A detailed list of the errors in Monckton's July 2008 Physics and Society article

This document and all opinions expressed here are purely my own, and do not represent the views of any organization with which I may be associated. I have received no funding or support from any source for this analysis or any other work I have done on climate or energy issues.

Arthur Smith

Selden, NY

apsmith@altenergyaction.org

Substantially completed: September 6, 2008 (see below for updates)



The following critique has reference to the article "Climate Sensitivity Reconsidered" by Christopher Monckton published in the APS Forum on Physics and Society Newsletter "Physics and Society", July 2008.

Please note several other critiques of this article have appeared online, after I started collecting my own notes, and their analysis has informed mine to some degree, so I thank them for that. In particular see the commentaries from Tim Lambert, Gavin Schmidt and Duae Quartunciae. I felt compelled to write a more thorough critique based on my own interest and long history as a member of the APS Forum, having written several letters and an article for the newsletter on energy issues, and given that I have recently been closely involved in several email and online discussions on climate and thus have become quite familiar with most of the issues involved. The list included here is not intended for publication in "Physics and Society" - it would overwhelm that small publication - and I have prepared a much shorter separate response for that venue, focused on the central issue of sensitivity.

Also please note that simply itemizing errors in an article doesn't prove one way or another whether the central premise of the article is wrong or not (the "fallacy fallacy"). Monckton's central question is on climate sensitivity. The magnitude of that sensitivity is a central question of climate science as a whole, and in particular centers on the sign and magnitudes of various feedbacks to temperature increase in Earth's climate system. The most recent IPCC report (AR4, Working Group 1, 2007) presented a robust collection of evidence from physical modeling, paleoclimate, and observed recent response of the climate system for their conclusions of a temperature response to CO2 doubling of between 2 and 4.5 K, with a best estimate around 3 K. The substantial collection of errors in Monckton's article renders his arguments against this IPCC conclusion quite unconvincing.

September 11, 2008: formatting fixes: added greek character entities and replaced non-ASCII characters that came in via cut-and-paste.

September 12, 2008: added a linked table of contents, and expanded references section with more of the cited papers (now rather randomly ordered...)

Errors or fallacies in the text are categorized and denoted under the following headings:

Errors of fact: "Wrong"

Irrelevant conclusions and non sequiturs: "Red Herring"

Other errors of logic: "Nonsense"

Errors of interpretation or misunderstanding: "Confused"

Arguments that only work for specially selected data: "Cherry Picking"

Other arguments that have no scientific validity: "Invalid"

Statements that contradict or conflict with other statements in the text: "Inconsistent"

Monckton: (IPCC, 2007) concluded that anthropogenic CO2 emissions probably caused more than half of the "global warming" of the past 50 years

Confused. The relevant statement from the IPCC AR4 WG1 SPM is "Most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations." (p. 10). Note Monckton has substituted "more than half" for "most" ("most" is an approximate term, but generally implies more than "more than half"), "CO2" for "greenhouse gas" (incorrect but irrelevant), "probably" for "very likely" (strong reduction in implied certainty), "past 50 years" for "since the mid-20th century" (inconsequential) and "global warming" (in quotes) for "observed increase in global average temperatures" (Monckton's change loses the IPCC's implication that warming has in fact been observed).

Monckton: global mean surface temperature has not risen since 1998 and may have fallen since late 2001.

Wrong and Cherry Picking: Both of these claims, no warming since 1998 and cooling in 2007/2008 are familiar to anybody who has watched online discussion of climate in recent years. 1998 as a whole was anomalously warm in all temperature measurements, and some months in 2008 appear to have been anomalously cool. If you look at 8- or 11-year trends rather than 7 or 10 as of mid 2008, temperature is up. This is hardly unexpected given the complexity of Earth's coupled oceans and atmosphere, and it is worth referring back to the definition of climate itself to see what's wrong with this sort of argument based on looking at the temperature in any given month or year. From the IPCC AR4 WG1 Glossary (Annex 1), p. 942:

IPCC: Climate in a narrow sense is usually defined as the average weather, or more rigorously, as the statistical description in terms of the mean and variability of relevant quantities over a period of time ranging from months to thousands or millions of years. The classical period for averaging these variables is 30 years, as defined by the World Meteorological Organization. The relevant quantities are most often surface variables such as temperature, precipitation and wind. Climate in a wider sense is the state, including a statistical description, of the climate system. In various chapters in this report different averaging periods, such as a period of 20 years, are also used

When you look at 20-year or 30-year averages, the temperature rise through the present is extremely clear.

Monckton: the failure of the IPCC's models to predict this and many other climatic phenomena

Wrong and Red Herring. See the above definition (E2) of "climate" from the IPCC. Phenomena on less than a 20-year time scale are not relevant to a climate discussion. Nevertheless, the IPCC referred to many climate models that included patterns of temperature variation very similar to the plateau or dips on less than 10-year time-scales observed recently. The IPCC AR4 individual realisations figure in the linked RealClimate article shows models with all variety of behavior on a decadal scale. See below on the "many other climate phenomena".

Monckton: Some reasons why the IPCC's estimates may be excessive and unsafe are explained.

Invalid and Nonsense. Safety or lack thereof is not discussed in Monckton's paper, nor is it a topic of the IPCC's "Working Group 1" which discusses the science under review here. Working groups 2 and 3 focus on impacts (safety) and adaptation or mitigation. The errors in the remainder of the article make the "excessive" claim not logically follow. And why the "may be" qualifier?

Monckton: More importantly, the conclusion is that, perhaps, there is no "climate crisis", and that currently-fashionable efforts by governments to reduce anthropogenic CO2 emissions are pointless, may be ill-conceived, and could even be harmful.

Nonsense. There is no valid logic in the article supporting these claims. And why the definitive "are pointless", while all else is modified by "perhaps", "may be", or "could even be"? The level of certainty seems very inconsistent. But let's move on to the article itself.

Monckton: GLOBALLY-AVERAGED land and sea surface absolute temperature T S has not risen since 1998. [...] For almost seven years, T S may even have fallen.

Wrong and Cherry Picking - a repeat of the claims in the abstract addressed above (E2). To reiterate, climate is long-term, not short term, and in terms of 20-year averages, the temperature has continued to rise.

Monckton: There may be no new peak until 2015

Confused. The reference is to a 2008 Keenlyside et al article in Nature, but this paper looked only at decadal average temperatures (a reasonable climatic measure), not annual averages which Monckton is talking about here ("peak" presumably referring to 1998). Furthermore, Keenlyside's prediction gave only a plateau in the 2005-2010 time-frame (decadal averages centered on those dates), certainly not a decline in temperatures. For an example of another prediction, one could refer to the Hadley Center's 2007 paper in Science: "at least half of the years after 2009 predicted to exceed the warmest year currently on record."

Monckton: The models [...] had not projected this multidecadal stasis in "global warming"

Wrong and Nonsense. Wrong on two counts actually: first, there is no "multidecadal stasis" in observations; the only statement on longer than a decade for any sort of "stasis" is Monckton's misinterpretation of Keenlyside's prediction; it is hardly relevant to claim this misinterpreted prediction constitutes a failure of projection. Second, the models do indeed show periods of a decade or less with "stasis", simply because the projected 0.2 degrees per decade temperature rise is within the natural year-on-year variability of measured temperatures (and there are some long-term cycles like El Nino that have that level of impact).

[The models had not projected] the fall in T S from 1940-1975

Wrong and Red Herring: there were no realistic climate models predating 1940 or even 1975, so there was little possibility of projection. These years predated satellite measurements so many of the input parameters to models have to be estimated and are hard to calibrate. There is also some dispute over the sea surface temperature records during this period. Nevertheless, present climate models are quite capable of matching this period's temperature record with reasonable estimates for aerosol levels and the known measurements of greenhouse gases. See also these notes on the "ice age scare" and the reliability of climate models (graphs there show the matching of model results in the 1940-1975 period and throughout the 20th century).

[The models had not projected] 50 years’ cooling in Antarctica [...] and the Arctic

Wrong, Cherry Picking, and Red Herring: Cooling in eastern Antarctica is a regional, not global effect; models that don't get to that level of detail obviously won't project it. West Antarctica has experienced some of the fastest warming on Earth in the last half-century, as has the Arctic. Nevertheless, even some early models did project a delay in warming or even a cooling of Antarctica to this point: see Stephen H. Schneider and S.L. Thompson (1981) J. Geophysical Research 86: 3135-3147; also Kirk Bryan et al. (1988) J. Physical Oceanography 18: 851-67. See also this discussion of Antarctic cooling.

[The models had not projected] the absence of ocean warming since 2003

Red Herring and Confused. See above (E2) on 1998 and friends: 5 years of records is insufficient to form any conclusions on climate, and the measurement techniques are themselves still being refined.

[The models had not projected] the onset, duration, or intensity of the Madden-Julian intraseasonal oscillation, the Quasi-Biennial Oscillation in the tropical stratosphere

Red Herring: intra-seasonal changes are weather, not climate, by definition. Quasi-Biennial oscillations are similarly well below the timescale relevant for climate. Any oscillation contributes nothing to climate (long-term) averages, though it may alter slightly the variability of quantities that is part of the full description of a climate state. Also, see IPCC AR4 WG1 section 8.4 (more on this in the next item).

[The models had not projected] El Nino/La Nina oscillations, the Atlantic Multidecadal Oscillation, or the Pacific Decadal Oscillation that has recently transited from its warming to its cooling phase

Wrong, Confused, and Red Herring: most of the models used by the IPCC exhibit significant oceanic oscillations of these sorts: in particular see section 8.4 of IPCC AR4 WG1 (p. 620 and following) - "Evaluation of Large-Scale Climate Variability as Simulated by Coupled Global Models". Once again, oscillations contribute nothing in the long term to actual climate measures (like average global temperature), although long-period oscillations would add additional variability in the 20- or 30-year timeframe traditionally used for averaging. Another interpretation here is that Monckton is attacking the models because they don't specifically predict the detailed evolution of these oceanic oscillations. But they are not intended to and this is a misinterpretation of the purpose of climate models and the definition (once again) of climate. The ocean oscillations are not strictly periodic, and their evolution is most likely chaotic as the coupled ocean and atmosphere respond to one another and external forcings. Projecting their detailed evolution would be impossible if they are actually chaotic, and pointless for the purposes of assessing climate since climate is defined by long-term averages, not short-term oscillations.

oceanic oscillations which, on their own, may account for all of the observed warmings and coolings over the past half-century

Wrong and Confused: This refers to a paper by Tsonis, Swanson, and Kravtsov, Geophys.Res. Lett.,34: L13705, which looked at the correlation between indexes of the oceanic oscillations and modeled the chaotic processes through variations in coupling and occasional synchronization. They argue that the oceanic oscillations account for temperature variations after you subtract out a trend for anthropogenic warming - see for example the difference in global temperature curves between their figure 1 and 3. The oceanic oscillations emphatically do not account for the observed overall warming of the 20th century.

