamical system is in operation. Climate indices are seen as nodes on a nonlinear global network. So it is impossible to discount a credible risk of abrupt and extreme change – as our nonlinear world enters new territory.

        Tapio Schneider and colleagues at Caltech have analysed one such risk.

        https://www.nature.com/articles/s41561-019-0310-1

        It comes against a background of change seen in sediment records. “More data points surfaced in China, then Europe, then all over. A picture emerged of a brief, cataclysmic hot spell 56 million years ago, now known as the Paleocene-Eocene Thermal Maximum (PETM). After heat-trapping carbon leaked into the sky from an unknown source, the planet, which was already several degrees Celsius hotter than it is today, gained an additional 6 degrees. The ocean turned jacuzzi-hot near the equator and experienced mass extinctions worldwide. On land, primitive monkeys, horses and other early mammals marched northward, following vegetation to higher latitudes. The mammals also miniaturized over generations, as leaves became less nutritious in the carbonaceous air. Violent storms ravaged the planet; the geologic record indicates flash floods and protracted droughts. As Kennett put it, “Earth was triggered, and all hell broke loose.” https://www.quantamagazine.org/cloud-loss-could-add-8-degrees-to-global-warming-20190225/

        Does Judith Curry or John Christie disagree? Why don’t you ask them? The most Judith curry says is that it is not likely an existential threat this century. Regardless – the pragmatic responses Judith has advocated make sense. You do not.

      • A science journalist of the Daily Express newspaper was convinced enough during a telephone interview that I “made sense”. Otherwise he wouldn’t have printed the article.

        My starting point is that over 350 years ago, when dark matter was an unknown concept, before man had set foot on the moon, the laws of motion for surface objects don’t directly translate to orbital mechanics by evidence of the ocean tides.

        If the lunar body pulled directly on water to create the ocean tides, then there would be known cloud patterns, called moon-twirls, which would be evidence of the moon’s gravitational effect on water vapour.

        A better more logical explanation is that the solid body bulge of the Earth pushes the oceans solely from beneath. This should have been spotted by Pierre-Simon Laplace but unfortunately wasn’t.

        I don’t believe you have the artistic imagination combined with logic and critical reasoning to comprehend the depth of argument I’m making.

      • Article??? And no one else shares your ahead of your time artistic temperament either. Including Christy ans Curry.

      • Professor John Christy is likely unaware of it and Dr. Judith Curry is yet to make a reply although I’m sure she’s more open to a new suggestion of a driver of climate change than you are.

      • The article??? And I was more referring to the anthropogenic part. For the natural part – Occam suggests a more obvious and well documented explanation.

      • My apologies, here’s the initial article with gives a broad brush overview of the new insight:

        https://www.express.co.uk/news/science/1308437/dark-matter-news-scientist-moon-core-theory-newton-einstein

      • “More than 100 years after Albert Einstein published his iconic general theory of relativity, it is beginning to fray at the edges, said Andrea Ghez, UCLA professor of physics and astronomy. Now, in the most comprehensive test of general relativity near the monstrous black hole at the center of our galaxy, Ghez and her research team report July 25 in the journal Science that Einstein’s theory holds up.

        “Einstein’s right, at least for now,” said Ghez, a co-lead author of the research. “We can absolutely rule out Newton’s law of gravity. Our observations are consistent with Einstein’s general theory of relativity. However, his theory is definitely showing vulnerability. It cannot fully explain gravity inside a black hole, and at some point we will need to move beyond Einstein’s theory to a more comprehensive theory of gravity that explains what a black hole is.”
        https://scitechdaily.com/einsteins-general-relativity-theory-beginning-to-fray-at-the-edges/

      • The reason I chose Tom Fish was an article which described a “hesitation” as the star orbited the centre of the galaxy in a highly inclined orbit. I interpreted this a possibility for a stronger gravitational force on the galactic plane. Professor Ghez later attributed this anomaly to a second ‘black hole’ assumed to be accompanying the main one (I believe):

        “This 16-year-long mapping of S0-2’s orbit allowed the team to test how gravity works near a supermassive black hole – a mysterious object weighing some 4 million suns.

        Professor Ghez said: “We were looking for a slight hesitation of how you perceive a star to move as it goes through its closest approach to the black hole.

        “That happened this past summer, and that hesitation tells us how gravity is co-mingling space and time.”

