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Imbers et al. Test Human-Caused Global Warming Detection

Posted on 3 June 2013 by dana1981

A new study published in the Journal of Geophysical Research – Atmospheres by Imbers, Lopez, Huntingford, and Allen tests the robustness of the detection of human-caused global warming in previous studies.  Specifically their study builds on Lean and Rind (2009), Folland et al. (2013) (which they refer to as Folland 2011, based on an abstract presented at the AGU conference in 2011 of the recently-published 2013 paper), Kaufmann et al. (2011), and Lockwood (2008), as well as considering Loehle and Scafetta (2011).

Imbers et al. investigated whether using different characterizations and models of internal natural variability in the climate system (for example the El Niño Southern Oscillation [ENSO] and Atlantic Multidecadal Oscillation [AMO]), with both short and long memory processes, would impact the detection of the human-caused global warming signal.  The results of the previous studies listed above are illustrated in Figure 1.

Imbrie Fig 1

Figure 1: The top panel shows the observed global mean air surface temperature anomaly from HadCRUT3 (gray line) and the best multivariate fits using the methods of Lean and Rind [2009] (blue line), Lockwood [2008] (red line), Folland et al. [2011] (green line), and Kaufmann et al. [2011] (orange line). The remaining panels show the individual temperature contributions to the top panel fits from ENSO (second panel), volcanoes (third panel), solar irradiance (fourth panel), anthropogenic contribution (fifth panel), and other factors (sixth panel) that include the AMO for Folland et al. [2011] and minor annual, semi-annual, and 17.5 year cycle identified by Kopp and Lean [2011] in the residuals of Lean and Rind’s [2009] model.

The human contribution to global surface warming (the fifth panel in Figure 1) is shown in Figure 2.  Click the image for a larger version.

Imbrie Anthro

Figure 2: The human (anthropogenic) contribution to global surface warming.  From Imbers et al. (2013).

These studies estimate the human contribution to global surface warming over the past 30–60 years at approximately:

  • 0.15°C per decade (Lockwood)
  • 0.12°C per decade (Folland)
  • 0.16°C per decade (Kaufmann)
  • 0.17°C per decade (Lean)

Note that the overall global surface warming trend over this timeframe is approximately 0.16–0.17°C per decade, meaning that these studies put the human contribution in the 70–100% range.

Imbers et al. found that all of the global surface temperature influences they examined (ENSO, AMO, solar, volcanic, and anthropogenic) were detectable in the data from all of these studies, with the possible exception of the solar influence in the Kaufmann study, whose range of possible temperature influences did overlap with zero.

Overall, regardless of their modeled characteristics of internal climate variability, Imbers et al. found a robust detection of the human-caused global surface warming signal.

They also tested what would happen when the temperature contribution of ENSO contribution is separated as a signal and removed from the data (dotted lines in Figure 3) vs. when it's included in the residual internal climate variability (solid lines in Figure 3).  A lower value (scaling factor) means a smaller contribution from an influence on global surface temperature.  For example, the volcanic influence blue solid line is lower than the blue dotted line, indicating that when ENSO is treated as a part of residual internal climate variability, it suggests a smaller volcanic temperature influence.

Imbers Fig 3

Figure 3: Scaling factors and their 95% confidence interval (vertical axis) for the different signals: ENSO, volcanic (VOL), solar (SOL), anthropogenic (ANT), and AMO (as indicated in the horizontal axis); using the data from the four studies: Lean (blue), Lockwood (red), Folland (green), and Kaufmann (orange).  Illustrating the sensitivity of the detection statistics to ENSO, when its contribution to the global mean temperature is separated as a signal (dotted lines) or included in the residual internal variability (thick lines).

As you can see, the treatment of ENSO does not make a significant difference in the detection of the human-caused global warming signal.  It's the non-anthropogenic signals where the treatment of ENSO makes a difference in their contributions to global surface warming.

Imbers et al. also considered the 20-year and 60-year cycles proposed by Loehle and Scafetta.  Once again, they found that including these cycles did not make a significant difference in the detection of the human-caused global warming signal.  The biggest difference was in the temperature contribution of AMO.  However, Imbers et al. found that overall the cycles proposed by Loehle and Scafetta were insignificant contributors to global surface temperature changes.

"The results of this statistical study suggest that adding these two low-frequency [20- and 60-year] oscillations does not change significantly the detection and attribution of the anthropogenic signal in any of the studies considered ... These results suggest that statistically these cycles are not significant and are not clearly distinguishable from the internal variability as described by our noise models."

Ultimately Imbers et al. conclude,

"the detection of the anthropogenic signal is statistically robust independent of the model utilized to characterize the internal variability."

In other words, consistent with the 97% expert consensus, human-caused global warming is a reality, and humans are responsible for the majority of the global surface warming in recent decades.

