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Thread: Impact of recent forcing and ocean heat data on climate sensitivity estimates

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    Default Impact of recent forcing and ocean heat data on climate sensitivity estimates

    I wonder how many on here even understand the abstract to this paper published in the AMS, let alone appreciate its significance? The usual suspects are threadbanned.

    Abstract


    Energy budget estimates of equilibrium climate sensitivity (ECS) and transient climate response (TCR) are derived based on the best estimates and uncertainty ranges for forcing provided in the IPCC Fifth Assessment Scientific Report (AR5). Recent revisions to greenhouse gas forcing and post-1990 ozone and aerosol forcing estimates are incorporated and the forcing data extended from 2011 to 2016. Reflecting recent evidence against strong aerosol forcing, its AR5 uncertainty lower bound is increased slightly. Using a 1869–1882 base period and a 2007−2016 final period, which are well-matched for volcanic activity and influence from internal variability, medians are derived for ECS of 1.50 K (5−95%: 1.05−2.45 K) and for TCR of 1.20 K (5−95%: 0.9−1.7 K). These estimates both have much lower upper bounds than those from a predecessor study using AR5 data ending in 2011. Using infilled, globally-complete temperature data gives slightly higher estimates; a median of 1.66 K for ECS (5−95%: 1.15−2.7 K) and 1.33 K for TCR (5−95%:1.0−1.90 K). These ECS estimates reflect climate feedbacks over the historical period, assumed time-invariant. Allowing for possible time-varying climate feedbacks increases the median ECS estimate to 1.76 K (5−95%: 1.2−3.1 K), using infilled temperature data. Possible biases from non-unit forcing efficacy, temperature estimation issues and variability in sea-surface temperature change patterns are examined and found to be minor when using globally-complete temperature data. These results imply that high ECS and TCR values derived from a majority of CMIP5 climate models are inconsistent with observed warming during the historical period.

    https://journals.ametsoc.org/doi/10....LI-D-17-0667.1

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    Impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity

    Posted on April 24, 2018 by niclewis
    by Nic Lewis

    We have now updated the LC15 paper with a new paper that has been published in the Journal of Climate “The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity“. The paper also addresses critiques of LC15.

    There has been considerable scientific investigation of the magnitude of the warming of Earth’s climate by changes in atmospheric carbon dioxide (CO2) concentration. Two standard metrics summarize the sensitivity of global surface temperature to an externally imposed radiative forcing. Equilibrium climate sensitivity (ECS) represents the equilibrium change in surface temperature to a doubling of atmospheric CO2 concentration. Transient climate response (TCR), a shorter-term measure over 70 years, represents warming at the time CO2 concentration has doubled when it is increased by 1% a year.

    For over thirty years, climate scientists have presented a likely range for ECS that has hardly changed. The ECS range 1.5−4.5 K in 1979 (Charney 1979) is unchanged in the 2013 Fifth Assessment Scientific Report (AR5) from the Intergovernmental Panel on Climate Change (IPCC). AR5 did not provide a best estimate value for ECS, stating (Summary for Policymakers D.2): “No best estimate for equilibrium climate sensitivity can now be given because of a lack of agreement on values across assessed lines of evidence”.

    At the heart of the difficulty surrounding the values of ECS and TCR is the substantial difference between values derived from climate models versus values derived from changes over the historical instrumental data record using energy budget models. The median ECS given in AR5 for current generation (CMIP5) atmosphere-ocean global climate models (AOGCMs) was 3.2 K, versus 2.0 K for the median values from historical-period energy budget based studies cited by AR5.

    Subsequently Lewis and Curry (2015; hereafter LC15) [i] derived, using observationally-based energy budget methodology, a median ECS estimate of 1.6 K from AR5’s global forcing and heat content estimate time series, which made the discrepancy with ECS values derived from AOGCMs even larger. LC15 also derived a median TCR value of 1.3 K, well below the 1.8 K median TCR for CMIP5 models in AR5.

    The LC15 analysis used a global energy budget model that relates ECS and TCR to changes (Δ) in global mean surface temperature [T], effective radiative forcing (ERF) [F] and the planetary radiative imbalance [N] (estimated from its counterpart, the rate of climate system heat uptake) [ii] between a base and a final period. The resulting estimates were considerably less dependent on comprehensive global climate models (GCMs) and allowed more thoroughly for forcing uncertainties than many others.[iii]

    Considerable effort has been expended recently in attempts to reconcile observationally-based ECS values with values determined using climate models. Most of these efforts have focused on arguments that the methodologies used in the energy budget model determinations result in downwards-biased ECS and/or TCR estimates (e.g., Marvel et al. 2016; Richardson et al. 2016; Armour 2017).

