Klotzbach revisited, a reply by John Christy

Recently Jos Hagelaars published a very extensive blog post (on the blog of Bart Verheggen) about a widely discussed paper of Klotzbach et al 2009. The title of the blog post – Klotzbach revisited – is in English, however, the post itself was written in Dutch. As a fellow Dutchman I understand that writing in Dutch is easier than writing in English. However, in this case, the blog post is focussed so much on one single paper, that Jos Hagelaars, in my opinion, should have chosen for an English version, in order to give the authors of the Klotzbach papers the chance to give a reaction. I translated the article with google translator and did some minor editing. I then shared the article with a few of the coauthors. John Christy looked at some of the issues raised by Hagelaars and wrote the following reaction which I publish here as a guest blog.

Guest blog by John Christy

In a blog post entitled “Klotzbach Revisited” Jos Hagelaars updated the results of Klotzbach et al. 2009, 2010, suggesting that the main point of Klotzbach was no longer substantiated. Klotzbach et al.’s main point was that a direct comparison of the relationship of the magnitude of surface temperature trends vs. temperature trends of the troposphere revealed an inconsistency with model projections of the same quantities.  Klotzbach et al. offered suggestions for this result which included the notion that near-surface air temperatures are easily affected by factors unrelated to greenhouse gas increases, which then implies they may be poor proxies for detecting the magnitude of the greenhouse effect which has its main impact in the deep atmosphere.

It appears Hagelaars’ key point is that when the data from Klotzbach et al. are extended beyond 2008 to include data through 2012, the discrepancies, i.e. the observed difference between surface and tropospheric trends relative to what models project, are reduced somewhat.

The reader must understand that there are two issues that have unfortunately been convoluted and misinterpreted on this issue.  The first issue deals specifically with the relationship between a surface temperature trend and the temperature trend of the corresponding tropospheric layer above (roughly surface to 10 km altitude and referred to as LT for “Lower Troposphere”).  The second issue deals with the actual magnitude of the surface and tropospheric trends.  Thus the first issue is a question of the physics of the vertical temperature structure (i.e. internal model processes) and the second issue is a question of trend magnitudes (i.e. rates of warming or climate sensitivity).  The two are, of course, related.

Here is how the confusion often happens.  As shown in many results, the observed tropospheric trend is often near (or slightly below) the magnitude of the surface trend.  Thus, someone may say “the surface and troposphere agree” as if that validates greenhouse warming theory.  However, in model results (i.e. according to theory) the surface and tropospheric trends should NOT agree because in models the troposphere warms faster than the surface.  So, if surface and tropospheric trends agree, then by implication, model output is incorrect. Below we shall look at this more closely.

Regarding the first issue, there have been many studies which have looked at the relationship between the magnitude of the surface temperature trend relative to that of the tropospheric layer as defined above (e.g. Douglass et al. 2007.)  Global climate models when forced by extra greenhouse gases on average indicate their global average troposphere warms at a rate about 1.25 times that of the surface, i.e. the trend of the troposphere is amplified by a factor of 1.25 over that of the surface.  When confined to the tropics (20°S – 20°N) the amplification is about 1.4 times that of the surface.  This model-generated tropospheric warming in the tropics is known as the “hot spot” and has been claimed to be a signature of greenhouse warming because of its prominence in models.

When separated by land and ocean, the model amplification factor is found to be larger over oceans than land.  Klotzbach et al. 2010 calculated the ratio over global land to be 1.1, and this was confirmed by independent analysis (see http://climateaudit.org/2011/11/07/un-muddying-the-waters/).  Hagelaars follows an early calculation by Gavin Schmidt, claiming the land value should be 0.95.  As noted however, several additional calculations confirm the value of 1.1 utilized by Klotzbach et al. 2010.  The model amplification of the ocean trends is close to 1.6 as determined by the NASA-GISS model.

The second issue is the simple magnitude of global temperature trends of the surface and troposphere as depicted by models and as observed by instruments.  Since both issues can be examined by investigating the observational record, we have created the Table below to update Klotzbach et al. 2010 and address the concerns of Hagelaars.