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Comments 1 to 48:

  1. Am I reading Fig 2 correctly?  It appears that this chart is saying that the human contribution before 1985 was negative, which implies cooling.  That doesn't seem to make sense to me.  I thought that most of the warming since 1900 was man made?

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  2. No, the zero point on that graph is meaningless. They've rebaselined everything so the mean on 1980-2000 is zero - presumably for comparison purposes.

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  3. Having gone and looked at the paper itself, I do not get the impression that the 0 point is meaningless. In order to extract the components (ENSO, Volcanoes, AGW, Sun, Other) of the temperature change, they must conclude that the AGW component prior to 1985 was negative in order to get all the numbers to "balance." That doesn't seem right to me.

    I guess I can understand that they can pull ENSO and Volcanic effects from the global temperature record based upon physics modeling, but how did they separate out Sun and Other effects from ANT? This shows that the Sun is very stable – perhaps it is in total solar intensity, but the Sun does a bunch of other things that may affect the climate – like solar wind, coronal mass ejections (CME), magnetics fields, to name a couple of major ones. These clearly are not very stable and are highly related to sun spots and the solar cycle. If you assume the sun is stable and other factors are stable, then I suppose you can easily conclude the ANT is a major player. But what if the Sun and Other are not as stable as assumed? Then the ANT contribution would be much lower.

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  4. Stealth @3 - the solar contribution appears 'stable' because the change in solar forcing is so small compared to the change in GHG forcing.  And there is no evidence that solar wind, CME, etc. have a non-negligible impact on global temperatures.  That's not an assumption, it's what the scientific literature says.

    Kevin @2 is also correct about the baselining being the reason some of the values are negative.

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  5. Can you respond with some links that point me to some of this scientific literature that asserts that solar wind, CME, etc have a negligible effect on climate? I am having a hard time believing this claim and I would love to see how someone proved this. I like to follow CME and solar weather for auroras, and the last X class CME that hit the earth dump more energy into the upper atmosphere in 24 hours than has been released by all of mankind over all of history. CMEs set up huge electrical currents in the ground and wires and can knock out the power grid, fry satellites, and force astronauts into protective and shielded quarters on the ISS. That, in my book, isn’t trivial or negligible, so I do not see how you can make that claim.

    I’ve done a quick Google search and haven’t found any such documentation supporting your claim. Wikipedia states, “The IPCC acknowledges that there is a low level of scientific understanding with respect to solar variation.” ( under the “Effect on global warming.”) I doubt the IPCC would say this if there was clear science to the contrary, so I really look forward to your references.

    As for the zero point, still just don’t buy that the zero point is a re baseline for comparison as you can Kevin state. That makes no sense based on the other charts. All other factors (ENSO, etc) are relative to zero showing how they added or subtracted from the global temperature. Note how VOL is always negative, which makes sense. A volcano burps out a bunch of aerosols which reflects some sun light and cools the earth some amount. The ENSO can warm or cool the planet and they show that in their chart.

    If you look at the five charts, you can see a global cooling trend from 1945 to about 1965. ENSO is near zero over this time span, VOL is also zero, and the SUN and Other are always near zero. In order to have cooling from 1945 to 1965, then ANT has to be negative as the authors have clearly shown on their chart, otherwise things just do not add up. If ANT is related to GHG, and GHG always warm the planet, then the ANT chart should never be negative. Hence the reason this paper seems incorrect to me.

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  6. Stealth - Regarding zero point: If you are examining correlation/causation, the only thing that matters is the change, the anomaly. Baseline value makes no difference whatsoever for such studies. 

    Regarding solar winds and coronal mass ejections (CME): solar winds vary time-correlated with total insolation (TSI), any effect from solar wind appears (is folded in) as a larger contribution from the 11-year solar cycle, a larger solar attribution.

    The energy in a CME is roughly that of 1/6 second of total solar output, and few of them actually strike the earth - not much of a contribution. And the frequency of solar flares is also tied to the 11-year solar cycle - that would again just fold into causation studies as a larger solar attribution.

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  7. Stealth @5 - see here.  In some cases it's perhaps more accurate to say there's no evidence or research supporting a link between your proposed solar variable and global temps.

    Whether or not you buy it, Kevin and I are correct on the baselining issue.  Just look at the top panel of Figure 1.  The panels below add up to the model simulations shown in the top panel.  The top panel has a negative temp anomaly before ~1970.  All of the lower panels are plotted in terms of temp anomalies as well.  It's just a baselining choice issue.

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  8. StealthAircraftSoftwareModeler @5.

    Concerning the position of the zero on the vertical axes of figure 1 of the post. You say "That makes no sense based on the other charts" but the position of the zero is actually what makes those six panels sensible.

    The top panel has its zero point set by the global temperature anomaly based on 1980-2000. As the caption explains - "The remaining panels show the individual temperature contributions to the top panel..."  As the top panel of global temperature is well below zero at the start of the series (c -0.65ºC), the sum of all the contributions in the other panels must also total to that same value (of c -0.65ºC).

