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Could climate shifts be causing global warming?

Posted on 7 February 2010 by John Cook

The work of Tsonis and Swanson are often cited as evidence against man-made global warming. Their research suggests our climate is subject to dramatic regime shifts. At key moments, the climate shifts from a warm regime to a cool regime, or vica versa. They claim climate shifts occured around 1910, 1940, 1976 and 2001. Some have interpreted this work to say climate shifts can explain the last few decades of global warming. Richard Lindzen's take is that 'this variability is enough to account for all climate change since the 19th Century'. Is this what Tsonis and Swanson's research shows? The best people to answer this question are the authors themselves as they address this very question in their peer-reviewed work.

The initial paper by Tsonis, Swanson and Kravtsov proposed that climate is subject to a phenomenon called synchronised chaos (Tsonis et al 2007). When examining a number of ocean cycles such as the El Nino Southern Oscillation and North Atlantic Oscillation, it was observed that the various ocean cycles synchronised at certain moments after which climate seemed to shift to a new regime. In 1910, the synchronisation was followed by a warmer regime and several decades of warming. Another synchronisation occured in 1940, switching to a cooler regime. This coincided with mid-century cooling from 1940 to 1970. In the 1970s, the planet began warming again.

Global temperature (HadCRUT) with periods of synchronised chaos
Figure 1: HadCRUT3 global mean temperature over the 20th century, with approximate breaks in temperature indicated. The cross-hatched areas indicated time periods when synchronization is accompanied by increasing coupling (Swanson & Tsonis 2009).

Conventional understanding for the switch to warming in the 1970s is that warming from CO2 overcame cooling from forcings such as sulfate aerosols. Tsonis and Swanson suggest an 'alternative hypothesis, namely that the climate shifted after the 1970s event to a different state of a warmer climate, which may be superimposed on an anthropogenic warming trend'. It's this final phrase, 'superimposed on an anthropogenic warming trend', that Swanson and Tsonis explore further in a subsequent research.

In 2009, they continue to examine the coupling of ocean cycles, stressing 'caution that the shifts described here are presumably superimposed upon a long term warming trend due to anthropogenic forcing' (Swanson & Tsonis 2009). They extend their analysis further in a paper that uses climate modelling to separate man-made and natural variability (Swanson et al 2009). When internal variability is filtered from the smoothed observed temperature (solid black line), the cleaned signal (dashed line) shows nearly monotonic warming throughout the 20th Century. In fact, the cleaned signal fits a quadratic shape which indicates the warming is accelerating.


Figure 2: Observed GISS 21-year running mean global mean surface temperature (heavy solid) along with that temperature cleaned of the internal signal (dashed). The cleaned global mean temperature warms monotonically, and closely resembles a quadratic fit to the observed 20th century global mean temperature (thin solid) (Swanson 2009).

If climate shifts do actually occur, Tsonis and Swanson's research finds they are not responsible for the warming found over the 20th Century. Instead, they superimpose variability over the long-term trend which is that of steadily accelerating warming. This is consistent with observations which find the planet has been accumulating heat since 1950 (Murphy 2009). Climate shifts do not stop the planet's energy imbalance. They merely cause temporary slow downs or speeding up of surface temperature warming.

Nevertheless, the theory of climate shifts has some unresolved issues. A key result of Tsonis and Swanson's work is that a shift to a cooler regime occured around 2001/2002. This shift is more marked in the HadCRUT record which is not a global temperature record. When Arctic regions are included, the global warming trend is greater in recent years and hence the 2001/2002 shift is not so pronounced. Hence the theory is dependent somewhat on an incomplete global record.

Another issue discussed in Swanson 2009 is that if climate is more sensitive to internal variability than currently thought, this would also mean climate is more sensitive to imposed forcings. This includes radiative forcings such as a warming sun, cooling from sulfate aerosols or warming from CO2. This leads to a crucial question that the authors themselves raise but don't answer. Conventional thought is that the warming sun and reduced volcanic activity caused much of the early 20th Century warming. Similarly, cooling from increased sulfate aerosols was a major contributor to mid-century cooling. In suggesting climate shifts as the cause, the authors offer no physical explanation as to why the warming sun and cooling aerosols didn't have their expected effect?