In his last table, Hagelaars appears to be subtracting the actual observed values of LT and Sfc which produces values very similar to those shown in the upper half of our table.  It is true that these differences are a little closer to zero than shown in Klotzbach et al., but that is due to the fact that there has been no warming in the past 10 years in both types of data.  (Note too, that if the surface and tropospheric trends “agree” in absolute magnitude, that means they do not agree with model output as noted earlier – hence closer agreement of absolute trends can imply greater disagreement with model results.)

Now, a more direct, “apples to apples” comparison test for the model output is to amplify the surface trends (with model factors) for comparison with the LT trends.  We have been conservative with the amplification factors, but even so, the differences are large – and very large over land.  Thus the basic point of Klotzbach et al. 2010 is confirmed, i.e. that the average climate model warms its atmosphere, relative to its land surface, more than seen in observations. (Other studies focus on the tropical “hot spot” where it is clear models also significantly warm the troposphere relative to observations, e.g. Christy et al. 2010.) This raises at least some suspicion as to the ability of the near-surface air temperature to be used as a proxy for greenhouse detection.

Table:  1979-2012 trends (°C/decade).  No amplification factors are applied in the upper half of the table, thus they compare different quantities.  Land, Ocean and Global factors of 1.1, 1.2 and 1.4 are applied to the surface data in the lower half.  Recent results from Santer et al. 2012 indicate a global amplification factor greater than 1.3 for model LT vs. Sfc, but we use only 1.2 below.  Lower Tropospheric data are from the University of Alabama in Huntsville v5.5 (UAH) and Remote Sensing Systems v3.3 (RSS), and surface data from the National Climatic Data Center (NCDC) and the Hadley and Climate Research Unit Temperature v4 (HadCRUT4).  Artificial values of “NCDC LT” and “HadCRUT4 LT” are calculated by multiplying their actual trends by the model amplification factors.




















Difference (No Amplification)




















Hypothetical (with Amplification)



Land (1.1xSfc)



Ocean (1.4xSfc)



Globe (1.2xSfc)



Difference LT





















CMIP5 versus observations
Of equal importance here are the magnitudes of the actual trends of the surface and troposphere.  The average global surface trend for 90 model simulations for 1979-2012 (Climate Model Intercomparison Project 5 or CMIP-5 used for IPCC AR5) is +0.232 °C/decade.  The average of the observations is +0.157 °C/decade.  Therefore models, on average, depict the last 34 years as warming about 1.5 times what actually occurred.  Santer et al. 2012 (for 1979-2011 model output) noted that a subset of CMIP-5 models produce warming in LT that is 1.9 times observed, and for a deeper layer of the atmosphere (mid-troposphere, surface to about 18 km) the models warm the air 2.5 times that of observations.  These are significant differences, implying the climate sensitivity of models is too high.

All of the above addresses the two issues mentioned at the beginning.  First, global climate models on average depict a relationship between the surface and upper air that is different than that observed, i.e. models depict an amplifying factor into the upper air that is greater than observed.  Secondly, the average climate model depicts the warming rate since 1979 as much higher than observed with increasing discrepancies as the altitude increases (which is consistent with the first issue).

Since this increased warming in the upper layers is a signature of greenhouse gas forcing in models, and it is not observed, this raises questions about the ability of models to represent the true vertical heat flux processes of the atmosphere and thus to represent the climate impact of the extra greenhouses gases we are putting into the atmosphere.  It is not hard to imagine that as the atmosphere is warmed by whatever means (i.e. extra greenhouse gases) that existing processes which naturally expel heat from the Earth (i.e. negative feedbacks) can be more vigorously engaged and counteract the direct warming of the forcing. This result is related to the idea of climate sensitivity, i.e. how sensitive is the surface temperature to higher greenhouse forcing, for which several recent publications suggest models, on average, have been overly sensitive.