    We have now updated the LC15 paper with a new paper that has been published in the Journal of Climate “The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity“.[iv] The paper (hereafter, LC18) addresses a range of concerns that have been raised about climate sensitivity estimates derived using energy balance models. We provide estimates of ECS and TCR based on a globally-complete infilled version of the HadCRUT4 surface temperature dataset as well as estimates based on HadCRUT4 itself.[v] Table 1 gives the ECS and TCR estimates for the four base period – final period combinations used.


    Table 1 (based on Table 3 in LC18) Best estimates (medians) and uncertainty ranges for ECS and TCR using the base and final periods indicated. Values in roman type compute the temperature change involved (ΔT) using the HadCRUT4v5 dataset; values in italics compute using the infilled, globally-complete Had4_krig_v2 (Cowtan & Way) dataset. The preferred estimates are shown in bold. Ranges are stated to the nearest 0.05 K. Also shown are the comparable results (using the HadCRUT4v2 dataset) from LC15 for the first two period combinations given in that paper. The values from the IPCC AR5 are provided for reference.
    .
    The new LC18 ECS and TCR estimates are very similar for all the period combinations used. That implies that the ‘hiatus’ – the period of slow warming from the early 2000s until a few years ago – had little effect on estimation. The preferred pairing is of the 1869–1882 and 2007–2016 periods, which provides the largest change in forcing and hence the narrowest uncertainty ranges, notwithstanding that both these periods are the shortest ones used. Using 1869–1882 as the base period avoids both any significant volcanism and the period of particularly sparse temperature data spanning most of the 1860s. Estimates are almost identical when using the longer 1850–1882 base period and excluding years affected by volcanism or with very sparse temperature data.

    The new LC18 ECS and TCR HadCRUT4-based best estimates, respectively 1.50°C and 1.20°C, are approximately 10% lower than those in LC15. These reductions stem primarily from a significant upwards revision in estimated methane forcing following more accurate determination of the forcing-concentration relationships for the principal well-mixed greenhouse gases (WMGG)[vi] and revisions to post-1990 AR5 aerosol and ozone forcing estimates that reflect updated emission data,[vii] partially offset by a 2.5% upwards revision in the forcing from a doubling of preindustrial carbon dioxide (CO2) concentration, F2⤬CO2.[viii]

    The 5% uncertainty bound of the AR5 2011 aerosol forcing estimate was changed from −1.9 Wm−2 to −1.7 Wm−2 to reflect substantial recent evidence against aerosol forcing being extremely strong.[ix] Doing so had virtually no effect on the median ECS and TCR estimates, and accounted for only a small fraction of the major reductions in their 83% and 95% upper uncertainty bounds from those in LC15. Most of that reduction is due to the revised forcing estimates and to average greenhouse gas concentrations over 2007–2016 being higher than over 1995–2011.

    Figure 1 shows a comparison of the revised, extended forcings estimates with their original AR5 values. The significant increase in ‘Other WMGG’ forcing reflects the revision of the methane forcing component. Figure 1 shows a comparison of the revised, extended forcings estimates with their original AR5 values. The significant increase in ‘Other WMGG’ forcing reflects the revision of the methane forcing component.[x]

    There is some recent evidence that AR5 volcanic forcing estimates, which in LC18 are extended to 2016 using the AR5 calculation basis, may be biased low due to omission of volcanic aerosol in the lower stratosphere.[xi] However, once an adjustment is made for the background level of volcanic aerosol there appears to be virtually no effect on the changes in volcanic forcing between the base and final periods used in LC18.[xii]


    Figure 1 (based on Figure 2 of LC18) Anthropogenic forcings from 1750 to 2016. In some cases the Original AR5 1750–2011 time-series overlay the Revised 1750–2016 time-series prior to 2012. Unrevised anthropogenic forcing components have been combined into a single ‘Other Anthropogenic’ time-series. Solar and Volcanic forcings are not shown; they have not been revised and their post 2011 changes are very small.