[The models had not projected] the magnitude nor duration of multi-century events such as the Mediaeval Warm Period or the Little Ice Age

Wrong and Red Herring: once again, no climate models predate the MWP or LIA, so "projecting" them would have been rather astonishing. Nevertheless, see IPCC AR4 WG1 section 9.3.3, "What Can be Learned from the Past 1,000 Years?", p. 680. For example, "all simulations show relatively cold conditions during the period around 1675 to 1715 in response to natural forcing, which is in qualitative agreement with the proxy reconstructions."

[The models had not projected] the cessation since 2000 of the previously-observed growth in atmospheric methane concentration

Red Herring: atmospheric methane is almost entirely anthropogenic, so it would be an input, not an output, of climate models. Monckton may here be complaining that none of the emissions scenarios predicted this, but emissions scenarios are very different from climate models, and not the subject of this discussion at all.

[The models had not projected] the active 2004 hurricane season; nor the inactive subsequent seasons; nor the UK flooding of 2007

Wrong and Red Herring: Weather is not Climate. On the other hand, the climate models have long predicted an increase in weather variability caused by increasing temperatures and higher water vapor levels in the atmosphere, so these sort of events are hardly unexpected in a warming world.

[The models had not projected] the solar Grand Maximum of the past 70 years, during which the Sun was more active, for longer, than at almost any similar period in the past 11,400 years

Red Herring, Confused, Inconsistent, and Invalid: Solar irradiance is an input to the climate models, not an output. Estimating solar irradiance in the past based on sunspot or radiocarbon variations is a shaky extrapolation of the science at best, though it has some foundation in recent measurements. There has certainly been no significant change in what we receive from the sun since satellite measurements started, but that has been the period of fastest temperature increase on the surface. IPCC estimated very little change in solar irradiance over the past 250 years. If these very small irradiance changes have caused the temperature changes observed, then the climate is more sensitive to small forcing changes, not less. See also the following commentary on the sunspot-TSI issue.

[The models had not projected] surface "global warming" on Mars, Jupiter, Neptune's largest moon, and even distant Pluto

Red Herring, Cherry Picking and Invalid It seems odd to claim that models of Earth's climate would project climate on the other planets in the solar system - but perhaps Monckton has forgotten the start of his sentence by this point. At any given time, one might expect some of the bodies in the solar system to be warming up, some to be cooling down, and some to stay about the same, for a variety of reasons. In fact, Uranus has been observed to be cooling. If this is supposed to be some argument for changes in the Sun causing warming, see the previous section (E18) on sunspots and TSI. In fact, none of the changes observed in the planets can be explained by the minor solar changes in the period under observation, and they all have other logical causes, from changing albedo on Mars to natural orbital variations (Neptune and Pluto haven't even completed a third of a full orbit since we've had good observations). See discussion of the claims for Mars, Jupiter, and Triton and Pluto.

[The models had not projected] the eerily-continuing 2006 solar minimum

Red Herring and Inconsistent Why would climate models predict sunspots? TSI is input, not output. Also see above (E18) on TSI. What happened to the "Grand Solar Maximum"? Global temperatures in 2006 and 2007 were among the highest ever recorded according to satellites and ground measurements; There is no relevance of this lack of sunspots to the subject under discussion.

[The models had not projected] precipitate decline of ~0.8 °C in T S from January 2007 to May 2008 that has canceled out almost all of the observed warming of the 20th century

Cherry Picking, Confused, and Red Herring. First, Weather is not Climate. A drop as large as 0.8 K for that period is seen in only one of the temperature records (UAH MSU) - the Hadley curve which Monckton also plots shows a drop in that period of about 0.35 K. Just like the whole year 1998, the month January 2007 was extraordinarily warm - if we were looking at monthly records instead of yearly ones for our earlier discussion of "peaks", the absolute peak in monthly temperature anomalies was then, January 2007. Not so long ago. So it's not surprising that temperatures would drop from that point. And to repeat, climate models aren't designed to predict 16 month temperature behavior: weather is not climate. Finally, to have "canceled out almost all the observed warming" one would think the measured temperature anomalies would have to have returned to their early 20th century values, but in fact even the precipitous drop seen in the UAH MSU record is still above where that measurement was in the early 1980s, and the May 2008 temperature measurement for Hadley was almost 0.3 K above its 1961-1990 reference period.

Monckton: Since the phase-transition in mean global surface temperature late in 2001, a pronounced downtrend has set in.

Red Herring, Cherry Picking and Nonsense First note that the figure shows temperatures starting in 2002, not 2001. However, this data is irrelevant because 6-7 years is not a sufficiently long period of time to obtain the averages that define climate. Weather is not climate. It also constitutes cherry picking because while the 6- and 7-year trends are flat or slightly down, the 8+ year trends are up. The figure is also missing any estimate of error bars on the trends, essential for any claim of science-based analysis. Whether calculated from the observed temperature variations of the past seven years or from a longer history of temperature variation, those error bars are known, and anybody with experience in such estimations can see from the image that the calculated trends are not inconsistent with an underlying rising trend, given the large variations in monthly temperature numbers. The decline in the trend lines shown is just over 0.1 K over 7 years, well within the large yearly average variations. Calling this a "pronounced downtrend" is vastly overstating the case. Finally - what "phase transition" is referred to here? Monckton appears to be basing his claim on the oceanic oscillation work of Tsonis et al; there is certainly no other claim or consensus of a "phase transition" in the global climate system in that year.

Monckton: In the cold winter of 2007/8, record sea-ice extents were observed at both Poles.

Wrong and Red Herring: As can be seen from this image, the Northern Hemisphere sea ice last winter was still well below typical winter extents from 2003 and earlier, no record. Antarctic ice extents have been gradually increasing over time, so it's not surprising when records (for which we only have a 30 year history!) are broken there.

Monckton: The January-to-January fall in temperature from 2007-2008 was the greatest since global records began in 1880.

Cherry Picking For a 100-year record with no underlying trend, any given year will have a 1% chance of breaking that record, up or down. Furthermore, Monckton's statement is true only for the GISS temperature record which he does not explicitly cite here (but which does start in 1880, as opposed to the satellite records that start in the 1970s, and the Hadley center data which starts in 1850). For the Hadley center data which he cites and shows in his figure, a far larger drop of 1.1 K is given from January 1863 to January 1864. Year-over-year temperature drops larger than January to January 2007-2008 are also present in the Hadley data for January 1860-61, December 1861-62, February 1869-70, January 1874-75, December 1891-92 and February 1892-93, August 1945-46, and February 1973-74. The temperature drop was unusual, but not that unusual. Weather is not climate.

Monckton: In 1988, Hansen showed Congress a graph projecting rapid increases in T S to 2020 through "global warming" (Fig. 2)

Confused and Inconsistent: Hansen did indeed show Congress a graph in 1988, but not quite this one. The original (at least the published version of the paper the congressional testimony was based on) can be downloaded from GISS - see Figure 3a in the scanned PDF. Monckton has changed the graph in the following ways:

truncated the graph from the left by starting in 1988 instead of 1958, and from the bottom by starting at 0.1 instead of -0.4

further shrunk the vertical scale - the effect reduces the visual slope by changing the aspect ratio of the graph

switched the labeling of Hansen's scenarios A and C

replaced dashed lines with colored lines - the effect visually underweights the B and C (A in Monckton's) curves compared to A (C), which were equally weighted in Hansen's version. Hansen's scenario A (Monckton's C) is known to have significantly overestimated the increase in anthropogenic greenhouse gases over the past 20 years; the reality has been much closer to B. Hansen actually testified in 1988 that his "B" was the most likely scenario.

added a title and various other curves and labels

Also, Monckton has been stating the central point of his article is an analysis of sensitivity: Hansen's 1988 analysis found a climate sensitivity of 4.2 K for doubled CO2 (see section 6.1 of the paper); this is at the very high end of the range in the latest IPCC report, so the detailed comparison with Hansen's predictions addresses a significantly different number than the recent IPCC estimate that Monckton claims here is too large.

Monckton: IPCC (1990) agreed (D)

Nonsense: Monckton doesn't describe where he got this IPCC (1990) projection. The 1990 (first) IPCC report did present a "best estimate" of a roughly 3 K rise from 1990 to 2100, but this was hardly expected to be the straight line (with no error bars!) that Monckton plots here.

Monckton: these projections proved well above the National Climate Data Center's outturn (E-F), which, in contrast to the Hadley Center and UAH records (Fig. 1), show a modest rise in temperature from 1998-2007.

Wrong and Nonsense: Monckton projects a straight line from the observations to 2020 (point F), but temperatures in 2020 have nothing to do with actual observations to this point. In fact, the difference between the observed temperatures and Hansen's scenario B has never been more than 0.3 degrees, and it was already 0.2 degrees high in 1989. In 1998 the observed temperature was almost 0.2 K above Hansen's scenario B. So even Hansen's over-estimated projection is hardly "well above" observations as yet.

Also, the Hadley and UAH data also show a rise almost exactly matching the NCDC numbers. Monckton's Fig. 1 shows monthly temperatures from 2002, not annual averages from 1998!

Monckton: If McKitrick (2007) (G,H) is correct that temperature since 1980 has risen at only half of the observed rate, outturn tracks Hansen's CO2 stabilization case (A), although emissions have risen rapidly since 1988.

Confused and Red Herring: This appears to be a reference to McKitrick and Michaels, (J. Geophys. Res., 112, D24S09) which claimed that land temperature anomalies may be overestimated by a factor of two based on a statistical correlation argument and claims of Urban Heat Island effects. This is despite the fact that the temperature records are already corrected for such effects, and earlier analyses (Parker, David E. (2004), "Large-scale warming is not urban", Nature 432 (7015): 290 and David E. Parker (2006). "A demonstration that large-scale warming is not urban". Journal of Climate 19: 2882-2895) found no residual impact. Even if this disputed claim were correct, it would only affect 30% of the Earth's surface, and Monckton is completely unjustified in dividing the entire record in half here. The claim that surface temperature records are unreliable is a common one; follow the link for further discussion.