        “We have basically opened up a new approach to studying supermassive black holes through the orbits of stars.”

        https://www.express.co.uk/news/science/1043472/einstein-theory-gravity-wrong-black-hole-experiment-andrea-ghez

        She’s recently been awarded joint Nobel prize in physics for her work, in case it passed you by.

      • Consistent with Einstein’s space/time continuum and its curvature. Your wild guesses make no difference to us at the bottom of a gravity well. Or indeed in the Newtonian universe. Einstein is right – for now. We will see what black holes have to say about it.

      • A simple test of Einstein would be monitoring solid body tides to see whether they’re increasing as the new gravity hypothesis predicts.

        It also doubles as a test of whether this potential increase is a major cause of sea level rise.

        It’s the difference between unnecessary manmade global warming alarmism or a new economic revolution of the entire world.

      • And yet you still can’t admit that Einstein was correct.

      • And yet you still can’t admit that Einstein was correct. Where are the honest skeptics on this site?

      • Professor Randall of Theoretical Physics at Harvard is an honest sceptic:

        “Harvard professor’s radical theory of dark matter…building on the idea, Randall and her collaborators have been working on the theory that a particular type of the dark matter, a fraction of what’s out there, could exhibit interactions with itself other than gravity, ultimately leading it to collapse and form a thin disc within the midplane of the Milky Way.”

        https://www.theguardian.com/science/2016/jan/12/dark-matter-physics-dinosaurs-extinction-lisa-randell

      • Speculation that has nothing to do with climate. You are just on the wrong track and pulling a long bow.

      • And yet another honest sceptic who is only one small step away from the insight of a strong gravitational force eminating in a disc away from the dark matter core of the stars themselves:

        “Professor Michael Rampino, a geologist at New York University who has long been a proponent of the idea that the solar system’s movement through the galactic midplane is linked to a periodicity in impact crater formation on Earth, has recently suggested that clumps might exist within the ‘dark disc’ – and that these could accumulate in the Earth’s core as our solar system passes through the disc.”

      • Yes – it’s quoted from the Guardian article you probably didn’t read:

        https://www.theguardian.com/science/2016/jan/12/dark-matter-physics-dinosaurs-extinction-lisa-randell

      • Robert – if you’re so confident in manmade global warming & sea level rise, why doesn’t the mainstream rule out increasing solid body earth tides which could be a component?

        “The Earth tide encompasses the entire body of the Earth and is unhindered by the thin crust and land masses of the surface, on scales that make the rigidity of rock irrelevant.”

        https://en.m.wikipedia.org/wiki/Earth_tide

  29. The devastation and economic impacts are overwhelming to comprehend. There will be a migration problem from Central America presumably:

    https://youtu.be/YpqH79OnK5M

  30. I’ve spotted another correlation that lends itself to the tidal forcing by orbital inclination hypothesis. The Cold Tongue of the Indian Ocean Dipole is *directly* on the line of equator, just like the Pacific Cold Tongue:

    https://en.m.wikipedia.org/wiki/Indian_Ocean_Dipole

    https://en.m.wikipedia.org/wiki/Indian_Ocean

  31. Early snow in Russia with 80% coverage in contrast to headlines news of record Arctic coastline high temperatures during the summer:

    https://youtu.be/8JLcOZC0ke0

  32. The gyre hypothesis posits that strong westerly winds in both hemispheres at 70-90 degrees north and south spin up up gyres in all the world’s oceans. It is significant in the Pacific ocean as gyres transport cold water from polar regions to – and warm surface water away from the coast – in upwelling regions of the eastern Pacific.

    https://watertechbyrie.files.wordpress.com/2017/01/pacific-gyres.png

    Strong high latitude zonal winds are characteristic of the positives phases of the polar annular modes. La Niña (and cold phases of the Pacific Decadal Oscillation – PDO) are associated with positive annular modes. Both annular modes have turned positive this century.

    https://climatedataguide.ucar.edu/sites/default/files/styles/node_key_figures_display/public/key_figures/climate_data_set/Marshall-SAM-F2.png
    https://www.pmel.noaa.gov/arctic-zone/detect/detection-images/climate-ao-win_2016.png

    Shifts in Pacific states are synchronized and cause shifts in global hydrology, biology and surface temperature trajectories suggesting a common external trigger for north and sea surface temperature shifts.

