In 2011, the Hadley Centre of the UK Met Office replaced their global sea surface temperature series, HadSST2, with a new one, HadSST3, an upgrade allegedly necessitated by, among other things, the particular ‘discovery’ that the recorded temperature evolution of the global ocean surface had, since about 1979, for one particular reason followed a path that trended artificially low. The official global sea surface temperature data as compiled simply showed too little overall warming. Since 1978-79, that is, during the satellite era.
This is funny, because the Hadley Centre’s own official global SST dataset, HadSST2, already showed an overall warming since the late 70s that was much larger than the other official datasets out there, like ERSST, Reynolds OI and HadISST:
Note that the new ERSSTv4 series is also included in Anim.1 (red curve), and that it distinctly supports the group of ‘others’: The light blue HadSST2 curve all of a sudden makes a giant upward leap of nearly 0.1K at the 1997-1998 transition (light green vertical line). There is hardly any divergence to be observed between it and the others, however, either before or after this point (save that from ERSSTv4 post 2005; more on that later …). Continue reading →
More than fifteen months ago I wrote the post “What of the Pause?”, where I tried to analyse the state of the global climate with a special focus on the interesting developments following the 2011/12 La Niña. I have also later discussed that particular time period here.
I have earlier pointed out the close connection between the SSTa in that central-eastern part of the narrow Pacific equatorial zone called “NINO3.4” and “global” SSTa over decadal time frames, how the former consistently seems to lead the latter in a tightknit relationship, firmly constraining the progression of global mean anomalies through time – flat (though with much noise) as long as the NINO3.4 signal remains strong enough to override (and/or control) all other regional signals around the globe, which most of the time it does.
I have then proceeded to show how “global warming” (or “global cooling”) only appears to come about at times when the influence of this tight relationship on the global climate is somehow offset by surface processes elsewhere, meaning outside the NINO3.4 region. This obviously doesn’t happen too often, because it would take a very powerful and persistent process to disrupt and even break the sturdy grip of the NINO3.4 region on the leash with which it controls the generally flat progression of global mean temps over time.
In fact, from 1970 to 2013 it evidently only happened three times. Which means that within these three instances of abrupt extra-NINO surface heat is contained the entire “global warming” between those years. Before, between and after, global temp anomalies obediently follow NINO3.4 in a generally (though pretty noisy) horizontal direction; no intervening gradual upward (or downward) divergence whatsoever.
With the year 2015 completed, I felt an update of this NINO3.4-global SSTa relationship was in order. Is there evidence of a new step as of late …?
My answer to this can only be: ‘It is still too early to tell.’ But interesting things have happened – and are indeed still happening – over the last two to three years, since about mid 2013:
Global SSTa has really been ratcheting up now for a while. At the moment, the strong ongoing El Niño is doing most of the work, but there is no question that even this has been provided with a significantly elevated baseline from which to soar, a raised mean level seemingly establishing itself already years before the current El Niño started moving.
Well, it just so happens that this new level is higher than the old one by quite exactly 0.1 K. How can one tell?
Like this …
We noted and discussed already a year ago how the global lower troposphere has yet to respond to the conspicuous and mostly extratropical accumulation of surface heat in the NE Pacific basin starting in mid 2013.
Under the working hypothesis that this abnormal and persistent NE Pacific surface heat phenomenon (often simply nicknamed “The Blob”) is responsible for the entire 0.1K lift in the mean level of global SSTa since 2013, and positing that the lower troposphere has not yet responded to it, hence giving rise to the distinct divergence seen over the last couple of years between the “gl SSTa” and “tlt” curves, we lower the former en bloc by 0.1K from July 2013 onwards (yellow vertical line in Fig.1) and superimpose it on the latter: Continue reading →
Update (March 9th) – Dr. Roy Spencer just gave an interesting response:
“yes, we have been aware of some spurious warming over land versus over the ocean after approximately 2000. Our version 6 dataset (now close to completion) will have most of that removed, although it looks like some of it is genuine.”
I guess we all just have to wait and see …
I have earlier noted a rather curious blocklike shift up in the UAH tlt (lower troposphere temperature) timeseries occurring abruptly some time in 2005. (There is most likely a similar – only downward – step at the same time in the RSS tlt timeseries; however, this post will not address this one.)