Additionally, the comparison to Hansen's scenario C (Monckton's "A") is also irrelevant, as Hansen's projections for temperature under the B and C scenarios don't start to significantly diverge from one another until 2010. Most of the recent warming is residual warming from increased CO2 in years past, not directly from the most recent few years worth of emissions.

Monckton: There is no good statistical basis for any such quantification, for the object to which it is applied is, in the formal sense, chaotic. The climate is "a complex, non-linear, chaotic object" that defies long-run prediction of its future states (IPCC, 2001)

Confused and Red Herring: This is in reference to IPCC (AR4)'s quantified estimates of confidence ("very likely" or "likely") in various statements. However, these estimates have nothing to do with "long-run prediction of future states" of the Earth. IPCC's confidence estimates are explained in box TS.1 in the technical summary of AR4 WG1, p. 22-23. Some of these assessments are based on stastitical analyses, and where that is not possible, on expert judgment. See the IPCC statements for details.

Furthermore, the quoted phrase "a complex, non-linear, chaotic object" does not actually appear in the 2001 IPCC assessment, not to mention the longer unattributed phrase regarding long-run prediction. In fact, as described clearly by the IPCC, climate is reasonably well-defined as an average state; the complex non-linearity and chaos of weather (the subject of Lorenz) is simply averaged over when it comes to climate, and the impact of the chaos is seen only in the statistical distribution of variables that defines the climate. Once again, climate is not weather. There is always a concern that, with such a complex underlying system, we may not end up with stable averages over the 20 or 30-year periods that define climate, or more importantly that the response of this complex underlying system to our forced changes will be in some unanticipated direction simply because it is so complex. Those "unknown unknowns" feed into the uncertainty estimates of the expert authors of the IPCC reports. Science is never fully certain of anything. Nevertheless, these authors have clearly stated their level of confidence, and Monckton has no real argument against that here.

Monckton: The Summary for Policymakers in IPCC (2007) says - "The CO2 radiative forcing increased by 20% in the last 10 years (1995-2005)."

Wrong and Confused: This statement as written does not appear in the SPM. The closest statement to this (p. 4 of the AR4 SPM) is part of a paragraph, the full context of which is:

IPCC: The combined radiative forcing due to increases in carbon dioxide, methane, and nitrous oxide is +2.30 [+2.07 to +2.53] Wm-2, and its rate of increase during the industrial era is very likely to have been unprecedented in more than 10,000 years (see Figures SPM.1 and SPM.2). The carbon dioxide radiative forcing increased by 20% from 1995 to 2005, the largest change for any decade in at least the last 200 years. {2.3, 6.4}

Monckton: insertion, after the scientists had completed their final draft, of a table in which four decimal points had been right-shifted so as to multiply tenfold the observed contribution of ice-sheets and glaciers to sea-level rise

Confused: This apparently refers to table SPM.1 (p. 7 of AR4 WG1 SPM), which is a copy of Table 5.3 in the full report and which shows identical numbers. The scientists wrote up chapter 5, not the "bureaucrats", so Monckton's claim appears very strange, but of course I don't have access to whatever drafts he is talking about. The confusion is most likely because sea level rise is often shown in meters per century, rather than mm per year as in this table, and the difference in numerical value with those units is indeed a factor of 10 in the direction indicated. Perhaps the table was originally shown in meters per century units, and changed between draft and final publication. There have been no allegations from the scientists that the published numbers are wrong.

Monckton: heavy reliance upon computer models unskilled even in short-term projection, with initial values of key variables unmeasurable and unknown, with advancement of multiple, untestable, non-Popper-falsifiable theories,

Wrong, Red Herring, and Nonsense: Weather is not climate, so short-term projection is not the purpose of the models at all. Nevertheless, several of the computer models used are closely related to numerical weather-prediction codes which people apparently find reasonably reliable these days. Climate models are run with a wide variety of initial states (ensemble averaging) which is a standard statistical technique since climate is defined by statistical averaging. The "unmeasurable and unknown" initial values are irrelevant to climate. And Monckton has even made a case already that some of Hansen's 1988 projections were wrong, so the theories are hardly non-falsifiable. Fortunately, the theories have improved since 1988.

Monckton: quantitative assignment of unduly high statistical confidence levels to non-quantitative statements that are ineluctably subject to very large uncertainties

Confused and Red Herring: see above (E29) on confidence.

Monckton: the now-prolonged failure of T S to rise as predicted (Figures 1, 2),

Wrong: climate-relevant (long-term) averages continue to rise. See above (E2) on temperatures since 1998.

Monckton: [the above] raise questions about the reliability and hence policy-relevance of the IPCC's central projections.

Monckton: Dr. Rajendra Pachauri, chairman of the UN Intergovernmental Panel on Climate Change (IPCC), has recently said that the IPCC's evaluation of climate sensitivity must now be revisited

Almost certainly Wrong or Confused: I could find no such statement by Pachauri, and Monckton cites none. It is, however, a reasonable statement for Pachauri to make, in the context of the IPCC's main purpose every few years to re-evaluate the science, they will most certainly revisit their assessment of sensitivity. But I find it very unlikely Pachauri made this statement in relation to just a few months of temperature records: he is also quite aware that Weather is not Climate. Until the next report, the IPCC's AR4 WG1 assessment of sensitivity is the most well-grounded set of numbers we have.

Monckton: The IPCC defines climate sensitivity as equilibrium temperature change [...] in response to all anthropogenic-era radiative forcings and consequent "temperature feedbacks" - further changes in T S that occur because T S has already changed in response to a forcing - arising in response to the doubling of pre-industrial CO2 concentration (expected later this century).

Confused. Although Monckton is close, the differences between this and the real definition lead to further errors later in Monckton's article. Here are the IPCC's actual statements defining sensitivity in the AR4 WG1 report: from section 8.6.1:

IPCC: equilibrium global mean surface temperature change following a doubling of atmospheric CO2 concentration

IPCC: equilibrium globally averaged surface air temperature change for a doubling of CO2 for the atmosphere coupled to a non-dynamic slab ocean

The definitions also do not refer to "pre-industrial" CO2 levels. The radiative forcing is close to logarithmic in CO2 concentration, and the response terms are close to linear for relatively small forcings, so the equilibrium response should be roughly the same for doubling from any starting point within a few factors of 2 of present values. The IPCC definitions also do not refer to any time period (Monckton's "later this century") - in particular, the meaning of "equilibrium" is a long-term, century-scale equilibration of the ocean, atmosphere, and land surface system under the different CO2 conditions. IPCC also defines a shorter-term sensitivity, the "transient climate response" or TCR, which does refer to time periods and rates of change (see chapter 10 executive summary, p. 749):

TCR, defined as the globally averaged SAT change at the time of CO2 doubling in the 1% yr-1 transient CO2 increase experiment

Monckton: To [CO2 radiative forcing] is added the slightly net-negative sum of all other anthropogenic-era radiative forcings, calculated from IPCC values (Table 1), to obtain total anthropogenic-era radiative forcing [...] at CO2 doubling (Eqn. 3). Note that forcings occurring in the anthropogenic era may not be anthropogenic.

Confused and Invalid: This would indeed be a way to calculate the "total anthropogenic-era radiative forcing at CO2 doubling", but that quantity is not the forcing relevant to examining IPCC's studies of sensitivity. As noted above (E37), sensitivity is defined specifically by the equilibrium response to a doubling of CO2 with all other forcings held fixed. That means the forcing related to sensitivity is simply what Monckton computed in Eq. 3 (3.7 Wm-2), not what he ends up with in Eq. 4 (3.4 Wm-2). Given that radiative forcings depend on atmospheric profiles which have to be averaged over, they are only believed to be known to within about 10%, so Monckton's error here is of little real consequence. However, Monckton's use of 4 digits in his calculations implies far greater precision than is warranted.

Even his calculation of the 3.4 Wm-2 value is invalid, however. The correct value for "total anthropogenic-era radiative forcing at CO2 doubling" would be the 3.66 Wm-2 of the second-last line in his table 1. Monckton then adjusts this by an unexplained and unreferenced "IPCC probability-density function" to get his final number. What does this "probability density function" have to do with anything, and where did it come from?

Update It was pointed out to me that Duae Quartunciae seems to have figured out where Monckton got his "probability density function", from another IPCC table. It makes no more sense than any of the rest of his analysis here, but the numbers seem to fit. Go read the source for details.

Monckton: To preserve the focus on anthropogenic forcings, the IPCC's minuscule estimate of the solar forcing during the anthropogenic era is omitted.

Red Herring: and this is actually an important point. Once again, IPCC's estimate for climate sensitivity is based on a forcing change only in CO2 doubling. Everything else, including solar forcing, is held fixed. Monckton has correctly shown (in Eq. 1) that the temperature change in response to forcing is believed to be independent of the type of forcing. Therefore, the surface temperature response to a change in solar forcing should be essentially the same as the response to a change in CO2 levels that gives an equivalent forcing in terms of energy flux at the tropopause (the temperature response at different altitudes and latitudes is, however, dependent on the type of forcing as we'll see later).

What that means is that, if climate sensitivity is low to CO2, then it will be low to solar changes as well. Since the satellite era, solar forcing changes are measurable and known to be very small. That is why changes in the Sun cannot explain changes in Earth's surface temperature over at least the past few decades.

ΔT κ is the response of T S to radiative forcings ignoring temperature feedbacks [...] b is the sum in Wm-2K-1 of all individual temperature feedbacks [..] κ = ΔT λ /(ΔF 2x + b ΔT λ ) KW-1m2 (6) [...] ΔT κ , [...] is the change in surface temperature in response to a tropopausal forcing ΔF 2x , ignoring any feedbacks.

Confused: it is helpful to quote the definition of Bony et al (Journal of Climate 19:3445 (2006)), appendix A, to get a fuller understanding of what "no feedbacks" means. In particular, it is a physical quantity defined by the atmospheric temperature profile and radiative properties, and has no dependence on the feedbacks (b):

The most fundamental feedback in the climate system is the temperature dependence of LW emission through the Stefan-Boltzmann law of blackbody emission (Planck response). For this reason, the surface temperature response of the climate system is often compared to the response that would be obtained [...] if the temperature was the only variable to respond to the radiative forcing, and if the temperature change was horizontally and vertically uniform [...]