    Because the anomaly base is 1980-2000, a period in which ther was quite a lot of cooling due to volcanic activity, you will find that the panel VOL plots a positive contribution to temperatures for the vast majority of the series. This means that for most of the period 1880-2010, volcanic activity resulted in a higher temperature in comparison with the base period 1980-2000.

    Likewise the human impact ANT. Because human positive forcings were less before 1980-2000, the impact of those human forcings will be lower temperatures before that period. To describe it as "cooling" as you do requires the analysis to run backwards in time. Forwards in time, the usual way, 'cold' becomes 'hot' which is usually considered to be 'warming.'

    And as plotted, the period 1945-65 is consistent with a rising human contribution.

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  9. Stealth @5:

    1)  Volcanic contribution is not always zero.  If you run a line across at the zero level you see that it is mostly positive, only becoming noticably negative near major volcanic erruptions (approx 1905, 1965, 1985, and 1992).  The later two mean that the average is near zero over the baseline period as determined by eye.

    2)  The CME striking Earth in March 2012 was exceptional, but only released 26 billion kWh (93.6 x 10^15 Joules) of energy to Earth's upper atmosphere over three days.   That represents an average 0.0007 W/M^2 energy over the three days.  Only 5% of that energy actually reached the Earth's surface, the rest being radiated to space.  Therefore the CME increased the Earth's energy imbalance for three days by only 10,000th of the minimum current Top Of Atmoshere energy imbalance.  I would consider that inconsequential. 

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  10. Sealth said... "That, in my book, isn’t trivial or negligible, so I do not see how you can make that claim."

    Yes, it's not trivial if you are a tiny and highly sensitive piece of electronics several miles above the surface of the earth, or if you're a biological creature floating around in space susceptible to gene damage.

    What is being discussed here is the radiative forcing on the climate system.  Irradiance from the sun in coming in a ~1340W/m^2, and that varies ~0.25W/m^2 over the course of the 11 year solar cycle.  Thus, the radiative change in forcing from solar activity is tiny compared to the net change of 2.8W/m^2 in anthropogenic factors.

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  11. Okay, I think I now see the baseline issue. I think a better way to say it is that the zero line on the top temperature anomaly is around 1985. In order to get to the temperature for any given date (future or backward) then add up all the component effects of ENSO, VOL, SUN, ANT, and Other. It does appear that if you add these up then you can compute the temperature for the second date. For example, to get the temperature for 1950 from 1985, we take the temperature anomaly of 0 deg C and add -0.1 deg C for ENSO component at 1950, then 0 for VOL, then about 0 for SUN, then about -0.3 or -0.4 for ANT, and about 0 for Other. Then we arrive at about -0.4 or -0.5 for 1950, which matches the top temperature graph. Is this correct? If so, thanks for taking the time to explain it.

    I’ve done a bit of research into AGW just for fun. I’m not a “denier” per se since I’m sure CO2 does absorbs some IR wavelengths; I model some of this in aircraft detection and sensor computation for my job. My main question is “how much has CO2 contributed to global warming?” This set of charts seems to indicate that GHG is all of it over the last 100 years since all the charts (except ANT) wiggle about their respective zero line. I have a hard time believing that that Sun and Other are that stable. If you assume they are stable, then the conclusion has to be that GHG is the problem. I am curious as to how scientists have split out and determined that the Sun and Other are that stable.

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  12. Well, if you are proposing a strong solar impact on temperature, then you have the problem that solar output has declined over the past 30 years when the climate has been warming most rapidly. If you want to argue for a stronger solar term, you are also arguing for a stronger anthopogenic contribution.

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  13. I dont think any model assumes "Sun and Other are that stable". Solar input has been measured since 70s and inferred from proxies before that etc. If you look at the IPCC WG1 report, you can see what the models use for the various forcings and how these have changed over time. The references will take you to the papers that tell you how these are estimated. You might want to look at Benestad and Schmidt 2009 for a statistical look at the climate and solar forcings.

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  14. Out of interest has there been any modelling in which CO2 levels are stable and solar input isn't?

    I would think that the resulting changes would be different to that of CO2 changing, eg different types of weather patterns, different impacts on warming in different regions etc.

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  15. Stealth...  If you're interested in the topic, you should definitely check out this lecture from Dr Richard Alley.  It's a nice overview of climate science.  And Alley's a pretty entertaining speaker.

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  16. Stealth,

    The human contribution is not only GHG.  Aerosols are also included as a human forcing.  Keep in mind that aerosols are a negative forcing.  That means that the GHG effect is more than 100% of the measured warming.  The rest of the forcings add up to peanuts in the long term (probably negative).  When coal is scaled back the aerosols will quickly be removed from the equation.  That means more warming at first when less coal is used.

    It sounds to me like you have just started looking at AGW.  Read a lot more before you reach conclusions.  There are a lot of open threads here at SkS.