    The new best estimates using globally-complete surface temperature data, of 1.66°C for ECS and 1.33°C for TCR, are almost the same as the LC15 ECS and TCR estimates based on non-infilled temperature data. Both the LC15 and LC18 ‘likely’ (66%+ probability) ranges are both very much towards the bottom ends of the corresponding IPCC AR5 ranges.

    Figure 2 shows probability density functions for each of the ECS and TCR estimates, with the AR5 ‘likely’ ranges (shaded lime green) for comparison. The PDFs are skewed due principally to the dominant uncertainty in forcing, affecting the denominator of the fractions used to estimate ECS and TCR.


    Figure 2 (based on Figure 4 of LC18) Estimated probability density functions for ECS and TCR using each main results period combination. Original GMST refers to use of the HadCRUT4v5 record; Infilled GMST refers to use of the Had4_krig_v2 record. Box plots show probability percentiles, accounting for probability beyond the range plotted: 5–95 (bars at line ends), 17–83 (box-ends) and 50 (bar in box: median). Lime green shading shows the AR5 ‘likely’ (17–83% or better) ranges.

    LC18 also derived, on comparable bases, ECS and TCR values for all current generation (CMIP5) GCMs for which the requisite data were available.[xiii] A majority of this ensemble of 31 CMIP5 models had ECS and TCR values that exceeded the 2.7°C and 1.9°C 95% uncertainty bounds that we derived for those parameters using globally-complete surface temperature data.

    The foregoing ECS estimates reflect climate feedbacks over the historical period, assumed time-invariant. Two recent studies asserted that ECS estimates for CMIP5 models derived from forcing data comparable to that available for use in historical period (post-1850) observationally-based energy budget studies, using a constant feedbacks assumption, were biased low. They concluded that CMIP5 model ECS estimates were on average some 30% higher when derived from their response to an increase in CO2 concentration in a way that allows, insofar as practicable, for time-varying feedbacks.[xiv] We show that their calculations are biased and that, when calculated appropriately, the difference is under 10%.[xv] Allowing for such possible time-varying climate feedbacks increases the median ECS estimate to 1.76°C (5−95%: 1.2−3.1°C), using globally-complete temperature data. A majority of our ensemble of CMIP5 models have ECS values, estimated in the way designed to allow for time-varying feedbacks, that exceed 3.1°C.

    It has been suggested in various studies that effects of non-unit forcing efficacy, temperature estimation issues and variability in sea-surface temperature change patterns likely lead to historical period energy budget estimates being biased low.[xvi] We examined all these issues in LC18 and found that only very minor bias was to be expected when using globally-complete temperature data.[xvii]

    Over half of the 31 CMIP5 models have ECS values estimated using a comparable change in forcing to that over the historical period[xviii] of 2.9 K or higher, exceeding by over 7% our 2.7 K observationally-based 95% uncertainty bound using infilled temperature data. Moreover, a majority of these models have a TCR above our corresponding 1.9 K 95% bound.

    The implications of our results are that high estimates of ECS and TCR derived from a majority of CMIP5 climate models are inconsistent (at a 95% confidence level) with observed warming during the historical period. Moreover, our median ECS and TCR estimates using infilled temperature data imply multicentennial or multidecadal future warming under increasing forcing of only 55−70% of the mean warming simulated by CMIP5 models.

    I hope to discuss in more depth in a subsequent article some of the material in LC18 and its Supporting Information that has been dealt with only very briefly here.

    .Nic Lewis April 2018.