Christy, J.R., B. Herman, R. Pielke, Sr., P. Klotzbach, R.T. McNider, J.J. Hnilo, R.W. Spencer, T. Chase and D. Douglass, 2010:  What do observational datasets say about modeled tropospheric temperature trends since 1979? Remote Sens. 2, 2138-2169. Doi:10.3390/rs2092148.

Douglass D. H., J. R. Christy, B. D. Pearson and S. F. Singer (2007) A comparison of tropical temperatures trends with model predictions.. International J of Climatology 5 Dec 2007. doi: 10.1002ijoc.1651

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2009:

An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J.Geophys. Res., 114, D21102, doi:10.1029/2009JD011841.<http://pielkeclimatesci.wordpress.com/files/2009/11/r-345.pdf>

Klotzbach, P.J., R.A. Pielke Sr., R.A. Pielke Jr., J.R. Christy, and R.T. McNider, 2010:

Correction to: “An alternative explanation for differential temperature trends at the surface and in the lower troposphere. J. Geophys. Res., 114, D21102, doi:10.1029/2009JD011841”, J. Geophys. Res., 115, D1, doi:10.1029/2009JD013655.

Santer B. and 26 others (2012). Identifying human influence on atmospheric temperatures. Proceeding of the National Academy of Sciences. doi:10.1073/pnas.1210514109.


15 comments to Klotzbach revisited, a reply by John Christy

  • Jos Hagelaars

    Thanks Dr. Christy for your extensive blog post regarding my ‘Klotzbach Revisited’ post. I’m currently doing some thinking on your post and my response.
    Regards, Jos Hagelaars

  • Robert

    Models are models, a fantastic tool but not the word of God. We know too little of this dynamic system they call Earth.Scientists who use these models to misinform the general public have no right to that title. Which of these models have been able to reproduce the past? To use models as the only truth is dangerous. Just look at the economic models and the disaster they provoke. And economics are much more easier than climate science.

  • Robert

    ps Today we had snow in Barcelona.

  • Bob Brand


    ps Today we had snow in Barcelona.

    That is most definitely weather, not climate. Also, the European weather models (e.g. ECMWF) do quite well in forecasting these cold spells. Not just that, but also:


    Models are models, a fantastic tool but not the word of God.

    Nobody is claiming they are the word of God.

    General Circulation Models generate ensembles, many different possible solutions which tend to cluster within a range. That range is what is interesting – there is no way to know which ‘solution’ nature will actually choose, but those within the range are more probable. And that is why the IPCC indicates quite broad ranges, such as 1.7 – 4.4 °C warmer over 2090-2099 (A1B).

    These are not trying to predict the weather in Barcelona on 23 feb. 2099 at 6 PM. They predict changes in *average* temperatures taken over a period of 10, 20 or 30 years.

    If you’re going to boil some water on the stove, it is really hard (impossible over the long run) to predict where the next bubble of steam is going to rise – that is ‘weather’. It is however rather easy to predict after how much time it is going to boil – that is ‘climate’. Climate is the aggregate, the average over both time and space.

    Which of these models have been able to reproduce the past?

    All CMIP3 and CMIP5 models have to ‘hindcast’ the past successfully, before they are considered for the next IPCC report. However, that is not a guarantee they will be 100% correct for the future. They are certainly not used as ‘the only truth’.

    “Prediction is very difficult, especially if it’s about the future” – Yogi Berra 😉

  • Robert


    If prediction is very difficult why are there no models that predict cooling? What if the stove runs out of wood?

  • Bob Brand


    Because less heat out of the pot (e.g. when you close the lid), means more heat is retained within the pot. And heat wams things up…

    There is less heat escaping from the pot, because we are adding more greenhouse gases to the atmosphere than there were before. And greenhouse gases retain heat. If you don’t want to believe that, you can ask Dr. Roy Spencer, here:


    “Prediction is very difficult, but if you turn up the heat it does get warmer” – Yogi Berra 😉

  • Robert

    So if we get cooling there must be something we did not think of.

