Troy's Scratchpad

May 21, 2013

Another “reconstruction” of underlying temperatures from 1979-2012

Filed under: Uncategorized — troyca @ 7:56 am

Or, “could the multiple regression approach detect a recent pause in warming, part 4”.  For those following the series, you know what I mean by “underlying temperatures” is the temperature evolution if we attempted to remove the influence of solar, volcanic, and ENSO variations.  

It has been a while since I posted the first three parts of a series on whether using multiple linear regressions to remove the solar, volcanic, and ENSO effects from temperature was an accurate way to "reconstruct" the underlying trend. Generally, these did not perform too well, and tended to overestimate the solar influence and underestimate the volcanic influence, particularly if there was indeed a "slowdown" in the underlying temperature data.  One of the problems with that method is that it includes an assumption about the form of the underlying trend when doing the regressions.  

So, I’d thought I’d put a temperature series (actually, a couple of options) out there that have been adjusted for these factors, using a method that is not particularly sensitive to the form of the underlying trend.  Essentially, I take the multi-model mean of the models I used in the last post in this series to adjust for the volcanic and solar components, and then remove ENSO based on a regression against that adjusted series.  Fortunately, the ENSO variations are high enough frequency that the regression is not particularly sensitive to form of the the underlying trend (whether it be linear or quadratic) as we have limited the number of variables.

It should be noted that this method might *over-adjust* for volcanic and solar if the CMIP5 models are too sensitive, which my recent paper (Masters 2013, Climate Dynamics) seems to indicate.  I have therefore included an adjusted series that adjusts by only 50% of the MMM as well.  Since the difference between the sensitivies in the transient state are likely to be less than after equilibration, let’s say the "true" adjustment should lie somewhere in-between those two adjustments.

Anyhow, here is the reconstructed series of NCDC (NOAA) temperatures.  (On a side note, I have become a little annoyed with trying to grab data from HadCRUT4 and GISS.  The former seems to return a "Not Found" error quite frequently, and the latter doesn’t let the R default user-agent grab data at all.  Hence the usage of NOAA temperatures). 


If I were to go strictly by the eyeball test, the blue line (adjusted by 50% of MMM) seems to get it “most right” in terms of compensating for the volcanic eruptions without over-adjusting.  Below are the trends for the various start years ending in 2012 in these series:


Here you’ll note that the “adjusted” series actually results in a lower trend for all start years up until about 2001, when the influence of ENSO seems to really take over.  The blue line never dips below 0 for these adjusted trends of 10 years or longer, so one could argue that the underlying warming (if the blue line indeed captures this correctly) never really “stopped”.  On the other hand, the trends are substantially lower towards the end than they are at the beginning (and indeed smaller than in most model runs), so saying that the recent “slowdown” is simply the result of known natural factors rings a bit hollow to me.  It would be interesting to run a similar experiment on the CMIP5 model runs and see how much “natural” variation remains in those runs, of if this is something unique to the real world. 

Code and data for this post available here.



  1. How are you using the multimodel mean to adjust?

    Comment by R — May 23, 2013 @ 12:03 pm

    • R – I am simply taking the temperature anomalies for the MMM natural-only forcing ensemble (from the last post) and subtracting them (or .5 times these anomalies in the 50% case) from the NOAA temperature record.

      Comment by troyca — May 23, 2013 @ 2:36 pm

  2. Troy,
    The problem with HADCRUT is that they have the version number built into the URL, so you need to change every time they upgrade. The link on this page always works, and you can get a script to scrape it from there.

    The problem with GISS is that they only respond to HTML 1.1 calls, which wget can’t make. cURL can, and that might work in R, with or without RCurl, but I use cURL directly.

    Comment by Nick Stokes — May 24, 2013 @ 3:55 am

    • Thanks Nick, I will need to update my scripts!

      Comment by troyca — May 25, 2013 @ 9:34 am

  3. Troy,

    I was interested by your comments in this and in “part 3” about volcanic rebound. I recently tried an overlay of the six major events during the thermometer record to try to average out other climatic cycles and noise since it has been noted that both Mt P and El Chichon were superimposed on a downward temp trend that began before the eruption. The result rather surprised me.

    Follow links in the description for the other regions and explanation of the processing.

    I split temps in to tropical , ex-tropical : NH,SH. and looked at the cumulative integral of degree.days several years before and after eruption date.

    What this suggested is that the tropics are almost totally self-compensating, even recovering the integral a few years after the event. This implies an non-linear negative feedback that produces a warmer than average period that recovers the integral.

    Extra-tropics recover their temperature but retain a net loss in degree.days. ie there was a net colder period. This is more compatible with a linear response and may reflect a stabilising influence provided by some degree of mixing with the self-regulating tropics.

    I was interested to notice on Nick’s recent attempt at multivariate regression that his ENSO term seemed to be roughly in anti-phase with the volcanic forcing. ie the regression gave it opposing sign. Now since ENSO is not really exogenous, this lead me to wonder whether it was not to some extent a manifestation of the non linear tropical response.

    That is to say, if we assume a linear response to radiative forcing in the tropics (by implication of a linear global response) and the reality is a strongly non linear feedback, there will be a need for another linear term in addition to the assumed linear response to approximate what actually happens.

    This seems open to two interpretations. Either ENSO is an indication of some real active compensatory response in tropical climate ( there are indications of greater likelihood of La Nina following eruption and El Nino 6 years on, in the literature); or simply that the regression is finding a spurious correlation in ENSO because that’s all we give it to work with.

    You clearly have a detailed knowledge of both real climate and the models’ behaviour w.r.t. volcanism , does this kind of interpretation tie in with your understanding of the data?


    Comment by Greg Goodman — June 23, 2013 @ 3:31 pm

    • Hi Greg,

      Sorry for the slow response, been on vacation. I hate to disappoint, but I would not say I have a detailed knowledge of volcanism in the real climate or models, apart from my somewhat simplistic looks at their longer-term global surface temperature impacts. In fact, your mention of volcanic activity influencing the probability of certain ENSO phases is not something I was actively aware of. When you are calculating the radiative forcing for the tropics vs extra-tropics, are you only using the strat aerosols over each of the regions? It also seems like heat exchange between the tropics and extra-tropics would need to be considered?

      Comment by troyca — July 2, 2013 @ 8:31 am

  4. Thanks Troy. I kinda lost track of why I contacted you now. It seemed from you posts that you were well up on all this. I may have over-estimated, but you seem to have a good grip, so I wondered whether the non linearity made sense to you.

    I don’t have a ref for the other article about proximity of El Nino to major eruptions but this came up today on WUWT, includes a similar claim.

    I did not calculations of forcing or heat exchange it’s purely observational data. The method is explained in the text.

    I basically average the six major events in an attempt to average any uncorrelated climate variations and use the cumulative integral to even out any periodic patterns.

    I think separating the tropics does show they provide a stabalising infulence to ex-tropics but the key finding is that the product is maintained in the tropics. This implies a non linear negative feedback governs tropical climate.

    Comment by Greg Goodman — July 2, 2013 @ 1:47 pm

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