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  17. If Atlant  uses the electron released by the antenna to seed clouds, how much seeding dose high voltage power lines create ? 

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  18. Paul D - for modelling the difference, see Hansen 2005 "Efficacy of climate forcings"

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  19. Stealth

    Solar output as measured by satellites is around 1366 W/M2 here at the Earths orbit around the sun. Over the 11 year solar cycle it varies by around +/- 0.5 W/M2 so less than 0.04% variation around its average. Over the history of observations this has declined slightly, by perhaps 0.1 W/M2

    Comparing solar output strength to radiative forcing requires that we adjust for the fact that the frontal area the Earth presents to the Sun is only 1/4 of the Earth's surface are so this gives us a solar cycle variation at the Earths surface of +/- 0.125 W/M2 and a longer term trend variation of -0.025 W/M2.


    In contrast the direct forcing due to CO2 is given by the eqn

    F = 5.35 ln(C/C0)

    where C0 is taken as being preindustrial levels of 280 ppm. Currently we are at around 400 ppm. This gives a CO2 alone a forcing of 1.9 W/M2 since pre-industrial times.

    So the complete solar cycle is only around 7% of the CO2 forcing and the long term trend change is only around 1.3% of the CO2 forcing, and negative.

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  20. jmorpuss

    My reading of your link is that Atlant doesn't release electrons. It releases ionized particles, or possibly ionized atoms or molecules. And they are generating a Corona Discharge to produce them. It isn't simply the presence of a high voltage.

    So on that basis I would expect that high voltage powerlines alone wouldn't generate any. Anything that caused arcing from such power lines might, but that is a fairly rare event. And the quantities of ionised particles needed to influence clouds would be substantial so anything coming from such arcing events would have miniscule impact.

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  21. Glenn@19: I think you forgot the albedo factor (0.7), so your solar forcing variation should be even smaller - about 0.1W/m2. Similarly for the trend term.

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  22. Yeah Kevin, forgot that part.

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  23. Okay, there's a lot of information here that I would like to take a closer look, and it will take a little bit to go through it. This post and thread is exactly what I have been wondering about, which is specifically trying to address and measure how much warming is due to AGW. I’ve done a lot of general internet research over the last year or two and have been on this site, Real Climate, Anthony Watts’ site, Roy Spencer, Steve McIntyre among other sites trying to gather information and fuse it together into what I think it a coherent picture. I expect that mentioning some of these names on this site might be offensive, so I apologize in advance.

    My general philosophy is that I believe none of what I hear and only half of what I see. My background is dual BS in Physics and Computer Science with 30+ years in software development and modeling, most all of it related to stealth aircraft -- real time software systems operating in real world environments to support pilot decision making process. It requires modeling aircraft, weather, terrain, weapons, sensors, threats and so on. Lots of optimization algorithms to maximize opportunity and minimize risk. It has been a fun and cool job, and very interesting. If I have learned one thing, it is that modeling is always wrong (meaning it is never fully correct under all cases) and that the real world is different than the lab world, which is different than the modeled world, at least for aircraft and radars. I strongly suspect the climate is even more complex than what I have dealt with, which makes me very skeptical that climate scientists have a full grasp on the complexities of the climate. This is not a criticism of climate scientists, it is just hat things are hard and complex. After all, if it was easy, then everyone would agree and there wouldn’t be much debate.

    Give me a day or two to wallow in these links and I’ll post some more questions shortly. Thanks for the feedback.

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  24. On the question of the Sun, and its impact on Earthly climate, it's worth noting that the question of Solar variability has been revolutionized by satellite observations.  Prior to the satellite era, variations in solar output were less than experimental error, and it was commonplace to use the term 'solar constant' to refer to a particular defined measure of solar energy:

    Since then, the term has fallen largely out of use.

    However, that doesn't mean that measurement of solar output was non-existent prior to satellites.  Indeed, the history goes back to the late 18th century at least:

    It's worth mentioning Claude Pouillet in this context; he was able to make a pretty decent estimate in the 1830s--better, in fact, than the formidable American astronomer Samuel Langley, some of whose data was so serviceable to Svante Arrhenius in calculating the first model of CO2-induced warming, back in 1896.  I've written about Poillet, and Langley and Arrhenius, too--for those who may be interested, those stories are at:

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  25. Stealth @23...  I think you'll find people here to be very supportive of taking a genuinely skeptical approach to this issue.  It is a very complex science, but there are some very fundamental elements that drive the scientific understanding of climate.

    Primarily, the scientific understanding of climate change is not based on modeling or hockey stick graphs.  It's based on the fundamental physics of atmospheric greenhouse gases that has been known for 150 years.

    I think you'll find that climate modelers actually would agree with you when you state, "modeling is always wrong (meaning it is never fully correct under all cases)."  That's why climate modeling is about establishing boundary conditions rather than attempting to specifically model exactly what the climate is going to do.  That is why you'll always see climate scientists referring to "model ensembles" rather than any specific model.