    [i] Lewis, N., and J. A. Curry, 2015: The implications for climate sensitivity of AR5 forcing and heat uptake estimates. Climate Dynamics, 45(3-4), 1009-1023. Note: the paper was initially published online in 2014. An article about the paper and its results was posted here.
    [ii] Total heat uptake by the Earth’s climate system, 90%+ in the ocean, necessarily equals the Earth’s top-of-atmosphere radiative imbalance, neglecting the tiny and near-constant geothermal heat flux (which has a negligible effect on ΔN).
    [iii] Although none of the forcing estimates used are fully independent of GCMs, they do not appear to be materially affected by the ECS and TCR values of the GCMs involved. The early industrial heat uptake estimates used are GCM-derived and dependent on the GCM’s sensitivity, but they are small and a correction factor is applied to allow for the sensitivity of the GCM being higher than the energy budget derived sensitivity estimate.
    [iv] Lewis, N. ,and J. Curry, 2018:The impact of recent forcing and ocean heat uptake data on estimates of climate sensitivity. J. Clim. JCLI-D-17-0667 A copy of the final submitted manuscript, reformatted for easier reading, is available at my personal webpages, here. The Supporting Information is available here.
    [v] Cowtan, K., and R. G. Way, 2014: Coverage bias in the HadCRUT4 temperature series and its impact on recent temperature trends. Quart. J. Roy. Meteor. Soc., 140(683), 1935-1944 (update at http://www.webcitation.org/6t09bN8vM).
    [vi] Etminan, M., G. Myhre, E. J. Highwood, and K. P. Shine, 2016: Radiative forcing of carbon dioxide, methane, and nitrous oxide: A significant revision of the methane radiative forcing. Geophys. Res. Lett. 43(24) doi:10.1002/2016GL071930.
    [vii] Myhre, G., and Coauthors, 2017: Multi-model simulations of aerosol and ozone radiative forcing due to anthropogenic emission changes during the period 1990–2015. Atmos. Chemistry and Phys., 17(4), 2709-2720.
    [viii] The almost identical proportional reduction in HadCRUT4-based ECS and TCR estimates between LC15 and the new study reflects the fact that heat uptake and forcing changes increased in similar proportions relative to the temperature change.
    [ix] See extensive discussion in section 3a of LC18. Note that the (revised) 2011 AR5 aerosol forcing uncertainty range is – as for all the AR5 forcing uncertainty ranges – merely used, after dividing by its median, to estimate fractional uncertainty in the ERF best estimate time series, as revised.
    [x] The reason why recent CO2 forcing is almost unchanged despite F2⤬CO2 being 2.5% higher is that the revised greenhouse gas forcing formulae embody a slightly faster than logarithmic increase in CO2 forcing with concentration.
    [xi] Andersson, S. M., et al., 2015: Significant radiative impact of volcanic aerosol in the lowermost stratosphere. Nature communications, 6, 8692.
    [xii] LC18 Supporting Information, S1
    [xiii] We excluded FGOALS-g2 as its 1pctCO2 simulation results are abnormal and the p2 variants of GISS-E2-H and GISS-E2-R as their model physics is intermediate between the main (p1) and p3 physics versions. That left 31 CMIP5 models. See Table 2 in the Supporting Information for their calculated ECS and TCR values. Note that the reference to ECS calculated on a comparable basis (to our observational energy budget ECS estimates) is to the ECShist values in Table 2.
    [xiv] Armour, K. C., 2017: Energy budget constraints on climate sensitivity in light of inconstant climate feedbacks. Nature Climate Change, 7, 331-335.
    Proistosescu, C., and P. J. Huybers, 2017: Slow climate mode reconciles historical and model-based estimates of climate sensitivity. Science Advances, 3(7), e1602821.
    [xv] Section 7f and Supporting Information S5.
    [xvi] Marvel, K., G. A. Schmidt, R. L. Miller and L. S. Nazarenko, 2016: Implications for climate sensitivity from the response to individual forcings. Nature Climate Change, 6(4), 386-389.
    Richardson, M., K. Cowtan, E. Hawkins, and M. B. Stolpe, 2016: Reconciled climate response estimates from climate models and the energy budget of Earth. Nature Climate Change, 6(10), 931-935.
    Gregory, J. M., and T. Andrews, 2016: Variation in climate sensitivity and feedback parameters during the historical period. Geophys. Res. Lett., 43: 3911–3920.
    [xvii] See sections 7a, 7c and 7e of LC18.
    [xviii] Where types of ECS estimate are distinguished in LC18, this type is termed ECShist. Since forcing in CMIP5 models’ historical simulations is model-dependent and unknown, their ECShist is estimated (in LC18 and other studies) using data from their simulations driven by known changes in CO2, in such a way as to mimic the ECS estimates that would be derivable from their responses to representative historical forcing.

    https://judithcurry.com/2018/04/24/i...ty/#more-24068
    Last edited by cancel2 2022; 04-25-2018 at 04:14 AM.