    “During the past 400 years, climate shifts associated with changes in the PDO are shown to have occurred with a similar frequency to those documented in the 20th Century. Importantly, phase changes in the PDO have a propensity to coincide with changes in the relative frequency of ENSO events, where the positive phase of the PDO is associated with an enhanced frequency of El Niño events, while the negative phase is shown to be more favourable for the development of La Niña events.” Verdon and ranks, 2006, Long‐term behaviour of ENSO: Interactions with the PDO over the past 400 years inferred from paleoclimate records

    Planetary energetics are influenced by cloud dynamics in the upwelling zones. Closed cloud convection cells persist for longer over cool water before raining out to leave open cells.

    “Marine stratocumulus cloud decks forming over dark, subtropical oceans are regarded as the reflectors of the atmosphere.1 The decks of low clouds 1000s of km in scale reflect back to space a significant portion of the direct solar radiation and therefore dramatically increase the local albedo of areas otherwise characterized by dark oceans below.2,3 This cloud system has been shown to have two stable states: open and closed cells. Closed cell cloud systems have high cloud fraction and are usually shallower, while open cells have low cloud fraction and form thicker clouds mostly over the convective cell walls and therefore have a smaller domain average albedo.4–6 Closed cells tend to be associated with the eastern part of the subtropical oceans, forming over cold water (upwelling areas) and within a low, stable atmospheric marine boundary layer (MBL), while open cells tend to form over warmer water with a deeper MBL. Nevertheless, both states can coexist for a wide range of environmental conditions.5,7” Korem, 2017, Exploring the nonlinear cloud and rain equation

    High latitude zonal wind correlations with Australian rainfall enabled a millennial ENSO proxy to be constructed from salt content in a Law Dome, Antarctica, ice core. There were more El Niño like states early in the record and in the modern era – with La Niña states more prevalent in the intervening centuries.

    “ENSO causes climate extremes across and beyond the Pacific basin; however, evidence of ENSO at high southern latitudes is generally restricted to the South Pacific and West Antarctica. Here, the authors report a statistically significant link between ENSO and sea salt deposition during summer from the Law Dome (LD) ice core in East Antarctica. ENSO-related atmospheric anomalies from the central-western equatorial Pacific (CWEP) propagate to the South Pacific and the circumpolar high latitudes. These anomalies modulate high-latitude zonal winds, with El Niño (La Niña) conditions causing reduced (enhanced) zonal wind speeds and subsequent reduced (enhanced) summer sea salt deposition at LD.”

    https://watertechbyrie.files.wordpress.com/2014/06/vance2012-antartica-law-dome-ice-core-salt-content-e1540939103404.jpg
    Vance et al, 2013, A Millennial Proxy Record of ENSO and Eastern Australian Rainfall from the Law Dome Ice Core, East Antarctica

    The Mansurov effect is a positive correlation between south polar surface pressure – thus the southern annular mode – and solar winds.

    https://agupubs.onlinelibrary.wiley.com/cms/asset/f56fcd9f-89d8-451e-b611-e2e626d958b0/grl52088-fig-0001-m.png
    Lam et al, 2014, Solar wind‐driven geopotential height anomalies originate in the Antarctic lower troposphere

    “Here, we use nearly 30 years of output from a data-constrained magnetohydrodynamic model of the solar corona to calibrate heliospheric reconstructions based solely on sunspot observations. Using these empirical relations, we produce the first quantitative estimate of global solar wind variations over the last 400 years. Relative to the modern era, the MM shows a factor 2 reduction in near-Earth heliospheric magnetic field strength and solar wind speed, and up to a factor 4 increase in solar wind Mach number.”
    Owens et al, 2017, Global solar wind variations over the last four centuries

    The cool states of the Pacific Ocean emerge with low solar activity as a control variable in the terms of complex dynamical systems theory. .

    • The top graph is a record of cosmogenic isotopes over 9,400 years. A stronger magnetosphere shields Earth from cosmic radiation – thus there is an inverse relationship between cosmic ray intensity and solar activity. The bottom graph is a Holocene spanning ENSO proxy.