Nevertheless, if these issues are resolved and Tsonis and Swanson's theory is found to be valid, it's clear that climate shifts do not invalidate the human influence on climate. On the contrary, they show that underneath internal variability is a long-term trend. Tsonis and Swanson's analysis finds that imposed forcings have exerted a monotonic and accelerating warming trend throughout the 20th Century.

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Comments 51 to 52 out of 52:

  1. Parallel Lines, Part II of II

    Looking on page 9 of Chou's presentation:
    Rationale of satellite water vapor retrievals

    * Radiation measured by the satellite in channels with various opacities comes from different regions in the atmosphere.

    * The radiation measured in more transparent channels originates from lower atmosphere, and the radiation measured in less transparent channels originates from higher atmosphere.

    * Therefore, radiation measured in a number of channels with different opacity provides information on temperature and water vapor at different levels of the atmosphere.

    ibid, pg. 9
    Stated in very basic terms, this is precisely what I concluded from my understanding of Kirchoff's law. Judging from this, no complex model is necessary.

    I see some mention of the use of "GPS Radio Occultation Measurements" where they need to identify the position of the satellite on the sweeps (pg.11) -- but one would expect that from a moving satellite. There are some complexities to that, for example, having to do with the bending of radio signals as they pass through the atmosphere at an angle. On page 10 there is mention of limb observations where the AIRS is being used to peer through the atmosphere almost parallel to the surface.

    There is some employment of geometry and some modeling (I presume) involved in limb observations -- with the air pressure and density of the atmosphere and the partial pressures of the greenhouse gases going from low to high to low. This, I presume, is a rarer use case.

    Page 13 is titled "AIRS and NCEP/NCAR Reanalyses (Global water vapor data sets)." It states that reanalyses "assimilate satellite and other observations." Seems accurate enough.

    In contrast what I take to be the more common use case would involve the air pressure and density of the atmosphere and the partial pressures of the greenhouse gases going strictly from high to low where the satellite is directly overhead of the atmosphere it is imaging. What was mentioned on page 9 and the use case to which I was applying Kirchoff's law. But it most certainly does not involve using a climate or weather model to interpret the sensory data of a satellite.

    I also notice that there are some comparisons of AIRS and FORMOSAT results on pages 16 (pretty much spot-on), 17 (same basic shape, but somewhat higher levels of water vapor from Formosat in the tropics). AIRS and FC differ by perhaps as much as 20% on water vapor as grams per kilogram at the 350 and 650 hPa levels. Particularly around the poles (which would be closer to limb measurements I presume) although to some extent in the tropics. The difference I presume is most likely a matter of the specific channels being used. Perhaps some sensitivity on the part of the instruments, orbital variation, etc..

    Anyway, I see various somewhat vague assertions. Satellite microwave observations are referred to as "a priori" information. Would that be the same satellite? Are we talking about height? Orbit? Vague. I don't see much of anything in terms of actual references in Chou's presentation. Not really to be expected since this is only a presentation, not a peer-reviewed paper.
    *
    Berényi Péter wrote in 45:
    So. The question still stands. To what extent "measured" (actually: calculated) values are dependent on model?

    For the general idea, still used in AIRS reconstructions see:

    High resolution observations of free tropospheric
    humidity from METEOSAT over the Indian Ocean.
    R´emy Roca, H´el`ene Brogniez, Laurence Picon and Michel Desbois
    Laboratoire de M´et´eorologie Dynamique, CNRS, Palaiseau, France
    MEGHA-TROPIQUES 2nd Scientific Workshop, 2-6 July 2001, Paris, France.


    Regarding METEOSAT:
    The retrieval algorithm is similar to the operational algorithm run at EUMETSAT with slight modifications in the interpretation of the inverted signal. It relies on the use of local look up table and radiative transfer computations. The ancillary data needed for the algorithm are composed of the temperature profile taken from the ECMWF analysis. The final product is the weighting function weighted mean relative humidity over the free troposphere (FTH).