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    Quote Originally Posted by Havana Moon View Post
    I wonder how many on here even understand the abstract to this paper published in the AMS, let alone appreciate its significance? The usual suspects are threadbanned.



    https://journals.ametsoc.org/doi/10....LI-D-17-0667.1

    what actually matters is the massive increase in man introduced CO2 in the atmosphere. For the last 800,000 years temp and CO2 levels change in lock step. CO2 levels indicate significant temp increases are coming.

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    Quote Originally Posted by katzgar View Post
    what actually matters is the massive increase in man introduced CO2 in the atmosphere. For the last 800,000 years temp and CO2 levels change in lock step. CO2 levels indicate significant temp increases are coming.
    Case in point. This old buffer has absolutely no idea what the paper is about and I don't have the patience to explain it to him.

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    Quote Originally Posted by Havana Moon View Post
    Case in point. This old buffer has absolutely no idea what the paper is about and I don't have the patience to explain it to him.

    Sent from my Lenovo K52e78 using Tapatalk

    I care about the science, not your cluster fuck of a post

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    Quote Originally Posted by katzgar View Post
    I care about the science, not your cluster fuck of a post
    Look up hubris and humility, then try doing less of the former and far more of the latter.
    It's patently obvious that you don't understand the science, you leave El Gordo to do your thinking for you.
    Last edited by cancel2 2022; 04-25-2018 at 09:12 AM.

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    Quote Originally Posted by Havana Moon View Post
    Look up hubris and humility, then try doing less of the former and far more of the latter.
    It's patently obvious that you don't understand the science, you leave El Gordo to do you thinking for you.

    the science is simple, I explained it to you and you still dont get it. I will post it again for you. "what actually matters is the massive increase in man introduced CO2 in the atmosphere. For the last 800,000 years temp and CO2 levels change in lock step. CO2 levels indicate significant temp increases are coming." I can only hope you can follow this.

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    So, what's your point?

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    Quote Originally Posted by katzgar View Post
    the science is simple, I explained it to you and you still dont get it. I will post it again for you. "what actually matters is the massive increase in man introduced CO2 in the atmosphere. For the last 800,000 years temp and CO2 levels change in lock step. CO2 levels indicate significant temp increases are coming." I can only hope you can follow this.
    Seemingly these good people would beg to differ with your incredibly simplistic analysis. Maybe you should get in contact and show them the error of their ways?

    Harde, 2017

    Abstract:

    Climate scientists presume that the carbon cycle has come out of balance due to the increasing anthropogenic emissions from fossil fuel combustion and land use change. This is made responsible for the rapidly increasing atmospheric CO2 concentrations over recent years, and it is estimated that the removal of the additional emissions from the atmosphere will take a few hundred thousand years. Since this goes along with an increasing greenhouse effect and a further global warming, a better understanding of the carbon cycle is of great importance for all future climate change predictions. We have critically scrutinized this cycle and present an alternative concept, for which the uptake of CO2 by natural sinks scales proportional with the CO2 concentration. In addition, we consider temperature dependent natural emission and absorption rates, by which the paleoclimatic CO2 variations and the actual CO2 growth rate can well be explained. The anthropogenic contribution to the actual CO2 concentration is found to be 4.3%, its fraction to the CO2 increase over the Industrial Era is 15% and the average residence time 4 years.


    Conclusion:

    Climate scientists assume that a disturbed carbon cycle, which has come out of balance by the increasing anthropogenic emissions from fossil fuel combustion and land use change, is responsible for the rapidly increasing atmospheric CO2 concentrations over recent years. While over the whole Holocene up to the entrance of the Industrial Era (1750) natural emissions by heterotrophic processes and fire were supposed to be in equilibrium with the uptake by photosynthesis and the net oceanatmosphere gas exchange, with the onset of the Industrial Era the IPCC estimates that about 15 – 40 % of the additional emissions cannot further be absorbed by the natural sinks and are accumulating in the atmosphere.

    The IPCC further argues that CO2 emitted until 2100 will remain in the atmosphere longer than 1000 years, and in the same context it is even mentioned that the removal of human-emitted CO2 from the atmosphere by natural processes will take a few hundred thousand years (high confidence) (see AR5-Chap.6-Executive-Summary).