IPCC AR4 WG1 (ch. 8 as noted by Monckton) similar defines it as the "uniform temperature radiative cooling response". I.e. "No feedbacks" in Monckton's (and common climatological) terms means this bare "Planck response" of the atmosphere where the temperature at every altitude and around the globe is increased in a uniform fashion, while the other physical properties (density and molecular constituents, etc.) are held constant, to bring about a return to radiative equilibrium under conditions of a forced energy flux at the tropopause. This is a well-defined physical quantity that is simply computed from radiative properties under typical atmospheric conditions (as is the forcing term above).

What Monckton has done with his equation (6) is find a way to calculate something he states is unobservable (κ) from an observable temperature change (delta T λ , which nevertheless he claims is "subject to great uncertainty"), combined with two other unobservable numbers (forcing change, and the feedback parameter b). Aside from any difficulties in measuring temperatures, Monckton's feedback parameter b is also not known to any great degree of accuracy. The simpler straightforward definition in (5) defines κ in terms of two purely theoretical numbers which are well-defined for given atmospheric conditions.

ΔT κ , estimated by Hansen (1984) and IPCC (2007) as 1.2-1.3 K at CO2 doubling

Monckton: A "temperature feedback" is a change in T S that occurs precisely because T S has already changed in response to a forcing or combination of forcings.

Confused: While for the most part Monckton's use and examples of feedback here are correct and quite coherent, this definition incorrectly implies a time-dependence via the word "already". Bony's definition is the clearest I have read, although it is given mathematically by partial differential relationships (see discussion around equation A3 of the article refered to above - E40). The basic issue is that the full response is defined by a return to radiative equilibrium, and some of the things responding (water vapor for instance) have dependencies on others (temperature change over water). To get to radiative equilibrium, all the feedbacks (including the "Planck" or uniform-temperature one) work simultaneously, it is not as if one goes first, and then another.

However, there is a time-scale issue in defining what is included among the "feedbacks" and what is considered "forcing". For the WMO definition of climate at 30 years, and in IPCC terminology, long-term feedbacks that may change CO2, methane, and other long-lived greenhouse gas levels are not included, and the levels of these gases are assumed to be controlled (forced). On much longer time-scales (paleoclimate studies) where tens of thousands of years are considered, the levels of these long-lived greenhouse gases are themselves a feedback to other forcings. Needless to say, this is a frequent source of confusion, and likely explains Monckton's attempt to include CO2 feedback later on.

Monckton: IPCC (2007: ch.8) defines f in terms of a form of the feedback-amplification function for electronic circuits given in Bode (1945)

Confused: IPCC never mentions Bode, not in chapter 8 or in any other chapter I examined. The partial differential equations described by Bony et al (Appendix A) force you to the same mathematical structure upon linearization as for Bode's, but there is no underlying assumption here of some sort of mapping from one system to the other. Bony's paper does mention Bode at the start of Appendix A:

Bony et al: The concept of feedback, which has long been used in electronics to characterize the behavior of a perturbed system (Bode 1945), is also used in climatology to characterize the response of the climate system to an external radiative forcing (Hansen et al. 1984).

Monckton: f = (1 - b κ)-1 (8) [...] f = (1 - b κ)-1 [...] (9) [...] ΔF κ (1 - κ b)-1 = ΔF κ f [...] (10) [...] Figure 3 - Bode (1945) feedback amplification schematic [...] [...] the base or "no-feedbacks" climate sensitivity parameter κ is successively amplified round the feedback-loop by feedbacks summing to b.

Nonsense: Actually, I don't know what to make of this. Perhaps argument by verbosity is what's being attempted. Monckton appears to be going around in circles with his math. Most charitably I think he is trying to relate one IPCC statement to another, or one of the ones from Bony, with the Bode approach, but he certainly doesn't explain what he's trying to do here. Other than repeatedly, in at least four different ways, to show that the feedback parameter f is equal to the inverse of 1 minus b times κ. Yes, we got that, you didn't need 13 lines of elementary algebra to prove it.

To these we add the CO 2 feedback, which IPCC (2007, ch. 7) separately expresses not as Wm-2K-1 but as concentration increase per CO 2 doubling: [25, 225] ppmv, central estimate q = 87 ppmv.

Confused and Wrong: IPCC does not express the carbon cycle feedback as concentration increase per CO 2 doubling (as that would make no sense on its face, also see the above discussion (E37) on definition of sensitivity) - the relevant discussion is in section 7.3.5.2 "Coupled Climate-Carbon Cycle Projections", p. 533 and following of the IPCC AR4 WG1 report. See table 7.4 and the discussion below it, on p. 535. In particular, where Monckton's numbers appear to come from is the statement "This translates into an additional CO2 concentration of between 20 and 224 ppm by 2100, with a mean of 87 ppm (Table 7.4)."

In other words, the IPCC discussion on CO2 feedback was about CO2 levels by the year 2100, not CO2 levels when CO2 concentrations are doubled (that is obviously a fixed number!) More importantly, anthropogenic CO2 causes both this positive feedback due to temperature, but also strong negative feedbacks from absorption by land and ocean as CO2 levels increase, as table 7.4 demonstrates in detail. The net effects of emitting enough CO2 to add 280 ppm to the atmosphere can be calculated from the table: land and ocean sinks would absorb 700 +- 224 GtC due to the increase in CO2 levels directly, while (with transient sensitivity 2.1 degrees) releasing 229 +- 60 GtC due to the temperature rise. Both effects would work together with anthropogenic emissions to reach the doubled atmospheric CO2 level used by models to estimate sensitivity.

However, Monckton is correct that this CO2 feedback should be included when discussing (at least longer-term) climate response to other forcings such as changes in solar irradiance. But it is simply wrong to add it in, as he does in his eq. 12, to the sensitivity-relevant feedback parameter 'b', which he then uses to estimate "Final climate sensitivity" in the next section. The corrected equation 12 would gives b roughly 1.9 Wm-2K-1, and equation 13 then gives feedback factor f of about 2.5. Monckton's seemingly small addition of the CO2 feedback gives a 25% error in his calculation of this number.

Thus, at CO2 doubling, -



ΔT λ = ΔF 2x κ f = 3.405 x 0.313 x 3.077 = 3.28 K (14)



IPCC (2007) gives dT λ on [2.0, 4.5] K at CO2 doubling, central estimate dT λ = 3.26 K, demonstrating that the IPCC's method has been faithfully replicated. There is a further checksum,



ΔT κ = ΔT λ / f = κ ΔF 2x = 0.313 x 3.405 = 1.1 K, (15)



sufficiently close to the IPCC's estimate ΔT κ = 1.2 K, based on Hansen (1984), who had estimated a range 1.2-1.3 K based on his then estimate that the radiative forcing ΔF 2xCO2 arising from a CO2 doubling would amount to 4.8 Wm-2, whereas the IPCC's current estimate is ΔF 2xCO2 = 3.71 Wm-2 (see Eqn. 2), requiring a commensurate reduction in ΔT κ that the IPCC has not made.

A final checksum is provided by Eqn. (5), giving a value identical to that of the IPCC at Eqn (7):



κ = ΔT λ / (ΔF 2x + b ΔT λ ) = 3.28 / (3.405 + 2.16 x 3.28) = 0.313 KW-1m2. (16)

Wrong, Confused, Inconsistent and Invalid: Let's start by correcting Monckton's 3 equations here for the actual values, rather than his misestimations above. Kappa of course we are in agreement on, at (3.2)-1. ΔF 2x , the forcing at CO2 doubling, should be 3.7 Wm-2, not 3.405. f should be 2.5 rather than 3.077, and the value of b should be 1.9 rather than 2.16. That gives us corrected versions as follows:



ΔT λ = ΔF 2x κ f = 3.7 x 2.5/3.2 = 2.9 K (14)



ΔT κ = ΔT λ / f = κ ΔF 2x = 3.7/3.2 = 1.2 K (15)



κ = ΔT λ / (ΔF 2x + b ΔT λ ) = 2.9/(3.7 + 1.9*2.9) = 0.31 (16)



Note in particular that Monckton's "final checksum" (16) works just as well for the correct numbers as for his wrong ones - it's an algebraic tautology. Completely invalid as a verification for anything other than that he punched numbers into his calculator correctly. Let's examine both of the other numbers, and Monckton's claims for getting them right.

First, Monckton makes much of the fact that his result, 3.28 K, is close to the "central estimate" of the IPCC's range from 2.0 to 4.5 K. However, IPCC not only published a range, but a "best estimate", which was 3.0 K, not 3.26. The reason the "best estimate" is distinct from the center of the range is primarily because the largest uncertainties are in the feedback parameter, Monckton's 'b', which has that inverse relationship to sensitivity. If 'b' is larger than its central estimate, that disproportionately pushes the sensitivity to larger numbers; if 'b' is smaller, that has a lesser effect on sensitivity. So using the central estimate for the feedback parameter 'b', as Monckton has done here, ought to produce a sensitivity value that is lower than the central estimate for the sensitivity, because of this inverse relationship. Monckton's result is, despite the superficial resemblence, significantly inconsistent with the IPCC numbers. Using the correct numbers gives a consistent result (to within the 2-digit accuracy of the numbers presented).

On the equation (15) number for no-feedback (Planck) response; obviously Monckton's number is 10% too low because he has used the wrong value for the forcing from doubled CO2. Note also that this is the same issue mentioned above (E41) that gives an inconsistent estimate for κ relative to those found in Monckton's table 2. In any case, using the correct value for forcing gives exactly the right number for no-feedback response. Monckton then claims that IPCC's estimate of this 1.2 K is based in some way on Hansen's early calculations, rather than the more recent work he himself cited (Bony et al, see E40) - there is absolutely no need for a "commensurate reduction" in estimates of the no-feedback response, it stands on its own. He also misquotes Hansen's estimate of forcing from the 1984 paper, which treated two different situations: doubled CO2, and a 2% increase in solar irradiance. From p. 135 of Hansen's article, we find:

The 2% S 0 change corresponds to a forcing of 4.8 Wm-2. The initial radiative imbalance at the top of the atmosphere due to doubling CO2 is only ~2.5 Wm-2, but after CO2 cools the stratosphere (within a few months) the global mean radiative forcing is about 4 Wm-2 (Fig. 4, Hansen et al. 1981).

Note also Monckton is again being strangely inconsistent by here quoting IPCC's current estimate for ΔF 2xCO2 of 3.71 Wm-2, while in equations 14-16 using his own value of 3.405. Why?

None of these three factors is directly mensurable. For this and other reasons, it is not possible to obtain climate sensitivity numerically using general-circulation models: for, as Akasofu (2008) has pointed out, climate sensitivity must be an input to any such model, not an output from it.