    “Unlike in Britain, there has been little publicity in Australia given to recent acknowledgment by peak climate-science bodies in Britain and the US of what has been a 17-year pause in global warming. Britain’s Met Office has revised down its forecast for a global temperature rise, predicting no further increase to 2017, which would extend the pause to 21 years.”


    So at the moment there is a pause in temperature rise but not in CO2 going up.

    Maybe by altering the temperature record a little bit more models will correctly forecast the past.


  • “For example, there is a tradition in many newsgroups and other Internet discussion forums that once such a link is placed, the thread is finished and whomever mentioned the RealScience blog has automatically lost whatever debate was in progress. This principle is itself frequently referred to as Goddard’s law.”

  • Robert

    Yep, You can’t debate ugly facts.

    Figure 7.20:

    “Sea-ice conditions are now reported regularly in marine synoptic observations, as well as by special reconnaissance flights, and coastal radar. Especially importantly, satellite observations have been used to map sea-ice extent routinely since the early 1970s. The American Navy Joint Ice Center has produced weekly charts which have been digitised by NOAA. These data are summarized in Figure 7.20 which is based on analyses carried out on a 1°latitude x 2.5° longitude grid. Sea-ice is defined to be present when its concentration exceeds 10% (Ropelewski, 1983). Since about 1976 the areal extent of sea-ice in the Northern Hemisphere has varied about a constant climatological level but in 1972-1975 sea-ice extent was significantly less.”


  • Bob Brand


    So at the moment there is a pause in temperature rise but not in CO2 going up.

    Really? Doesn’t look like a ‘pause’ to me:

    UAH satellite temperatures until 1998 and since 1999

    The rise in temperatures actually accelerated, in comparison to the first half of the record.

  • Robert, you can’t splice graphs together like that with the WUWT/Goddard-method. Ugly it definitely is, but a fact? Nope, not even close.

    Before spreading their deliberate lies, you might want to investigate some more. If you want we can do it together. I remember having a look at the time when Goddard first came with it, but forgot which thing(s) was exactly wrong with it. Something with baselines, difference between area and extent, cut-off percentages etc. If you want to learn about Arctic Sea Ice – and who doesn’t as it is one of Earth’s most important features – you can visit the Arctic Sea Ice Blog.

    And again, you should be careful quoting or linking to Steven Goddard, as it has a 99% chance of no one taking you seriously any longer. Marcel Crok even removed Goddard’s aggressive drivel from his blog list. Don’t let yourself be fooled so easily. It’s embarrassing.

  • […] of the original Dutch post) by Klotzbach’s co-author John Christy has been posted by Marcel Crok and reposted at WUWT. A reply to John Christy is […]

  • […] to my Dutch ‘Klotzbach Revisited’ post (English version here), it is published on “Staat van het Klimaat” and WUWT. I would like to thank Dr. Christy for his interest in my […]

  • barry

    Another confusing issue that didn’t manage to get teased out in this explanatory post is that the tropical ‘hotspot’ is not a specific signature (“fingerprint”) of greenhouse warming alone. It is an expected consequence of warming at the surface from any cause (solar/volcanic etc). So if there is no hotspot, that doesn’t injure the case for surface warming from greenhouse gases, but it does draw into doubt models of heat transfer in the atmosphere for this particular zone.

    The confusion arises because some discuss the matter in terms of observations solely within the context of greenhouse warming (observational record), and neglect to qualify that this enhanced warming effect is expected regardless of the cause of surface warming. Less well informed people take that to mean that the tropical tropospheric hotspot is a “fingerprint” solely of greenhouse warming, and then pass that view on, which has become popular, particularly among those critical of AGW theory.

    At this point it is well to re-quote an email from John Christy.

    “Yes, the hot spot is expected via the traditional view that the lapse rate feedback operates on both short and long time scales… it [the hot spot] is broader than just the enhanced greenhouse effect because any thermal forcing should elicit a response such as the “expected” hot spot.”


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