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  26. scaddenp@18

    I might be missing something, but I can't see a mention of varying insolation in that Hansen paper abstract.

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  27. @SASM #23

    modeling is always wrong (meaning it is never fully correct under all cases) and that the real world is different than the lab world, which is different than the modeled world, at least for aircraft and radars. I strongly suspect the climate is even more complex than what I have dealt with, which makes me very skeptical that climate scientists have a full grasp on the complexities of the climate.

    I would like to chip in with a thought about climate modelling -big picture- which your comment reminded me of. A model by definition is "wrong", but lately I have been trying to use the word "incomplete" instead so that I don't create the impression that a model has no utility.  I would agree that our planet's climate system is more complex than smaller scale models pertaining to stealth aircraft design - however that doesn't mean that climate models have less predictive power than the models you have dealt with.

    I like to use the example of radioactive elements. The moment when an individual nucleus will blow is fundamentally unknowable. However, from this utter lack of causation knowledge comes a term "half-life" that is startilingly accurate in it predictions. Sometimes an infinite mess of choas when looked at in small chunks is freakishly predictable in the large scale. Like-wise, I think the earth's climate system is surprisingly reducable to a planet-wide, yearly average temperature, despite the appearence of innumerable interactions and parameters depending on how deep you go in the oceans, how high in the atmosphere, and with what 3-D pixel size resolution you care about. And I don't think we've seen a great increase in accuracy in our climate models since in the early eighties. Those simpler models spat out numbers with great "big picture" accuracy.

    From a distance, the earth is a tiny speck of wet rock , with a thin coating of gas, circling a heat source.  Dead simple to calculate its average temperature over long time scales... well, maybe having to guess a bit about aerosols...

    Now models zoom in more, calculate more, they add more coupling between the various "spheres" (litho, cryo, atmos, oceans) but even after decades when you get the same big picture answer for the earth's average temperature, you realize these "complex" models are merely arguing over who/what/where gets the energy that is sloshing around our planet. Does chopping the energy units into smaller and smaller peices and putting GPS-like tracking on them as they move around really make that much  difference? When you put a bubble around the earth and measure every thing that is going in and out - this is something much simplier to model than wing dynamics at different altitudes, or whatever cool classified things you were working on.

    Stealth, earlier you said, "I’m sure CO2 does absorbs some IR wavelengths; ".

    That is so important to focus on  -CO2 MUST warm the planet. If you still have any doubts, visit a lab with an infrared microscope and exhale on it. You will get the same absorption pattern you see from satellites looking down at the earth. So, with no way to argue against increasing CO2 causing warming, the interesting questions become: warming where, how fast, will it be dangerous, is there anything that will cool us down, etc.

    The questions we want climate models to answer now are much more specific: will the water level in this river go up or down in the next 30 years? What is the climate like on that exo-planet? Would you recommend I build my hut on this hectare of permafrost here?


    You mentioned some of the websites you go to for information. I've recently become sad about the futility of the Anthony Watts site. I think of the wasted hours people put in there under the partial guise of growing our scientific knowledge. If the purpose is public opinion and political medling, then it is less wasteful - but I have found it to be a very irrelevant space for scientific knowledge as it pertains to climate change. It feels like I'm watching a movie starring teenagers who get deeper and deeper into trouble because they refuse to take the advice of the police. 

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  28. Paul D - sorry, the paper has a data page which produces plots for various forcings. You can do say a lat/lon map for 2xCO2 with 100 year response and then compare that to an equivalent Solar forcing.

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  29. Stealth - if you are going to wallow in likes of Watts or McIntyre, then I hope you will try to ensure that you opinions are formed on the basis of published science and not misrepresentation of science. When you are presented with conflicted information, what method are you going to use evaluate truth here?

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  30. Stealth

    I come from a combined MechanicalEngineering/IT background. So lots of thermodynamics etc and software - although not modelling.

    An important point to consider when thinking in terms of models is the scale (in space, time, magnitude) of the different factors. To take an analogy:

    I install a new swimming pool in my backyard. To fill it I throw the garden hose in and turn it on. This may take daya to fill the pool. My family are impatient so they start using the pool before it is full.

    If I want to model what will happen to the water level I have different factors to consider-

    • volume and shape of the pool which might be complex but is static.
    • Flow rate through the hose
    • Volume of my families bodies and how much water they displace
    • How often and when they use the pool
    • how much they splash around and thus how many and what waves they make
    • Whether the dog occassionally leaps into the pool chasing a frisbee.

    Although there are multiple factors, they are not all equal. The Volume/Flowrate factors are the dominant factors and they are actually fairly simple to model. To a first order approximation that is all I need to model.

    When I factor in the displacement of my families bodies there are multiple questions to be resolved - how often and when do they use the pool, fully submerged or only partly, do they all use it at the same time etc. But the magnitude of the total effect they can have is small compared to the total volume of the pool.