    Remy Roca, et al. (2001) High resolution observations of free tropospheric humidity from METEOSAT over the Indian Ocean, MEGHA-TROPIQUES 2nd Scientific Workshop, 2-6 July 2001, Paris, France
    http://meghatropiques.ipsl.polytechnique.fr/dmdocuments/proc_s2p06.pdf


    So if AIRS did things the same way as METEOSAT (as you tell us that it does) then the one thing it requires is the temperature profile from ECMWF analysis -- where ECMWF may be the weather model or:
    The European Centre for Medium-Range Weather Forecasts (ECMWF, the Centre) is an international organisation supported by 31 States, based in Reading, west of London, in the United Kingdom.

    http://www.ecmwf.int/about/
    ... the weather agency.

    Assuming it is the model we still aren't trying to identify a unique state that gives rise to the "radiation signature." Each Radiation line could be handled individually. And all that is required of your complicated model is the temperature profile.

    However, going back to Chou's presentation, page 20:
    Satellite observations of radiance and radiowave occultation are sensitive to both water vapor and temperature. It requires accurate retrievals of temperature prior to retrieving water vapor.


    It would seem that AIRS can calculate its own temperature profiles -- but perhaps he is simply referring to temperature being retrieved by "something" prior to the use of temperature in the determination of water vapor content.

    I dug a little further...
    Level 2 Algorithm Theoretical Basis Document (ATBD)

    Describes the theoretical basis of the AIRS Level 2 Products Algorithm. Many products are presented in one document because of the basic structure and approach of the Level 2 Products Algorithm. In order to achieve the basic requirement of temperature profile accuracy of 1K in 1 km thick tropospheric layers, a multi-spectral simultaneous retrieval of both the atmospheric thermodynamic state and atmospheric composition is attempted. Hence the Level 2 Products refer to the basic thermodynamic variables and trace gas abundance that control the outgoing infrared radiance.

    http://airs.jpl.nasa.gov/data_products/algorithms/
    Not saying that is what they generally use -- but it would appear that they do not need a weather model for the determination of temperature profile. And that sounds to me like "Consequently, given enough channels and enough unique absorption lines one could peel back the layers of the atmosphere like an onion.... Given my analysis it would seem that there is no need for some sort of all-purpose model for computing one unique physical state that would produce the specific full spectrum. All you need are a certain set of well-chosen frequencies for the particular problem at hand." That is, what I concluded given Kirchoff's Law.
    *
    Berényi Péter wrote in 45:
    As for the multitude of spectral channels. Some women are tetrachromats. I don't think they can grasp reality more accurately than anyone else. Myopic girls could do worse.


    I don't believe there has been even a single verified case of this -- although two women have been suspected tetrachromats. But maybe you know differently. I have to admit I was hoping you got that one right. Would have been fascinating.
    *
    Berényi Péter wrote in 45:
    As for doubting Descartes, consider the following tiny piece: ...
    Might want to re-examine what you wrote in step 2. Additionally, I somehow doubt that "senselessness" is an epistemic term. Would the law of identity be "senseless" since a contradiction does not make sense? What about 2+2=4? Does it fail to make sense since 2+2=5 fails to? In any case, I think Descartes' self-referential argument was the one thing he got right. Otherwise, my interest in him lies primarily in understanding his influence upon later thinkers -- including Kant.
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  2. Patrick 027,
    if you look at Swanson 2009 paper (fig. 1B), you will see the various part of the oceans that influence multidecadal variability; the North Atlantic is included, although with a lower weight than the tropical pacific ocean.

    As for the synchronization of the modes of variability, it's purely empirical. The idea of climate shift itself, i.e. the climate system as a sort of bystable system, is just postulated. Given the complexity of the teleconnections between the various (so called) oscillations, they do not even try a deterministic approach nor a statistical analysis. They just rely on observations to calculate the influence of these oscillations on the global mean temperature and end up with their fig. 2B (Swanson 2009).
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