Inconsistent and Nonsense: Monckton is correct that neither the forcing, the no-feedback response, or the feedback factor are directly measurable from observations. But each of them is determined by physical constraints on the system. Both forcing and the no-feedback response are determined by the spectroscopic properties of atmospheric constituents and the distribution of temperature profiles through the atmosphere. Each component of the feedback terms is given by its own physical properties in the context of Earth's surface and atmosphere. For example the water vapor feedback is strongly governed by the temperature dependence of the saturation pressure for water, and the impact of increased evaporation on latent heat transport is determined by the value of water vapor's latent heat. Since the purpose of a numerical model of the system such as one of the General Circulation Models (GCM's) is to use these underlying physical properties to analyze the whole system, each of the terms individually and the sensitivity as a whole are straightforward to calculate from the detailed model results. Monckton even quoted the results of these GCM's on feedback values just a few paragraphs before, from the IPCC quote stating "In AOGCMs, the water vapor feedback ...".

The "draft" paper that Monckton refers to to support the astonishing claim that "climate sensitivity must be an input" to the GCM's is by a Dr. Akasofu and can be downloaded here. Despite the many obvious flaws in this paper, which has not been subjected to any peer review, I could not find any claim in it that even supported Monckton's statement that sensitivity must be an input to GCMs. Akasofu appears not to discuss sensitivity or feedbacks at all, rather the discussion relating to GCMs concerns the regional distribution of temperature changes.

To reiterate - sensitivity is in no way an input to the GCM's, it is one of their primary output values, and all three terms under discussion here can be readily calculated from the properties that the climate models keep track of in their simulations. In fact, Monckton himself used the outputs of climate models in discussing feedback earlier in this article.

We cannot even measure changes in T S to within a factor of two (McKitrick, 2007).

Confused: See above (E28) on McKitrick - Monckton has mis-stated McKitrick and Michaels' dubious urban heat-island claims as if they put both land and ocean temperatures in doubt.

The models draw upon results of laboratory experiments in passing sunlight through chambers in which atmospheric constituents are artificially varied; such experiments are, however, of limited value when translated into the real atmosphere, where radiative transfers and non-radiative transports (convection and evaporation up, advection along, subsidence and precipitation down), as well as altitudinal and latitudinal asymmetries, greatly complicate the picture.

Wrong, Red Herring, Confused: The start of this sentence appears to be a reference to spectroscopic measurements, though the phrasing significantly downplays the unparalleled experimental precision that has been routine in spectroscopy for many decades. The "models" in fact draw upon large databases of the spectroscopic parameters of atmospheric constituents to understand their effects on thermal radiation. One of the most frequently used is the HITRAN database from Harvard-Smithsonian, which contains details on close to 2 million spectral lines for 37 different molecules. A summarized version of this detailed spectroscopic data is used in the "moderate resolution" ModTran program, which calculates radiative forcings based on specific atmospheric profiles and can be run online here. Modern climate models may use either the HITRAN data (line by line calculation) or a simpler version as ModTran does.

In particular, there is no question that these spectroscopic details and calculations used by the models very accurately portray the behavior of thermal radiation as it passes through the atmosphere, and satellite and air-borne measurements confirm that they indeed apply to the "real atmosphere". Monckton's list of non-radiative terms - "convection", "evaporation", "advection", "subsidence", "precipitation" - is completely irrelevant to radiative transport and forcing: those factors certainly play a role in determining the temperature profiles of the atmosphere at different "latitudes" and "altitudes", but those temperature profiles are input to the radiative calculation. Remember, the definition of forcing is the effect on the balance of energy flux at the tropopause when the term at issue (here CO2 concentration) changes, all else being held constant.

In short, the forcing from CO2 or other greenhouse gases is determined by taking the current profile of temperatures, pressures and constituent concentrations throughout the atmosphere, averaged over suitable climatic time periods, along with averages of cloud cover and similar factors, and applying these well-known detailed spectroscopic databases. The uncertainties (at about the 10% level) come from uncertainty in measuring those atmospheric temperature profiles and similar factors, not from the inapplicability of the spectroscopic data, nor from any influence of "convection" or other non-radiative factors.

Using these laboratory values, the models attempt to produce latitude-versus-altitude plots to display the characteristic signature of each type of forcing.

Confused, Cherry Picking: there is a vast quantity of information that can be gleaned from the models, both statistical (means and distributions), and more detailed (regional changes in temperature, precipitation, etc.). Much of the IPCC AR4 WG1 content (chapters 8 through 11) is devoted to what models can tell us about the climate response to changes in various forcings. The earlier chapters of the WG1 report discuss what observations tell us about changes thus far, and some of the later sections compare models with observations in some detail. This "latitude vs altitude" plot is but one of hundreds of indicators of change that can be compared between models and observations. This particular comparison is discussed in section 9.2.2.1 (p. 674-676), "Spatial and Temporal Patterns of Response" in the WG1 report.

The signature or fingerprint of anthropogenic greenhouse-gas forcing, as predicted by the models on which the IPCC relies, is distinct from that of any other forcing, in that the models project that the rate of change in temperature in the tropical mid-troposphere - the region some 6-10 km above the surface - will be twice or thrice the rate of change at the surface

Wrong and Red Herring: Monckton's Figure 4 is a relabeled copy of the IPCC's Figure 9.1 (p. 675) and as he himself notes in his caption to the figure, it is the modeled response to the actual forcings believed to be relevant for the period 1890 to 1999. Since the forcing from well-mixed greenhouse gases during this period (the third image) is many times larger than any other forcing, it will of course show the strongest response. Nevertheless, the fact is, all the images show an enhancement in warming or cooling in the mid-troposphere region in response. This is hard to see in Monckton's reproduction of the images where some of the color contours are washed out, but in the original IPCC figure 9.1, the small solar forcing shows a stronger response in the tropical mid troposphere; the ozone forcing also shows patches of additional warming in the mid troposphere, and the direct aerosol forcing shows enhanced cooling in the same place, the tropical mid troposphere. In particular, the contours in the original figure 9.1 for the solar forcing show a warming of 0 to 0.2 K at the surface and 0.2 to 0.4 K in the tropical mid-troposphere, an amplification perfectly compatible with the 2 to 3 factor Monckton claims is unique to greenhouse gas forcing. When the solar forcing is scaled to the same value as the greenhouse gas forcing, the tropical mid-troposphere region looks almost identical, as can be seen for example in the images shown in this RealClimate discussion of the mid-troposphere predictions.

So, far from being a unique signature of greenhouse gas forcing, an enhanced response in the tropical mid troposphere is a characteristic of all of the forcings. It is in fact a consequence of the change in the adiabatic lapse rate (the decline in temperatures with altitude) expected for an atmosphere with higher water vapor levels. The more water vapor, on average, the slower the rate of temperature decrease as you rise through the atmosphere, on very general basic physical principles. Therefore, if the surface temperature rises and the lapse rate declines, the temperature for some distance above the surface will rise faster than at the surface. The exact same mechanism arises whatever the cause of the surface warming. The comparison of this basic theoretical prediction with observations is made in section 9.4.4.4 "Differential Temperature Trends" in the IPCC report; more on this below (E53).

However, there is a unique signature for one of the forcings - not greenhouse gases, but solar forcing. As the text of section 9.2.2.1 states: "Solar forcing results in a general warming of the atmosphere with a pattern of surface warming that is similar to that expected from greenhouse gas warming, but in contrast to the response to greenhouse warming, the simulated solar-forced warming extends throughout the atmosphere." You can see this signature in the images of figure 9.1 and perhaps more clearly in the RealClimate images linked just above. For solar forcing, the warming is everywhere from surface to stratosphere. For all the others, whatever the surface does, the stratosphere (above about 20 km) does the opposite. In particular, the greater emissivity associated with increased greenhouse gas concentrations directly causes a cooling of the stratosphere, even before any warming seen at lower altitudes. The observation of stratospheric cooling is strong proof that the sun cannot be responsible for recent changes in global surface temperatures.

The fingerprint of anthropogenic greenhouse-gas forcing is a distinctive "hot-spot" in the tropical mid-troposphere. Figure 4 shows altitude-vs.-latitude plots from four of the IPCC's models: [...] - Figure 5 - Fingerprints of anthropogenic warming projected by four models All show the projected fingerprint of anthropogenic greenhouse-gas warming: the tropical mid-troposphere "hot-spot" is projected to warm at twice or even thrice the surface rate.

Wrong, Confused and Red Herring: Aside from getting his own figure number wrong, see the commentary above (E51) on why Monckton has completely confused the nature of the "fingerprint" shown in these images. All four images do clearly show the true fingerprint: cooling of the stratosphere. Warming of the tropical mid-troposphere is, as discussed above, due to changes in the lapse rate predicted from an increase in water vapor levels in a warmer world. It is unrelated to the cause of the warming and is in no way a "fingerprint" of any one of them, so this is a complete red herring.

the projected fingerprint of anthropogenic greenhouse-gas warming in the tropical mid-troposphere is not observed in reality. [...] In the tropical mid-troposphere, at approximately 300 hPa pressure, the model-projected fingerprint of anthropogenic greenhouse warming is absent from this and all other observed records of temperature changes in the satellite and radiosonde eras: - Figure 6 - The absent fingerprint of anthropogenic greenhouse warming - [...] The greater rate of warming in the tropical mid-troposphere that is projected by general-circulation models is absent in this and all other observational datasets, whether satellite or radiosonde.

Wrong, Nonsense and Inconsistent: Monckton repeats his unfounded assertion that enhanced warming of the tropical mid-troposphere is a "fingerprint" of greenhouse warming half a dozen times here and in the previous few paragraphs, indicating the centrality of this false notion to his whole argument in this section.

On the actual observations, first note that they do demonstrate the actual fingerprint of greenhouse (non-solar) warming: cooling of the stratosphere while the surface and lower atmospheric layers warm. So we can be quite certain just from these observations that the sun is not responsible for recent warming of the Earth.