    Then when I look at the impact of the waves they create it gets even more complex - all the factors previously plus what are they doing in the pool - just quietly floating, swimming laps, fighting, diving, splashing water out of the pool. Are they relaxed adults or hyperactive teenagers. How many high caffiene energy drinks have they had. Again much more complexity but now dealing with smaller scale phenomena; not really the average level of the pool anymore but the spatial distibution of its level in the form of waves.

    But our first order approximation is still pretty close to the right result.

    Climate modelling is similar. A range of basic processes that aren't as complex as people think, leading to a general result. Then additional details that add complexity and more detail to the result but don't significantly change the broad result.

    People often look at the complexity of weather and asume that this is  the starting point for Climate modelling when it isn't. Climate modelling actually comes at the problem from the opposity direction - start with the broadest mechanisms then seek to progressively refine the result through more detail and complexity. Interestingly the history of Climate Models has been that the results produced by the very earliest models haven't changed much as they have been refined to the very much larger models of today.

    The modellers have been trying to do two things by adding more features and detail.

    1. Try and determine whether any of these additional complexities have changed the broad conclusions of the simpler models. By and large they haven't.
    2. Try and determine in greater detail what the trajectory of the warming will be, what path it will follow to the final conclusion. This has had some success but not as well. Models of Arctic sea ice haven't captured the pace of melting very well, they aren't modelling changes in the Trade winds very well etc.

    The problem is that if we want to compare real world changes with the model predictions, in shorter time frames it is harder to discern the broader trends from beneath the 'noise' of the smaller details in the data, and the models don't do as well at modelling the smaller details.

    So some people fall into the fallacy of thinking that if the models can't capture the detail as well, that this in someway constitutes evidence that they can't model the basics. If I can't model the waves on my pool very well, then surely I aren't modelling the volume of the pool and the flow rate in the hose very well.

    Also it is very easy to look at the complexity of weather and asume that this is the starting point for the level of complexity in modelling climate. However climate is actually the average of the weather and the average of the weather patterns are actually simpler than the details - storm tracks tend to run here, rainfall bands are here, ocean currents follow these tracks etc.

    Then the underlying drivers for these patterns can be simpler still. Evaporation is strongest in the tropics so more upwelling of air happens there. Air cools and changes density at known rates with altitude, warming water by x degrees will change it's density by y. At it's simplest adding a certain amount of Greenhouse gas will restrict the flow of energy to space by X Watts/M2 , the Earths surface needs to warm by Y degrees to restore the Earth's energy balance.

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  31. Hi SASM-

    My understanding of the magnetic impulse hypothesis is that the energy dumped into the upper atmosphere by a coronal mass ejection is supposed to radiate/convect to the ground, and this is being ignored in conventional measurement of TSI.  That doesn't actually happen.


    NASA Coronal Mass Ejection

    As this article indicates, the green house gases in the thermosphere reradiate 95% of the energy back into space....sort of an energy shield out of science fiction.  (But it being cited by people who mince words as proof that AGW isn't real because in this case CO2 acts as coolant)

    The article also note that as big as this energy dump was, comparted to the earth's outbound IR buget the amount is very small, and wouldn't ever be notice by anyone on the surface of the earth.  Compare this qaulitatively with the feeling of the sun on your face or a cloudy night being warmier than a clear one.

    "footnote: (1) No one on Earth’s surface would have felt this impulse of heat. Mlynczak puts it into perspective: “Heat radiated by the solid body of the Earth is very large compared to the amount of heat being exchanged in the upper atmosphere. The daily average infrared radiation from the entire planet is 240 W/m2—enough to power NYC for 200,000 years.”

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  32. Stealth, to illustrate and augment the advice given you about modeling by other folks in this thread, I encourage you to read a brief history of modeling here at Skeptical Science, and for more the detailed history by Spencer Weart.  Note that even in the 1820s, Fourier was using a model.  Not a computerized model. Not a model as complex as the ones used today.  Each improvement in the science involved an improvement in the models, but only relatively recently did they get "complicated" in modern terms.  Even the earliest models were quite successful in predicting global temperature relative to other possible predictions such as "the Earth is frozen solid" and "the Earth is cooling drastically" and "the Earth is maintaining its temperature" and "the Earth will be as hot as the Sun in fifty years."  Complication is needed only to fine tune the predictions by the desired amount.

    You can try some simple models yourself by getting an introductory textbook such as David Archer's "Global Warming: Understanding the Forecast," or by taking notes while watching his free online lectures from his class at the University of Chicago.

    Tamino has illustrated a simple climate model you can run without a computer if you have a lot of time, or with a spreadsheet if you don't mind using a computer. He also has a followup that's only a bit more complicated.

    There are a bunch of other climate models that are simple enough for learning and teaching. One list has been compiled by Steve Easterbrook.