      There was a shift from La Niña dominance to El Niño dominance that is associated with the drying of the Sahel – and that occurred at a time of transition from low to high solar activity. The shift is seen some 5500 years BP in the spectral decomposition. Grand solar minimums are shown in the last 1000 years – in periods of enhanced La Niña intensity and frequency. The modern era sees a return to high solar activity and El Niño dominance. The record shows periods of high and low El Niño frequency and intensity alternating with a period of about 2,000 years. There is a period around 3,500 years ago of high El Niño intensity associated with the demise of the Minoan civilisation (Tsonis et al, 2010).

      https://watertechbyrie.files.wordpress.com/2017/05/isotope-9400-e1531338833901.png
      Steinhilber et al, 2011, 9,400 years of cosmic radiation and solar activity from ice cores and tree rings
      https://watertechbyrie.files.wordpress.com/2020/01/moy-2002.png
      Moy et al, 2002, Variability of EI Ni??o/Southern Oscillation activity at millennial timescales during the Holocene epoch

      Change is perpetual and it may be that the only way forward is down from the modern era highs in solar activity and El Niño frequency and intensity.

  33. Earth’s atmosphere has only traces of carbon dioxide CO2 gas content

    CO2 content in Earth’s atmosphere is measured to be some 400 ppm.

    400 parts per million is one part per 1.000.000 /400 = 2.500

    So we have one molecule of CO2 for every 2.500 molecules of air.

    Or to make it even more clear: 1 /2.500 = 0,0004 or 0,04 %

    Now let’s compare the 0,04% CO2 content in Earth’s atmosphere with the water vapor content of about 1% on average.

    0,04% CO2 /1% H2O = 0,04

    or one molecule of CO2 for every 25 molecules of H2O in Earth’s atmosphere.

    One may say there are still too many CO2 molecules.

    But Earth’s atmosphere is very thin, it is an almost transparent atmosphere in both ways – in and out.

    It is not only the CO2% content in the Earth’s atmosphere general content that matters, but we have also to consider how many CO2 molecules are in Earth’s atmosphere in total.

    If Earth’s atmosphere were consisted from the actually existing CO2 molecules only, the atmospheric pressure on the Earth’s surface would have been 0,0004 bar.

    http://www.cristos-vournas.com

  34. 2. MOON’S MEAN SURFACE TEMPERATURE CALCULATION
    Tmean.moon

    Surface temp..Tmin..Tmean..Tmax
    Kelvin………….100.K…220.K…390.K

    So = 1.361 W/m² (So is the Solar constant)
    Moon’s albedo: amoon = 0,11

    Moon’s sidereal rotation period is 27,32 days. But Moon is Earth’s satellite, so the lunar day is 29,5 days

    Moon does N = 1/29,5 rotations/per day

    Moon is a rocky planet, Moon’s surface irradiation accepting factor Φmoon = 0,47
    (Accepted by a Smooth Hemisphere with radius r sunlight is S* Φ*π*r²*(1-a), where Φ = 0,47)

    cp.moon = 0,19 cal/gr oC, moon’s surface specific heat (moon’s surface is considered as a dry soil)

    β = 150 days*gr*oC/rotation*cal – it is a Rotating Planet Surface Solar Irradiation Absorbing-Emitting Universal Law constant

    σ = 5,67*10⁻⁸ W/m²K⁴, the Stefan-Boltzmann constant

    MOON’S MEAN SURFACE TEMPERATURE EQUATION
    Tmean.moon:

    Tmean.moon = [ Φ (1 – a) So (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴

    Tmean.moon = { 0,47 (1 – 0,11) 1.361 W/m² [150* (1/29,5)*0,19]¹∕ ⁴ /4*5,67*10⁻⁸ W/m²K⁴ }¹∕ ⁴ =

    Tmean.moon = ( 2.488.581.418,96 )¹∕ ⁴ = 223,35 K

    Tmean.moon = 223,35 Κ

    The newly calculated Moon’s Mean Surface Temperature differs only by 1,54% from that measured by satellites!

    Tsat.mean.moon = 220 K, measured by satellites.

    http;//www.cristos-vournas.com

  35. There is NO +33°C greenhouse ENHANCEMENT on the Earth’s mean surface temperature.

    The calculated by equation

    Tmean.earth = [ Φ (1 – a) So (β*N*cp)¹∕ ⁴ /4σ ]¹∕ ⁴

    and the satellite measured EARTH’S MEAN SURFACE TEMPERATURES are almost IDENTICAL:

    Tmean.earth = 287,74K
    Tsat = 288 K

    http://www.cristos-vournas.com