Second, note that the time period for these observations is much shorter than in the graphs of projections (figure 4 and 5): Figure 4 referred to the forcings over about 100 years, from 1890 to 1999. Figure 5 looked at the modeled responses to a doubling of CO2, roughly 300 years from from 1780. Figure 6, in contrast, refers to observational data from "the satellite era", the late 1970s to the present, or at most 30 years. As discussed in E2, 30 years of averaging is barely long enough to define climate, and for detailed features such as these altitude vs latitude averages, one would still expect significant noise. Error bars and uncertainties for these radiosonde and satellite observations are discussed extensively in the IPCC reports - see section 9.4.4 and section 3.4.1 ("Temperature of the Upper Air: Troposphere and Stratosphere") of IPCC AR4 WG1:

Within the community that constructs and actively analyses satellite- and radiosonde-based temperature records there is agreement that the uncertainties about long-term change are substantial. Changes in instrumentation and protocols pervade both sonde and satellite records, obfuscating the modest long-term trends. Historically there is no reference network to anchor the record and establish the uncertainties arising from these changes - many of which are both barely documented and poorly understood. Therefore, investigators have to make seemingly reasonable choices of how to handle these sometimes known but often unknown influences. It is difficult to make quantitatively defensible judgments as to which, if any, of the multiple, independently derived estimates is closer to the true climate evolution. This reflects almost entirely upon the inadequacies of the historical observing network and points to the need for future network design that provides the reference sonde-based ground truth. Karl et al. (2006) provide a comprehensive review of this issue.

The radiosonde record extends back much further than the satellite one (starting in the 1940s) but there is much uncertainty about long-term calibration, for instance (sec 3.4.1.1, p. 266):

Sherwood et al. (2005) found substantial changes in the diurnal cycle in unadjusted radiosonde data. These changes are probably a consequence of improved sensors and radiation error adjustments. Relative to nighttime values, they found a daytime warming of sonde temperatures prior to 1971 that is likely to be spurious and then a spurious daytime cooling from 1979 to 1997. They estimated that there was probably a spurious overall downward trend in sonde temperature records during the satellite era (since 1978) throughout the atmosphere of order 0.1 C per decade globally. The assessed spurious cooling is greatest in the tropics (0.16 C per decade for the 850 to 300 hPa layer) and least in the NH extratropics (0.04 C per decade). Randel and Wu (2006) used collocated MSU data to show that cooling biases remain in some of the LKS and RATPAC radiosonde data for the tropical stratosphere and upper troposphere due to changes in instruments and radiation correction adjustments. They also identified problems in night data as well as day, indicating that negative biases are not limited to daytime observations. However, a few stations may have positive biases (Christy and Spencer, 2005). The radiosonde data set is limited to land areas, and coverage is poor over the tropics and SH. Accordingly, when global estimates based solely on radiosondes are presented, there are considerable uncertainties (Hurrell et al., 2000; Agudelo and Curry, 2004) and denser networks - which perforce still omit oceanic areas - may not yield more reliable 'global' trends (Free and Seidel, 2005).

Section 9.4.4.4 (p. 701 of IPCC AR4 WG1) discusses the central issue of the apparently missing warming in the tropical mid-troposphere in some more detail:

Since 1979, globally averaged modelled trends in tropospheric lapse rates are consistent with those observed. However, this is not the case in the tropics, where most models have more warming aloft than at the surface while most observational estimates show more warming at the surface than in the troposphere (Karl et al., 2006). Karl et al. (2006) carried out a systematic review of this issue. There is greater consistency between simulated and observed differential warming in the tropics in some satellite measurements of tropospheric temperature change, particularly when the effect of the cooling stratosphere on tropospheric retrievals is taken into account (Karl et al., 2006). External forcing other than greenhouse gas changes can also help to reconcile some of the differential warming, since both volcanic eruptions and stratospheric ozone depletion are expected to have cooled the troposphere more than the surface over the last several decades (Santer et al., 2000, 2001; IPCC, 2001; Free and Angell, 2002; Karl et al., 2006). There are, however, uncertainties in quantifying the differential cooling caused by these forcings, both in models and observations, arising from uncertainties in the forcings and model response to the forcings. [...] A systematic intercomparison between radiosonde-based (Radiosonde Atmospheric Temperature Products for Assessing Climate (RATPAC); Free et al., 2005, and Hadley Centre Atmospheric Temperature (HadAT), Thorne et al., 2005) and satellite-based (RSS, UAH) observational estimates of tropical lapse rate trends with those simulated by 19 MMD models shows that on monthly and annual time scales, variations in temperature at the surface are amplified aloft in both models and observations by consistent amounts (Santer et al., 2005; Karl et al., 2006). It is only on longer time scales that disagreement between modelled and observed lapse rates arises (Hegerl and Wallace, 2002), that is, on the time scales over which discrepancies would arise from inhomogeneities in the observational record. Only one observational data set (RSS) was found to be consistent with the models on both short and long time scales. While Vinnikov et al. (2006) have not produced a lower-tropospheric retrieval, their estimate of the T2 temperature trend (Figure 3.18) is consistent with model simulations (Karl et al., 2006). One possibility is that amplification effects are controlled by different physical mechanisms on short and long time scales, although a more probable explanation is that some observational records are contaminated by errors that affect their long-term trends (Section 3.4.1; Karl et al., 2006).

This is clearly a scientific question with considerable uncertainty in its resolution at the time of the writing of the latest IPCC report in early 2007 (and for the most part papers had to be published well before the report came out to be fully considered). There have been several more recent papers on the topic, both re-evaluating the calibrations of the different data sets and looking additionally at wind shear numbers from the radiosonde measurements to get better long-term temperature reliability. This is discussed in considerable detail in this RealClimate article on the subject, and there is good reason to believe that the observations, not the models, need to be corrected to reach agreement on this.

In fact, Monckton refers directly to one of these new papers, "Allen et al (2008)" in subsequent paragraphs which illustrate why the observations are certainly not clearly definitive on this (red herring) issue at this point.

One final note here - Monckton is relying on satellite measurements of the temperatures of layers of the atmosphere. This can only be done through measurements of thermal emissions observed at satellite altitudes, and comparing that in detail to the "results of laboratory experiments in passing sunlight through chambers" - the spectroscopic characteristics of the emitting species in the atmosphere (molecular oxygen lines near 60 GHz are typically used). Translating the observed spectra into an averaged atmospheric temperature profile is a tricky business, but Monckton expresses no doubt in its validity. So how can one possibly explain, except through willful ignorance, his doubts about applying essentially the same theoretical analysis to calculation of the forcing from greenhouse gases in the first place?

There are two principal reasons why the models appear to be misrepresenting the tropical atmosphere so starkly.

Nonsense: the models aren't, see above (E53).

the concentration of water vapor in the tropical lower troposphere is already so great that there is little scope for additional greenhouse-gas forcing

Wrong, Confused, and Inconsistent: the limit on water vapor concentration is determined by the Clausius-Clapeyron relation under which the saturation vapor pressure increases roughly exponentially with temperature. Monckton himself points this out later in this very article, in the discussion on non-linearity: "The increase in water-vapor concentration as the space occupied by the atmosphere warms is near-exponential". So there is plenty of scope for more water vapor as the surface (and near-surface atmosphere) warms.

As to the effect of this increase in water vapor on greenhouse-gas forcing, changes in the water vapor component of the greenhouse effect are never considered as a part of the forcing, rather they are part of the feedback response. Additional water vapor in the atmosphere most certainly does have an effect on the radiative properties of the atmosphere; the water vapor component of the atmosphere is an important part of the total greenhouse effect, and changes in water vapor are the most important part of the feedback process.

But more than this, the "hot spot" from the models is, as discussed above (E53), caused by changes in the "lapse rate", the temperature decrease with altitude that balances the pressure reduction with height due to gravity. The higher the water vapor content of the atmosphere, the lower the lapse rate. This has absolutely nothing to do with radiative forcing or the greenhouse properties of water vapor. Monckton continues to completely misrepresent the basic questions here.

Secondly, though the models assume that the concentration of water vapor will increase in the tropical mid-troposphere as the space occupied by the atmosphere warms, advection transports much of the additional water vapor poleward from the tropics at that altitude.

Invalid: There is no reason changes in advection in a warmer world would somehow transport the "additional water vapor" only (or mostly). In any case, this would be an issue for estimation of feedbacks, not radiative forcing, the supposed topic of this entire section.

the great majority of the incoming solar radiation incident upon the Earth strikes the tropics

Wrong and Red Herring: The tropics are usually defined in climate discussions as from 20 degrees S to 20 degrees N. The fraction of incoming sunlight striking that part of the globe at the top of the atmosphere is about 43%, less than half. Even using the full tropical range of 23.4 degrees N and S gives only about 49%. Hardly the "great majority".

Moreover, the relevant factor for radiative forcing (supposedly the topic of this section of the article) is the outgoing thermal flux, not incoming solar, and that comes simultaneously from all parts of the globe, day and night. You need to expand the definition of tropics to 30 degrees S to 30 degrees N (as is sometimes done) to include half of Earth's surface area; 20 S to 20 N is just 34%.

any reduction in tropical radiative forcing has a disproportionate effect on mean global forcings. On the basis of Lindzen (2007), the anthropogenic-ear radiative forcing as established in Eqn. (3) are divided by 3 to take account of the observed failure of the tropical mid-troposphere to warm as projected by the models

Invalid and Nonsense: Lindzen's claim (hardly supported by much evidence, given the above discussion (E53) on the tropical troposphere observations) is concerned with the feedback effect of water vapor levels in the tropical atmosphere, and has nothing to do with the radiative forcing calculated for greenhouse gases. So the factor of three applied here might be more correctly applied to the feedback factor discussed later - it clearly has absolutely nothing to do with the value of the greenhouse gas forcing number ΔF 2x that Monckton attributes it to here.

Even if this factor of 3 is real it cannot be applied to the entire globe - it applies only to the tropics. As noted above (E53), the models and observations agree well outside the tropics. Monckton is claiming the unlikely factor of 3 reduction in tropical water vapor feedback can be applied globally based on the preceding erroneous claim about the "great majority" of incoming solar radiation. One would have to slice this reduction at least in half since the "great majority" is itself less than half. In the end, if the models are wrong about the tropical troposphere by overestimating water vapor levels as Monckton is arguing here, the final effect on the water vapor feedback term would be on the order of a 30% reduction, rather than the claimed factor of 3. Such a 30% reduction is well within the existing range of estimates of the water vapor feedback from different climate models anyway - see figure 8.14 in IPCC AR4 WG1 (p. 631).

In any case, Monckton's equation 17 is wrong and of no value; the arguments here have absolutely no bearing on the forcing from greenhouse gases.