    You also might be interested in Steve Easterbrook's comments on verification and validation (V&V) of climate models.  Steve once did V&V for NASA.

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  33. scaddenp@28

    Thanks, that's interesting.

    Not a great deal of difference other than higher solar irradience would seem to make it hotter than the CO2 forcing and the Arctic and land masses would be much more hotter than would be the case if the forcing were just CO2 and/or others.

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  34. Manwichstick @27

    I agree that “incomplete” is a better word for models. My full saying about models is: “all models are wrong, but some are more useful than others.” My group does the best it can in our models, and there can be life and death decisions riding on them (that’s always humbling). All sorts of design trades have to be made, and real time is a major one – a great answer 5 minutes after you are dead is not better than a good answer in 5 seconds.

    scaddenp @29

    Your question about “evaluating truth” is a good one. I think “wallow” is a bit of a strong negative word, but I understand what you are saying. I read what “the others guys” have to say and examine the data they have. If it makes sense then I incorporate it into my world view. I guess since I don’t believe anyone, and I become convinced of things based on the data and the most creditable explanation of the data. I think my bullsh*t sensor is pretty good. But I also know I have been wrong many times in my life on many things, and have changed positions based on the results, so I feel that I am very open to the facts and what they say. I truly believe that reality has a persistent voice.

    So far, what I really like about this site is that everyone seems open and has provide excellent information, and a lot of it. I have to wait until the weekend to review and digest some of it. My day job isn’t paying me to research the climate. :-)

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  35. New question about the charts in this post:

    The contributing factors (all the ones in the various colors) seem to add up relative to the 1985 baseline for years between 1955 and 2010. If I add up ENSO, VOL, etc to the temperature on the top chart, they all add up. Before 1955 there is component data but it doesn’t produce any temperature movement. From 1910 to 1945 there was a large warming period of almost 1 deg C, but the component values do not reproduce that. The ANT chart also seems to be saying that all ANT effects have been from 1960 until today – is this censuses view on AGW? I thought the AGW claim is that the industrial age and CO2 increase has caused most of the warming. If ANT hasn’t affected temperature from 1910 to 1945, what caused the large temperature increase from 1910 to 1945?

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  36. Stealth - In the early 20th century solar activity was relatively high (positive influence), and even more importantly there was a distinct paucity of volcanic action (less negative influence); notice the flat volcanic graph during that period. There's a SkS thread on this very topic - What caused early 20th Century warming - which is worth looking at.

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  37. Stealth: Here's the Potsdam data which was an input to CMIP5 in excruciating detail. link

    Start with pages 4-7. Volcanic is on page 45. Solar is on page 46 (note the scales).

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  38. Stealth...  I may be repeating Kevin and KR, but I think you'll find there to be a general consensus in the research that early 20th century warming was only partly due to anthro-GHG forcing.  From ~1940 to 1970 you get a slight cooling due to anthro-aerosols, and then late 20th century is likely all due to anthro-GHG forcing.

    I have to say, it sounds like you're taking an appropriately skeptical approach to the issue.  It's greatly appreciated.  It's hard but we all have to try to check our biases at the door when looking into scientific issues.

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  39. Stealth


    In addition to the other comments about 1910 to 1940's warmth, this is interesting from GISS. Warming by latitude vs time (available here):

    A significant part of the warming was just in the Arctic. Also the station coverage of the Earth was in flux during that period. Stations were being added to the Arctic at that time which previously had no useful coverage. The Antarctic only started getting decent coverage after the International Geophysical year in 1957. I have some doubts about how much credence we can give the 1910-1940's data if there was a regional warming just as station coverage was changing in that very region.

    Also there was a definite bias change in the measurement of Sea Surface Temperatures during the years of WWII due to a change in the mix of nationalities measuring SSTs (and thus measurement methods) during the war. This has been partly corrected through an adjustment to those records just recently but it is unclear how completely that has resolved the issue.

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  40. Stealth @35, by a rough pixel count, there is an approximately 0.15 C increase in temperature due to anthropogenic factors shown in the chart from 1880-1950.  That is much smaller than post 1950 but not zero.  Others have provided an the data needed on natural forcings over that period.  It should be noted that part of the 1910-1940 temperature increase is due to a switch from strong La Nina conditions arount 1910 to strong El Nino conditions around 1940.  

    There remains, however, a small component of that increase which is not yet explained by either known forcings or ENSO variation.  This may be due to problems in the temperature record.  Global coverage of SST (in particular) fell significantly during WWI and WWII and immediately after due to reduced the effect of the wars on merchant shipping.  It may also be due to an underestimate of the forcing from Black Carbon (BC).  Finally, it may also be due to the Atlantic Multi-decadal Oscilation. 

    Post 1950, natural forcings are negative such that anthropogenic factors represent around 90% of all forcings from 1880-2010 (as shown above).  The uncertainty about that is sufficiently large, however, that it could be significantly lower than that.