    Since the rising CO2 concentrations go along with an increasing greenhouse effect and, thus, a further global warming, a better understanding of the carbon cycle is a necessary prerequisite for all future climate change predictions. In their accounting schemes and models of the carbon cycle the IPCC uses many new and detailed data which are primarily focussing on fossil fuel emission, cement fabrication or net land use change (see AR5-WG1-Chap.6.3.2), but it largely neglects any changes of the natural emissions, which contribute to more than 95 % to the total emissions and by far cannot be assumed to be constant over longer periods (see, e.g.: variations over the last 800,000 years (Jouzel et al., 2007); the last glacial termination (Monnin et al., 2001); or the younger Holocene (Monnin et al., 2004; Wagner et al., 2004)).

    Since our own estimates of the average CO2 residence time in the atmosphere differ by several orders of magnitude from the announced IPCC values, and on the other hand actual investigations of Humlum et al. (2013) or Salby (2013, 2016) show a strong relation between the natural CO2 emission rate and the surface temperature, this was motivation enough to scrutinize the IPCC accounting scheme in more detail and to contrast this to our own calculations.

    Different to the IPCC we start with a rate equation for the emission and absorption processes, where the uptake is not assumed to be saturated but scales proportional with the actual CO2 concentration in the atmosphere (see also Essenhigh, 2009; Salby, 2016). This is justified by the observation of an exponential decay of 14C. A fractional saturation, as assumed by the IPCC, can directly be expressed by a larger residence time of CO2 in the atmosphere and makes a distinction between a turnover time and adjustment time needless. Based on this approach and as solution of the rate equation we derive a concentration at steady state, which is only determined by the product of the total emission rate and the residence time. Under present conditions the natural emissions contribute 373 ppm and anthropogenic emissions 17 ppm to the total concentration of 390 ppm (2012). For the average residence time we only find 4 years.

    The stronger increase of the concentration over the Industrial Era up to present times can be explained by introducing a temperature dependent natural emission rate as well as a temperature affected residence time. With this approach not only the exponential increase with the onset of the Industrial Era but also the concentrations at glacial and cooler interglacial times can well be reproduced in full agreement with all observations. So, different to the IPCC’s interpretation the steep increase of the concentration since 1850 finds its natural explanation in the self accelerating processes on the one hand by stronger degassing of the oceans as well as a faster plant growth and decomposition, on the other hand by an increasing residence time at reduced solubility of CO2 in oceans.

    Together this results in a dominating temperature controlled natural gain, which contributes about 85 % to the 110 ppm CO2 increase over the Industrial Era, whereas the actual anthropogenic emissions of 4.3 % only donate 15 %. These results indicate that almost all of the observed change of CO2 during the Industrial Era followed, not from anthropogenic emission, but from changes of natural emission.

    The results are consistent with the observed lag of CO2 changes behind temperature changes (Humlum et al., 2013; Salby, 2013), a signature of cause and effect. Our analysis of the carbon cycle, which exclusively uses data for the CO2 concentrations and fluxes as published in AR5, shows that also a completely different interpretation of these data is possible, this in complete conformity with all observations and natural causalities.



    https://www.sciencedirect.com/scienc...21818116304787
    Last edited by cancel2 2022; 04-25-2018 at 08:34 AM.

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    800,000 years of correlation works.

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    Havana, before I address this, have you looked at what peer review is out there for this?
    You Are Not So Smart Podcast - A celebration of Self-Delusion

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    Quote Originally Posted by DigitalDave View Post
    Havana, before I address this, have you looked at what peer review is out there for this?
    Lol, peer reviewed, this is Havana you are addressing.

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    Quote Originally Posted by Phantasmal View Post
    Lol, peer reviewed, this is Havana you are addressing.
    Luckily I've been gone long enough to not know who Havana is to have developed a bias. I saw that he/she posted a schorlarly article, and seems to be asking who understands it. I understood it completely but I also understand that there are processes to science that found tons of holes in this as well.
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    Quote Originally Posted by katzgar View Post
    800,000 years of correlation works.
    You are correct for the wrong reason. There is data going back 800,000 years, that was gathered from drilling core samples deep under the ice sheets of Greenland and Antarctica. Detailed information on air temperature and CO2 levels have disproved that a rise in CO2 will cause a rise in temperature. The core samples from EPICA Dome C ice core on the Antarctic Plateau established that temperature rises first and the atmospheric CO2 level lags behind.

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    Quote Originally Posted by Phantasmal View Post
    Lol, peer reviewed, this is Havana you are addressing.
    Doris, have you got a Hot Whopper blog article to post?

    Sent from my Lenovo K52e78 using Tapatalk

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