The base climate sensitivity parameter ... is the most influential of the three factors

Invalid - the statement is meaningless. What criteria would make one factor more influential than others? Monckton's argument seems to be that the heightened influence comes from the parameter appearing in more than one place in the equations, but what relevance does that have? If all three parameters were unknown to an equal degree, then one could argue that the equations imply a greater variability of the final sensitivity to the variability in this parameter, which may be what Monckton is trying to imply. But the fact is, as we will see below (E72), this no-feedbacks parameter is the most tightly constrained of the three. The forcing is nearly as tightly constrained, while it is in the feedbacks that by far the largest uncertainties, and all the real scientific questions at this time, are present. So whatever the base climate sensitivity parameter's "influence", we know pretty precisely what it is, and any remaining questions about its exact value are inconsequential to the sensitivity compared to the unknown factors in the feedback parameter.

Yet κ has received limited attention in the literature. In IPCC (2001, 2007) it is not mentioned. However, its value may be deduced from hints in the IPCC's reports.

Confused and Invalid: Monckton's κ (the inverse of Bony et al's Planck response noted in E40) is a somewhat artificial construct not particularly relevant for the discussions in the IPCC reports. Climate models don't use anything resembling Monckton's "κ" in working out the full temperature response, they use the actual radiative properties of the atmosphere under the modeled conditions. Nevertheless, the bare uniform temperature response is mentioned in the 2007 (AR4) report, section 8.6.2.3 (p. 631):

In the idealised situation that the climate response to a doubling of atmospheric CO2 consisted of a uniform temperature change only, with no feedbacks operating (but allowing for the enhanced radiative cooling resulting from the temperature increase), the global warming from GCMs would be around 1.2 degrees C (Hansen et al., 1984; Bony et al., 2006).

The program Monckton here embarks on to try to extract his "κ" parameter from statements about other quantities in the IPCC reports and other sources is a pointless exercise in textual archeology (which, unsurprisingly, he completely flubs anyway: see E76 and related entries below). This may be of interest in validating the self-consistency of various statements in the reports, but it is not a scientifically valid way of discovering what value some real physical parameter should have!

Since λ = κ f = κ (1 - b κ)-1 (Eqns. 1, 2), where λ = 0.5 KW-1m2 and b ≈ 2.16 Wm-2 K-1 (Eqn. 12), it is simple to calculate that, in 2001, one of the IPCC's values for f was 2.08.

Invalid: First, see above (E45) - b should be 1.9, not 2.16. Also, this value for the feedbacks comes from the 2007 AR4 IPCC report, so why is Monckton applying it to the 2001 report? Second, the quoted statement from IPCC 2001 puts the value of λ at "about 0.5 KW-1m2", for "one-dimensional radiative-convective models", quoting a 1985 paper, which was the basis for thinking that the surface temperature response would usually be independent of the forcing. The point is that whatever the cause of the change in power delivered to the top of the troposphere (the forcing), whether from solar irradiance changes, aerosols, or greenhouse gases, the temperature response at the surface of the Earth is expected to respond in close to the same way for all. That is the reason this separation into different feedback factors makes sense at all.

This value of 0.5 was not some magically precise value for the response for the 2001 IPCC report. Given the doubling forcing of about 3.7 Wm-2, the IPCC TAR (2001) sensitivity range of 1.5 to 4.5 K gives values of λ in the range 0.4 to 1.2, far from being precisely the 0.5 that Monckton clings to. Monckton's formulas are useless for deriving the feedback parameter f appropriate to this range, because the primary cause of variability in the sensitivity is uncertainty in the value of Monckton's 'b'. For the established value of κ around 0.3, however, this gives values of f in the range from 1.3 to 4, and the corresponding values of b would be in the range about 0.8 to 2.5 Wm-2K-1. For more discussion on some of these issues from the perspective of the 2001 IPCC report (TAR WG1), see for example section 7.2.1.1 on the water vapour feedback, giving an f for water vapour of roughly 2.

Thus the value f = 3.077 in IPCC (2007) represents a near-50% increase in the value of f in only five years

Wrong and Invalid: See above (E45) - the correct value of Monckton's f for the 2007 IPCC report is actually 2.5 (best estimate of feedbacks), not 3.077. Given that AR4 tightened the sensitivity range to 2.0 to 4.5 K from the TAR 1.5 to 4.5 K, a slight increase in the feedback parameter is not unexpected. But even by this odd analysis (based on the dubious claim that 0.5 was the best value for λ in the 2001 report) the increase is about 25%, not 50%.

Where f = 2.08, κ = λ / f ≈ 0.5 / 2.08 ≈ 0.24 KW-1m2, again substantially lower than the value implicit in IPCC (2007).

Invalid: to the single-digit precision implied but probably not even relevant for the "0.5" value, this ratio with f roughly equal to (and slightly below) 2 gives a value of κ approximately equal to 0.3 KW-1m2. Little more can be said - it is certainly within the range of the real κ, as of course it has to be.

The fundamental equation of radiative transfer at the emitting surface of an astronomical body, relating changes in radiant-energy flux to changes in temperature, is the Stefan-Boltzmann equation ... (18)

Confused: First, this stuff doesn't just apply to astronomical bodies. Second, the true fundamental equation for thermal radiation is the product of frequency-dependent emissivity with the Planck black-body spectrum. The Stefan-Boltzmann equation, Monckton's equation 18 (other than the extraneous Wm-2 which should be part of the definition of the Stefan-Boltzmann constant) comes from integrating the Planck spectrum assuming emissivity is independent of frequency. This isn't a bad approximation for Earth's surface which is close to a black body at thermal frequencies, but the spectral dependence of emissivity is critical for understanding radiative transfer in the atmosphere, which this expression obviously ignores.

Note also that Monckton has used the variable name 'F' here for the radiant flux - which is fine, but easily confused with the F used previously for "forcing" at the tropopause. He immediately compounds this with:

κ = dT/dF ... (19)

Confused and inconsistent: this is a new definition of κ - see Monckton's equation 5 for the original, and note that there the delta T in the numerator is surface temperature, while the delta F is the (forcing) change in radiative flux at the tropopause. In Monckton's equation 19 the flux and temperature are associated with the same emitting surface. In other words this κ is not the same as the earlier κ. Why use the same variable name, except to cause confusion?

Monckton himself notes the problem, but blames the IPCC for his confusion about κ in his comment a few paragraphs down which deserves its own out-of-order discussion here:

E66

However, the IPCC, in its evaluation of κ, does not follow the rule that in the Stefan-Boltzmann equation the temperature and radiant-energy flux must be taken at the same level of the atmosphere. The IPCC's value for κ is dependent upon temperature at the surface and radiant-energy flux at the tropopause

Nonsense and Inconsistent: Monckton previously asserted that the IPCC made no mention of his "κ" - yet now he blames them for "not following the rule". It is Monckton who has provided two inconsistent definitions of κ here, not the IPCC. No wonder Monckton's numbers on this don't make any sense.

λ max = 2897 / T S = 2897 / 288 ≈ 10 micron. (20)

Inconsistent: this should also be labeled "sloppy" - he's missing units on the "2897" (should be x 10^-6 m K). More importantly, the Wien law comes from differentiating the Planck spectrum, while he is otherwise consistently ignoring the issue of spectral dependence here.

the Earth/troposphere system is a blackbody with respect to the infrared radiation

Wrong: Uh, no it isn't. That's sort of the whole point of the influence of greenhouse gases on radiative transfer. If Earth was a black body this would be much simpler. Earth's surface (not including any atmosphere) isn't far from a black body (though it doesn't ever carry a single uniform temperature, another issue for this), but Monckton specifically includes the troposphere here. Wrong.

At the Earth's surface, T S ≈ 288 K, so that κ S ≈ 0.185 KW-1m2. At the characteristic-emission level, Z C , the variable altitude at which incoming and outgoing radiative fluxes balance, T C ≈ 254 K, so that κ C ≈ 0.269 KW-1m2.

Red Herring and Confused: at least Monckton implicitly acknowledges through the subscript labels "C" and "S" that these κ's are not the same as the κ associated with climate sensitivity. The one associated with climate sensitivity is in particular defined by flux at the tropopause. Since by definition the temperature change in this bare "Planck" response is assumed to be uniform, the response change in temperature delta T S at the surface would be the same temperature change at the tropopause. Therefore, to the extent it has any validity for this purpose, one could use the Stefan-Boltzmann approach Monckton has outlined here provided the temperature used is the one that follows the "rule" he lays out: "the temperature and radiant-energy flux must be taken at the same level of the atmosphere". I.e. the relevant temperature is not at the surface, nor at the "characteristic-emission" level, whatever that's supposed to be, but at the tropopause, because that's the altitude at which radiative forcing is defined.

Now, the average temperature of the tropopause is quite a bit lower than either of the two temperatures Monckton cites, at roughly 220 K. Plugging that into Monckton's equation 21 we find a value for κ at the tropopause of about 0.41 KW-1m2. Of course the black-body assumption that went into equation 21 is wrong as noted above (E68); the actual value for κ is lower thanks to the frequency dependence of emissivity and the atmospheric layering and temperature and pressure variations with altitude that contribute to the outgoing thermal radiation spectrum.

Hansen says dF 2x is equivalent to a 2% increase in incoming total solar irradiance (TSI). [...] Thus a 2% increase in F C is equivalent to 4.72 Wm-2, rounded up by Hansen to 4.8 Wm-2, implying that κ ≈ 1.25 / 4.8 ≈ 0.260 KW-1m2. However, Hansen, in his Eqn. {14}, prefers 0.29 Wm-2.

Invalid and Confused: See above (E46) - in 1984 Hansen cites a radiative forcing of about 4 Wm-2, not 4.8. This is about 1.7% of net TSI, or when rounded to one significant figure, about 2%. The 1984 paper also does not claim that the two forcings studied are "equivalent", rather that they have "similar magnitudes". Once again Monckton is using low-precision numbers to try to derive high-precision consequences, a completely invalid process. For a forcing of 4 Wm-2 we naturally find κ close to 0.31 KW-1m2 (between 0.30 and 0.325 given the 1.2-1.3 K range Hansen estimated for the bare response), as it must be.

Bony takes T C ≈ 255 K and F C ≈ 235 Wm-2 at Z C as the theoretical basis for the stated prima facie value κ-1 ≈ T C / 4F C ≈ 3.8 Wm-2K-1, so that κ ≈ 0.263 KW-1m2, in very close agreement with Hansen. However, Bony cites two further papers, Colman (2003) and Soden&Held (2006), as justification for the value κ-1 ≈ 3.2 Wm-2K-1, so that κ ≈ 0.313 KW-1m2.