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  41. stealth @34: "I think my bullsh*t sensor is pretty good."

    One component of an effective bullsh*t sensor that is often missing is an appropriate respect for expertise.  An expert has been succinctly defined as a person who knows all the  basic mistakes in their field, and how to avoid them.  Ergo the most basic feature of the non-expert is that they do not know how to avoid basic mistakes.  That can be simply because the relevant information available to them is limited compared to that possessed by the expert; or because of lack of knowledge of the literature in which the basic mistake they are making was first proposed, then refuted. 

    This is not to suggest that experts are always right.  However, if you are genuine about avoiding bullsh*t your first instinct when you come up with a significantly different answer to that of the experts is to ask yourself, "What am I missing?"  The arrogance of AGW "skepticism" as practised at WUWT etc is seen in the failure of this form of self skepticism.  

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  42. John Nielson-Gammon gave a talk at last year's AGU meeting on Scientific Meta-Literacy. His key point:

    But there’s an important lesson here about how we decide which scientific statements to believe and which ones not to believe. Those of us who are trained scientists but who do not have enough personal literacy to independently evaluate a particular statement do not throw up our hands in despair. Instead, we evaluate the source and the context.

    We scientists rely upon a hierarchy of reliability. We know that a talking head is less reliable than a press release. We know that a press release is less reliable than a paper. We know that an ordinary peer-reviewed paper is less reliable than a review article. And so on, all the way up to a National Academy report. If we’re equipped with knowledge of this hierarchy of reliability, we can generally do a good job navigating through an unfamiliar field, even if we have very little prior technical knowledge in that field.

    Well, the typical member of the public has very little retained technical knowledge about just about everything. I claim that it’s an impossible task to raise the level of climate literacy in the general public to the point where most can tell that the statement about the ice age is wrong, let alone whether the statement about Sandy is wrong. And what about all the other fields in which they need to be literate as well?

    The solution to this problem is not scientific literacy, but what I call scientific meta-literacy. Forget that dream about enabling the public to independently evaluate scientific claims on their merits – that’s just not going to happen. Instead, enable the public to distinguish between reliable and unreliable sources of scientific information.

    Skepticism is all very well, but it's important to understand that it takes work to become an expert, and if you're not willing to do the work, you have little choice but to trust the ones who have. A genuine skeptic recognizes and respects expertise. Otherwise, he risks falling prey to the Dunning-Kruger effect.

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  43. As far as the CO2 part of the equation goes, I would need to see robust evidence for the proposition that atmospheric CO2 did not absorb/emit at various pressure-broadened bands in the thermal infrared range.  Or I would need to see robust evidence that atmospheric CO2 is not actually present in observed concentration.

    The only other forcing that can match CO2's persistent (non-condensing, well-mixed, long residence time) forcing is solar variation.  I would need to see evidence that falsifies every major assessment of solar contribution of the past two decades (add Pasini et al. 2012, Jones et al. 2013, and Mann et al. 2013).

    There can be evidence.  There's always the possibility that aliens are manipulating instrumentation.  Climate science is one of the most scrutinized sciences.  All someone has to do to get a Nobel is falsify a major element of the current mainstream theory of climate, and do it in such a way that removes human responsibility.  People have been trying for decades. 

    I think your characterization of climate science is a little off, as well.  The current science lays the foundation for the discoveries of tomorrow, unlike the practice of blood-letting and modern medical practice.  Your assertion strongly suggests that current climate science is utterly wrong.  Where's the evidence for such an assertion?  You talk of clouds and sun, and everything you know about them is blood-letting.  Were the Wright brothers blood-letters, or were they useful pioneers? 

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  44. Mal Adapted: That's a great article, thanks for pointing it out. I've suggested to the powers that be that it might be worth a post.

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  45. DSL @43. It seems my comment may have been deleted and I am not sure why. I did ask some questions and you seemed to answer one of them, so it was posted for some time. Perhaps the moderator thought my post was an ad hominem or not on topic or inflammatory. If so, I apologize. I’m not looking to start any flame wars and I am honestly looking for a good discussion.

    Let me just completely back up and ask some basic questions:

    (-snip-).  Thanks!  Stealth

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    Moderator Response:

    [DB] Your previous comment was moderated out as it contained multiple off topic statements, as does this one.  Please take your individual concerns and questions to the most appropriate threads and place them there.  The regulars providing dialogue interaction and guidance here will see them, no matter where you place your questions, and will respond as appropriate on those same threads.

  46. Stealth, you can play with the numbers yourself with this wonderful calculator. The mathematical introduction in Ramanathan Coakley 1978. Doubling CO2 from 280 adds 3.7W/m2 from CO2 alone.

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  47. And please move further comments to the appropriate thread. Regulars view this site through "comments" link so you comment doesnt get lost. Offtopic comments will be deleted.

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  48. SASM @45, I have responded here.

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