The 2005 shift seems very much to originate in the land portion of the UAH dataset. The shift can readily be seen here, but not at all in the oceanic portion, a situation which is quite unprecedented in the record – global land temps simply do not by any known natural mechanism all of a sudden jump out of step with the global ocean temps and then remain elevated high above thereafter:
Figure 1. As you can see, something quite out of the ordinary happens in the UAH land curve in 2005.Continue reading →
I have previously shown how global temperatures rose in three distinct and abrupt steps from the 70s to the 00s – one in 1979, one in 1988 and one in 1998 – and at all other times, not at all. These three steps occurred relative to the SSTa curve of the NINO3.4 region in the equatorial zone of the central-eastern part of the Pacific Ocean. Before, between and after the three steps, global temperatures appear simply obediently to follow NINO3.4 without any sign of a continued slow, but steady upward drawing away as if from a ‘steady rising background forcing’:
My opinion on the much talked about “Pause” or “Hiatus” in ‘global warming’ still said to be going on (the considerable final, level stretch of the upper blue curve in Figure 1), is thus naturally coloured by this understanding of how global temperatures normally progress through time, as exemplified by the period from 1970 till today.
Within this perspective, the “Pause” is but one of many temperature ‘plateaus’ between sudden steps up or down (the last time it went down was back in 1964, before the ‘modern warming’). The relevant questions are: When did the last step occur? When will the next one take place? And will it go up? Or down?
At the present time, I would still maintain that the last well-established step in global temperatures happened in 1998, following directly in the wake of the mighty 1997/98 El Niño. Simply because not enough time has elapsed to be able to say anything for certain about more recent events.
But there are definitely a couple of things at work today that deserve some close attention. Continue reading →
In July I wrote a blog post where a strange and very conspicuous step change indeed in global mean temps relative to the trended AMO (North Atlantic SSTa), occurring across the 8-year period of 1963-70, was pointed out:
As you can clearly see, the two curves generally follow each other in remarkable style all the way from 1860 till today, except for the relatively sudden and substantial global upward shift taking place across the last half of the 60s, being firmly established by the end of 1970. After this point, the curves are back to tracking each other to an equally impressive degree as before the shift, only now with the global raised 0.25 degrees above the North Atlantic.
“So, how to sort this out and do a more realistic job of detecting climate change and (…) attributing it to natural variability versus anthropogenic forcing? Observationally based methods and simple models have been underutilized in this regard.”
There is a very simple way of doing this that people at large still seem to be absolutely blind to. To echo the words of ‘Statistician to the Stars!’ William M. Briggs: “Just look at the data!” You have to do it in detail. Both temporally and spatially. I have done this already here, here and here + a summary of the first three here. In this post I plan to highlight even more clearly the difference between what an anthropogenic (‘CO2 forcing’) signal would and should look like and a signal pointing to natural processes.
Curry has many sensible points. She says among other things:
“Because historical records aren’t long enough and paleo reconstructions are not reliable, the climate models ‘detect’ AGW by comparing natural forcing simulations with anthropogenically forced simulations. When the spectra of the variability of the unforced simulations is compared with the observed spectra of variability, the AR4 simulations show insufficient variability at 40-100 yrs, whereas AR5 simulations show reasonable variability. The IPCC then regards the divergence between unforced and anthropogenically forced simulations after ~1980 as the heart of the their detection and attribution argument. (…)
The glaring flaw in their logic is this. If you are trying to attribute warming over a short period, e.g. since 1980, detection requires that you explicitly consider the phasing of multidecadal natural internal variability during that period (e.g. AMO, PDO), not just the spectra over a long time period. Attribution arguments of late 20th century warming have failed to pass the detection threshold which requires accounting for the phasing of the AMO and PDO. It is typically argued that these oscillations go up and down, in net they are a wash. Maybe, but they are NOT a wash when you are considering a period of the order, or shorter than, the multidecadal time scales associated with these oscillations.
Further, in the presence of multidecadal oscillations with a nominal 60-80 yr time scale, convincing attribution requires that you can attribute the variability for more than one 60-80 yr period, preferably back to the mid 19th century. Not being able to address the attribution of change in the early 20th century to my mind precludes any highly confident attribution of change in the late 20th century.“