Wrong and Confused: the zero-dimensional uniform-temperature atmosphere-free Earth represented by Monckton's "C" subscripts is a common reference frame for climate parameters - it is of course the basis for claims of 33 K of warming from the greenhouse effect as a whole. Bony's use of it is only as a plausibility argument for the rough order of magnitude that this κ value should have, it is clearly not a coherent scientific derivation of what the parameter should be for the real Earth - Bony's paper describes specifically how it is calculated, and as it was calculated long ago. There is no claim here by Bony that the value of the inverse of κ should be 3.8, the paper very specifically cites the agreed value of 3.2.

Also, Monckton claims this atmosphere-free Earth number (0.263 from inverting Bony's 3.8) is "in very close agreement with Hansen" by which he can only mean Monckton's erroneous derivation of 0.260 above (E70); Hansen never states such a value and neither does Bony. The agreement here is only in Monckton's imagination.

Colman (2003) does not state a value for κ, but cites Hansen et al. (1984), rounding up the value κ ≈ 0.260 KW-1m2 to 0.3 KW-1m2 - "The method used assumes a surface temperature increase of 1.2 K with only the CO2 forcing and the 'surface temperature' feedback operating (value originally taken from Hansen et al. 1984)." Soden& Held (2006) likewise do not declare a value for κ. However, we may deduce their implicit central estimate κ ≈ 1 / 4 = 0.250 KW-1m2 from the following passage - "The increase in opacity due to a doubling of CO2 causes [the characteristic emission level Z C ] to rise by ~150 meters. This results in a reduction in the effective temperature of the emission across the tropopause by ~(6.5K/km)(150 m) ≈ 1 K, which converts to 4 Wm-2 using the Stefan-Boltzmann law." Thus the IPCC cites only two papers that cite two others in turn. None of these papers provides any theoretical or empirical justification for a value as high as the κ ≈ 0.313 KW-1m2 chosen by the IPCC.

Wrong and Invalid: This assertion that the sources referenced by Bony et al do not provide detailed evidence for the -3.2 W/Km2 value for the uniform temperature response is simply false. The Soden and Held paper can be downloaded here. Table 1 provides feedback parameters including the "no-feedback" "Planck" response for 14 different coupled ocean-atmosphere models, and Table 2 provides similar numbers from the coupled model intercomparison project (CMIP II). The entire range of the numbers is from -3.13 to -3.28 W/Km2, with a mean of -3.216 and standard deviation of 0.04. See also the discussion of this parameter, referred to as λ 0 , in the paper. In other words, Monckton's "κ" is well known from these calculations to within about 1%, and there is no significant scientific question about what the value should be for Earth's real atmosphere.

Monckton claims to quote a passage from Soden and Held (2006) which does not in fact exist in that article. Wherever he got it from, it sounds like it was a calculation done to get a rough estimation of the forcing due to doubling of CO2, and certainly not intended as a precise calculation of "κ" or the no-feedback response. "Roughly 1 K" and "roughly 4 Wm-2" does not allow you to quote κ to 3 significant figures! And to one significant figure, 0.25 is the same as 0.3 because the uncertainty in the numbers justifies no distinction between them; Colman's "rounding up" under similar circumstances is perfectly appropriate.

Kiehl (1992) gives the following method, where F C is total flux at Z C :

κ S = T S / (4F C ) ≈ 288 / (4 x 236) ≈ 0.305 KW-1m2. (23) Hartmann (1994) echoes Kiehl's method, generalizing it to any level J of an n-level troposphere thus:

κ J = T J / (4F C ) [...] ≈ T J / 944 KW-1m2. (24)

Confused: Neither of these (14+ years old now) are intended as precise calculations of the no-feedbacks response. They merely give a heuristic formulation for that sensitivity based on a re-writing of the derivative of the Stefan-Boltzmann law similar to Monckton's equation 19, but resolving the issue of the distinction between tropopause and surface (or another layer) in a different manner, under the assumption that the effect of greenhouse gases is essentially to give a uniform increase in surface temperature (or temperature of another atmospheric layer) proportional to the radiative forcing, relative to the no-greenhouse-gas case. This is not strictly true, but note that the true effect consists of two components which this heuristic roughly captures - first, the increase in height of the tropopause (mentioned by Monckton a few paragraphs before), and second the uniform increase in temperature under the assumption of no feedbacks. These particular arguments are certainly not why the Bony et al paper or IPCC picked their number for Monckton's "κ", that number came from detailed calculations of the uniform temperature response.

The greatest value, chosen in IPCC (2007), is 30% above the least, chosen in IPCC (2001).

Wrong: First, note that Monckton has ignored several even larger "largest values" that could be derived from similar textual archeology. For example, in the definition of Monckton's equation 5, using the IPCC (2007) no-feedbacks response of 1.2-1.3 K and forcing of 3.7 Wm-2 we get κ values of 0.324 to 0.351! Not to mention the 0.41 value we obtained above (E69) using the actual temperature of the tropopause.

Second, the lowest number in his "table 2" that actually appears in the literature regarding the real Earth (as opposed to imaginary atmosphere-free planets) is Hansen's 0.29 from 1984. Both IPCC 2001 and IPCC 2007 agree that the number is close to 0.3, and Bony's number of 0.31 or so appears to be pretty definitive. As noted above (E72), the range from actual largest to smallest value in model calculations is at most 1/3.13 to 1/3.28, a total range of about 5% with a standard deviation only a little over 1%, nowhere near Monckton's 30%.

because the feedback factor f depends not only upon the feedback-sum b ≈ 2.16 Wm-2K-1 but also upon κ, the 30% increase in κ nearly doubles final climate sensitivity

Nonsense: You would think that a doubling of climate sensitivity from the 2001 to the 2007 IPCC reports due to such a large change in the value of this "κ" would have been noticed before! Clearly the climate models don't care what Monckton's "κ" is... In any case, since the actual range of possible values for κ is at most 5%, and with the correct central value for b of 1.9 Wm-2 K, one gets a range of sensitivity parameters λ for this range of κ values of 0.73 to 0.81 Km2/W, or about 11%, not 100%!

Table 2 - [...] The range of values for κ in the IPCC's assessment reports and in the papers which it cites is substantial. The value of κ implicit in IPCC (2007) is some 30% above that which is implicit in IPCC (2001): consequently, the value of the climate-sensitivity parameter λ is almost doubled.

Invalid and Nonsense: Of the nine "value of κ" entries in this table, only two are explicitly stated in the citations Monckton gives here: the 0.29 of Hansen (1984) and the 0.3 of Colman (2003); the largest two are given in terms of their inverses, while the lowest five values are from one or another of the misinterpretations Monckton himself has made as noted above (E63, E69, E70, E71, E72, etc.). Monckton's use of the word "implicit" indicates how divorced these numbers are from the actual assumptions of the cited works. One example of this is Monckton's use of Bony et al (2006)'s "atmosphere-free Earth" number (0.263 from Monckton's inversion) as if it was ever intended as a realistic estimate for Earth. See the above notes on the other examples, and on the impact of the actual small variation in κ on climate sensitivity. In reality, other than Hansen's 0.29 from 1984, all the cited works actually agree on a value for κ of roughly 0.30 to 0.32, with the model calculations agreeing now with a standard deviation of only about 1%.

Though it is usual to assume a constant temperature lapse-rate, and hence to use the value of κ that obtains at the characteristic-emission level, where inbound and outbound radiative fluxes balance by definition, the IPCC's current value for κ assumes that the lapse-rate increases as temperature rises. Also, the IPCC does not sufficiently allow for latitudinal asymmetry in distribution of the values of κ.

Wrong, Nonsense, and Inconsistent: IPCC, as Monckton has noted before, does not cite any "current value for κ". What he is talking about is Bony's Planck response number, but Bony describes quite explicitly how that is calculated. This is the bare response, it is under the assumption that the only response to forcing is a uniform increase in temperature throughout the atmosphere. That means the lapse rate, the change in temperature with altitude, is unchanged when κ is calculated. There is no assumption that lapse rate increases. In any case, the lapse rate is expected to decrease (causing the tropical mid-troposphere hot-spot discussed at length above - E53!) under warming conditions due to higher water vapor concentrations, once the water vapor response is included. But the water vapor feedback is obviously not included in the no-feedbacks response - lapse rate remains constant.

Monckton talks about a "value for κ" that "obtains" at the "characteristic emission level", and "latitudinal asymmetry in distribution of the values for κ", but again he defined κ explicitly via equation 5 as the ratio of the average surface temperature change, with no feedbacks, to the forcing at the tropopause. This is a single number for the entire planet, not something that depends on either altitude or latitude. Whatever he is talking about here, it is yet another "κ" that has no relation to the actual no-feedbacks climate sensitivity for our planet. Bony's κ (stated as an inverse) meets Monckton's definition from equation 5; whatever he is talking about here clearly does not.

it is possible to calculate κ using Eqn. (6), provided that the temperature change ΔT λ , radiative forcings ΔF 2x , and feedback-sum b over a given period are known.

Invalid and Wrong: First, Monckton is proposing to determine a value that cannot be observed but can be readily calculated (κ) by combining observations (which he in any case asserts are wrong) with two more values that cannot be observed: the radiative forcing (which also can be readily calculated, though Monckton has just asserted again that the number is badly wrong), and the feedback sum, the value of which is very complex to determine theoretically given its dependence on clouds in particular. This is hardly a prescription for finding an accurate value for the no-feedback response!

Second, Monckton refers to "a given period", but the definitions associated with the temperature change ΔT λ in Monckton's equation 6 are relevant to the equilibrium response. The equilibrium response is the change in surface temperature after a very long period of time has passed to allow all the various responses to stabilize. If you are looking at a shorter "given period" of time than the multiple century-scale needed for equilibrium, then the responses will naturally be different - generally smaller. This is known as the transient response. According to IPCC AR4 WG1, the range for the transient sensitivity to doubling is expected to be 1 K and 3.5 K (see section 9.6.2.3), as opposed to the 2 K to 4.5 K sensitivity range at equilibrium. This reduces the central value for the feedback sum b from 1.9 Wm-2K-1 to about 1.3 Wm-2K-1 for transient (decadal-scale) vs. equilibrium (century-scale) response. Monckton acknowledges this assumption with a citation in the follow-on paragraph: "We assume that Chylek (2008) is right to find transient and equilibrium climate sensitivity near-identical" - but this citation is to one paper that, attributing much of the coldness of the most recent glacial maximum to aerosols (dust), determined climate sensitivity to be on the very low end of the IPCC range. This is hardly a review of 